diff --git a/DEPS b/DEPS
index ab68dde..c48ac9c 100644
--- a/DEPS
+++ b/DEPS
@@ -245,15 +245,15 @@
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling Skia
   # and whatever else without interference from each other.
-  'skia_revision': '3887123079922a846fa43260740d2b86de450d91',
+  'skia_revision': '93e0041c6ca7e2e9fa8047ef67ed3804f2ccbef9',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling V8
   # and whatever else without interference from each other.
-  'v8_revision': '239e6102fad60fb3317e8f4349f69df760291ef1',
+  'v8_revision': '8280a12b2bdf7c22235d44f27998d6de3b47a3bd',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling ANGLE
   # and whatever else without interference from each other.
-  'angle_revision': '8ab13284ad8c9f05d1cce6b4fd6b3f51a2e1e9b3',
+  'angle_revision': '40c5cb255c0a07bdab574aa076ee603e7d791ab3',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling SwiftShader
   # and whatever else without interference from each other.
@@ -268,7 +268,7 @@
   #
   # Note this revision should be updated with
   # third_party/boringssl/roll_boringssl.py, not roll-dep.
-  'boringssl_revision': '3a667d10e94186fd503966f5638e134fe9fb4080',
+  'boringssl_revision': '295b31324f8c557dcd3c1c831857e33a7f23bc52',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling google-toolbox-for-mac
   # and whatever else without interference from each other.
@@ -288,7 +288,7 @@
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling NaCl
   # and whatever else without interference from each other.
-  'nacl_revision': '8694f994aeb5f8d7bb6b1bb5ec68e490366d9e61',
+  'nacl_revision': '38e06bc9954cbe8582f557d525d2effbbc0d849e',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling freetype
   # and whatever else without interference from each other.
@@ -320,7 +320,7 @@
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling devtools-frontend
   # and whatever else without interference from each other.
-  'devtools_frontend_revision': 'd3425b95d0ff161d2615702f7a686cc8702980a7',
+  'devtools_frontend_revision': '7d228add956c220c44e95914472c0d56b969152c',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling libprotobuf-mutator
   # and whatever else without interference from each other.
@@ -360,11 +360,11 @@
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling feed
   # and whatever else without interference from each other.
-  'dawn_revision': '8b4d03d30231aec2755322a9f2200f3ad05d51f7',
+  'dawn_revision': '03b3594f79a2fb322dad39b757dbe706b905666c',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling feed
   # and whatever else without interference from each other.
-  'quiche_revision': 'cb6ab3eb3fdf36c5db3a4a845f4af1c7c5d68b7e',
+  'quiche_revision': 'b0fda3339a7e0c24d8bea7cfb6d9ea306e2686a1',
   # Three lines of non-changing comments so that
   # the commit queue can handle CLs rolling ios_webkit
   # and whatever else without interference from each other.
@@ -427,7 +427,7 @@
   'libcxx_revision':       '79a2e924d96e2fc1e4b937c42efd08898fa472d7',
 
   # GN CIPD package version.
-  'gn_version': 'git_revision:54284c12607e2818293157cd76d29d03a36bfd68',
+  'gn_version': 'git_revision:f1b1412521b41e47118b29863224171e434a27a2',
 }
 
 # Only these hosts are allowed for dependencies in this DEPS file.
@@ -805,7 +805,7 @@
     'packages': [
       {
           'package': 'chromium/third_party/androidx',
-          'version': 'SBd1_afac7GmjsqtDzNI7TUwKr4KVbHuX3oqnduAW9EC',
+          'version': 'hyrO0XEiBqf22_8YM-FkRhjqAyxUWeSZ_9LZqPJDkYIC',
       },
     ],
     'condition': 'checkout_android',
@@ -1024,7 +1024,7 @@
   # Tools used when building Chrome for Chrome OS. This affects both the Simple
   # Chrome workflow, as well as the chromeos-chrome ebuild.
   'src/third_party/chromite': {
-      'url': Var('chromium_git') + '/chromiumos/chromite.git' + '@' + '81093092ece1b06a493257f50a23ec429c01529a',
+      'url': Var('chromium_git') + '/chromiumos/chromite.git' + '@' + 'd0f15301899309b439cf5710ef2752f8075d4dc3',
       'condition': 'checkout_chromeos',
   },
 
@@ -1044,7 +1044,7 @@
   },
 
   'src/third_party/depot_tools':
-    Var('chromium_git') + '/chromium/tools/depot_tools.git' + '@' + '44dda9648cce2a12c67aa96a498adfb3245d38e7',
+    Var('chromium_git') + '/chromium/tools/depot_tools.git' + '@' + '59e6796cd25bb2fd957d411a23ab33bea36e2732',
 
   'src/third_party/devtools-frontend/src':
     Var('chromium_git') + '/devtools/devtools-frontend' + '@' + Var('devtools_frontend_revision'),
@@ -1609,7 +1609,7 @@
   'src/third_party/usrsctp/usrsctplib':
     Var('chromium_git') + '/external/github.com/sctplab/usrsctp' + '@' + '62d7d0c928c9a040dce96aa2f16c00e7e67d59cb',
 
-  'src/third_party/vulkan-deps': '{chromium_git}/vulkan-deps@57e7495dc76d1dd940f6603db80adcdd62c27d5a',
+  'src/third_party/vulkan-deps': '{chromium_git}/vulkan-deps@9e7f44a63b2e5265935eeddb98159a0ddb8205ef',
 
   'src/third_party/vulkan_memory_allocator':
     Var('chromium_git') + '/external/github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git' + '@' + '5e49f57a6e71a026a54eb42e366de09a4142d24e',
@@ -1648,7 +1648,7 @@
     Var('chromium_git') + '/external/github.com/gpuweb/cts.git' + '@' + 'fca7b339442bd70c5dc49bb33ee7f9466b560a97',
 
   'src/third_party/webrtc':
-    Var('webrtc_git') + '/src.git' + '@' + 'd908d74fac46c58b80c1120b982d3f1b407292f3',
+    Var('webrtc_git') + '/src.git' + '@' + '651586c4e1b97a4615b8522a3a3d56bb4376e72f',
 
   'src/third_party/libgifcodec':
      Var('skia_git') + '/libgifcodec' + '@'+  Var('libgifcodec_revision'),
@@ -1730,7 +1730,7 @@
     Var('chromium_git') + '/v8/v8.git' + '@' +  Var('v8_revision'),
 
   'src-internal': {
-    'url': 'https://chrome-internal.googlesource.com/chrome/src-internal.git@82d92b1bf860b2e239f7a62a1eedbb306caa055a',
+    'url': 'https://chrome-internal.googlesource.com/chrome/src-internal.git@5f4f6cba430b42f7ef03457af99737cf73aa908e',
     'condition': 'checkout_src_internal',
   },
 
@@ -1760,7 +1760,7 @@
     'packages': [
       {
         'package': 'chromeos_internal/apps/help_app/app',
-        'version': 'ALKqv_hdzRbzx6zAqVrRyRoC7_l0PzxpaXcMy8FY12gC',
+        'version': 'iznE7Bnmb5EY-LvHVo0U6uawQvfDk5Rp7Q5FEh6DSd8C',
       },
     ],
     'condition': 'checkout_chromeos and checkout_src_internal',
@@ -1771,7 +1771,7 @@
     'packages': [
       {
         'package': 'chromeos_internal/apps/media_app/app',
-        'version': 'AbBYfsC4757NystoBycRj-9JENE23kFNcGpJfUoBw5IC',
+        'version': 'ww1_CusDQQSjKCZTDoFyYzAl_CHJPeA2OSIxwVGUAPkC',
       },
     ],
     'condition': 'checkout_chromeos and checkout_src_internal',
diff --git a/ash/app_list/app_list_bubble_event_filter.cc b/ash/app_list/app_list_bubble_event_filter.cc
index 226794f..5c814d79 100644
--- a/ash/app_list/app_list_bubble_event_filter.cc
+++ b/ash/app_list/app_list_bubble_event_filter.cc
@@ -5,9 +5,12 @@
 #include "ash/app_list/app_list_bubble_event_filter.h"
 
 #include "ash/bubble/bubble_utils.h"
+#include "ash/shelf/hotseat_widget.h"
+#include "ash/shelf/shelf.h"
 #include "ash/shell.h"
 #include "base/callback.h"
 #include "base/check.h"
+#include "ui/aura/window.h"
 #include "ui/events/event.h"
 #include "ui/gfx/geometry/point.h"
 #include "ui/gfx/geometry/rect.h"
@@ -66,6 +69,16 @@
       return;
   }
 
+  // Ignore clicks in the shelf area containing app icons.
+  aura::Window* target = static_cast<aura::Window*>(event.target());
+  if (target) {
+    Shelf* shelf = Shelf::ForWindow(target);
+    if (target == shelf->hotseat_widget()->GetNativeWindow() &&
+        shelf->hotseat_widget()->EventTargetsShelfView(event)) {
+      return;
+    }
+  }
+
   on_click_outside_.Run();
 }
 
diff --git a/ash/app_list/app_list_bubble_presenter.cc b/ash/app_list/app_list_bubble_presenter.cc
index b39195eb..0006a1a7 100644
--- a/ash/app_list/app_list_bubble_presenter.cc
+++ b/ash/app_list/app_list_bubble_presenter.cc
@@ -22,6 +22,7 @@
 #include "ash/shelf/shelf.h"
 #include "ash/shelf/shelf_navigation_widget.h"
 #include "ash/shell.h"
+#include "ash/system/tray/tray_background_view.h"
 #include "ash/wm/container_finder.h"
 #include "base/bind.h"
 #include "base/check.h"
@@ -302,7 +303,7 @@
     // Check for widget because the code could be waiting for zero-state search
     // results before first show.
     if (bubble_widget_)
-      bubble_widget_->Hide();
+      OnHideAnimationEnded();
   }
   controller_->OnVisibilityChanged(/*visible=*/false, display_id);
 
@@ -404,6 +405,10 @@
 }
 
 void AppListBubblePresenter::OnHideAnimationEnded() {
+  // Hiding the launcher causes a window activation change. If the launcher is
+  // hiding because the user opened a system tray bubble, don't immediately
+  // close the bubble in response.
+  auto lock = TrayBackgroundView::DisableCloseBubbleOnWindowActivated();
   bubble_widget_->Hide();
 
   controller_->MaybeCloseAssistant();
diff --git a/ash/app_list/app_list_bubble_presenter_unittest.cc b/ash/app_list/app_list_bubble_presenter_unittest.cc
index 8fe30dc..35f3e53 100644
--- a/ash/app_list/app_list_bubble_presenter_unittest.cc
+++ b/ash/app_list/app_list_bubble_presenter_unittest.cc
@@ -20,7 +20,9 @@
 #include "ash/shelf/shelf.h"
 #include "ash/shelf/shelf_navigation_widget.h"
 #include "ash/shell.h"
+#include "ash/system/unified/unified_system_tray.h"
 #include "ash/test/ash_test_base.h"
+#include "ash/test/layer_animation_stopped_waiter.h"
 #include "ash/test/test_widget_builder.h"
 #include "base/run_loop.h"
 #include "base/strings/string_number_conversions.h"
@@ -490,6 +492,34 @@
   EXPECT_TRUE(presenter->IsShowing());
 }
 
+// Regression test for https://crbug.com/1285443.
+TEST_F(AppListBubblePresenterTest, CanOpenBubbleThenOpenSystemTray) {
+  // Enable animations.
+  base::test::ScopedFeatureList features(
+      features::kProductivityLauncherAnimation);
+  ui::ScopedAnimationDurationScaleMode duration(
+      ui::ScopedAnimationDurationScaleMode::NON_ZERO_DURATION);
+
+  // Create a widget, which will activate itself when the launcher closes.
+  std::unique_ptr<views::Widget> widget =
+      TestWidgetBuilder().SetShow(true).BuildOwnsNativeWidget();
+
+  // Show the launcher.
+  AppListBubblePresenter* presenter = GetBubblePresenter();
+  presenter->Show(GetPrimaryDisplay().id());
+
+  // Click on the system tray.
+  LeftClickOn(GetPrimaryUnifiedSystemTray());
+
+  // Wait for launcher animations to end.
+  LayerAnimationStoppedWaiter().Wait(
+      presenter->bubble_view_for_test()->layer());
+
+  // Launcher is closed and system tray is open.
+  EXPECT_FALSE(presenter->IsShowing());
+  EXPECT_TRUE(GetPrimaryUnifiedSystemTray()->IsBubbleShown());
+}
+
 TEST_F(AppListBubblePresenterTest, BubbleOpensInBottomLeftForBottomShelf) {
   GetPrimaryShelf()->SetAlignment(ShelfAlignment::kBottom);
 
diff --git a/ash/app_list/app_list_presenter_unittest.cc b/ash/app_list/app_list_presenter_unittest.cc
index 42ada8a..621ec3fa 100644
--- a/ash/app_list/app_list_presenter_unittest.cc
+++ b/ash/app_list/app_list_presenter_unittest.cc
@@ -3829,8 +3829,12 @@
   EXPECT_EQ(SHELF_AUTO_HIDE_SHOWN, shelf->GetAutoHideState());
 }
 
-// TODO(crbug.com/1273162): Fix for ProductivityLauncher.
-TEST_F(AppListPresenterTest, ClickingShelfArrowDoesNotHideAppList) {
+TEST_P(AppListPresenterTest, ClickingShelfArrowDoesNotHideAppList) {
+  // Parameterize by ProductivityLauncher.
+  base::test::ScopedFeatureList feature_list;
+  feature_list.InitWithFeatureState(features::kProductivityLauncher,
+                                    GetParam());
+
   // Add enough shelf items for the shelf to enter overflow.
   Shelf* const shelf = GetPrimaryShelf();
   ScrollableShelfView* const scrollable_shelf_view =
diff --git a/ash/app_list/views/app_list_folder_view.cc b/ash/app_list/views/app_list_folder_view.cc
index 579f467..9a5ee18 100644
--- a/ash/app_list/views/app_list_folder_view.cc
+++ b/ash/app_list/views/app_list_folder_view.cc
@@ -630,6 +630,7 @@
       contents_container_->AddChildView(std::make_unique<PagedAppsGridView>(
           contents_view, a11y_announcer_, this, /*folder_controller=*/nullptr,
           /*container_delegate=*/this));
+  contents_container_->layer()->SetMasksToBounds(true);
   items_grid_view_ = items_grid_view;
 
   items_grid_view_->Init();
diff --git a/ash/app_list/views/app_list_item_view.h b/ash/app_list/views/app_list_item_view.h
index 077ea40..6a14412 100644
--- a/ash/app_list/views/app_list_item_view.h
+++ b/ash/app_list/views/app_list_item_view.h
@@ -232,8 +232,8 @@
 
  private:
   friend class AppListItemViewProductivityLauncherTest;
+  friend class AppListMainViewTest;
   friend class test::AppsGridViewTest;
-  friend class test::AppListMainViewTest;
 
   class IconImageView;
   class AppNotificationIndicatorView;
diff --git a/ash/app_list/views/app_list_main_view_unittest.cc b/ash/app_list/views/app_list_main_view_unittest.cc
index d90cd4c..7adb0cffc 100644
--- a/ash/app_list/views/app_list_main_view_unittest.cc
+++ b/ash/app_list/views/app_list_main_view_unittest.cc
@@ -19,8 +19,10 @@
 #include "ash/app_list/views/page_switcher.h"
 #include "ash/app_list/views/paged_apps_grid_view.h"
 #include "ash/app_list/views/search_box_view.h"
+#include "ash/constants/ash_features.h"
 #include "ash/public/cpp/app_list/app_list_features.h"
 #include "ash/public/cpp/test/test_app_list_color_provider.h"
+#include "ash/style/ash_color_provider.h"
 #include "base/test/scoped_feature_list.h"
 #include "ui/compositor/layer.h"
 #include "ui/compositor/scoped_animation_duration_scale_mode.h"
@@ -34,17 +36,20 @@
 #include "ui/views/widget/widget.h"
 
 namespace ash {
-namespace test {
-
 namespace {
 
 const int kInitialItems = 2;
 
 }  // namespace
 
-class AppListMainViewTest : public views::ViewsTestBase {
+// Parameterized by ProductivityLauncher.
+class AppListMainViewTest : public views::ViewsTestBase,
+                            public testing::WithParamInterface<bool> {
  public:
-  AppListMainViewTest() = default;
+  AppListMainViewTest() {
+    feature_list_.InitWithFeatureState(features::kProductivityLauncher,
+                                       GetParam());
+  }
   AppListMainViewTest(const AppListMainViewTest& other) = delete;
   AppListMainViewTest& operator=(const AppListMainViewTest& other) = delete;
   ~AppListMainViewTest() override = default;
@@ -57,7 +62,7 @@
             ui::ScopedAnimationDurationScaleMode::ZERO_DURATION);
 
     // Create, and show the app list is fullscreen apps grid state.
-    delegate_ = std::make_unique<AppListTestViewDelegate>();
+    delegate_ = std::make_unique<test::AppListTestViewDelegate>();
     app_list_view_ = new AppListView(delegate_.get());
     app_list_view_->InitView(GetContext());
     app_list_view_->Show(AppListViewState::kFullscreenAllApps,
@@ -236,37 +241,43 @@
   }
 
  protected:
-  TestAppListColorProvider color_provider_;  // Needed by AppListView.
+  base::test::ScopedFeatureList feature_list_;
+  TestAppListColorProvider app_list_color_provider_;  // Needed by AppListView.
+  AshColorProvider ash_color_provider_;      // Needed by ContinueContainer.
   AppListView* app_list_view_ = nullptr;     // Owned by native widget.
-  std::unique_ptr<AppListTestViewDelegate> delegate_;
+  std::unique_ptr<test::AppListTestViewDelegate> delegate_;
 
  private:
   std::unique_ptr<ui::ScopedAnimationDurationScaleMode> zero_duration_mode_;
 };
 
+INSTANTIATE_TEST_SUITE_P(ProductivityLauncher,
+                         AppListMainViewTest,
+                         testing::Bool());
+
 // Tests that the close button becomes invisible after close button is clicked.
-TEST_F(AppListMainViewTest, CloseButtonInvisibleAfterCloseButtonClicked) {
+TEST_P(AppListMainViewTest, CloseButtonInvisibleAfterCloseButtonClicked) {
   PressKeyInSearchBox(ui::VKEY_A);
   ClickButton(search_box_view()->close_button());
   EXPECT_FALSE(search_box_view()->close_button()->GetVisible());
 }
 
 // Tests that the search box becomes empty after close button is clicked.
-TEST_F(AppListMainViewTest, SearchBoxEmptyAfterCloseButtonClicked) {
+TEST_P(AppListMainViewTest, SearchBoxEmptyAfterCloseButtonClicked) {
   PressKeyInSearchBox(ui::VKEY_A);
   ClickButton(search_box_view()->close_button());
   EXPECT_TRUE(search_box_view()->search_box()->GetText().empty());
 }
 
 // Tests that the search box is no longer active after close button is clicked.
-TEST_F(AppListMainViewTest, SearchBoxActiveAfterCloseButtonClicked) {
+TEST_P(AppListMainViewTest, SearchBoxActiveAfterCloseButtonClicked) {
   PressKeyInSearchBox(ui::VKEY_A);
   ClickButton(search_box_view()->close_button());
   EXPECT_FALSE(search_box_view()->is_search_box_active());
 }
 
 // Tests changing the AppListModel when switching profiles.
-TEST_F(AppListMainViewTest, ModelChanged) {
+TEST_P(AppListMainViewTest, ModelChanged) {
   delegate_->GetTestModel()->PopulateApps(kInitialItems);
   EXPECT_EQ(kInitialItems, GetRootViewModel()->view_size());
 
@@ -283,7 +294,7 @@
 
 // Tests dragging an item out of a single item folder and dropping it onto the
 // page switcher. Regression test for http://crbug.com/415530/.
-TEST_F(AppListMainViewTest, DragReparentItemOntoPageSwitcher) {
+TEST_P(AppListMainViewTest, DragReparentItemOntoPageSwitcher) {
   AppListItemView* folder_item_view = CreateAndOpenSingleItemFolder();
   ASSERT_TRUE(folder_item_view);
 
@@ -318,7 +329,7 @@
 // Test that an interrupted drag while reparenting an item from a folder, when
 // canceled via the root grid, correctly forwards the cancelation to the drag
 // ocurring from the folder.
-TEST_F(AppListMainViewTest, MouseDragItemOutOfFolderWithCancel) {
+TEST_P(AppListMainViewTest, MouseDragItemOutOfFolderWithCancel) {
   CreateAndOpenSingleItemFolder();
   AppListItemView* dragged = StartDragForReparent(0);
 
@@ -341,7 +352,7 @@
 // Test that dragging an app out of a single item folder and reparenting it
 // back into its original folder results in a cancelled reparent. This is a
 // regression test for http://crbug.com/429083.
-TEST_F(AppListMainViewTest, ReparentSingleItemOntoSelf) {
+TEST_P(AppListMainViewTest, ReparentSingleItemOntoSelf) {
   // Add a folder with 1 item.
   AppListItemView* folder_item_view = CreateAndOpenSingleItemFolder();
   std::string folder_id = folder_item_view->item()->id();
@@ -369,5 +380,4 @@
   EXPECT_EQ(1u, folder_item->item_list()->item_count());
 }
 
-}  // namespace test
 }  // namespace ash
diff --git a/ash/app_list/views/apps_container_view.cc b/ash/app_list/views/apps_container_view.cc
index 469574f..3258af4 100644
--- a/ash/app_list/views/apps_container_view.cc
+++ b/ash/app_list/views/apps_container_view.cc
@@ -29,6 +29,7 @@
 #include "ash/public/cpp/app_list/app_list_switches.h"
 #include "ash/resources/vector_icons/vector_icons.h"
 #include "ash/search_box/search_box_constants.h"
+#include "ash/shelf/gradient_layer_delegate.h"
 #include "ash/style/ash_color_provider.h"
 #include "ash/style/style_util.h"
 #include "base/bind.h"
@@ -119,9 +120,8 @@
 // Minimal horizontal distance from the page switcher to apps container bounds.
 constexpr int kPageSwitcherEndMargin = 16;
 
-// The apps grid view's fadeout zone height, that contains a fadeout mask, and
-// which is used as a margin for the `AppsGridView` contents.
-constexpr int kGridFadeoutZoneHeight = 24;
+// The vertical margin for the `AppsGridView` contents.
+constexpr int kGridVerticalMargin = 24;
 
 // The space between sort ui controls (including sort button and redo button).
 constexpr int kSortUiControlSpacing = 10;
@@ -143,6 +143,10 @@
 // The width of the separator.
 constexpr int kSeparatorWidth = 240;
 
+// The actual height of the fadeout gradient mask at the top and bottom of the
+// `scrollable_container_`.
+constexpr int kDefaultFadeoutMaskHeight = 16;
+
 // SortUiControl ---------------------------------------------------------------
 
 class SortUiControl : public views::ImageButton {
@@ -370,10 +374,11 @@
   AppListViewDelegate* view_delegate =
       contents_view_->GetAppListMainView()->view_delegate();
 
+  // The bounds of the |scrollable_container_| will visually clip the
+  // |continue_container_| and |apps_grid_view_| layers.
+  scrollable_container_->layer()->SetMasksToBounds(true);
+
   if (features::IsProductivityLauncherEnabled()) {
-    // The bounds of the |scrollable_container_| will visually clip the
-    // |continue_container_| layer during page changes.
-    scrollable_container_->layer()->SetMasksToBounds(true);
     continue_container_ = scrollable_container_->AddChildView(
         std::make_unique<ContinueContainer>(this, view_delegate));
   } else {
@@ -395,9 +400,9 @@
                                           /*container_delegate=*/this),
       0);
   apps_grid_view_->Init();
-
+  apps_grid_view_->pagination_model()->AddObserver(this);
   if (features::IsProductivityLauncherEnabled())
-    apps_grid_view_->pagination_model()->AddObserver(this);
+    apps_grid_view_->set_margin_for_gradient_mask(kDefaultFadeoutMaskHeight);
 
   // Page switcher should be initialized after AppsGridView.
   auto page_switcher = std::make_unique<PageSwitcher>(
@@ -429,9 +434,7 @@
 
 AppsContainerView::~AppsContainerView() {
   AppListModelProvider::Get()->RemoveObserver(this);
-
-  if (features::IsProductivityLauncherEnabled())
-    apps_grid_view_->pagination_model()->RemoveObserver(this);
+  apps_grid_view_->pagination_model()->RemoveObserver(this);
 
   // Make sure |page_switcher_| is deleted before |apps_grid_view_| because
   // |page_switcher_| uses the PaginationModel owned by |apps_grid_view_|.
@@ -471,7 +474,7 @@
           contents_view_->GetSearchBoxSize(AppListState::kStateApps)),
       0, 0);
   // Subtracts apps grid view insets from space available for apps grid.
-  available_bounds.Inset(0, kGridFadeoutZoneHeight);
+  available_bounds.Inset(0, kGridVerticalMargin);
 
   return available_bounds;
 }
@@ -610,6 +613,11 @@
 // PaginationModelObserver:
 void AppsContainerView::SelectedPageChanged(int old_selected,
                                             int new_selected) {
+  // There is no |continue_container_| to translate when productivity launcher
+  // is not enabled, so return early.
+  if (!features::IsProductivityLauncherEnabled())
+    return;
+
   // |continue_container_| is hidden above the grid when not on the first page.
   gfx::Transform transform;
   gfx::Vector2dF translate;
@@ -619,6 +627,11 @@
 }
 
 void AppsContainerView::TransitionChanged() {
+  // There is no |continue_container_| to translate when productivity launcher
+  // is not enabled, so return early.
+  if (!features::IsProductivityLauncherEnabled())
+    return;
+
   auto* pagination_model = apps_grid_view_->pagination_model();
   const PaginationModel::Transition& transition =
       pagination_model->transition();
@@ -646,6 +659,28 @@
   }
 }
 
+void AppsContainerView::TransitionStarted() {
+  MaybeCreateGradientMask();
+}
+
+void AppsContainerView::TransitionEnded() {
+  // TODO(crbug.com/1285184): Sometimes gradient mask is not removed because
+  // this function does not get called in some cases.
+
+  // Gradient mask is no longer necessary once transition is finished.
+  MaybeRemoveGradientMask();
+}
+
+void AppsContainerView::ScrollStarted() {
+  MaybeCreateGradientMask();
+}
+
+void AppsContainerView::ScrollEnded() {
+  // Need to reset the mask because transition will not happen in some
+  // cases. (See https://crbug.com/1049275)
+  MaybeRemoveGradientMask();
+}
+
 // PagedAppsGridView::ContainerDelegate:
 bool AppsContainerView::IsPointWithinPageFlipBuffer(
     const gfx::Point& point_in_apps_grid) const {
@@ -674,6 +709,36 @@
          point_in_parent.y() < kBottomDragBufferMax;
 }
 
+void AppsContainerView::MaybeCreateGradientMask() {
+  if (features::IsBackgroundBlurEnabled()) {
+    if (!layer()->layer_mask_layer() && !gradient_layer_delegate_) {
+      gradient_layer_delegate_ = std::make_unique<GradientLayerDelegate>();
+      UpdateGradientMaskBounds();
+    }
+    if (gradient_layer_delegate_) {
+      scrollable_container_->layer()->SetMaskLayer(
+          gradient_layer_delegate_->layer());
+    }
+  }
+}
+
+void AppsContainerView::MaybeRemoveGradientMask() {
+  if (scrollable_container_->layer()->layer_mask_layer() &&
+      !keep_gradient_mask_for_cardified_state_) {
+    scrollable_container_->layer()->SetMaskLayer(nullptr);
+  }
+}
+
+void AppsContainerView::OnCardifiedStateStarted() {
+  keep_gradient_mask_for_cardified_state_ = true;
+  MaybeCreateGradientMask();
+}
+
+void AppsContainerView::OnCardifiedStateEnded() {
+  keep_gradient_mask_for_cardified_state_ = false;
+  MaybeRemoveGradientMask();
+}
+
 // RecentAppsView::Delegate:
 void AppsContainerView::MoveFocusUpFromRecents() {
   DCHECK(!GetRecentApps()->children().empty());
@@ -848,19 +913,31 @@
       GetContentsBounds(),
       contents_view_->GetSearchBoxSize(AppListState::kStateApps));
   gfx::Rect grid_rect = rect;
-  grid_rect.Inset(margins.left(), kGridFadeoutZoneHeight, margins.right(),
+  grid_rect.Inset(margins.left(), kGridVerticalMargin, margins.right(),
                   margins.bottom());
   // The grid rect insets are added to calculated margins. Given that the
   // grid bounds rect should include insets, they have to be removed from
   // added margins.
   grid_rect.Inset(-grid_insets);
-  scrollable_container_->SetBoundsRect(grid_rect);
+
+  gfx::Rect scrollable_bounds = grid_rect;
+  // With productivity launcher enabled, add space to the top of the
+  // `scrollable_container_` bounds to make room for the gradient mask to be
+  // placed above the continue section.
+  if (features::IsProductivityLauncherEnabled())
+    scrollable_bounds.Inset(0, -kDefaultFadeoutMaskHeight, 0, 0);
+  scrollable_container_->SetBoundsRect(scrollable_bounds);
+
+  if (gradient_layer_delegate_)
+    UpdateGradientMaskBounds();
+
   bool first_page_config_changed = false;
   if (features::IsProductivityLauncherEnabled()) {
     const int continue_container_height =
         continue_container_->GetPreferredSize().height();
-    continue_container_->SetBoundsRect(
-        gfx::Rect(0, 0, grid_rect.width(), continue_container_height));
+    continue_container_->SetBoundsRect(gfx::Rect(0, kDefaultFadeoutMaskHeight,
+                                                 grid_rect.width(),
+                                                 continue_container_height));
     // Setting this offset prevents the app items in the grid from overlapping
     // with the continue section.
     first_page_config_changed = apps_grid_view_->ConfigureFirstPagePadding(
@@ -872,7 +949,11 @@
   // shown in the grid.
   UpdateTopLevelGridDimensions();
 
-  const gfx::Rect apps_grid_bounds(grid_rect.size());
+  gfx::Rect apps_grid_bounds(grid_rect.size());
+  // Set the apps grid bounds y to make room for the top gradient mask.
+  if (features::IsProductivityLauncherEnabled())
+    apps_grid_bounds.set_y(kDefaultFadeoutMaskHeight);
+
   if (apps_grid_view_->bounds() != apps_grid_bounds) {
     apps_grid_view_->SetBoundsRect(apps_grid_bounds);
   } else if (first_page_config_changed) {
@@ -1085,9 +1166,7 @@
           ? 0
           : kSuggestionChipContainerHeight + kSuggestionChipContainerTopMargin;
 
-  // NOTE: Use the fadeout zone height as min top margin to match the apps grid
-  // view's bottom margin.
-  return search_box_size.height() + kGridFadeoutZoneHeight +
+  return search_box_size.height() + kGridVerticalMargin +
          suggestion_chip_container_size;
 }
 
@@ -1152,7 +1231,7 @@
     // Productivity launcher does not have a preset number of rows per page.
     // Instead of adjusting the margins to fit a set number of rows, the grid
     // will change the number of rows to fit within the provided space.
-    vertical_margin = kGridFadeoutZoneHeight;
+    vertical_margin = kGridVerticalMargin;
   } else {
     vertical_margin =
         calculate_margin(GetIdealVerticalMargin(), available_height,
@@ -1166,9 +1245,9 @@
   const int min_horizontal_margin = GetMinHorizontalMarginForAppsGrid();
 
   cached_container_margins_.margins =
-      gfx::Insets(std::max(vertical_margin, kGridFadeoutZoneHeight),
+      gfx::Insets(std::max(vertical_margin, kGridVerticalMargin),
                   std::max(horizontal_margin, min_horizontal_margin),
-                  std::max(vertical_margin, kGridFadeoutZoneHeight),
+                  std::max(vertical_margin, kGridVerticalMargin),
                   std::max(horizontal_margin, min_horizontal_margin));
   cached_container_margins_.bounds_size = available_bounds.size();
   cached_container_margins_.search_box_size = search_box_size;
@@ -1390,4 +1469,21 @@
     suggestion_chip_container_view_->SetBlurDisabled(false);
 }
 
+void AppsContainerView::UpdateGradientMaskBounds() {
+  const gfx::Rect container_bounds = scrollable_container_->bounds();
+  const gfx::Rect top_gradient_bounds(0, 0, container_bounds.width(),
+                                      kDefaultFadeoutMaskHeight);
+  const gfx::Rect bottom_gradient_bounds(
+      0, container_bounds.height() - kDefaultFadeoutMaskHeight,
+      container_bounds.width(), kDefaultFadeoutMaskHeight);
+
+  gradient_layer_delegate_->set_start_fade_zone({top_gradient_bounds,
+                                                 /*fade_in=*/true,
+                                                 /*is_horizontal=*/false});
+  gradient_layer_delegate_->set_end_fade_zone({bottom_gradient_bounds,
+                                               /*fade_in=*/false,
+                                               /*is_horizonal=*/false});
+  gradient_layer_delegate_->layer()->SetBounds(container_bounds);
+}
+
 }  // namespace ash
diff --git a/ash/app_list/views/apps_container_view.h b/ash/app_list/views/apps_container_view.h
index e942e32d..d23a730 100644
--- a/ash/app_list/views/apps_container_view.h
+++ b/ash/app_list/views/apps_container_view.h
@@ -31,6 +31,7 @@
 class FolderBackgroundView;
 class PageSwitcher;
 class SuggestionChipContainerView;
+class GradientLayerDelegate;
 
 // AppsContainerView contains a root level AppsGridView to render the root level
 // app items, and a AppListFolderView to render the app items inside the
@@ -149,11 +150,17 @@
   // PaginationModelObserver:
   void SelectedPageChanged(int old_selected, int new_selected) override;
   void TransitionChanged() override;
+  void TransitionStarted() override;
+  void TransitionEnded() override;
+  void ScrollStarted() override;
+  void ScrollEnded() override;
 
   // PagedAppsGridView::ContainerDelegate:
   bool IsPointWithinPageFlipBuffer(const gfx::Point& point) const override;
   bool IsPointWithinBottomDragBuffer(const gfx::Point& point,
                                      int page_flip_zone_size) const override;
+  void OnCardifiedStateStarted() override;
+  void OnCardifiedStateEnded() override;
 
   // RecentAppsView::Delegate:
   void MoveFocusUpFromRecents() override;
@@ -252,6 +259,22 @@
   // Callback returned by DisableBlur().
   void OnSuggestionChipsBlurDisablerReleased();
 
+  // Updates the bounds of the gradient mask to fit the current bounds of the
+  // `scrollable_container_`.
+  void UpdateGradientMaskBounds();
+
+  // Creates a layer mask for gradient alpha when the feature is enabled. The
+  // gradient appears at the top and bottom of the 'scrollable_container_' to
+  // create a "fade out" effect when dragging the whole page.
+  void MaybeCreateGradientMask();
+
+  // Removes the gradient mask from being set as the mask layer.
+  void MaybeRemoveGradientMask();
+
+  // While true, the gradient mask will not be removed as a mask layer until
+  // cardified state ends.
+  bool keep_gradient_mask_for_cardified_state_ = false;
+
   ContentsView* const contents_view_;
 
   // The app list config used to configure sizing and layout of apps grid items
@@ -292,6 +315,8 @@
   // arguments (otherwise the margins will be recalculated).
   CachedContainerMargins cached_container_margins_;
 
+  std::unique_ptr<GradientLayerDelegate> gradient_layer_delegate_;
+
   base::WeakPtrFactory<AppsContainerView> weak_ptr_factory_{this};
 };
 
diff --git a/ash/app_list/views/apps_grid_view.cc b/ash/app_list/views/apps_grid_view.cc
index 86209f2..60d8fd8 100644
--- a/ash/app_list/views/apps_grid_view.cc
+++ b/ash/app_list/views/apps_grid_view.cc
@@ -307,10 +307,7 @@
   if (!folder_delegate_)
     DCHECK(folder_controller_);
 
-  // Clip any icons that are outside the grid view's bounds. These icons would
-  // otherwise be visible to the user when the grid view is off screen.
   SetPaintToLayer(ui::LAYER_NOT_DRAWN);
-  layer()->SetMasksToBounds(true);
 
   items_container_ = AddChildView(std::make_unique<views::View>());
   items_container_->SetPaintToLayer();
diff --git a/ash/app_list/views/apps_grid_view_unittest.cc b/ash/app_list/views/apps_grid_view_unittest.cc
index 83969bf..2d12141 100644
--- a/ash/app_list/views/apps_grid_view_unittest.cc
+++ b/ash/app_list/views/apps_grid_view_unittest.cc
@@ -3757,7 +3757,12 @@
 
   AppListItemView* folder_view = GetItemViewInTopLevelGrid(0);
   ASSERT_TRUE(folder_view->is_folder());
-  ASSERT_FALSE(apps_grid_view_->layer()->layer_mask_layer());
+
+  views::View* scrollable_container = app_list_view_->app_list_main_view()
+                                          ->contents_view()
+                                          ->apps_container_view()
+                                          ->scrollable_container_for_test();
+  ASSERT_FALSE(scrollable_container->layer()->layer_mask_layer());
 
   // On the first page drag upwards, there should not be a page switch and the
   // layer mask should make the folder lose blur.
@@ -3768,7 +3773,7 @@
   EXPECT_TRUE(scroll_update_upwards.handled());
 
   ASSERT_EQ(0, GetPaginationModel()->selected_page());
-  ASSERT_TRUE(apps_grid_view_->layer()->layer_mask_layer());
+  ASSERT_TRUE(scrollable_container->layer()->layer_mask_layer());
 
   // Continue drag, now switching directions and release. There shouldn't be
   // any transition and the mask layer should've been reset.
@@ -3778,7 +3783,7 @@
   EXPECT_TRUE(scroll_end.handled());
 
   EXPECT_FALSE(GetPaginationModel()->has_transition());
-  EXPECT_FALSE(apps_grid_view_->layer()->layer_mask_layer());
+  EXPECT_FALSE(scrollable_container->layer()->layer_mask_layer());
 }
 
 TEST_F(AppsGridViewTest, PopulateAppsGridWithTwoApps) {
diff --git a/ash/app_list/views/paged_apps_grid_view.cc b/ash/app_list/views/paged_apps_grid_view.cc
index a2930be..9bdd897 100644
--- a/ash/app_list/views/paged_apps_grid_view.cc
+++ b/ash/app_list/views/paged_apps_grid_view.cc
@@ -144,67 +144,6 @@
 
 }  // namespace
 
-// A layer delegate used for PagedAppsGridView's mask layer, with top and bottom
-// gradient fading out zones.
-class PagedAppsGridView::FadeoutLayerDelegate : public ui::LayerDelegate {
- public:
-  explicit FadeoutLayerDelegate(int fadeout_mask_height)
-      : layer_(ui::LAYER_TEXTURED), fadeout_mask_height_(fadeout_mask_height) {
-    layer_.set_delegate(this);
-    layer_.SetFillsBoundsOpaquely(false);
-  }
-  FadeoutLayerDelegate(const FadeoutLayerDelegate&) = delete;
-  FadeoutLayerDelegate& operator=(const FadeoutLayerDelegate&) = delete;
-
-  ~FadeoutLayerDelegate() override { layer_.set_delegate(nullptr); }
-
-  ui::Layer* layer() { return &layer_; }
-
- private:
-  // ui::LayerDelegate:
-  // TODO(warx): using a mask is expensive. It would be more efficient to avoid
-  // the mask for the central area and only use it for top/bottom areas.
-  void OnPaintLayer(const ui::PaintContext& context) override {
-    const gfx::Size size = layer()->size();
-    gfx::Rect top_rect(0, 0, size.width(), fadeout_mask_height_);
-    gfx::Rect bottom_rect(0, size.height() - fadeout_mask_height_, size.width(),
-                          fadeout_mask_height_);
-
-    views::PaintInfo paint_info =
-        views::PaintInfo::CreateRootPaintInfo(context, size);
-    const auto& prs = paint_info.paint_recording_size();
-
-    //  Pass the scale factor when constructing PaintRecorder so the MaskLayer
-    //  size is not incorrectly rounded (see https://crbug.com/921274).
-    ui::PaintRecorder recorder(context, paint_info.paint_recording_size(),
-                               static_cast<float>(prs.width()) / size.width(),
-                               static_cast<float>(prs.height()) / size.height(),
-                               nullptr);
-
-    gfx::Canvas* canvas = recorder.canvas();
-    // Clear the canvas.
-    canvas->DrawColor(SK_ColorBLACK, SkBlendMode::kSrc);
-    // Draw top gradient zone.
-    cc::PaintFlags flags;
-    flags.setBlendMode(SkBlendMode::kSrc);
-    flags.setAntiAlias(false);
-    flags.setShader(gfx::CreateGradientShader(
-        gfx::Point(), gfx::Point(0, fadeout_mask_height_), SK_ColorTRANSPARENT,
-        SK_ColorBLACK));
-    canvas->DrawRect(top_rect, flags);
-    // Draw bottom gradient zone.
-    flags.setShader(gfx::CreateGradientShader(
-        gfx::Point(0, size.height() - fadeout_mask_height_),
-        gfx::Point(0, size.height()), SK_ColorBLACK, SK_ColorTRANSPARENT));
-    canvas->DrawRect(bottom_rect, flags);
-  }
-  void OnDeviceScaleFactorChanged(float old_device_scale_factor,
-                                  float new_device_scale_factor) override {}
-
-  ui::Layer layer_;
-  const int fadeout_mask_height_;
-};
-
 PagedAppsGridView::PagedAppsGridView(
     ContentsView* contents_view,
     AppListA11yAnnouncer* a11y_announcer,
@@ -521,9 +460,6 @@
                                                page_height * pages));
   }
 
-  if (fadeout_layer_delegate_)
-    fadeout_layer_delegate_->layer()->SetBounds(layer()->bounds());
-
   CalculateIdealBounds();
   for (int i = 0; i < view_model()->view_size(); ++i) {
     AppListItemView* view = GetItemViewAt(i);
@@ -539,7 +475,6 @@
       items_container()->layer()->StackAtBottom(background_card);
     }
     MaskContainerToBackgroundBounds();
-    MaybeCreateGradientMask();
   }
   views::ViewModelUtils::SetViewBoundsToIdealBounds(pulsing_blocks_model());
 }
@@ -783,7 +718,6 @@
   // Drag ends and animation starts.
   presentation_time_recorder_.reset();
 
-  MaybeCreateGradientMask();
   CancelContextMenusOnCurrentPage();
 }
 
@@ -828,16 +762,11 @@
 
 void PagedAppsGridView::TransitionEnded() {
   pagination_metrics_tracker_->Stop();
-
-  // Gradient mask is no longer necessary once transition is finished.
-  if (layer()->layer_mask_layer())
-    layer()->SetMaskLayer(nullptr);
 }
 
 void PagedAppsGridView::ScrollStarted() {
   DCHECK(!presentation_time_recorder_);
 
-  MaybeCreateGradientMask();
   if (IsTabletMode()) {
     presentation_time_recorder_ = CreatePresentationTimeHistogramRecorder(
         GetWidget()->GetCompositor(), kPageDragScrollInTabletHistogram,
@@ -852,9 +781,6 @@
 void PagedAppsGridView::ScrollEnded() {
   // Scroll can end without triggering state animation.
   presentation_time_recorder_.reset();
-  // Need to reset the mask because transition will not happen in some
-  // cases. (See https://crbug.com/1049275)
-  layer()->SetMaskLayer(nullptr);
 }
 
 ////////////////////////////////////////////////////////////////////////////////
@@ -936,24 +862,6 @@
   return true;
 }
 
-void PagedAppsGridView::MaybeCreateGradientMask() {
-  if (!IsInFolder() && features::IsBackgroundBlurEnabled()) {
-    // TODO(newcomer): Improve implementation of the mask layer so we can
-    // enable it on all devices https://crbug.com/765292.
-    if (!layer()->layer_mask_layer()) {
-      // Always create a new layer. The layer may be recreated by animation,
-      // and using the mask layer used by the detached layer can lead to
-      // crash. b/118822974.
-      if (!fadeout_layer_delegate_) {
-        fadeout_layer_delegate_ =
-            std::make_unique<FadeoutLayerDelegate>(GetFadeoutMaskHeight());
-        fadeout_layer_delegate_->layer()->SetBounds(layer()->bounds());
-      }
-      layer()->SetMaskLayer(fadeout_layer_delegate_->layer());
-    }
-  }
-}
-
 bool PagedAppsGridView::IsValidPageFlipTarget(int page) const {
   if (pagination_model_.is_valid_page(page))
     return true;
@@ -1047,7 +955,7 @@
     AppendBackgroundCard();
   cardified_state_ = true;
   UpdateTilePadding();
-  MaybeCreateGradientMask();
+  container_delegate_->OnCardifiedStateStarted();
   AnimateCardifiedState();
 }
 
@@ -1201,6 +1109,11 @@
   if (bounds_animation_for_cardified_state_in_progress_ == 0) {
     animation_observers_.clear();
     OnBoundsAnimatorDone(/*animator=*/nullptr);
+
+    // Notify container that cardified state has ended once ending animations
+    // are complete.
+    if (!cardified_state_)
+      container_delegate_->OnCardifiedStateEnded();
   }
 }
 
@@ -1274,10 +1187,12 @@
 
 void PagedAppsGridView::MaskContainerToBackgroundBounds() {
   DCHECK(!background_cards_.empty());
-  // Mask apps grid container layer to the background card width.
-  layer()->SetClipRect(gfx::Rect(background_cards_[0]->bounds().x(), 0,
-                                 background_cards_[0]->bounds().width(),
-                                 layer()->bounds().height()));
+  // Mask apps grid container layer to the background card width. Optionally
+  // also include extra height to ensure the top gradient mask is shown as well.
+  layer()->SetClipRect(
+      gfx::Rect(background_cards_[0]->bounds().x(), -margin_for_gradient_mask_,
+                background_cards_[0]->bounds().width(),
+                layer()->bounds().height() + margin_for_gradient_mask_));
 }
 
 void PagedAppsGridView::RemoveAllBackgroundCards() {
diff --git a/ash/app_list/views/paged_apps_grid_view.h b/ash/app_list/views/paged_apps_grid_view.h
index e05b554..3f5fee0c 100644
--- a/ash/app_list/views/paged_apps_grid_view.h
+++ b/ash/app_list/views/paged_apps_grid_view.h
@@ -55,6 +55,13 @@
     virtual bool IsPointWithinBottomDragBuffer(
         const gfx::Point& point,
         int page_flip_zone_size) const = 0;
+
+    // Triggered when cardified state begins before animations start.
+    virtual void OnCardifiedStateStarted() {}
+
+    // Triggered when cardified state ends and the bounds animations for leaving
+    // cardified state have completed.
+    virtual void OnCardifiedStateEnded() {}
   };
 
   PagedAppsGridView(ContentsView* contents_view,
@@ -175,11 +182,13 @@
   int GetFirstPageRowsForTesting() const { return max_rows_on_first_page_; }
   int GetRowsForTesting() const { return max_rows_; }
 
+  void set_margin_for_gradient_mask(int margin) {
+    margin_for_gradient_mask_ = margin;
+  }
+
  private:
   friend class test::AppsGridViewTest;
 
-  class FadeoutLayerDelegate;
-
   // Gets the leading padding for app list item grid on the first app list page.
   // Includes the space reserved for the continue seaction of the app list UI,
   // and additional vertical tile padding before the first row of apps when
@@ -198,11 +207,6 @@
   // handled by PagedAppsGridView.
   bool ShouldHandleDragEvent(const ui::LocatedEvent& event);
 
-  // Creates a layer mask for gradient alpha when the feature is enabled. The
-  // gradient appears at the top and bottom of the apps grid to create a
-  // "fade out" effect when dragging the whole page.
-  void MaybeCreateGradientMask();
-
   // Returns true if the page is the right target to flip to.
   bool IsValidPageFlipTarget(int page) const;
 
@@ -282,10 +286,6 @@
   // between-item drags that move the entire grid, not for app icon drags.
   gfx::PointF last_mouse_drag_point_;
 
-  // Implements a "fade out" gradient at the top and bottom of the grid. Used
-  // during page flip transitions and for cardified drags.
-  std::unique_ptr<FadeoutLayerDelegate> fadeout_layer_delegate_;
-
   // Records smoothness of pagination animation.
   absl::optional<ui::ThroughputTracker> pagination_metrics_tracker_;
 
@@ -326,6 +326,10 @@
   std::vector<std::unique_ptr<ui::ImplicitAnimationObserver>>
       animation_observers_;
 
+  // A margin added to the height of the clip rect used for clipping the
+  // cardified state's background cards.
+  int margin_for_gradient_mask_ = 0;
+
   base::WeakPtrFactory<PagedAppsGridView> weak_ptr_factory_{this};
 };
 
diff --git a/ash/components/phonehub/BUILD.gn b/ash/components/phonehub/BUILD.gn
index fbb1f56f..780020c 100644
--- a/ash/components/phonehub/BUILD.gn
+++ b/ash/components/phonehub/BUILD.gn
@@ -220,6 +220,7 @@
   sources = [
     "browser_tabs_model_controller_unittest.cc",
     "browser_tabs_model_unittest.cc",
+    "camera_roll_item_unittest.cc",
     "camera_roll_manager_impl_unittest.cc",
     "camera_roll_thumbnail_decoder_impl_unittest.cc",
     "connection_scheduler_impl_unittest.cc",
diff --git a/ash/components/phonehub/camera_roll_item_unittest.cc b/ash/components/phonehub/camera_roll_item_unittest.cc
new file mode 100644
index 0000000..adf394c
--- /dev/null
+++ b/ash/components/phonehub/camera_roll_item_unittest.cc
@@ -0,0 +1,80 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "ash/components/phonehub/camera_roll_item.h"
+
+#include "ash/components/phonehub/proto/phonehub_api.pb.h"
+#include "testing/gtest/include/gtest/gtest.h"
+#include "ui/gfx/image/image.h"
+#include "ui/gfx/image/image_skia.h"
+
+namespace ash {
+namespace phonehub {
+
+namespace {
+
+const gfx::Image CreateTestImage() {
+  SkBitmap test_bitmap;
+  test_bitmap.allocN32Pixels(1, 1);
+  gfx::ImageSkia image_skia = gfx::ImageSkia::CreateFrom1xBitmap(test_bitmap);
+  image_skia.MakeThreadSafe();
+  return gfx::Image(image_skia);
+}
+
+}  // namespace
+
+class CameraRollItemTest : public testing::Test {
+ protected:
+  CameraRollItemTest() = default;
+  CameraRollItemTest(const CameraRollItemTest&) = delete;
+  CameraRollItemTest& operator=(const CameraRollItemTest&) = delete;
+  ~CameraRollItemTest() override = default;
+};
+
+TEST_F(CameraRollItemTest, ItemsMatch) {
+  proto::CameraRollItemMetadata metadata_1;
+  metadata_1.set_key("key1");
+  metadata_1.set_mime_type("image/png");
+  metadata_1.set_last_modified_millis(123456789L);
+  metadata_1.set_file_size_bytes(123456789L);
+  metadata_1.set_file_name("FakeImage.png");
+
+  proto::CameraRollItemMetadata metadata_2;
+  metadata_2.set_key("key1");
+  metadata_2.set_mime_type("image/png");
+  metadata_2.set_last_modified_millis(123456789L);
+  metadata_2.set_file_size_bytes(123456789L);
+  metadata_2.set_file_name("FakeImage.png");
+
+  CameraRollItem item_1(metadata_1, CreateTestImage());
+  CameraRollItem item_2(metadata_2, CreateTestImage());
+
+  EXPECT_TRUE(item_1 == item_2);
+  EXPECT_FALSE(item_1 != item_2);
+}
+
+TEST_F(CameraRollItemTest, ItemsDoNotMatch) {
+  proto::CameraRollItemMetadata metadata_1;
+  metadata_1.set_key("key1");
+  metadata_1.set_mime_type("image/png");
+  metadata_1.set_last_modified_millis(123456789L);
+  metadata_1.set_file_size_bytes(123456789L);
+  metadata_1.set_file_name("FakeImage.png");
+
+  proto::CameraRollItemMetadata metadata_2;
+  metadata_2.set_key("key2");
+  metadata_2.set_mime_type("video/mp4");
+  metadata_2.set_last_modified_millis(987654321L);
+  metadata_2.set_file_size_bytes(987654321L);
+  metadata_2.set_file_name("FakeVideo.mp4");
+
+  CameraRollItem item_1(metadata_1, CreateTestImage());
+  CameraRollItem item_2(metadata_2, CreateTestImage());
+
+  EXPECT_FALSE(item_1 == item_2);
+  EXPECT_TRUE(item_1 != item_2);
+}
+
+}  // namespace phonehub
+}  // namespace ash
diff --git a/ash/drag_drop/drag_drop_controller.cc b/ash/drag_drop/drag_drop_controller.cc
index b55f11e..e6d5759 100644
--- a/ash/drag_drop/drag_drop_controller.cc
+++ b/ash/drag_drop/drag_drop_controller.cc
@@ -241,8 +241,11 @@
       !pending_long_tap_.get()) {
     // If drag cancel animation is running, this cleanup is done when the
     // animation completes.
-    if (drag_source_window_)
+    if (drag_source_window_) {
+      // A check to catch an UAF issue like crbug.com/1282480 on non asan build.
+      DCHECK(!drag_source_window_->is_destroying());
       drag_source_window_->RemoveObserver(this);
+    }
     drag_source_window_ = nullptr;
   }
 
@@ -703,9 +706,14 @@
 void DragDropController::Cleanup() {
   for (aura::client::DragDropClientObserver& observer : observers_)
     observer.OnDragEnded();
-  if (drag_window_)
+
+  // Do not remove observer `the drag_window_1 is same as `drag_source_window_`.
+  // `drag_source_window_` is still necessary to process long tab and the
+  // observer will be reset when `drag_source_window_` is destroyed.
+  if (drag_window_ && drag_window_ != drag_source_window_)
     drag_window_->RemoveObserver(this);
   drag_window_ = nullptr;
+
   drag_data_.reset();
   allowed_operations_ = 0;
   tab_drag_drop_delegate_.reset();
diff --git a/ash/login/ui/public_account_menu_view.cc b/ash/login/ui/public_account_menu_view.cc
index 11b51c53..7c7cacae 100644
--- a/ash/login/ui/public_account_menu_view.cc
+++ b/ash/login/ui/public_account_menu_view.cc
@@ -62,7 +62,8 @@
 PublicAccountMenuView::PublicAccountMenuView(const std::vector<Item>& items,
                                              const size_t selected_index,
                                              const OnSelect& on_select)
-    : views::Combobox(new PublicAccountComboboxModel(items, selected_index)),
+    : views::Combobox(
+          std::make_unique<PublicAccountComboboxModel>(items, selected_index)),
       items_(items),
       on_select_(on_select) {
   SetPreferredSize(
diff --git a/ash/quick_pair/common/fast_pair/fast_pair_metrics.cc b/ash/quick_pair/common/fast_pair/fast_pair_metrics.cc
index 3ce4e034..c2b70c687 100644
--- a/ash/quick_pair/common/fast_pair/fast_pair_metrics.cc
+++ b/ash/quick_pair/common/fast_pair/fast_pair_metrics.cc
@@ -140,6 +140,17 @@
     "TotalConnectTime";
 const char kDeviceMetadataFetchResult[] =
     "Bluetooth.ChromeOS.FastPair.DeviceMetadataFetcher.Result";
+const char kFootprintsFetcherDeleteResult[] =
+    "Bluetooth.ChromeOS.FastPair.FootprintsFetcher.Delete.Result";
+const char kFootprintsFetcherPostResult[] =
+    "Bluetooth.ChromeOS.FastPair.FootprintsFetcher.Post.Result";
+const char kFootprintsFetcherGetResult[] =
+    "Bluetooth.ChromeOS.FastPair.FootprintsFetcher.Get.Result";
+const char kFastPairRepositoryCacheResult[] =
+    "Bluetooth.ChromeOS.FastPair.FastPairRepository.Cache.Result";
+const char kHandshakeResult[] = "Bluetooth.ChromeOS.FastPair.Handshake.Result";
+const char kHandshakeFailureReason[] =
+    "Bluetooth.ChromeOS.FastPair.Handshake.FailureReason";
 
 }  // namespace
 
@@ -385,5 +396,28 @@
   base::UmaHistogramBoolean(kDeviceMetadataFetchResult, success);
 }
 
+void RecordFootprintsFetcherDeleteResult(bool success) {
+  base::UmaHistogramBoolean(kFootprintsFetcherDeleteResult, success);
+}
+
+void RecordFootprintsFetcherPostResult(bool success) {
+  base::UmaHistogramBoolean(kFootprintsFetcherPostResult, success);
+}
+
+void RecordFootprintsFetcherGetResult(bool success) {
+  base::UmaHistogramBoolean(kFootprintsFetcherGetResult, success);
+}
+
+void RecordFastPairRepositoryCacheResult(bool success) {
+  base::UmaHistogramBoolean(kFastPairRepositoryCacheResult, success);
+}
+
+void RecordHandshakeResult(bool success) {
+  base::UmaHistogramBoolean(kHandshakeResult, success);
+}
+void RecordHandshakeFailureReason(HandshakeFailureReason failure_reason) {
+  base::UmaHistogramEnumeration(kHandshakeFailureReason, failure_reason);
+}
+
 }  // namespace quick_pair
 }  // namespace ash
diff --git a/ash/quick_pair/common/fast_pair/fast_pair_metrics.h b/ash/quick_pair/common/fast_pair/fast_pair_metrics.h
index 9eb26eec..9a70582 100644
--- a/ash/quick_pair/common/fast_pair/fast_pair_metrics.h
+++ b/ash/quick_pair/common/fast_pair/fast_pair_metrics.h
@@ -60,6 +60,19 @@
   kMaxValue = kSystemPairingUi,
 };
 
+// These values are persisted to logs. Entries should not be renumbered and
+// numeric values should never be reused. This enum should be kept in sync
+// with the FastPairHandshakeFailureReason enum in
+// src/tools/metrics/histograms/enums.xml.
+enum class COMPONENT_EXPORT(QUICK_PAIR_COMMON) HandshakeFailureReason {
+  kFailedGattInit = 0,
+  kFailedCreateEncryptor = 1,
+  kFailedWriteResponse = 2,
+  kFailedDecryptResponse = 3,
+  kFailedIncorrectResponseType = 4,
+  kMaxValue = kFailedIncorrectResponseType,
+};
+
 COMPONENT_EXPORT(QUICK_PAIR_COMMON)
 void AttemptRecordingFastPairEngagementFlow(const Device& device,
                                             FastPairEngagementFlowEvent event);
@@ -179,6 +192,24 @@
 COMPONENT_EXPORT(QUICK_PAIR_COMMON)
 void RecordDeviceMetadataFetchResult(bool success);
 
+COMPONENT_EXPORT(QUICK_PAIR_COMMON)
+void RecordFootprintsFetcherDeleteResult(bool success);
+
+COMPONENT_EXPORT(QUICK_PAIR_COMMON)
+void RecordFootprintsFetcherPostResult(bool success);
+
+COMPONENT_EXPORT(QUICK_PAIR_COMMON)
+void RecordFootprintsFetcherGetResult(bool success);
+
+COMPONENT_EXPORT(QUICK_PAIR_COMMON)
+void RecordFastPairRepositoryCacheResult(bool success);
+
+COMPONENT_EXPORT(QUICK_PAIR_COMMON)
+void RecordHandshakeResult(bool success);
+
+COMPONENT_EXPORT(QUICK_PAIR_COMMON)
+void RecordHandshakeFailureReason(HandshakeFailureReason failure_reason);
+
 }  // namespace quick_pair
 }  // namespace ash
 
diff --git a/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl.cc b/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl.cc
index 73c5893c..fce55b61 100644
--- a/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl.cc
+++ b/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl.cc
@@ -48,6 +48,8 @@
                     << ": Failed to init gatt client with failure = "
                     << failure.value();
     std::move(on_complete_callback_).Run(device_, failure.value());
+    RecordHandshakeResult(/*success=*/false);
+    RecordHandshakeFailureReason(HandshakeFailureReason::kFailedGattInit);
     return;
   }
 
@@ -68,6 +70,9 @@
                     << ": Fast Pair Data Encryptor failed to be created.";
     std::move(on_complete_callback_)
         .Run(device_, PairFailure::kDataEncryptorRetrieval);
+    RecordHandshakeResult(/*success=*/false);
+    RecordHandshakeFailureReason(
+        HandshakeFailureReason::kFailedCreateEncryptor);
     return;
   }
 
@@ -98,6 +103,8 @@
     QP_LOG(WARNING) << __func__
                     << ": Failed to write request: " << failure.value();
     RecordWriteKeyBasedCharacteristicPairFailure(failure.value());
+    RecordHandshakeResult(/*success=*/false);
+    RecordHandshakeFailureReason(HandshakeFailureReason::kFailedWriteResponse);
     std::move(on_complete_callback_).Run(device_, failure.value());
     return;
   }
@@ -118,6 +125,9 @@
     std::move(on_complete_callback_)
         .Run(device_, PairFailure::kKeybasedPairingResponseDecryptFailure);
     RecordKeyBasedCharacteristicDecryptResult(/*success=*/false);
+    RecordHandshakeResult(/*success=*/false);
+    RecordHandshakeFailureReason(
+        HandshakeFailureReason::kFailedDecryptResponse);
     return;
   }
 
@@ -127,6 +137,9 @@
     std::move(on_complete_callback_)
         .Run(device_, PairFailure::kIncorrectKeyBasedPairingResponseType);
     RecordKeyBasedCharacteristicDecryptResult(/*success=*/false);
+    RecordHandshakeResult(/*success=*/false);
+    RecordHandshakeFailureReason(
+        HandshakeFailureReason::kFailedIncorrectResponseType);
     return;
   }
 
@@ -138,6 +151,7 @@
   device_->set_classic_address(device_address);
 
   completed_successfully_ = true;
+  RecordHandshakeResult(/*success=*/true);
   std::move(on_complete_callback_).Run(device_, absl::nullopt);
 }
 
diff --git a/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl_unittest.cc b/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl_unittest.cc
index 57d9864..d53ab6eb 100644
--- a/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl_unittest.cc
+++ b/ash/quick_pair/fast_pair_handshake/fast_pair_handshake_impl_unittest.cc
@@ -105,6 +105,9 @@
     "Bluetooth.ChromeOS.FastPair.KeyBasedPairing.DecryptResult";
 const char kTotalDataEncryptorCreateTimeMetric[] =
     "Bluetooth.ChromeOS.FastPair.FastPairDataEncryptor.CreateTime";
+const char kHandshakeResult[] = "Bluetooth.ChromeOS.FastPair.Handshake.Result";
+const char kHandshakeFailureReason[] =
+    "Bluetooth.ChromeOS.FastPair.Handshake.FailureReason";
 
 }  // namespace
 
@@ -161,13 +164,19 @@
 };
 
 TEST_F(FastPairHandshakeImplTest, GattError) {
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
   fake_fast_pair_gatt_service_client()->RunOnGattClientInitializedCallback(
       PairFailure::kCreateGattConnection);
   EXPECT_EQ(failure_.value(), PairFailure::kCreateGattConnection);
   EXPECT_FALSE(handshake_->completed_successfully());
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 1);
 }
 
 TEST_F(FastPairHandshakeImplTest, DataEncryptorCreateError) {
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
   histogram_tester().ExpectTotalCount(kWriteKeyBasedCharacteristicResultMetric,
                                       0);
   histogram_tester().ExpectTotalCount(kDataEncryptorCreateResultMetric, 0);
@@ -184,9 +193,13 @@
   histogram_tester().ExpectTotalCount(
       kWriteKeyBasedCharacteristicPairFailureMetric, 0);
   histogram_tester().ExpectTotalCount(kTotalDataEncryptorCreateTimeMetric, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 1);
 }
 
 TEST_F(FastPairHandshakeImplTest, WriteResponseError) {
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
   histogram_tester().ExpectTotalCount(kDataEncryptorCreateResultMetric, 0);
   histogram_tester().ExpectTotalCount(kWriteKeyBasedCharacteristicResultMetric,
                                       0);
@@ -204,9 +217,13 @@
                                       1);
   histogram_tester().ExpectTotalCount(
       kWriteKeyBasedCharacteristicPairFailureMetric, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 1);
 }
 
 TEST_F(FastPairHandshakeImplTest, ParseResponseError) {
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptTime, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptResult, 0);
   histogram_tester().ExpectTotalCount(
@@ -222,9 +239,13 @@
       kWriteKeyBasedCharacteristicPairFailureMetric, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptTime, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 1);
 }
 
 TEST_F(FastPairHandshakeImplTest, ParseResponseWrongType) {
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptTime, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptResult, 0);
   fake_fast_pair_gatt_service_client()->RunOnGattClientInitializedCallback();
@@ -239,9 +260,13 @@
   EXPECT_FALSE(handshake_->completed_successfully());
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptTime, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 1);
 }
 
 TEST_F(FastPairHandshakeImplTest, Success) {
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 0);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptTime, 0);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptResult, 0);
   fake_fast_pair_gatt_service_client()->RunOnGattClientInitializedCallback();
@@ -255,6 +280,8 @@
   EXPECT_TRUE(handshake_->completed_successfully());
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptTime, 1);
   histogram_tester().ExpectTotalCount(kKeyBasedCharacteristicDecryptResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeResult, 1);
+  histogram_tester().ExpectTotalCount(kHandshakeFailureReason, 0);
 }
 
 }  // namespace quick_pair
diff --git a/ash/quick_pair/keyed_service/BUILD.gn b/ash/quick_pair/keyed_service/BUILD.gn
index 511b8b8f..ad3b8f0 100644
--- a/ash/quick_pair/keyed_service/BUILD.gn
+++ b/ash/quick_pair/keyed_service/BUILD.gn
@@ -57,6 +57,7 @@
     "//ash/quick_pair/message_stream:test_support",
     "//ash/quick_pair/pairing:test_support",
     "//ash/quick_pair/repository",
+    "//ash/quick_pair/repository:test_support",
     "//ash/quick_pair/scanning:test_support",
     "//ash/quick_pair/ui:test_support",
     "//ash/services/quick_pair",
diff --git a/ash/quick_pair/keyed_service/quick_pair_mediator.cc b/ash/quick_pair/keyed_service/quick_pair_mediator.cc
index bffbcad..41e58834 100644
--- a/ash/quick_pair/keyed_service/quick_pair_mediator.cc
+++ b/ash/quick_pair/keyed_service/quick_pair_mediator.cc
@@ -131,7 +131,9 @@
 
 void Mediator::OnDeviceFound(scoped_refptr<Device> device) {
   QP_LOG(INFO) << __func__ << ": " << device;
+  // On discovery, download and decode device images.
   ui_broker_->ShowDiscovery(device);
+  fast_pair_repository_->FetchDeviceImages(device);
 }
 
 void Mediator::OnDeviceLost(scoped_refptr<Device> device) {
@@ -156,7 +158,8 @@
 
 void Mediator::OnDevicePaired(scoped_refptr<Device> device) {
   QP_LOG(INFO) << __func__ << ": Device=" << device;
-  ui_broker_->RemoveNotifications(std::move(device));
+  ui_broker_->RemoveNotifications(device);
+  fast_pair_repository_->PersistDeviceImages(device);
 }
 
 void Mediator::OnPairFailure(scoped_refptr<Device> device,
diff --git a/ash/quick_pair/keyed_service/quick_pair_mediator_unittest.cc b/ash/quick_pair/keyed_service/quick_pair_mediator_unittest.cc
index b06b977..e200da02 100644
--- a/ash/quick_pair/keyed_service/quick_pair_mediator_unittest.cc
+++ b/ash/quick_pair/keyed_service/quick_pair_mediator_unittest.cc
@@ -18,7 +18,7 @@
 #include "ash/quick_pair/pairing/mock_pairer_broker.h"
 #include "ash/quick_pair/pairing/pairer_broker.h"
 #include "ash/quick_pair/pairing/retroactive_pairing_detector.h"
-#include "ash/quick_pair/repository/fast_pair_repository.h"
+#include "ash/quick_pair/repository/mock_fast_pair_repository.h"
 #include "ash/quick_pair/scanning/mock_scanner_broker.h"
 #include "ash/quick_pair/scanning/scanner_broker.h"
 #include "ash/quick_pair/ui/mock_ui_broker.h"
@@ -72,11 +72,16 @@
     std::unique_ptr<UIBroker> ui_broker = std::make_unique<MockUIBroker>();
     mock_ui_broker_ = static_cast<MockUIBroker*>(ui_broker.get());
 
+    std::unique_ptr<FastPairRepository> fast_pair_repository =
+        std::make_unique<MockFastPairRepository>();
+    mock_fast_pair_repository_ =
+        static_cast<MockFastPairRepository*>(fast_pair_repository.get());
+
     mediator_ = std::make_unique<Mediator>(
         std::move(tracker), std::move(scanner_broker),
         std::move(retroactive_pairing_detector),
         std::make_unique<FakeMessageStreamLookup>(), std::move(pairer_broker),
-        std::move(ui_broker), std::unique_ptr<FastPairRepository>(),
+        std::move(ui_broker), std::move(fast_pair_repository),
         std::make_unique<QuickPairProcessManagerImpl>());
 
     device_ = base::MakeRefCounted<Device>(kTestMetadataId, kTestAddress,
@@ -91,6 +96,7 @@
   FakeRetroactivePairingDetector* fake_retroactive_pairing_detector_;
   MockPairerBroker* mock_pairer_broker_;
   MockUIBroker* mock_ui_broker_;
+  MockFastPairRepository* mock_fast_pair_repository_;
   std::unique_ptr<Mediator> mediator_;
   base::test::SingleThreadTaskEnvironment task_environment_;
 };
diff --git a/ash/quick_pair/pairing/fast_pair/fast_pair_pairer.cc b/ash/quick_pair/pairing/fast_pair/fast_pair_pairer.cc
index c29dadfa..a9d7013 100644
--- a/ash/quick_pair/pairing/fast_pair/fast_pair_pairer.cc
+++ b/ash/quick_pair/pairing/fast_pair/fast_pair_pairer.cc
@@ -339,6 +339,7 @@
   if (device->GetAddress() == device_->ble_address ||
       device->GetAddress() == device_->classic_address()) {
     std::move(paired_callback_).Run(device_);
+    std::move(pairing_procedure_complete_).Run(device_);
   }
 }
 
diff --git a/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler.cc b/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler.cc
index a45424c..87a271e 100644
--- a/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler.cc
+++ b/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler.cc
@@ -31,6 +31,14 @@
   if (new_paired_status)
     return;
 
+  if (FastPairRepository::Get()->EvictDeviceImages(device)) {
+    QP_LOG(INFO) << __func__ << ": Repository evicted device images.";
+  } else {
+    QP_LOG(INFO) << __func__
+                 << ": Repository did not evict device images (no images found "
+                    "or other matching device IDs still paired).";
+  }
+
   if (FastPairRepository::Get()->DeleteAssociatedDevice(device)) {
     QP_LOG(INFO) << __func__ << ": Repository is processing the delete";
   } else {
diff --git a/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler_unittest.cc b/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler_unittest.cc
index 91a8387..d321abb 100644
--- a/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler_unittest.cc
+++ b/ash/quick_pair/pairing/fast_pair/fast_pair_unpair_handler_unittest.cc
@@ -66,5 +66,16 @@
   NotifyPairChanged(/*new_pair_state=*/false);
 }
 
+TEST_F(FastPairUnpairHandlerTest, DoesntEvictIfDevicePaired) {
+  EXPECT_CALL(*(mock_repository_.get()), EvictDeviceImages).Times(0);
+  NotifyPairChanged(/*new_pair_state=*/true);
+}
+
+TEST_F(FastPairUnpairHandlerTest, EvictsExpectedDevice) {
+  EXPECT_CALL(*(mock_repository_.get()), EvictDeviceImages(device_.get()))
+      .Times(1);
+  NotifyPairChanged(/*new_pair_state=*/false);
+}
+
 }  // namespace quick_pair
 }  // namespace ash
diff --git a/ash/quick_pair/repository/BUILD.gn b/ash/quick_pair/repository/BUILD.gn
index 83da8b0..1661ab5b 100644
--- a/ash/quick_pair/repository/BUILD.gn
+++ b/ash/quick_pair/repository/BUILD.gn
@@ -79,6 +79,7 @@
     "//ash/quick_pair/proto:fastpair_proto",
     "//base",
     "//base/test:test_support",
+    "//chromeos/services/bluetooth_config/public/cpp",
     "//device/bluetooth",
     "//net/traffic_annotation:test_support",
     "//testing/gtest",
diff --git a/ash/quick_pair/repository/fake_fast_pair_repository.cc b/ash/quick_pair/repository/fake_fast_pair_repository.cc
index 20ca579..772d442 100644
--- a/ash/quick_pair/repository/fake_fast_pair_repository.cc
+++ b/ash/quick_pair/repository/fake_fast_pair_repository.cc
@@ -6,6 +6,7 @@
 
 #include "ash/quick_pair/proto/fastpair.pb.h"
 #include "base/strings/string_util.h"
+#include "chromeos/services/bluetooth_config/public/cpp/device_image_info.h"
 #include "device/bluetooth/bluetooth_device.h"
 
 namespace ash {
@@ -74,5 +75,27 @@
   return saved_account_keys_.erase(device->GetAddress()) == 1;
 }
 
+// Unimplemented.
+void FakeFastPairRepository::FetchDeviceImages(scoped_refptr<Device> device) {
+  return;
+}
+
+// Unimplemented.
+bool FakeFastPairRepository::PersistDeviceImages(scoped_refptr<Device> device) {
+  return true;
+}
+
+// Unimplemented.
+bool FakeFastPairRepository::EvictDeviceImages(
+    const device::BluetoothDevice* device) {
+  return true;
+}
+
+// Unimplemented.
+absl::optional<const chromeos::bluetooth_config::DeviceImageInfo>
+FakeFastPairRepository::GetImagesForDevice(const std::string& device_id) {
+  return absl::nullopt;
+}
+
 }  // namespace quick_pair
 }  // namespace ash
diff --git a/ash/quick_pair/repository/fake_fast_pair_repository.h b/ash/quick_pair/repository/fake_fast_pair_repository.h
index 9bc7fb35..ad55b91 100644
--- a/ash/quick_pair/repository/fake_fast_pair_repository.h
+++ b/ash/quick_pair/repository/fake_fast_pair_repository.h
@@ -13,9 +13,15 @@
 #include "base/containers/flat_map.h"
 #include "third_party/abseil-cpp/absl/types/optional.h"
 
+namespace chromeos {
+namespace bluetooth_config {
+class DeviceImageInfo;
+}  // namespace bluetooth_config
+}  // namespace chromeos
+
 namespace device {
 class BluetoothDevice;
-}
+}  // namespace device
 
 namespace ash {
 namespace quick_pair {
@@ -49,6 +55,11 @@
   void AssociateAccountKey(scoped_refptr<Device> device,
                            const std::vector<uint8_t>& account_key) override;
   bool DeleteAssociatedDevice(const device::BluetoothDevice* device) override;
+  void FetchDeviceImages(scoped_refptr<Device> device) override;
+  bool PersistDeviceImages(scoped_refptr<Device> device) override;
+  bool EvictDeviceImages(const device::BluetoothDevice* device) override;
+  absl::optional<const chromeos::bluetooth_config::DeviceImageInfo>
+  GetImagesForDevice(const std::string& device_id) override;
 
  private:
   static void SetInstance(FastPairRepository* instance);
diff --git a/ash/quick_pair/repository/fast_pair/footprints_fetcher.cc b/ash/quick_pair/repository/fast_pair/footprints_fetcher.cc
index fba4778..e92216d 100644
--- a/ash/quick_pair/repository/fast_pair/footprints_fetcher.cc
+++ b/ash/quick_pair/repository/fast_pair/footprints_fetcher.cc
@@ -4,6 +4,7 @@
 
 #include "ash/quick_pair/repository/fast_pair/footprints_fetcher.h"
 
+#include "ash/quick_pair/common/fast_pair/fast_pair_metrics.h"
 #include "ash/quick_pair/common/logging.h"
 #include "ash/quick_pair/proto/fastpair.pb.h"
 #include "ash/quick_pair/proto/fastpair_data.pb.h"
@@ -89,6 +90,7 @@
 
   if (!response_body) {
     QP_LOG(WARNING) << __func__ << ": No response.";
+    RecordFootprintsFetcherGetResult(/*success=*/false);
     std::move(callback).Run(absl::nullopt);
     return;
   }
@@ -96,10 +98,12 @@
   nearby::fastpair::UserReadDevicesResponse devices;
   if (!devices.ParseFromString(*response_body)) {
     QP_LOG(WARNING) << __func__ << ": Failed to parse.";
+    RecordFootprintsFetcherGetResult(/*success=*/false);
     std::move(callback).Run(absl::nullopt);
     return;
   }
 
+  RecordFootprintsFetcherGetResult(/*success=*/true);
   QP_LOG(VERBOSE)
       << __func__
       << ": Successfully retrived footprints data.  Paired devices:";
@@ -131,6 +135,7 @@
     std::unique_ptr<HttpFetcher> http_fetcher,
     std::unique_ptr<std::string> response_body) {
   QP_LOG(VERBOSE) << __func__;
+  RecordFootprintsFetcherPostResult(/*success=*/response_body ? true : false);
 
   if (!response_body) {
     QP_LOG(WARNING) << __func__ << ": No response.";
@@ -158,6 +163,7 @@
     std::unique_ptr<HttpFetcher> http_fetcher,
     std::unique_ptr<std::string> response_body) {
   QP_LOG(VERBOSE) << __func__;
+  RecordFootprintsFetcherDeleteResult(/*success=*/response_body ? true : false);
 
   if (!response_body) {
     QP_LOG(WARNING) << __func__ << ": No response.";
diff --git a/ash/quick_pair/repository/fast_pair_repository.h b/ash/quick_pair/repository/fast_pair_repository.h
index addfd93..c92b63b 100644
--- a/ash/quick_pair/repository/fast_pair_repository.h
+++ b/ash/quick_pair/repository/fast_pair_repository.h
@@ -11,11 +11,18 @@
 #include "ash/quick_pair/repository/fast_pair/pairing_metadata.h"
 #include "base/callback.h"
 #include "base/containers/flat_map.h"
+#include "chromeos/services/bluetooth_config/public/cpp/device_image_info.h"
 #include "third_party/abseil-cpp/absl/types/optional.h"
 
+namespace chromeos {
+namespace bluetooth_config {
+class DeviceImageInfo;
+}  // namespace bluetooth_config
+}  // namespace chromeos
+
 namespace device {
 class BluetoothDevice;
-}
+}  // namespace device
 
 namespace ash {
 namespace quick_pair {
@@ -62,6 +69,22 @@
   virtual bool DeleteAssociatedDevice(
       const device::BluetoothDevice* device) = 0;
 
+  // Fetches the |device| images and a record of the device ID -> model ID
+  // mapping to memory.
+  virtual void FetchDeviceImages(scoped_refptr<Device> device) = 0;
+
+  // Persists the images and device ID belonging to |device| to
+  // disk, if model ID is not already persisted.
+  virtual bool PersistDeviceImages(scoped_refptr<Device> device) = 0;
+
+  // Evicts the images and device ID belonging to |device| from
+  // disk, if model ID is not in use by other device IDs.
+  virtual bool EvictDeviceImages(const device::BluetoothDevice* device) = 0;
+
+  // Returns device images belonging to |device_id|, if found.
+  virtual absl::optional<const chromeos::bluetooth_config::DeviceImageInfo>
+  GetImagesForDevice(const std::string& device_id) = 0;
+
  protected:
   static void SetInstance(FastPairRepository* instance);
 };
diff --git a/ash/quick_pair/repository/fast_pair_repository_impl.cc b/ash/quick_pair/repository/fast_pair_repository_impl.cc
index 1b3eee03..0b2b138d 100644
--- a/ash/quick_pair/repository/fast_pair_repository_impl.cc
+++ b/ash/quick_pair/repository/fast_pair_repository_impl.cc
@@ -16,8 +16,11 @@
 #include "ash/quick_pair/repository/fast_pair/proto_conversions.h"
 #include "ash/quick_pair/repository/fast_pair/saved_device_registry.h"
 #include "ash/services/quick_pair/public/cpp/account_key_filter.h"
+#include "base/callback_helpers.h"
+#include "base/memory/scoped_refptr.h"
 #include "base/strings/string_number_conversions.h"
 #include "base/strings/stringprintf.h"
+#include "chromeos/services/bluetooth_config/public/cpp/device_image_info.h"
 #include "components/image_fetcher/core/image_fetcher.h"
 #include "device/bluetooth/bluetooth_device.h"
 
@@ -48,10 +51,12 @@
   std::string normalized_id = base::ToUpperASCII(hex_model_id);
   if (metadata_cache_.contains(normalized_id)) {
     QP_LOG(VERBOSE) << __func__ << ": Data already in cache.";
+    RecordFastPairRepositoryCacheResult(/*success=*/true);
     std::move(callback).Run(metadata_cache_[normalized_id].get());
     return;
   }
   QP_LOG(VERBOSE) << __func__ << ": Not cached, fetching from web service.";
+  RecordFastPairRepositoryCacheResult(/*success=*/false);
   device_metadata_fetcher_->LookupHexDeviceId(
       normalized_id, base::BindOnce(&FastPairRepositoryImpl::OnMetadataFetched,
                                     weak_ptr_factory_.GetWeakPtr(),
@@ -242,5 +247,62 @@
   return true;
 }
 
+void FastPairRepositoryImpl::FetchDeviceImages(scoped_refptr<Device> device) {
+  QP_LOG(INFO) << __func__ << ": Fetching device images for model ID "
+               << device->metadata_id;
+  // Save a record of the device ID -> model ID for this device so that we can
+  // display images for device objects that lack a model ID, such as
+  // device::BluetoothDevice.
+  device_id_map_->SaveModelIdForDevice(device);
+
+  GetDeviceMetadata(
+      device->metadata_id,
+      base::BindOnce(&FastPairRepositoryImpl::CompleteFetchDeviceImages,
+                     weak_ptr_factory_.GetWeakPtr(), device->metadata_id));
+}
+
+void FastPairRepositoryImpl::CompleteFetchDeviceImages(
+    const std::string& hex_model_id,
+    DeviceMetadata* device_metadata) {
+  QP_LOG(INFO) << __func__
+               << ": Completing fetching device images for model ID "
+               << hex_model_id;
+  device_image_store_->SaveDeviceImages(hex_model_id, device_metadata,
+                                        base::DoNothing());
+}
+
+bool FastPairRepositoryImpl::PersistDeviceImages(scoped_refptr<Device> device) {
+  QP_LOG(INFO) << __func__ << ": Persisting device images for model ID "
+               << device->metadata_id;
+  device_id_map_->PersistRecordsForDevice(device);
+  return device_image_store_->PersistDeviceImages(device->metadata_id);
+}
+
+bool FastPairRepositoryImpl::EvictDeviceImages(
+    const device::BluetoothDevice* device) {
+  const std::string device_id = device->GetIdentifier();
+  absl::optional<const std::string> hex_model_id =
+      device_id_map_->GetModelIdForDeviceId(device_id);
+  if (!hex_model_id)
+    return false;
+  device_id_map_->EvictDeviceIdRecord(device_id);
+
+  // Before evicting images, check if other device IDs map to this model ID.
+  if (device_id_map_->HasPersistedRecordsForModelId(hex_model_id.value()))
+    return false;
+
+  return device_image_store_->EvictDeviceImages(hex_model_id.value());
+}
+
+absl::optional<const chromeos::bluetooth_config::DeviceImageInfo>
+FastPairRepositoryImpl::GetImagesForDevice(const std::string& device_id) {
+  absl::optional<const std::string> hex_model_id =
+      device_id_map_->GetModelIdForDeviceId(device_id);
+  if (!hex_model_id)
+    return absl::nullopt;
+
+  return device_image_store_->GetImagesForDeviceModel(hex_model_id.value());
+}
+
 }  // namespace quick_pair
 }  // namespace ash
diff --git a/ash/quick_pair/repository/fast_pair_repository_impl.h b/ash/quick_pair/repository/fast_pair_repository_impl.h
index b9a81470..b8ee590 100644
--- a/ash/quick_pair/repository/fast_pair_repository_impl.h
+++ b/ash/quick_pair/repository/fast_pair_repository_impl.h
@@ -13,9 +13,15 @@
 #include "base/time/time.h"
 #include "third_party/abseil-cpp/absl/types/optional.h"
 
+namespace chromeos {
+namespace bluetooth_config {
+class DeviceImageInfo;
+}  // namespace bluetooth_config
+}  // namespace chromeos
+
 namespace device {
 class BluetoothDevice;
-}
+}  // namespace device
 
 namespace nearby {
 namespace fastpair {
@@ -52,6 +58,11 @@
   void AssociateAccountKey(scoped_refptr<Device> device,
                            const std::vector<uint8_t>& account_key) override;
   bool DeleteAssociatedDevice(const device::BluetoothDevice* device) override;
+  void FetchDeviceImages(scoped_refptr<Device> device) override;
+  bool PersistDeviceImages(scoped_refptr<Device> device) override;
+  bool EvictDeviceImages(const device::BluetoothDevice* device) override;
+  absl::optional<const chromeos::bluetooth_config::DeviceImageInfo>
+  GetImagesForDevice(const std::string& device_id) override;
 
  private:
   void CheckAccountKeysImpl(const AccountKeyFilter& account_key_filter,
@@ -81,6 +92,10 @@
   void OnAddToFootprintsComplete(const std::string& mac_address,
                                  const std::vector<uint8_t>& account_key,
                                  bool success);
+  // Fethces the |device_metadata| images to the DeviceImageStore for
+  // |hex_model_id|.
+  void CompleteFetchDeviceImages(const std::string& hex_model_id,
+                                 DeviceMetadata* device_metadata);
 
   std::unique_ptr<DeviceMetadataFetcher> device_metadata_fetcher_;
   std::unique_ptr<FootprintsFetcher> footprints_fetcher_;
diff --git a/ash/quick_pair/repository/mock_fast_pair_repository.h b/ash/quick_pair/repository/mock_fast_pair_repository.h
index 822cbc6..3c09cc1 100644
--- a/ash/quick_pair/repository/mock_fast_pair_repository.h
+++ b/ash/quick_pair/repository/mock_fast_pair_repository.h
@@ -8,6 +8,7 @@
 #include "ash/quick_pair/repository/fast_pair_repository.h"
 #include "base/memory/scoped_refptr.h"
 #include "testing/gmock/include/gmock/gmock.h"
+#include "third_party/abseil-cpp/absl/types/optional.h"
 
 namespace ash {
 namespace quick_pair {
@@ -42,6 +43,22 @@
               DeleteAssociatedDevice,
               (const device::BluetoothDevice* device),
               (override));
+  MOCK_METHOD(void,
+              FetchDeviceImages,
+              (scoped_refptr<Device> device),
+              (override));
+  MOCK_METHOD(bool,
+              PersistDeviceImages,
+              (scoped_refptr<Device> device),
+              (override));
+  MOCK_METHOD(bool,
+              EvictDeviceImages,
+              (const device::BluetoothDevice* device),
+              (override));
+  MOCK_METHOD(absl::optional<const chromeos::bluetooth_config::DeviceImageInfo>,
+              GetImagesForDevice,
+              (const std::string& device_id),
+              (override));
 };
 
 }  // namespace quick_pair
diff --git a/ash/system/phonehub/camera_roll_thumbnail.h b/ash/system/phonehub/camera_roll_thumbnail.h
index 914dee7..c925b93 100644
--- a/ash/system/phonehub/camera_roll_thumbnail.h
+++ b/ash/system/phonehub/camera_roll_thumbnail.h
@@ -36,6 +36,9 @@
   const char* GetClassName() const override;
 
  private:
+  FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, ImageThumbnail);
+  FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, VideoThumbnail);
+
   void ButtonPressed();
   ui::SimpleMenuModel* GetMenuModel();
   void DownloadRequested();
diff --git a/ash/system/phonehub/camera_roll_view.h b/ash/system/phonehub/camera_roll_view.h
index 6abbd23..66fb42e 100644
--- a/ash/system/phonehub/camera_roll_view.h
+++ b/ash/system/phonehub/camera_roll_view.h
@@ -41,10 +41,13 @@
   bool should_disable_annimator_timer_for_test_ = false;
 
  private:
+  friend class CameraRollViewTest;
   FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, DisplayOptInView);
   FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, OptInAlready);
   FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, RightAfterOptIn);
   FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, ViewLayout);
+  FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, ImageThumbnail);
+  FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, VideoThumbnail);
 
   class CameraRollItemsView : public views::View {
    public:
@@ -64,6 +67,8 @@
 
    private:
     FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, ViewLayout);
+    FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, ImageThumbnail);
+    FRIEND_TEST_ALL_PREFIXES(CameraRollViewTest, VideoThumbnail);
 
     gfx::Point GetCameraRollItemPosition(int index);
     void CalculateIdealBounds();
diff --git a/ash/system/phonehub/camera_roll_view_unittest.cc b/ash/system/phonehub/camera_roll_view_unittest.cc
index 3e6b55f..29e0571 100644
--- a/ash/system/phonehub/camera_roll_view_unittest.cc
+++ b/ash/system/phonehub/camera_roll_view_unittest.cc
@@ -7,6 +7,8 @@
 #include "ash/components/phonehub/camera_roll_item.h"
 #include "ash/components/phonehub/fake_camera_roll_manager.h"
 #include "ash/components/phonehub/fake_user_action_recorder.h"
+#include "ash/system/phonehub/camera_roll_thumbnail.h"
+#include "ash/system/phonehub/phone_hub_metrics.h"
 #include "ash/test/ash_test_base.h"
 #include "camera_roll_view.h"
 #include "third_party/skia/include/core/SkBitmap.h"
@@ -85,12 +87,36 @@
     return items;
   }
 
-  const views::View* GetItemsView() const {
-    return camera_roll_view()->children().at(1);
+  const std::vector<phonehub::CameraRollItem> CreateSingleItemWithType(
+      bool is_video) {
+    phonehub::proto::CameraRollItemMetadata metadata;
+    metadata.set_key("key");
+    metadata.set_last_modified_millis(1577865600);
+    metadata.set_file_size_bytes(123456);
+
+    if (is_video) {
+      metadata.set_mime_type("video/mp4");
+      metadata.set_file_name("fake_video.mp4");
+    } else {
+      metadata.set_mime_type("image/png");
+      metadata.set_file_name("fake_image.png");
+    }
+
+    SkBitmap bitmap;
+    bitmap.allocN32Pixels(1, 1);
+    gfx::Image thumbnail = gfx::Image::CreateFrom1xBitmap(bitmap);
+
+    return std::vector<phonehub::CameraRollItem>{
+        phonehub::CameraRollItem(metadata, thumbnail)};
   }
 
-  const views::MenuButton* GetThumbnailView(int index) const {
-    return static_cast<views::MenuButton*>(
+  CameraRollView::CameraRollItemsView* GetItemsView() const {
+    return static_cast<CameraRollView::CameraRollItemsView*>(
+        camera_roll_view()->children().at(1));
+  }
+
+  CameraRollThumbnail* GetThumbnailView(int index) const {
+    return static_cast<CameraRollThumbnail*>(
         GetItemsView()->children().at(index));
   }
 
@@ -189,16 +215,12 @@
   // Test the layout size and positions of the items. If the layout is being
   // intentionally changed this test will need to be updated.
   fake_camera_roll_manager()->SetCurrentItems(CreateFakeItems(4));
-  EXPECT_EQ(camera_roll_view()->items_view_->CalculatePreferredSize(),
-            gfx::Size(328, 82));
-  EXPECT_EQ(camera_roll_view()->items_view_->GetCameraRollItemPosition(0),
-            gfx::Point(4, 4));
-  EXPECT_EQ(camera_roll_view()->items_view_->GetCameraRollItemPosition(1),
-            gfx::Point(86, 4));
-  EXPECT_EQ(camera_roll_view()->items_view_->GetCameraRollItemPosition(2),
-            gfx::Point(168, 4));
-  EXPECT_EQ(camera_roll_view()->items_view_->GetCameraRollItemPosition(3),
-            gfx::Point(250, 4));
+  GetItemsView()->Layout();
+  EXPECT_EQ(GetItemsView()->CalculatePreferredSize(), gfx::Size(328, 82));
+  EXPECT_EQ(GetThumbnailView(0)->bounds(), gfx::Rect(4, 4, 74, 74));
+  EXPECT_EQ(GetThumbnailView(1)->bounds(), gfx::Rect(86, 4, 74, 74));
+  EXPECT_EQ(GetThumbnailView(2)->bounds(), gfx::Rect(168, 4, 74, 74));
+  EXPECT_EQ(GetThumbnailView(3)->bounds(), gfx::Rect(250, 4, 74, 74));
 }
 
 TEST_F(CameraRollViewTest, AccessibleNameAndTooltip) {
@@ -216,4 +238,24 @@
   EXPECT_EQ(u"Recent photo 4 of 4.", GetThumbnailView(3)->GetTooltipText());
 }
 
+TEST_F(CameraRollViewTest, ImageThumbnail) {
+  PresetCameraRollOptInState(/*has_been_dismissed=*/true,
+                             /*can_be_enabled=*/false);
+  fake_camera_roll_manager()->SetCurrentItems(
+      CreateSingleItemWithType(/*is_video=*/false));
+
+  EXPECT_EQ(GetThumbnailView(0)->GetMediaType(),
+            phone_hub_metrics::CameraRollMediaType::kPhoto);
+}
+
+TEST_F(CameraRollViewTest, VideoThumbnail) {
+  PresetCameraRollOptInState(/*has_been_dismissed=*/true,
+                             /*can_be_enabled=*/false);
+  fake_camera_roll_manager()->SetCurrentItems(
+      CreateSingleItemWithType(/*is_video=*/true));
+
+  EXPECT_EQ(GetThumbnailView(0)->GetMediaType(),
+            phone_hub_metrics::CameraRollMediaType::kVideo);
+}
+
 }  // namespace ash
diff --git a/ash/system/toast/toast_manager_impl.cc b/ash/system/toast/toast_manager_impl.cc
index b11bf73..9eb56c7 100644
--- a/ash/system/toast/toast_manager_impl.cc
+++ b/ash/system/toast/toast_manager_impl.cc
@@ -31,7 +31,11 @@
   DCHECK(!id.empty());
 
   if (current_toast_data_ && current_toast_data_->id == id) {
-    // TODO(yoshiki): Replaces the visible toast.
+    // Replace the visible toast by adding the new toast data to the front of
+    // the queue and hiding the visible toast. Once the visible toast finishes
+    // hiding, the new toast will be displayed.
+    queue_.emplace_front(data);
+    overlay_->Show(false);
     return;
   }
 
diff --git a/ash/system/toast/toast_manager_unittest.cc b/ash/system/toast/toast_manager_unittest.cc
index 75172c4..bc000e4 100644
--- a/ash/system/toast/toast_manager_unittest.cc
+++ b/ash/system/toast/toast_manager_unittest.cc
@@ -7,6 +7,7 @@
 #include <string>
 
 #include "ash/public/cpp/shelf_config.h"
+#include "ash/public/cpp/toast_data.h"
 #include "ash/root_window_controller.h"
 #include "ash/screen_util.h"
 #include "ash/session/session_controller_impl.h"
@@ -121,6 +122,14 @@
 
   void CancelToast(const std::string& id) { manager()->Cancel(id); }
 
+  void ReplaceToast(const std::string& id,
+                    const std::string& text,
+                    int32_t duration,
+                    bool visible_on_lock_screen = false) {
+    manager()->Show(ToastData(id, base::ASCIIToUTF16(text), duration,
+                              visible_on_lock_screen));
+  }
+
   void ChangeLockState(bool lock) {
     SessionInfo info;
     info.state = lock ? session_manager::SessionState::LOCKED
@@ -451,6 +460,54 @@
   EXPECT_EQ(2, GetToastSerial());
 }
 
+TEST_F(ToastManagerImplTest, ReplaceContentsOfQueuedToast) {
+  std::string id1 = ShowToast(/*text=*/"TEXT1", ToastData::kInfiniteDuration);
+  std::string id2 = ShowToast(/*text=*/"TEXT2", ToastData::kInfiniteDuration);
+
+  // Confirm that the first toast is shown.
+  EXPECT_EQ(u"TEXT1", GetCurrentText());
+  EXPECT_EQ(1, GetToastSerial());
+
+  // Replace the contents of the queued toast.
+  ReplaceToast(id2, /*text=*/"TEXT2_updated", ToastData::kInfiniteDuration);
+
+  // Confirm that the shown toast is still visible.
+  EXPECT_EQ(u"TEXT1", GetCurrentText());
+  EXPECT_EQ(1, GetToastSerial());
+
+  // Cancel the shown toast.
+  CancelToast(id1);
+
+  // Confirm that the next toast is visible with the updated text.
+  EXPECT_EQ(u"TEXT2_updated", GetCurrentText());
+  EXPECT_EQ(2, GetToastSerial());
+}
+
+TEST_F(ToastManagerImplTest, ReplaceContentsOfCurrentToast) {
+  std::string id1 = ShowToast(/*text=*/"TEXT1", ToastData::kInfiniteDuration);
+  std::string id2 = ShowToast(/*text=*/"TEXT2", ToastData::kInfiniteDuration);
+
+  // Confirm that the first toast is shown.
+  EXPECT_EQ(u"TEXT1", GetCurrentText());
+  EXPECT_EQ(1, GetToastSerial());
+
+  // Replace the contents of the current toast showing.
+  ReplaceToast(id1, /*text=*/"TEXT1_updated", ToastData::kInfiniteDuration);
+
+  // Confirm that the new toast content is visible. The toast serial should be
+  // different, indicating the original toast's timeout won't close the new
+  // toast's.
+  EXPECT_EQ(u"TEXT1_updated", GetCurrentText());
+  EXPECT_EQ(2, GetToastSerial());
+
+  // Cancel the shown toast.
+  CancelToast(id1);
+
+  // Confirm that the second toast is now showing.
+  EXPECT_EQ(u"TEXT2", GetCurrentText());
+  EXPECT_EQ(3, GetToastSerial());
+}
+
 TEST_F(ToastManagerImplTest, ShowToastOnLockScreen) {
   // Simulate device lock.
   ChangeLockState(true);
diff --git a/ash/system/tray/tray_background_view.cc b/ash/system/tray/tray_background_view.cc
index 60704e08..4620d02 100644
--- a/ash/system/tray/tray_background_view.cc
+++ b/ash/system/tray/tray_background_view.cc
@@ -82,6 +82,9 @@
 // TrayBackgroundView.
 const base::TimeDelta kShowAnimationDelayMs = base::Milliseconds(100);
 
+// Number of active requests to disable CloseBubble().
+int g_disable_close_bubble_on_window_activated = 0;
+
 // Switches left and right insets if RTL mode is active.
 void MirrorInsetsIfNecessary(gfx::Insets* insets) {
   if (base::i18n::IsRTL()) {
@@ -339,6 +342,18 @@
       weak_factory_.GetWeakPtr()));
 }
 
+base::ScopedClosureRunner
+TrayBackgroundView::DisableCloseBubbleOnWindowActivated() {
+  ++g_disable_close_bubble_on_window_activated;
+  return base::ScopedClosureRunner(
+      base::BindOnce([]() { --g_disable_close_bubble_on_window_activated; }));
+}
+
+// static
+bool TrayBackgroundView::ShouldCloseBubbleOnWindowActivated() {
+  return g_disable_close_bubble_on_window_activated == 0;
+}
+
 void TrayBackgroundView::UpdateStatusArea(bool should_log_visible_pod_count) {
   auto* status_area_widget = shelf_->GetStatusAreaWidget();
   if (status_area_widget) {
@@ -451,8 +466,6 @@
   return nullptr;
 }
 
-void TrayBackgroundView::CloseBubble() {}
-
 void TrayBackgroundView::ShowBubble() {}
 
 void TrayBackgroundView::CalculateTargetBounds() {
diff --git a/ash/system/tray/tray_background_view.h b/ash/system/tray/tray_background_view.h
index f16a0e6..32e2a42 100644
--- a/ash/system/tray/tray_background_view.h
+++ b/ash/system/tray/tray_background_view.h
@@ -68,9 +68,16 @@
   // returns nullptr.
   virtual views::Widget* GetBubbleWidget() const;
 
+  // Returns a lock that prevents window activation from closing bubbles.
+  static base::ScopedClosureRunner DisableCloseBubbleOnWindowActivated()
+      WARN_UNUSED_RESULT;
+
+  // Whether a window activation change should close bubbles.
+  static bool ShouldCloseBubbleOnWindowActivated();
+
   // Closes the associated tray bubble view if it exists and is currently
   // showing.
-  virtual void CloseBubble();
+  virtual void CloseBubble() {}
 
   // Shows the associated tray bubble if one exists. |show_by_click| indicates
   // whether the showing operation is initiated by mouse or gesture click.
diff --git a/ash/system/tray/tray_bubble_wrapper.cc b/ash/system/tray/tray_bubble_wrapper.cc
index 5cca406..4d64131 100644
--- a/ash/system/tray/tray_bubble_wrapper.cc
+++ b/ash/system/tray/tray_bubble_wrapper.cc
@@ -85,6 +85,10 @@
   if (!gained_active)
     return;
 
+  // Check for the CloseBubble() lock.
+  if (!TrayBackgroundView::ShouldCloseBubbleOnWindowActivated())
+    return;
+
   views::Widget* bubble_widget = bubble_view()->GetWidget();
   // Don't close the bubble if a transient child is gaining or losing
   // activation.
diff --git a/ash/system/unified/unified_system_tray_bubble.cc b/ash/system/unified/unified_system_tray_bubble.cc
index 74da714..bd2b0f9d 100644
--- a/ash/system/unified/unified_system_tray_bubble.cc
+++ b/ash/system/unified/unified_system_tray_bubble.cc
@@ -9,6 +9,7 @@
 #include "ash/shell.h"
 #include "ash/system/message_center/unified_message_center_bubble.h"
 #include "ash/system/status_area_widget.h"
+#include "ash/system/tray/tray_background_view.h"
 #include "ash/system/tray/tray_constants.h"
 #include "ash/system/tray/tray_event_filter.h"
 #include "ash/system/tray/tray_utils.h"
@@ -280,6 +281,10 @@
   if (!gained_active || !bubble_widget_)
     return;
 
+  // Check for the CloseBubble() lock.
+  if (!TrayBackgroundView::ShouldCloseBubbleOnWindowActivated())
+    return;
+
   // Don't close the bubble if a transient child is gaining or losing
   // activation.
   if (bubble_widget_ == views::Widget::GetWidgetForNativeView(gained_active) ||
diff --git a/ash/webui/personalization_app/BUILD.gn b/ash/webui/personalization_app/BUILD.gn
index f116736a..ad4948f 100644
--- a/ash/webui/personalization_app/BUILD.gn
+++ b/ash/webui/personalization_app/BUILD.gn
@@ -9,6 +9,7 @@
 
 static_library("personalization_app") {
   sources = [
+    "personalization_app_theme_provider.h",
     "personalization_app_ui.cc",
     "personalization_app_ui.h",
     "personalization_app_url_constants.cc",
@@ -46,6 +47,8 @@
 source_set("browser_test_support") {
   testonly = true
   sources = [
+    "test/fake_personalization_app_theme_provider.cc",
+    "test/fake_personalization_app_theme_provider.h",
     "test/fake_personalization_app_wallpaper_provider.cc",
     "test/fake_personalization_app_wallpaper_provider.h",
     "test/personalization_app_browsertest_fixture.cc",
diff --git a/ash/webui/personalization_app/mojom/personalization_app.mojom b/ash/webui/personalization_app/mojom/personalization_app.mojom
index ed87407..823ad4e8 100644
--- a/ash/webui/personalization_app/mojom/personalization_app.mojom
+++ b/ash/webui/personalization_app/mojom/personalization_app.mojom
@@ -176,3 +176,20 @@
     // called in preview mode.
     CancelPreviewWallpaper();
 };
+
+// Receives information whenever there are theme related changes such as color
+// mode.
+interface ThemeObserver {
+  // Triggered by |ColorModeObserver::OnColorModeChanged|. Retrieves information
+  // whether dark mode is enabled
+  OnColorModeChanged(bool dark_mode_enabled);
+};
+
+// Provides APIs to expose theme settings such dark/light color mode.
+interface ThemeProvider {
+  // Binds a listener to start receiving updates on color mode changes.
+  SetThemeObserver(pending_remote<ThemeObserver> observer);
+
+  // Disables or enables dark color mode.
+  SetColorModePref(bool dark_mode_enabled);
+};
diff --git a/ash/webui/personalization_app/personalization_app_theme_provider.h b/ash/webui/personalization_app/personalization_app_theme_provider.h
new file mode 100644
index 0000000..6f7e51d45
--- /dev/null
+++ b/ash/webui/personalization_app/personalization_app_theme_provider.h
@@ -0,0 +1,23 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef ASH_WEBUI_PERSONALIZATION_APP_PERSONALIZATION_APP_THEME_PROVIDER_H_
+#define ASH_WEBUI_PERSONALIZATION_APP_PERSONALIZATION_APP_THEME_PROVIDER_H_
+
+#include "ash/webui/personalization_app/mojom/personalization_app.mojom.h"
+#include "mojo/public/cpp/bindings/pending_receiver.h"
+
+namespace ash {
+
+class PersonalizationAppThemeProvider
+    : public personalization_app::mojom::ThemeProvider {
+ public:
+  virtual void BindInterface(
+      mojo::PendingReceiver<personalization_app::mojom::ThemeProvider>
+          receiver) = 0;
+};
+
+}  // namespace ash
+
+#endif  // ASH_WEBUI_PERSONALIZATION_APP_PERSONALIZATION_APP_THEME_PROVIDER_H_
diff --git a/ash/webui/personalization_app/personalization_app_ui.cc b/ash/webui/personalization_app/personalization_app_ui.cc
index 46f5336..fe32c0c 100644
--- a/ash/webui/personalization_app/personalization_app_ui.cc
+++ b/ash/webui/personalization_app/personalization_app_ui.cc
@@ -7,6 +7,7 @@
 #include "ash/constants/ash_features.h"
 #include "ash/grit/ash_personalization_app_resources.h"
 #include "ash/grit/ash_personalization_app_resources_map.h"
+#include "ash/webui/personalization_app/personalization_app_theme_provider.h"
 #include "ash/webui/personalization_app/personalization_app_url_constants.h"
 #include "ash/webui/personalization_app/personalization_app_wallpaper_provider.h"
 #include "base/strings/strcat.h"
@@ -77,7 +78,10 @@
       {"exitFullscreen", IDS_PERSONALIZATION_APP_EXIT_FULL_SCREEN},
       {"ariaLabelExitFullscreen",
        IDS_PERSONALIZATION_APP_ARIA_LABEL_EXIT_FULL_SCREEN},
-      {"setAsWallpaper", IDS_PERSONALIZATION_APP_SET_AS_WALLPAPER}};
+      {"setAsWallpaper", IDS_PERSONALIZATION_APP_SET_AS_WALLPAPER},
+      {"themeLabel", IDS_PERSONALIZATION_APP_THEME_LABEL},
+      {"darkColorMode", IDS_PERSONALIZATION_APP_THEME_DARK_COLOR_MODE},
+      {"lightColorMode", IDS_PERSONALIZATION_APP_THEME_LIGHT_COLOR_MODE}};
   source->AddLocalizedStrings(kLocalizedStrings);
 
   if (features::IsWallpaperGooglePhotosIntegrationEnabled()) {
@@ -113,8 +117,10 @@
 
 PersonalizationAppUI::PersonalizationAppUI(
     content::WebUI* web_ui,
+    std::unique_ptr<PersonalizationAppThemeProvider> theme_provider,
     std::unique_ptr<PersonalizationAppWallpaperProvider> wallpaper_provider)
     : ui::MojoWebUIController(web_ui),
+      theme_provider_(std::move(theme_provider)),
       wallpaper_provider_(std::move(wallpaper_provider)) {
   DCHECK(wallpaper_provider_);
 
@@ -148,6 +154,11 @@
 PersonalizationAppUI::~PersonalizationAppUI() = default;
 
 void PersonalizationAppUI::BindInterface(
+    mojo::PendingReceiver<personalization_app::mojom::ThemeProvider> receiver) {
+  theme_provider_->BindInterface(std::move(receiver));
+}
+
+void PersonalizationAppUI::BindInterface(
     mojo::PendingReceiver<personalization_app::mojom::WallpaperProvider>
         receiver) {
   wallpaper_provider_->BindInterface(std::move(receiver));
diff --git a/ash/webui/personalization_app/personalization_app_ui.h b/ash/webui/personalization_app/personalization_app_ui.h
index 7ba53dff..df962c5 100644
--- a/ash/webui/personalization_app/personalization_app_ui.h
+++ b/ash/webui/personalization_app/personalization_app_ui.h
@@ -13,12 +13,14 @@
 
 namespace ash {
 
+class PersonalizationAppThemeProvider;
 class PersonalizationAppWallpaperProvider;
 
 class PersonalizationAppUI : public ui::MojoWebUIController {
  public:
   PersonalizationAppUI(
       content::WebUI* web_ui,
+      std::unique_ptr<PersonalizationAppThemeProvider> theme_provider,
       std::unique_ptr<PersonalizationAppWallpaperProvider> wallpaper_provider);
 
   PersonalizationAppUI(const PersonalizationAppUI&) = delete;
@@ -27,10 +29,15 @@
   ~PersonalizationAppUI() override;
 
   void BindInterface(
+      mojo::PendingReceiver<personalization_app::mojom::ThemeProvider>
+          receiver);
+
+  void BindInterface(
       mojo::PendingReceiver<personalization_app::mojom::WallpaperProvider>
           receiver);
 
  private:
+  std::unique_ptr<PersonalizationAppThemeProvider> theme_provider_;
   std::unique_ptr<PersonalizationAppWallpaperProvider> wallpaper_provider_;
 
   WEB_UI_CONTROLLER_TYPE_DECL();
diff --git a/ash/webui/personalization_app/resources/BUILD.gn b/ash/webui/personalization_app/resources/BUILD.gn
index fa11e78..fd6fb87 100644
--- a/ash/webui/personalization_app/resources/BUILD.gn
+++ b/ash/webui/personalization_app/resources/BUILD.gn
@@ -28,6 +28,11 @@
   "trusted/personalization_state.ts",
   "trusted/personalization_store.ts",
   "trusted/personalization_test_api.ts",
+  "trusted/theme/theme_actions.ts",
+  "trusted/theme/theme_controller.ts",
+  "trusted/theme/theme_interface_provider.ts",
+  "trusted/theme/theme_reducers.ts",
+  "trusted/theme/theme_state.ts",
   "trusted/utils.ts",
   "trusted/wallpaper/wallpaper_actions.ts",
   "trusted/wallpaper/untrusted_message_handler.ts",
@@ -49,6 +54,7 @@
   "trusted/ambient/ambient_subpage_element.ts",
   "trusted/personalization_main_element.ts",
   "trusted/personalization_router_element.ts",
+  "trusted/personalization_theme_element.ts",
   "trusted/personalization_toast_element.ts",
   "trusted/personalization_breadcrumb_element.ts",
   "trusted/user/user_subpage_element.ts",
diff --git a/ash/webui/personalization_app/resources/common/styles.html b/ash/webui/personalization_app/resources/common/styles.html
index 6e39147..78291781c 100644
--- a/ash/webui/personalization_app/resources/common/styles.html
+++ b/ash/webui/personalization_app/resources/common/styles.html
@@ -218,5 +218,17 @@
       width: 100%;
       z-index: 1;
     }
+    cr-button {
+      border-color: var(--cros-button-stroke-color-secondary);
+      border-radius: 16px;
+    }
+    cr-button[aria-pressed=true],
+    cr-button[aria-selected=true] {
+      background-color: var(--cros-highlight-color);
+      border: 0;
+    }
+    cr-button + cr-button {
+      margin-inline-start: 8px;
+    }
   </style>
 </template>
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_actions.ts b/ash/webui/personalization_app/resources/trusted/personalization_actions.ts
index 19fd56e..2b20806 100644
--- a/ash/webui/personalization_app/resources/trusted/personalization_actions.ts
+++ b/ash/webui/personalization_app/resources/trusted/personalization_actions.ts
@@ -4,6 +4,7 @@
 
 import {Action} from 'chrome://resources/js/cr/ui/store.js';
 
+import {ThemeActions} from './theme/theme_actions.js';
 import {WallpaperActions} from './wallpaper/wallpaper_actions.js';
 
 /**
@@ -24,4 +25,4 @@
   return {name: PersonalizationActionName.DISMISS_ERROR};
 }
 
-export type Actions = WallpaperActions|DismissErrorAction;
+export type Actions = ThemeActions|WallpaperActions|DismissErrorAction;
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_app.ts b/ash/webui/personalization_app/resources/trusted/personalization_app.ts
index bda9b01..47f7209 100644
--- a/ash/webui/personalization_app/resources/trusted/personalization_app.ts
+++ b/ash/webui/personalization_app/resources/trusted/personalization_app.ts
@@ -15,6 +15,7 @@
 import './personalization_toast_element.js';
 import './personalization_breadcrumb_element.js';
 import './personalization_main_element.js';
+import './personalization_theme_element.js';
 import './user/user_subpage_element.js';
 import './wallpaper/wallpaper_subpage.js';
 import {emptyState} from './personalization_state.js';
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_main_element.html b/ash/webui/personalization_app/resources/trusted/personalization_main_element.html
index a5102cee..407ed982 100644
--- a/ash/webui/personalization_app/resources/trusted/personalization_main_element.html
+++ b/ash/webui/personalization_app/resources/trusted/personalization_main_element.html
@@ -2,4 +2,7 @@
 <div id="container">
   <h1>Personalization</h1>
   <wallpaper-preview></wallpaper-preview>
-</div>
\ No newline at end of file
+  <template is="dom-if" if="[[isDarkLightModeEnabled_()]]">
+    <personalization-theme></personalization-theme>
+  </template>
+</div>
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_main_element.ts b/ash/webui/personalization_app/resources/trusted/personalization_main_element.ts
index 56c5806..a11c8ce 100644
--- a/ash/webui/personalization_app/resources/trusted/personalization_main_element.ts
+++ b/ash/webui/personalization_app/resources/trusted/personalization_main_element.ts
@@ -7,6 +7,7 @@
  * the personalization hub.
  */
 
+import {loadTimeData} from 'chrome://resources/js/load_time_data.m.js';
 import {html} from 'chrome://resources/polymer/v3_0/polymer/polymer_bundled.min.js';
 import {WithPersonalizationStore} from './personalization_store.js';
 
@@ -22,6 +23,10 @@
   static get properties() {
     return {};
   }
+
+  private isDarkLightModeEnabled_(): boolean {
+    return loadTimeData.getBoolean('isDarkLightModeEnabled');
+  }
 }
 
 customElements.define(PersonalizationMain.is, PersonalizationMain);
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_reducers.ts b/ash/webui/personalization_app/resources/trusted/personalization_reducers.ts
index 138336d..aff2da7 100644
--- a/ash/webui/personalization_app/resources/trusted/personalization_reducers.ts
+++ b/ash/webui/personalization_app/resources/trusted/personalization_reducers.ts
@@ -16,6 +16,8 @@
 import {Actions} from './personalization_actions.js';
 import {WallpaperImage} from './personalization_app.mojom-webui.js';
 import {PersonalizationState} from './personalization_state.js';
+import {themeReducers} from './theme/theme_reducers.js';
+import {ThemeState} from './theme/theme_state.js';
 import {WallpaperActionName} from './wallpaper/wallpaper_actions.js';
 import {wallpaperReducers} from './wallpaper/wallpaper_reducers.js';
 import {WallpaperState} from './wallpaper/wallpaper_state.js';
@@ -94,6 +96,7 @@
 }
 
 const root = combineReducers<PersonalizationState>({
+  theme: combineReducers<ThemeState>(themeReducers),
   wallpaper: combineReducers<WallpaperState>(wallpaperReducers),
   error: errorReducer,
 });
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_state.ts b/ash/webui/personalization_app/resources/trusted/personalization_state.ts
index 3232e2c..6fb0278 100644
--- a/ash/webui/personalization_app/resources/trusted/personalization_state.ts
+++ b/ash/webui/personalization_app/resources/trusted/personalization_state.ts
@@ -2,16 +2,19 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+import {emptyState as emptyThemeState, ThemeState} from './theme/theme_state.js';
 import {emptyState as emptyWallpaperState, WallpaperState} from './wallpaper/wallpaper_state.js';
 
 export interface PersonalizationState {
   wallpaper: WallpaperState;
   error: string|null;
+  theme: ThemeState;
 }
 
 export function emptyState(): PersonalizationState {
   return {
     wallpaper: emptyWallpaperState(),
     error: null,
+    theme: emptyThemeState(),
   };
 }
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_theme_element.html b/ash/webui/personalization_app/resources/trusted/personalization_theme_element.html
new file mode 100644
index 0000000..7f6a9c4
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/personalization_theme_element.html
@@ -0,0 +1,15 @@
+<style include="common-style">
+</style>
+<div id="container">
+  <h2>[[i18n('themeLabel')]]</h2>
+  <cr-button id="lightMode" data-color-mode="LIGHT"
+      on-click="onClickColorModeButton_"
+      aria-pressed$="[[getLightAriaPressed_(darkModeEnabled_)]]">
+    <div class="text">[[i18n('lightColorMode')]]</div>
+  </cr-button>
+  <cr-button id="darkMode" data-color-mode="DARK"
+      on-click="onClickColorModeButton_"
+      aria-pressed$="[[getDarkAriaPressed_(darkModeEnabled_)]]">
+    <div class="text">[[i18n('darkColorMode')]]</div>
+  </cr-button>
+</div>
diff --git a/ash/webui/personalization_app/resources/trusted/personalization_theme_element.ts b/ash/webui/personalization_app/resources/trusted/personalization_theme_element.ts
new file mode 100644
index 0000000..7e561a0
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/personalization_theme_element.ts
@@ -0,0 +1,94 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+/**
+ * @fileoverview This component displays color mode settings.
+ */
+
+import 'chrome://resources/cr_elements/cr_button/cr_button.m.js';
+import 'chrome://resources/polymer/v3_0/iron-icon/iron-icon.js';
+import 'chrome://resources/polymer/v3_0/iron-iconset-svg/iron-iconset-svg.js';
+import '../common/styles.js';
+
+import {html} from 'chrome://resources/polymer/v3_0/polymer/polymer_bundled.min.js';
+
+import {ThemeObserverInterface, ThemeObserverReceiver, ThemeProviderInterface} from './personalization_app.mojom-webui.js';
+import {WithPersonalizationStore} from './personalization_store.js';
+import {setDarkModeEnabledAction} from './theme/theme_actions.js';
+import {setColorModePref} from './theme/theme_controller.js';
+import {getThemeProvider} from './theme/theme_interface_provider.js';
+
+/**
+ * Set up the observer to listen for color mode changes.
+ */
+function initThemeObserver(
+    themeProvider: ThemeProviderInterface,
+    target: ThemeObserverInterface): ThemeObserverReceiver {
+  const receiver = new ThemeObserverReceiver(target);
+  themeProvider.setThemeObserver(receiver.$.bindNewPipeAndPassRemote());
+  return receiver;
+}
+
+export class PersonalizationThemeElement extends WithPersonalizationStore
+    implements ThemeObserverInterface {
+  static get is() {
+    return 'personalization-theme';
+  }
+
+  static get template() {
+    return html`{__html_template__}`;
+  }
+
+  static get properties() {
+    return {
+      darkModeEnabled_: Boolean,
+    };
+  }
+
+  private darkModeEnabled_: boolean;
+  private themeProvider_: ThemeProviderInterface;
+  private themeObserver_: ThemeObserverReceiver|null;
+
+  constructor() {
+    super();
+    this.themeProvider_ = getThemeProvider();
+    this.themeObserver_ = null;
+  }
+
+  connectedCallback() {
+    super.connectedCallback();
+    this.themeObserver_ = initThemeObserver(this.themeProvider_, this);
+    this.watch<PersonalizationThemeElement['darkModeEnabled_']>(
+        'darkModeEnabled_', state => state.theme.darkModeEnabled);
+    this.updateFromStore();
+  }
+
+  disconnectedCallback() {
+    if (this.themeObserver_) {
+      this.themeObserver_.$.close();
+    }
+  }
+
+  onColorModeChanged(darkModeEnabled: boolean) {
+    this.dispatch(setDarkModeEnabledAction(darkModeEnabled));
+  }
+
+  private getLightAriaPressed_(darkModeEnabled: boolean) {
+    return (!darkModeEnabled).toString();
+  }
+
+  private getDarkAriaPressed_(darkModeEnabled: boolean) {
+    return darkModeEnabled.toString();
+  }
+
+  private onClickColorModeButton_(event: Event) {
+    const eventTarget = event.currentTarget as HTMLElement;
+    const colorMode = eventTarget.dataset['colorMode'];
+    setColorModePref(
+        colorMode === 'DARK', this.themeProvider_, this.getStore());
+  }
+}
+
+customElements.define(
+    PersonalizationThemeElement.is, PersonalizationThemeElement);
diff --git a/ash/webui/personalization_app/resources/trusted/theme/theme_actions.ts b/ash/webui/personalization_app/resources/trusted/theme/theme_actions.ts
new file mode 100644
index 0000000..66439e1
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/theme/theme_actions.ts
@@ -0,0 +1,25 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+import {Action} from 'chrome://resources/js/cr/ui/store.js';
+
+/**
+ * @fileoverview Defines the actions to change theme state.
+ */
+
+export enum ThemeActionName {
+  SET_DARK_MODE_ENABLED = 'set_dark_mode_enabled',
+}
+
+export type ThemeActions = SetDarkModeEnabledAction;
+
+export type SetDarkModeEnabledAction = Action&{
+  name: ThemeActionName.SET_DARK_MODE_ENABLED;
+  enabled: boolean;
+};
+
+export function setDarkModeEnabledAction(enabled: boolean):
+    SetDarkModeEnabledAction {
+  return {name: ThemeActionName.SET_DARK_MODE_ENABLED, enabled};
+}
diff --git a/ash/webui/personalization_app/resources/trusted/theme/theme_controller.ts b/ash/webui/personalization_app/resources/trusted/theme/theme_controller.ts
new file mode 100644
index 0000000..33639cd
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/theme/theme_controller.ts
@@ -0,0 +1,22 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+import {ThemeProviderInterface} from '../personalization_app.mojom-webui.js';
+import {PersonalizationStore} from '../personalization_store.js';
+import {setDarkModeEnabledAction} from './theme_actions.js';
+
+/**
+ * @fileoverview contains all of the functions to interact with C++ side through
+ * mojom calls. Handles setting |PersonalizationStore| state in response to
+ * mojom data.
+ */
+
+// Disables or enables dark color mode.
+export async function setColorModePref(
+    darkModeEnabled: boolean, provider: ThemeProviderInterface,
+    store: PersonalizationStore): Promise<void> {
+  await provider.setColorModePref(darkModeEnabled);
+  // Dispatch action to highlight color mode.
+  store.dispatch(setDarkModeEnabledAction(darkModeEnabled));
+}
diff --git a/ash/webui/personalization_app/resources/trusted/theme/theme_interface_provider.ts b/ash/webui/personalization_app/resources/trusted/theme/theme_interface_provider.ts
new file mode 100644
index 0000000..d6b6f42
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/theme/theme_interface_provider.ts
@@ -0,0 +1,29 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+/**
+ * @fileoverview a singleton getter for the theme mojom interface used in
+ * the Personalization SWA. Also contains utility functions around fetching
+ * mojom data and mocking out the implementation for testing.
+ */
+
+import 'chrome://resources/mojo/mojo/public/js/bindings.js';
+import 'chrome://resources/mojo/url/mojom/url.mojom-webui.js';
+
+import {ThemeProvider, ThemeProviderInterface} from '../personalization_app.mojom-webui.js';
+
+let themeProvider: ThemeProviderInterface|null = null;
+
+export function setThemeProviderForTesting(
+    testProvider: ThemeProviderInterface): void {
+  themeProvider = testProvider;
+}
+
+/** Returns a singleton for the ThemeProvider mojom interface. */
+export function getThemeProvider(): ThemeProviderInterface {
+  if (!themeProvider) {
+    themeProvider = ThemeProvider.getRemote();
+  }
+  return themeProvider;
+}
diff --git a/ash/webui/personalization_app/resources/trusted/theme/theme_reducers.ts b/ash/webui/personalization_app/resources/trusted/theme/theme_reducers.ts
new file mode 100644
index 0000000..08b46f8
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/theme/theme_reducers.ts
@@ -0,0 +1,26 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+import {Actions} from '../personalization_actions.js';
+import {ReducerFunction} from '../personalization_reducers.js';
+import {PersonalizationState} from '../personalization_state.js';
+
+import {ThemeActionName} from './theme_actions.js';
+import {ThemeState} from './theme_state.js';
+
+export function darkModeEnabledReducer(
+    state: ThemeState['darkModeEnabled'], action: Actions,
+    _: PersonalizationState): ThemeState['darkModeEnabled'] {
+  switch (action.name) {
+    case ThemeActionName.SET_DARK_MODE_ENABLED:
+      return action.enabled;
+    default:
+      return state;
+  }
+}
+
+export const themeReducers:
+    {[K in keyof ThemeState]: ReducerFunction<ThemeState[K]>} = {
+      darkModeEnabled: darkModeEnabledReducer,
+    };
diff --git a/ash/webui/personalization_app/resources/trusted/theme/theme_state.ts b/ash/webui/personalization_app/resources/trusted/theme/theme_state.ts
new file mode 100644
index 0000000..f24d7db
--- /dev/null
+++ b/ash/webui/personalization_app/resources/trusted/theme/theme_state.ts
@@ -0,0 +1,16 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+/**
+ * Stores theme related states.
+ */
+export interface ThemeState {
+  darkModeEnabled: boolean;
+}
+
+export function emptyState(): ThemeState {
+  return {
+    darkModeEnabled: false,
+  };
+}
diff --git a/ash/webui/personalization_app/resources/trusted/wallpaper/styles.html b/ash/webui/personalization_app/resources/trusted/wallpaper/styles.html
index 040474e..782b9ddf 100644
--- a/ash/webui/personalization_app/resources/trusted/wallpaper/styles.html
+++ b/ash/webui/personalization_app/resources/trusted/wallpaper/styles.html
@@ -25,17 +25,5 @@
     iframe:focus-within {
       outline: none;
     }
-    cr-button {
-      border-color: var(--cros-button-stroke-color-secondary);
-      border-radius: 16px;
-    }
-    cr-button[aria-pressed=true],
-    cr-button[aria-selected=true] {
-      background-color: var(--cros-highlight-color);
-      border: 0;
-    }
-    cr-button + cr-button {
-      margin-inline-start: 8px;
-    }
   </style>
 </template>
diff --git a/ash/webui/personalization_app/test/fake_personalization_app_theme_provider.cc b/ash/webui/personalization_app/test/fake_personalization_app_theme_provider.cc
new file mode 100644
index 0000000..4f1677f3
--- /dev/null
+++ b/ash/webui/personalization_app/test/fake_personalization_app_theme_provider.cc
@@ -0,0 +1,27 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "ash/webui/personalization_app/test/fake_personalization_app_theme_provider.h"
+
+FakePersonalizationAppThemeProvider::FakePersonalizationAppThemeProvider(
+    content::WebUI* web_ui) {}
+
+FakePersonalizationAppThemeProvider::~FakePersonalizationAppThemeProvider() =
+    default;
+
+void FakePersonalizationAppThemeProvider::BindInterface(
+    mojo::PendingReceiver<ash::personalization_app::mojom::ThemeProvider>
+        receiver) {
+  theme_receiver_.reset();
+  theme_receiver_.Bind(std::move(receiver));
+}
+
+void FakePersonalizationAppThemeProvider::SetThemeObserver(
+    mojo::PendingRemote<ash::personalization_app::mojom::ThemeObserver>
+        observer) {}
+
+void FakePersonalizationAppThemeProvider::SetColorModePref(
+    bool dark_mode_enabled) {
+  return;
+}
diff --git a/ash/webui/personalization_app/test/fake_personalization_app_theme_provider.h b/ash/webui/personalization_app/test/fake_personalization_app_theme_provider.h
new file mode 100644
index 0000000..a918967
--- /dev/null
+++ b/ash/webui/personalization_app/test/fake_personalization_app_theme_provider.h
@@ -0,0 +1,49 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef ASH_WEBUI_PERSONALIZATION_APP_TEST_FAKE_PERSONALIZATION_APP_THEME_PROVIDER_H_
+#define ASH_WEBUI_PERSONALIZATION_APP_TEST_FAKE_PERSONALIZATION_APP_THEME_PROVIDER_H_
+
+#include "ash/webui/personalization_app/personalization_app_theme_provider.h"
+
+#include <stdint.h>
+
+#include "ash/public/cpp/wallpaper/wallpaper_types.h"
+#include "ash/webui/personalization_app/mojom/personalization_app.mojom.h"
+#include "base/unguessable_token.h"
+#include "mojo/public/cpp/bindings/pending_receiver.h"
+#include "mojo/public/cpp/bindings/receiver.h"
+
+namespace content {
+class WebUI;
+}  // namespace content
+
+class FakePersonalizationAppThemeProvider
+    : public ash::PersonalizationAppThemeProvider {
+ public:
+  explicit FakePersonalizationAppThemeProvider(content::WebUI* web_ui);
+
+  FakePersonalizationAppThemeProvider(
+      const FakePersonalizationAppThemeProvider&) = delete;
+  FakePersonalizationAppThemeProvider& operator=(
+      const FakePersonalizationAppThemeProvider&) = delete;
+
+  ~FakePersonalizationAppThemeProvider() override;
+
+  void BindInterface(
+      mojo::PendingReceiver<ash::personalization_app::mojom::ThemeProvider>
+          receiver) override;
+
+  void SetThemeObserver(
+      mojo::PendingRemote<ash::personalization_app::mojom::ThemeObserver>
+          observer) override;
+
+  void SetColorModePref(bool dark_mode_enabled) override;
+
+ private:
+  mojo::Receiver<ash::personalization_app::mojom::ThemeProvider>
+      theme_receiver_{this};
+};
+
+#endif  // ASH_WEBUI_PERSONALIZATION_APP_TEST_FAKE_PERSONALIZATION_APP_THEME_PROVIDER_H_
diff --git a/ash/webui/personalization_app/test/personalization_app_browsertest.js b/ash/webui/personalization_app/test/personalization_app_browsertest.js
index ce609d7..9035c54 100644
--- a/ash/webui/personalization_app/test/personalization_app_browsertest.js
+++ b/ash/webui/personalization_app/test/personalization_app_browsertest.js
@@ -9,6 +9,7 @@
 GEN('#include "ash/webui/personalization_app/test/personalization_app_browsertest_fixture.h"');
 
 GEN('#include "ash/constants/ash_features.h"');
+GEN('#include "chromeos/constants/chromeos_features.h"');
 GEN('#include "content/public/test/browser_test.h"');
 
 const ROOT_PAGE = 'chrome://personalization/';
@@ -24,7 +25,9 @@
   get featureList() {
     return {
       enabled: [
-        'ash::features::kWallpaperWebUI', 'ash::features::kPersonalizationHub'
+        'ash::features::kWallpaperWebUI',
+        'ash::features::kPersonalizationHub',
+        'chromeos::features::kDarkLightMode',
       ]
     };
   }
@@ -62,6 +65,20 @@
   testDone();
 });
 
+TEST_F('PersonalizationAppBrowserTest', 'ShowsThemeButtons', () => {
+  const theme = document.querySelector('personalization-router')
+                    .shadowRoot.querySelector('personalization-main')
+                    .shadowRoot.querySelector('personalization-theme');
+
+  const lightButton = theme.shadowRoot.getElementById('lightMode');
+  assertTrue(!!lightButton);
+  assertEquals(lightButton.getAttribute('aria-pressed'), 'true');
+  const darkButton = theme.shadowRoot.getElementById('darkMode');
+  assertTrue(!!darkButton);
+  assertEquals(darkButton.getAttribute('aria-pressed'), 'false');
+  testDone();
+});
+
 class WallpaperSubpageBrowserTest extends PersonalizationAppBrowserTest {
   /** @override */
   get browsePreload() {
diff --git a/ash/webui/personalization_app/test/personalization_app_browsertest_fixture.cc b/ash/webui/personalization_app/test/personalization_app_browsertest_fixture.cc
index 0f4dbfc..81ff842 100644
--- a/ash/webui/personalization_app/test/personalization_app_browsertest_fixture.cc
+++ b/ash/webui/personalization_app/test/personalization_app_browsertest_fixture.cc
@@ -8,16 +8,19 @@
 
 #include "ash/webui/personalization_app/personalization_app_ui.h"
 #include "ash/webui/personalization_app/personalization_app_url_constants.h"
+#include "ash/webui/personalization_app/test/fake_personalization_app_theme_provider.h"
 #include "ash/webui/personalization_app/test/fake_personalization_app_wallpaper_provider.h"
 #include "chrome/test/base/mojo_web_ui_browser_test.h"
 
 std::unique_ptr<content::WebUIController>
 TestPersonalizationAppWebUIProvider::NewWebUI(content::WebUI* web_ui,
                                               const GURL& url) {
+  auto theme_provider =
+      std::make_unique<FakePersonalizationAppThemeProvider>(web_ui);
   auto wallpaper_provider =
       std::make_unique<FakePersonalizationAppWallpaperProvider>(web_ui);
   return std::make_unique<ash::PersonalizationAppUI>(
-      web_ui, std::move(wallpaper_provider));
+      web_ui, std::move(theme_provider), std::move(wallpaper_provider));
 }
 
 void PersonalizationAppBrowserTestFixture::SetUpOnMainThread() {
diff --git a/ash/wm/desks/templates/desks_templates_item_view.cc b/ash/wm/desks/templates/desks_templates_item_view.cc
index 90eb0d73..ca3c21b 100644
--- a/ash/wm/desks/templates/desks_templates_item_view.cc
+++ b/ash/wm/desks/templates/desks_templates_item_view.cc
@@ -331,8 +331,18 @@
   updated_template->set_template_name(name_view_->GetText());
   OnTemplateNameChanged(updated_template->template_name());
 
-  DesksTemplatesPresenter::Get()->SaveOrUpdateDeskTemplate(
-      /*is_update=*/false, std::move(updated_template));
+  // Calling `SaveOrUpdateDeskTemplate` will trigger rebuilding the desks
+  // templates grid views hierarchy which includes `this`. Use a post task as
+  // some other `ViewObserver`'s may still be using `this`.
+  // TODO(crbug.com/1266552): Remove the post task once saving and updating does
+  // not cause a `this` to be deleted anymore.
+  base::ThreadTaskRunnerHandle::Get()->PostTask(
+      FROM_HERE, base::BindOnce(
+                     [](std::unique_ptr<DeskTemplate> desk_template) {
+                       DesksTemplatesPresenter::Get()->SaveOrUpdateDeskTemplate(
+                           /*is_update=*/false, std::move(desk_template));
+                     },
+                     std::move(updated_template)));
 }
 
 views::Button::KeyClickAction DesksTemplatesItemView::GetKeyClickActionForEvent(
diff --git a/ash/wm/desks/templates/desks_templates_presenter.cc b/ash/wm/desks/templates/desks_templates_presenter.cc
index 1aacb2d..6337eb6 100644
--- a/ash/wm/desks/templates/desks_templates_presenter.cc
+++ b/ash/wm/desks/templates/desks_templates_presenter.cc
@@ -234,6 +234,11 @@
   if (status != desks_storage::DeskModel::GetEntryByUuidStatus::kOk)
     return;
 
+  // `CreateAndActivateNewDeskForTemplate` may destroy `this`. Copy the member
+  // variables to a local to prevent UAF. See https://crbug.com/1284138.
+  base::OnceClosure on_update_ui_closure_for_testing =
+      std::move(on_update_ui_closure_for_testing_);
+
   // Launch the windows as specified in the template to a new desk.
   // Calling `CreateAndActivateNewDeskForTemplate` results in exiting overview
   // mode, which means the presenter doesn't exist anymore on callback (since it
@@ -244,8 +249,8 @@
       template_name,
       base::BindOnce(&OnNewDeskCreatedForTemplate, std::move(entry)));
 
-  if (on_update_ui_closure_for_testing_)
-    std::move(on_update_ui_closure_for_testing_).Run();
+  if (on_update_ui_closure_for_testing)
+    std::move(on_update_ui_closure_for_testing).Run();
 
   RecordLaunchTemplateHistogram();
 }
diff --git a/ash/wm/overview/overview_grid.h b/ash/wm/overview/overview_grid.h
index 1dcdb7ee..f85d611f 100644
--- a/ash/wm/overview/overview_grid.h
+++ b/ash/wm/overview/overview_grid.h
@@ -337,10 +337,6 @@
   // `was_zero_state` is true then we will expand the desks bar.
   void ShowDesksTemplatesGrid(bool was_zero_state);
 
-  // Hides the overview mode items that must be closed for the grid of desks
-  // templates to show.
-  void HideForDesksTemplatesGrid();
-
   // Hides the grid of desks templates and reshow the overview items. Updates
   // the templates button if we are not exiting overview.
   void HideDesksTemplatesGrid(bool exit_overview);
diff --git a/ash/wm/overview/overview_item.cc b/ash/wm/overview/overview_item.cc
index 229fd78..e5cd36bc 100644
--- a/ash/wm/overview/overview_item.cc
+++ b/ash/wm/overview/overview_item.cc
@@ -218,8 +218,8 @@
   DCHECK(item_widget_);
   PerformFadeOutLayer(item_widget_->GetLayer());
 
-  for (aura::Window* transient_child :
-       GetTransientTreeIterator(transform_window_.window())) {
+  for (aura::Window* transient_child : GetTransientTreeIterator(GetWindow())) {
+    transient_child->SetProperty(kForceVisibleInMiniViewKey, true);
     PerformFadeOutLayer(transient_child->layer());
   }
 
diff --git a/base/BUILD.gn b/base/BUILD.gn
index 64ea2b1..250dde1 100644
--- a/base/BUILD.gn
+++ b/base/BUILD.gn
@@ -1394,7 +1394,6 @@
     "//build:branding_buildflags",
     "//build:chromecast_buildflags",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//build/config/compiler:compiler_buildflags",
     "//third_party/modp_b64",
   ]
@@ -2231,6 +2230,7 @@
       "files/file_util_mac.mm",
       "mac/backup_util.h",
       "mac/backup_util.mm",
+      "mac/bridging.h",
       "mac/bundle_locations.h",
       "mac/bundle_locations.mm",
       "mac/call_with_eh_frame.cc",
@@ -3346,7 +3346,6 @@
     "//base/third_party/dynamic_annotations",
     "//build:chromecast_buildflags",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//testing/gmock",
     "//testing/gtest",
     "//third_party/icu",
diff --git a/base/files/file_util_unittest.cc b/base/files/file_util_unittest.cc
index 68117262..0860d64 100644
--- a/base/files/file_util_unittest.cc
+++ b/base/files/file_util_unittest.cc
@@ -46,7 +46,6 @@
 #include "base/time/time.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
-#include "build/os_buildflags.h"
 #include "testing/gtest/include/gtest/gtest.h"
 #include "testing/multiprocess_func_list.h"
 #include "testing/platform_test.h"
diff --git a/base/logging.cc b/base/logging.cc
index b910fd6e..6d9b6cf 100644
--- a/base/logging.cc
+++ b/base/logging.cc
@@ -28,7 +28,6 @@
 #include "base/task/common/task_annotator.h"
 #include "base/trace_event/base_tracing.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 
 #if defined(OS_WIN)
 #include <io.h>
diff --git a/base/logging.h b/base/logging.h
index b6ab61b..5ec3939 100644
--- a/base/logging.h
+++ b/base/logging.h
@@ -20,7 +20,6 @@
 #include "base/strings/string_piece_forward.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
-#include "build/os_buildflags.h"
 
 #if BUILDFLAG(IS_CHROMEOS)
 #include <cstdio>
diff --git a/base/mac/bridging.h b/base/mac/bridging.h
new file mode 100644
index 0000000..49467dd
--- /dev/null
+++ b/base/mac/bridging.h
@@ -0,0 +1,193 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef BASE_MAC_BRIDGING_H_
+#define BASE_MAC_BRIDGING_H_
+
+#include <CoreText/CoreText.h>
+#import <Foundation/Foundation.h>
+
+#include "base/base_export.h"
+#include "base/check.h"
+#include "build/build_config.h"
+
+#if defined(OS_IOS)
+#import <UIKit/UIKit.h>
+#endif
+
+#if defined(OS_MAC)
+#import <AppKit/AppKit.h>
+#endif
+
+#if !defined(__has_feature) || !__has_feature(objc_arc)
+#error "base/mac/bridging.h requires ARC."
+#endif
+
+// These functions convert pointers of bridged CFTypes to NSTypes and
+// vice-versa. They come in two flavors: those that transfer ownership
+// (`OwnershipCast`) and those that just convert the pointer (`PtrCast`).
+//
+// Examples:
+//
+// Ownership transference (as in `CFBridgingRetain`/`Release`):
+//   CFStringRef cf_string = CFStringCreateWithCString(...);
+//   NSString* ns_string = CFToNSOwnershipCast(cf_string);
+//   // At this point, `cf_string` does not need releasing.
+//
+//   NSString* ns_string = [[NSString alloc] initWithString:...];
+//   CFStringRef cf_string = NSToCFOwnershipCast(ns_string);
+//   // At this point, `cf_string` must be released.
+//
+// Pointer conversion (as in `__bridge`):
+//   // `cf_data` is some `CFDataRef` from somewhere.
+//   NSImage* ns_image = [[NSImage alloc] initWithData:CFToNSPtrCast(cf_data)];
+//
+//   // `ns_data` is some `NSData *` from somewhere.
+//   SecKeyRef sec_key = SecKeyCreateFromData(..., NSToCFPtrCast(ns_data), ...);
+//
+// The reason to use these functions (rather than using `__bridge` and
+// `CFBridgingRetain`/`Release`) is because they are type-safe. The OS-provided
+// bridging calls do not type check, while these calls do the appropriate type
+// checking via the magic of macros.
+//
+// Implementation note: Why not templates? Type checking in Core Foundation
+// involves functions named in a specific pattern, and only macro token pasting
+// works for this purpose.
+
+#define CF_TO_NS_CAST_IMPL(TypeCF, TypeNS)                                  \
+  namespace base::mac {                                                     \
+  inline BASE_EXPORT TypeNS* _Nullable CFToNSOwnershipCast(                 \
+      TypeCF##Ref CF_CONSUMED _Nullable cf_val) {                           \
+    DCHECK(!cf_val || TypeCF##GetTypeID() == CFGetTypeID(cf_val));          \
+    return (__bridge_transfer TypeNS*)cf_val;                               \
+  }                                                                         \
+  inline BASE_EXPORT CF_RETURNS_RETAINED                                    \
+      TypeCF##Ref _Nullable NSToCFOwnershipCast(TypeNS* _Nullable ns_val) { \
+    TypeCF##Ref cf_val = (__bridge_retained TypeCF##Ref)ns_val;             \
+    DCHECK(!cf_val || TypeCF##GetTypeID() == CFGetTypeID(cf_val));          \
+    return cf_val;                                                          \
+  }                                                                         \
+  inline BASE_EXPORT TypeNS* _Nullable CFToNSPtrCast(                       \
+      TypeCF##Ref _Nullable cf_val) {                                       \
+    DCHECK(!cf_val || TypeCF##GetTypeID() == CFGetTypeID(cf_val));          \
+    return (__bridge TypeNS*)cf_val;                                        \
+  }                                                                         \
+  inline BASE_EXPORT TypeCF##Ref _Nullable NSToCFPtrCast(                   \
+      TypeNS* _Nullable ns_val) {                                           \
+    TypeCF##Ref cf_val = (__bridge TypeCF##Ref)ns_val;                      \
+    DCHECK(!cf_val || TypeCF##GetTypeID() == CFGetTypeID(cf_val));          \
+    return cf_val;                                                          \
+  }                                                                         \
+  }
+
+#define CF_TO_NS_MUTABLE_CAST_IMPL(name)                                 \
+  CF_TO_NS_CAST_IMPL(CF##name, NS##name)                                 \
+  namespace base::mac {                                                  \
+  inline BASE_EXPORT NSMutable##name* _Nullable CFToNSOwnershipCast(     \
+      CFMutable##name##Ref CF_CONSUMED _Nullable cf_val) {               \
+    DCHECK(!cf_val || CF##name##GetTypeID() == CFGetTypeID(cf_val));     \
+    return (__bridge_transfer NSMutable##name*)cf_val;                   \
+  }                                                                      \
+  inline BASE_EXPORT CF_RETURNS_RETAINED                                 \
+      CFMutable##name##Ref _Nullable NSToCFOwnershipCast(                \
+          NSMutable##name* _Nullable ns_val) {                           \
+    CFMutable##name##Ref cf_val =                                        \
+        (__bridge_retained CFMutable##name##Ref)ns_val;                  \
+    DCHECK(!cf_val || CF##name##GetTypeID() == CFGetTypeID(cf_val));     \
+    return cf_val;                                                       \
+  }                                                                      \
+  inline BASE_EXPORT NSMutable##name* _Nullable CFToNSPtrCast(           \
+      CFMutable##name##Ref _Nullable cf_val) {                           \
+    DCHECK(!cf_val || CF##name##GetTypeID() == CFGetTypeID(cf_val));     \
+    return (__bridge NSMutable##name*)cf_val;                            \
+  }                                                                      \
+  inline BASE_EXPORT CFMutable##name##Ref _Nullable NSToCFPtrCast(       \
+      NSMutable##name* _Nullable ns_val) {                               \
+    CFMutable##name##Ref cf_val = (__bridge CFMutable##name##Ref)ns_val; \
+    DCHECK(!cf_val || CF##name##GetTypeID() == CFGetTypeID(cf_val));     \
+    return cf_val;                                                       \
+  }                                                                      \
+  }
+
+// List of toll-free bridged types taken from:
+// https://web.archive.org/web/20111124025525/http://www.cocoadev.com/index.pl?TollFreeBridged
+// https://developer.apple.com/library/archive/documentation/CoreFoundation/Conceptual/CFDesignConcepts/Articles/tollFreeBridgedTypes.html#//apple_ref/doc/uid/TP40010677-SW4
+
+// Foundation
+CF_TO_NS_MUTABLE_CAST_IMPL(Array)
+CF_TO_NS_MUTABLE_CAST_IMPL(AttributedString)
+CF_TO_NS_CAST_IMPL(CFCalendar, NSCalendar)
+CF_TO_NS_MUTABLE_CAST_IMPL(CharacterSet)
+CF_TO_NS_MUTABLE_CAST_IMPL(Data)
+CF_TO_NS_CAST_IMPL(CFDate, NSDate)
+CF_TO_NS_MUTABLE_CAST_IMPL(Dictionary)
+CF_TO_NS_CAST_IMPL(CFError, NSError)
+CF_TO_NS_CAST_IMPL(CFLocale, NSLocale)
+CF_TO_NS_CAST_IMPL(CFNumber, NSNumber)
+CF_TO_NS_CAST_IMPL(CFRunLoopTimer, NSTimer)
+CF_TO_NS_CAST_IMPL(CFTimeZone, NSTimeZone)
+CF_TO_NS_MUTABLE_CAST_IMPL(Set)
+CF_TO_NS_CAST_IMPL(CFReadStream, NSInputStream)
+CF_TO_NS_CAST_IMPL(CFWriteStream, NSOutputStream)
+CF_TO_NS_MUTABLE_CAST_IMPL(String)
+CF_TO_NS_CAST_IMPL(CFURL, NSURL)
+
+// AppKit / UIKit
+#if defined(OS_IOS)
+CF_TO_NS_CAST_IMPL(CTFont, UIFont)
+#else
+// The NSFont/CTFont toll-free bridging is broken before 10.15.
+// http://www.openradar.me/15341349 rdar://15341349
+//
+// TODO(https://crbug.com/1076527): This is fixed in 10.15. When 10.15 is the
+// minimum OS for Chromium, remove this specialization and replace it with just:
+//
+// CF_TO_NS_CAST_IMPL(CTFont, NSFont)
+
+extern "C" {
+Boolean _CFIsObjC(CFTypeID typeID, CFTypeRef obj);
+}  // extern "C"
+
+namespace base::mac {
+
+inline BASE_EXPORT NSFont* _Nullable CFToNSOwnershipCast(
+    CTFontRef CF_CONSUMED _Nullable cf_val) {
+  NSFont* ns_val = (__bridge_transfer NSFont*)cf_val;
+  DCHECK(!cf_val || CTFontGetTypeID() == CFGetTypeID(cf_val) ||
+         (_CFIsObjC(CTFontGetTypeID(), cf_val) &&
+          [ns_val isKindOfClass:[NSFont class]]));
+  return ns_val;
+}
+
+inline BASE_EXPORT CF_RETURNS_RETAINED _Nullable CTFontRef NSToCFOwnershipCast(
+    NSFont* _Nullable ns_val) {
+  CTFontRef cf_val = (__bridge_retained CTFontRef)ns_val;
+  DCHECK(!cf_val || CTFontGetTypeID() == CFGetTypeID(cf_val) ||
+         [ns_val isKindOfClass:[NSFont class]]);
+  return cf_val;
+}
+
+inline BASE_EXPORT _Nullable NSFont* CFToNSPtrCast(CTFontRef _Nullable cf_val) {
+  NSFont* ns_val = (__bridge NSFont*)cf_val;
+  DCHECK(!cf_val || CTFontGetTypeID() == CFGetTypeID(cf_val) ||
+         (_CFIsObjC(CTFontGetTypeID(), cf_val) &&
+          [ns_val isKindOfClass:[NSFont class]]));
+  return ns_val;
+}
+
+inline BASE_EXPORT _Nullable CTFontRef NSToCFPtrCast(NSFont* _Nullable ns_val) {
+  CTFontRef cf_val = (__bridge CTFontRef)ns_val;
+  DCHECK(!cf_val || CTFontGetTypeID() == CFGetTypeID(cf_val) ||
+         [ns_val isKindOfClass:[NSFont class]]);
+  return cf_val;
+}
+
+}  // namespace base::mac
+
+#endif
+
+#undef CF_TO_NS_CAST_IMPL
+#undef CF_TO_NS_MUTABLE_CAST_IMPL
+
+#endif  // BASE_MAC_BRIDGING_H_
diff --git a/base/mac/foundation_util.h b/base/mac/foundation_util.h
index 28f1d7a..f20ec23 100644
--- a/base/mac/foundation_util.h
+++ b/base/mac/foundation_util.h
@@ -153,6 +153,10 @@
 
 }  // namespace base::mac
 
+// These casting functions cannot be implemented in a way that will work with
+// ARC. Use the casting functions in base/mac/bridging.h instead.
+#if !defined(__has_feature) || !__has_feature(objc_arc)
+
 #if !defined(__OBJC__)
 #define OBJC_CPP_CLASS_DECL(x) class x;
 #else  // __OBJC__
@@ -224,6 +228,8 @@
 #undef CF_TO_NS_MUTABLE_CAST_DECL
 #undef OBJC_CPP_CLASS_DECL
 
+#endif  // !defined(__has_feature) || !__has_feature(objc_arc)
+
 namespace base::mac {
 
 // CFCast<>() and CFCastStrict<>() cast a basic CFTypeRef to a more
diff --git a/base/process/process_util_unittest.cc b/base/process/process_util_unittest.cc
index c4abf41..dfc69405 100644
--- a/base/process/process_util_unittest.cc
+++ b/base/process/process_util_unittest.cc
@@ -36,7 +36,6 @@
 #include "base/threading/simple_thread.h"
 #include "base/threading/thread.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "testing/gtest/include/gtest/gtest.h"
 #include "testing/multiprocess_func_list.h"
 
diff --git a/base/task/thread_pool/task_tracker.cc b/base/task/thread_pool/task_tracker.cc
index 6ec32c84..56aa70c 100644
--- a/base/task/thread_pool/task_tracker.cc
+++ b/base/task/thread_pool/task_tracker.cc
@@ -446,7 +446,8 @@
 }
 
 RegisteredTaskSource TaskTracker::RunAndPopNextTask(
-    RegisteredTaskSource task_source) {
+    RegisteredTaskSource task_source,
+    base::Location* posted_from) {
   DCHECK(task_source);
 
   const bool should_run_tasks = BeforeRunTask(task_source->shutdown_behavior());
@@ -462,6 +463,8 @@
   }
 
   if (task) {
+    if (posted_from)
+      *posted_from = task->posted_from;
     // Run the |task| (whether it's a worker task or the Clear() closure).
     RunTask(std::move(task.value()), task_source.get(), traits);
   }
diff --git a/base/task/thread_pool/task_tracker.h b/base/task/thread_pool/task_tracker.h
index b2c68855..1db4ef6 100644
--- a/base/task/thread_pool/task_tracker.h
+++ b/base/task/thread_pool/task_tracker.h
@@ -118,7 +118,11 @@
   // (which indicates that it should be reenqueued). WillPostTask() must have
   // allowed the task in front of |task_source| to be posted before this is
   // called.
-  RegisteredTaskSource RunAndPopNextTask(RegisteredTaskSource task_source);
+  // |posted_from| is optionally used to capture base::Location of the task ran
+  // for investigation of memory corruption.
+  // TODO(crbug.com/1218384): Remove |posted_from| once resolved.
+  RegisteredTaskSource RunAndPopNextTask(RegisteredTaskSource task_source,
+                                         base::Location* posted_from = nullptr);
 
   // Returns true once shutdown has started (StartShutdown() was called).
   // Note: sequential consistency with the thread calling StartShutdown() isn't
diff --git a/base/task/thread_pool/worker_thread.cc b/base/task/thread_pool/worker_thread.cc
index 4ebe5426..3bd4944e 100644
--- a/base/task/thread_pool/worker_thread.cc
+++ b/base/task/thread_pool/worker_thread.cc
@@ -375,12 +375,15 @@
     // Alias pointer for investigation of memory corruption. crbug.com/1218384
     TaskSource* task_source_before_run = task_source.get();
     base::debug::Alias(&task_source_before_run);
+    base::Location posted_from;
+    task_source =
+        task_tracker_->RunAndPopNextTask(std::move(task_source), &posted_from);
 
-    task_source = task_tracker_->RunAndPopNextTask(std::move(task_source));
-
-    // Alias pointer for investigation of memory corruption. crbug.com/1218384
+    // Alias pointer and posted_from for investigation of memory corruption.
+    // crbug.com/1218384
     TaskSource* task_source_before_move = task_source.get();
     base::debug::Alias(&task_source_before_move);
+    DEBUG_ALIAS_FOR_CSTR(posted_from_str, posted_from.ToString().c_str(), 128);
 
     delegate_->DidProcessTask(std::move(task_source));
 
diff --git a/base/test/BUILD.gn b/base/test/BUILD.gn
index f626b80f..372dc70 100644
--- a/base/test/BUILD.gn
+++ b/base/test/BUILD.gn
@@ -163,7 +163,6 @@
   deps = [
     "//base/third_party/dynamic_annotations",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//third_party/icu:icuuc",
     "//third_party/libxml:libxml_utils",
     "//third_party/libxml:xml_reader",
diff --git a/base/test/perf_test_suite.cc b/base/test/perf_test_suite.cc
index 15c3ae2..63c6f41 100644
--- a/base/test/perf_test_suite.cc
+++ b/base/test/perf_test_suite.cc
@@ -11,7 +11,7 @@
 #include "base/process/launch.h"
 #include "base/strings/string_util.h"
 #include "base/test/perf_log.h"
-#include "build/os_buildflags.h"
+#include "build/build_config.h"
 #include "testing/gtest/include/gtest/gtest.h"
 
 #if BUILDFLAG(IS_FUCHSIA)
diff --git a/base/test/test_suite.cc b/base/test/test_suite.cc
index 62b14d0..94b9f289 100644
--- a/base/test/test_suite.cc
+++ b/base/test/test_suite.cc
@@ -46,7 +46,6 @@
 #include "base/time/time.h"
 #include "base/tracing_buildflags.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "testing/gmock/include/gmock/gmock.h"
 #include "testing/gtest/include/gtest/gtest.h"
 #include "testing/multiprocess_func_list.h"
diff --git a/base/tracing/protos/chrome_track_event.proto b/base/tracing/protos/chrome_track_event.proto
index d856269..1102a59 100644
--- a/base/tracing/protos/chrome_track_event.proto
+++ b/base/tracing/protos/chrome_track_event.proto
@@ -615,6 +615,39 @@
   optional FrameType frame_type = 4;
 }
 
+message EventLatency {
+  enum EventType {
+    MOUSE_PRESSED = 1;
+    MOUSE_RELEASED = 2;
+    MOUSE_WHEEL = 3;
+    KEY_PRESSED = 4;
+    KEY_RELEASED = 5;
+    TOUCH_PRESSED = 6;
+    TOUCH_RELEASED = 7;
+    TOUCH_MOVED = 8;
+    GESTURE_SCROLL_BEGIN = 9;
+    GESTURE_SCROLL_UPDATE = 10;
+    GESTURE_SCROLL_END = 11;
+    GESTURE_DOUBLE_TAP = 12;
+    GESTURE_LONG_PRESS = 13;
+    GESTURE_LONG_TAP = 14;
+    GESTURE_SHOW_PRESS = 15;
+    GESTURE_TAP = 16;
+    GESTURE_TAP_CANCEL = 17;
+    GESTURE_TAP_DOWN = 18;
+    GESTURE_TAP_UNCONFIRMED = 19;
+    GESTURE_TWO_FINGER_TAP = 20;
+    FIRST_GESTURE_SCROLL_UPDATE = 21;
+    MOUSE_DRAGGED = 22;
+    GESTURE_PINCH_BEGIN = 23;
+    GESTURE_PINCH_END = 24;
+    GESTURE_PINCH_UPDATE = 25;
+    INERTIAL_GESTURE_SCROLL_UPDATE = 26;
+  }
+
+  optional EventType event_type = 1;
+}
+
 message ChromeTrackEvent {
   // Extension range for Chrome: 1000-1999
   // Next ID: 1032
@@ -687,5 +720,7 @@
 
     optional RendererMainThreadTaskExecution
         renderer_main_thread_task_execution = 1031;
+
+    optional EventLatency event_latency = 1032;
   }
 }
diff --git a/build/BUILD.gn b/build/BUILD.gn
index d18e914..93759ef 100644
--- a/build/BUILD.gn
+++ b/build/BUILD.gn
@@ -45,19 +45,3 @@
     "IS_CHROMEOS_WITH_HW_DETAILS=$is_chromeos_with_hw_details",
   ]
 }
-
-buildflag_header("os_buildflags") {
-  header = "os_buildflags.h"
-  flags = [
-    "IS_ANDROID=$is_android",
-    "IS_CHROMEOS=$is_chromeos",
-    "IS_FUCHSIA=$is_fuchsia",
-    "IS_IOS=$is_ios",
-    "IS_LINUX=$is_linux",
-    "IS_MAC=$is_mac",
-    "IS_NACL=$is_nacl",
-    "IS_WIN=$is_win",
-    "IS_APPLE=$is_apple",
-    "IS_POSIX=$is_posix",
-  ]
-}
diff --git a/build/android/gyp/compile_java.py b/build/android/gyp/compile_java.py
index cbce3a4..842ca18 100755
--- a/build/android/gyp/compile_java.py
+++ b/build/android/gyp/compile_java.py
@@ -482,7 +482,7 @@
 
       if enable_partial_javac:
         all_changed_paths_are_java = all(
-            [p.endswith(".java") for p in changes.IterChangedPaths()])
+            p.endswith(".java") for p in changes.IterChangedPaths())
         if (all_changed_paths_are_java and not changes.HasStringChanges()
             and os.path.exists(jar_path)
             and (jar_info_path is None or os.path.exists(jar_info_path))):
diff --git a/build/android/gyp/java_cpp_enum.py b/build/android/gyp/java_cpp_enum.py
index 62f1162a..ca89abce 100755
--- a/build/android/gyp/java_cpp_enum.py
+++ b/build/android/gyp/java_cpp_enum.py
@@ -96,7 +96,7 @@
                   'k' + self.original_enum_name]
 
       for prefix in prefixes:
-        if all([w.startswith(prefix) for w in self.entries.keys()]):
+        if all(w.startswith(prefix) for w in self.entries.keys()):
           prefix_to_strip = prefix
           break
       else:
diff --git a/build/android/gyp/java_google_api_keys.py b/build/android/gyp/java_google_api_keys.py
index 9a75f038..d2bd34f 100755
--- a/build/android/gyp/java_google_api_keys.py
+++ b/build/android/gyp/java_google_api_keys.py
@@ -95,8 +95,6 @@
 
   values = {}
   values['GOOGLE_API_KEY'] = google_api_keys.GetAPIKey()
-  values['GOOGLE_API_KEY_PHYSICAL_WEB_TEST'] = (
-      google_api_keys.GetAPIKeyAndroidNonStable())
   values['GOOGLE_API_KEY_ANDROID_NON_STABLE'] = (
       google_api_keys.GetAPIKeyAndroidNonStable())
   values['GOOGLE_CLIENT_ID_MAIN'] = google_api_keys.GetClientID('MAIN')
diff --git a/build/build_config.h b/build/build_config.h
index 48edcf4bd..1b25276 100644
--- a/build/build_config.h
+++ b/build/build_config.h
@@ -2,19 +2,29 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-// This file adds defines about the platform we're currently building on.
+// This file doesn't belong to any GN target by design for faster build and
+// less developer overhead.
+
+// This file adds build flags about the OS we're currently building on. They are
+// defined directly in this file instead of via a `buildflag_header` target in a
+// GN file for faster build. They are defined using the corresponding OS defines
+// (e.g. OS_WIN) which are also defined in this file (except for OS_CHROMEOS,
+// which is set by the build system). These defines are deprecated and should
+// NOT be used directly. For example:
+//    Please Use: #if BUILDFLAG(IS_WIN)
+//    Deprecated: #if defined(OS_WIN)
 //
 //  Operating System:
-//    OS_AIX / OS_ANDROID / OS_ASMJS / OS_FREEBSD / OS_FUCHSIA / OS_IOS /
-//    OS_LINUX / OS_MAC / OS_NACL / OS_NETBSD / OS_OPENBSD /
-//    OS_QNX / OS_SOLARIS / OS_WIN
+//    IS_AIX / IS_ANDROID / IS_ASMJS / IS_FREEBSD / IS_FUCHSIA / IS_IOS /
+//    IS_LINUX / IS_MAC / IS_NACL / IS_NETBSD / IS_OPENBSD /
+//    IS_QNX / IS_SOLARIS / IS_WIN
 //  Operating System family:
-//    OS_APPLE: IOS or MAC
-//    OS_BSD: FREEBSD or NETBSD or OPENBSD
-//    OS_POSIX: AIX or ANDROID or ASMJS or CHROMEOS or FREEBSD or IOS or LINUX
+//    IS_APPLE: IOS or MAC
+//    IS_BSD: FREEBSD or NETBSD or OPENBSD
+//    IS_POSIX: AIX or ANDROID or ASMJS or CHROMEOS or FREEBSD or IOS or LINUX
 //              or MAC or NACL or NETBSD or OPENBSD or QNX or SOLARIS
-//
-//  /!\ Note: OS_CHROMEOS is set by the build system, not this file
+
+// This file also adds defines specific to the platform, architecture etc.
 //
 //  Compiler:
 //    COMPILER_MSVC / COMPILER_GCC
@@ -36,6 +46,8 @@
 #ifndef BUILD_BUILD_CONFIG_H_
 #define BUILD_BUILD_CONFIG_H_
 
+#include "build/buildflag.h"
+
 // A set of macros to use for platform detection.
 #if defined(__native_client__)
 // __native_client__ must be first, so that other OS_ defines are not set.
@@ -111,6 +123,115 @@
 #define OS_POSIX 1
 #endif
 
+// OS build flags
+#if defined(OS_AIX)
+#define BUILDFLAG_INTERNAL_IS_AIX() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_AIX() (0)
+#endif
+
+#if defined(OS_ANDROID)
+#define BUILDFLAG_INTERNAL_IS_ANDROID() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_ANDROID() (0)
+#endif
+
+#if defined(OS_APPLE)
+#define BUILDFLAG_INTERNAL_IS_APPLE() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_APPLE() (0)
+#endif
+
+#if defined(OS_ASMJS)
+#define BUILDFLAG_INTERNAL_IS_ASMJS() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_ASMJS() (0)
+#endif
+
+#if defined(OS_BSD)
+#define BUILDFLAG_INTERNAL_IS_BSD() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_BSD() (0)
+#endif
+
+#if defined(OS_CHROMEOS)
+#define BUILDFLAG_INTERNAL_IS_CHROMEOS() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_CHROMEOS() (0)
+#endif
+
+#if defined(OS_FREEBSD)
+#define BUILDFLAG_INTERNAL_IS_FREEBSD() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_FREEBSD() (0)
+#endif
+
+#if defined(OS_FUCHSIA)
+#define BUILDFLAG_INTERNAL_IS_FUCHSIA() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_FUCHSIA() (0)
+#endif
+
+#if defined(OS_IOS)
+#define BUILDFLAG_INTERNAL_IS_IOS() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_IOS() (0)
+#endif
+
+#if defined(OS_LINUX)
+#define BUILDFLAG_INTERNAL_IS_LINUX() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_LINUX() (0)
+#endif
+
+#if defined(OS_MAC)
+#define BUILDFLAG_INTERNAL_IS_MAC() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_MAC() (0)
+#endif
+
+#if defined(OS_NACL)
+#define BUILDFLAG_INTERNAL_IS_NACL() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_NACL() (0)
+#endif
+
+#if defined(OS_NETBSD)
+#define BUILDFLAG_INTERNAL_IS_NETBSD() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_NETBSD() (0)
+#endif
+
+#if defined(OS_OPENBSD)
+#define BUILDFLAG_INTERNAL_IS_OPENBSD() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_OPENBSD() (0)
+#endif
+
+#if defined(OS_POSIX)
+#define BUILDFLAG_INTERNAL_IS_POSIX() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_POSIX() (0)
+#endif
+
+#if defined(OS_QNX)
+#define BUILDFLAG_INTERNAL_IS_QNX() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_QNX() (0)
+#endif
+
+#if defined(OS_SOLARIS)
+#define BUILDFLAG_INTERNAL_IS_SOLARIS() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_SOLARIS() (0)
+#endif
+
+#if defined(OS_WIN)
+#define BUILDFLAG_INTERNAL_IS_WIN() (1)
+#else
+#define BUILDFLAG_INTERNAL_IS_WIN() (0)
+#endif
+
 // Compiler detection. Note: clang masquerades as GCC on POSIX and as MSVC on
 // Windows.
 #if defined(__GNUC__)
diff --git a/build/fuchsia/linux.sdk.sha1 b/build/fuchsia/linux.sdk.sha1
index e360093..59be4ea 100644
--- a/build/fuchsia/linux.sdk.sha1
+++ b/build/fuchsia/linux.sdk.sha1
@@ -1 +1 @@
-7.20220107.1.1
+7.20220107.2.5
diff --git a/build/fuchsia/linux_internal.sdk.sha1 b/build/fuchsia/linux_internal.sdk.sha1
index e360093..8a9206c 100644
--- a/build/fuchsia/linux_internal.sdk.sha1
+++ b/build/fuchsia/linux_internal.sdk.sha1
@@ -1 +1 @@
-7.20220107.1.1
+7.20220107.2.4
diff --git a/build/fuchsia/mac.sdk.sha1 b/build/fuchsia/mac.sdk.sha1
index e360093..59be4ea 100644
--- a/build/fuchsia/mac.sdk.sha1
+++ b/build/fuchsia/mac.sdk.sha1
@@ -1 +1 @@
-7.20220107.1.1
+7.20220107.2.5
diff --git a/cc/layers/render_surface_impl.cc b/cc/layers/render_surface_impl.cc
index 4a99f99..b3b5794 100644
--- a/cc/layers/render_surface_impl.cc
+++ b/cc/layers/render_surface_impl.cc
@@ -170,7 +170,8 @@
 
 bool RenderSurfaceImpl::CopyOfOutputRequired() const {
   return HasCopyRequest() || ShouldCacheRenderSurface() ||
-         SubtreeCaptureId().is_valid();
+         SubtreeCaptureId().is_valid() ||
+         OwningEffectNode()->shared_element_resource_id.IsValid();
 }
 
 int RenderSurfaceImpl::TransformTreeIndex() const {
diff --git a/cc/metrics/compositor_frame_reporter.cc b/cc/metrics/compositor_frame_reporter.cc
index 19d10a8d..678364c 100644
--- a/cc/metrics/compositor_frame_reporter.cc
+++ b/cc/metrics/compositor_frame_reporter.cc
@@ -348,6 +348,41 @@
   return args.frame_time + (args.interval * 1.5);
 }
 
+perfetto::protos::pbzero::EventLatency::EventType ToProtoEnum(
+    EventMetrics::EventType event_type) {
+#define CASE(event_type, proto_event_type)  \
+  case EventMetrics::EventType::event_type: \
+    return perfetto::protos::pbzero::EventLatency::proto_event_type
+  switch (event_type) {
+    CASE(kMousePressed, MOUSE_PRESSED);
+    CASE(kMouseReleased, MOUSE_RELEASED);
+    CASE(kMouseWheel, MOUSE_WHEEL);
+    CASE(kKeyPressed, KEY_PRESSED);
+    CASE(kKeyReleased, KEY_RELEASED);
+    CASE(kTouchPressed, TOUCH_PRESSED);
+    CASE(kTouchReleased, TOUCH_RELEASED);
+    CASE(kTouchMoved, TOUCH_MOVED);
+    CASE(kGestureScrollBegin, GESTURE_SCROLL_BEGIN);
+    CASE(kGestureScrollUpdate, GESTURE_SCROLL_UPDATE);
+    CASE(kGestureScrollEnd, GESTURE_SCROLL_END);
+    CASE(kGestureDoubleTap, GESTURE_DOUBLE_TAP);
+    CASE(kGestureLongPress, GESTURE_LONG_PRESS);
+    CASE(kGestureLongTap, GESTURE_LONG_TAP);
+    CASE(kGestureShowPress, GESTURE_SHOW_PRESS);
+    CASE(kGestureTap, GESTURE_TAP);
+    CASE(kGestureTapCancel, GESTURE_TAP_CANCEL);
+    CASE(kGestureTapDown, GESTURE_TAP_DOWN);
+    CASE(kGestureTapUnconfirmed, GESTURE_TAP_UNCONFIRMED);
+    CASE(kGestureTwoFingerTap, GESTURE_TWO_FINGER_TAP);
+    CASE(kFirstGestureScrollUpdate, FIRST_GESTURE_SCROLL_UPDATE);
+    CASE(kMouseDragged, MOUSE_DRAGGED);
+    CASE(kGesturePinchBegin, GESTURE_PINCH_BEGIN);
+    CASE(kGesturePinchEnd, GESTURE_PINCH_END);
+    CASE(kGesturePinchUpdate, GESTURE_PINCH_UPDATE);
+    CASE(kInertialGestureScrollUpdate, INERTIAL_GESTURE_SCROLL_UPDATE);
+  }
+}
+
 }  // namespace
 
 // CompositorFrameReporter::ProcessedBlinkBreakdown::Iterator ==================
@@ -1206,10 +1241,16 @@
         event_metrics->GetDispatchStageTimestamp(
             EventMetrics::DispatchStage::kGenerated);
 
-    const auto trace_id = TRACE_ID_LOCAL(event_metrics.get());
-    TRACE_EVENT_NESTABLE_ASYNC_BEGIN_WITH_TIMESTAMP1(
-        kTraceEventCategory, "EventLatency", trace_id, generated_timestamp,
-        "event", event_metrics->GetTypeName());
+    const auto trace_track =
+        perfetto::Track(base::trace_event::GetNextGlobalTraceId());
+    TRACE_EVENT_BEGIN(
+        kTraceEventCategory, "EventLatency", trace_track, generated_timestamp,
+        [&](perfetto::EventContext context) {
+          auto* event =
+              context.event<perfetto::protos::pbzero::ChromeTrackEvent>();
+          auto* event_latency = event->set_event_latency();
+          event_latency->set_event_type(ToProtoEnum(event_metrics->type()));
+        });
 
     // Event dispatch stages.
     EventMetrics::DispatchStage dispatch_stage =
@@ -1235,10 +1276,10 @@
 
       const char* breakdown_name =
           GetEventLatencyDispatchBreakdownName(dispatch_stage, end_stage);
-      TRACE_EVENT_NESTABLE_ASYNC_BEGIN_WITH_TIMESTAMP0(
-          kTraceEventCategory, breakdown_name, trace_id, dispatch_timestamp);
-      TRACE_EVENT_NESTABLE_ASYNC_END_WITH_TIMESTAMP0(
-          kTraceEventCategory, breakdown_name, trace_id, end_timestamp);
+      TRACE_EVENT_BEGIN(kTraceEventCategory,
+                        perfetto::StaticString{breakdown_name}, trace_track,
+                        dispatch_timestamp);
+      TRACE_EVENT_END(kTraceEventCategory, trace_track, end_timestamp);
 
       dispatch_stage = end_stage;
       dispatch_timestamp = end_timestamp;
@@ -1267,11 +1308,10 @@
     const char* d2c_breakdown_name =
         GetEventLatencyDispatchToCompositorBreakdownName(dispatch_stage,
                                                          stage_it->stage_type);
-    TRACE_EVENT_NESTABLE_ASYNC_BEGIN_WITH_TIMESTAMP0(
-        kTraceEventCategory, d2c_breakdown_name, trace_id, dispatch_timestamp);
-    TRACE_EVENT_NESTABLE_ASYNC_END_WITH_TIMESTAMP0(kTraceEventCategory,
-                                                   d2c_breakdown_name, trace_id,
-                                                   stage_it->start_time);
+    TRACE_EVENT_BEGIN(kTraceEventCategory,
+                      perfetto::StaticString{d2c_breakdown_name}, trace_track,
+                      dispatch_timestamp);
+    TRACE_EVENT_END(kTraceEventCategory, trace_track, stage_it->start_time);
 
     // Compositor stages.
     for (; stage_it != stage_history_.end(); ++stage_it) {
@@ -1285,8 +1325,8 @@
         continue;
       const char* stage_name = GetStageName(stage_type_index);
 
-      TRACE_EVENT_NESTABLE_ASYNC_BEGIN_WITH_TIMESTAMP0(
-          kTraceEventCategory, stage_name, trace_id, stage_it->start_time);
+      TRACE_EVENT_BEGIN(kTraceEventCategory, perfetto::StaticString{stage_name},
+                        trace_track, stage_it->start_time);
 
       if (stage_it->stage_type ==
           StageType::kSubmitCompositorFrameToPresentationCompositorFrame) {
@@ -1298,18 +1338,16 @@
           if (start_time >= end_time)
             continue;
           const char* breakdown_name = GetVizBreakdownName(it.GetBreakdown());
-          TRACE_EVENT_NESTABLE_ASYNC_BEGIN_WITH_TIMESTAMP0(
-              kTraceEventCategory, breakdown_name, trace_id, start_time);
-          TRACE_EVENT_NESTABLE_ASYNC_END_WITH_TIMESTAMP0(
-              kTraceEventCategory, breakdown_name, trace_id, end_time);
+          TRACE_EVENT_BEGIN(kTraceEventCategory,
+                            perfetto::StaticString{breakdown_name}, trace_track,
+                            start_time);
+          TRACE_EVENT_END(kTraceEventCategory, trace_track, end_time);
         }
       }
 
-      TRACE_EVENT_NESTABLE_ASYNC_END_WITH_TIMESTAMP0(
-          kTraceEventCategory, stage_name, trace_id, stage_it->end_time);
+      TRACE_EVENT_END(kTraceEventCategory, trace_track, stage_it->end_time);
     }
-    TRACE_EVENT_NESTABLE_ASYNC_END_WITH_TIMESTAMP0(
-        kTraceEventCategory, "EventLatency", trace_id, frame_termination_time_);
+    TRACE_EVENT_END(kTraceEventCategory, trace_track, frame_termination_time_);
   }
 }
 
diff --git a/cc/trees/layer_tree_host_impl.cc b/cc/trees/layer_tree_host_impl.cc
index de7dba8..814e6fab 100644
--- a/cc/trees/layer_tree_host_impl.cc
+++ b/cc/trees/layer_tree_host_impl.cc
@@ -1262,14 +1262,12 @@
     const size_t surface_index = render_surface_list_size - 1 - i;
     RenderSurfaceImpl* render_surface =
         (*frame->render_surface_list)[surface_index];
-    const auto& shared_element_id =
-        render_surface->GetDocumentTransitionSharedElementId();
 
     const bool is_root_surface =
         render_surface->EffectTreeIndex() == EffectTree::kContentsRootNodeId;
     const bool should_draw_into_render_pass =
         is_root_surface || render_surface->contributes_to_drawn_surface() ||
-        render_surface->CopyOfOutputRequired() || shared_element_id.valid();
+        render_surface->CopyOfOutputRequired();
     if (should_draw_into_render_pass)
       frame->render_passes.push_back(render_surface->CreateRenderPass());
   }
diff --git a/chrome/VERSION b/chrome/VERSION
index 29b6fb8..7a6bf14 100644
--- a/chrome/VERSION
+++ b/chrome/VERSION
@@ -1,4 +1,4 @@
 MAJOR=99
 MINOR=0
-BUILD=4813
+BUILD=4814
 PATCH=0
diff --git a/chrome/android/BUILD.gn b/chrome/android/BUILD.gn
index ebec747..3a126ad7 100644
--- a/chrome/android/BUILD.gn
+++ b/chrome/android/BUILD.gn
@@ -1389,6 +1389,7 @@
     "//chrome/browser/signin/services/android:javatests",
     "//chrome/browser/sync/android:java",
     "//chrome/browser/sync/test/android:test_support_java",
+    "//chrome/browser/tab:critical_persisted_tab_data_flatbuffer_java",
     "//chrome/browser/tab:critical_persisted_tab_data_proto_java",
     "//chrome/browser/tab:java",
     "//chrome/browser/tab_group:java",
diff --git a/chrome/android/chrome_java_resources.gni b/chrome/android/chrome_java_resources.gni
index 1824e362..2eeaac5 100644
--- a/chrome/android/chrome_java_resources.gni
+++ b/chrome/android/chrome_java_resources.gni
@@ -547,8 +547,6 @@
   "java/res/drawable/signin_header_animation.xml",
   "java/res/drawable/store_locally_tooltip_background.xml",
   "java/res/drawable/tab_indicator.xml",
-  "java/res/drawable/thumbnail_gradient_top_left.xml",
-  "java/res/drawable/thumbnail_gradient_top_right.xml",
   "java/res/drawable/tile_view_hairline_border_background.xml",
   "java/res/drawable/toolbar_shadow.xml",
   "java/res/drawable/visa_card.xml",
diff --git a/chrome/android/chrome_java_sources.gni b/chrome/android/chrome_java_sources.gni
index ce0ae39..115cabc 100644
--- a/chrome/android/chrome_java_sources.gni
+++ b/chrome/android/chrome_java_sources.gni
@@ -1072,7 +1072,6 @@
   "java/src/org/chromium/chrome/browser/suggestions/SuggestionsOfflineModelObserver.java",
   "java/src/org/chromium/chrome/browser/suggestions/SuggestionsUiDelegate.java",
   "java/src/org/chromium/chrome/browser/suggestions/SuggestionsUiDelegateImpl.java",
-  "java/src/org/chromium/chrome/browser/suggestions/ThumbnailGradient.java",
   "java/src/org/chromium/chrome/browser/suggestions/mostvisited/MostVisitedSites.java",
   "java/src/org/chromium/chrome/browser/suggestions/mostvisited/MostVisitedSitesBridge.java",
   "java/src/org/chromium/chrome/browser/suggestions/mostvisited/MostVisitedSitesMetadataUtils.java",
diff --git a/chrome/android/features/autofill_assistant/javatests/src/org/chromium/chrome/browser/autofill_assistant/TestingAutofillAssistantModuleEntryProvider.java b/chrome/android/features/autofill_assistant/javatests/src/org/chromium/chrome/browser/autofill_assistant/TestingAutofillAssistantModuleEntryProvider.java
index 10fb91ce..65f2c81 100644
--- a/chrome/android/features/autofill_assistant/javatests/src/org/chromium/chrome/browser/autofill_assistant/TestingAutofillAssistantModuleEntryProvider.java
+++ b/chrome/android/features/autofill_assistant/javatests/src/org/chromium/chrome/browser/autofill_assistant/TestingAutofillAssistantModuleEntryProvider.java
@@ -11,7 +11,6 @@
 import org.chromium.chrome.browser.ActivityTabProvider;
 import org.chromium.chrome.browser.autofill_assistant.onboarding.OnboardingCoordinatorFactory;
 import org.chromium.chrome.browser.browser_controls.BrowserControlsStateProvider;
-import org.chromium.chrome.browser.tab.Tab;
 import org.chromium.components.browser_ui.bottomsheet.BottomSheetController;
 import org.chromium.content_public.browser.WebContents;
 
@@ -108,13 +107,13 @@
     }
 
     @Override
-    public void getModuleEntry(
-            Tab tab, Callback<AutofillAssistantModuleEntry> callback, boolean showUi) {
+    public void getModuleEntry(Callback<AutofillAssistantModuleEntry> callback,
+            AssistantModuleInstallUi.Provider moduleInstallUiProvider, boolean showUi) {
         if (mCannotInstall) {
             callback.onResult(null);
             return;
         }
         mNotInstalled = false;
-        super.getModuleEntry(tab, callback, showUi);
+        super.getModuleEntry(callback, moduleInstallUiProvider, showUi);
     }
 }
diff --git a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUi.java b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUi.java
new file mode 100644
index 0000000..626174e
--- /dev/null
+++ b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUi.java
@@ -0,0 +1,32 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+package org.chromium.chrome.browser.autofill_assistant;
+
+import org.chromium.base.Consumer;
+
+/**
+ * UI informing the user about the status of installing a dynamic feature module.
+ */
+public interface AssistantModuleInstallUi {
+    /**
+     * Used to create {@link AssistantModuleInstallUi}.
+     */
+    public interface Provider {
+        /**
+         * Creates a {@link AssistantModuleInstallUi}.
+         */
+        AssistantModuleInstallUi create(Consumer<Boolean> onFailure);
+    }
+
+    /**
+     * Show UI indicating the start of a module install.
+     */
+    public void showInstallStartUi();
+
+    /**
+     * Show UI indicating the failure of a module install.
+     */
+    public void showInstallFailureUi();
+}
diff --git a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUiProviderChrome.java b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUiProviderChrome.java
new file mode 100644
index 0000000..eb9e589
--- /dev/null
+++ b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUiProviderChrome.java
@@ -0,0 +1,45 @@
+
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+package org.chromium.chrome.browser.autofill_assistant;
+
+import org.chromium.base.Consumer;
+import org.chromium.chrome.R;
+import org.chromium.chrome.browser.modules.ModuleInstallUi;
+import org.chromium.chrome.browser.tab.Tab;
+
+/**
+ * Implementation of {@link AssistantModuleInstallUi.Provider} for Chrome.
+ */
+public class AssistantModuleInstallUiProviderChrome implements AssistantModuleInstallUi.Provider {
+    private final Tab mTab;
+
+    public AssistantModuleInstallUiProviderChrome(Tab tab) {
+        mTab = tab;
+    }
+
+    @Override
+    public AssistantModuleInstallUi create(Consumer<Boolean> onFailure) {
+        ModuleInstallUi ui = new ModuleInstallUi(mTab, R.string.autofill_assistant_module_title,
+                new ModuleInstallUi.FailureUiListener() {
+                    @Override
+                    public void onFailureUiResponse(boolean retry) {
+                        onFailure.accept(retry);
+                    }
+                });
+
+        return new AssistantModuleInstallUi() {
+            @Override
+            public void showInstallStartUi() {
+                ui.showInstallStartUi();
+            }
+
+            @Override
+            public void showInstallFailureUi() {
+                ui.showInstallFailureUi();
+            }
+        };
+    }
+}
diff --git a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantDirectActionHandler.java b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantDirectActionHandler.java
index d662744f..ef837b4 100644
--- a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantDirectActionHandler.java
+++ b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantDirectActionHandler.java
@@ -254,10 +254,10 @@
             callback.onResult(null);
             return;
         }
-        mModuleEntryProvider.getModuleEntry(tab, (entry) -> {
+        mModuleEntryProvider.getModuleEntry((entry) -> {
             mDelegate = createDelegate(entry);
             callback.onResult(mDelegate);
-        }, /* showUi = */ true);
+        }, new AssistantModuleInstallUiProviderChrome(tab), /* showUi = */ true);
     }
 
     /** Creates a delegate from the given {@link AutofillAssistantModuleEntry}, if possible. */
diff --git a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantModuleEntryProvider.java b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantModuleEntryProvider.java
index 0030be4..7cf52d01 100644
--- a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantModuleEntryProvider.java
+++ b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantModuleEntryProvider.java
@@ -10,10 +10,7 @@
 import org.chromium.base.Callback;
 import org.chromium.base.Log;
 import org.chromium.base.SysUtils;
-import org.chromium.chrome.R;
 import org.chromium.chrome.browser.autofill_assistant.metrics.FeatureModuleInstallation;
-import org.chromium.chrome.browser.modules.ModuleInstallUi;
-import org.chromium.chrome.browser.tab.Tab;
 
 /**
  * Manages the loading of autofill assistant DFM, and provides implementation of
@@ -46,13 +43,14 @@
 
     /** Gets the AA module entry, installing it if necessary. */
     /* package */
-    void getModuleEntry(Tab tab, Callback<AutofillAssistantModuleEntry> callback, boolean showUi) {
+    void getModuleEntry(Callback<AutofillAssistantModuleEntry> callback,
+            AssistantModuleInstallUi.Provider moduleInstallUiProvider, boolean showUi) {
         AutofillAssistantModuleEntry entry = getModuleEntryIfInstalled();
         if (entry != null) {
             callback.onResult(entry);
             return;
         }
-        loadDynamicModule(tab, callback, showUi);
+        loadDynamicModule(callback, moduleInstallUiProvider, showUi);
     }
 
     /**
@@ -85,19 +83,16 @@
         AutofillAssistantModule.installDeferred();
     }
 
-    private static void loadDynamicModule(
-            Tab tab, Callback<AutofillAssistantModuleEntry> callback, boolean showUi) {
-        ModuleInstallUi ui = new ModuleInstallUi(tab, R.string.autofill_assistant_module_title,
-                new ModuleInstallUi.FailureUiListener() {
-                    @Override
-                    public void onFailureUiResponse(boolean retry) {
-                        if (retry) {
-                            loadDynamicModule(tab, callback, showUi);
-                        } else {
-                            callback.onResult(null);
-                        }
-                    }
-                });
+    private static void loadDynamicModule(Callback<AutofillAssistantModuleEntry> callback,
+            AssistantModuleInstallUi.Provider moduleInstallUiProvider, boolean showUi) {
+        AssistantModuleInstallUi ui = moduleInstallUiProvider.create((Boolean retry) -> {
+            if (retry) {
+                loadDynamicModule(callback, moduleInstallUiProvider, showUi);
+            } else {
+                callback.onResult(null);
+            }
+        });
+
         if (showUi) {
             // Shows toast informing user about install start.
             ui.showInstallStartUi();
diff --git a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantTabHelper.java b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantTabHelper.java
index 7e454a1..fa52fe0e0 100644
--- a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantTabHelper.java
+++ b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AutofillAssistantTabHelper.java
@@ -17,9 +17,10 @@
      * the tab as observer and connect to its native counterpart in order to fulfill startup
      * requests from either side.
      */
-    public static void createForTab(Tab tab, AssistantIsGsaFunction isGsaFunction,
-            AssistantIsMsbbEnabledFunction isMsbbEnabledFunction) {
-        Starter starter = new Starter(tab, isGsaFunction, isMsbbEnabledFunction);
+    public static void createForTab(Tab tab) {
+        Starter starter = new Starter(tab, AssistantDependencyUtilsChrome::isGsa,
+                AssistantDependencyUtilsChrome::isMakeSearchesAndBrowsingBetterSettingEnabled,
+                new AssistantModuleInstallUiProviderChrome(tab));
         tab.addObserver(starter);
         tab.getUserDataHost().setUserData(USER_DATA_KEY, starter);
     }
diff --git a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/Starter.java b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/Starter.java
index 234d962..374c24e 100644
--- a/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/Starter.java
+++ b/chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/Starter.java
@@ -32,6 +32,7 @@
 
     private final AssistantIsGsaFunction mIsGsaFunction;
     private final AssistantIsMsbbEnabledFunction mIsMsbbEnabledFunction;
+    private final AssistantModuleInstallUi.Provider mModuleInstallUiProvider;
 
     /**
      * The WebContents associated with the Tab which this starter is monitoring, unless detached.
@@ -65,10 +66,12 @@
      * This will wait for dependencies to become available and then create the native-side starter.
      */
     public Starter(Tab tab, AssistantIsGsaFunction isGsaFunction,
-            AssistantIsMsbbEnabledFunction isMsbbEnabledFunction) {
+            AssistantIsMsbbEnabledFunction isMsbbEnabledFunction,
+            AssistantModuleInstallUi.Provider moduleInstallUiProvider) {
         mTab = tab;
         mIsGsaFunction = isGsaFunction;
         mIsMsbbEnabledFunction = isMsbbEnabledFunction;
+        mModuleInstallUiProvider = moduleInstallUiProvider;
         detectWebContentsChange(tab);
     }
 
@@ -202,14 +205,14 @@
             return;
         }
 
-        AutofillAssistantModuleEntryProvider.INSTANCE.getModuleEntry(mTab,
+        AutofillAssistantModuleEntryProvider.INSTANCE.getModuleEntry(
                 (moduleEntry)
                         -> safeNativeOnFeatureModuleInstalled(moduleEntry != null
                                         ? FeatureModuleInstallation
                                                   .DFM_FOREGROUND_INSTALLATION_SUCCEEDED
                                         : FeatureModuleInstallation
                                                   .DFM_FOREGROUND_INSTALLATION_FAILED),
-                showUi);
+                mModuleInstallUiProvider, showUi);
     }
 
     @CalledByNative
diff --git a/chrome/android/features/autofill_assistant/public/java_sources.gni b/chrome/android/features/autofill_assistant/public/java_sources.gni
index 5e2e8cf..5c409dc 100644
--- a/chrome/android/features/autofill_assistant/public/java_sources.gni
+++ b/chrome/android/features/autofill_assistant/public/java_sources.gni
@@ -12,6 +12,8 @@
   "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantInfoPageUtil.java",
   "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantIsGsaFunction.java",
   "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantIsMsbbEnabledFunction.java",
+  "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUi.java",
+  "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantModuleInstallUiProviderChrome.java",
   "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantOnboardingHelper.java",
   "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantProfileImageUtil.java",
   "//chrome/android/features/autofill_assistant/public/java/src/org/chromium/chrome/browser/autofill_assistant/AssistantSnackbar.java",
diff --git a/chrome/android/features/start_surface/internal/java/src/org/chromium/chrome/features/start_surface/StartSurfaceLayout.java b/chrome/android/features/start_surface/internal/java/src/org/chromium/chrome/features/start_surface/StartSurfaceLayout.java
index e1b4bb7..cd046de9 100644
--- a/chrome/android/features/start_surface/internal/java/src/org/chromium/chrome/features/start_surface/StartSurfaceLayout.java
+++ b/chrome/android/features/start_surface/internal/java/src/org/chromium/chrome/features/start_surface/StartSurfaceLayout.java
@@ -305,6 +305,7 @@
     @Override
     public void startHiding(int nextId, boolean hintAtTabSelection) {
         int startSurfaceState = mController.getStartSurfaceState();
+        StartSurfaceUserData.getInstance().setUnusedTabRestoredAtStartup(false);
         if (startSurfaceState == StartSurfaceState.SHOWN_HOMEPAGE) {
             startHidingStartSurface(nextId, hintAtTabSelection);
         } else {
diff --git a/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/InstantStartTabSwitcherTest.java b/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/InstantStartTabSwitcherTest.java
index 7d61a10..04b3601 100644
--- a/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/InstantStartTabSwitcherTest.java
+++ b/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/InstantStartTabSwitcherTest.java
@@ -42,6 +42,12 @@
 import org.junit.runner.RunWith;
 
 import org.chromium.base.MathUtils;
+import org.chromium.base.metrics.RecordHistogram;
+import org.chromium.base.test.params.ParameterAnnotations;
+import org.chromium.base.test.params.ParameterAnnotations.UseMethodParameter;
+import org.chromium.base.test.params.ParameterProvider;
+import org.chromium.base.test.params.ParameterSet;
+import org.chromium.base.test.params.ParameterizedRunner;
 import org.chromium.base.test.util.CommandLineFlags;
 import org.chromium.base.test.util.Criteria;
 import org.chromium.base.test.util.CriteriaHelper;
@@ -61,17 +67,20 @@
 import org.chromium.chrome.browser.tasks.pseudotab.TabAttributeCache;
 import org.chromium.chrome.browser.tasks.tab_management.TabUiFeatureUtilities;
 import org.chromium.chrome.browser.tasks.tab_management.TabUiTestHelper;
-import org.chromium.chrome.test.ChromeJUnit4ClassRunner;
+import org.chromium.chrome.test.ChromeJUnit4RunnerDelegate;
 import org.chromium.chrome.test.ChromeTabbedActivityTestRule;
 import org.chromium.chrome.test.util.ActivityTestUtils;
 import org.chromium.chrome.test.util.ChromeRenderTestRule;
 import org.chromium.chrome.test.util.browser.Features.DisableFeatures;
 import org.chromium.chrome.test.util.browser.Features.EnableFeatures;
+import org.chromium.components.embedder_support.util.UrlUtilitiesJni;
 import org.chromium.content_public.browser.test.util.TestThreadUtils;
 import org.chromium.ui.test.util.UiRestriction;
 import org.chromium.ui.test.util.ViewUtils;
 
 import java.io.IOException;
+import java.util.Arrays;
+import java.util.List;
 import java.util.concurrent.ExecutionException;
 import java.util.concurrent.atomic.AtomicInteger;
 
@@ -79,7 +88,8 @@
  * Integration tests of tab switcher with Instant Start which requires 2-stage initialization for
  * Clank startup.
  */
-@RunWith(ChromeJUnit4ClassRunner.class)
+@RunWith(ParameterizedRunner.class)
+@ParameterAnnotations.UseRunnerDelegate(ChromeJUnit4RunnerDelegate.class)
 // clang-format off
 @CommandLineFlags.
     Add({ChromeSwitches.DISABLE_FIRST_RUN_EXPERIENCE, "force-fieldtrials=Study/Group"})
@@ -91,6 +101,7 @@
 public class InstantStartTabSwitcherTest {
     // clang-format on
     private static final String SHADOW_VIEW_TAG = "TabListViewShadow";
+    private static final long MAX_TIMEOUT_MS = 30000L;
 
     @Rule
     public ChromeTabbedActivityTestRule mActivityTestRule = new ChromeTabbedActivityTestRule();
@@ -99,6 +110,23 @@
     public ChromeRenderTestRule mRenderTestRule =
             ChromeRenderTestRule.Builder.withPublicCorpus().setRevision(1).build();
 
+    /**
+     * {@link ParameterProvider} used for parameterized test that provides whether it's single tab
+     * switcher or carousel tab switcher and whether last visited tab is a search result page.
+     */
+    public static class LVTIsSRPTestParams implements ParameterProvider {
+        private static final List<ParameterSet> sLVTIsSRPTestParams =
+                Arrays.asList(new ParameterSet().value(false, false).name("CarouselTab_NotSRP"),
+                        new ParameterSet().value(true, false).name("SingleTab_NotSRP"),
+                        new ParameterSet().value(false, true).name("CarouselTab_SRP"),
+                        new ParameterSet().value(true, true).name("SingleTab_SRP"));
+
+        @Override
+        public List<ParameterSet> getParameters() {
+            return sLVTIsSRPTestParams;
+        }
+    }
+
     @After
     public void tearDown() {
         if (mActivityTestRule.getActivity() != null) {
@@ -434,7 +462,7 @@
         Assert.assertFalse(HomepageManager.isHomepageEnabled());
 
         // Launches Chrome and verifies that the Tab switcher is showing.
-        mActivityTestRule.startMainActivityFromLauncher();
+        StartSurfaceTestUtils.startMainActivityFromLauncher(mActivityTestRule);
         ChromeTabbedActivity cta = mActivityTestRule.getActivity();
         StartSurfaceTestUtils.waitForTabModel(cta);
         TabUiTestHelper.verifyTabModelTabCount(cta, 1, 0);
@@ -448,6 +476,62 @@
         });
     }
 
+    @Test
+    @MediumTest
+    // clang-format off
+    @CommandLineFlags.Add({ChromeSwitches.DISABLE_NATIVE_INITIALIZATION,
+        INSTANT_START_TEST_BASE_PARAMS  + "/show_last_active_tab_only/true"})
+    @UseMethodParameter(LVTIsSRPTestParams.class)
+    public void testRecordLastVisitedTabIsSRPHistogram(boolean isSingleTabSwitcher, boolean isSRP)
+            throws IOException {
+        // clang-format on
+        testRecordLastVisitedTabIsSRP(isSingleTabSwitcher, isSRP);
+    }
+
+    @Test
+    @MediumTest
+    @DisableFeatures(ChromeFeatureList.INSTANT_START)
+    @UseMethodParameter(LVTIsSRPTestParams.class)
+    // clang-format off
+    @CommandLineFlags.Add({ChromeSwitches.DISABLE_NATIVE_INITIALIZATION,
+        INSTANT_START_TEST_BASE_PARAMS})
+    // clang-format on
+    public void testRecordLastVisitedTabIsSRPHistogram_NoInstant(
+            boolean isSingleTabSwitcher, boolean isSRP) throws IOException {
+        testRecordLastVisitedTabIsSRP(isSingleTabSwitcher, isSRP);
+    }
+
+    private void testRecordLastVisitedTabIsSRP(boolean isSingleTabSwitcher, boolean isSRP)
+            throws IOException {
+        StartSurfaceConfiguration.START_SURFACE_LAST_ACTIVE_TAB_ONLY.setForTesting(
+                isSingleTabSwitcher);
+        StartSurfaceTestUtils.createTabStateFile(new int[] {0, 1},
+                new String[] {"https://www.google.com/search?q=test", "https://www.google.com"},
+                isSRP ? 0 : 1);
+        StartSurfaceTestUtils.createThumbnailBitmapAndWriteToFile(0);
+        StartSurfaceTestUtils.createThumbnailBitmapAndWriteToFile(1);
+        TabAttributeCache.setTitleForTesting(0, "Google SRP");
+        TabAttributeCache.setTitleForTesting(1, "Google Homepage");
+        StartSurfaceTestUtils.startMainActivityFromLauncher(mActivityTestRule);
+        StartSurfaceTestUtils.startAndWaitNativeInitialization(mActivityTestRule);
+        ChromeTabbedActivity cta = mActivityTestRule.getActivity();
+        StartSurfaceTestUtils.waitForOverviewVisible(cta);
+        StartSurfaceTestUtils.waitForDeferredStartup(mActivityTestRule);
+
+        Assert.assertEquals(isSRP,
+                UrlUtilitiesJni.get().isGoogleSearchUrl(
+                        StartSurfaceUserData.getInstance().getLastVisitedTabAtStartupUrl()));
+        Assert.assertEquals(1,
+                RecordHistogram.getHistogramTotalCountForTesting(
+                        ReturnToChromeExperimentsUtil
+                                .LAST_VISITED_TAB_IS_SRP_WHEN_OVERVIEW_IS_SHOWN_AT_LAUNCH_UMA));
+        Assert.assertEquals(1,
+                RecordHistogram.getHistogramValueCountForTesting(
+                        ReturnToChromeExperimentsUtil
+                                .LAST_VISITED_TAB_IS_SRP_WHEN_OVERVIEW_IS_SHOWN_AT_LAUNCH_UMA,
+                        isSRP ? 1 : 0));
+    }
+
     private boolean allCardsHaveThumbnail(RecyclerView recyclerView) {
         RecyclerView.Adapter adapter = recyclerView.getAdapter();
         assert adapter != null;
diff --git a/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTest.java b/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTest.java
index 800c4d5..da34e879 100644
--- a/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTest.java
+++ b/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTest.java
@@ -101,6 +101,7 @@
 import org.chromium.chrome.test.util.browser.suggestions.SuggestionsDependenciesRule;
 import org.chromium.components.browser_ui.bottomsheet.BottomSheetTestSupport;
 import org.chromium.components.embedder_support.util.UrlUtilities;
+import org.chromium.content_public.browser.test.util.RenderProcessHostUtils;
 import org.chromium.content_public.browser.test.util.TestThreadUtils;
 import org.chromium.ui.modelutil.MVCListAdapter.ModelList;
 import org.chromium.ui.test.util.UiRestriction;
@@ -571,8 +572,28 @@
             // Disable feed placeholder animation because it causes waitForDeferredStartup() to time
             // out.
             FeedPlaceholderLayout.DISABLE_ANIMATION_SWITCH})
-    public void startSurfaceRecordHistogramsTest() {
+    public void startSurfaceRecordHistogramsTest_SingleTab() {
         // clang-format on
+        startSurfaceRecordHistogramsTest(true);
+    }
+
+    @Test
+    @MediumTest
+    @Restriction({UiRestriction.RESTRICTION_TYPE_PHONE})
+    // clang-format off
+    @EnableFeatures({ChromeFeatureList.TAB_SWITCHER_ON_RETURN + "<Study",
+        ChromeFeatureList.TAB_GRID_LAYOUT_ANDROID,
+        ChromeFeatureList.START_SURFACE_ANDROID + "<Study"})
+    @CommandLineFlags.Add({START_SURFACE_TEST_BASE_PARAMS,
+        // Disable feed placeholder animation because it causes waitForDeferredStartup() to time
+        // out.
+        FeedPlaceholderLayout.DISABLE_ANIMATION_SWITCH})
+    public void startSurfaceRecordHistogramsTest_CarouselTab() {
+        // clang-format on
+        startSurfaceRecordHistogramsTest(false);
+    }
+
+    private void startSurfaceRecordHistogramsTest(boolean isSingleTabSwitcher) {
         if (!mImmediateReturn) {
             assertNotEquals(0, ReturnToChromeExperimentsUtil.TAB_SWITCHER_ON_RETURN_MS.getValue());
             StartSurfaceTestUtils.pressHomePageButton(mActivityTestRule.getActivity());
@@ -581,20 +602,12 @@
         }
 
         Assert.assertEquals("single", StartSurfaceConfiguration.START_SURFACE_VARIATION.getValue());
-        Assert.assertTrue(StartSurfaceConfiguration.START_SURFACE_LAST_ACTIVE_TAB_ONLY.getValue());
+        Assert.assertEquals(isSingleTabSwitcher,
+                StartSurfaceConfiguration.START_SURFACE_LAST_ACTIVE_TAB_ONLY.getValue());
         StartSurfaceTestUtils.waitForOverviewVisible(
                 mLayoutChangedCallbackHelper, mCurrentlyActiveLayout);
         mActivityTestRule.waitForActivityNativeInitializationComplete();
-
-        // Waits for the current Tab to complete loading. The deferred startup will be triggered
-        // after the loading.
-        Tab tab = mActivityTestRule.getActivity().getActivityTab();
-        if (tab != null && tab.isLoading()) {
-            CriteriaHelper.pollUiThread(()
-                                                -> !tab.isLoading(),
-                    MAX_TIMEOUT_MS, CriteriaHelper.DEFAULT_POLLING_INTERVAL);
-        }
-        assertTrue("Deferred startup never completed", mActivityTestRule.waitForDeferredStartup());
+        StartSurfaceTestUtils.waitForDeferredStartup(mActivityTestRule);
 
         boolean isInstantStart =
                 TabUiFeatureUtilities.supportInstantStart(false, mActivityTestRule.getActivity());
@@ -606,11 +619,18 @@
         int expectedRecordCount = mImmediateReturn ? 1 : 0;
         // Histograms should be only recorded when StartSurface is shown immediately after
         // launch.
+        if (isSingleTabSwitcher) {
+            Assert.assertEquals(expectedRecordCount,
+                    RecordHistogram.getHistogramTotalCountForTesting(
+                            StartSurfaceConfiguration.getHistogramName(
+                                    SingleTabSwitcherMediator.SINGLE_TAB_TITLE_AVAILABLE_TIME_UMA,
+                                    isInstantStart)));
+        }
+
         Assert.assertEquals(expectedRecordCount,
                 RecordHistogram.getHistogramTotalCountForTesting(
-                        StartSurfaceConfiguration.getHistogramName(
-                                SingleTabSwitcherMediator.SINGLE_TAB_TITLE_AVAILABLE_TIME_UMA,
-                                isInstantStart)));
+                        ReturnToChromeExperimentsUtil
+                                .LAST_VISITED_TAB_IS_SRP_WHEN_OVERVIEW_IS_SHOWN_AT_LAUNCH_UMA));
 
         Assert.assertEquals(expectedRecordCount,
                 RecordHistogram.getHistogramTotalCountForTesting(
@@ -1076,6 +1096,42 @@
         assertEquals(hasUpdateMenuItem ? 12 : 11, menuItemsModelList.size());
     }
 
+    @Test
+    @MediumTest
+    @Feature({"StartSurface"})
+    // clang-format off
+    @CommandLineFlags.Add({START_SURFACE_TEST_BASE_PARAMS})
+    public void test_DoNotLoadLastSelectedTabOnStartup() {
+        // clang-format on
+        doTestNotLoadLastSelectedTabOnStartupImpl();
+    }
+
+    @Test
+    @MediumTest
+    @Feature({"StartSurface"})
+    // clang-format off
+    @CommandLineFlags.Add({START_SURFACE_TEST_BASE_PARAMS + "/show_last_active_tab_only/true"})
+    public void test_DoNotLoadLastSelectedTabOnStartupV2() {
+        // clang-format on
+        doTestNotLoadLastSelectedTabOnStartupImpl();
+    }
+
+    private void doTestNotLoadLastSelectedTabOnStartupImpl() {
+        assumeTrue(mImmediateReturn);
+
+        ChromeTabbedActivity cta = mActivityTestRule.getActivity();
+        StartSurfaceTestUtils.waitForOverviewVisible(
+                mLayoutChangedCallbackHelper, mCurrentlyActiveLayout);
+        StartSurfaceTestUtils.waitForTabModel(cta);
+        TabUiTestHelper.verifyTabModelTabCount(cta, 1, 0);
+        Assert.assertEquals(0, RenderProcessHostUtils.getCurrentRenderProcessCount());
+
+        StartSurfaceTestUtils.launchFirstMVTile(cta, /* currentTabCount = */ 1);
+        TabUiTestHelper.verifyTabModelTabCount(cta, 2, 0);
+        StartSurfaceTestUtils.waitForCurrentTabLoaded(mActivityTestRule);
+        Assert.assertEquals(1, RenderProcessHostUtils.getCurrentRenderProcessCount());
+    }
+
     /**
      * Check that the next decision time is within |numOfDays| from now.
      * @param numOfDays Number of days to check.
diff --git a/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTestUtils.java b/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTestUtils.java
index 7adcf7f..55cf296 100644
--- a/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTestUtils.java
+++ b/chrome/android/features/start_surface/internal/javatests/src/org/chromium/chrome/features/start_surface/StartSurfaceTestUtils.java
@@ -57,6 +57,7 @@
 import org.chromium.chrome.browser.suggestions.tile.TileSectionType;
 import org.chromium.chrome.browser.suggestions.tile.TileSource;
 import org.chromium.chrome.browser.suggestions.tile.TileTitleSource;
+import org.chromium.chrome.browser.tab.Tab;
 import org.chromium.chrome.browser.tab.TabState;
 import org.chromium.chrome.browser.tabmodel.TabPersistentStore;
 import org.chromium.chrome.browser.tabmodel.TabbedModeTabPersistencePolicy;
@@ -482,6 +483,30 @@
     }
 
     /**
+     * Wait for the deferred startup to be triggered.
+     * @param activityTestRule The ChromeTabbedActivityTestRule under test.
+     */
+    public static void waitForDeferredStartup(ChromeTabbedActivityTestRule activityTestRule) {
+        // Waits for the current Tab to complete loading. The deferred startup will be triggered
+        // after the loading.
+        waitForCurrentTabLoaded(activityTestRule);
+        assertTrue("Deferred startup never completed", activityTestRule.waitForDeferredStartup());
+    }
+
+    /**
+     * Waits for the current Tab to complete loading.
+     * @param activityTestRule The ChromeTabbedActivityTestRule under test.
+     */
+    public static void waitForCurrentTabLoaded(ChromeTabbedActivityTestRule activityTestRule) {
+        Tab tab = activityTestRule.getActivity().getActivityTab();
+        if (tab != null && tab.isLoading()) {
+            CriteriaHelper.pollUiThread(()
+                                                -> !tab.isLoading(),
+                    MAX_TIMEOUT_MS, CriteriaHelper.DEFAULT_POLLING_INTERVAL);
+        }
+    }
+
+    /**
      * Create a file so that a TabState can be restored later.
      * @param tabId the Tab ID
      * @param encrypted for Incognito mode
diff --git a/chrome/android/features/start_surface/public/java/src/org/chromium/chrome/features/start_surface/StartSurfaceUserData.java b/chrome/android/features/start_surface/public/java/src/org/chromium/chrome/features/start_surface/StartSurfaceUserData.java
index 4c7b533..150189a2 100644
--- a/chrome/android/features/start_surface/public/java/src/org/chromium/chrome/features/start_surface/StartSurfaceUserData.java
+++ b/chrome/android/features/start_surface/public/java/src/org/chromium/chrome/features/start_surface/StartSurfaceUserData.java
@@ -18,9 +18,14 @@
     private boolean mFocusOnOmnibox;
     private boolean mCreatedAsNtp;
     private boolean mOpenedFromStart;
-
+    private String mLastVisitedTabAtStartupUrl;
     // Saves the Feeds instance state.
     private String mFeedsInstanceState;
+    /**
+     * Tracks whether the last visited Tab is restored at startup but not showing due to the
+     * overview page is showing at the startup.
+     */
+    private boolean mUnusedTabRestoredAtStartup;
 
     /**
      * Static class that implements the initialization-on-demand holder idiom.
@@ -154,4 +159,35 @@
     protected String restoreFeedInstanceState() {
         return mFeedsInstanceState;
     }
+
+    /**
+     * Sets the url of last visited tab at start up.
+     * @param lastVisitedTabAtStartupUrl The url of last visited tab at start up.
+     */
+    public void setLastVisitedTabAtStartupUrl(String lastVisitedTabAtStartupUrl) {
+        mLastVisitedTabAtStartupUrl = lastVisitedTabAtStartupUrl;
+    }
+
+    /**
+     * Returns the saved url of last visited tab at start up.
+     */
+    public String getLastVisitedTabAtStartupUrl() {
+        return mLastVisitedTabAtStartupUrl;
+    }
+
+    /**
+     * Sets whether an unused Tab is restored at startup due to an overview page is showing at the
+     * startup.
+     */
+    public void setUnusedTabRestoredAtStartup(boolean overviewShownAtStartup) {
+        mUnusedTabRestoredAtStartup = overviewShownAtStartup;
+    }
+
+    /**
+     * Gets whether an unused Tab is restored at startup due to an overview page is showing at the
+     * startup.
+     */
+    public boolean getUnusedTabRestoredAtStartup() {
+        return mUnusedTabRestoredAtStartup;
+    }
 }
diff --git a/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/SingleTabSwitcherMediator.java b/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/SingleTabSwitcherMediator.java
index f565fa2c..1f643b9e 100644
--- a/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/SingleTabSwitcherMediator.java
+++ b/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/SingleTabSwitcherMediator.java
@@ -252,6 +252,7 @@
         StartSurfaceConfiguration.recordHistogram(SINGLE_TAB_TITLE_AVAILABLE_TIME_UMA,
                 mTabTitleAvailableTime - activityCreationTimeMs,
                 TabUiFeatureUtilities.supportInstantStart(false, mContext));
+        ReturnToChromeExperimentsUtil.recordLastVisitedTabIsSRPWhenOverviewIsShownAtLaunch();
     }
 
     @Override
diff --git a/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/tab_management/TabSwitcherMediator.java b/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/tab_management/TabSwitcherMediator.java
index f972598..63052848 100644
--- a/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/tab_management/TabSwitcherMediator.java
+++ b/chrome/android/features/tab_ui/java/src/org/chromium/chrome/browser/tasks/tab_management/TabSwitcherMediator.java
@@ -774,7 +774,11 @@
     }
 
     @Override
-    public void onOverviewShownAtLaunch(long activityCreationTimeMs) {}
+    public void onOverviewShownAtLaunch(long activityCreationTimeMs) {
+        if (mMode == TabListMode.CAROUSEL) {
+            ReturnToChromeExperimentsUtil.recordLastVisitedTabIsSRPWhenOverviewIsShownAtLaunch();
+        }
+    }
 
     /**
      * Do clean-up work after the overview hiding animation is finished.
diff --git a/chrome/android/java/res/drawable/thumbnail_gradient_top_left.xml b/chrome/android/java/res/drawable/thumbnail_gradient_top_left.xml
deleted file mode 100644
index bac6d72..0000000
--- a/chrome/android/java/res/drawable/thumbnail_gradient_top_left.xml
+++ /dev/null
@@ -1,10 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<shape xmlns:android="http://schemas.android.com/apk/res/android">
-
-    <!-- The spec for the gradient is #25272B applied at 6% transparency. This gives #0F25272B. -->
-
-    <gradient
-        android:angle="315"
-        android:startColor="#0F25272B"
-        android:endColor="#00000000" />
-</shape>
\ No newline at end of file
diff --git a/chrome/android/java/res/drawable/thumbnail_gradient_top_right.xml b/chrome/android/java/res/drawable/thumbnail_gradient_top_right.xml
deleted file mode 100644
index 536c7f07..0000000
--- a/chrome/android/java/res/drawable/thumbnail_gradient_top_right.xml
+++ /dev/null
@@ -1,10 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<shape xmlns:android="http://schemas.android.com/apk/res/android">
-
-    <!-- The spec for the gradient is #25272B applied at 6% transparency. This gives #0F25272B. -->
-
-    <gradient
-        android:angle="225"
-        android:startColor="#0F25272B"
-        android:endColor="#00000000" />
-</shape>
\ No newline at end of file
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/ChromeTabbedActivity.java b/chrome/android/java/src/org/chromium/chrome/browser/ChromeTabbedActivity.java
index 5f3d0be..99a4267 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/ChromeTabbedActivity.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/ChromeTabbedActivity.java
@@ -1708,10 +1708,14 @@
                 ChromePreferenceKeys.TABBED_ACTIVITY_LAST_BACKGROUNDED_TIME_MS_PREF);
 
         assert getActivityTabStartupMetricsTracker() != null;
+        boolean shouldShowOverviewPageOnStart = shouldShowOverviewPageOnStart();
+        if (shouldShowOverviewPageOnStart) {
+            StartSurfaceUserData.getInstance().setUnusedTabRestoredAtStartup(true);
+        }
         if (StartupPaintPreviewHelper.isEnabled()) {
             StartupPaintPreviewHelper paintPreviewHelper = new StartupPaintPreviewHelper(
                     getWindowAndroid(), getOnCreateTimestampMs(), getBrowserControlsManager(),
-                    getTabModelSelector(), shouldShowOverviewPageOnStart(), () -> {
+                    getTabModelSelector(), shouldShowOverviewPageOnStart, () -> {
                         return getToolbarManager() == null
                                 ? null
                                 : getToolbarManager().getProgressBarCoordinator();
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/app/flags/ChromeCachedFlags.java b/chrome/android/java/src/org/chromium/chrome/browser/app/flags/ChromeCachedFlags.java
index 51b412c..b223f31 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/app/flags/ChromeCachedFlags.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/app/flags/ChromeCachedFlags.java
@@ -67,6 +67,7 @@
         // Workaround for crbug.com/1223545: Do not use Arrays.asList().
         List<String> featuresToCache = new ArrayList<String>() {
             {
+                add(ChromeFeatureList.ANONYMOUS_UPDATE_CHECKS);
                 add(ChromeFeatureList.APP_MENU_MOBILE_SITE_OPTION);
                 add(ChromeFeatureList.APP_TO_WEB_ATTRIBUTION);
                 add(ChromeFeatureList.BOOKMARK_BOTTOM_SHEET);
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/app/tab_activity_glue/ReparentingTask.java b/chrome/android/java/src/org/chromium/chrome/browser/app/tab_activity_glue/ReparentingTask.java
index fce01ed8..b6a061ca 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/app/tab_activity_glue/ReparentingTask.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/app/tab_activity_glue/ReparentingTask.java
@@ -26,7 +26,7 @@
 import org.chromium.chrome.browser.flags.ChromeFeatureList;
 import org.chromium.chrome.browser.tab.Tab;
 import org.chromium.chrome.browser.tab.TabDelegateFactory;
-import org.chromium.chrome.browser.tab.TabStateAttributes;
+import org.chromium.chrome.browser.tab.TabImpl;
 import org.chromium.chrome.browser.tabmodel.TabModelSelector;
 import org.chromium.chrome.browser.tabmodel.TabReparentingParams;
 import org.chromium.content_public.browser.WebContents;
@@ -168,9 +168,7 @@
     public void finish(@NonNull Delegate delegate, @Nullable Runnable finalizeCallback) {
         delegate.getCompositorViewHolder().prepareForTabReparenting();
         attach(delegate.getWindowAndroid(), delegate.getTabDelegateFactory());
-        if (!mTab.isDestroyed()) {
-            TabStateAttributes.from(mTab).setIsTabStateDirty(true);
-        }
+        ((TabImpl) mTab).setIsTabStateDirty(true);
         if (finalizeCallback != null) finalizeCallback.run();
     }
 
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/compositor/CompositorViewHolder.java b/chrome/android/java/src/org/chromium/chrome/browser/compositor/CompositorViewHolder.java
index 58f4e976..8a736f3 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/compositor/CompositorViewHolder.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/compositor/CompositorViewHolder.java
@@ -65,6 +65,7 @@
 import org.chromium.chrome.browser.toolbar.ControlContainer;
 import org.chromium.chrome.browser.ui.TabObscuringHandler;
 import org.chromium.chrome.browser.util.ChromeAccessibilityUtil;
+import org.chromium.chrome.features.start_surface.StartSurfaceUserData;
 import org.chromium.components.browser_ui.widget.InsetObserverView;
 import org.chromium.components.browser_ui.widget.TouchEventObserver;
 import org.chromium.components.content_capture.OnscreenContentProvider;
@@ -1421,7 +1422,13 @@
     }
 
     private void setTab(Tab tab) {
-        if (tab != null) tab.loadIfNeeded();
+        // The StartSurfaceUserData.getInstance().getUnusedTabRestoredAtStartup() is only true when
+        // the Start surface is showing in the startup and there isn't any Tab opened. Thus, no
+        // Tab needs to be loaded. Once a new Tab is opening and Start surface is hiding, this flag
+        // will be reset.
+        if (tab != null && !StartSurfaceUserData.getInstance().getUnusedTabRestoredAtStartup()) {
+            tab.loadIfNeeded();
+        }
 
         View newView = tab != null ? tab.getView() : null;
         if (mView == newView) return;
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/download/OMADownloadHandler.java b/chrome/android/java/src/org/chromium/chrome/browser/download/OMADownloadHandler.java
index 6e5f347..35e24ca 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/download/OMADownloadHandler.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/download/OMADownloadHandler.java
@@ -120,6 +120,25 @@
             "953 Non-Acceptable Content \n\r";
     private static final String DOWNLOAD_STATUS_LOADER_ERROR = "954 Loader Error \n\r";
 
+    private static final NetworkTrafficAnnotationTag TRAFFIC_ANNOTATION =
+            NetworkTrafficAnnotationTag.createComplete("oma_download_handler_android",
+                    "semantics {"
+                            + "  sender: 'OMA Download Handler (Android)'"
+                            + "  description: 'Uploads file download status to the server URL '"
+                            + "               'specified in the download descriptor XML, as ' "
+                            + "               'required by the OMA DRM specification.'"
+                            + "  trigger: 'After an OMA DRM file download completes.'"
+                            + "  data: 'Info related to the download.'"
+                            + "  destination: OTHER"
+                            + "}"
+                            + "policy {"
+                            + "  cookies_allowed: NO"
+                            + "  setting: 'This feature cannot be disabled by settings as it is '"
+                            + "           'part of the OMA DRM specification.'"
+                            + "  policy_exception_justification:"
+                            + "      'Not implemented.'"
+                            + "}");
+
     private final Context mContext;
     private final SharedPreferencesManager mSharedPrefs;
     private final LongSparseArray<DownloadItem> mSystemDownloadIdMap =
@@ -945,7 +964,7 @@
             try {
                 URL url = new URL(mOMAInfo.getValue(OMA_INSTALL_NOTIFY_URI));
                 urlConnection = (HttpURLConnection) ChromiumNetworkAdapter.openConnection(
-                        url, NetworkTrafficAnnotationTag.MISSING_TRAFFIC_ANNOTATION);
+                        url, TRAFFIC_ANNOTATION);
                 urlConnection.setDoOutput(true);
                 urlConnection.setUseCaches(false);
                 urlConnection.setRequestMethod("POST");
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/omaha/RequestGenerator.java b/chrome/android/java/src/org/chromium/chrome/browser/omaha/RequestGenerator.java
index 3b9d973..e8e6974 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/omaha/RequestGenerator.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/omaha/RequestGenerator.java
@@ -14,6 +14,8 @@
 import org.xmlpull.v1.XmlSerializer;
 
 import org.chromium.base.BuildInfo;
+import org.chromium.chrome.browser.flags.CachedFeatureFlags;
+import org.chromium.chrome.browser.flags.ChromeFeatureList;
 import org.chromium.chrome.browser.uid.SettingsSecureBasedIdentificationGenerator;
 import org.chromium.chrome.browser.uid.UniqueIdentificationGeneratorFactory;
 import org.chromium.ui.base.DeviceFormFactor;
@@ -80,8 +82,12 @@
             serializer.attribute(null, "requestid", "{" + data.getRequestID() + "}");
             serializer.attribute(null, "sessionid", "{" + sessionID + "}");
             serializer.attribute(null, "installsource", data.getInstallSource());
-            serializer.attribute(null, "userid", "{" + getDeviceID() + "}");
-            serializer.attribute(null, "dedup", "uid");
+            if (CachedFeatureFlags.isEnabled(ChromeFeatureList.ANONYMOUS_UPDATE_CHECKS)) {
+                serializer.attribute(null, "dedup", "cr");
+            } else {
+                serializer.attribute(null, "userid", "{" + getDeviceID() + "}");
+                serializer.attribute(null, "dedup", "uid");
+            }
 
             // Set up <os platform="android"... />
             serializer.startTag(null, "os");
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/suggestions/ThumbnailGradient.java b/chrome/android/java/src/org/chromium/chrome/browser/suggestions/ThumbnailGradient.java
deleted file mode 100644
index 5b6383f..0000000
--- a/chrome/android/java/src/org/chromium/chrome/browser/suggestions/ThumbnailGradient.java
+++ /dev/null
@@ -1,148 +0,0 @@
-// Copyright 2017 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-package org.chromium.chrome.browser.suggestions;
-
-import android.content.res.Resources;
-import android.graphics.Bitmap;
-import android.graphics.Color;
-import android.graphics.drawable.BitmapDrawable;
-import android.graphics.drawable.Drawable;
-import android.graphics.drawable.LayerDrawable;
-import android.os.SystemClock;
-
-import androidx.annotation.IntDef;
-
-import org.chromium.base.ApiCompatibilityUtils;
-import org.chromium.base.metrics.RecordHistogram;
-import org.chromium.chrome.R;
-import org.chromium.ui.base.LocalizationUtils;
-
-import java.lang.annotation.Retention;
-import java.lang.annotation.RetentionPolicy;
-
-/**
- * When suggestions cards are displayed on a white background, thumbnails with white backgrounds
- * have a gradient overlaid to provide contrast at the edge of the cards.
- */
-public class ThumbnailGradient {
-    /** If all the RGB values of a pixel are greater than this value, it is counted as 'light'. */
-    private static final int LIGHT_PIXEL_THRESHOLD = 0xcc;
-
-    /** The percent of the border pictures that need to be 'light' for a Bitmap to be 'light'. */
-    private static final float PIXEL_BORDER_RATIO = 0.4f;
-
-    /** Where the image is located in the card. */
-    @IntDef({ThumbnailLocation.START, ThumbnailLocation.END})
-    @Retention(RetentionPolicy.SOURCE)
-    public @interface ThumbnailLocation {
-        int START = 0;
-        int END = 1;
-    }
-
-    /** The corner of the thumbnail where the gradient is darkest. */
-    @IntDef({GradientDirection.TOP_LEFT, GradientDirection.TOP_RIGHT})
-    @Retention(RetentionPolicy.SOURCE)
-    private @interface GradientDirection {
-        int TOP_LEFT = 0;
-        int TOP_RIGHT = 1;
-    }
-
-    /**
-     * Calls {@link #createDrawableWithGradientIfNeeded(Bitmap, int, Resources)} with the default
-     * {@link ThumbnailLocation#END}.
-     */
-    public static Drawable createDrawableWithGradientIfNeeded(Bitmap bitmap, Resources resources) {
-        return createDrawableWithGradientIfNeeded(bitmap, ThumbnailLocation.END, resources);
-    }
-
-    /**
-     * If the {@link Bitmap} should have a gradient applied this method returns a Drawable
-     * containing the Bitmap and a gradient. Otherwise it returns a BitmapDrawable containing just
-     * the Bitmap.
-     * @param bitmap The {@link Bitmap} used to create the drawable.
-     * @param thumbnailLocation Where the image is located in the card.
-     * @param resources The {@link Resources} for the current activity.
-     */
-    public static Drawable createDrawableWithGradientIfNeeded(
-            Bitmap bitmap, @ThumbnailLocation int thumbnailLocation, Resources resources) {
-        int direction = getGradientDirection(thumbnailLocation);
-
-        // We want to keep an eye on how long this takes.
-        long time = SystemClock.elapsedRealtime();
-        boolean lightImage = hasLightCorner(bitmap, direction);
-        RecordHistogram.recordTimesHistogram(
-                "Thumbnails.Gradient.ImageDetectionTime", SystemClock.elapsedRealtime() - time);
-
-        RecordHistogram.recordBooleanHistogram(
-                "Thumbnails.Gradient.ImageRequiresGradient", lightImage);
-
-        if (lightImage) {
-            Drawable gradient = ApiCompatibilityUtils.getDrawable(resources,
-                    direction == GradientDirection.TOP_LEFT
-                            ? R.drawable.thumbnail_gradient_top_left
-                            : R.drawable.thumbnail_gradient_top_right);
-
-            return new LayerDrawable(
-                    new Drawable[] {new BitmapDrawable(resources, bitmap), gradient});
-        }
-
-        return new BitmapDrawable(resources, bitmap);
-    }
-
-    /**
-     * Determines whether a Bitmap has a light corner.
-     */
-    private static boolean hasLightCorner(Bitmap bitmap, @GradientDirection int direction) {
-        int lightPixels = 0;
-
-        final int width = bitmap.getWidth();
-        final int height = bitmap.getHeight();
-        // We test all the pixels along the top and one side. The |-1| is so we don't count the
-        // corner twice.
-        final int threshold = (int) ((width + height - 1) * PIXEL_BORDER_RATIO);
-
-        for (int x = 0; x < width; x++) {
-            if (isPixelLight(bitmap.getPixel(x, 0))) lightPixels++;
-        }
-
-        // If we've already exceeded the threshold of light pixels, don't bother counting the rest.
-        if (lightPixels > threshold) {
-            return true;
-        }
-
-        final int x = direction == GradientDirection.TOP_LEFT ? 0 : width - 1;
-        // Avoid counting the corner pixels twice.
-        for (int y = 1; y < height - 1; y++) {
-            if (isPixelLight(bitmap.getPixel(x, y))) lightPixels++;
-        }
-
-        return lightPixels > threshold;
-    }
-
-    /**
-     * Whether a pixel counts as light.
-     */
-    private static boolean isPixelLight(int color) {
-        return Color.red(color) > LIGHT_PIXEL_THRESHOLD && Color.blue(color) > LIGHT_PIXEL_THRESHOLD
-                && Color.green(color) > LIGHT_PIXEL_THRESHOLD;
-    }
-
-    /**
-     * The gradient should come from the upper corner of the thumbnail that is touching the side of
-     * the card.
-     */
-    @GradientDirection
-    private static int getGradientDirection(@ThumbnailLocation int thumbnailLocation) {
-        // The drawable resource does not get flipped automatically if we are in RTL, so we must
-        // flip it ourselves.
-        boolean rtl = LocalizationUtils.isLayoutRtl();
-
-        // If the thumbnail is on the left side of the card, the gradient should be applied
-        // to the top left corner. If it is on the right side of the card, the gradient should be
-        // applied to the top right corner.
-        return thumbnailLocation == ThumbnailLocation.END == rtl ? GradientDirection.TOP_LEFT
-                                                                 : GradientDirection.TOP_RIGHT;
-    }
-}
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/tab/TabHelpers.java b/chrome/android/java/src/org/chromium/chrome/browser/tab/TabHelpers.java
index 9262692c..1a771c3 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/tab/TabHelpers.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/tab/TabHelpers.java
@@ -5,7 +5,6 @@
 package org.chromium.chrome.browser.tab;
 
 import org.chromium.chrome.browser.SwipeRefreshHandler;
-import org.chromium.chrome.browser.autofill_assistant.AssistantDependencyUtilsChrome;
 import org.chromium.chrome.browser.autofill_assistant.AutofillAssistantTabHelper;
 import org.chromium.chrome.browser.complex_tasks.TaskTabHelper;
 import org.chromium.chrome.browser.contextualsearch.ContextualSearchTabHelper;
@@ -38,8 +37,7 @@
         TabBrowserControlsConstraintsHelper.createForTab(tab);
         ContinuousSearchTabHelper.createForTab(tab);
         if (ReaderModeManager.isEnabled()) ReaderModeManager.createForTab(tab);
-        AutofillAssistantTabHelper.createForTab(tab, AssistantDependencyUtilsChrome::isGsa,
-                AssistantDependencyUtilsChrome::isMakeSearchesAndBrowsingBetterSettingEnabled);
+        AutofillAssistantTabHelper.createForTab(tab);
 
         // The following will start prefetching data for the price drops feature, so
         // we should only do it if the user is eligible for the feature (e.g. has sync enabled).
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/tab/TabImpl.java b/chrome/android/java/src/org/chromium/chrome/browser/tab/TabImpl.java
index e6ef840..074a257 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/tab/TabImpl.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/tab/TabImpl.java
@@ -135,6 +135,9 @@
     private boolean mIsClosing;
     private boolean mIsShowingErrorPage;
 
+    /** Whether or not the TabState has changed. */
+    private boolean mIsTabStateDirty = true;
+
     /**
      * Saves how this tab was launched (from a link, external app, etc) so that
      * we can determine the different circumstances in which it should be
@@ -782,6 +785,18 @@
         return !(activity instanceof ChromeActivity);
     }
 
+    /**
+     * @return Whether the TabState representing this Tab has been updated.
+     */
+    public boolean isTabStateDirty() {
+        return mIsTabStateDirty;
+    }
+
+    @Override
+    public void setIsTabStateDirty(boolean isDirty) {
+        mIsTabStateDirty = isDirty;
+    }
+
     @Override
     public void setIsTabSaveEnabled(boolean isTabSaveEnabled) {
         mIsTabSaveEnabledSupplier.set(isTabSaveEnabled);
@@ -1043,6 +1058,7 @@
      * @param url URL that was loaded.
      */
     void didFinishPageLoad(GURL url) {
+        mIsTabStateDirty = true;
         updateTitle();
 
         for (TabObserver observer : mObservers) observer.onPageLoadFinished(this, url);
@@ -1103,6 +1119,7 @@
      * Called when navigation entries were removed.
      */
     void notifyNavigationEntriesDeleted() {
+        mIsTabStateDirty = true;
         for (TabObserver observer : mObservers) observer.onNavigationEntriesDeleted(this);
     }
 
@@ -1198,6 +1215,7 @@
     void updateTitle(String title) {
         if (TextUtils.equals(CriticalPersistedTabData.from(this).getTitle(), title)) return;
 
+        mIsTabStateDirty = true;
         CriticalPersistedTabData.from(this).setTitle(title);
         notifyPageTitleChanged();
     }
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/tab/TabWebContentsObserver.java b/chrome/android/java/src/org/chromium/chrome/browser/tab/TabWebContentsObserver.java
index 562656b..acbc4424 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/tab/TabWebContentsObserver.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/tab/TabWebContentsObserver.java
@@ -334,9 +334,7 @@
             if (!navigation.hasCommitted()) return;
 
             if (navigation.isInPrimaryMainFrame()) {
-                if (!mTab.isDestroyed()) {
-                    TabStateAttributes.from(mTab).setIsTabStateDirty(true);
-                }
+                mTab.setIsTabStateDirty(true);
                 mTab.updateTitle();
                 mTab.handleDidFinishNavigation(navigation.getUrl(), navigation.pageTransition());
                 mTab.setIsShowingErrorPage(navigation.isErrorPage());
@@ -380,9 +378,7 @@
 
         @Override
         public void navigationEntriesChanged() {
-            if (!mTab.isDestroyed()) {
-                TabStateAttributes.from(mTab).setIsTabStateDirty(true);
-            }
+            mTab.setIsTabStateDirty(true);
         }
 
         @Override
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/tabmodel/TabPersistentStore.java b/chrome/android/java/src/org/chromium/chrome/browser/tabmodel/TabPersistentStore.java
index 393785a..7b2ff52 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/tabmodel/TabPersistentStore.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/tabmodel/TabPersistentStore.java
@@ -41,15 +41,16 @@
 import org.chromium.chrome.browser.tab.Tab;
 import org.chromium.chrome.browser.tab.TabCreationState;
 import org.chromium.chrome.browser.tab.TabIdManager;
+import org.chromium.chrome.browser.tab.TabImpl;
 import org.chromium.chrome.browser.tab.TabLaunchType;
 import org.chromium.chrome.browser.tab.TabState;
-import org.chromium.chrome.browser.tab.TabStateAttributes;
 import org.chromium.chrome.browser.tab.TabStateExtractor;
 import org.chromium.chrome.browser.tab.state.CriticalPersistedTabData;
 import org.chromium.chrome.browser.tab.state.FilePersistedTabDataStorage;
 import org.chromium.chrome.browser.tab.state.PersistedTabData;
 import org.chromium.chrome.browser.tabpersistence.TabStateDirectory;
 import org.chromium.chrome.browser.tabpersistence.TabStateFileManager;
+import org.chromium.chrome.features.start_surface.StartSurfaceUserData;
 import org.chromium.components.embedder_support.util.UrlConstants;
 import org.chromium.components.embedder_support.util.UrlUtilities;
 import org.chromium.content_public.browser.LoadUrlParams;
@@ -130,9 +131,6 @@
         new TabModelSelectorTabObserver(mTabModelSelector) {
             @Override
             public void onNavigationEntriesDeleted(Tab tab) {
-                if (!tab.isDestroyed()) {
-                    TabStateAttributes.from(tab).setIsTabStateDirty(true);
-                }
                 addTabToSaveQueue(tab);
             }
 
@@ -145,20 +143,6 @@
             public void onRootIdChanged(Tab tab, int newRootId) {
                 addTabToSaveQueue(tab);
             }
-
-            @Override
-            public void onPageLoadFinished(Tab tab, GURL url) {
-                if (!tab.isDestroyed()) {
-                    TabStateAttributes.from(tab).setIsTabStateDirty(true);
-                }
-            }
-
-            @Override
-            public void onTitleUpdated(Tab tab) {
-                if (!tab.isDestroyed()) {
-                    TabStateAttributes.from(tab).setIsTabStateDirty(true);
-                }
-            }
         };
 
         mTabModelObserver = new TabModelObserver() {
@@ -734,8 +718,9 @@
             boolean wasIncognitoTabModelSelected = mTabModelSelector.isIncognitoSelected();
             int selectedModelTabCount = mTabModelSelector.getCurrentModel().getCount();
 
-            // TODO(hanxi): Sets the correct value for skipLoadingTab.
-            TabModelUtils.setIndex(model, TabModelUtils.getTabIndexById(model, tabId), false);
+            TabModelUtils.setIndex(model, TabModelUtils.getTabIndexById(model, tabId),
+                    StartSurfaceUserData.getInstance().getUnusedTabRestoredAtStartup());
+            StartSurfaceUserData.getInstance().setLastVisitedTabAtStartupUrl(tabToRestore.url);
             boolean isIncognitoTabModelSelected = mTabModelSelector.isIncognitoSelected();
 
             // Setting the index will cause the tab's model to be selected. Set it back to the model
@@ -825,8 +810,8 @@
     }
 
     private void addTabToSaveQueueIfApplicable(Tab tab) {
-        if (tab == null || tab.isDestroyed()) return;
-        if (mTabsToSave.contains(tab) || !TabStateAttributes.from(tab).isTabStateDirty()
+        if (tab == null) return;
+        if (mTabsToSave.contains(tab) || !((TabImpl) tab).isTabStateDirty()
                 || isTabUrlContentScheme(tab)) {
             return;
         }
@@ -1267,9 +1252,7 @@
         protected void onPostExecute(Void v) {
             if (mDestroyed || isCancelled()) return;
             if (mStateSaved) {
-                if (!mTab.isDestroyed()) {
-                    TabStateAttributes.from(mTab).setIsTabStateDirty(false);
-                }
+                ((TabImpl) mTab).setIsTabStateDirty(false);
                 mTab.setIsTabSaveEnabled(isCriticalPersistedTabDataEnabled());
             }
             mSaveTabTask = null;
diff --git a/chrome/android/java/src/org/chromium/chrome/browser/tasks/ReturnToChromeExperimentsUtil.java b/chrome/android/java/src/org/chromium/chrome/browser/tasks/ReturnToChromeExperimentsUtil.java
index d877564c5..359a519 100644
--- a/chrome/android/java/src/org/chromium/chrome/browser/tasks/ReturnToChromeExperimentsUtil.java
+++ b/chrome/android/java/src/org/chromium/chrome/browser/tasks/ReturnToChromeExperimentsUtil.java
@@ -47,6 +47,7 @@
 import org.chromium.chrome.features.start_surface.StartSurfaceUserData;
 import org.chromium.components.embedder_support.util.UrlConstants;
 import org.chromium.components.embedder_support.util.UrlUtilities;
+import org.chromium.components.embedder_support.util.UrlUtilitiesJni;
 import org.chromium.components.optimization_guide.proto.ModelsProto.OptimizationTarget;
 import org.chromium.components.segmentation_platform.SegmentationPlatformService;
 import org.chromium.components.signin.identitymanager.ConsentLevel;
@@ -67,6 +68,9 @@
     @VisibleForTesting
     public static final long INVALID_DECISION_TIMESTAMP = -1L;
     public static final long MILLISECONDS_PER_DAY = TimeUtils.SECONDS_PER_DAY * 1000;
+    @VisibleForTesting
+    public static final String LAST_VISITED_TAB_IS_SRP_WHEN_OVERVIEW_IS_SHOWN_AT_LAUNCH_UMA =
+            "Startup.Android.LastVisitedTabIsSRPWhenOverviewShownAtLaunch";
 
     private static final String START_SEGMENTATION_PLATFORM_KEY = "chrome_start_android";
 
@@ -880,6 +884,17 @@
         onUIClicked(ChromePreferenceKeys.TAP_MV_TILES_COUNT);
     }
 
+    /**
+     * Record whether the last visited tab shown in the single tab switcher or carousel tab switcher
+     * is a search result page or not. This should be called when Start surface is shown at startup.
+     */
+    public static void recordLastVisitedTabIsSRPWhenOverviewIsShownAtLaunch() {
+        RecordHistogram.recordBooleanHistogram(
+                LAST_VISITED_TAB_IS_SRP_WHEN_OVERVIEW_IS_SHOWN_AT_LAUNCH_UMA,
+                UrlUtilitiesJni.get().isGoogleSearchUrl(
+                        StartSurfaceUserData.getInstance().getLastVisitedTabAtStartupUrl()));
+    }
+
     @VisibleForTesting
     public static String getBehaviourTypeKeyForTesting(String key) {
         return getBehaviourType(key);
diff --git a/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/OmahaBaseTest.java b/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/OmahaBaseTest.java
index b9ecdbef..daa94d3f 100644
--- a/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/OmahaBaseTest.java
+++ b/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/OmahaBaseTest.java
@@ -18,8 +18,10 @@
 import org.junit.runner.RunWith;
 
 import org.chromium.base.ApiCompatibilityUtils;
+import org.chromium.base.FeatureList;
 import org.chromium.base.test.util.AdvancedMockContext;
 import org.chromium.base.test.util.Feature;
+import org.chromium.chrome.browser.flags.ChromeFeatureList;
 import org.chromium.chrome.test.ChromeJUnit4ClassRunner;
 import org.chromium.chrome.test.omaha.MockRequestGenerator;
 import org.chromium.chrome.test.omaha.MockRequestGenerator.DeviceType;
@@ -188,10 +190,14 @@
         Context targetContext = InstrumentationRegistry.getTargetContext();
         OmahaBase.setIsDisabledForTesting(false);
         mContext = new AdvancedMockContext(targetContext);
+        FeatureList.TestValues overrides = new FeatureList.TestValues();
+        overrides.addFeatureFlagOverride(ChromeFeatureList.ANONYMOUS_UPDATE_CHECKS, true);
+        FeatureList.setTestValues(overrides);
     }
 
     @After
     public void tearDown() {
+        FeatureList.setTestValues(null);
         OmahaBase.setIsDisabledForTesting(true);
     }
 
diff --git a/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/RequestGeneratorTest.java b/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/RequestGeneratorTest.java
index 8abf7fc..8fac2c1 100644
--- a/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/RequestGeneratorTest.java
+++ b/chrome/android/javatests/src/org/chromium/chrome/browser/omaha/RequestGeneratorTest.java
@@ -14,13 +14,17 @@
 
 import androidx.test.filters.SmallTest;
 
+import org.junit.After;
 import org.junit.Assert;
+import org.junit.Before;
 import org.junit.Rule;
 import org.junit.Test;
 import org.junit.runner.RunWith;
 
+import org.chromium.base.FeatureList;
 import org.chromium.base.test.util.AdvancedMockContext;
 import org.chromium.base.test.util.Feature;
+import org.chromium.chrome.browser.flags.ChromeFeatureList;
 import org.chromium.chrome.browser.signin.services.IdentityServicesProvider;
 import org.chromium.chrome.browser.uid.SettingsSecureBasedIdentificationGenerator;
 import org.chromium.chrome.browser.uid.UniqueIdentificationGenerator;
@@ -42,6 +46,18 @@
     @Rule
     public final AccountManagerTestRule mAccountManagerTestRule = new AccountManagerTestRule();
 
+    @Before
+    public void setUp() {
+        FeatureList.TestValues overrides = new FeatureList.TestValues();
+        overrides.addFeatureFlagOverride(ChromeFeatureList.ANONYMOUS_UPDATE_CHECKS, true);
+        FeatureList.setTestValues(overrides);
+    }
+
+    @After
+    public void tearDown() {
+        FeatureList.setTestValues(null);
+    }
+
     @Test
     @SmallTest
     @Feature({"Omaha"})
@@ -121,6 +137,31 @@
         createAndCheckXML(DeviceType.TABLET, false);
     }
 
+    @Test
+    @SmallTest
+    @Feature({"Omaha"})
+    public void testXMLCreationWithUID() {
+        FeatureList.TestValues overrides = new FeatureList.TestValues();
+        overrides.addFeatureFlagOverride(ChromeFeatureList.ANONYMOUS_UPDATE_CHECKS, false);
+        FeatureList.setTestValues(overrides);
+        IdentityServicesProvider.setInstanceForTests(mock(IdentityServicesProvider.class));
+        when(IdentityServicesProvider.get().getIdentityManager(any()))
+                .thenReturn(mock(IdentityManager.class));
+        when(IdentityServicesProvider.get().getIdentityManager(any()).hasPrimaryAccount(anyInt()))
+                .thenReturn(true);
+        MockRequestGenerator generator = new MockRequestGenerator(
+                new AdvancedMockContext(InstrumentationRegistry.getTargetContext()),
+                DeviceType.TABLET);
+        String xml = null;
+        try {
+            xml = generator.generateXML(
+                    "", "", 0, 0, new RequestData(false, 0, "", INSTALL_SOURCE));
+        } catch (RequestFailureException e) {
+            Assert.fail("XML generation failed.");
+        }
+        checkForAttributeAndValue(xml, "request", "userid", "{" + generator.getDeviceID() + "}");
+    }
+
     /**
      * Checks that the XML is being created properly.
      */
@@ -179,8 +220,6 @@
                     checkForTag(xml, "updatecheck"));
         }
 
-        checkForAttributeAndValue(xml, "request", "userid", "{" + generator.getDeviceID() + "}");
-
         return generator;
     }
 
diff --git a/chrome/android/javatests/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabDataTest.java b/chrome/android/javatests/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabDataTest.java
index b1c2d8f..a3bd67b 100644
--- a/chrome/android/javatests/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabDataTest.java
+++ b/chrome/android/javatests/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabDataTest.java
@@ -33,7 +33,8 @@
 import org.chromium.chrome.browser.tab.TabStateExtractor;
 import org.chromium.chrome.browser.tab.TabUserAgent;
 import org.chromium.chrome.browser.tab.WebContentsState;
-import org.chromium.chrome.browser.tab.proto.CriticalPersistedTabData.CriticalPersistedTabDataProto;
+import org.chromium.chrome.browser.tab.flatbuffer.LaunchTypeAtCreation;
+import org.chromium.chrome.browser.tab.flatbuffer.UserAgentType;
 import org.chromium.chrome.test.ChromeTabbedActivityTestRule;
 import org.chromium.chrome.test.batch.BlankCTATabInitialStateRule;
 import org.chromium.components.embedder_support.util.UrlConstants;
@@ -311,16 +312,31 @@
     @SmallTest
     @Test
     public void testWebContentsStateBug_crbug_1220839() throws InterruptedException {
+        PersistedTabDataConfiguration.setUseTestConfig(false);
         String url = mTestServer.getURL("/chrome/test/data/browsing_data/e.html");
         Tab tab = sActivityTestRule.loadUrlInNewTab(url);
+        final Semaphore semaphore = new Semaphore(0);
+        // Saving serialized CriticalPersistedTabData ensures we get a direct ByteBuffer
+        // which is assumed in the rest of Clank. See crbug.com/1220839 for more details.
         ThreadUtils.runOnUiThreadBlocking(() -> {
             CriticalPersistedTabData criticalPersistedTabData =
                     new CriticalPersistedTabData(tab, "", "", PARENT_ID, ROOT_ID, TIMESTAMP,
                             TabStateExtractor.getWebContentsState(tab), CONTENT_STATE_VERSION,
                             OPENER_APP_ID, THEME_COLOR, LAUNCH_TYPE_AT_CREATION, USER_AGENT_A);
-            ByteBuffer serialized = criticalPersistedTabData.getSerializeSupplier().get();
             PersistedTabDataConfiguration config = PersistedTabDataConfiguration.get(
-                    ShoppingPersistedTabData.class, tab.isIncognito());
+                    CriticalPersistedTabData.class, tab.isIncognito());
+            FilePersistedTabDataStorage persistedTabDataStorage = new FilePersistedTabDataStorage();
+            persistedTabDataStorage.save(tab.getId(), config.getId(), () -> {
+                return criticalPersistedTabData.getSerializeSupplier().get();
+            }, semaphore::release);
+        });
+        semaphore.acquire();
+        ThreadUtils.runOnUiThreadBlocking(() -> {
+            PersistedTabDataConfiguration config = PersistedTabDataConfiguration.get(
+                    CriticalPersistedTabData.class, tab.isIncognito());
+
+            ByteBuffer serialized =
+                    CriticalPersistedTabData.restore(tab.getId(), tab.isIncognito());
             CriticalPersistedTabData deserialized = new CriticalPersistedTabData(
                     tab, serialized, config.getStorage(), config.getId());
             Assert.assertEquals(
@@ -581,9 +597,8 @@
     @SmallTest
     @Test
     public void testConvertProtoLaunchTypeToTabLaunchType() {
-        for (CriticalPersistedTabDataProto.LaunchTypeAtCreation type :
-                CriticalPersistedTabDataProto.LaunchTypeAtCreation.values()) {
-            if (type == CriticalPersistedTabDataProto.LaunchTypeAtCreation.UNKNOWN) continue;
+        for (int type = 0; type < LaunchTypeAtCreation.names.length; type++) {
+            if (type == LaunchTypeAtCreation.UNKNOWN) continue;
             CriticalPersistedTabData.getLaunchType(type);
         }
     }
@@ -593,37 +608,24 @@
     public void testConvertTabUserAgentToProtoUserAgentType() {
         for (@TabUserAgent int tabUserAgent = 0; tabUserAgent <= TabUserAgent.SIZE;
                 tabUserAgent++) {
-            CriticalPersistedTabDataProto.UserAgentType protoUserAgentType =
-                    CriticalPersistedTabData.getUserAgentType(tabUserAgent);
-            if (tabUserAgent == TabUserAgent.DEFAULT) {
-                Assert.assertEquals("TabUserAgent value is mapped incorrectly.", protoUserAgentType,
-                        CriticalPersistedTabDataProto.UserAgentType.DEFAULT);
-            } else {
-                Assert.assertNotEquals("TabUserAgent value is invalid.", protoUserAgentType,
-                        CriticalPersistedTabDataProto.UserAgentType.DEFAULT);
-            }
+            int flatBufferUserAgentType = CriticalPersistedTabData.getUserAgentType(tabUserAgent);
+            Assert.assertNotEquals("TabUserAgent value is invalid.", flatBufferUserAgentType,
+                    UserAgentType.USER_AGENT_UNKNOWN);
             if (tabUserAgent != TabUserAgent.SIZE) continue;
             Assert.assertEquals("TabUserAgent and ProtoUserAgentType should have the same size.",
-                    protoUserAgentType,
-                    CriticalPersistedTabDataProto.UserAgentType.USER_AGENT_SIZE);
+                    flatBufferUserAgentType, UserAgentType.USER_AGENT_SIZE);
         }
     }
 
     @SmallTest
     @Test
     public void testConvertProtoUserAgentTypeToTabUserAgent() {
-        for (CriticalPersistedTabDataProto.UserAgentType type :
-                CriticalPersistedTabDataProto.UserAgentType.values()) {
+        for (int type = 0; type < UserAgentType.names.length; type++) {
+            if (type == UserAgentType.USER_AGENT_UNKNOWN) continue;
             @TabUserAgent
-            int tabUserAgent = CriticalPersistedTabData.getUserAgentType(type);
-            if (type == CriticalPersistedTabDataProto.UserAgentType.DEFAULT) {
-                Assert.assertEquals("ProtoUserAgentType value is mapped incorrectly.", tabUserAgent,
-                        TabUserAgent.DEFAULT);
-            } else {
-                Assert.assertNotEquals(
-                        "ProtoUserAgentType value is invalid.", tabUserAgent, TabUserAgent.DEFAULT);
-            }
-            if (type != CriticalPersistedTabDataProto.UserAgentType.USER_AGENT_SIZE) continue;
+            int tabUserAgent = CriticalPersistedTabData.getTabUserAgentType(type);
+            Assert.assertNotNull("ProtoUserAgentType value is invalid.", tabUserAgent);
+            if (type != UserAgentType.USER_AGENT_SIZE) continue;
             Assert.assertEquals("TabUserAgent and ProtoUserAgentType should have the same size.",
                     tabUserAgent, TabUserAgent.SIZE);
         }
diff --git a/chrome/android/javatests/src/org/chromium/chrome/browser/tabmodel/TabPersistentStoreUnitTest.java b/chrome/android/javatests/src/org/chromium/chrome/browser/tabmodel/TabPersistentStoreUnitTest.java
index 254f778..565cac0 100644
--- a/chrome/android/javatests/src/org/chromium/chrome/browser/tabmodel/TabPersistentStoreUnitTest.java
+++ b/chrome/android/javatests/src/org/chromium/chrome/browser/tabmodel/TabPersistentStoreUnitTest.java
@@ -41,7 +41,6 @@
 import org.chromium.chrome.browser.tab.TabImpl;
 import org.chromium.chrome.browser.tab.TabLaunchType;
 import org.chromium.chrome.browser.tab.TabState;
-import org.chromium.chrome.browser.tab.TabStateAttributes;
 import org.chromium.chrome.browser.tabmodel.TabPersistentStore.TabModelSelectorMetadata;
 import org.chromium.chrome.browser.tabmodel.TabPersistentStore.TabRestoreDetails;
 import org.chromium.components.embedder_support.util.UrlConstants;
@@ -137,7 +136,7 @@
 
         TabImpl emptyNtpTab = mock(TabImpl.class);
         when(emptyNtpTab.getUrl()).thenReturn(new GURL(UrlConstants.NTP_URL));
-        TabStateAttributes.from(emptyNtpTab).setIsTabStateDirty(true);
+        when(emptyNtpTab.isTabStateDirty()).thenReturn(true);
         when(emptyNtpTab.canGoBack()).thenReturn(false);
         when(emptyNtpTab.canGoForward()).thenReturn(false);
 
@@ -146,7 +145,7 @@
 
         TabImpl ntpWithBackNavTab = mock(TabImpl.class);
         when(ntpWithBackNavTab.getUrl()).thenReturn(new GURL(UrlConstants.NTP_URL));
-        TabStateAttributes.from(ntpWithBackNavTab).setIsTabStateDirty(true);
+        when(ntpWithBackNavTab.isTabStateDirty()).thenReturn(true);
         when(ntpWithBackNavTab.canGoBack()).thenReturn(true);
         when(ntpWithBackNavTab.canGoForward()).thenReturn(false);
 
@@ -155,7 +154,7 @@
 
         TabImpl ntpWithForwardNavTab = mock(TabImpl.class);
         when(ntpWithForwardNavTab.getUrl()).thenReturn(new GURL(UrlConstants.NTP_URL));
-        TabStateAttributes.from(ntpWithForwardNavTab).setIsTabStateDirty(true);
+        when(ntpWithForwardNavTab.isTabStateDirty()).thenReturn(true);
         when(ntpWithForwardNavTab.canGoBack()).thenReturn(false);
         when(ntpWithForwardNavTab.canGoForward()).thenReturn(true);
 
@@ -164,7 +163,7 @@
 
         TabImpl ntpWithAllTheNavsTab = mock(TabImpl.class);
         when(ntpWithAllTheNavsTab.getUrl()).thenReturn(new GURL(UrlConstants.NTP_URL));
-        TabStateAttributes.from(ntpWithAllTheNavsTab).setIsTabStateDirty(true);
+        when(ntpWithAllTheNavsTab.isTabStateDirty()).thenReturn(true);
         when(ntpWithAllTheNavsTab.canGoBack()).thenReturn(true);
         when(ntpWithAllTheNavsTab.canGoForward()).thenReturn(true);
 
diff --git a/chrome/android/junit/src/org/chromium/chrome/browser/tab/TabUnitTest.java b/chrome/android/junit/src/org/chromium/chrome/browser/tab/TabUnitTest.java
index ccf2a54..7e70563 100644
--- a/chrome/android/junit/src/org/chromium/chrome/browser/tab/TabUnitTest.java
+++ b/chrome/android/junit/src/org/chromium/chrome/browser/tab/TabUnitTest.java
@@ -119,21 +119,21 @@
         verify(mCriticalPersistedTabDataObserver).onRootIdChanged(mTab, TAB2_ID);
 
         assertThat(CriticalPersistedTabData.from(mTab).getRootId(), equalTo(TAB2_ID));
-        assertThat(TabStateAttributes.from(mTab).isTabStateDirty(), equalTo(true));
+        assertThat(mTab.isTabStateDirty(), equalTo(true));
     }
 
     @Test
     @SmallTest
     public void testSetRootIdWithoutChange() {
         assertThat(CriticalPersistedTabData.from(mTab).getRootId(), equalTo(TAB1_ID));
-        TabStateAttributes.from(mTab).setIsTabStateDirty(false);
+        mTab.setIsTabStateDirty(false);
 
         CriticalPersistedTabData.from(mTab).setRootId(TAB1_ID);
 
         verify(mCriticalPersistedTabDataObserver, never())
                 .onRootIdChanged(any(Tab.class), anyInt());
         assertThat(CriticalPersistedTabData.from(mTab).getRootId(), equalTo(TAB1_ID));
-        assertThat(TabStateAttributes.from(mTab).isTabStateDirty(), equalTo(false));
+        assertThat(mTab.isTabStateDirty(), equalTo(false));
     }
 
     @Test
diff --git a/chrome/android/static_initializers.gni b/chrome/android/static_initializers.gni
index cf8ea29..977465e 100644
--- a/chrome/android/static_initializers.gni
+++ b/chrome/android/static_initializers.gni
@@ -20,12 +20,9 @@
   # Comments show static_initializers according to
   # tools/linux/dump-static-initializers.py.
 
-  # 000101 (initializer offset 0x142e924 size 0xc)
-  # std::__1::ios_base::Init::Init()
-  #
   # iostream.cpp (initializer offset 0x142e930 size 0x2)
   #   [empty ctor, but it still has cost on gcc <4.6]
-  expected_static_initializer_count = 2
+  expected_static_initializer_count = 1
 
   # TODO(https://crbug.com/1177849): Remove from tflite:
   # tflite_engine.cc (initializer offset 0x34cb88c size 0x2c)
diff --git a/chrome/browser/BUILD.gn b/chrome/browser/BUILD.gn
index c6cb2db..fa185249 100644
--- a/chrome/browser/BUILD.gn
+++ b/chrome/browser/BUILD.gn
@@ -1645,10 +1645,6 @@
     "signin/identity_manager_factory.h",
     "signin/investigator_dependency_provider.cc",
     "signin/investigator_dependency_provider.h",
-    "signin/primary_account_policy_manager.cc",
-    "signin/primary_account_policy_manager.h",
-    "signin/primary_account_policy_manager_factory.cc",
-    "signin/primary_account_policy_manager_factory.h",
     "signin/reauth_result.h",
     "signin/reauth_tab_helper.cc",
     "signin/reauth_tab_helper.h",
@@ -1939,7 +1935,6 @@
     "//base/allocator:buildflags",
     "//build:branding_buildflags",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//build/config/compiler:compiler_buildflags",
     "//cc",
     "//chrome:extra_resources",
diff --git a/chrome/browser/android/customtabs/custom_tabs_browsertest.cc b/chrome/browser/android/customtabs/custom_tabs_browsertest.cc
index 2d8129e..5b1ec79 100644
--- a/chrome/browser/android/customtabs/custom_tabs_browsertest.cc
+++ b/chrome/browser/android/customtabs/custom_tabs_browsertest.cc
@@ -2,7 +2,8 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/run_loop.h"
 #include "base/strings/string_number_conversions.h"
 #include "base/strings/string_util.h"
@@ -94,7 +95,7 @@
     auto* web_contents = content::WebContents::FromRenderFrameHost(host);
     ClientDataHeaderWebContentsObserver::FromWebContents(web_contents)
         ->SetHeader(kHeaderValue2);
-    ignore_result(ExecJs(host, "document.images[0].src = 'google3.jpg'"));
+    std::ignore = ExecJs(host, "document.images[0].src = 'google3.jpg'");
   }
 
  private:
diff --git a/chrome/browser/apps/app_service/media_access_browsertest.cc b/chrome/browser/apps/app_service/media_access_browsertest.cc
index 7e1afa9..f6bc1ab 100644
--- a/chrome/browser/apps/app_service/media_access_browsertest.cc
+++ b/chrome/browser/apps/app_service/media_access_browsertest.cc
@@ -288,7 +288,7 @@
 
   // Request accessing the camera for |web_contents|.
   MediaRequestChangeForWebContent(
-      web_contents, web_contents->GetLastCommittedURL(),
+      web_contents, web_contents->GetVisibleURL(),
       blink::mojom::MediaStreamType::DEVICE_VIDEO_CAPTURE,
       content::MEDIA_REQUEST_STATE_DONE);
 
@@ -297,7 +297,7 @@
 
   // Request accessing the microphone for |web_contents|.
   MediaRequestChangeForWebContent(
-      web_contents, web_contents->GetLastCommittedURL(),
+      web_contents, web_contents->GetVisibleURL(),
       blink::mojom::MediaStreamType::DEVICE_AUDIO_CAPTURE,
       content::MEDIA_REQUEST_STATE_DONE);
 
@@ -306,7 +306,7 @@
 
   // Stop accessing the microphone for |web_contents|.
   MediaRequestChangeForWebContent(
-      web_contents, web_contents->GetLastCommittedURL(),
+      web_contents, web_contents->GetVisibleURL(),
       blink::mojom::MediaStreamType::DEVICE_AUDIO_CAPTURE,
       content::MEDIA_REQUEST_STATE_CLOSING);
 
@@ -315,7 +315,7 @@
 
   // Stop accessing the camera for |web_contents|.
   MediaRequestChangeForWebContent(
-      web_contents, web_contents->GetLastCommittedURL(),
+      web_contents, web_contents->GetVisibleURL(),
       blink::mojom::MediaStreamType::DEVICE_VIDEO_CAPTURE,
       content::MEDIA_REQUEST_STATE_CLOSING);
 
diff --git a/chrome/browser/apps/app_service/publishers/arc_apps_unittest.cc b/chrome/browser/apps/app_service/publishers/arc_apps_unittest.cc
index 96d244a..5ff34f35 100644
--- a/chrome/browser/apps/app_service/publishers/arc_apps_unittest.cc
+++ b/chrome/browser/apps/app_service/publishers/arc_apps_unittest.cc
@@ -111,7 +111,8 @@
 
 // Verifies that a call to set the supported links preference from ARC persists
 // the setting in app service.
-TEST_F(ArcAppsPublisherTest, SetSupportedLinksFromArc) {
+// Flaky: https://crbug.com/1285361.
+TEST_F(ArcAppsPublisherTest, DISABLED_SetSupportedLinksFromArc) {
   constexpr char kTestAuthority[] = "www.example.com";
   const auto& fake_apps = arc_test()->fake_apps();
   std::string package_name = fake_apps[0].package_name;
diff --git a/chrome/browser/ash/accessibility/dictation_browsertest.cc b/chrome/browser/ash/accessibility/dictation_browsertest.cc
index 32cfe60..fa966a9 100644
--- a/chrome/browser/ash/accessibility/dictation_browsertest.cc
+++ b/chrome/browser/ash/accessibility/dictation_browsertest.cc
@@ -286,6 +286,12 @@
   DictationTest(const DictationTest&) = delete;
   DictationTest& operator=(const DictationTest&) = delete;
 
+  void SetUpCommandLine(base::CommandLine* command_line) override {
+    DictationBaseTest::SetUpCommandLine(command_line);
+    scoped_feature_list_.InitAndDisableFeature(
+        ::features::kExperimentalAccessibilityDictationExtension);
+  }
+
   void SetUpOnMainThread() override {
     DictationBaseTest::SetUpOnMainThread();
 
@@ -340,6 +346,7 @@
   std::unique_ptr<ui::MockIMEInputContextHandler> input_context_handler_;
   std::unique_ptr<ui::test::EventGenerator> generator_;
   ui::CompositionText empty_composition_text_;
+  base::test::ScopedFeatureList scoped_feature_list_;
 };
 
 INSTANTIATE_TEST_SUITE_P(
diff --git a/chrome/browser/ash/app_mode/kiosk_profile_loader.cc b/chrome/browser/ash/app_mode/kiosk_profile_loader.cc
index 49d06b07..0eb84ed5 100644
--- a/chrome/browser/ash/app_mode/kiosk_profile_loader.cc
+++ b/chrome/browser/ash/app_mode/kiosk_profile_loader.cc
@@ -5,11 +5,11 @@
 #include "chrome/browser/ash/app_mode/kiosk_profile_loader.h"
 
 #include <memory>
+#include <tuple>
 
 #include "ash/components/login/auth/auth_status_consumer.h"
 #include "ash/components/login/auth/user_context.h"
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/location.h"
 #include "base/logging.h"
 #include "base/memory/weak_ptr.h"
@@ -179,7 +179,7 @@
 void KioskProfileLoader::OnAuthSuccess(const UserContext& user_context) {
   // LoginPerformer will delete itself.
   login_performer_->set_delegate(NULL);
-  ignore_result(login_performer_.release());
+  std::ignore = login_performer_.release();
 
   failed_mount_attempts_ = 0;
 
diff --git a/chrome/browser/ash/file_system_provider/operations/get_metadata.cc b/chrome/browser/ash/file_system_provider/operations/get_metadata.cc
index d691b88..9e4621c 100644
--- a/chrome/browser/ash/file_system_provider/operations/get_metadata.cc
+++ b/chrome/browser/ash/file_system_provider/operations/get_metadata.cc
@@ -9,9 +9,9 @@
 #include <algorithm>
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 
-#include "base/ignore_result.h"
 #include "chrome/common/extensions/api/file_system_provider.h"
 #include "chrome/common/extensions/api/file_system_provider_internal.h"
 
@@ -55,8 +55,8 @@
     // Allow to pass invalid modification time, since there is no way to verify
     // it easily on any earlier stage.
     base::Time output_modification_time;
-    ignore_result(base::Time::FromString(input_modification_time.c_str(),
-                                         &output_modification_time));
+    std::ignore = base::Time::FromString(input_modification_time.c_str(),
+                                         &output_modification_time);
     output->modification_time =
         std::make_unique<base::Time>(output_modification_time);
   }
diff --git a/chrome/browser/ash/login/existing_user_controller.cc b/chrome/browser/ash/login/existing_user_controller.cc
index 1053ec8..8079f64 100644
--- a/chrome/browser/ash/login/existing_user_controller.cc
+++ b/chrome/browser/ash/login/existing_user_controller.cc
@@ -5,6 +5,7 @@
 #include "chrome/browser/ash/login/existing_user_controller.h"
 
 #include <memory>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -23,7 +24,6 @@
 #include "base/callback_helpers.h"
 #include "base/command_line.h"
 #include "base/compiler_specific.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/metrics/histogram_functions.h"
 #include "base/scoped_observation.h"
@@ -911,7 +911,7 @@
 
   // LoginPerformer instance will delete itself in case of successful auth.
   login_performer_->set_delegate(nullptr);
-  ignore_result(login_performer_.release());
+  std::ignore = login_performer_.release();
 
   if (user_context.GetAuthFlow() == UserContext::AUTH_FLOW_OFFLINE) {
     base::UmaHistogramCounts100("Login.OfflineSuccess.Attempts",
diff --git a/chrome/browser/ash/login/users/chrome_user_manager_impl.cc b/chrome/browser/ash/login/users/chrome_user_manager_impl.cc
index 21c2a46..3eb1ef1 100644
--- a/chrome/browser/ash/login/users/chrome_user_manager_impl.cc
+++ b/chrome/browser/ash/login/users/chrome_user_manager_impl.cc
@@ -8,6 +8,7 @@
 
 #include <memory>
 #include <set>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -25,7 +26,6 @@
 #include "base/containers/span.h"
 #include "base/feature_list.h"
 #include "base/format_macros.h"
-#include "base/ignore_result.h"
 #include "base/location.h"
 #include "base/logging.h"
 #include "base/memory/ptr_util.h"
@@ -162,7 +162,7 @@
 // Runs on SequencedWorkerPool thread. Passes resolved locale to UI thread.
 void ResolveLocale(const std::string& raw_locale,
                    std::string* resolved_locale) {
-  ignore_result(l10n_util::CheckAndResolveLocale(raw_locale, resolved_locale));
+  std::ignore = l10n_util::CheckAndResolveLocale(raw_locale, resolved_locale);
 }
 
 bool GetUserLockAttributes(const user_manager::User* user,
diff --git a/chrome/browser/ash/settings/device_settings_provider.cc b/chrome/browser/ash/settings/device_settings_provider.cc
index a613af3f..1d9742c8e 100644
--- a/chrome/browser/ash/settings/device_settings_provider.cc
+++ b/chrome/browser/ash/settings/device_settings_provider.cc
@@ -154,6 +154,7 @@
     kReportDeviceSystemInfo,
     kReportDevicePrintJobs,
     kReportDeviceLoginLogout,
+    kReportCRDSessions,
     kReportOsUpdateStatus,
     kReportRunningKioskApp,
     kReportUploadFrequency,
diff --git a/chrome/browser/ash/smb_client/smb_service_unittest.cc b/chrome/browser/ash/smb_client/smb_service_unittest.cc
index 6626467..9b04c7c1 100644
--- a/chrome/browser/ash/smb_client/smb_service_unittest.cc
+++ b/chrome/browser/ash/smb_client/smb_service_unittest.cc
@@ -7,6 +7,7 @@
 #include <stddef.h>
 
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "ash/components/disks/disk_mount_manager.h"
@@ -15,7 +16,6 @@
 #include "base/bind.h"
 #include "base/callback_helpers.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/memory/ptr_util.h"
 #include "base/run_loop.h"
@@ -710,10 +710,10 @@
         std::string(kSharePath) + base::NumberToString(i);
     const std::string mount_path =
         std::string(kMountPath) + base::NumberToString(i);
-    ignore_result(MountBasicShare(share_path, mount_path,
+    std::ignore = MountBasicShare(share_path, mount_path,
                                   base::BindOnce([](SmbMountResult result) {
                                     EXPECT_EQ(SmbMountResult::kSuccess, result);
-                                  })));
+                                  }));
   }
 
   // Check: After mounting the maximum number of shares, requesting to mount an
@@ -722,24 +722,24 @@
       std::string(kSharePath) + base::NumberToString(kMaxSmbFsShares);
   const std::string mount_path =
       std::string(kMountPath) + base::NumberToString(kMaxSmbFsShares);
-  ignore_result(MountBasicShare(
+  std::ignore = MountBasicShare(
       share_path, mount_path, base::BindOnce([](SmbMountResult result) {
         EXPECT_EQ(SmbMountResult::kTooManyOpened, result);
-      })));
+      }));
 }
 
 TEST_F(SmbServiceWithSmbfsTest, GetSmbFsShareForPath) {
   CreateService(profile_);
   WaitForSetupComplete();
 
-  ignore_result(MountBasicShare(kSharePath, kMountPath,
+  std::ignore = MountBasicShare(kSharePath, kMountPath,
                                 base::BindOnce([](SmbMountResult result) {
                                   EXPECT_EQ(SmbMountResult::kSuccess, result);
-                                })));
-  ignore_result(MountBasicShare(kSharePath2, kMountPath2,
+                                }));
+  std::ignore = MountBasicShare(kSharePath2, kMountPath2,
                                 base::BindOnce([](SmbMountResult result) {
                                   EXPECT_EQ(SmbMountResult::kSuccess, result);
-                                })));
+                                }));
 
   SmbFsShare* share =
       smb_service_->GetSmbFsShareForPath(base::FilePath(kMountPath));
@@ -764,23 +764,23 @@
   CreateService(profile_);
   WaitForSetupComplete();
 
-  ignore_result(MountBasicShare(kSharePath, kMountPath,
+  std::ignore = MountBasicShare(kSharePath, kMountPath,
                                 base::BindOnce([](SmbMountResult result) {
                                   EXPECT_EQ(SmbMountResult::kSuccess, result);
-                                })));
+                                }));
 
   // A second mount with the same share path should fail.
-  ignore_result(MountBasicShare(
+  std::ignore = MountBasicShare(
       kSharePath, kMountPath2, base::BindOnce([](SmbMountResult result) {
         EXPECT_EQ(SmbMountResult::kMountExists, result);
-      })));
+      }));
 
   // Unmounting and mounting again should succeed.
   smb_service_->UnmountSmbFs(base::FilePath(kMountPath));
-  ignore_result(MountBasicShare(kSharePath, kMountPath2,
+  std::ignore = MountBasicShare(kSharePath, kMountPath2,
                                 base::BindOnce([](SmbMountResult result) {
                                   EXPECT_EQ(SmbMountResult::kSuccess, result);
-                                })));
+                                }));
 }
 
 }  // namespace smb_client
diff --git a/chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.cc b/chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.cc
new file mode 100644
index 0000000..40a333bb
--- /dev/null
+++ b/chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.cc
@@ -0,0 +1,47 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.h"
+
+#include "ash/style/ash_color_provider.h"
+#include "chrome/browser/profiles/profile.h"
+
+ChromePersonalizationAppThemeProvider::ChromePersonalizationAppThemeProvider(
+    content::WebUI* web_ui)
+    : web_ui_(web_ui), profile_(Profile::FromWebUI(web_ui_)) {}
+
+ChromePersonalizationAppThemeProvider::
+    ~ChromePersonalizationAppThemeProvider() = default;
+
+void ChromePersonalizationAppThemeProvider::BindInterface(
+    mojo::PendingReceiver<ash::personalization_app::mojom::ThemeProvider>
+        receiver) {
+  theme_receiver_.reset();
+  theme_receiver_.Bind(std::move(receiver));
+}
+
+void ChromePersonalizationAppThemeProvider::SetThemeObserver(
+    mojo::PendingRemote<ash::personalization_app::mojom::ThemeObserver>
+        observer) {
+  // May already be bound if user refreshes page.
+  theme_observer_remote_.reset();
+  theme_observer_remote_.Bind(std::move(observer));
+  if (!color_mode_observer_.IsObserving())
+    color_mode_observer_.Observe(ash::AshColorProvider::Get());
+  // Call it once to get the current color mode.
+  OnColorModeChanged(ash::ColorProvider::Get()->IsDarkModeEnabled());
+}
+
+void ChromePersonalizationAppThemeProvider::OnColorModeChanged(
+    bool dark_mode_enabled) {
+  DCHECK(theme_observer_remote_.is_bound());
+  theme_observer_remote_->OnColorModeChanged(dark_mode_enabled);
+}
+
+void ChromePersonalizationAppThemeProvider::SetColorModePref(
+    bool dark_mode_enabled) {
+  auto* color_provider = ash::AshColorProvider::Get();
+  if (color_provider->IsDarkModeEnabled() != dark_mode_enabled)
+    color_provider->ToggleColorMode();
+}
diff --git a/chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.h b/chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.h
new file mode 100644
index 0000000..e82fbb5
--- /dev/null
+++ b/chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.h
@@ -0,0 +1,65 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef CHROME_BROWSER_ASH_WEB_APPLICATIONS_PERSONALIZATION_APP_CHROME_PERSONALIZATION_APP_THEME_PROVIDER_H_
+#define CHROME_BROWSER_ASH_WEB_APPLICATIONS_PERSONALIZATION_APP_CHROME_PERSONALIZATION_APP_THEME_PROVIDER_H_
+
+#include "ash/public/cpp/style/color_mode_observer.h"
+#include "ash/public/cpp/style/color_provider.h"
+#include "ash/webui/personalization_app/personalization_app_theme_provider.h"
+#include "base/scoped_observation.h"
+#include "mojo/public/cpp/bindings/receiver.h"
+#include "mojo/public/cpp/bindings/remote.h"
+
+class Profile;
+
+namespace content {
+class WebUI;
+}  // namespace content
+
+class ChromePersonalizationAppThemeProvider
+    : public ash::PersonalizationAppThemeProvider,
+      ash::ColorModeObserver {
+ public:
+  explicit ChromePersonalizationAppThemeProvider(content::WebUI* web_ui);
+
+  ChromePersonalizationAppThemeProvider(
+      const ChromePersonalizationAppThemeProvider&) = delete;
+  ChromePersonalizationAppThemeProvider& operator=(
+      const ChromePersonalizationAppThemeProvider&) = delete;
+
+  ~ChromePersonalizationAppThemeProvider() override;
+
+  // PersonalizationAppThemeProvider:
+  void BindInterface(
+      mojo::PendingReceiver<ash::personalization_app::mojom::ThemeProvider>
+          receiver) override;
+
+  // ash::personalization_app::mojom::ThemeProvider:
+  void SetThemeObserver(
+      mojo::PendingRemote<ash::personalization_app::mojom::ThemeObserver>
+          observer) override;
+
+  void SetColorModePref(bool dark_mode_enabled) override;
+
+  // ash::ColorModeObserver:
+  void OnColorModeChanged(bool dark_mode_enabled) override;
+
+ private:
+  content::WebUI* const web_ui_ = nullptr;
+
+  // Pointer to profile of user that opened personalization SWA. Not owned.
+  Profile* const profile_ = nullptr;
+
+  base::ScopedObservation<ash::ColorProvider, ash::ColorModeObserver>
+      color_mode_observer_{this};
+
+  mojo::Receiver<ash::personalization_app::mojom::ThemeProvider>
+      theme_receiver_{this};
+
+  mojo::Remote<ash::personalization_app::mojom::ThemeObserver>
+      theme_observer_remote_;
+};
+
+#endif  // CHROME_BROWSER_ASH_WEB_APPLICATIONS_PERSONALIZATION_APP_CHROME_PERSONALIZATION_APP_THEME_PROVIDER_H_
diff --git a/chrome/browser/autofill/autofill_browsertest.cc b/chrome/browser/autofill/autofill_browsertest.cc
index bb45dea..d868e8f3 100644
--- a/chrome/browser/autofill/autofill_browsertest.cc
+++ b/chrome/browser/autofill/autofill_browsertest.cc
@@ -6,10 +6,10 @@
 
 #include <memory>
 #include <string>
+#include <tuple>
 
 #include "base/command_line.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/memory/ref_counted.h"
 #include "base/rand_util.h"
@@ -872,9 +872,9 @@
 
   int host_id = prerender_helper().AddPrerender(prerender_url);
   auto* rfh = prerender_helper().GetPrerenderedMainFrameHost(host_id);
-  ignore_result(
+  std::ignore =
       content::ExecJs(rfh, "document.querySelector('#NAME_FIRST').focus();",
-                      content::EXECUTE_SCRIPT_NO_USER_GESTURE));
+                      content::EXECUTE_SCRIPT_NO_USER_GESTURE);
 
   // Since the initial prerender page load has finished at this point and we
   // have issued our programmatic focus, we need to check that the expectations
diff --git a/chrome/browser/browsing_data/access_context_audit_database.cc b/chrome/browser/browsing_data/access_context_audit_database.cc
index 8b67a6b..70fbe5a 100644
--- a/chrome/browser/browsing_data/access_context_audit_database.cc
+++ b/chrome/browser/browsing_data/access_context_audit_database.cc
@@ -4,8 +4,9 @@
 
 #include "chrome/browser/browsing_data/access_context_audit_database.h"
 
+#include <tuple>
+
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/metrics/histogram_functions.h"
 #include "base/rand_util.h"
@@ -43,7 +44,7 @@
     // or hardware issues, not coding errors at the client level, so displaying
     // the error would probably lead to confusion.  The ignored call signals the
     // test-expectation framework that the error was handled.
-    ignore_result(sql::Database::IsExpectedSqliteError(extended_error));
+    std::ignore = sql::Database::IsExpectedSqliteError(extended_error);
     return;
   }
 
diff --git a/chrome/browser/captive_portal/captive_portal_browsertest.cc b/chrome/browser/captive_portal/captive_portal_browsertest.cc
index 1d99805d..d798dce 100644
--- a/chrome/browser/captive_portal/captive_portal_browsertest.cc
+++ b/chrome/browser/captive_portal/captive_portal_browsertest.cc
@@ -9,6 +9,7 @@
 #include <memory>
 #include <set>
 #include <string>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -18,7 +19,6 @@
 #include "base/compiler_specific.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/path_service.h"
 #include "base/run_loop.h"
@@ -916,7 +916,7 @@
     EXPECT_EQ(expected_num_jobs,
               static_cast<int>(ongoing_mock_requests_.size()));
     for (auto& job : ongoing_mock_requests_)
-      ignore_result(job.client.Unbind().PassPipe().release());
+      std::ignore = job.client.Unbind().PassPipe().release();
     ongoing_mock_requests_.clear();
   }
 
diff --git a/chrome/browser/chrome_browser_interface_binders.cc b/chrome/browser/chrome_browser_interface_binders.cc
index 80e960e..e792281 100644
--- a/chrome/browser/chrome_browser_interface_binders.cc
+++ b/chrome/browser/chrome_browser_interface_binders.cc
@@ -975,6 +975,12 @@
         ash::PersonalizationAppUI>(map);
   }
 
+  if (ash::features::IsPersonalizationHubEnabled()) {
+    RegisterWebUIControllerInterfaceBinder<
+        ash::personalization_app::mojom::ThemeProvider,
+        ash::PersonalizationAppUI>(map);
+  }
+
   RegisterWebUIControllerInterfaceBinder<
       launcher_internals::mojom::PageHandlerFactory,
       chromeos::LauncherInternalsUI>(map);
diff --git a/chrome/browser/chrome_browser_main.cc b/chrome/browser/chrome_browser_main.cc
index e194037..712138e 100644
--- a/chrome/browser/chrome_browser_main.cc
+++ b/chrome/browser/chrome_browser_main.cc
@@ -10,6 +10,7 @@
 #include <memory>
 #include <set>
 #include <string>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -24,7 +25,6 @@
 #include "base/feature_list.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/memory/ptr_util.h"
 #include "base/memory/scoped_refptr.h"
@@ -1867,7 +1867,7 @@
   // The below call to browser_shutdown::ShutdownPostThreadsStop() deletes
   // |browser_process_|. We release it so that we don't keep holding onto an
   // invalid reference.
-  ignore_result(browser_process_.release());
+  std::ignore = browser_process_.release();
 
 #if BUILDFLAG(ENABLE_DOWNGRADE_PROCESSING)
   if (result_code_ == chrome::RESULT_CODE_DOWNGRADE_AND_RELAUNCH) {
diff --git a/chrome/browser/chrome_security_exploit_browsertest.cc b/chrome/browser/chrome_security_exploit_browsertest.cc
index e0bc0c3..8902f577 100644
--- a/chrome/browser/chrome_security_exploit_browsertest.cc
+++ b/chrome/browser/chrome_security_exploit_browsertest.cc
@@ -2,9 +2,10 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
+
 #include "base/bind.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/memory/ptr_util.h"
 #include "base/memory/raw_ptr.h"
 #include "base/run_loop.h"
@@ -500,8 +501,8 @@
 
   // The renderer should always get killed, but sometimes ExecuteScript returns
   // true anyway, so just ignore the result.
-  ignore_result(
-      content::ExecuteScript(rfh, "URL.createObjectURL(new Blob(['foo']))"));
+  std::ignore =
+      content::ExecuteScript(rfh, "URL.createObjectURL(new Blob(['foo']))");
 
   // If the process is killed, this test passes.
   EXPECT_EQ(
@@ -544,8 +545,8 @@
 
   // The renderer should always get killed, but sometimes ExecuteScript returns
   // true anyway, so just ignore the result.
-  ignore_result(
-      content::ExecuteScript(rfh, "URL.createObjectURL(new Blob(['foo']))"));
+  std::ignore =
+      content::ExecuteScript(rfh, "URL.createObjectURL(new Blob(['foo']))");
 
   // If the process is killed, this test passes.
   EXPECT_EQ(
diff --git a/chrome/browser/chromeos/BUILD.gn b/chrome/browser/chromeos/BUILD.gn
index d4e3b674..ffb4574 100644
--- a/chrome/browser/chromeos/BUILD.gn
+++ b/chrome/browser/chromeos/BUILD.gn
@@ -3195,6 +3195,8 @@
     "../ash/web_applications/os_settings_web_app_info.h",
     "../ash/web_applications/os_url_handler_system_web_app_info.cc",
     "../ash/web_applications/os_url_handler_system_web_app_info.h",
+    "../ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.cc",
+    "../ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.h",
     "../ash/web_applications/personalization_app/chrome_personalization_app_wallpaper_provider.cc",
     "../ash/web_applications/personalization_app/chrome_personalization_app_wallpaper_provider.h",
     "../ash/web_applications/personalization_app/personalization_app_info.cc",
diff --git a/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManager.java b/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManager.java
index abab6ea..893cfa9a 100644
--- a/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManager.java
+++ b/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManager.java
@@ -21,6 +21,7 @@
 import androidx.annotation.Nullable;
 import androidx.annotation.VisibleForTesting;
 
+import org.chromium.base.Callback;
 import org.chromium.base.ContextUtils;
 import org.chromium.base.IntentUtils;
 import org.chromium.base.Log;
@@ -62,6 +63,8 @@
             "org.chromium.chrome.browser.price_tracking.DESTINATION_URL";
     static final String EXTRA_ACTION_ID = "org.chromium.chrome.browser.price_tracking.ACTION_ID";
     static final String EXTRA_OFFER_ID = "org.chromium.chrome.browser.price_tracking.OFFER_ID";
+    static final String EXTRA_PRODUCT_CLUSTER_ID =
+            "org.chromium.chrome.browser.price_tracking.PRODUCT_CLUSTER_ID";
 
     private static NotificationManagerProxy sNotificationManagerForTesting;
 
@@ -76,6 +79,7 @@
             String destinationUrl = IntentUtils.safeGetStringExtra(intent, EXTRA_DESTINATION_URL);
             String actionId = IntentUtils.safeGetStringExtra(intent, EXTRA_ACTION_ID);
             String offerId = IntentUtils.safeGetStringExtra(intent, EXTRA_OFFER_ID);
+            String clusterId = IntentUtils.safeGetStringExtra(intent, EXTRA_PRODUCT_CLUSTER_ID);
 
             if (TextUtils.isEmpty(offerId)) {
                 Log.e(TAG, "No offer id is provided when handling turn off alert action.");
@@ -90,7 +94,7 @@
                 assert ACTION_ID_TURN_OFF_ALERT.equals(actionId)
                     : "Currently only turn off alert action uses this activity.";
                 priceDropNotificationManager.onNotificationActionClicked(
-                        actionId, destinationUrl, offerId, /*recordMetrics=*/false);
+                        actionId, destinationUrl, offerId, clusterId, /*recordMetrics=*/false);
                 // Finish immediately. Could be better to have a callback from shopping backend.
                 finish();
             });
@@ -194,28 +198,52 @@
      */
     public void onNotificationActionClicked(
             String actionId, String url, @Nullable String offerId, boolean recordMetrics) {
+        onNotificationActionClicked(actionId, url, offerId, null, recordMetrics);
+    }
+
+    /**
+     * Handles the notification action click events.
+     *
+     * @param actionId the id used to identify certain action.
+     * @param url of the tab which triggered the notification.
+     * @param offerId the id of the offer associated with this notification.
+     * @param clusterId The id of the cluster associated with the product notification.
+     * @param recordMetrics Whether to record metrics using {@link NotificationUmaTracker}. Only
+     *         Chime notification code path should set this to true.
+     */
+    public void onNotificationActionClicked(String actionId, String url, @Nullable String offerId,
+            @Nullable String clusterId, boolean recordMetrics) {
         if (actionId.equals(ACTION_ID_VISIT_SITE) && recordMetrics) {
             NotificationUmaTracker.getInstance().onNotificationActionClick(
                     NotificationUmaTracker.ActionType.PRICE_DROP_VISIT_SITE,
                     NotificationUmaTracker.SystemNotificationType.PRICE_DROP_ALERTS,
                     NotificationIntentInterceptor.INVALID_CREATE_TIME);
         } else if (actionId.equals(ACTION_ID_TURN_OFF_ALERT)) {
-            if (offerId == null) return;
+            if (offerId == null && clusterId == null) return;
             SubscriptionsManagerImpl subscriptionsManager =
                     (new CommerceSubscriptionsServiceFactory())
                             .getForLastUsedProfile()
                             .getSubscriptionsManager();
-            subscriptionsManager.unsubscribe(
-                    new CommerceSubscription(CommerceSubscriptionType.PRICE_TRACK, offerId,
-                            SubscriptionManagementType.CHROME_MANAGED, TrackingIdType.OFFER_ID),
-                    (status) -> {
-                        assert status
-                                == SubscriptionsManager.StatusCode.OK
-                            : "Failed to remove subscriptions.";
-                        Log.e(TAG,
-                                String.format(Locale.US,
-                                        "Failed to remove subscriptions. Status: %d", status));
-                    });
+            Callback<Integer> callback = (status) -> {
+                assert status
+                        == SubscriptionsManager.StatusCode.OK : "Failed to remove subscriptions.";
+                Log.e(TAG,
+                        String.format(
+                                Locale.US, "Failed to remove subscriptions. Status: %d", status));
+            };
+            if (offerId != null) {
+                subscriptionsManager.unsubscribe(
+                        new CommerceSubscription(CommerceSubscriptionType.PRICE_TRACK, offerId,
+                                SubscriptionManagementType.CHROME_MANAGED, TrackingIdType.OFFER_ID),
+                        callback);
+            }
+            if (clusterId != null) {
+                subscriptionsManager.unsubscribe(
+                        new CommerceSubscription(CommerceSubscriptionType.PRICE_TRACK, clusterId,
+                                SubscriptionManagementType.USER_MANAGED,
+                                TrackingIdType.PRODUCT_CLUSTER_ID),
+                        callback);
+            }
             if (recordMetrics) {
                 NotificationUmaTracker.getInstance().onNotificationActionClick(
                         NotificationUmaTracker.ActionType.PRICE_DROP_TURN_OFF_ALERT,
@@ -252,12 +280,26 @@
      * @param offerId The offer id of the product.
      */
     public Intent getNotificationActionClickIntent(String actionId, String url, String offerId) {
+        return getNotificationActionClickIntent(actionId, url, offerId, null);
+    }
+
+    /**
+     * Gets the notification action click intents.
+     *
+     * @param actionId the id used to identify certain action.
+     * @param url of the tab which triggered the notification.
+     * @param offerId The offer id of the product.
+     * @param clusterId The cluster id of the product.
+     */
+    public Intent getNotificationActionClickIntent(
+            String actionId, String url, String offerId, String clusterId) {
         if (ACTION_ID_VISIT_SITE.equals(actionId)) return getNotificationClickIntent(url);
         if (ACTION_ID_TURN_OFF_ALERT.equals(actionId)) {
             Intent intent = new Intent(mContext, TrampolineActivity.class);
             intent.putExtra(EXTRA_DESTINATION_URL, url);
             intent.putExtra(EXTRA_ACTION_ID, actionId);
             intent.putExtra(EXTRA_OFFER_ID, offerId);
+            if (clusterId != null) intent.putExtra(EXTRA_PRODUCT_CLUSTER_ID, clusterId);
             return intent;
         }
         return null;
diff --git a/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifier.java b/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifier.java
index 2ff303b..ac5b8fd 100644
--- a/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifier.java
+++ b/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifier.java
@@ -42,12 +42,14 @@
 
     static class NotificationData {
         public NotificationData(CharSequence title, CharSequence text, String iconUrl,
-                String destinationUrl, String offerId, List<ActionData> actions) {
+                String destinationUrl, String offerId, String productClusterId,
+                List<ActionData> actions) {
             this.title = title;
             this.text = text;
             this.iconUrl = iconUrl;
             this.destinationUrl = destinationUrl;
             this.offerId = offerId;
+            this.productClusterId = productClusterId;
             this.actions = actions;
         }
 
@@ -74,6 +76,10 @@
          */
         public final String offerId;
         /**
+         * Associated cluster ID.
+         */
+        public final String productClusterId;
+        /**
          * A list of button actions.
          */
         public final List<ActionData> actions;
@@ -170,8 +176,9 @@
                 PriceTrackingNotificationConfig.getNotificationTimeoutMs());
         if (notificationData.actions != null) {
             for (ActionData action : notificationData.actions) {
-                PendingIntentProvider actionClickIntentProvider = createClickIntent(
-                        action.actionId, notificationData.destinationUrl, notificationData.offerId);
+                PendingIntentProvider actionClickIntentProvider =
+                        createClickIntent(action.actionId, notificationData.destinationUrl,
+                                notificationData.offerId, notificationData.productClusterId);
                 notificationBuilder.addAction(0, action.text, actionClickIntentProvider,
                         actionIdToUmaActionType(action.actionId));
             }
@@ -197,9 +204,10 @@
                 mContext, 0, intent, PendingIntent.FLAG_UPDATE_CURRENT);
     }
 
-    private PendingIntentProvider createClickIntent(String actionId, String url, String offerId) {
+    private PendingIntentProvider createClickIntent(
+            String actionId, String url, String offerId, String clusterId) {
         Intent intent = mPriceDropNotificationManager.getNotificationActionClickIntent(
-                actionId, url, offerId);
+                actionId, url, offerId, clusterId);
         return PendingIntentProvider.getActivity(
                 mContext, 0, intent, PendingIntent.FLAG_UPDATE_CURRENT);
     }
diff --git a/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceTrackingNotificationBridge.java b/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceTrackingNotificationBridge.java
index 3ddba7d..1565b88 100644
--- a/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceTrackingNotificationBridge.java
+++ b/chrome/browser/commerce/price_tracking/android/java/src/org/chromium/chrome/browser/price_tracking/PriceTrackingNotificationBridge.java
@@ -111,11 +111,12 @@
 
         // Use UnsignedLongs to convert OfferId to avoid overflow.
         String offerId = UnsignedLongs.toString(priceDropPayload.getOfferId());
+        String clusterId = UnsignedLongs.toString(priceDropPayload.getProductClusterId());
         ChromeMessage chromeMessage = chromeNotification.getChromeMessage();
         PriceDropNotifier.NotificationData notificationData =
                 new PriceDropNotifier.NotificationData(title, text,
                         chromeMessage.hasIconImageUrl() ? chromeMessage.getIconImageUrl() : null,
-                        priceDropPayload.getDestinationUrl(), offerId,
+                        priceDropPayload.getDestinationUrl(), offerId, clusterId,
                         parseActions(chromeNotification));
         mNotifier.showNotification(notificationData);
     }
diff --git a/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManagerTest.java b/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManagerTest.java
index e3db2da..2c20ad02 100644
--- a/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManagerTest.java
+++ b/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotificationManagerTest.java
@@ -77,6 +77,7 @@
     private static final String ACTION_ID_TURN_OFF_ALERT = "turn_off_alert";
     private static final String TEST_URL = "www.test.com";
     private static final String OFFER_ID = "offer_id";
+    private static final String PRODUCT_CLUSTER_ID = "cluster_id";
 
     private MockNotificationManagerProxy mMockNotificationManager;
     private PriceDropNotificationManager mPriceDropNotificationManager;
@@ -220,12 +221,15 @@
     @MediumTest
     public void testGetNotificationActionClickIntent() {
         verifyClickIntent(mPriceDropNotificationManager.getNotificationActionClickIntent(
-                ACTION_ID_VISIT_SITE, TEST_URL, OFFER_ID));
+                ACTION_ID_VISIT_SITE, TEST_URL, OFFER_ID, PRODUCT_CLUSTER_ID));
         Intent turnOffAlertIntent = mPriceDropNotificationManager.getNotificationActionClickIntent(
-                ACTION_ID_TURN_OFF_ALERT, TEST_URL, OFFER_ID);
+                ACTION_ID_TURN_OFF_ALERT, TEST_URL, OFFER_ID, PRODUCT_CLUSTER_ID);
         assertNotNull(turnOffAlertIntent);
         assertEquals(PriceDropNotificationManager.TrampolineActivity.class.getName(),
                 turnOffAlertIntent.getComponent().getClassName());
+        assertEquals(PRODUCT_CLUSTER_ID,
+                IntentUtils.safeGetStringExtra(
+                        turnOffAlertIntent, PriceDropNotificationManager.EXTRA_PRODUCT_CLUSTER_ID));
         assertEquals(OFFER_ID,
                 IntentUtils.safeGetStringExtra(
                         turnOffAlertIntent, PriceDropNotificationManager.EXTRA_OFFER_ID));
@@ -252,12 +256,12 @@
                         SubscriptionManagementType.CHROME_MANAGED, TrackingIdType.OFFER_ID);
 
         mPriceDropNotificationManager.onNotificationActionClicked(
-                ACTION_ID_TURN_OFF_ALERT, TEST_URL, null, false);
+                ACTION_ID_TURN_OFF_ALERT, TEST_URL, null, null, false);
         verify(mMockSubscriptionsManager, times(0))
                 .unsubscribe(eq(commerceSubscription), any(Callback.class));
 
         mPriceDropNotificationManager.onNotificationActionClicked(
-                ACTION_ID_TURN_OFF_ALERT, TEST_URL, offerId, false);
+                ACTION_ID_TURN_OFF_ALERT, TEST_URL, offerId, null, false);
         verify(mMockSubscriptionsManager, times(1))
                 .unsubscribe(eq(commerceSubscription), any(Callback.class));
     }
diff --git a/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifierUnitTest.java b/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifierUnitTest.java
index e3dcb517..fc7d5d10 100644
--- a/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifierUnitTest.java
+++ b/chrome/browser/commerce/price_tracking/android/javatests/src/org/chromium/chrome/browser/price_tracking/PriceDropNotifierUnitTest.java
@@ -68,6 +68,7 @@
     private static final String ICON_URL = "http://www.example.com/icon";
     private static final String DESTINATION_URL = "http://www.example.com/destination";
     private static final String OFFER_ID = "offer_id";
+    private static final String PRODUCT_CLUSTER_ID = "cluster_id";
     private static final String ACTION_TEXT_0 = "action_text_0";
     private static final String ACTION_TEXT_1 = "action_text_1";
 
@@ -166,8 +167,8 @@
     }
 
     private void showNotification(List<ActionData> actionDataList) {
-        PriceDropNotifier.NotificationData data = new NotificationData(
-                TITLE, TEXT, ICON_URL, DESTINATION_URL, OFFER_ID, actionDataList);
+        PriceDropNotifier.NotificationData data = new NotificationData(TITLE, TEXT, ICON_URL,
+                DESTINATION_URL, OFFER_ID, PRODUCT_CLUSTER_ID, actionDataList);
         mPriceDropNotifier.showNotification(data);
     }
 
@@ -205,7 +206,7 @@
     @Test
     public void testShowNotificationNoIconURL() {
         PriceDropNotifier.NotificationData data = new NotificationData(
-                TITLE, TEXT, /*iconUrl=*/null, DESTINATION_URL, OFFER_ID, null);
+                TITLE, TEXT, /*iconUrl=*/null, DESTINATION_URL, OFFER_ID, PRODUCT_CLUSTER_ID, null);
         mPriceDropNotifier.showNotification(data);
         verify(mNotificationBuilder, times(0)).setLargeIcon(any());
         verify(mNotificationBuilder, times(0)).setBigPictureStyle(any(), any());
diff --git a/chrome/browser/commerce/price_tracking/proto/notifications.proto b/chrome/browser/commerce/price_tracking/proto/notifications.proto
index a8cf97d..475c6d0c 100644
--- a/chrome/browser/commerce/price_tracking/proto/notifications.proto
+++ b/chrome/browser/commerce/price_tracking/proto/notifications.proto
@@ -58,4 +58,5 @@
   optional string destination_url = 3;
   optional commerce.ProductPrice current_price = 4;
   optional commerce.ProductPrice previous_price = 5;
+  optional uint64 product_cluster_id = 6;
 }
diff --git a/chrome/browser/component_updater/first_party_sets_component_installer.cc b/chrome/browser/component_updater/first_party_sets_component_installer.cc
index 0f469640..7451e1f 100644
--- a/chrome/browser/component_updater/first_party_sets_component_installer.cc
+++ b/chrome/browser/component_updater/first_party_sets_component_installer.cc
@@ -4,9 +4,13 @@
 
 #include "chrome/browser/component_updater/first_party_sets_component_installer.h"
 
+#include <utility>
+
 #include "base/bind.h"
+#include "base/callback.h"
 #include "base/cxx17_backports.h"
 #include "base/feature_list.h"
+#include "base/files/file.h"
 #include "base/files/file_util.h"
 #include "base/logging.h"
 #include "base/memory/ref_counted.h"
@@ -17,18 +21,21 @@
 #include "base/version.h"
 #include "chrome/browser/browser_process.h"
 #include "chrome/browser/first_party_sets/first_party_sets_pref_names.h"
+#include "components/component_updater/component_installer.h"
 #include "components/component_updater/component_updater_paths.h"
 #include "components/prefs/pref_service.h"
 #include "content/public/browser/network_service_instance.h"
 #include "net/base/features.h"
 #include "net/cookies/cookie_util.h"
 #include "services/network/public/mojom/network_service.mojom.h"
-#include "third_party/abseil-cpp/absl/types/optional.h"
 
 using component_updater::ComponentUpdateService;
 
 namespace {
 
+using SetsReadyOnceCallback = component_updater::
+    FirstPartySetsComponentInstallerPolicy::SetsReadyOnceCallback;
+
 constexpr base::FilePath::CharType kFirstPartySetsSetsFileName[] =
     FILE_PATH_LITERAL("sets.json");
 
@@ -61,6 +68,10 @@
   if (!base::FeatureList::IsEnabled(net::features::kFirstPartySets)) {
     return false;
   }
+  // Some java tests start the browser in minimal mode, in which
+  // `g_browser_process` is unset.
+  if (!g_browser_process)
+    return false;
   auto* local_state = g_browser_process->local_state();
   if (!local_state ||
       !local_state->HasPrefPath(first_party_sets::kFirstPartySetsEnabled)) {
@@ -69,14 +80,21 @@
   return local_state->GetBoolean(first_party_sets::kFirstPartySetsEnabled);
 }
 
-// Invokes `on_sets_ready` with the contents of the component, if:
-// * the component has been installed; and
+// Invokes `on_sets_ready`, if:
 // * First-Party Sets is enabled; and
-// * the component was read successfully.
-void SetFirstPartySetsConfig(
-    base::OnceCallback<void(base::File)> on_sets_ready) {
+// * `on_sets_ready` is not null.
+//
+// If the component has been installed and can be read, we pass the component
+// file; otherwise, we pass an invalid file.
+void SetFirstPartySetsConfig(SetsReadyOnceCallback on_sets_ready) {
+  if (!IsFirstPartySetsEnabled() || on_sets_ready.is_null()) {
+    return;
+  }
+
   const base::FilePath instance_path = GetConfigPathInstance();
-  if (instance_path.empty() || !IsFirstPartySetsEnabled()) {
+  if (instance_path.empty()) {
+    // Registration is complete, but no component version exists on disk.
+    std::move(on_sets_ready).Run(base::File());
     return;
   }
 
@@ -95,12 +113,16 @@
 
 // static
 void FirstPartySetsComponentInstallerPolicy::ReconfigureAfterNetworkRestart(
-    base::OnceCallback<void(base::File)> on_sets_ready) {
+    SetsReadyOnceCallback on_sets_ready) {
   SetFirstPartySetsConfig(std::move(on_sets_ready));
 }
 
+void FirstPartySetsComponentInstallerPolicy::OnRegistrationComplete() {
+  SetFirstPartySetsConfig(std::move(on_sets_ready_));
+}
+
 FirstPartySetsComponentInstallerPolicy::FirstPartySetsComponentInstallerPolicy(
-    base::RepeatingCallback<void(base::File)> on_sets_ready)
+    SetsReadyOnceCallback on_sets_ready)
     : on_sets_ready_(std::move(on_sets_ready)) {}
 
 FirstPartySetsComponentInstallerPolicy::
@@ -150,7 +172,7 @@
 
   GetConfigPathInstance() = GetInstalledPath(install_dir);
 
-  SetFirstPartySetsConfig(on_sets_ready_);
+  SetFirstPartySetsConfig(std::move(on_sets_ready_));
 }
 
 // Called during startup and installation before ComponentReady().
@@ -201,14 +223,23 @@
 void RegisterFirstPartySetsComponent(ComponentUpdateService* cus) {
   VLOG(1) << "Registering First-Party Sets component.";
 
-  base::MakeRefCounted<ComponentInstaller>(
-      std::make_unique<FirstPartySetsComponentInstallerPolicy>(
-          /*on_sets_ready=*/base::BindRepeating([](base::File sets_file) {
-            VLOG(1) << "Received First-Party Sets";
-            content::GetNetworkService()->SetFirstPartySets(
-                std::move(sets_file));
-          })))
-      ->Register(cus, base::OnceClosure());
+  auto policy = std::make_unique<FirstPartySetsComponentInstallerPolicy>(
+      /*on_sets_ready=*/base::BindOnce([](base::File sets_file) {
+        VLOG(1) << "Received First-Party Sets";
+        content::GetNetworkService()->SetFirstPartySets(std::move(sets_file));
+      }));
+
+  FirstPartySetsComponentInstallerPolicy* raw_policy = policy.get();
+  // Dereferencing `raw_policy` this way is safe because the closure is invoked
+  // by the ComponentInstaller instance, which owns `policy` (so they have the
+  // same lifetime). Therefore if/when the closure is invoked, `policy` is still
+  // alive.
+  base::MakeRefCounted<ComponentInstaller>(std::move(policy))
+      ->Register(cus, base::BindOnce(
+                          [](FirstPartySetsComponentInstallerPolicy* policy) {
+                            policy->OnRegistrationComplete();
+                          },
+                          raw_policy));
 }
 
 // static
diff --git a/chrome/browser/component_updater/first_party_sets_component_installer.h b/chrome/browser/component_updater/first_party_sets_component_installer.h
index 6fcf843..6ccdfe5de 100644
--- a/chrome/browser/component_updater/first_party_sets_component_installer.h
+++ b/chrome/browser/component_updater/first_party_sets_component_installer.h
@@ -28,10 +28,12 @@
 
 class FirstPartySetsComponentInstallerPolicy : public ComponentInstallerPolicy {
  public:
+  using SetsReadyOnceCallback = base::OnceCallback<void(base::File)>;
+
   // |on_sets_ready| will be called on the UI thread when the sets are ready. It
   // is exposed here for testing.
   explicit FirstPartySetsComponentInstallerPolicy(
-      base::RepeatingCallback<void(base::File)> on_sets_ready);
+      SetsReadyOnceCallback on_sets_ready);
   ~FirstPartySetsComponentInstallerPolicy() override;
 
   FirstPartySetsComponentInstallerPolicy(
@@ -42,7 +44,9 @@
   // Calls the callback with the current First-Party Sets data, if the data
   // exists and can be read.
   static void ReconfigureAfterNetworkRestart(
-      base::OnceCallback<void(base::File)>);
+      SetsReadyOnceCallback on_sets_ready);
+
+  void OnRegistrationComplete();
 
   // Resets static state. Should only be used to clear state during testing.
   static void ResetForTesting();
@@ -59,10 +63,14 @@
   FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
                            NonexistentFile_OnComponentReady);
   FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
+                           NonexistentFile_OnRegistrationComplete);
+  FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
                            LoadsSets_OnComponentReady);
   FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
                            LoadsSets_OnNetworkRestart);
   FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
+                           IgnoreNewSets_NoInitialComponent);
+  FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
                            IgnoreNewSets_OnComponentReady);
   FRIEND_TEST_ALL_PREFIXES(FirstPartySetsComponentInstallerTest,
                            IgnoreNewSets_OnNetworkRestart);
@@ -98,7 +106,9 @@
 
   static base::FilePath GetInstalledPath(const base::FilePath& base);
 
-  base::RepeatingCallback<void(base::File)> on_sets_ready_;
+  // We use a OnceCallback to ensure we only pass along the sets file once
+  // during Chrome's lifetime (modulo reconfiguring the network service).
+  SetsReadyOnceCallback on_sets_ready_;
 };
 
 // Call once during startup to make the component update service aware of
diff --git a/chrome/browser/component_updater/first_party_sets_component_installer_unittest.cc b/chrome/browser/component_updater/first_party_sets_component_installer_unittest.cc
index a3ba4ae..df54ca7 100644
--- a/chrome/browser/component_updater/first_party_sets_component_installer_unittest.cc
+++ b/chrome/browser/component_updater/first_party_sets_component_installer_unittest.cc
@@ -5,6 +5,8 @@
 #include "chrome/browser/component_updater/first_party_sets_component_installer.h"
 
 #include "base/callback_helpers.h"
+#include "base/check.h"
+#include "base/files/file.h"
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
 #include "base/run_loop.h"
@@ -86,6 +88,23 @@
   base::RunLoop().RunUntilIdle();
 }
 
+TEST_F(FirstPartySetsComponentInstallerTest,
+       NonexistentFile_OnRegistrationComplete) {
+  ASSERT_TRUE(
+      base::DeleteFile(FirstPartySetsComponentInstallerPolicy::GetInstalledPath(
+          component_install_dir_.GetPath())));
+
+  base::RunLoop run_loop;
+  FirstPartySetsComponentInstallerPolicy(
+      base::BindLambdaForTesting([&](base::File file) {
+        EXPECT_FALSE(file.IsValid());
+        run_loop.Quit();
+      }))
+      .OnRegistrationComplete();
+
+  run_loop.Run();
+}
+
 TEST_F(FirstPartySetsComponentInstallerTest, LoadsSets_OnComponentReady) {
   SEQUENCE_CHECKER(sequence_checker);
   const std::string expectation = "some first party sets";
@@ -93,6 +112,7 @@
   auto policy = std::make_unique<FirstPartySetsComponentInstallerPolicy>(
       base::BindLambdaForTesting([&](base::File file) {
         DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+        EXPECT_TRUE(file.IsValid());
         EXPECT_EQ(ReadToString(std::move(file)), expectation);
         run_loop.Quit();
       }));
@@ -108,6 +128,41 @@
   run_loop.Run();
 }
 
+// Test that when the first version of the component is installed,
+// ComponentReady is a no-op, because OnRegistrationComplete already executed
+// the OnceCallback.
+TEST_F(FirstPartySetsComponentInstallerTest, IgnoreNewSets_NoInitialComponent) {
+  SEQUENCE_CHECKER(sequence_checker);
+
+  int callback_calls = 0;
+  FirstPartySetsComponentInstallerPolicy policy(
+      // This should run only once for the OnRegistrationComplete call.
+      base::BindLambdaForTesting([&](base::File file) {
+        DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+        EXPECT_FALSE(file.IsValid());
+        callback_calls++;
+      }));
+
+  policy.OnRegistrationComplete();
+  env_.RunUntilIdle();
+  EXPECT_EQ(callback_calls, 1);
+
+  // Install the component, which should be ignored.
+  base::ScopedTempDir install_dir;
+  CHECK(install_dir.CreateUniqueTempDirUnderPath(
+      component_install_dir_.GetPath()));
+  ASSERT_TRUE(
+      base::WriteFile(FirstPartySetsComponentInstallerPolicy::GetInstalledPath(
+                          install_dir.GetPath()),
+                      "first party sets content"));
+  policy.ComponentReady(base::Version(), install_dir.GetPath(),
+                        base::Value(base::Value::Type::DICTIONARY));
+
+  env_.RunUntilIdle();
+
+  EXPECT_EQ(callback_calls, 1);
+}
+
 // Test if a component has been installed, ComponentReady will be no-op when
 // newer versions are installed.
 TEST_F(FirstPartySetsComponentInstallerTest, IgnoreNewSets_OnComponentReady) {
@@ -125,6 +180,7 @@
       // It should run only once for the first ComponentReady call.
       base::BindLambdaForTesting([&](base::File file) {
         DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+        EXPECT_TRUE(file.IsValid());
         EXPECT_EQ(ReadToString(std::move(file)), sets_v1);
         callback_calls++;
       }));
@@ -160,6 +216,7 @@
     FirstPartySetsComponentInstallerPolicy policy(
         base::BindLambdaForTesting([&](base::File file) {
           DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+          EXPECT_TRUE(file.IsValid());
           EXPECT_EQ(ReadToString(std::move(file)), expectation);
           run_loop.Quit();
         }));
@@ -181,6 +238,7 @@
     FirstPartySetsComponentInstallerPolicy::ReconfigureAfterNetworkRestart(
         base::BindLambdaForTesting([&](base::File file) {
           DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+          EXPECT_TRUE(file.IsValid());
           EXPECT_EQ(ReadToString(std::move(file)), expectation);
           run_loop.Quit();
         }));
@@ -205,6 +263,7 @@
   FirstPartySetsComponentInstallerPolicy policy(
       base::BindLambdaForTesting([&](base::File file) {
         DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+        EXPECT_TRUE(file.IsValid());
         EXPECT_EQ(ReadToString(std::move(file)), sets_v1);
       }));
 
@@ -231,6 +290,7 @@
   FirstPartySetsComponentInstallerPolicy::ReconfigureAfterNetworkRestart(
       base::BindLambdaForTesting([&](base::File file) {
         DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker);
+        EXPECT_TRUE(file.IsValid());
         EXPECT_EQ(ReadToString(std::move(file)), sets_v1);
         callback_calls++;
       }));
diff --git a/chrome/browser/enterprise/reporting/report_scheduler_unittest.cc b/chrome/browser/enterprise/reporting/report_scheduler_unittest.cc
index e872580..96286739 100644
--- a/chrome/browser/enterprise/reporting/report_scheduler_unittest.cc
+++ b/chrome/browser/enterprise/reporting/report_scheduler_unittest.cc
@@ -104,7 +104,8 @@
   MockReportUploader& operator=(const MockReportUploader&) = delete;
 
   ~MockReportUploader() override = default;
-  MOCK_METHOD2(SetRequestAndUpload, void(ReportRequestQueue, ReportCallback));
+  MOCK_METHOD3(SetRequestAndUpload,
+               void(ReportType, ReportRequestQueue, ReportCallback));
 };
 
 class MockRealTimeReportGenerator : public RealTimeReportGenerator {
@@ -313,8 +314,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -334,8 +335,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kTransientError));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kTransientError));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -355,8 +356,8 @@
   EXPECT_CALL_SetupRegistrationWithSetDMToken();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kPersistentError));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kPersistentError));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -381,7 +382,7 @@
   EXPECT_CALL_SetupRegistrationWithSetDMToken();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(0)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _)).Times(0);
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _, _)).Times(0);
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -409,8 +410,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -429,8 +430,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -466,8 +467,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -502,8 +503,9 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kBrowserVersion, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_,
+              SetRequestAndUpload(ReportType::kBrowserVersion, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   g_browser_process->GetBuildState()->SetUpdate(
@@ -525,8 +527,9 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kBrowserVersion, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kPersistentError));
+  EXPECT_CALL(*uploader_,
+              SetRequestAndUpload(ReportType::kBrowserVersion, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kPersistentError));
 
   CreateScheduler();
   g_browser_process->GetBuildState()->SetUpdate(
@@ -559,8 +562,10 @@
 
   // Hang on to the uploader's ReportCallback.
   ReportUploader::ReportCallback saved_callback;
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce([&saved_callback](ReportRequestQueue requests,
+  EXPECT_CALL(*uploader_,
+              SetRequestAndUpload(ReportType::kBrowserVersion, _, _))
+      .WillOnce([&saved_callback](ReportType report_type,
+                                  ReportRequestQueue requests,
                                   ReportUploader::ReportCallback callback) {
         saved_callback = std::move(callback);
       });
@@ -582,8 +587,8 @@
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
   auto new_uploader = std::make_unique<MockReportUploader>();
-  EXPECT_CALL(*new_uploader, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*new_uploader, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
   std::move(saved_callback).Run(ReportUploader::kSuccess);
   ExpectLastUploadTimestampUpdated(false);
   ::testing::Mock::VerifyAndClearExpectations(generator_);
@@ -612,8 +617,9 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kBrowserVersion, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_,
+              SetRequestAndUpload(ReportType::kBrowserVersion, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
 
@@ -642,8 +648,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
 
@@ -664,7 +670,7 @@
 TEST_F(ReportSchedulerTest, ExtensionRequestWithRealTimePipeline) {
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(_, _)).Times(0);
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _)).Times(0);
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _, _)).Times(0);
 
   Profile* profile = profile_manager_.CreateTestingProfile("profile");
 
diff --git a/chrome/browser/extensions/api/developer_private/developer_private_api.cc b/chrome/browser/extensions/api/developer_private/developer_private_api.cc
index 7b56123..f9e3dbb 100644
--- a/chrome/browser/extensions/api/developer_private/developer_private_api.cc
+++ b/chrome/browser/extensions/api/developer_private/developer_private_api.cc
@@ -7,13 +7,13 @@
 #include <stddef.h>
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 #include <vector>
 
 #include "base/bind.h"
 #include "base/files/file_util.h"
 #include "base/guid.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/memory/scoped_refptr.h"
 #include "base/metrics/histogram_macros.h"
@@ -159,7 +159,7 @@
   std::string data;
   // This call can fail, but it doesn't matter for our purposes. If it fails,
   // we simply return an empty string for the manifest, and ignore it.
-  ignore_result(base::ReadFileToString(path, &data));
+  std::ignore = base::ReadFileToString(path, &data);
   return data;
 }
 
diff --git a/chrome/browser/extensions/api/extension_action/page_action_browsertest.cc b/chrome/browser/extensions/api/extension_action/page_action_browsertest.cc
index 7b8ef728..99fcd5b 100644
--- a/chrome/browser/extensions/api/extension_action/page_action_browsertest.cc
+++ b/chrome/browser/extensions/api/extension_action/page_action_browsertest.cc
@@ -144,7 +144,11 @@
 }
 
 // Regression test for crbug.com/44415.
-IN_PROC_BROWSER_TEST_P(PageActionBrowserTest, PageActionRefreshCrash) {
+// TODO(crbug.com/1284555): Re-enable test to run with service workers after
+// fixing flakiness.
+using PageActionWithoutServiceWorkerTest = ExtensionBrowserTest;
+IN_PROC_BROWSER_TEST_F(PageActionWithoutServiceWorkerTest,
+                       PageActionRefreshCrash) {
   ExtensionRegistry* registry =
       extensions::ExtensionRegistry::Get(browser()->profile());
 
diff --git a/chrome/browser/extensions/api/messaging/native_messaging_test_util.cc b/chrome/browser/extensions/api/messaging/native_messaging_test_util.cc
index 8b4a85d..c673c30 100644
--- a/chrome/browser/extensions/api/messaging/native_messaging_test_util.cc
+++ b/chrome/browser/extensions/api/messaging/native_messaging_test_util.cc
@@ -5,11 +5,11 @@
 #include "chrome/browser/extensions/api/messaging/native_messaging_test_util.h"
 
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/json/json_file_value_serializer.h"
 #include "base/path_service.h"
 #include "base/strings/stringprintf.h"
@@ -126,7 +126,7 @@
 
 ScopedTestNativeMessagingHost::~ScopedTestNativeMessagingHost() {
   base::ScopedAllowBlockingForTesting allow_blocking;
-  ignore_result(temp_dir_.Delete());
+  std::ignore = temp_dir_.Delete();
 }
 
 }  // namespace extensions
diff --git a/chrome/browser/extensions/crx_installer.cc b/chrome/browser/extensions/crx_installer.cc
index 5643078..c1889aa 100644
--- a/chrome/browser/extensions/crx_installer.cc
+++ b/chrome/browser/extensions/crx_installer.cc
@@ -32,6 +32,8 @@
 #include "chrome/browser/extensions/load_error_reporter.h"
 #include "chrome/browser/extensions/permissions_updater.h"
 #include "chrome/browser/extensions/webstore_installer.h"
+#include "chrome/browser/profiles/keep_alive/profile_keep_alive_types.h"
+#include "chrome/browser/profiles/keep_alive/scoped_profile_keep_alive.h"
 #include "chrome/browser/profiles/profile.h"
 #include "chrome/common/chrome_paths.h"
 #include "chrome/common/chrome_switches.h"
@@ -1057,6 +1059,9 @@
 }
 
 void CrxInstaller::NotifyCrxInstallBegin() {
+  profile_keep_alive_ = std::make_unique<ScopedProfileKeepAlive>(
+      profile_, ProfileKeepAliveOrigin::kCrxInstaller);
+
   InstallTrackerFactory::GetForBrowserContext(profile())
       ->OnBeginCrxInstall(expected_id_);
 }
@@ -1121,6 +1126,8 @@
           FROM_HERE, base::BindOnce(std::move(installer_callback_), error))) {
     NOTREACHED();
   }
+
+  profile_keep_alive_.reset();
 }
 
 void CrxInstaller::CleanupTempFiles() {
diff --git a/chrome/browser/extensions/crx_installer.h b/chrome/browser/extensions/crx_installer.h
index ea0f700..089ab148 100644
--- a/chrome/browser/extensions/crx_installer.h
+++ b/chrome/browser/extensions/crx_installer.h
@@ -30,6 +30,7 @@
 #include "third_party/abseil-cpp/absl/types/optional.h"
 
 class ExtensionServiceTest;
+class ScopedProfileKeepAlive;
 class SkBitmap;
 
 namespace base {
@@ -368,6 +369,9 @@
   // The Profile the extension is being installed in.
   raw_ptr<Profile> profile_;
 
+  // Prevent Profile destruction until the CrxInstaller is done.
+  std::unique_ptr<ScopedProfileKeepAlive> profile_keep_alive_;
+
   // The extension being installed.
   scoped_refptr<const Extension> extension_;
 
diff --git a/chrome/browser/extensions/process_management_browsertest.cc b/chrome/browser/extensions/process_management_browsertest.cc
index 1d3f959..56342e8 100644
--- a/chrome/browser/extensions/process_management_browsertest.cc
+++ b/chrome/browser/extensions/process_management_browsertest.cc
@@ -4,7 +4,8 @@
 
 #include <stddef.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/strings/stringprintf.h"
 #include "base/strings/utf_string_conversions.h"
 #include "base/test/scoped_feature_list.h"
@@ -709,8 +710,8 @@
 
     // WaitForLoadStop() will return false on a 404, but that can happen if we
     // navigate to a blocked or nonexistent extension page.
-    ignore_result(content::WaitForLoadStop(
-        browser()->tab_strip_model()->GetActiveWebContents()));
+    std::ignore = content::WaitForLoadStop(
+        browser()->tab_strip_model()->GetActiveWebContents());
 
     EXPECT_TRUE(content::ExecuteScriptAndExtractBool(web_contents, kGetAccess,
                                                      &can_access));
diff --git a/chrome/browser/file_system_access/chrome_file_system_access_permission_context_browsertest.cc b/chrome/browser/file_system_access/chrome_file_system_access_permission_context_browsertest.cc
index 44361a3..bca3a39 100644
--- a/chrome/browser/file_system_access/chrome_file_system_access_permission_context_browsertest.cc
+++ b/chrome/browser/file_system_access/chrome_file_system_access_permission_context_browsertest.cc
@@ -4,9 +4,10 @@
 
 #include "chrome/browser/file_system_access/chrome_file_system_access_permission_context.h"
 
+#include <tuple>
+
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
-#include "base/ignore_result.h"
 #include "chrome/browser/file_system_access/file_system_access_permission_request_manager.h"
 #include "chrome/browser/profiles/profile.h"
 #include "chrome/browser/ui/browser.h"
@@ -194,7 +195,7 @@
   // In order to get the file handle without the file picker dialog in the
   // prerendered page, BroadcastChannel gets the file handle from the current
   // active page.
-  ignore_result(
+  std::ignore =
       content::ExecJs(prerendered_frame_host, R"(
             var createWritableAndClose = (async () => {
               let b = new BroadcastChannel('channel');
@@ -208,17 +209,17 @@
               await w.close();
               return "";})();
             )",
-                      content::EvalJsOptions::EXECUTE_SCRIPT_NO_USER_GESTURE));
+                      content::EvalJsOptions::EXECUTE_SCRIPT_NO_USER_GESTURE);
 
   // The active page picks files and sends it to the prerendered page to test
   // 'close()' in prerendering.
-  ignore_result(content::ExecJs(
+  std::ignore = content::ExecJs(
       GetWebContents(),
       "(async () => {"
       "  let [e] = await self.showOpenFilePicker();"
       "  self.entry = e;"
       "  new BroadcastChannel('channel').postMessage({entry: e});"
-      "  return e.name; })()"));
+      "  return e.name; })()");
 
   // PerformAfterWriteChecks() is not called in prerendering.
   EXPECT_FALSE(permission_context.performed_after_write_checks());
diff --git a/chrome/browser/first_run/first_run.cc b/chrome/browser/first_run/first_run.cc
index 18e21abc..2dadc0c 100644
--- a/chrome/browser/first_run/first_run.cc
+++ b/chrome/browser/first_run/first_run.cc
@@ -6,13 +6,13 @@
 
 #include <algorithm>
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/command_line.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/metrics/histogram_macros.h"
 #include "base/metrics/user_metrics.h"
 #include "base/no_destructor.h"
@@ -344,7 +344,7 @@
 
   // Causes the first run sentinel creation time to be read and cached, while
   // I/O is still allowed.
-  ignore_result(GetFirstRunSentinelCreationTime());
+  std::ignore = GetFirstRunSentinelCreationTime();
 }
 
 base::Time GetFirstRunSentinelCreationTime() {
diff --git a/chrome/browser/flags/android/chrome_feature_list.cc b/chrome/browser/flags/android/chrome_feature_list.cc
index ddfeffdc..e4b3f1c 100644
--- a/chrome/browser/flags/android/chrome_feature_list.cc
+++ b/chrome/browser/flags/android/chrome_feature_list.cc
@@ -102,6 +102,7 @@
     &download::features::kSmartSuggestionForLargeDownloads,
     &download::features::kUseDownloadOfflineContentProvider,
     &embedder_support::kShowTrustedPublisherURL,
+    &features::kAnonymousUpdateChecks,
     &features::kContinuousSearch,
     &features::kEarlyLibraryLoad,
     &features::kGenericSensorExtraClasses,
diff --git a/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/CachedFeatureFlags.java b/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/CachedFeatureFlags.java
index af111e7..c07010d 100644
--- a/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/CachedFeatureFlags.java
+++ b/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/CachedFeatureFlags.java
@@ -48,6 +48,7 @@
      */
     private static Map<String, Boolean> sDefaults =
             ImmutableMap.<String, Boolean>builder()
+                    .put(ChromeFeatureList.ANONYMOUS_UPDATE_CHECKS, true)
                     .put(ChromeFeatureList.BOOKMARK_BOTTOM_SHEET, false)
                     .put(ChromeFeatureList.CONDITIONAL_TAB_STRIP_ANDROID, false)
                     .put(ChromeFeatureList.LENS_CAMERA_ASSISTED_SEARCH, false)
diff --git a/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/ChromeFeatureList.java b/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/ChromeFeatureList.java
index 2d6b15f..08839df 100644
--- a/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/ChromeFeatureList.java
+++ b/chrome/browser/flags/android/java/src/org/chromium/chrome/browser/flags/ChromeFeatureList.java
@@ -216,6 +216,7 @@
             "AndroidLayoutChangeTabReparenting";
     public static final String ANDROID_SEARCH_ENGINE_CHOICE_NOTIFICATION =
             "AndroidSearchEngineChoiceNotification";
+    public static final String ANONYMOUS_UPDATE_CHECKS = "AnonymousUpdateChecks";
     public static final String APP_LANGUAGE_PROMPT = "AppLanguagePrompt";
     public static final String ASSISTANT_CONSENT_SIMPLIFIED_TEXT = "AssistantConsentSimplifiedText";
     public static final String ASSISTANT_CONSENT_V2 = "AssistantConsentV2";
diff --git a/chrome/browser/google/google_update_policy_fetcher_win.cc b/chrome/browser/google/google_update_policy_fetcher_win.cc
index fb1ce9f..458369f 100644
--- a/chrome/browser/google/google_update_policy_fetcher_win.cc
+++ b/chrome/browser/google/google_update_policy_fetcher_win.cc
@@ -6,10 +6,11 @@
 
 #include <ATLComTime.h>
 #include <wrl/client.h>
+
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/numerics/safe_conversions.h"
 #include "base/strings/string_split.h"
 #include "base/strings/string_util_win.h"
@@ -71,11 +72,11 @@
   ::COleDateTime date_time(date);
   base::Time time;
   if (date_time.m_status == ::COleDateTime::valid) {
-    ignore_result(base::Time::FromLocalExploded(
+    std::ignore = base::Time::FromLocalExploded(
         {date_time.GetYear(), date_time.GetMonth(), date_time.GetDayOfWeek(),
          date_time.GetDay(), date_time.GetHour(), date_time.GetMinute(),
          date_time.GetSecond(), 0},
-        &time));
+        &time);
   }
   return time;
 }
diff --git a/chrome/browser/media/cdm_document_service_impl_test.cc b/chrome/browser/media/cdm_document_service_impl_test.cc
index df8d388..ae85d16 100644
--- a/chrome/browser/media/cdm_document_service_impl_test.cc
+++ b/chrome/browser/media/cdm_document_service_impl_test.cc
@@ -5,10 +5,10 @@
 #include "chrome/browser/media/cdm_document_service_impl.h"
 
 #include <memory>
+#include <tuple>
 
 #include "base/files/file.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/json/values_util.h"
 #include "base/logging.h"
 #include "base/run_loop.h"
@@ -172,7 +172,7 @@
   // Call GetMediaFoundationCdmData to create the origin id first, otherwise
   // `SetCdmClientToken()` will assume the preference data associated with the
   // origin was recently cleared and will not save the client token.
-  ignore_result(GetMediaFoundationCdmData());
+  std::ignore = GetMediaFoundationCdmData();
 
   std::vector<uint8_t> expected_client_token = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
   SetCdmClientToken(expected_client_token);
@@ -192,12 +192,12 @@
   // Call GetMediaFoundationCdmData to create the origin id first, otherwise
   // `SetCdmClientToken()` will assume the preference data associated with the
   // origin was recently cleared and will not save the client token.
-  ignore_result(GetMediaFoundationCdmData());
+  std::ignore = GetMediaFoundationCdmData();
   std::vector<uint8_t> expected_client_token = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
   SetCdmClientToken(expected_client_token);
 
   NavigateToUrlAndCreateCdmDocumentService(GURL(kTestOrigin2));
-  ignore_result(GetMediaFoundationCdmData());
+  std::ignore = GetMediaFoundationCdmData();
   SetCdmClientToken({1, 2, 3, 4, 5});
 
   NavigateToUrlAndCreateCdmDocumentService(GURL(kTestOrigin));
@@ -210,7 +210,7 @@
 // remove that entry and return without saving the client token.
 TEST_F(CdmDocumentServiceImplTest, SetClientTokenAfterCorruption) {
   NavigateToUrlAndCreateCdmDocumentService(GURL(kTestOrigin));
-  ignore_result(GetMediaFoundationCdmData());
+  std::ignore = GetMediaFoundationCdmData();
   CorruptCdmPreference();
 
   std::vector<uint8_t> expected_client_token = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
diff --git a/chrome/browser/media/encrypted_media_supported_types_browsertest.cc b/chrome/browser/media/encrypted_media_supported_types_browsertest.cc
index 61bc7e7..5b3019b 100644
--- a/chrome/browser/media/encrypted_media_supported_types_browsertest.cc
+++ b/chrome/browser/media/encrypted_media_supported_types_browsertest.cc
@@ -5,11 +5,11 @@
 #include <stddef.h>
 
 #include <string>
+#include <tuple>
 #include <vector>
 
 #include "base/base_switches.h"
 #include "base/files/file_path.h"
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/strings/stringprintf.h"
 #include "base/strings/utf_string_conversions.h"
@@ -76,7 +76,7 @@
 // Any support is acceptable. This can be used around new CDM check-in time
 // where test expectations can change based on the new CDM's capability.
 // For any usage of EXPECT_ANY, add a TODO explaining the plan to fix it.
-#define EXPECT_ANY(test) ignore_result(test)
+#define EXPECT_ANY(test) std::ignore = test
 
 #if BUILDFLAG(ENABLE_AV1_DECODER)
 #define EXPECT_AV1 EXPECT_SUCCESS
diff --git a/chrome/browser/media/history/media_history_store.cc b/chrome/browser/media/history/media_history_store.cc
index 3be6bfd..34579ac 100644
--- a/chrome/browser/media/history/media_history_store.cc
+++ b/chrome/browser/media/history/media_history_store.cc
@@ -4,10 +4,11 @@
 
 #include "chrome/browser/media/history/media_history_store.h"
 
+#include <tuple>
+
 #include "base/callback.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/metrics/histogram_functions.h"
 #include "base/strings/stringprintf.h"
 #include "base/task/task_runner_util.h"
@@ -52,7 +53,7 @@
     // or hardware issues, not coding errors at the client level, so displaying
     // the error would probably lead to confusion.  The ignored call signals the
     // test-expectation framework that the error was handled.
-    ignore_result(sql::Database::IsExpectedSqliteError(extended_error));
+    std::ignore = sql::Database::IsExpectedSqliteError(extended_error);
     return;
   }
 
diff --git a/chrome/browser/media/webrtc/conditional_focus_browsertest.cc b/chrome/browser/media/webrtc/conditional_focus_browsertest.cc
index 07ee4d1..e4cbfbd 100644
--- a/chrome/browser/media/webrtc/conditional_focus_browsertest.cc
+++ b/chrome/browser/media/webrtc/conditional_focus_browsertest.cc
@@ -258,8 +258,16 @@
             browser()->tab_strip_model()->GetWebContentsAt(0));
 }
 
+// TODO(crbug.com/1285418): Flaky on Win and Linux bots.
+#if defined(OS_WIN) || defined(OS_LINUX)
+#define MAYBE_ExceptionRaisedIfFocusCalledMultipleTimes \
+  DISABLED_ExceptionRaisedIfFocusCalledMultipleTimes
+#else
+#define MAYBE_ExceptionRaisedIfFocusCalledMultipleTimes \
+  ExceptionRaisedIfFocusCalledMultipleTimes
+#endif
 IN_PROC_BROWSER_TEST_F(ConditionalFocusBrowserTest,
-                       ExceptionRaisedIfFocusCalledMultipleTimes) {
+                       MAYBE_ExceptionRaisedIfFocusCalledMultipleTimes) {
   // Setup.
   SetUpTestTabs();
   Capture(0, FocusEnumValue::kFocusCapturedSurface);
diff --git a/chrome/browser/media/webrtc/test_stats_dictionary_unittest.cc b/chrome/browser/media/webrtc/test_stats_dictionary_unittest.cc
index c893d5f..a5e0c48 100644
--- a/chrome/browser/media/webrtc/test_stats_dictionary_unittest.cc
+++ b/chrome/browser/media/webrtc/test_stats_dictionary_unittest.cc
@@ -6,10 +6,10 @@
 
 #include <memory>
 #include <set>
+#include <tuple>
 #include <vector>
 
 #include "base/check.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/memory/ref_counted.h"
 #include "base/values.h"
@@ -52,7 +52,7 @@
     CHECK(value);
     base::DictionaryValue* dictionary;
     CHECK(value->GetAsDictionary(&dictionary));
-    ignore_result(value.release());
+    std::ignore = value.release();
     report_ = new TestStatsReportDictionary(
         std::unique_ptr<base::DictionaryValue>(dictionary));
   }
diff --git a/chrome/browser/media/webrtc/webrtc_browsertest_base.cc b/chrome/browser/media/webrtc/webrtc_browsertest_base.cc
index aef3d05b..9cf2dd6 100644
--- a/chrome/browser/media/webrtc/webrtc_browsertest_base.cc
+++ b/chrome/browser/media/webrtc/webrtc_browsertest_base.cc
@@ -7,8 +7,8 @@
 #include <stddef.h>
 
 #include <limits>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/lazy_instance.h"
 #include "base/logging.h"
@@ -566,7 +566,7 @@
   base::DictionaryValue* dictionary;
   CHECK(parsed_json);
   CHECK(parsed_json->GetAsDictionary(&dictionary));
-  ignore_result(parsed_json.release());
+  std::ignore = parsed_json.release();
   return scoped_refptr<content::TestStatsReportDictionary>(
       new content::TestStatsReportDictionary(
           std::unique_ptr<base::DictionaryValue>(dictionary)));
diff --git a/chrome/browser/media/webrtc/webrtc_internals_perf_browsertest.cc b/chrome/browser/media/webrtc/webrtc_internals_perf_browsertest.cc
index b8e5553b..9169c9a 100644
--- a/chrome/browser/media/webrtc/webrtc_internals_perf_browsertest.cc
+++ b/chrome/browser/media/webrtc/webrtc_internals_perf_browsertest.cc
@@ -3,10 +3,10 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 
 #include "base/command_line.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/strings/string_split.h"
 #include "base/test/test_timeouts.h"
@@ -76,7 +76,7 @@
         base::JSONReader::ReadDeprecated(all_stats_json);
     base::DictionaryValue* result;
     if (parsed_json.get() && parsed_json->GetAsDictionary(&result)) {
-      ignore_result(parsed_json.release());
+      std::ignore = parsed_json.release();
       return result;
     }
 
diff --git a/chrome/browser/media/webrtc/webrtc_video_display_perf_browsertest.cc b/chrome/browser/media/webrtc/webrtc_video_display_perf_browsertest.cc
index 33dd615..e027535 100644
--- a/chrome/browser/media/webrtc/webrtc_video_display_perf_browsertest.cc
+++ b/chrome/browser/media/webrtc/webrtc_video_display_perf_browsertest.cc
@@ -3,8 +3,8 @@
 // found in the LICENSE file.
 
 #include <algorithm>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/strings/string_tokenizer.h"
 #include "base/strings/stringprintf.h"
@@ -132,7 +132,7 @@
   base::DictionaryValue* dictionary = nullptr;
   if (!parsed_json.get() || !parsed_json->GetAsDictionary(&dictionary))
     return goog_decode_ms;
-  ignore_result(parsed_json.release());
+  std::ignore = parsed_json.release();
 
   // |dictionary| should have exactly two entries, one per ssrc.
   if (!dictionary || dictionary->DictSize() != 2u)
diff --git a/chrome/browser/media_galleries/media_galleries_test_util.cc b/chrome/browser/media_galleries/media_galleries_test_util.cc
index 2691835e..481bbbc 100644
--- a/chrome/browser/media_galleries/media_galleries_test_util.cc
+++ b/chrome/browser/media_galleries/media_galleries_test_util.cc
@@ -7,12 +7,12 @@
 #include <stddef.h>
 
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/base_paths.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/strings/string_number_conversions.h"
 #include "base/threading/thread_restrictions.h"
@@ -97,7 +97,7 @@
 
 EnsureMediaDirectoriesExists::~EnsureMediaDirectoriesExists() {
   base::ScopedAllowBlockingForTesting allow_blocking;
-  ignore_result(fake_dir_.Delete());
+  std::ignore = fake_dir_.Delete();
 }
 
 void EnsureMediaDirectoriesExists::ChangeMediaPathOverrides() {
diff --git a/chrome/browser/metrics/chrome_browser_main_extra_parts_metrics.cc b/chrome/browser/metrics/chrome_browser_main_extra_parts_metrics.cc
index 7393962c..91990009b 100644
--- a/chrome/browser/metrics/chrome_browser_main_extra_parts_metrics.cc
+++ b/chrome/browser/metrics/chrome_browser_main_extra_parts_metrics.cc
@@ -24,7 +24,6 @@
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
 #include "build/config/compiler/compiler_buildflags.h"
-#include "build/os_buildflags.h"
 #include "chrome/browser/about_flags.h"
 #include "chrome/browser/browser_process.h"
 #include "chrome/browser/buildflags.h"
diff --git a/chrome/browser/metrics/perf/profile_provider_unittest_main.cc b/chrome/browser/metrics/perf/profile_provider_unittest_main.cc
index 068e93c2..7ddcc6fe 100644
--- a/chrome/browser/metrics/perf/profile_provider_unittest_main.cc
+++ b/chrome/browser/metrics/perf/profile_provider_unittest_main.cc
@@ -4,10 +4,11 @@
 
 #include "chrome/browser/metrics/perf/profile_provider_chromeos.h"
 
+#include <tuple>
+
 #include "base/bind.h"
 #include "base/callback_helpers.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/metrics/field_trial.h"
 #include "base/metrics/statistics_recorder.h"
 #include "base/run_loop.h"
@@ -214,7 +215,7 @@
     ASSERT_TRUE(profile.has_perf_data());
 
     // Collection succeeded: don't output the error log.
-    ignore_result(scoped_log_error.Release());
+    std::ignore = scoped_log_error.Release();
   }
 
  protected:
diff --git a/chrome/browser/metrics/perf/windowed_incognito_observer.cc b/chrome/browser/metrics/perf/windowed_incognito_observer.cc
index dd4e95e..6c5b8f7 100644
--- a/chrome/browser/metrics/perf/windowed_incognito_observer.cc
+++ b/chrome/browser/metrics/perf/windowed_incognito_observer.cc
@@ -4,7 +4,8 @@
 
 #include "chrome/browser/metrics/perf/windowed_incognito_observer.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/no_destructor.h"
 #include "chrome/browser/profiles/profile.h"
 #include "chrome/browser/ui/browser.h"
@@ -30,7 +31,7 @@
 
 // static
 void WindowedIncognitoMonitor::Init() {
-  ignore_result(WindowedIncognitoMonitor::Get());
+  std::ignore = WindowedIncognitoMonitor::Get();
 }
 
 // static
diff --git a/chrome/browser/navigation_predictor/navigation_predictor_browsertest.cc b/chrome/browser/navigation_predictor/navigation_predictor_browsertest.cc
index d8e1e46..e3a51ef4 100644
--- a/chrome/browser/navigation_predictor/navigation_predictor_browsertest.cc
+++ b/chrome/browser/navigation_predictor/navigation_predictor_browsertest.cc
@@ -3,6 +3,7 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 
 #include "base/run_loop.h"
 #include "base/sequence_checker.h"
@@ -750,8 +751,8 @@
   // Create a fenced frame.
   const GURL& fenced_frame_url =
       test_server()->GetURL("/fenced_frames/simple_page_with_anchors.html");
-  ignore_result(fenced_frame_test_helper().CreateFencedFrame(
-      web_contents()->GetMainFrame(), fenced_frame_url));
+  std::ignore = fenced_frame_test_helper().CreateFencedFrame(
+      web_contents()->GetMainFrame(), fenced_frame_url);
 
   // Make sure the fenced frame doesn't log any anchors.
   anchor_entries = test_ukm_recorder->GetEntriesByName(AnchorEntry::kEntryName);
diff --git a/chrome/browser/net/errorpage_browsertest.cc b/chrome/browser/net/errorpage_browsertest.cc
index 1fc3187..8460a2ad 100644
--- a/chrome/browser/net/errorpage_browsertest.cc
+++ b/chrome/browser/net/errorpage_browsertest.cc
@@ -1082,7 +1082,8 @@
       : web_app::SystemWebAppBrowserTestBase(true) {}
 };
 
-IN_PROC_BROWSER_TEST_F(ErrorPageOfflineAppLaunchTest, DiagnosticsConnectivity) {
+IN_PROC_BROWSER_TEST_F(ErrorPageOfflineAppLaunchTest,
+                       DISABLED_DiagnosticsConnectivity) {
   WaitForTestSystemAppInstall();
   ASSERT_TRUE(ui_test_utils::NavigateToURL(
       browser(),
diff --git a/chrome/browser/net/profile_network_context_service.cc b/chrome/browser/net/profile_network_context_service.cc
index e0a3e473..c052559 100644
--- a/chrome/browser/net/profile_network_context_service.cc
+++ b/chrome/browser/net/profile_network_context_service.cc
@@ -707,10 +707,25 @@
         local_state->GetFilePath(prefs::kDiskCacheDir);
     if (!disk_cache_dir.empty())
       base_cache_path = disk_cache_dir.Append(base_cache_path.BaseName());
-    network_context_params->http_cache_path =
+    base::FilePath http_cache_path =
         base_cache_path.Append(chrome::kCacheDirname);
-    network_context_params->http_cache_max_size =
-        local_state->GetInteger(prefs::kDiskCacheSize);
+    if (base::FeatureList::IsEnabled(features::kDisableHttpDiskCache)) {
+      // Clear any existing on-disk cache first since if the user tries to
+      // remove the cache it would only affect the in-memory cache while in the
+      // experiment.
+      base::ThreadPool::PostTask(
+          FROM_HERE,
+          {base::TaskPriority::BEST_EFFORT, base::MayBlock(),
+           base::TaskShutdownBehavior::CONTINUE_ON_SHUTDOWN},
+          base::BindOnce(base::GetDeletePathRecursivelyCallback(),
+                         http_cache_path));
+      network_context_params->http_cache_max_size =
+          features::kDisableHttpDiskCacheMemoryCacheSizeParam.Get();
+    } else {
+      network_context_params->http_cache_path = http_cache_path;
+      network_context_params->http_cache_max_size =
+          local_state->GetInteger(prefs::kDiskCacheSize);
+    }
 
     network_context_params->file_paths =
         ::network::mojom::NetworkContextFilePaths::New();
@@ -747,6 +762,8 @@
 
     network_context_params->file_paths->transport_security_persister_file_name =
         base::FilePath(chrome::kTransportSecurityPersisterFilename);
+    network_context_params->file_paths->sct_auditing_pending_reports_file_name =
+        base::FilePath(chrome::kSCTAuditingPendingReportsFileName);
   }
   const base::Value* hsts_policy_bypass_list =
       g_browser_process->local_state()->GetList(prefs::kHSTSPolicyBypassList);
diff --git a/chrome/browser/page_load_metrics/page_load_metrics_browsertest.cc b/chrome/browser/page_load_metrics/page_load_metrics_browsertest.cc
index 2931e64c..ffb259f 100644
--- a/chrome/browser/page_load_metrics/page_load_metrics_browsertest.cc
+++ b/chrome/browser/page_load_metrics/page_load_metrics_browsertest.cc
@@ -26,7 +26,6 @@
 #include "base/time/time.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
-#include "build/os_buildflags.h"
 #include "chrome/browser/page_load_metrics/observers/aborts_page_load_metrics_observer.h"
 #include "chrome/browser/page_load_metrics/observers/core/ukm_page_load_metrics_observer.h"
 #include "chrome/browser/page_load_metrics/observers/document_write_page_load_metrics_observer.h"
diff --git a/chrome/browser/pdf/pdf_extension_test.cc b/chrome/browser/pdf/pdf_extension_test.cc
index f300450..ce1e519 100644
--- a/chrome/browser/pdf/pdf_extension_test.cc
+++ b/chrome/browser/pdf/pdf_extension_test.cc
@@ -18,7 +18,6 @@
 #include "base/files/file_enumerator.h"
 #include "base/files/file_util.h"
 #include "base/hash/hash.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/memory/raw_ptr.h"
 #include "base/memory/ref_counted.h"
@@ -1183,7 +1182,7 @@
   // TODO(crbug.com/1228987): Load success or failure is non-deterministic
   // currently, due to races between viewport messages and loading. For this
   // test, we only care that loading terminated, not about success or failure.
-  ignore_result(pdf_extension_test_util::EnsurePDFHasLoaded(contents));
+  std::ignore = pdf_extension_test_util::EnsurePDFHasLoaded(contents);
 }
 
 IN_PROC_BROWSER_TEST_P(PDFExtensionJSTest, ViewerToolbar) {
diff --git a/chrome/browser/performance_manager/policies/bfcache_policy_browsertest.cc b/chrome/browser/performance_manager/policies/bfcache_policy_browsertest.cc
index 271e025..06b0b9f 100644
--- a/chrome/browser/performance_manager/policies/bfcache_policy_browsertest.cc
+++ b/chrome/browser/performance_manager/policies/bfcache_policy_browsertest.cc
@@ -12,7 +12,7 @@
 #include "base/run_loop.h"
 #include "base/test/bind.h"
 #include "base/test/scoped_feature_list.h"
-#include "build/os_buildflags.h"
+#include "build/build_config.h"
 #include "chrome/browser/ui/browser.h"
 #include "chrome/test/base/in_process_browser_test.h"
 #include "chrome/test/base/ui_test_utils.h"
diff --git a/chrome/browser/plugins/plugin_response_interceptor_url_loader_throttle.cc b/chrome/browser/plugins/plugin_response_interceptor_url_loader_throttle.cc
index ae5c53a9..8179ba9 100644
--- a/chrome/browser/plugins/plugin_response_interceptor_url_loader_throttle.cc
+++ b/chrome/browser/plugins/plugin_response_interceptor_url_loader_throttle.cc
@@ -4,12 +4,12 @@
 
 #include "chrome/browser/plugins/plugin_response_interceptor_url_loader_throttle.h"
 
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/feature_list.h"
 #include "base/guid.h"
-#include "base/ignore_result.h"
 #include "chrome/browser/extensions/api/streams_private/streams_private_api.h"
 #include "chrome/browser/plugins/plugin_utils.h"
 #include "content/public/browser/browser_task_traits.h"
@@ -131,7 +131,7 @@
   std::string payload = view_id;
 
   mojo::PendingRemote<network::mojom::URLLoader> dummy_new_loader;
-  ignore_result(dummy_new_loader.InitWithNewPipeAndPassReceiver());
+  std::ignore = dummy_new_loader.InitWithNewPipeAndPassReceiver();
   mojo::Remote<network::mojom::URLLoaderClient> new_client;
   mojo::PendingReceiver<network::mojom::URLLoaderClient> new_client_receiver =
       new_client.BindNewPipeAndPassReceiver();
diff --git a/chrome/browser/portal/portal_recently_audible_browsertest.cc b/chrome/browser/portal/portal_recently_audible_browsertest.cc
index c799323..a84c9593 100644
--- a/chrome/browser/portal/portal_recently_audible_browsertest.cc
+++ b/chrome/browser/portal/portal_recently_audible_browsertest.cc
@@ -2,8 +2,9 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
+
 #include "base/containers/contains.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/test/test_timeouts.h"
 #include "base/threading/thread_task_runner_handle.h"
@@ -238,7 +239,7 @@
   // Ideally this would never briefly flicker to false, but it can because the
   // hystersis here applies at the WebContents level, not the tab level, and
   // portals swaps WebContents. So if it does change to false, ignore that...
-  ignore_result(ActiveTabChangesTo(TabAlertState::AUDIO_PLAYING, false));
+  std::ignore = ActiveTabChangesTo(TabAlertState::AUDIO_PLAYING, false);
 
   // ...for it will shortly become true again.
   EXPECT_TRUE(ActiveTabChangesTo(TabAlertState::AUDIO_PLAYING, true));
diff --git a/chrome/browser/predictors/predictor_database.cc b/chrome/browser/predictors/predictor_database.cc
index 9465c76b..e593300 100644
--- a/chrome/browser/predictors/predictor_database.cc
+++ b/chrome/browser/predictors/predictor_database.cc
@@ -11,7 +11,6 @@
 #include "base/check.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/task/sequenced_task_runner.h"
 #include "chrome/browser/predictors/autocomplete_action_predictor_table.h"
 #include "chrome/browser/predictors/loading_predictor_config.h"
@@ -118,10 +117,6 @@
   autocomplete_table_->Initialize(db_.get());
   resource_prefetch_tables_->Initialize(db_.get());
 
-  // The logged_in_predictor table is obsolete as of Chrome 44.
-  // TODO(davidben): Remove this after April 16, 2016.
-  ignore_result(db_->Execute("DROP TABLE IF EXISTS logged_in_predictor"));
-
   LogDatabaseStats();
 }
 
diff --git a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.cc b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.cc
index 1d3d1ea..e3eaad9 100644
--- a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.cc
+++ b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.cc
@@ -5,6 +5,7 @@
 #include "chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.h"
 
 #include "chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.h"
+#include "streaming_search_prefetch_request.h"
 
 StreamingSearchPrefetchRequest::StreamingSearchPrefetchRequest(
     const GURL& prefetch_url,
@@ -19,7 +20,9 @@
     std::unique_ptr<network::ResourceRequest> resource_request,
     const net::NetworkTrafficAnnotationTag& network_traffic_annotation) {
   streaming_url_loader_ = std::make_unique<StreamingSearchPrefetchURLLoader>(
-      this, profile, std::move(resource_request), network_traffic_annotation);
+      this, profile, std::move(resource_request), network_traffic_annotation,
+      base::BindOnce(&StreamingSearchPrefetchRequest::StopPrefetch,
+                     weak_factory_.GetWeakPtr()));
 }
 
 std::unique_ptr<SearchPrefetchURLLoader>
diff --git a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.h b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.h
index ff051c6..ad75d40 100644
--- a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.h
+++ b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_request.h
@@ -47,6 +47,8 @@
  private:
   // The ongoing prefetch request. Null before and after the fetch.
   std::unique_ptr<StreamingSearchPrefetchURLLoader> streaming_url_loader_;
+
+  base::WeakPtrFactory<StreamingSearchPrefetchRequest> weak_factory_{this};
 };
 
 #endif  // CHROME_BROWSER_PREFETCH_SEARCH_PREFETCH_STREAMING_SEARCH_PREFETCH_REQUEST_H_
diff --git a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.cc b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.cc
index cf2a420..0c3f0c9 100644
--- a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.cc
+++ b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.cc
@@ -26,15 +26,18 @@
 #include "services/network/public/cpp/shared_url_loader_factory.h"
 #include "services/network/public/mojom/early_hints.mojom.h"
 #include "services/network/public/mojom/url_response_head.mojom.h"
+#include "streaming_search_prefetch_url_loader.h"
 #include "url/gurl.h"
 
 StreamingSearchPrefetchURLLoader::StreamingSearchPrefetchURLLoader(
     StreamingSearchPrefetchRequest* streaming_prefetch_request,
     Profile* profile,
     std::unique_ptr<network::ResourceRequest> resource_request,
-    const net::NetworkTrafficAnnotationTag& network_traffic_annotation)
+    const net::NetworkTrafficAnnotationTag& network_traffic_annotation,
+    base::OnceClosure stop_prefetch_closure)
     : resource_request_(std::move(resource_request)),
-      streaming_prefetch_request_(streaming_prefetch_request) {
+      streaming_prefetch_request_(streaming_prefetch_request),
+      stop_prefetch_closure_(std::move(stop_prefetch_closure)) {
   DCHECK(streaming_prefetch_request_);
   auto url_loader_factory = profile->GetDefaultStoragePartition()
                                 ->GetURLLoaderFactoryForBrowserProcess();
@@ -126,7 +129,7 @@
   if (streaming_prefetch_request_) {
     streaming_prefetch_request_->ErrorEncountered();
   } else {
-    delete this;
+    PostTaskToStopPrefetchAndDeleteSelf();
   }
 }
 
@@ -210,7 +213,7 @@
       mojo::CreateDataPipe(&options, producer_handle_, consumer_handle);
 
   if (rv != MOJO_RESULT_OK) {
-    delete this;
+    PostTaskToStopPrefetchAndDeleteSelf();
     return;
   }
 
@@ -232,7 +235,7 @@
     MojoResult result,
     const mojo::HandleSignalsState& state) {
   if (result != MOJO_RESULT_OK) {
-    delete this;
+    PostTaskToStopPrefetchAndDeleteSelf();
     return;
   }
   PushData();
@@ -258,7 +261,7 @@
     }
 
     if (result != MOJO_RESULT_OK) {
-      delete this;
+      PostTaskToStopPrefetchAndDeleteSelf();
       return;
     }
 
@@ -347,16 +350,24 @@
     DCHECK(streaming_prefetch_request_);
     streaming_prefetch_request_->ErrorEncountered();
   } else {
-    delete this;
+    PostTaskToStopPrefetchAndDeleteSelf();
   }
 }
 
 void StreamingSearchPrefetchURLLoader::OnURLLoaderClientMojoDisconnect() {
   DCHECK(forwarding_client_);
   DCHECK(!streaming_prefetch_request_);
-  delete this;
+  PostTaskToStopPrefetchAndDeleteSelf();
 }
 
 void StreamingSearchPrefetchURLLoader::ClearOwnerPointer() {
   streaming_prefetch_request_ = nullptr;
 }
+
+void StreamingSearchPrefetchURLLoader::PostTaskToStopPrefetchAndDeleteSelf() {
+  // To avoid UAF bugs, post a separate task to delete this object.
+  if (stop_prefetch_closure_) {
+    base::SequencedTaskRunnerHandle::Get()->PostTask(
+        FROM_HERE, std::move(stop_prefetch_closure_));
+  }
+}
diff --git a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.h b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.h
index c49a0e0..bdf2924 100644
--- a/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.h
+++ b/chrome/browser/prefetch/search_prefetch/streaming_search_prefetch_url_loader.h
@@ -40,7 +40,8 @@
       StreamingSearchPrefetchRequest* streaming_prefetch_request,
       Profile* profile,
       std::unique_ptr<network::ResourceRequest> resource_request,
-      const net::NetworkTrafficAnnotationTag& network_traffic_annotation);
+      const net::NetworkTrafficAnnotationTag& network_traffic_annotation,
+      base::OnceClosure stop_prefetch_closure);
 
   ~StreamingSearchPrefetchURLLoader() override;
 
@@ -106,6 +107,9 @@
   // Clears |producer_handle_| and |handle_watcher_|.
   void Finish();
 
+  // Post a task to delete this object by running stop_prefetch_closure_.
+  void PostTaskToStopPrefetchAndDeleteSelf();
+
   // Sets up mojo forwarding to the navigation path. Resumes
   // |network_url_loader_| calls. Serves the start of the response to the
   // navigation path. After this method is called, |this| manages its own
@@ -165,6 +169,9 @@
   mojo::ScopedDataPipeProducerHandle producer_handle_;
   std::unique_ptr<mojo::SimpleWatcher> handle_watcher_;
 
+  // Closure to cancel this prefetch. Running this callback will destroy |this|.
+  base::OnceClosure stop_prefetch_closure_;
+
   base::WeakPtrFactory<StreamingSearchPrefetchURLLoader> weak_factory_{this};
 };
 
diff --git a/chrome/browser/printing/cloud_print/cloud_print_proxy_service_unittest.cc b/chrome/browser/printing/cloud_print/cloud_print_proxy_service_unittest.cc
index fb6b838..1e4d705 100644
--- a/chrome/browser/printing/cloud_print/cloud_print_proxy_service_unittest.cc
+++ b/chrome/browser/printing/cloud_print/cloud_print_proxy_service_unittest.cc
@@ -8,11 +8,11 @@
 
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/location.h"
 #include "base/run_loop.h"
 #include "base/task/single_thread_task_runner.h"
@@ -161,7 +161,7 @@
             &TestCloudPrintProxyService::HandleCloudPrintProxyRequest,
             base::Unretained(this)));
     mojo::PendingRemote<service_manager::mojom::InterfaceProvider> handle;
-    ignore_result(handle.InitWithNewPipeAndPassReceiver());
+    std::ignore = handle.InitWithNewPipeAndPassReceiver();
     process_control_.SetMojoHandle(std::move(handle));
   }
 
diff --git a/chrome/browser/profiles/chrome_browser_main_extra_parts_profiles.cc b/chrome/browser/profiles/chrome_browser_main_extra_parts_profiles.cc
index 074ea8a..98cd5b7 100644
--- a/chrome/browser/profiles/chrome_browser_main_extra_parts_profiles.cc
+++ b/chrome/browser/profiles/chrome_browser_main_extra_parts_profiles.cc
@@ -9,7 +9,6 @@
 
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
-#include "build/os_buildflags.h"
 #include "chrome/browser/accuracy_tips/accuracy_service_factory.h"
 #include "chrome/browser/autocomplete/autocomplete_classifier_factory.h"
 #include "chrome/browser/autocomplete/in_memory_url_index_factory.h"
diff --git a/chrome/browser/profiles/keep_alive/profile_keep_alive_types.cc b/chrome/browser/profiles/keep_alive/profile_keep_alive_types.cc
index 7c364d8..a5d217af 100644
--- a/chrome/browser/profiles/keep_alive/profile_keep_alive_types.cc
+++ b/chrome/browser/profiles/keep_alive/profile_keep_alive_types.cc
@@ -53,6 +53,8 @@
       return out << "kWebAppUpdate";
     case ProfileKeepAliveOrigin::kGettingWebAppInfo:
       return out << "kGettingWebAppInfo";
+    case ProfileKeepAliveOrigin::kCrxInstaller:
+      return out << "kCrxInstaller";
   }
   NOTREACHED();
   return out << static_cast<int>(origin);
diff --git a/chrome/browser/profiles/keep_alive/profile_keep_alive_types.h b/chrome/browser/profiles/keep_alive/profile_keep_alive_types.h
index 5a3148e..02e54bc 100644
--- a/chrome/browser/profiles/keep_alive/profile_keep_alive_types.h
+++ b/chrome/browser/profiles/keep_alive/profile_keep_alive_types.h
@@ -104,7 +104,10 @@
   // --list-apps switch.
   kGettingWebAppInfo = 23,
 
-  kMaxValue = kGettingWebAppInfo,
+  // An extension .crx is being installed.
+  kCrxInstaller = 24,
+
+  kMaxValue = kCrxInstaller,
 };
 
 std::ostream& operator<<(std::ostream& out,
diff --git a/chrome/browser/profiles/keep_alive/scoped_profile_keep_alive.cc b/chrome/browser/profiles/keep_alive/scoped_profile_keep_alive.cc
index a709aac..5f26b2a 100644
--- a/chrome/browser/profiles/keep_alive/scoped_profile_keep_alive.cc
+++ b/chrome/browser/profiles/keep_alive/scoped_profile_keep_alive.cc
@@ -45,6 +45,10 @@
     const Profile* profile,
     ProfileKeepAliveOrigin origin) {
   DCHECK_CURRENTLY_ON(content::BrowserThread::UI);
+  // |g_browser_process| could be nullptr if this is called during shutdown,
+  // e.g. in tests.
+  if (!g_browser_process)
+    return;
   // |profile_manager| could be nullptr if this is called during shutdown, e.g.
   // for system/guest profiles or in tests.
   auto* profile_manager = g_browser_process->profile_manager();
diff --git a/chrome/browser/profiles/profile_manager.cc b/chrome/browser/profiles/profile_manager.cc
index 798a594..e7d59e6 100644
--- a/chrome/browser/profiles/profile_manager.cc
+++ b/chrome/browser/profiles/profile_manager.cc
@@ -68,7 +68,6 @@
 #include "chrome/browser/profiles/profiles_state.h"
 #include "chrome/browser/signin/account_reconcilor_factory.h"
 #include "chrome/browser/signin/identity_manager_factory.h"
-#include "chrome/browser/signin/primary_account_policy_manager_factory.h"
 #include "chrome/browser/signin/signin_util.h"
 #include "chrome/browser/sync/sync_service_factory.h"
 #include "chrome/browser/ui/startup/startup_browser_creator.h"
@@ -1548,7 +1547,7 @@
   // had enough time to initialize and should have updated the user signout
   // flag attached to the profile.
   signin_util::EnsureUserSignoutAllowedIsInitializedForProfile(profile);
-  PrimaryAccountPolicyManagerFactory::GetForProfile(profile)->Initialize();
+  signin_util::EnsurePrimaryAccountAllowedForProfile(profile);
 
 #if !defined(OS_ANDROID)
   // The caret browsing command-line switch toggles caret browsing on
diff --git a/chrome/browser/resources/access_code_cast/access_code_cast.ts b/chrome/browser/resources/access_code_cast/access_code_cast.ts
index a71f5d7..b40c6f8 100644
--- a/chrome/browser/resources/access_code_cast/access_code_cast.ts
+++ b/chrome/browser/resources/access_code_cast/access_code_cast.ts
@@ -63,6 +63,10 @@
     this.router = BrowserProxy.getInstance().callbackRouter;
 
     this.accessCode = '';
+
+    window.onblur = () => {
+      this.close();
+    };
   }
 
   ready() {
diff --git a/chrome/browser/resources/chromeos/edu_coexistence/edu_coexistence_template.html b/chrome/browser/resources/chromeos/edu_coexistence/edu_coexistence_template.html
index c41e908..d6f32db 100644
--- a/chrome/browser/resources/chromeos/edu_coexistence/edu_coexistence_template.html
+++ b/chrome/browser/resources/chromeos/edu_coexistence/edu_coexistence_template.html
@@ -2,11 +2,11 @@
   :host {
     overflow-y: hidden;
     --background-gradient-0: linear-gradient(0deg,
-        rgba(var(--google-grey-refresh-100-rgb), 1) 0,
-        rgba(var(--google-grey-refresh-100-rgb), 0) 8px);
+        rgba(var(--google-grey-100-rgb), 1) 0,
+        rgba(var(--google-grey-100-rgb), 0) 8px);
     --background-gradient-180: linear-gradient(180deg,
-        rgba(var(--google-grey-refresh-100-rgb), 1) 0,
-        rgba(var(--google-grey-refresh-100-rgb), 0) 8px);
+        rgba(var(--google-grey-100-rgb), 1) 0,
+        rgba(var(--google-grey-100-rgb), 0) 8px);
   }
 </style>
 <div class="template-container">
diff --git a/chrome/browser/resources/chromeos/emoji_picker/emoji_button.html b/chrome/browser/resources/chromeos/emoji_picker/emoji_button.html
index 46f3abb..8b30593d 100644
--- a/chrome/browser/resources/chromeos/emoji_picker/emoji_button.html
+++ b/chrome/browser/resources/chromeos/emoji_picker/emoji_button.html
@@ -54,7 +54,7 @@
     * dark mode since dark mode is the same.
     */
     background: linear-gradient(
-        315deg, var(--google-grey-refresh-500) 4px,
+        315deg, var(--google-grey-500) 4px,
         var(--emoji-background) 4px, var(--emoji-background));
     content: '';
     display: block;
diff --git a/chrome/browser/resources/chromeos/login/components/common_styles/common_styles.html b/chrome/browser/resources/chromeos/login/components/common_styles/common_styles.html
index 133fa9d..41b569b 100644
--- a/chrome/browser/resources/chromeos/login/components/common_styles/common_styles.html
+++ b/chrome/browser/resources/chromeos/login/components/common_styles/common_styles.html
@@ -45,22 +45,22 @@
          OobeScrollableBehavior. */
       .scrollable.can-scroll:not(.is-scrolled):not(.scrolled-to-bottom) {
         background: linear-gradient(0deg,
-                        rgba(var(--google-grey-refresh-100-rgb), 1) 0,
-                        rgba(var(--google-grey-refresh-100-rgb), 0) 8px);
+                        rgba(var(--google-grey-100-rgb), 1) 0,
+                        rgba(var(--google-grey-100-rgb), 0) 8px);
 
       }
       .scrollable.can-scroll.is-scrolled:not(.scrolled-to-bottom) {
         background: linear-gradient(0deg,
-                        rgba(var(--google-grey-refresh-100-rgb), 1) 0,
-                        rgba(var(--google-grey-refresh-100-rgb), 0) 8px),
+                        rgba(var(--google-grey-100-rgb), 1) 0,
+                        rgba(var(--google-grey-100-rgb), 0) 8px),
                     linear-gradient(180deg,
-                        rgba(var(--google-grey-refresh-100-rgb), 1) 0,
-                        rgba(var(--google-grey-refresh-100-rgb), 0) 8px);
+                        rgba(var(--google-grey-100-rgb), 1) 0,
+                        rgba(var(--google-grey-100-rgb), 0) 8px);
       }
       .scrollable.is-scrolled.scrolled-to-bottom {
         background: linear-gradient(180deg,
-                        rgba(var(--google-grey-refresh-100-rgb), 1) 0,
-                        rgba(var(--google-grey-refresh-100-rgb), 0) 8px);
+                        rgba(var(--google-grey-100-rgb), 1) 0,
+                        rgba(var(--google-grey-100-rgb), 0) 8px);
       }
 
       /* Links styles used within OOBE */
diff --git a/chrome/browser/resources/chromeos/login/screens/common/hw_data_collection.html b/chrome/browser/resources/chromeos/login/screens/common/hw_data_collection.html
index de9106f7..f776e512 100644
--- a/chrome/browser/resources/chromeos/login/screens/common/hw_data_collection.html
+++ b/chrome/browser/resources/chromeos/login/screens/common/hw_data_collection.html
@@ -21,7 +21,7 @@
   <template>
     <style include="oobe-dialog-host-styles">
       #dataUsageLabelContainer {
-        color: var(--google-grey-refresh-700); /* #5F6368 */
+        color: var(--google-grey-700); /* #5F6368 */
         line-height: 18px;
       }
 
diff --git a/chrome/browser/resources/chromeos/login/screens/oobe/oobe_eula.html b/chrome/browser/resources/chromeos/login/screens/oobe/oobe_eula.html
index 9f10f5a..a0bd9e84 100644
--- a/chrome/browser/resources/chromeos/login/screens/oobe/oobe_eula.html
+++ b/chrome/browser/resources/chromeos/login/screens/oobe/oobe_eula.html
@@ -80,7 +80,7 @@
       }
 
       #usageStatsLabelContainer {
-        color: var(--google-grey-refresh-700); /* #5F6368 */
+        color: var(--google-grey-700); /* #5F6368 */
         line-height: 18px;
       }
 
diff --git a/chrome/browser/resources/chromeos/login/screens/oobe/welcome.html b/chrome/browser/resources/chromeos/login/screens/oobe/welcome.html
index d573284c..77d714e 100644
--- a/chrome/browser/resources/chromeos/login/screens/oobe/welcome.html
+++ b/chrome/browser/resources/chromeos/login/screens/oobe/welcome.html
@@ -79,7 +79,7 @@
       }
 
       #oobeAdvancedOptionsScreen .advanced-option-subtitle {
-        color: var(--google-grey-refresh-700);
+        color: var(--google-grey-700);
       }
     </style>
     <oobe-welcome-dialog id="welcomeScreen" role="dialog" for-step="greeting"
diff --git a/chrome/browser/resources/feedback_webui/css/feedback.css b/chrome/browser/resources/feedback_webui/css/feedback.css
index 007821b..c3636b2 100644
--- a/chrome/browser/resources/feedback_webui/css/feedback.css
+++ b/chrome/browser/resources/feedback_webui/css/feedback.css
@@ -8,7 +8,6 @@
 }
 
 body {
-  background-color: #fbfbfb;
   display: flex;
   flex-direction: column;
   height: 100%;
@@ -24,9 +23,9 @@
 .title-bar {
   -webkit-align-items: center;
   -webkit-app-region: drag;
-  background-color: #fff;
-  box-shadow: 0 1px #d0d0d0;
-  color: rgb(80, 80, 82);
+  background-color: var(--feedback-bg-color);
+  box-shadow: 0 1px var(--feedback-box-shadow-color);
+  color: var(--feedback-primary-color);
   display: flex;
   flex-grow: 0;
   font-size: 15px;
@@ -50,7 +49,7 @@
 }
 
 .content {
-  color: #444;
+  color: var(--feedback-primary-color);
   font-size: 12px;
 }
 
@@ -59,7 +58,7 @@
 }
 
 .content #description-text {
-  border-color: #c8c8c8;
+  border-color: var(--feedback-separator-color);
   box-sizing: border-box;
   height: 120px;
   line-height: 18px;
@@ -86,18 +85,18 @@
 }
 
 .content .text-field-container > select {
-  border: 1px solid #c8c8c8;
-  color: #585858;
+  border: 1px solid var(--feedback-separator-color);
+  color: var(--feedback-secondary-color);
   flex: 1 1 auto;
   height: 100%;
   padding-inline-start: 5px;
 }
 
 .content .text-field-container > input[type=text] {
-  flex: 1 1 auto;
   border: 1px solid;
-  border-color: #c8c8c8;
-  color: #585858;
+  border-color: var(--feedback-separator-color);
+  color: var(--feedback-secondary-color);
+  flex: 1 1 auto;
   height: 100%;
   padding-inline-start: 5px;
 }
@@ -107,7 +106,7 @@
 }
 
 .content .description-empty-notification {
-  color: rgb(204, 0, 0);
+  color: var(--feedback-alert-color);
   font-weight: bold;
 }
 
@@ -228,7 +227,7 @@
 }
 
 .content .attach-file-notification {
-  color: rgb(204, 0, 0);
+  color: var(--feedback-alert-color);
   font-weight: bold;
 }
 
@@ -239,7 +238,7 @@
 
 button.blue-button {
   color: #fff;
-  text-shadow: 1px sharp drop shadow rgb(45, 106, 218);
+  text-shadow: 1px sharp drop shadow var(--feedback-prominent-color);
 }
 
 /* Used for elements that are hidden but not ignored by screen reader. */
diff --git a/chrome/browser/resources/feedback_webui/css/feedback_shared_vars.css b/chrome/browser/resources/feedback_webui/css/feedback_shared_vars.css
index 195bb77..a8a9583 100644
--- a/chrome/browser/resources/feedback_webui/css/feedback_shared_vars.css
+++ b/chrome/browser/resources/feedback_webui/css/feedback_shared_vars.css
@@ -4,25 +4,42 @@
 
 html:not(body) {
   /* Google colors used in UI. */
-  --google-blue-300: rgb(138, 180, 248);
+  --google-blue-50: rgb(232, 240, 254);
+  --google-blue-300-rgb: 138, 180, 248;
+  --google-blue-300: rgb(var(--google-blue-300-rgb));
   --google-blue-600: rgb(26, 115, 232);
 
   --google-grey-200: rgb(232, 234, 237);
-  --google-grey-900: rgb(32, 33, 36);
+  --google-grey-500: rgb(154, 160, 166);
+  --google-grey-700: rgb(95, 99, 104);
+  --google-grey-900-rgb: 32, 33, 36;
+  --google-grey-900: rgb(var(--google-grey-900-rgb));
 
   --google-red-300: rgb(242, 139, 130);
   --google-red-600: rgb(217, 48, 37);
 
   /* Feedback specific variables. */
-  --feedback-bg-color: #fff;
+  --feedback-alert-color: var(--google-red-600);
+  --feedback-bg-color: rgb(255, 255, 255);
+  --feedback-box-shadow-color: #d0d0d0;
+  --feedback-highlight-color: var(--google-blue-50);
   --feedback-link-color: var(--google-blue-600);
   --feedback-primary-color: var(--google-grey-900);
+  --feedback-prominent-color: var(--google-blue-600);
+  --feedback-secondary-color: var(--google-grey-700);
+  --feedback-separator-color: rgba(0, 0, 0, 0.14);
 }
 
 @media (prefers-color-scheme: dark) {
   html:not(body) {
+    --feedback-alert-color: var(--google-red-300);
     --feedback-bg-color: var(--google-grey-900);
+    --feedback-box-shadow-color: rgba(var(--google-grey-900-rgb), 0.04);
+    --feedback-highlight-color: rgba(var(--google-blue-300-rgb), 0.3);
     --feedback-link-color: var(--google-blue-300);
     --feedback-primary-color: var(--google-grey-200);
+    --feedback-prominent-color: var(--google-blue-300);
+    --feedback-secondary-color: var(--google-grey-500);
+    --feedback-separator-color: rgba(255, 255, 255, 0.14);
   }
 }
diff --git a/chrome/browser/resources/feedback_webui/css/sys_info.css b/chrome/browser/resources/feedback_webui/css/sys_info.css
index f2d8842..98fe1d8 100644
--- a/chrome/browser/resources/feedback_webui/css/sys_info.css
+++ b/chrome/browser/resources/feedback_webui/css/sys_info.css
@@ -13,11 +13,15 @@
 }
 
 #tableTitle {
-  color: #4a4a4a;
+  color: var(--feedback-primary-color);
 }
 
 #status {
-  color: rgb(66, 133, 244);
+  color: var(--feedback-prominent-color);
   display: inline-block;
   margin: .5em .5em;
 }
+
+.list:not(.filtered) tr:nth-child(odd) td {
+  background-color: var(--feedback-highlight-color);
+}
diff --git a/chrome/browser/resources/history/history_item.html b/chrome/browser/resources/history/history_item.html
index 78f2c68..51952ca 100644
--- a/chrome/browser/resources/history/history_item.html
+++ b/chrome/browser/resources/history/history_item.html
@@ -224,6 +224,7 @@
             <template is="dom-if" if="[[item.starred]]">
               <cr-icon-button id="bookmark-star" iron-icon="cr:star"
                   on-click="onRemoveBookmarkTap_"
+                  title="$i18n{removeBookmark}"
                   aria-hidden="true">
               </cr-icon-button>
             </template>
diff --git a/chrome/browser/resources/management/management_browser_proxy.ts b/chrome/browser/resources/management/management_browser_proxy.ts
index a05336d1..78bdba3 100644
--- a/chrome/browser/resources/management/management_browser_proxy.ts
+++ b/chrome/browser/resources/management/management_browser_proxy.ts
@@ -68,6 +68,7 @@
   EXTENSION = 'extension',
   ANDROID_APPLICATION = 'android application',
   LOGIN_LOGOUT = 'login-logout',
+  CRD_SESSIONS = 'crd sessions',
 }
 
 
diff --git a/chrome/browser/resources/management/management_ui.ts b/chrome/browser/resources/management/management_ui.ts
index 164100d..17883b6 100644
--- a/chrome/browser/resources/management/management_ui.ts
+++ b/chrome/browser/resources/management/management_ui.ts
@@ -280,6 +280,8 @@
         return 'management:play-store';
       case DeviceReportingType.LOGIN_LOGOUT:
         return 'management:timelapse';
+      case DeviceReportingType.CRD_SESSIONS:
+        return 'management:timelapse';
       default:
         return 'cr:computer';
     }
diff --git a/chrome/browser/resources/pdf/BUILD.gn b/chrome/browser/resources/pdf/BUILD.gn
index f20f682..3dc781e 100644
--- a/chrome/browser/resources/pdf/BUILD.gn
+++ b/chrome/browser/resources/pdf/BUILD.gn
@@ -53,7 +53,8 @@
   input_files =
       print_preview_non_webcomponents_files + shared_non_webcomponents_files +
       print_preview_webcomponents_files + shared_webcomponents_files
-  input_files_base_dir = rebase_path("$target_gen_dir/$preprocess_folder", "//")
+  input_files_base_dir =
+      rebase_path("$target_gen_dir/$preprocess_folder", root_build_dir)
   deps = [
     ":preprocess",
     ":preprocess_generated",
diff --git a/chrome/browser/resources/pdf/elements/shared-css.html b/chrome/browser/resources/pdf/elements/shared-css.html
index 66dfb56..eea9186 100644
--- a/chrome/browser/resources/pdf/elements/shared-css.html
+++ b/chrome/browser/resources/pdf/elements/shared-css.html
@@ -23,7 +23,7 @@
       --cr-menu-shadow: rgba(0, 0, 0, .3) 0 1px 2px 0,
                         rgba(0, 0, 0, .15) 0 3px 6px 2px;
       --cr-primary-text-color: var(--google-grey-200);
-      --cr-menu-background-focus-color: var(--google-grey-refresh-700);
+      --cr-menu-background-focus-color: var(--google-grey-700);
       --cr-menu-background-sheen: rgba(255, 255, 255, .06);
       --cr-separator-line: var(--cr-separator-height) solid
           rgba(255, 255, 255, .1);
diff --git a/chrome/browser/resources/pdf/elements/viewer-pdf-sidenav.html b/chrome/browser/resources/pdf/elements/viewer-pdf-sidenav.html
index cf7dea86..cc5c8ff3 100644
--- a/chrome/browser/resources/pdf/elements/viewer-pdf-sidenav.html
+++ b/chrome/browser/resources/pdf/elements/viewer-pdf-sidenav.html
@@ -1,6 +1,6 @@
 <style include="pdf-shared cr-hidden-style cr-shared-style">
   :host {
-    --sidenav-selected-tab-color: var(--google-blue-refresh-300);
+    --sidenav-selected-tab-color: var(--google-blue-300);
     background-color: var(--viewer-pdf-toolbar-background-color);
     display: flex;
     height: 100%;
diff --git a/chrome/browser/resources/pdf/elements/viewer-properties-dialog.html b/chrome/browser/resources/pdf/elements/viewer-properties-dialog.html
index 19c99f2..18d3ad9 100644
--- a/chrome/browser/resources/pdf/elements/viewer-properties-dialog.html
+++ b/chrome/browser/resources/pdf/elements/viewer-properties-dialog.html
@@ -12,7 +12,7 @@
   }
 
   .break > td {
-    --break-color: var(--google-grey-refresh-300);
+    --break-color: var(--google-grey-300);
     border-bottom: 1px solid var(--break-color);
     padding-bottom: var(--break-padding);
   }
diff --git a/chrome/browser/resources/pdf/elements/viewer-thumbnail.html b/chrome/browser/resources/pdf/elements/viewer-thumbnail.html
index d9fd672..b0cdb08c 100644
--- a/chrome/browser/resources/pdf/elements/viewer-thumbnail.html
+++ b/chrome/browser/resources/pdf/elements/viewer-thumbnail.html
@@ -1,6 +1,6 @@
 <style>
   :host {
-    --focus-border-color: var(--google-blue-refresh-300);
+    --focus-border-color: var(--google-blue-300);
     display: block;
   }
 
diff --git a/chrome/browser/resources/pdf/elements/viewer-toolbar.html b/chrome/browser/resources/pdf/elements/viewer-toolbar.html
index e6d49e2..08eadb8 100644
--- a/chrome/browser/resources/pdf/elements/viewer-toolbar.html
+++ b/chrome/browser/resources/pdf/elements/viewer-toolbar.html
@@ -132,7 +132,7 @@
   }
 
   paper-progress {
-    --paper-progress-active-color: var(--google-blue-refresh-300);
+    --paper-progress-active-color: var(--google-blue-300);
     --paper-progress-container-color: transparent;
     --paper-progress-height: 3px;
     bottom: 0;
diff --git a/chrome/browser/resources/pdf/pdf_viewer_pp.js b/chrome/browser/resources/pdf/pdf_viewer_pp.js
index 28ce7cf1..eb4edb5a 100644
--- a/chrome/browser/resources/pdf/pdf_viewer_pp.js
+++ b/chrome/browser/resources/pdf/pdf_viewer_pp.js
@@ -362,7 +362,7 @@
 }
 
 /**
- * The background color used for print preview (--google-grey-refresh-300). Keep
+ * The background color used for print preview (--google-grey-300). Keep
  * in sync with `ChromePdfStreamDelegate::MapToOriginalUrl()`.
  * @type {number}
  */
@@ -370,7 +370,7 @@
 
 /**
  * The background color used for print preview when dark mode is enabled
- * (--google-grey-refresh-700).
+ * (--google-grey-700).
  * @type {number}
  */
 const PRINT_PREVIEW_DARK_BACKGROUND_COLOR = 0xff5f6368;
diff --git a/chrome/browser/safe_browsing/chrome_cleaner/reporter_runner_win.cc b/chrome/browser/safe_browsing/chrome_cleaner/reporter_runner_win.cc
index bf117cf..11d1d3c4 100644
--- a/chrome/browser/safe_browsing/chrome_cleaner/reporter_runner_win.cc
+++ b/chrome/browser/safe_browsing/chrome_cleaner/reporter_runner_win.cc
@@ -8,6 +8,7 @@
 
 #include <algorithm>
 #include <memory>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -17,7 +18,6 @@
 #include "base/command_line.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/metrics/field_trial.h"
 #include "base/metrics/histogram_macros.h"
 #include "base/metrics/sparse_histogram.h"
@@ -470,7 +470,7 @@
 
     // The reporter sequence has been scheduled to run, so don't notify that
     // it has not been scheduled.
-    ignore_result(scoped_runner.Release());
+    std::ignore = scoped_runner.Release();
   }
 
  private:
@@ -620,8 +620,8 @@
     if (!invocations_.container().empty()) {
       // If there are other invocations to start, then we shouldn't finalize
       // this object. ScopedClosureRunner::Release requires its return value to
-      // be used, so simply ignore_result it, since it will not be needed.
-      ignore_result(scoped_runner.Release());
+      // be used, so simply std::ignore it, since it will not be needed.
+      std::ignore = scoped_runner.Release();
       PostNextInvocation();
     }
 
diff --git a/chrome/browser/safe_browsing/incident_reporting/last_download_finder.cc b/chrome/browser/safe_browsing/incident_reporting/last_download_finder.cc
index 1de851e..c0670cb 100644
--- a/chrome/browser/safe_browsing/incident_reporting/last_download_finder.cc
+++ b/chrome/browser/safe_browsing/incident_reporting/last_download_finder.cc
@@ -10,10 +10,10 @@
 #include <algorithm>
 #include <functional>
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/memory/ptr_util.h"
 #include "base/strings/string_util.h"
 #include "base/strings/utf_string_conversions.h"
@@ -187,7 +187,7 @@
   download_request->set_url(download.url_chain.back().spec());
   // digests is a required field, so force it to exist.
   // TODO(grt): Include digests in reports; http://crbug.com/389123.
-  ignore_result(download_request->mutable_digests());
+  std::ignore = download_request->mutable_digests();
   download_request->set_length(download.received_bytes);
   for (size_t i = 0; i < download.url_chain.size(); ++i) {
     const GURL& url = download.url_chain[i];
diff --git a/chrome/browser/share/android/javatests/src/org/chromium/chrome/browser/share/share_sheet/ChromeProvidedSharingOptionsProviderTest.java b/chrome/browser/share/android/javatests/src/org/chromium/chrome/browser/share/share_sheet/ChromeProvidedSharingOptionsProviderTest.java
index 11f292c..669ed7b 100644
--- a/chrome/browser/share/android/javatests/src/org/chromium/chrome/browser/share/share_sheet/ChromeProvidedSharingOptionsProviderTest.java
+++ b/chrome/browser/share/android/javatests/src/org/chromium/chrome/browser/share/share_sheet/ChromeProvidedSharingOptionsProviderTest.java
@@ -162,6 +162,7 @@
 
     @Test
     @MediumTest
+    @DisabledTest(message = "http://crbug/1285362")
     @Features.EnableFeatures({ChromeFeatureList.LIGHTWEIGHT_REACTIONS})
     public void getPropertyModels_lightweightReactionsEnabled() {
         setUpChromeProvidedSharingOptionsProviderTest(
diff --git a/chrome/browser/shared_highlighting/shared_highlighting_browsertest.cc b/chrome/browser/shared_highlighting/shared_highlighting_browsertest.cc
index daf7c78e..75bd2a8 100644
--- a/chrome/browser/shared_highlighting/shared_highlighting_browsertest.cc
+++ b/chrome/browser/shared_highlighting/shared_highlighting_browsertest.cc
@@ -2,7 +2,6 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
 #include "base/strings/string_util.h"
 #include "base/strings/utf_string_conversions.h"
 #include "build/build_config.h"
diff --git a/chrome/browser/signin/primary_account_policy_manager.cc b/chrome/browser/signin/primary_account_policy_manager.cc
deleted file mode 100644
index 35890f8..0000000
--- a/chrome/browser/signin/primary_account_policy_manager.cc
+++ /dev/null
@@ -1,52 +0,0 @@
-// Copyright 2022 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#include "chrome/browser/signin/primary_account_policy_manager.h"
-
-#include "chrome/browser/browser_process.h"
-#include "chrome/browser/profiles/profile.h"
-#include "chrome/browser/signin/signin_util.h"
-#include "components/signin/public/base/signin_metrics.h"
-#include "components/signin/public/base/signin_pref_names.h"
-
-PrimaryAccountPolicyManager::PrimaryAccountPolicyManager(Profile* profile)
-    : profile_(profile) {
-  DCHECK(profile_);
-  DCHECK(!profile_->IsOffTheRecord());
-}
-
-PrimaryAccountPolicyManager::~PrimaryAccountPolicyManager() = default;
-
-void PrimaryAccountPolicyManager::Initialize() {
-  signin_util::EnsurePrimaryAccountAllowedForProfile(
-      profile_, signin_metrics::SIGNIN_NOT_ALLOWED_ON_PROFILE_INIT);
-
-  signin_allowed_.Init(
-      prefs::kSigninAllowed, profile_->GetPrefs(),
-      base::BindRepeating(
-          &PrimaryAccountPolicyManager::OnSigninAllowedPrefChanged,
-          weak_pointer_factory_.GetWeakPtr()));
-
-  local_state_pref_registrar_.Init(g_browser_process->local_state());
-  local_state_pref_registrar_.Add(
-      prefs::kGoogleServicesUsernamePattern,
-      base::BindRepeating(
-          &PrimaryAccountPolicyManager::OnGoogleServicesUsernamePatternChanged,
-          weak_pointer_factory_.GetWeakPtr()));
-}
-
-void PrimaryAccountPolicyManager::Shutdown() {
-  local_state_pref_registrar_.RemoveAll();
-  signin_allowed_.Destroy();
-}
-
-void PrimaryAccountPolicyManager::OnGoogleServicesUsernamePatternChanged() {
-  signin_util::EnsurePrimaryAccountAllowedForProfile(
-      profile_, signin_metrics::GOOGLE_SERVICE_NAME_PATTERN_CHANGED);
-}
-
-void PrimaryAccountPolicyManager::OnSigninAllowedPrefChanged() {
-  signin_util::EnsurePrimaryAccountAllowedForProfile(
-      profile_, signin_metrics::SIGNOUT_PREF_CHANGED);
-}
diff --git a/chrome/browser/signin/primary_account_policy_manager.h b/chrome/browser/signin/primary_account_policy_manager.h
deleted file mode 100644
index 1901750..0000000
--- a/chrome/browser/signin/primary_account_policy_manager.h
+++ /dev/null
@@ -1,44 +0,0 @@
-// Copyright 2022 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#ifndef CHROME_BROWSER_SIGNIN_PRIMARY_ACCOUNT_POLICY_MANAGER_H_
-#define CHROME_BROWSER_SIGNIN_PRIMARY_ACCOUNT_POLICY_MANAGER_H_
-
-#include "base/memory/raw_ptr.h"
-#include "base/memory/weak_ptr.h"
-#include "components/keyed_service/core/keyed_service.h"
-#include "components/prefs/pref_change_registrar.h"
-#include "components/prefs/pref_member.h"
-
-class Profile;
-
-class PrimaryAccountPolicyManager : public KeyedService {
- public:
-  explicit PrimaryAccountPolicyManager(Profile* profile);
-  ~PrimaryAccountPolicyManager() override;
-
-  PrimaryAccountPolicyManager(const PrimaryAccountPolicyManager&) = delete;
-  PrimaryAccountPolicyManager& operator=(const PrimaryAccountPolicyManager&) =
-      delete;
-
-  void Initialize();
-  void Shutdown() override;
-
- private:
-  void OnSigninAllowedPrefChanged();
-  void OnGoogleServicesUsernamePatternChanged();
-
-  raw_ptr<Profile> profile_;
-
-  // Helper object to listen for changes to the signin allowed preference.
-  BooleanPrefMember signin_allowed_;
-
-  // Helper object to listen for changes to signin preferences stored in non-
-  // profile-specific local prefs (like kGoogleServicesUsernamePattern).
-  PrefChangeRegistrar local_state_pref_registrar_;
-
-  base::WeakPtrFactory<PrimaryAccountPolicyManager> weak_pointer_factory_{this};
-};
-
-#endif  // CHROME_BROWSER_SIGNIN_PRIMARY_ACCOUNT_POLICY_MANAGER_H_
diff --git a/chrome/browser/signin/primary_account_policy_manager_factory.cc b/chrome/browser/signin/primary_account_policy_manager_factory.cc
deleted file mode 100644
index da80239..0000000
--- a/chrome/browser/signin/primary_account_policy_manager_factory.cc
+++ /dev/null
@@ -1,40 +0,0 @@
-// Copyright 2022 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#include "chrome/browser/signin/primary_account_policy_manager_factory.h"
-
-#include "chrome/browser/profiles/profile.h"
-#include "chrome/browser/signin/identity_manager_factory.h"
-#include "components/keyed_service/content/browser_context_dependency_manager.h"
-
-// static
-PrimaryAccountPolicyManagerFactory*
-PrimaryAccountPolicyManagerFactory::GetInstance() {
-  static base::NoDestructor<PrimaryAccountPolicyManagerFactory> instance;
-  return instance.get();
-}
-
-// static
-PrimaryAccountPolicyManager* PrimaryAccountPolicyManagerFactory::GetForProfile(
-    Profile* profile) {
-  DCHECK(profile);
-  return static_cast<PrimaryAccountPolicyManager*>(
-      GetInstance()->GetServiceForBrowserContext(profile, true));
-}
-
-PrimaryAccountPolicyManagerFactory::PrimaryAccountPolicyManagerFactory()
-    : BrowserContextKeyedServiceFactory(
-          "PrimaryAccountPolicyManager",
-          BrowserContextDependencyManager::GetInstance()) {
-  DependsOn(IdentityManagerFactory::GetInstance());
-}
-
-PrimaryAccountPolicyManagerFactory::~PrimaryAccountPolicyManagerFactory() =
-    default;
-
-KeyedService* PrimaryAccountPolicyManagerFactory::BuildServiceInstanceFor(
-    content::BrowserContext* context) const {
-  Profile* profile = Profile::FromBrowserContext(context);
-  return new PrimaryAccountPolicyManager(profile);
-}
diff --git a/chrome/browser/signin/primary_account_policy_manager_factory.h b/chrome/browser/signin/primary_account_policy_manager_factory.h
deleted file mode 100644
index a82b211..0000000
--- a/chrome/browser/signin/primary_account_policy_manager_factory.h
+++ /dev/null
@@ -1,32 +0,0 @@
-// Copyright 2022 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#ifndef CHROME_BROWSER_SIGNIN_PRIMARY_ACCOUNT_POLICY_MANAGER_FACTORY_H_
-#define CHROME_BROWSER_SIGNIN_PRIMARY_ACCOUNT_POLICY_MANAGER_FACTORY_H_
-
-#include "base/no_destructor.h"
-#include "chrome/browser/signin/primary_account_policy_manager.h"
-#include "components/keyed_service/content/browser_context_keyed_service_factory.h"
-
-class Profile;
-
-class PrimaryAccountPolicyManagerFactory
-    : public BrowserContextKeyedServiceFactory {
- public:
-  // Returns an instance of the factory singleton.
-  static PrimaryAccountPolicyManagerFactory* GetInstance();
-  static PrimaryAccountPolicyManager* GetForProfile(Profile* profile);
-
- private:
-  friend base::NoDestructor<PrimaryAccountPolicyManagerFactory>;
-
-  PrimaryAccountPolicyManagerFactory();
-  ~PrimaryAccountPolicyManagerFactory() override;
-
-  // BrowserContextKeyedServiceFactory:
-  KeyedService* BuildServiceInstanceFor(
-      content::BrowserContext* context) const override;
-};
-
-#endif  // CHROME_BROWSER_SIGNIN_PRIMARY_ACCOUNT_POLICY_MANAGER_FACTORY_H_
diff --git a/chrome/browser/signin/primary_account_policy_manager_unittest.cc b/chrome/browser/signin/primary_account_policy_manager_unittest.cc
deleted file mode 100644
index 3844e09e..0000000
--- a/chrome/browser/signin/primary_account_policy_manager_unittest.cc
+++ /dev/null
@@ -1,100 +0,0 @@
-// Copyright 2022 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#include "chrome/browser/signin/primary_account_policy_manager.h"
-
-#include "build/buildflag.h"
-#include "build/chromeos_buildflags.h"
-#include "chrome/browser/signin/identity_test_environment_profile_adaptor.h"
-#include "chrome/browser/signin/primary_account_policy_manager_factory.h"
-#include "chrome/test/base/scoped_testing_local_state.h"
-#include "chrome/test/base/testing_browser_process.h"
-#include "chrome/test/base/testing_profile.h"
-#include "chrome/test/base/testing_profile_manager.h"
-#include "components/signin/public/base/signin_pref_names.h"
-#include "components/signin/public/identity_manager/identity_test_environment.h"
-#include "content/public/test/browser_task_environment.h"
-#include "testing/gtest/include/gtest/gtest.h"
-
-class PrimaryAccountPolicyManagerTest : public testing::Test {
- public:
-  PrimaryAccountPolicyManagerTest()
-      : profile_manager_(TestingBrowserProcess::GetGlobal()) {}
-
-  void SetUp() override { ASSERT_TRUE(profile_manager_.SetUp()); }
-
-  ~PrimaryAccountPolicyManagerTest() override = default;
-
-  void CreateTestingProfile() {
-    DCHECK(!profile_);
-
-    profile_ = profile_manager_.CreateTestingProfile(
-        "primary_account_policy_manager_test_profile_path",
-        IdentityTestEnvironmentProfileAdaptor::
-            GetIdentityTestEnvironmentFactories());
-    identity_test_env_adaptor_ =
-        std::make_unique<IdentityTestEnvironmentProfileAdaptor>(profile_);
-  }
-
-  void DestroyProfile() {
-    identity_test_env_adaptor_.reset();
-    profile_ = nullptr;
-    profile_manager_.DeleteTestingProfile(
-        "primary_account_policy_manager_test_profile_path");
-  }
-
-  PrefService* GetLocalState() { return profile_manager_.local_state()->Get(); }
-
-  TestingProfile* GetProfile() {
-    DCHECK(profile_);
-    return profile_;
-  }
-
-  signin::IdentityTestEnvironment* GetIdentityTestEnv() {
-    DCHECK(identity_test_env_adaptor_);
-    return identity_test_env_adaptor_->identity_test_env();
-  }
-
- private:
-  content::BrowserTaskEnvironment task_environment_;
-  TestingProfileManager profile_manager_;
-  TestingProfile* profile_ = nullptr;
-  std::unique_ptr<IdentityTestEnvironmentProfileAdaptor>
-      identity_test_env_adaptor_;
-};
-
-#if !BUILDFLAG(IS_CHROMEOS_ASH)
-// All primary accounts are allowed on ChromeOS, so this the
-// PrimaryAccountPolicyManagerTest does not clear the primary account on
-// ChromeOS.
-//
-// TODO(msarda): Exclude |PrimaryAccountPolicyManager| from the ChromeOS
-// build.
-TEST_F(PrimaryAccountPolicyManagerTest,
-       ClearPrimarySyncAccountWhenSigninNotAllowed) {
-  CreateTestingProfile();
-  GetIdentityTestEnv()->MakePrimaryAccountAvailable(
-      "test@foo.com", signin::ConsentLevel::kSync);
-  GetProfile()->GetPrefs()->SetBoolean(prefs::kSigninAllowed, false);
-
-  EXPECT_FALSE(GetIdentityTestEnv()->identity_manager()->HasPrimaryAccount(
-      signin::ConsentLevel::kSync));
-  EXPECT_FALSE(GetIdentityTestEnv()->identity_manager()->HasPrimaryAccount(
-      signin::ConsentLevel::kSignin));
-}
-
-TEST_F(PrimaryAccountPolicyManagerTest,
-       ClearPrimarySyncAccountWhenPatternNotAllowed) {
-  CreateTestingProfile();
-  GetIdentityTestEnv()->MakePrimaryAccountAvailable(
-      "test@foo.com", signin::ConsentLevel::kSync);
-  GetLocalState()->SetString(prefs::kGoogleServicesUsernamePattern,
-                             ".*@bar.com");
-
-  EXPECT_FALSE(GetIdentityTestEnv()->identity_manager()->HasPrimaryAccount(
-      signin::ConsentLevel::kSync));
-  EXPECT_FALSE(GetIdentityTestEnv()->identity_manager()->HasPrimaryAccount(
-      signin::ConsentLevel::kSignin));
-}
-#endif  // !BUILDFLAG(IS_CHROMEOS_ASH)
diff --git a/chrome/browser/signin/signin_util.cc b/chrome/browser/signin/signin_util.cc
index fc2ef2b..d3ab11f8 100644
--- a/chrome/browser/signin/signin_util.cc
+++ b/chrome/browser/signin/signin_util.cc
@@ -290,9 +290,7 @@
   UserSignoutSetting::GetForProfile(profile)->set_state(new_state);
 }
 
-void EnsurePrimaryAccountAllowedForProfile(
-    Profile* profile,
-    signin_metrics::ProfileSignout clear_primary_account_source) {
+void EnsurePrimaryAccountAllowedForProfile(Profile* profile) {
 // All primary accounts are allowed on ChromeOS, so this method is a no-op on
 // ChromeOS.
 #if !BUILDFLAG(IS_CHROMEOS_ASH)
@@ -320,7 +318,7 @@
       auto* primary_account_mutator =
           identity_manager->GetPrimaryAccountMutator();
       primary_account_mutator->ClearPrimaryAccount(
-          clear_primary_account_source,
+          signin_metrics::SIGNIN_NOT_ALLOWED_ON_PROFILE_INIT,
           signin_metrics::SignoutDelete::kIgnoreMetric);
       break;
     }
diff --git a/chrome/browser/signin/signin_util.h b/chrome/browser/signin/signin_util.h
index 0a6693f..10a436d 100644
--- a/chrome/browser/signin/signin_util.h
+++ b/chrome/browser/signin/signin_util.h
@@ -8,7 +8,6 @@
 #include <string>
 
 #include "build/build_config.h"
-#include "components/signin/public/base/signin_metrics.h"
 
 class Profile;
 
@@ -55,11 +54,7 @@
 //   is no longer allowed, then this clears the primary account.
 // * If |IsUserSignoutAllowedForProfile| is not allowed and the primary account
 //   is not longer allowed, then this removes the profile.
-//
-// TODO(msarda): Move to |primary_account_policy_manager.h|
-void EnsurePrimaryAccountAllowedForProfile(
-    Profile* profile,
-    signin_metrics::ProfileSignout clear_primary_account_source);
+void EnsurePrimaryAccountAllowedForProfile(Profile* profile);
 
 #if !defined(OS_ANDROID)
 // Returns true if profile separation is enforced by policy.
diff --git a/chrome/browser/ssl/sct_reporting_service_browsertest.cc b/chrome/browser/ssl/sct_reporting_service_browsertest.cc
index c0de69c8..5c6abad 100644
--- a/chrome/browser/ssl/sct_reporting_service_browsertest.cc
+++ b/chrome/browser/ssl/sct_reporting_service_browsertest.cc
@@ -3,9 +3,9 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 
 #include "base/callback.h"
-#include "base/ignore_result.h"
 #include "base/synchronization/lock.h"
 #include "base/test/scoped_feature_list.h"
 #include "build/build_config.h"
@@ -102,7 +102,7 @@
         true);
     // The report server must be initialized here so the reporting URL can be
     // set before the network service is initialized.
-    ignore_result(report_server()->InitializeAndListen());
+    std::ignore = report_server()->InitializeAndListen();
     SCTReportingService::GetReportURLInstance() = report_server()->GetURL("/");
   }
   ~SCTReportingServiceBrowserTest() override {
diff --git a/chrome/browser/sync/test/integration/two_client_web_apps_integration_test_mac_win_linux.cc b/chrome/browser/sync/test/integration/two_client_web_apps_integration_test_mac_win_linux.cc
index 5fd5c3f..40fddc3 100644
--- a/chrome/browser/sync/test/integration/two_client_web_apps_integration_test_mac_win_linux.cc
+++ b/chrome/browser/sync/test/integration/two_client_web_apps_integration_test_mac_win_linux.cc
@@ -405,7 +405,7 @@
 
 IN_PROC_BROWSER_TEST_F(
     TwoClientWebAppsIntegrationTestMacWinLinux,
-    WebAppIntegration_TurnSyncOff_InstCrtShctWindowedSiteA_TurnSyncOn_SwitchProfileClientClient2_InListNotLclyInstSiteA) {
+    DISABLED_WebAppIntegration_TurnSyncOff_InstCrtShctWindowedSiteA_TurnSyncOn_SwitchProfileClientClient2_InListNotLclyInstSiteA) {
   // Test contents are generated by script. Please do not modify!
   // See `chrome/test/webapps/README.md` for more info.
   // Sheriffs: Disabling this test is supported.
@@ -418,7 +418,7 @@
 
 IN_PROC_BROWSER_TEST_F(
     TwoClientWebAppsIntegrationTestMacWinLinux,
-    WebAppIntegration_TurnSyncOff_InstOmniboxSiteA_TurnSyncOn_SwitchProfileClientClient2_InListNotLclyInstSiteA) {
+    DISABLED_WebAppIntegration_TurnSyncOff_InstOmniboxSiteA_TurnSyncOn_SwitchProfileClientClient2_InListNotLclyInstSiteA) {
   // Test contents are generated by script. Please do not modify!
   // See `chrome/test/webapps/README.md` for more info.
   // Sheriffs: Disabling this test is supported.
diff --git a/chrome/browser/tab/BUILD.gn b/chrome/browser/tab/BUILD.gn
index 619931c..2769c88 100644
--- a/chrome/browser/tab/BUILD.gn
+++ b/chrome/browser/tab/BUILD.gn
@@ -24,7 +24,6 @@
     "java/src/org/chromium/chrome/browser/tab/TabObserver.java",
     "java/src/org/chromium/chrome/browser/tab/TabResolver.java",
     "java/src/org/chromium/chrome/browser/tab/TabState.java",
-    "java/src/org/chromium/chrome/browser/tab/TabStateAttributes.java",
     "java/src/org/chromium/chrome/browser/tab/TabViewManager.java",
     "java/src/org/chromium/chrome/browser/tab/TabViewProvider.java",
     "java/src/org/chromium/chrome/browser/tab/TabWebContentsDelegateAndroid.java",
@@ -61,6 +60,7 @@
   ]
 
   deps = [
+    ":critical_persisted_tab_data_flatbuffer_java",
     ":critical_persisted_tab_data_proto_java",
     ":java_resources",
     "//base:base_java",
@@ -90,6 +90,7 @@
     "//components/strings:components_strings_grd",
     "//content/public/android:content_java",
     "//net/android:net_java",
+    "//third_party/android_deps:com_google_flatbuffers_flatbuffers_java_java",
     "//third_party/android_deps:guava_android_java",
     "//third_party/android_deps:protobuf_lite_runtime_java",
     "//third_party/androidx:androidx_annotation_annotation_java",
@@ -132,6 +133,11 @@
   ]
 }
 
+flatbuffer_java_library("critical_persisted_tab_data_flatbuffer_java") {
+  root_dir = "java/src/org/chromium/chrome/browser/tab/state/flatbuffer"
+  sources = [ "$root_dir/critical_persisted_tab_data.fbs" ]
+}
+
 android_library("junit") {
   bypass_platform_checks = true
   testonly = true
diff --git a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/Tab.java b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/Tab.java
index d9cdc11..188f660 100644
--- a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/Tab.java
+++ b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/Tab.java
@@ -273,6 +273,14 @@
     void goForward();
 
     /**
+     * Set whether the TabState representing this Tab has been updated.
+     * This method will ultimately be deprecated when the migration
+     * to CriticalPersistedTabData is complete.
+     * @param isDirty Whether the Tab's state has changed.
+     */
+    void setIsTabStateDirty(boolean isTabStateDirty);
+
+    /**
      * Set whether {@link Tab} metadata (specifically all {@link PersistedTabData})
      * will be saved. Not all Tabs need to be persisted across restarts.
      * The default value when a Tab is initialized is false.
diff --git a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/TabStateAttributes.java b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/TabStateAttributes.java
deleted file mode 100644
index 098c9e7..0000000
--- a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/TabStateAttributes.java
+++ /dev/null
@@ -1,45 +0,0 @@
-// Copyright 2022 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-package org.chromium.chrome.browser.tab;
-
-import org.chromium.base.UserData;
-import org.chromium.base.UserDataHost;
-
-/**
- * Attributes related to {@link TabState}
- */
-public class TabStateAttributes implements UserData {
-    private static final Class<TabStateAttributes> USER_DATA_KEY = TabStateAttributes.class;
-    /** Whether or not the TabState has changed. */
-    private boolean mIsTabStateDirty = true;
-
-    /**
-     * @return {@link TabStateAttributes} for a {@link Tab}
-     */
-    public static TabStateAttributes from(Tab tab) {
-        UserDataHost host = tab.getUserDataHost();
-        TabStateAttributes attrs = host.getUserData(USER_DATA_KEY);
-        return attrs != null ? attrs : host.setUserData(USER_DATA_KEY, new TabStateAttributes());
-    }
-
-    private TabStateAttributes() {}
-
-    /**
-     * @return true if the {@link TabState} has been changed
-     */
-    public boolean isTabStateDirty() {
-        return mIsTabStateDirty;
-    }
-
-    /**
-     * Set whether the TabState representing this Tab has been updated.
-     * This method will ultimately be deprecated when the migration
-     * to CriticalPersistedTabData is complete.
-     * @param isTabStateDirty whether the Tab's state has changed.
-     */
-    public void setIsTabStateDirty(boolean isTabStateDirty) {
-        mIsTabStateDirty = isTabStateDirty;
-    }
-}
diff --git a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabData.java b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabData.java
index ef8a8acb..2ee58b3 100644
--- a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabData.java
+++ b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/CriticalPersistedTabData.java
@@ -10,20 +10,20 @@
 import androidx.annotation.Nullable;
 import androidx.annotation.VisibleForTesting;
 
-import com.google.protobuf.ByteString;
-import com.google.protobuf.InvalidProtocolBufferException;
+import com.google.flatbuffers.FlatBufferBuilder;
 
 import org.chromium.base.Callback;
-import org.chromium.base.Log;
 import org.chromium.base.ObserverList;
 import org.chromium.base.TraceEvent;
 import org.chromium.base.supplier.Supplier;
 import org.chromium.chrome.browser.tab.Tab;
 import org.chromium.chrome.browser.tab.TabLaunchType;
-import org.chromium.chrome.browser.tab.TabStateAttributes;
 import org.chromium.chrome.browser.tab.TabUserAgent;
 import org.chromium.chrome.browser.tab.WebContentsState;
 import org.chromium.chrome.browser.tab.WebContentsStateBridge;
+import org.chromium.chrome.browser.tab.flatbuffer.CriticalPersistedTabDataFlatBuffer;
+import org.chromium.chrome.browser.tab.flatbuffer.LaunchTypeAtCreation;
+import org.chromium.chrome.browser.tab.flatbuffer.UserAgentType;
 import org.chromium.chrome.browser.tab.proto.CriticalPersistedTabData.CriticalPersistedTabDataProto;
 import org.chromium.components.embedder_support.util.UrlConstants;
 import org.chromium.components.embedder_support.util.UrlUtilities;
@@ -32,7 +32,6 @@
 import org.chromium.url.GURL;
 
 import java.nio.ByteBuffer;
-import java.util.Locale;
 
 /**
  * Data which is core to the app and must be retrieved as quickly as possible on startup.
@@ -43,6 +42,7 @@
             CriticalPersistedTabData.class;
 
     private static final int UNSPECIFIED_THEME_COLOR = Color.TRANSPARENT;
+    private static final String NULL_OPENER_APP_ID = " ";
     public static final long INVALID_TIMESTAMP = -1;
 
     /**
@@ -215,41 +215,28 @@
     @Override
     boolean deserialize(@Nullable ByteBuffer bytes) {
         try (TraceEvent e = TraceEvent.scoped("CriticalPersistedTabData.Deserialize")) {
-            CriticalPersistedTabDataProto criticalPersistedTabDataProto =
-                    CriticalPersistedTabDataProto.parseFrom(bytes);
-            mParentId = criticalPersistedTabDataProto.getParentId();
-            mRootId = criticalPersistedTabDataProto.getRootId();
-            mTimestampMillis = criticalPersistedTabDataProto.getTimestampMillis();
-            ByteString webContentsStateByteString =
-                    criticalPersistedTabDataProto.getWebContentsStateBytes();
-            mWebContentsState = new WebContentsState(
-                    ByteBuffer.allocateDirect(webContentsStateByteString.size()));
-            webContentsStateByteString.copyTo(mWebContentsState.buffer());
+            CriticalPersistedTabDataFlatBuffer deserialized =
+                    CriticalPersistedTabDataFlatBuffer.getRootAsCriticalPersistedTabDataFlatBuffer(
+                            bytes);
+            mParentId = deserialized.parentId();
+            mRootId = deserialized.rootId();
+            mTimestampMillis = deserialized.timestampMillis();
+            mWebContentsState =
+                    new WebContentsState(deserialized.webContentsStateBytesAsByteBuffer().slice());
             mWebContentsState.setVersion(WebContentsState.CONTENTS_STATE_CURRENT_VERSION);
             mUrl = mWebContentsState.getVirtualUrlFromState() == null
                     ? GURL.emptyGURL()
                     : new GURL(mWebContentsState.getVirtualUrlFromState());
             mTitle = mWebContentsState.getDisplayTitleFromState();
-            mContentStateVersion = criticalPersistedTabDataProto.getContentStateVersion();
-            mOpenerAppId = TextUtils.isEmpty(criticalPersistedTabDataProto.getOpenerAppId())
+            mContentStateVersion = deserialized.contentStateVersion();
+            mOpenerAppId = NULL_OPENER_APP_ID.equals(deserialized.openerAppId())
                     ? null
-                    : criticalPersistedTabDataProto.getOpenerAppId();
-            mThemeColor = criticalPersistedTabDataProto.getThemeColor();
-            mTabLaunchTypeAtCreation =
-                    getLaunchType(criticalPersistedTabDataProto.getLaunchTypeAtCreation());
-            if (criticalPersistedTabDataProto.hasUserAgent()) {
-                mUserAgent = getUserAgentType(criticalPersistedTabDataProto.getUserAgent());
-            } else {
-                mUserAgent = TabUserAgent.UNSET;
-            }
+                    : deserialized.openerAppId();
+            mThemeColor = deserialized.themeColor();
+            mTabLaunchTypeAtCreation = getLaunchType(deserialized.launchTypeAtCreation());
+            mUserAgent = getTabUserAgentType(deserialized.userAgent());
             return true;
-        } catch (InvalidProtocolBufferException e) {
-            Log.e(TAG,
-                    String.format(Locale.ENGLISH,
-                            "There was a problem deserializing Tab %d. Details: %s", mTab.getId(),
-                            e.getMessage()));
         }
-        return false;
     }
 
     @Override
@@ -258,142 +245,135 @@
     }
 
     @VisibleForTesting
-    static @Nullable @TabLaunchType Integer getLaunchType(
-            CriticalPersistedTabDataProto.LaunchTypeAtCreation protoLaunchType) {
-        switch (protoLaunchType) {
-            case FROM_LINK:
+    static @Nullable @TabLaunchType Integer getLaunchType(int flatBufferLaunchType) {
+        switch (flatBufferLaunchType) {
+            case LaunchTypeAtCreation.FROM_LINK:
                 return TabLaunchType.FROM_LINK;
-            case FROM_EXTERNAL_APP:
+            case LaunchTypeAtCreation.FROM_EXTERNAL_APP:
                 return TabLaunchType.FROM_EXTERNAL_APP;
-            case FROM_CHROME_UI:
+            case LaunchTypeAtCreation.FROM_CHROME_UI:
                 return TabLaunchType.FROM_CHROME_UI;
-            case FROM_RESTORE:
+            case LaunchTypeAtCreation.FROM_RESTORE:
                 return TabLaunchType.FROM_RESTORE;
-            case FROM_LONGPRESS_FOREGROUND:
+            case LaunchTypeAtCreation.FROM_LONGPRESS_FOREGROUND:
                 return TabLaunchType.FROM_LONGPRESS_FOREGROUND;
-            case FROM_LONGPRESS_BACKGROUND:
+            case LaunchTypeAtCreation.FROM_LONGPRESS_BACKGROUND:
                 return TabLaunchType.FROM_LONGPRESS_BACKGROUND;
-            case FROM_REPARENTING:
+            case LaunchTypeAtCreation.FROM_REPARENTING:
                 return TabLaunchType.FROM_REPARENTING;
-            case FROM_LAUNCHER_SHORTCUT:
+            case LaunchTypeAtCreation.FROM_LAUNCHER_SHORTCUT:
                 return TabLaunchType.FROM_LAUNCHER_SHORTCUT;
-            case FROM_SPECULATIVE_BACKGROUND_CREATION:
+            case LaunchTypeAtCreation.FROM_SPECULATIVE_BACKGROUND_CREATION:
                 return TabLaunchType.FROM_SPECULATIVE_BACKGROUND_CREATION;
-            case FROM_BROWSER_ACTIONS:
+            case LaunchTypeAtCreation.FROM_BROWSER_ACTIONS:
                 return TabLaunchType.FROM_BROWSER_ACTIONS;
-            case FROM_LAUNCH_NEW_INCOGNITO_TAB:
+            case LaunchTypeAtCreation.FROM_LAUNCH_NEW_INCOGNITO_TAB:
                 return TabLaunchType.FROM_LAUNCH_NEW_INCOGNITO_TAB;
-            case FROM_STARTUP:
+            case LaunchTypeAtCreation.FROM_STARTUP:
                 return TabLaunchType.FROM_STARTUP;
-            case FROM_START_SURFACE:
+            case LaunchTypeAtCreation.FROM_START_SURFACE:
                 return TabLaunchType.FROM_START_SURFACE;
-            case FROM_TAB_GROUP_UI:
+            case LaunchTypeAtCreation.FROM_TAB_GROUP_UI:
                 return TabLaunchType.FROM_TAB_GROUP_UI;
-            case FROM_LONGPRESS_BACKGROUND_IN_GROUP:
+            case LaunchTypeAtCreation.FROM_LONGPRESS_BACKGROUND_IN_GROUP:
                 return TabLaunchType.FROM_LONGPRESS_BACKGROUND_IN_GROUP;
-            case FROM_APP_WIDGET:
+            case LaunchTypeAtCreation.FROM_APP_WIDGET:
                 return TabLaunchType.FROM_APP_WIDGET;
-            case SIZE:
+            case LaunchTypeAtCreation.SIZE:
                 return TabLaunchType.SIZE;
             default:
                 assert false : "Unexpected deserialization of LaunchAtCreationType: "
-                               + protoLaunchType;
+                               + flatBufferLaunchType;
                 // shouldn't happen
                 return null;
         }
     }
 
     @VisibleForTesting
-    static CriticalPersistedTabDataProto.LaunchTypeAtCreation getLaunchType(
-            @Nullable @TabLaunchType Integer protoLaunchType) {
-        if (protoLaunchType == null) {
-            return CriticalPersistedTabDataProto.LaunchTypeAtCreation.UNKNOWN;
+    static int getLaunchType(@Nullable @TabLaunchType Integer tabLaunchType) {
+        if (tabLaunchType == null) {
+            return LaunchTypeAtCreation.UNKNOWN;
         }
-        switch (protoLaunchType) {
+        switch (tabLaunchType) {
             case TabLaunchType.FROM_LINK:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_LINK;
+                return LaunchTypeAtCreation.FROM_LINK;
             case TabLaunchType.FROM_EXTERNAL_APP:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_EXTERNAL_APP;
+                return LaunchTypeAtCreation.FROM_EXTERNAL_APP;
             case TabLaunchType.FROM_CHROME_UI:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_CHROME_UI;
+                return LaunchTypeAtCreation.FROM_CHROME_UI;
             case TabLaunchType.FROM_RESTORE:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_RESTORE;
+                return LaunchTypeAtCreation.FROM_RESTORE;
             case TabLaunchType.FROM_LONGPRESS_FOREGROUND:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_LONGPRESS_FOREGROUND;
+                return LaunchTypeAtCreation.FROM_LONGPRESS_FOREGROUND;
             case TabLaunchType.FROM_LONGPRESS_BACKGROUND:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_LONGPRESS_BACKGROUND;
+                return LaunchTypeAtCreation.FROM_LONGPRESS_BACKGROUND;
             case TabLaunchType.FROM_REPARENTING:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_REPARENTING;
+                return LaunchTypeAtCreation.FROM_REPARENTING;
             case TabLaunchType.FROM_LAUNCHER_SHORTCUT:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_LAUNCHER_SHORTCUT;
+                return LaunchTypeAtCreation.FROM_LAUNCHER_SHORTCUT;
             case TabLaunchType.FROM_SPECULATIVE_BACKGROUND_CREATION:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation
-                        .FROM_SPECULATIVE_BACKGROUND_CREATION;
+                return LaunchTypeAtCreation.FROM_SPECULATIVE_BACKGROUND_CREATION;
             case TabLaunchType.FROM_BROWSER_ACTIONS:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_BROWSER_ACTIONS;
+                return LaunchTypeAtCreation.FROM_BROWSER_ACTIONS;
             case TabLaunchType.FROM_LAUNCH_NEW_INCOGNITO_TAB:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation
-                        .FROM_LAUNCH_NEW_INCOGNITO_TAB;
+                return LaunchTypeAtCreation.FROM_LAUNCH_NEW_INCOGNITO_TAB;
             case TabLaunchType.FROM_STARTUP:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_STARTUP;
+                return LaunchTypeAtCreation.FROM_STARTUP;
             case TabLaunchType.FROM_START_SURFACE:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_START_SURFACE;
+                return LaunchTypeAtCreation.FROM_START_SURFACE;
             case TabLaunchType.FROM_TAB_GROUP_UI:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_TAB_GROUP_UI;
+                return LaunchTypeAtCreation.FROM_TAB_GROUP_UI;
             case TabLaunchType.FROM_LONGPRESS_BACKGROUND_IN_GROUP:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation
-                        .FROM_LONGPRESS_BACKGROUND_IN_GROUP;
+                return LaunchTypeAtCreation.FROM_LONGPRESS_BACKGROUND_IN_GROUP;
             case TabLaunchType.FROM_APP_WIDGET:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.FROM_APP_WIDGET;
+                return LaunchTypeAtCreation.FROM_APP_WIDGET;
             case TabLaunchType.SIZE:
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.SIZE;
+                return LaunchTypeAtCreation.SIZE;
             default:
-                assert false : "Unexpected serialization of LaunchAtCreationType: "
-                               + protoLaunchType;
+                assert false : "Unexpected serialization of LaunchAtCreationType: " + tabLaunchType;
                 // shouldn't happen
-                return CriticalPersistedTabDataProto.LaunchTypeAtCreation.UNKNOWN;
+                return LaunchTypeAtCreation.UNKNOWN;
         }
     }
 
     @VisibleForTesting
-    static @TabUserAgent int getUserAgentType(
-            CriticalPersistedTabDataProto.UserAgentType protoUserAgent) {
-        switch (protoUserAgent) {
-            case DEFAULT:
+    static @TabUserAgent int getTabUserAgentType(int flatbufferUserAgentType) {
+        switch (flatbufferUserAgentType) {
+            case UserAgentType.DEFAULT:
                 return TabUserAgent.DEFAULT;
-            case MOBILE:
+            case UserAgentType.MOBILE:
                 return TabUserAgent.MOBILE;
-            case DESKTOP:
+            case UserAgentType.DESKTOP:
                 return TabUserAgent.DESKTOP;
-            case UNSET:
+            case UserAgentType.UNSET:
                 return TabUserAgent.UNSET;
-            case USER_AGENT_SIZE:
+            case UserAgentType.USER_AGENT_SIZE:
                 return TabUserAgent.SIZE;
             default:
-                assert false : "Unexpected deserialization of UserAgentType: " + protoUserAgent;
+                assert false : "Unexpected deserialization of UserAgentType: "
+                               + flatbufferUserAgentType;
                 // shouldn't happen
                 return TabUserAgent.DEFAULT;
         }
     }
 
     @VisibleForTesting
-    static CriticalPersistedTabDataProto.UserAgentType getUserAgentType(
-            @TabUserAgent int protoUserAgent) {
-        switch (protoUserAgent) {
+    static int getUserAgentType(@TabUserAgent int userAgent) {
+        switch (userAgent) {
             case TabUserAgent.DEFAULT:
-                return CriticalPersistedTabDataProto.UserAgentType.DEFAULT;
+                return UserAgentType.DEFAULT;
             case TabUserAgent.MOBILE:
-                return CriticalPersistedTabDataProto.UserAgentType.MOBILE;
+                return UserAgentType.MOBILE;
             case TabUserAgent.DESKTOP:
-                return CriticalPersistedTabDataProto.UserAgentType.DESKTOP;
+                return UserAgentType.DESKTOP;
             case TabUserAgent.UNSET:
-                return CriticalPersistedTabDataProto.UserAgentType.UNSET;
+                return UserAgentType.UNSET;
             case TabUserAgent.SIZE:
-                return CriticalPersistedTabDataProto.UserAgentType.USER_AGENT_SIZE;
+                return UserAgentType.USER_AGENT_SIZE;
             default:
-                assert false : "Unexpected serialization of UserAgentType: " + protoUserAgent;
+                assert false : "Unexpected serialization of UserAgentType: " + userAgent;
                 // shouldn't happen
-                return CriticalPersistedTabDataProto.UserAgentType.DEFAULT;
+                return UserAgentType.USER_AGENT_UNKNOWN;
         }
     }
 
@@ -429,32 +409,54 @@
         CriticalPersistedTabDataProto.Builder builder;
         final WebContentsState webContentsState;
         final ByteBuffer byteBuffer;
+        final String openerAppId;
+        final int parentId;
+        final int rootId;
+        final long timestampMillis;
+        final int webContentsStateVersion;
+        final int themeColor;
+        final int launchType;
+        final int userAgentType;
+        FlatBufferBuilder fbb = new FlatBufferBuilder();
         try (TraceEvent e = TraceEvent.scoped("CriticalPersistedTabData.PreSerialize")) {
             webContentsState = mWebContentsState == null ? getWebContentsStateFromTab(mTab)
                                                          : mWebContentsState;
             byteBuffer = webContentsState == null ? null : webContentsState.buffer();
-            builder = CriticalPersistedTabDataProto.newBuilder()
-                              .setParentId(mParentId)
-                              .setRootId(mRootId)
-                              .setTimestampMillis(mTimestampMillis)
-                              .setContentStateVersion(mContentStateVersion)
-                              .setOpenerAppId(mOpenerAppId == null ? "" : mOpenerAppId)
-                              .setThemeColor(mThemeColor)
-                              .setLaunchTypeAtCreation(getLaunchType(mTabLaunchTypeAtCreation))
-                              .setUserAgent(getUserAgentType(mUserAgent));
+            if (byteBuffer != null) {
+                byteBuffer.rewind();
+            }
+            openerAppId = mOpenerAppId;
+            parentId = mParentId;
+            rootId = mRootId;
+            timestampMillis = mTimestampMillis;
+            webContentsStateVersion = mContentStateVersion;
+            themeColor = mThemeColor;
+            launchType = getLaunchType(mTabLaunchTypeAtCreation);
+            userAgentType = getUserAgentType(mUserAgent);
         }
         return () -> {
             try (TraceEvent e = TraceEvent.scoped("CriticalPersistedTabData.Serialize")) {
-                // TODO(crbug.com/1203298) migrate to ByteString.copyFrom(ByteBuffer ...)
-                // in a thread safe way to avoid intermediate ByteBuffer -> byte[]. Be careful as
-                // this has caused crashes in the past crbug.com/1195550.
-                return builder
-                        .setWebContentsStateBytes(byteBuffer == null
-                                        ? ByteString.EMPTY
-                                        : ByteString.copyFrom(getContentStateByteArray(byteBuffer)))
-                        .build()
-                        .toByteString()
-                        .asReadOnlyByteBuffer();
+                int wcs = CriticalPersistedTabDataFlatBuffer.createWebContentsStateBytesVector(fbb,
+                        byteBuffer == null ? ByteBuffer.allocate(0).put(new byte[] {})
+                                           : byteBuffer);
+                int oaid =
+                        fbb.createString(mOpenerAppId == null ? NULL_OPENER_APP_ID : mOpenerAppId);
+                CriticalPersistedTabDataFlatBuffer.startCriticalPersistedTabDataFlatBuffer(fbb);
+                CriticalPersistedTabDataFlatBuffer.addParentId(fbb, parentId);
+                CriticalPersistedTabDataFlatBuffer.addRootId(fbb, rootId);
+                CriticalPersistedTabDataFlatBuffer.addTimestampMillis(fbb, timestampMillis);
+                CriticalPersistedTabDataFlatBuffer.addWebContentsStateBytes(fbb, wcs);
+                CriticalPersistedTabDataFlatBuffer.addContentStateVersion(
+                        fbb, webContentsStateVersion);
+                CriticalPersistedTabDataFlatBuffer.addOpenerAppId(fbb, oaid);
+                CriticalPersistedTabDataFlatBuffer.addThemeColor(fbb, themeColor);
+                CriticalPersistedTabDataFlatBuffer.addLaunchTypeAtCreation(fbb, launchType);
+                CriticalPersistedTabDataFlatBuffer.addUserAgent(fbb, userAgentType);
+                int r = CriticalPersistedTabDataFlatBuffer.endCriticalPersistedTabDataFlatBuffer(
+                        fbb);
+                fbb.finish(r);
+
+                return fbb.dataBuffer();
             }
         };
     }
@@ -565,13 +567,13 @@
      * Set root id
      */
     public void setRootId(int rootId) {
-        if (mRootId == rootId || mTab.isDestroyed()) return;
+        if (mRootId == rootId) return;
         // TODO(crbug.com/1059640) add in setters for all mutable fields
         mRootId = rootId;
         for (CriticalPersistedTabDataObserver observer : mObservers) {
             observer.onRootIdChanged(mTab, rootId);
         }
-        TabStateAttributes.from(mTab).setIsTabStateDirty(true);
+        mTab.setIsTabStateDirty(true);
         save();
     }
 
diff --git a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/FilePersistedTabDataStorage.java b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/FilePersistedTabDataStorage.java
index 3b042a3..cb7338e9 100644
--- a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/FilePersistedTabDataStorage.java
+++ b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/FilePersistedTabDataStorage.java
@@ -27,6 +27,7 @@
 import org.chromium.content_public.browser.UiThreadTaskTraits;
 
 import java.io.File;
+import java.io.FileInputStream;
 import java.io.FileNotFoundException;
 import java.io.FileOutputStream;
 import java.io.IOException;
@@ -34,6 +35,7 @@
 import java.lang.annotation.RetentionPolicy;
 import java.nio.ByteBuffer;
 import java.nio.channels.FileChannel;
+import java.nio.channels.FileChannel.MapMode;
 import java.util.LinkedList;
 import java.util.List;
 import java.util.Locale;
@@ -373,11 +375,14 @@
         @Override
         public ByteBuffer executeSyncTask() {
             boolean success = false;
-            byte[] res = null;
+            ByteBuffer res = null;
+            FileInputStream fileInputStream = null;
             try {
                 long startTime = SystemClock.elapsedRealtime();
                 AtomicFile atomicFile = new AtomicFile(mFile);
-                res = atomicFile.readFully();
+                fileInputStream = atomicFile.openRead();
+                FileChannel channel = fileInputStream.getChannel();
+                res = channel.map(MapMode.READ_ONLY, channel.position(), channel.size());
                 success = true;
                 RecordHistogram.recordTimesHistogram(
                         String.format(Locale.US, "Tabs.PersistedTabData.Storage.LoadTime.%s",
@@ -398,7 +403,7 @@
             }
             RecordHistogram.recordBooleanHistogram(
                     "Tabs.PersistedTabData.Storage.Restore." + getUmaTag(), success);
-            return res == null ? null : ByteBuffer.wrap(res);
+            return res;
         }
 
         @Override
diff --git a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/PersistedTabDataConfiguration.java b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/PersistedTabDataConfiguration.java
index cce2702..db519ce 100644
--- a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/PersistedTabDataConfiguration.java
+++ b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/PersistedTabDataConfiguration.java
@@ -16,8 +16,8 @@
 public enum PersistedTabDataConfiguration {
     // TODO(crbug.com/1059650) investigate should this go in the app code?
     // Also investigate if the storage instance should be shared.
-    CRITICAL_PERSISTED_TAB_DATA("CPTD"),
-    ENCRYPTED_CRITICAL_PERSISTED_TAB_DATA("ECPTD"),
+    CRITICAL_PERSISTED_TAB_DATA("CPTDFB"),
+    ENCRYPTED_CRITICAL_PERSISTED_TAB_DATA("ECPTDFB"),
     MOCK_PERSISTED_TAB_DATA("MPTD"),
     ENCRYPTED_MOCK_PERSISTED_TAB_DATA("EMPTD"),
     SHOPPING_PERSISTED_TAB_DATA("SPTD"),
diff --git a/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/flatbuffer/critical_persisted_tab_data.fbs b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/flatbuffer/critical_persisted_tab_data.fbs
new file mode 100644
index 0000000..340cfe6f
--- /dev/null
+++ b/chrome/browser/tab/java/src/org/chromium/chrome/browser/tab/state/flatbuffer/critical_persisted_tab_data.fbs
@@ -0,0 +1,64 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+namespace org.chromium.chrome.browser.tab.flatbuffer;
+
+enum LaunchTypeAtCreation:int {
+    FROM_LINK = 0,
+    FROM_EXTERNAL_APP = 1,
+    FROM_CHROME_UI = 2,
+    FROM_RESTORE = 3,
+    FROM_LONGPRESS_FOREGROUND = 4,
+    FROM_LONGPRESS_BACKGROUND = 5,
+    FROM_REPARENTING = 6,
+    FROM_LAUNCHER_SHORTCUT = 7,
+    FROM_SPECULATIVE_BACKGROUND_CREATION = 8,
+    FROM_BROWSER_ACTIONS = 9,
+    FROM_LAUNCH_NEW_INCOGNITO_TAB = 10,
+    FROM_STARTUP = 11,
+    FROM_START_SURFACE = 12,
+    FROM_TAB_GROUP_UI = 13,
+    FROM_LONGPRESS_BACKGROUND_IN_GROUP = 14,
+    FROM_APP_WIDGET = 15,
+    SIZE = 16,
+    UNKNOWN = 17,
+}
+
+enum UserAgentType:int {
+    DEFAULT = 0,
+    MOBILE = 1,
+    DESKTOP = 2,
+    UNSET = 3,
+    USER_AGENT_SIZE = 4,
+    USER_AGENT_UNKNOWN = 5,
+}
+
+table CriticalPersistedTabDataFlatBuffer {
+    // Parent Tab identifier.
+    parent_id:int;
+
+    // Root Tab identifier.
+    root_id:int;
+
+    // Timestamp when Tab was last accessed.
+    timestamp_millis:long;
+
+    // WebContentsState.
+    web_contents_state_bytes:[byte];
+
+    // Content State version.
+    content_state_version:int;
+
+    // Identifier for app which opened the Tab.
+    opener_app_id:string;
+
+    // Theme color.
+    theme_color:int;
+
+    // Launch type at creation.
+    launch_type_at_creation:LaunchTypeAtCreation;
+
+    // User Agent.
+    user_agent:UserAgentType=DEFAULT;
+}
diff --git a/chrome/browser/thumbnail/generator/android/thumbnail_media_parser_impl.cc b/chrome/browser/thumbnail/generator/android/thumbnail_media_parser_impl.cc
index 3952e07..aa0c2b4 100644
--- a/chrome/browser/thumbnail/generator/android/thumbnail_media_parser_impl.cc
+++ b/chrome/browser/thumbnail/generator/android/thumbnail_media_parser_impl.cc
@@ -4,10 +4,11 @@
 
 #include "chrome/browser/thumbnail/generator/android/thumbnail_media_parser_impl.h"
 
+#include <tuple>
+
 #include "base/bind.h"
 #include "base/files/file.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/numerics/safe_conversions.h"
 #include "base/task/post_task.h"
 #include "base/task/task_runner_util.h"
@@ -270,7 +271,7 @@
     // ThumbnailMediaParser does not use them, but the Mojo argument is
     // currently marked as required so pass a remote but drop the other end.
     mojo::PendingRemote<media::mojom::FrameInterfaceFactory> interfaces;
-    ignore_result(interfaces.InitWithNewPipeAndPassReceiver());
+    std::ignore = interfaces.InitWithNewPipeAndPassReceiver();
     content::GetMediaService().CreateInterfaceFactory(
         media_interface_factory_.BindNewPipeAndPassReceiver(),
         std::move(interfaces));
diff --git a/chrome/browser/ui/ash/clipboard_history_browsertest.cc b/chrome/browser/ui/ash/clipboard_history_browsertest.cc
index 43140256..537d12ef 100644
--- a/chrome/browser/ui/ash/clipboard_history_browsertest.cc
+++ b/chrome/browser/ui/ash/clipboard_history_browsertest.cc
@@ -4,6 +4,7 @@
 
 #include <list>
 #include <memory>
+#include <tuple>
 
 #include "ash/clipboard/clipboard_history.h"
 #include "ash/clipboard/clipboard_history_controller_impl.h"
@@ -15,7 +16,6 @@
 #include "ash/public/cpp/clipboard_image_model_factory.h"
 #include "ash/shell.h"
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/test/bind.h"
 #include "base/test/metrics/histogram_tester.h"
@@ -805,8 +805,8 @@
 
   // Wait for the paste event to propagate to the web contents.
   // The web contents will notify us a paste occurred by updating page title.
-  ignore_result(
-      content::TitleWatcher(web_contents, u"Paste 1").WaitAndGetTitle());
+  std::ignore =
+      content::TitleWatcher(web_contents, u"Paste 1").WaitAndGetTitle();
 
   // Confirm the expected paste data.
   base::ListValue last_paste = GetLastPaste();
@@ -825,8 +825,8 @@
 
   // Wait for the paste event to propagate to the web contents.
   // The web contents will notify us a paste occurred by updating page title.
-  ignore_result(
-      content::TitleWatcher(web_contents, u"Paste 2").WaitAndGetTitle());
+  std::ignore =
+      content::TitleWatcher(web_contents, u"Paste 2").WaitAndGetTitle();
 
   // Confirm the expected paste data.
   last_paste = GetLastPaste();
diff --git a/chrome/browser/ui/commander/commander_controller_unittest.cc b/chrome/browser/ui/commander/commander_controller_unittest.cc
index 2ea2c6d..7ef7bef5 100644
--- a/chrome/browser/ui/commander/commander_controller_unittest.cc
+++ b/chrome/browser/ui/commander/commander_controller_unittest.cc
@@ -5,10 +5,10 @@
 #include "chrome/browser/ui/commander/commander_controller.h"
 
 #include <string>
+#include <tuple>
 
 #include "base/callback.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/run_loop.h"
 #include "base/test/bind.h"
@@ -139,7 +139,7 @@
 
 TEST_F(CommanderControllerTest, ResultSetIdsDifferAcrossCalls) {
   std::vector<std::unique_ptr<CommandSource>> sources;
-  ignore_result(AddSource(&sources, CreateNoOpCommandSource()));
+  std::ignore = AddSource(&sources, CreateNoOpCommandSource());
   base::RunLoop run_loop;
   auto controller =
       CommanderController::CreateWithSourcesForTesting(std::move(sources));
diff --git a/chrome/browser/ui/login/login_handler_browsertest.cc b/chrome/browser/ui/login/login_handler_browsertest.cc
index f3045a6..2f3d1758 100644
--- a/chrome/browser/ui/login/login_handler_browsertest.cc
+++ b/chrome/browser/ui/login/login_handler_browsertest.cc
@@ -5,10 +5,10 @@
 #include <algorithm>
 #include <list>
 #include <map>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/metrics/field_trial.h"
 #include "base/strings/stringprintf.h"
 #include "base/strings/utf_string_conversions.h"
@@ -2428,10 +2428,10 @@
   const GURL kAuthIFrameUrl = embedded_test_server()->GetURL(kAuthBasicPage);
   content::RenderFrameHost* prerender_rfh =
       prerender_helper().GetPrerenderedMainFrameHost(host_id);
-  ignore_result(ExecJs(prerender_rfh,
-                       "var i = document.createElement('iframe'); i.src = '" +
-                           kAuthIFrameUrl.spec() +
-                           "'; document.body.appendChild(i);"));
+  std::ignore =
+      ExecJs(prerender_rfh,
+             "var i = document.createElement('iframe'); i.src = '" +
+                 kAuthIFrameUrl.spec() + "'; document.body.appendChild(i);");
 
   // The prerender should be destroyed.
   host_observer.WaitForDestroyed();
@@ -2473,8 +2473,8 @@
         imgElement.src = '/auth-basic/favicon.gif';
         document.body.appendChild(imgElement);
   )";
-  ignore_result(ExecJs(prerender_helper().GetPrerenderedMainFrameHost(host_id),
-                       fetch_subresource_script));
+  std::ignore = ExecJs(prerender_helper().GetPrerenderedMainFrameHost(host_id),
+                       fetch_subresource_script);
 
   // The prerender should be destroyed.
   host_observer.WaitForDestroyed();
diff --git a/chrome/browser/ui/views/bookmarks/bookmark_bar_view_test.cc b/chrome/browser/ui/views/bookmarks/bookmark_bar_view_test.cc
index a670b6c..3f4cdd2 100644
--- a/chrome/browser/ui/views/bookmarks/bookmark_bar_view_test.cc
+++ b/chrome/browser/ui/views/bookmarks/bookmark_bar_view_test.cc
@@ -731,13 +731,7 @@
   }
 };
 
-// TODO(crbug.com/1281365): Flakes on Linux.
-#if defined(OS_LINUX)
-#define MAYBE_Submenus DISABLED_Submenus
-#else
-#define MAYBE_Submenus Submenus
-#endif
-VIEW_TEST(BookmarkBarViewTest3, MAYBE_Submenus)
+VIEW_TEST(BookmarkBarViewTest3, Submenus)
 
 // Observer that posts a task upon the context menu creation.
 // This is necessary for Linux as the context menu has to check the clipboard,
@@ -828,13 +822,7 @@
   BookmarkContextMenuNotificationObserver observer_;
 };
 
-// TODO(crbug.com/1281302): Flaky on Linux
-#if defined(OS_LINUX)
-#define MAYBE_ContextMenus DISABLED_ContextMenus
-#else
-#define MAYBE_ContextMenus ContextMenus
-#endif
-VIEW_TEST(BookmarkBarViewTest4, MAYBE_ContextMenus)
+VIEW_TEST(BookmarkBarViewTest4, ContextMenus)
 
 // Tests drag and drop within the same menu.
 class BookmarkBarViewTest5 : public BookmarkBarViewDragTestBase {
@@ -1268,14 +1256,7 @@
   BookmarkContextMenuNotificationObserver observer_;
 };
 
-// TODO(https://crbug.com/1281220): Flaky on Linux
-#if defined(OS_LINUX)
-#define MAYBE_CloseMenuAfterClosingContextMenu \
-  DISABLED_CloseMenuAfterClosingContextMenu
-#else
-#define MAYBE_CloseMenuAfterClosingContextMenu CloseMenuAfterClosingContextMenu
-#endif
-VIEW_TEST(BookmarkBarViewTest11, MAYBE_CloseMenuAfterClosingContextMenu)
+VIEW_TEST(BookmarkBarViewTest11, CloseMenuAfterClosingContextMenu)
 
 // Tests showing a modal dialog from a context menu.
 class BookmarkBarViewTest12 : public BookmarkBarViewEventTestBase {
@@ -1484,13 +1465,7 @@
   BookmarkContextMenuNotificationObserver observer_;
 };
 
-// TODO(https://crbug.com/1281270): Flaky on Linux.
-#if defined(OS_LINUX)
-#define MAYBE_ContextMenus2 DISABLED_ContextMenus2
-#else
-#define MAYBE_ContextMenus2 ContextMenus2
-#endif
-VIEW_TEST(BookmarkBarViewTest14, MAYBE_ContextMenus2)
+VIEW_TEST(BookmarkBarViewTest14, ContextMenus2)
 
 // Makes sure deleting from the context menu keeps the bookmark menu showing.
 class BookmarkBarViewTest15 : public BookmarkBarViewEventTestBase {
diff --git a/chrome/browser/ui/views/commander_frontend_views.cc b/chrome/browser/ui/views/commander_frontend_views.cc
index f4de5c9..fd8bcc6 100644
--- a/chrome/browser/ui/views/commander_frontend_views.cc
+++ b/chrome/browser/ui/views/commander_frontend_views.cc
@@ -4,9 +4,10 @@
 
 #include "chrome/browser/ui/views/commander_frontend_views.h"
 
+#include <tuple>
+
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
@@ -213,7 +214,7 @@
 
   focus_loss_watcher_.reset();
   widget_delegate_->SetOwnedByWidget(true);
-  ignore_result(widget_delegate_.release());
+  std::ignore = widget_delegate_.release();
   widget_->Close();
   widget_ = nullptr;
 }
diff --git a/chrome/browser/ui/views/commander_frontend_views_browsertest.cc b/chrome/browser/ui/views/commander_frontend_views_browsertest.cc
index 596a2bc..25ca754 100644
--- a/chrome/browser/ui/views/commander_frontend_views_browsertest.cc
+++ b/chrome/browser/ui/views/commander_frontend_views_browsertest.cc
@@ -4,7 +4,8 @@
 
 #include "chrome/browser/ui/views/commander_frontend_views.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/memory/raw_ptr.h"
 #include "chrome/browser/ui/commander/commander_backend.h"
 #include "chrome/browser/ui/commander/commander_view_model.h"
@@ -234,7 +235,7 @@
   auto frontend = std::make_unique<CommanderFrontendViews>(backend_.get());
 
   frontend->Show(browser());
-  ignore_result(WaitForCommanderWidgetAttachedTo(browser()));
+  std::ignore = WaitForCommanderWidgetAttachedTo(browser());
 
   frontend->OnOptionSelected(8, 13);
   ASSERT_EQ(backend_->command_selected_invocations().size(), 1u);
@@ -245,7 +246,7 @@
 IN_PROC_BROWSER_TEST_F(CommanderFrontendViewsTest, PassesOnTextChanged) {
   auto frontend = std::make_unique<CommanderFrontendViews>(backend_.get());
   frontend->Show(browser());
-  ignore_result(WaitForCommanderWidgetAttachedTo(browser()));
+  std::ignore = WaitForCommanderWidgetAttachedTo(browser());
 
   const std::u16string input = u"orange";
   frontend->OnTextChanged(input);
@@ -258,7 +259,7 @@
                        PassesOnCompositeCommandCancelled) {
   auto frontend = std::make_unique<CommanderFrontendViews>(backend_.get());
   frontend->Show(browser());
-  ignore_result(WaitForCommanderWidgetAttachedTo(browser()));
+  std::ignore = WaitForCommanderWidgetAttachedTo(browser());
 
   EXPECT_EQ(backend_->composite_command_cancelled_invocation_count(), 0);
   frontend->OnCompositeCommandCancelled();
diff --git a/chrome/browser/ui/views/frame/glass_browser_frame_view_browsertest_win.cc b/chrome/browser/ui/views/frame/glass_browser_frame_view_browsertest_win.cc
index dbd2ebcb..060c697 100644
--- a/chrome/browser/ui/views/frame/glass_browser_frame_view_browsertest_win.cc
+++ b/chrome/browser/ui/views/frame/glass_browser_frame_view_browsertest_win.cc
@@ -4,9 +4,10 @@
 
 #include "chrome/browser/ui/views/frame/glass_browser_frame_view.h"
 
+#include <tuple>
+
 #include "base/bind.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/strings/stringprintf.h"
 #include "base/test/bind.h"
@@ -241,7 +242,7 @@
     web_app_frame_toolbar_helper_.SetupGeometryChangeCallback(web_contents);
     browser_view_->ToggleWindowControlsOverlayEnabled();
     content::TitleWatcher title_watcher(web_contents, u"ongeometrychange");
-    ignore_result(title_watcher.WaitAndGetTitle());
+    std::ignore = title_watcher.WaitAndGetTitle();
   }
 
   raw_ptr<BrowserView> browser_view_ = nullptr;
diff --git a/chrome/browser/ui/views/frame/opaque_browser_frame_view_browsertest.cc b/chrome/browser/ui/views/frame/opaque_browser_frame_view_browsertest.cc
index 75fce1e..5cfaff6 100644
--- a/chrome/browser/ui/views/frame/opaque_browser_frame_view_browsertest.cc
+++ b/chrome/browser/ui/views/frame/opaque_browser_frame_view_browsertest.cc
@@ -4,8 +4,9 @@
 
 #include "chrome/browser/ui/views/frame/opaque_browser_frame_view.h"
 
+#include <tuple>
+
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/test/bind.h"
 #include "build/build_config.h"
@@ -352,7 +353,7 @@
     web_app_frame_toolbar_helper_.SetupGeometryChangeCallback(web_contents);
     browser_view_->ToggleWindowControlsOverlayEnabled();
     content::TitleWatcher title_watcher(web_contents, u"ongeometrychange");
-    ignore_result(title_watcher.WaitAndGetTitle());
+    std::ignore = title_watcher.WaitAndGetTitle();
   }
 
   raw_ptr<BrowserView> browser_view_ = nullptr;
diff --git a/chrome/browser/ui/views/frame/top_controls_slide_controller_chromeos_browsertest.cc b/chrome/browser/ui/views/frame/top_controls_slide_controller_chromeos_browsertest.cc
index df9517c..6b03ab8e 100644
--- a/chrome/browser/ui/views/frame/top_controls_slide_controller_chromeos_browsertest.cc
+++ b/chrome/browser/ui/views/frame/top_controls_slide_controller_chromeos_browsertest.cc
@@ -6,6 +6,7 @@
 
 #include <memory>
 #include <numeric>
+#include <tuple>
 #include <vector>
 
 #include "ash/constants/ash_switches.h"
@@ -17,7 +18,6 @@
 #include "base/bind.h"
 #include "base/callback_helpers.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/strings/safe_sprintf.h"
 #include "build/chromeos_buildflags.h"
@@ -867,7 +867,7 @@
   EXPECT_TRUE(bool_result);
   // Evaluate an empty sentence to make sure that the event processing is done
   // in the content.
-  ignore_result(content::EvalJs(contents, ";"));
+  std::ignore = content::EvalJs(contents, ";");
 
   SCOPED_TRACE("Scroll to hide should now work.");
   ScrollAndExpectTopChromeToBe(ScrollDirection::kDown,
@@ -1085,7 +1085,7 @@
   send_key_event(ui::VKEY_RETURN);
   // Evaluate an empty sentence to make sure that the event processing is done
   // in the content.
-  ignore_result(content::EvalJs(contents, ";"));
+  std::ignore = content::EvalJs(contents, ";");
 
   // Verify that the selected option has changed and the fourth option is
   // selected.
diff --git a/chrome/browser/ui/views/omnibox/omnibox_view_views_browsertest.cc b/chrome/browser/ui/views/omnibox/omnibox_view_views_browsertest.cc
index 4a74a40b..4bd17d9 100644
--- a/chrome/browser/ui/views/omnibox/omnibox_view_views_browsertest.cc
+++ b/chrome/browser/ui/views/omnibox/omnibox_view_views_browsertest.cc
@@ -9,11 +9,14 @@
 #include "base/command_line.h"
 #include "base/feature_list.h"
 #include "base/memory/raw_ptr.h"
+#include "base/test/bind.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
 #include "chrome/app/chrome_command_ids.h"
 #include "chrome/browser/external_protocol/external_protocol_handler.h"
+#include "chrome/browser/interstitials/security_interstitial_page_test_utils.h"
 #include "chrome/browser/search_engines/template_url_service_factory.h"
+#include "chrome/browser/ssl/typed_navigation_upgrade_throttle.h"
 #include "chrome/browser/ui/browser.h"
 #include "chrome/browser/ui/browser_commands.h"
 #include "chrome/browser/ui/browser_window.h"
@@ -34,6 +37,8 @@
 #include "content/public/browser/web_contents.h"
 #include "content/public/common/url_constants.h"
 #include "content/public/test/browser_test.h"
+#include "content/public/test/test_navigation_observer.h"
+#include "content/public/test/url_loader_interceptor.h"
 #include "third_party/blink/public/common/chrome_debug_urls.h"
 #include "ui/accessibility/accessibility_switches.h"
 #include "ui/accessibility/ax_action_data.h"
@@ -129,6 +134,19 @@
     }
   }
 
+  OmniboxView* omnibox() {
+    return browser()->window()->GetLocationBar()->GetOmniboxView();
+  }
+
+  void PressEnterAndWaitForNavigations(size_t num_expected_navigations) {
+    content::TestNavigationObserver navigation_observer(
+        browser()->tab_strip_model()->GetActiveWebContents(),
+        num_expected_navigations);
+    EXPECT_TRUE(ui_test_utils::SendKeyPressSync(browser(), ui::VKEY_RETURN,
+                                                false, false, false, false));
+    navigation_observer.Wait();
+  }
+
  private:
   // InProcessBrowserTest:
   void SetUpOnMainThread() override {
@@ -989,3 +1007,69 @@
 
 #endif  // !defined(OS_MAC) || defined(USE_AURA)
 }
+
+// SendKeyPressSync times out on Mac, probably due to https://crbug.com/824418.
+#if defined(OS_MAC)
+#define MAYBE_DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade \
+  DISABLED_DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade
+#else
+#define MAYBE_DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade \
+  DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade
+#endif
+
+// Test that triggers a zero suggest autocomplete request by clicking on the
+// omnibox. These should never attempt an https upgrade or involve the typed
+// navigation upgrade throttle.
+// This is a regression test for https://crbug.com/1251065
+IN_PROC_BROWSER_TEST_F(
+    OmniboxViewViewsTest,
+    MAYBE_DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade) {
+  // Since the embedded test server only works for URLs with non-default ports,
+  // use a URLLoaderInterceptor to mimic port-free operation. This allows the
+  // rest of the test to operate as if all URLs are using the default ports.
+  content::URLLoaderInterceptor interceptor(base::BindLambdaForTesting(
+      [&](content::URLLoaderInterceptor::RequestParams* params) {
+        if (params->url_request.url.host() == "site-with-good-https.com") {
+          std::string headers =
+              "HTTP/1.1 200 OK\nContent-Type: text/html; charset=utf-8\n";
+          std::string body = "<html><title>Success</title>Hello world</html>";
+          content::URLLoaderInterceptor::WriteResponse(headers, body,
+                                                       params->client.get());
+          return true;
+        }
+        // Not handled by us.
+        return false;
+      }));
+
+  base::HistogramTester histograms;
+  const GURL url("https://site-with-good-https.com");
+
+  // Type "https://site-with-good-https.com". This should load fine without
+  // hitting TypedNavigationUpgradeThrottle.
+  omnibox()->SetUserText(base::UTF8ToUTF16(url.spec()), true);
+  PressEnterAndWaitForNavigations(1);
+  content::WebContents* contents =
+      browser()->tab_strip_model()->GetActiveWebContents();
+  EXPECT_EQ(url, contents->GetLastCommittedURL());
+  EXPECT_FALSE(chrome_browser_interstitials::IsShowingInterstitial(contents));
+
+  histograms.ExpectTotalCount(TypedNavigationUpgradeThrottle::kHistogramName,
+                              0);
+  ui_test_utils::HistoryEnumerator enumerator(browser()->profile());
+  EXPECT_TRUE(base::Contains(enumerator.urls(), url));
+
+  // Now click the omnibox. This should trigger a zero suggest request with the
+  // text "site-with-good-https.com" despite the omnibox URL being
+  // https://site-with-good-https.com. Autocomplete input class shouldn't try
+  // to upgrade this request.
+  const gfx::Rect omnibox_bounds =
+      BrowserView::GetBrowserViewForBrowser(browser())
+          ->GetViewByID(VIEW_ID_OMNIBOX)
+          ->GetBoundsInScreen();
+  const gfx::Point click_location = omnibox_bounds.CenterPoint();
+  ASSERT_NO_FATAL_FAILURE(
+      Click(ui_controls::LEFT, click_location, click_location));
+  PressEnterAndWaitForNavigations(1);
+  histograms.ExpectTotalCount(TypedNavigationUpgradeThrottle::kHistogramName,
+                              0);
+}
diff --git a/chrome/browser/ui/views/overlay/overlay_window_views.cc b/chrome/browser/ui/views/overlay/overlay_window_views.cc
index d575bf7..1087db0 100644
--- a/chrome/browser/ui/views/overlay/overlay_window_views.cc
+++ b/chrome/browser/ui/views/overlay/overlay_window_views.cc
@@ -851,12 +851,7 @@
 
 void OverlayWindowViews::Close() {
   views::Widget::Close();
-
-  if (has_registered_frame_sink_hierarchy_) {
-    DCHECK(GetCurrentFrameSinkId());
-    GetCompositor()->RemoveChildFrameSink(*GetCurrentFrameSinkId());
-    has_registered_frame_sink_hierarchy_ = false;
-  }
+  MaybeUnregisterFrameSinkHierarchy();
 }
 
 void OverlayWindowViews::ShowInactive() {
@@ -889,12 +884,7 @@
 
 void OverlayWindowViews::Hide() {
   views::Widget::Hide();
-
-  if (has_registered_frame_sink_hierarchy_) {
-    DCHECK(GetCurrentFrameSinkId());
-    GetCompositor()->RemoveChildFrameSink(*GetCurrentFrameSinkId());
-    has_registered_frame_sink_hierarchy_ = false;
-  }
+  MaybeUnregisterFrameSinkHierarchy();
 }
 
 bool OverlayWindowViews::IsVisible() {
@@ -996,10 +986,7 @@
   // The PiP window may have a previous surface set. If the window stays open
   // since then, we need to unregister the previous frame sink; otherwise the
   // surface frame sink should already be removed when the window closed.
-  if (has_registered_frame_sink_hierarchy_) {
-    DCHECK(GetCurrentFrameSinkId());
-    GetCompositor()->RemoveChildFrameSink(*GetCurrentFrameSinkId());
-  }
+  MaybeUnregisterFrameSinkHierarchy();
 
   // Add the new frame sink to the PiP window and set the surface.
   GetCompositor()->AddChildFrameSink(surface_id.frame_sink_id());
@@ -1026,11 +1013,7 @@
 
 void OverlayWindowViews::OnNativeWidgetDestroying() {
   views::Widget::OnNativeWidgetDestroying();
-  if (has_registered_frame_sink_hierarchy_) {
-    DCHECK(GetCurrentFrameSinkId());
-    GetCompositor()->RemoveChildFrameSink(*GetCurrentFrameSinkId());
-    has_registered_frame_sink_hierarchy_ = false;
-  }
+  MaybeUnregisterFrameSinkHierarchy();
 }
 
 void OverlayWindowViews::OnNativeWidgetDestroyed() {
@@ -1094,11 +1077,7 @@
 }
 
 void OverlayWindowViews::OnNativeWidgetRemovingFromCompositor() {
-  if (has_registered_frame_sink_hierarchy_) {
-    DCHECK(GetCurrentFrameSinkId());
-    GetCompositor()->RemoveChildFrameSink(*GetCurrentFrameSinkId());
-    has_registered_frame_sink_hierarchy_ = false;
-  }
+  MaybeUnregisterFrameSinkHierarchy();
 }
 
 void OverlayWindowViews::OnKeyEvent(ui::KeyEvent* event) {
@@ -1429,3 +1408,11 @@
 
   return nullptr;
 }
+
+void OverlayWindowViews::MaybeUnregisterFrameSinkHierarchy() {
+  if (has_registered_frame_sink_hierarchy_) {
+    DCHECK(GetCurrentFrameSinkId());
+    GetCompositor()->RemoveChildFrameSink(*GetCurrentFrameSinkId());
+    has_registered_frame_sink_hierarchy_ = false;
+  }
+}
diff --git a/chrome/browser/ui/views/overlay/overlay_window_views.h b/chrome/browser/ui/views/overlay/overlay_window_views.h
index 229b618..c1d1661 100644
--- a/chrome/browser/ui/views/overlay/overlay_window_views.h
+++ b/chrome/browser/ui/views/overlay/overlay_window_views.h
@@ -202,6 +202,11 @@
   // returns nullptr.
   const viz::FrameSinkId* GetCurrentFrameSinkId() const;
 
+  // Unregisters the current frame sink id for the surface displayed in the
+  // |video_view_| from its parent frame sink if the frame sink hierarchy has
+  // been registered before.
+  void MaybeUnregisterFrameSinkHierarchy();
+
   // Not owned; |controller_| owns |this|.
   raw_ptr<content::PictureInPictureWindowController> controller_;
 
diff --git a/chrome/browser/ui/views/toolbar/app_menu_browsertest.cc b/chrome/browser/ui/views/toolbar/app_menu_browsertest.cc
index 58ee6c4..f266aa7e 100644
--- a/chrome/browser/ui/views/toolbar/app_menu_browsertest.cc
+++ b/chrome/browser/ui/views/toolbar/app_menu_browsertest.cc
@@ -39,13 +39,7 @@
 // properly (this was triggering a crash in AppMenu where it was trying to make
 // use of RecentTabsMenuModelDelegate before created). See
 // https://crbug.com/1249741 for more.
-#if BUILDFLAG(IS_CHROMEOS_LACROS)
-// TODO(crbug.com/1284776): Re-enable once flakiness is fixed.
-#define MAYBE_ShowWithRecentlyClosedWindow DISABLED_ShowWithRecentlyClosedWindow
-#else
-#define MAYBE_ShowWithRecentlyClosedWindow ShowWithRecentlyClosedWindow
-#endif
-IN_PROC_BROWSER_TEST_F(AppMenuBrowserTest, MAYBE_ShowWithRecentlyClosedWindow) {
+IN_PROC_BROWSER_TEST_F(AppMenuBrowserTest, ShowWithRecentlyClosedWindow) {
   // Create an additional browser, close it, and ensure it is added to the
   // TabRestoreService.
   sessions::TabRestoreService* tab_restore_service =
diff --git a/chrome/browser/ui/views/web_apps/frame_toolbar/web_app_frame_toolbar_browsertest.cc b/chrome/browser/ui/views/web_apps/frame_toolbar/web_app_frame_toolbar_browsertest.cc
index e9bfaefb..ef08ab9 100644
--- a/chrome/browser/ui/views/web_apps/frame_toolbar/web_app_frame_toolbar_browsertest.cc
+++ b/chrome/browser/ui/views/web_apps/frame_toolbar/web_app_frame_toolbar_browsertest.cc
@@ -3,8 +3,8 @@
 // found in the LICENSE file.
 
 #include <cmath>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/run_loop.h"
 #include "base/test/bind.h"
@@ -465,7 +465,7 @@
     helper()->SetupGeometryChangeCallback(web_contents);
     content::TitleWatcher title_watcher(web_contents, u"ongeometrychange");
     helper()->browser_view()->ToggleWindowControlsOverlayEnabled();
-    ignore_result(title_watcher.WaitAndGetTitle());
+    std::ignore = title_watcher.WaitAndGetTitle();
   }
 
   bool GetWindowControlOverlayVisibility() {
@@ -490,7 +490,7 @@
                 ->app_browser()
                 ->tab_strip_model()
                 ->GetActiveWebContents()));
-    ignore_result(title_watcher.WaitAndGetTitle());
+    std::ignore = title_watcher.WaitAndGetTitle();
   }
 
   gfx::Rect GetWindowControlOverlayBoundingClientRect() {
@@ -532,7 +532,7 @@
     helper()->SetupGeometryChangeCallback(web_contents);
     content::TitleWatcher title_watcher(web_contents, u"ongeometrychange");
     helper()->browser_view()->GetWidget()->SetBounds(new_bounds);
-    ignore_result(title_watcher.WaitAndGetTitle());
+    std::ignore = title_watcher.WaitAndGetTitle();
   }
 
   gfx::Rect GetWindowControlOverlayBoundingClientRectFromEvent() {
diff --git a/chrome/browser/ui/web_applications/web_app_browsertest.cc b/chrome/browser/ui/web_applications/web_app_browsertest.cc
index c9e1c42..2d36656 100644
--- a/chrome/browser/ui/web_applications/web_app_browsertest.cc
+++ b/chrome/browser/ui/web_applications/web_app_browsertest.cc
@@ -18,7 +18,6 @@
 #include "base/time/time.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
-#include "build/os_buildflags.h"
 #include "chrome/browser/apps/app_service/app_launch_params.h"
 #include "chrome/browser/apps/app_service/app_service_proxy.h"
 #include "chrome/browser/apps/app_service/app_service_proxy_factory.h"
diff --git a/chrome/browser/ui/web_applications/web_app_ui_manager_impl.cc b/chrome/browser/ui/web_applications/web_app_ui_manager_impl.cc
index cf7f41a2..28b65a1 100644
--- a/chrome/browser/ui/web_applications/web_app_ui_manager_impl.cc
+++ b/chrome/browser/ui/web_applications/web_app_ui_manager_impl.cc
@@ -25,6 +25,7 @@
 #include "chrome/browser/ui/web_applications/web_app_metrics.h"
 #include "chrome/browser/ui/webui/web_app_internals/web_app_internals_source.h"
 #include "chrome/browser/web_applications/extensions/web_app_extension_shortcut.h"
+#include "chrome/browser/web_applications/os_integration_manager.h"
 #include "chrome/browser/web_applications/system_web_apps/system_web_app_manager.h"
 #include "chrome/browser/web_applications/web_app_callback_app_identity.h"
 #include "chrome/browser/web_applications/web_app_provider.h"
@@ -50,6 +51,12 @@
 #endif
 
 #if defined(OS_WIN)
+#include "base/process/process.h"
+#include "chrome/browser/browser_process.h"
+#include "chrome/browser/ui/browser_list.h"
+#include "chrome/browser/web_applications/web_app_install_finalizer.h"
+#include "components/keep_alive_registry/keep_alive_types.h"
+#include "components/keep_alive_registry/scoped_keep_alive.h"
 #include "ui/gfx/native_widget_types.h"
 #endif  // defined(OS_WIN)
 
@@ -68,23 +75,36 @@
 }
 
 #if defined(OS_WIN)
-
-// UninstallWebAppWithDialogFromStartupSwitch handles WebApp uninstallation from
-// the Windows Settings.
+// ScopedKeepAlive not only keeps the process from terminating early
+// during uninstall, it also ensures the process will terminate when it
+// is destroyed if there is no active browser window.
 void UninstallWebAppWithDialogFromStartupSwitch(const AppId& app_id,
                                                 Profile* profile,
                                                 WebAppProvider* provider) {
-  if (!provider->registrar().IsLocallyInstalled(app_id)) {
-    // App does not exist and controller is destroyed.
-    return;
+  // ScopedKeepAlive does not only keeps the process from early termination,
+  // but ensure the process termination when there is no active browser window.
+  std::unique_ptr<ScopedKeepAlive> scoped_keep_alive =
+      std::make_unique<ScopedKeepAlive>(KeepAliveOrigin::WEB_APP_UNINSTALL,
+                                        KeepAliveRestartOption::DISABLED);
+  if (provider->install_finalizer().CanUserUninstallWebApp(app_id)) {
+    WebAppUiManagerImpl::Get(provider)->dialog_manager().UninstallWebApp(
+        app_id, webapps::WebappUninstallSource::kOsSettings,
+        gfx::kNullNativeWindow,
+        base::BindOnce([](std::unique_ptr<ScopedKeepAlive> scoped_keep_alive,
+                          bool success) {},
+                       std::move(scoped_keep_alive)));
+  } else {
+    // There is a chance that a previous invalid uninstall operation (due
+    // to a crash or otherwise) could end up orphaning an OsSettings entry.
+    // In this case we clean up the OsSettings entry.
+    web_app::OsHooksOptions options;
+    options[OsHookType::kUninstallationViaOsSettings] = true;
+    provider->os_integration_manager().UninstallOsHooks(
+        app_id, options,
+        base::BindOnce([](std::unique_ptr<ScopedKeepAlive> scoped_keep_alive,
+                          OsHooksErrors os_hooks_errors) {},
+                       std::move(scoped_keep_alive)));
   }
-
-  // Note: WebAppInstallFinalizer::UninstallWebApp creates a ScopedKeepAlive
-  // object which ensures the browser stays alive during the WebApp
-  // uninstall.
-  WebAppUiManagerImpl::Get(provider)->dialog_manager().UninstallWebApp(
-      app_id, webapps::WebappUninstallSource::kOsSettings,
-      gfx::kNullNativeWindow, base::DoNothing());
 }
 
 #endif  // defined(OS_WIN)
diff --git a/chrome/browser/ui/webui/access_code_cast/access_code_cast_ui.cc b/chrome/browser/ui/webui/access_code_cast/access_code_cast_ui.cc
index dd54345..3047403 100644
--- a/chrome/browser/ui/webui/access_code_cast/access_code_cast_ui.cc
+++ b/chrome/browser/ui/webui/access_code_cast/access_code_cast_ui.cc
@@ -71,7 +71,9 @@
   webui_ = webui;
 }
 
-void AccessCodeCastDialog::OnDialogClosed(const std::string& json_retval) {}
+void AccessCodeCastDialog::OnDialogClosed(const std::string& json_retval) {
+  delete this;
+}
 
 void AccessCodeCastDialog::OnCloseContents(content::WebContents* source,
                                            bool* out_close_dialog) {
diff --git a/chrome/browser/ui/webui/chrome_web_ui_controller_factory.cc b/chrome/browser/ui/webui/chrome_web_ui_controller_factory.cc
index c72d362..28306c79e 100644
--- a/chrome/browser/ui/webui/chrome_web_ui_controller_factory.cc
+++ b/chrome/browser/ui/webui/chrome_web_ui_controller_factory.cc
@@ -207,6 +207,7 @@
 #include "chrome/browser/ash/web_applications/chrome_file_manager_ui_delegate.h"
 #include "chrome/browser/ash/web_applications/help_app/help_app_ui_delegate.h"
 #include "chrome/browser/ash/web_applications/media_app/chrome_media_app_ui_delegate.h"
+#include "chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_theme_provider.h"
 #include "chrome/browser/ash/web_applications/personalization_app/chrome_personalization_app_wallpaper_provider.h"
 #include "chrome/browser/feedback/feedback_dialog_utils.h"
 #include "chrome/browser/nearby_sharing/nearby_sharing_service_factory.h"
@@ -577,6 +578,18 @@
           chrome::WebUIFeedbackSource::kConnectivityDiagnostics),
       /*show_feedback_button=*/!chrome::IsRunningInAppMode());
 }
+
+template <>
+WebUIController* NewWebUI<ash::PersonalizationAppUI>(WebUI* web_ui,
+                                                     const GURL& url) {
+  auto theme_provider =
+      std::make_unique<ChromePersonalizationAppThemeProvider>(web_ui);
+  auto wallpaper_provider =
+      std::make_unique<ChromePersonalizationAppWallpaperProvider>(web_ui);
+  return new ash::PersonalizationAppUI(web_ui, std::move(theme_provider),
+                                       std::move(wallpaper_provider));
+}
+
 #endif  // BUILDFLAG(IS_CHROMEOS_ASH)
 
 #if BUILDFLAG(ENABLE_DICE_SUPPORT)
@@ -960,8 +973,7 @@
   }
   if (url.host_piece() == ash::kChromeUIPersonalizationAppHost &&
       chromeos::features::IsWallpaperWebUIEnabled()) {
-    return &NewComponentUI<ash::PersonalizationAppUI,
-                           ChromePersonalizationAppWallpaperProvider>;
+    return &NewWebUI<ash::PersonalizationAppUI>;
   }
   if (url.host_piece() == ash::kChromeUISystemExtensionsInternalsHost &&
       base::FeatureList::IsEnabled(ash::features::kSystemExtensions)) {
diff --git a/chrome/browser/ui/webui/components/components_ui.cc b/chrome/browser/ui/webui/components/components_ui.cc
index c6e87025..440d7f6 100644
--- a/chrome/browser/ui/webui/components/components_ui.cc
+++ b/chrome/browser/ui/webui/components/components_ui.cc
@@ -75,7 +75,8 @@
           user_manager::UserManager::Get()->IsLoggedInAsPublicAccount()
 #elif BUILDFLAG(IS_CHROMEOS_LACROS)
       chromeos::LacrosService::Get()->init_params()->session_type ==
-          crosapi::mojom::SessionType::kPublicSession
+              crosapi::mojom::SessionType::kPublicSession ||
+          profile->IsGuestSession()
 #else
       profile->IsOffTheRecord()
 #endif
diff --git a/chrome/browser/ui/webui/management/management_ui.cc b/chrome/browser/ui/webui/management/management_ui.cc
index 4f000cf..d7128ac 100644
--- a/chrome/browser/ui/webui/management/management_ui.cc
+++ b/chrome/browser/ui/webui/management/management_ui.cc
@@ -72,6 +72,7 @@
     {kManagementPrinting, IDS_MANAGEMENT_REPORT_PRINTING},
     {kManagementReportPrintJobs, IDS_MANAGEMENT_REPORT_PRINT_JOBS},
     {kManagementReportLoginLogout, IDS_MANAGEMENT_REPORT_LOGIN_LOGOUT},
+    {kManagementReportCRDSessions, IDS_MANAGEMENT_REPORT_CRD_SESSIONS},
     {kManagementCrostini, IDS_MANAGEMENT_CROSTINI},
     {kManagementCrostiniContainerConfiguration,
      IDS_MANAGEMENT_CROSTINI_CONTAINER_CONFIGURATION},
diff --git a/chrome/browser/ui/webui/management/management_ui_handler.cc b/chrome/browser/ui/webui/management/management_ui_handler.cc
index 77cca35e..25f8db3 100644
--- a/chrome/browser/ui/webui/management/management_ui_handler.cc
+++ b/chrome/browser/ui/webui/management/management_ui_handler.cc
@@ -171,6 +171,7 @@
     "managementReportAndroidApplications";
 const char kManagementReportPrintJobs[] = "managementReportPrintJobs";
 const char kManagementReportLoginLogout[] = "managementReportLoginLogout";
+const char kManagementReportCRDSessions[] = "managementReportCRDSessions";
 const char kManagementReportDlpEvents[] = "managementReportDlpEvents";
 const char kManagementPrinting[] = "managementPrinting";
 const char kManagementCrostini[] = "managementCrostini";
@@ -221,7 +222,8 @@
   kExtensions,
   kAndroidApplication,
   kDlpEvents,
-  kLoginLogout
+  kLoginLogout,
+  kCRDSessions,
 };
 
 // Corresponds to DeviceReportingType in management_browser_proxy.js
@@ -257,6 +259,8 @@
       return "dlp events";
     case DeviceReportingType::kLoginLogout:
       return "login-logout";
+    case DeviceReportingType::kCRDSessions:
+      return "crd sessions";
     default:
       NOTREACHED() << "Unknown device reporting type";
       return "device";
@@ -630,6 +634,14 @@
     AddDeviceReportingElement(report_sources, kManagementReportLoginLogout,
                               DeviceReportingType::kLoginLogout);
   }
+
+  bool report_crd_sessions = false;
+  chromeos::CrosSettings::Get()->GetBoolean(ash::kReportCRDSessions,
+                                            &report_crd_sessions);
+  if (report_crd_sessions) {
+    AddDeviceReportingElement(report_sources, kManagementReportCRDSessions,
+                              DeviceReportingType::kCRDSessions);
+  }
 }
 
 bool ManagementUIHandler::IsUpdateRequiredEol() const {
diff --git a/chrome/browser/ui/webui/management/management_ui_handler.h b/chrome/browser/ui/webui/management/management_ui_handler.h
index 474311e..2d9841b 100644
--- a/chrome/browser/ui/webui/management/management_ui_handler.h
+++ b/chrome/browser/ui/webui/management/management_ui_handler.h
@@ -36,6 +36,7 @@
 extern const char kManagementReportPrintJobs[];
 extern const char kManagementReportDlpEvents[];
 extern const char kManagementReportLoginLogout[];
+extern const char kManagementReportCRDSessions[];
 extern const char kManagementPrinting[];
 extern const char kManagementCrostini[];
 extern const char kManagementCrostiniContainerConfiguration[];
diff --git a/chrome/browser/ui/webui/settings/settings_localized_strings_provider.cc b/chrome/browser/ui/webui/settings/settings_localized_strings_provider.cc
index 8fc7ea14..d63ac6d 100644
--- a/chrome/browser/ui/webui/settings/settings_localized_strings_provider.cc
+++ b/chrome/browser/ui/webui/settings/settings_localized_strings_provider.cc
@@ -208,7 +208,8 @@
           user_manager::UserManager::Get()->IsLoggedInAsPublicAccount());
 #elif BUILDFLAG(IS_CHROMEOS_LACROS)
       chromeos::LacrosService::Get()->init_params()->session_type ==
-          crosapi::mojom::SessionType::kPublicSession);
+              crosapi::mojom::SessionType::kPublicSession ||
+          profile->IsGuestSession());
 #else
                           profile->IsGuestSession());
 #endif
diff --git a/chrome/browser/ui/webui/settings/site_settings_handler.cc b/chrome/browser/ui/webui/settings/site_settings_handler.cc
index 52c1642..9fcd702 100644
--- a/chrome/browser/ui/webui/settings/site_settings_handler.cc
+++ b/chrome/browser/ui/webui/settings/site_settings_handler.cc
@@ -622,9 +622,13 @@
 
 void SiteSettingsHandler::OnJavascriptAllowed() {
   ObserveSourcesForProfile(profile_);
-  if (profile_->HasPrimaryOTRProfile())
-    ObserveSourcesForProfile(
-        profile_->GetPrimaryOTRProfile(/*create_if_needed=*/true));
+  if (profile_->HasPrimaryOTRProfile()) {
+    auto* primary_otr_profile =
+        profile_->GetPrimaryOTRProfile(/*create_if_needed=*/true);
+    // Avoid duplicate observation.
+    if (primary_otr_profile != profile_)
+      ObserveSourcesForProfile(primary_otr_profile);
+  }
 
   // Here we only subscribe to the HostZoomMap for the default storage partition
   // since we don't allow the user to manage the zoom levels for apps.
diff --git a/chrome/browser/webshare/win/fake_storage_file_statics.cc b/chrome/browser/webshare/win/fake_storage_file_statics.cc
index 3088add..4c200158 100644
--- a/chrome/browser/webshare/win/fake_storage_file_statics.cc
+++ b/chrome/browser/webshare/win/fake_storage_file_statics.cc
@@ -9,10 +9,10 @@
 #include <wrl/module.h>
 
 #include <memory>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/test/bind.h"
 #include "base/test/fake_iasync_operation_win.h"
 #include "base/threading/thread_task_runner_handle.h"
@@ -63,7 +63,7 @@
     // and release ownership of the original 'back' to the caller.
     base::win::ScopedHString holder(display_name_with_extension);
     display_name_with_extension_ = holder.GetAsUTF8();
-    ignore_result(holder.release());
+    std::ignore = holder.release();
   }
   FakeStorageFile(const FakeStorageFile&) = delete;
   FakeStorageFile& operator=(const FakeStorageFile&) = delete;
diff --git a/chrome/browser/webshare/win/fake_uri_runtime_class_factory.cc b/chrome/browser/webshare/win/fake_uri_runtime_class_factory.cc
index d6fa279..acfe510a 100644
--- a/chrome/browser/webshare/win/fake_uri_runtime_class_factory.cc
+++ b/chrome/browser/webshare/win/fake_uri_runtime_class_factory.cc
@@ -5,8 +5,8 @@
 #include "chrome/browser/webshare/win/fake_uri_runtime_class_factory.h"
 
 #include <string>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/notreached.h"
 #include "base/win/scoped_hstring.h"
 #include "testing/gtest/include/gtest/gtest.h"
@@ -151,7 +151,7 @@
   // and release ownership of the original 'back' to the caller.
   base::win::ScopedHString holder(uri);
   auto uri_string = holder.GetAsUTF8();
-  ignore_result(holder.release());
+  std::ignore = holder.release();
 
   if (uri_string.empty()) {
     ADD_FAILURE() << "CreateUri called with empty uri.";
diff --git a/chrome/browser/xsurface/android/java/src/org/chromium/chrome/browser/xsurface/SurfaceActionsHandler.java b/chrome/browser/xsurface/android/java/src/org/chromium/chrome/browser/xsurface/SurfaceActionsHandler.java
index c776472..0894a01 100644
--- a/chrome/browser/xsurface/android/java/src/org/chromium/chrome/browser/xsurface/SurfaceActionsHandler.java
+++ b/chrome/browser/xsurface/android/java/src/org/chromium/chrome/browser/xsurface/SurfaceActionsHandler.java
@@ -6,6 +6,7 @@
 
 import android.view.View;
 
+import java.util.List;
 /**
  * Interface to provide chromium calling points for an external surface.
  */
@@ -48,6 +49,15 @@
 
     /**
      * Dismiss the open bottom sheet (or do nothing if there isn't one).
+     *
      */
     default void dismissBottomSheet() {}
+
+    /**
+     * Notifies the host app that url with broadTopicMids and entityMids was clicked.
+     * @param url The URL that the user clicked on
+     * @param entityMids Sorted list (most relevant to least) of entity MIDs that correspond to the
+     *         clicked URL
+     */
+    default void updateUserProfileOnLinkClick(String url, List<Long> entityMids) {}
 }
diff --git a/chrome/build/linux.pgo.txt b/chrome/build/linux.pgo.txt
index 863fa0a..29dd729 100644
--- a/chrome/build/linux.pgo.txt
+++ b/chrome/build/linux.pgo.txt
@@ -1 +1 @@
-chrome-linux-main-1641556507-e2d334876b7c435f81feb7b610d45fdc9019eb04.profdata
+chrome-linux-main-1641578242-e0d6e8e2f0ae433564dcd4bdef588458f8d9b944.profdata
diff --git a/chrome/build/mac.pgo.txt b/chrome/build/mac.pgo.txt
index 0fb791f..656a72cf 100644
--- a/chrome/build/mac.pgo.txt
+++ b/chrome/build/mac.pgo.txt
@@ -1 +1 @@
-chrome-mac-main-1641556507-72cc532d3d10b7e16fb62ec615fb675b5366780f.profdata
+chrome-mac-main-1641578242-7bbbc65858af9963fc8e8bd496e65e9b5bb8af08.profdata
diff --git a/chrome/build/win32.pgo.txt b/chrome/build/win32.pgo.txt
index c22bcf97..d94a2d4 100644
--- a/chrome/build/win32.pgo.txt
+++ b/chrome/build/win32.pgo.txt
@@ -1 +1 @@
-chrome-win32-main-1641556507-c8f9e38ff290f4fa5b5425e7ee57d20422cc8617.profdata
+chrome-win32-main-1641589129-0dde4ecb02410249eb818b00718aa90d6a6d6006.profdata
diff --git a/chrome/build/win64.pgo.txt b/chrome/build/win64.pgo.txt
index 67f523ea..52651dd 100644
--- a/chrome/build/win64.pgo.txt
+++ b/chrome/build/win64.pgo.txt
@@ -1 +1 @@
-chrome-win64-main-1641556507-6812bf0408b84a4c9d107273eda1d933a9a4d878.profdata
+chrome-win64-main-1641589129-dcfca0fc35387db301739a73849e085e42f51e67.profdata
diff --git a/chrome/common/BUILD.gn b/chrome/common/BUILD.gn
index 7515a12..7f441d95d 100644
--- a/chrome/common/BUILD.gn
+++ b/chrome/common/BUILD.gn
@@ -241,7 +241,6 @@
 
   deps = [
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//components/google/core/common",
     "//components/live_caption:constants",
     "//components/metrics:call_stack_profile_builder",
diff --git a/chrome/common/channel_info_mac.mm b/chrome/common/channel_info_mac.mm
index 6f13900..59da30c 100644
--- a/chrome/common/channel_info_mac.mm
+++ b/chrome/common/channel_info_mac.mm
@@ -6,8 +6,9 @@
 
 #import <Foundation/Foundation.h>
 
+#include <tuple>
+
 #include "base/check.h"
-#include "base/ignore_result.h"
 #include "base/mac/bundle_locations.h"
 #include "base/no_destructor.h"
 #include "base/strings/sys_string_conversions.h"
@@ -127,8 +128,8 @@
 }  // namespace
 
 void CacheChannelInfo() {
-  ignore_result(GetChannelState());
-  ignore_result(SideBySideCapable());
+  std::ignore = GetChannelState();
+  std::ignore = SideBySideCapable();
 }
 
 std::string GetChannelName(WithExtendedStable with_extended_stable) {
diff --git a/chrome/common/chrome_constants.cc b/chrome/common/chrome_constants.cc
index cc31b30..5e5e7a2 100644
--- a/chrome/common/chrome_constants.cc
+++ b/chrome/common/chrome_constants.cc
@@ -139,6 +139,8 @@
     FPL("previews_opt_out.db");
 const base::FilePath::CharType kQueryTileStorageDirname[] = FPL("Query Tiles");
 const base::FilePath::CharType kReadmeFilename[] = FPL("README");
+const base::FilePath::CharType kSCTAuditingPendingReportsFileName[] =
+    FPL("SCT Auditing Pending Reports");
 const base::FilePath::CharType kSecurePreferencesFilename[] =
     FPL("Secure Preferences");
 const base::FilePath::CharType kServiceStateFileName[] = FPL("Service State");
diff --git a/chrome/common/chrome_constants.h b/chrome/common/chrome_constants.h
index ad02022..dee5b6d 100644
--- a/chrome/common/chrome_constants.h
+++ b/chrome/common/chrome_constants.h
@@ -67,6 +67,7 @@
 extern const base::FilePath::CharType kQueryTileStorageDirname[];
 extern const base::FilePath::CharType kReadmeFilename[];
 extern const base::FilePath::CharType kReportingAndNelStoreFilename[];
+extern const base::FilePath::CharType kSCTAuditingPendingReportsFileName[];
 extern const base::FilePath::CharType kSecurePreferencesFilename[];
 extern const base::FilePath::CharType kSegmentationPlatformStorageDirName[];
 extern const base::FilePath::CharType kServiceStateFileName[];
diff --git a/chrome/common/chrome_features.cc b/chrome/common/chrome_features.cc
index 75dd8cd..8c8188e 100644
--- a/chrome/common/chrome_features.cc
+++ b/chrome/common/chrome_features.cc
@@ -52,6 +52,11 @@
 const base::Feature kAlwaysReinstallSystemWebApps{
     "ReinstallSystemWebApps", base::FEATURE_DISABLED_BY_DEFAULT};
 
+#if defined(OS_ANDROID)
+const base::Feature kAnonymousUpdateChecks{"AnonymousUpdateChecks",
+                                           base::FEATURE_ENABLED_BY_DEFAULT};
+#endif
+
 #if BUILDFLAG(IS_CHROMEOS_ASH)
 // Controls whether web apps can be installed via APKs on Chrome OS.
 const base::Feature kApkWebAppInstalls{"ApkWebAppInstalls",
@@ -323,6 +328,15 @@
 const base::Feature kDesktopPWAsWebBundles{"DesktopPWAsWebBundles",
                                            base::FEATURE_DISABLED_BY_DEFAULT};
 
+// Tries disabling the HTTP disk cache.
+const base::Feature kDisableHttpDiskCache{"DisableHttpDiskCache",
+                                          base::FEATURE_DISABLED_BY_DEFAULT};
+
+// The size of the memory cache when the HTTP disk cache is disabled. 0 uses the
+// default size.
+const base::FeatureParam<int> kDisableHttpDiskCacheMemoryCacheSizeParam{
+    &kDisableHttpDiskCache, "MemoryCacheSize", 0};
+
 // Enable DNS over HTTPS (DoH).
 const base::Feature kDnsOverHttps {
   "DnsOverHttps",
diff --git a/chrome/common/chrome_features.h b/chrome/common/chrome_features.h
index 73dc22583..fdab413 100644
--- a/chrome/common/chrome_features.h
+++ b/chrome/common/chrome_features.h
@@ -53,6 +53,11 @@
 COMPONENT_EXPORT(CHROME_FEATURES)
 extern const base::Feature kAlwaysReinstallSystemWebApps;
 
+#if defined(OS_ANDROID)
+COMPONENT_EXPORT(CHROME_FEATURES)
+extern const base::Feature kAnonymousUpdateChecks;
+#endif
+
 #if BUILDFLAG(IS_CHROMEOS_ASH)
 COMPONENT_EXPORT(CHROME_FEATURES)
 extern const base::Feature kApkWebAppInstalls;
@@ -219,6 +224,11 @@
 extern const base::Feature kDesktopPWAsWebBundles;
 
 COMPONENT_EXPORT(CHROME_FEATURES)
+extern const base::Feature kDisableHttpDiskCache;
+COMPONENT_EXPORT(CHROME_FEATURES)
+extern const base::FeatureParam<int> kDisableHttpDiskCacheMemoryCacheSizeParam;
+
+COMPONENT_EXPORT(CHROME_FEATURES)
 extern const base::Feature kDnsOverHttps;
 COMPONENT_EXPORT(CHROME_FEATURES)
 extern const base::FeatureParam<bool> kDnsOverHttpsFallbackParam;
diff --git a/chrome/common/logging_chrome.cc b/chrome/common/logging_chrome.cc
index a3594ca7..78840ec 100644
--- a/chrome/common/logging_chrome.cc
+++ b/chrome/common/logging_chrome.cc
@@ -3,7 +3,6 @@
 // found in the LICENSE file.
 
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 
 // Need to include this before most other files because it defines
 // IPC_MESSAGE_LOG_ENABLED. We need to use it to define
diff --git a/chrome/common/net/x509_certificate_model_nss.cc b/chrome/common/net/x509_certificate_model_nss.cc
index 8c43dff..46d5897 100644
--- a/chrome/common/net/x509_certificate_model_nss.cc
+++ b/chrome/common/net/x509_certificate_model_nss.cc
@@ -20,8 +20,8 @@
 
 #include <algorithm>
 #include <memory>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/numerics/safe_conversions.h"
 #include "base/strings/string_number_conversions.h"
@@ -258,7 +258,7 @@
   NSSCMSContentInfo *cinfo = NSS_CMSMessage_GetContentInfo(message.get());
   if (NSS_CMSContentInfo_SetContent_SignedData(
       message.get(), cinfo, signed_data.get()) == SECSuccess) {
-    ignore_result(signed_data.release());
+    std::ignore = signed_data.release();
   } else {
     DLOG(ERROR) << "NSS_CMSMessage_GetContentInfo failed";
     return std::string();
diff --git a/chrome/installer/util/beacons.cc b/chrome/installer/util/beacons.cc
index d72ee95..0745dca 100644
--- a/chrome/installer/util/beacons.cc
+++ b/chrome/installer/util/beacons.cc
@@ -6,7 +6,8 @@
 
 #include <stdint.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/notreached.h"
 #include "base/win/registry.h"
 #include "base/win/win_util.h"
@@ -16,7 +17,7 @@
 void UpdateDefaultBrowserBeaconForPath(const base::FilePath& chrome_exe) {
   // Getting Chrome's default state causes the beacon to be updated via a call
   // to UpdateDefaultBrowserBeaconWithState below.
-  ignore_result(ShellUtil::GetChromeDefaultStateFromPath(chrome_exe));
+  std::ignore = ShellUtil::GetChromeDefaultStateFromPath(chrome_exe);
 }
 
 void UpdateDefaultBrowserBeaconWithState(
diff --git a/chrome/installer/util/beacons_unittest.cc b/chrome/installer/util/beacons_unittest.cc
index e9cadd5..5e5417f 100644
--- a/chrome/installer/util/beacons_unittest.cc
+++ b/chrome/installer/util/beacons_unittest.cc
@@ -7,7 +7,6 @@
 #include <memory>
 #include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/test/test_reg_util_win.h"
 #include "base/test/test_timeouts.h"
 #include "base/threading/platform_thread.h"
@@ -141,7 +140,7 @@
   //   Software\Chromium, so it always exists.
 
   // Silence unused variable warnings.
-  ignore_result(wrong_root);
+  std::ignore = wrong_root;
 #endif
 
   // The right key should exist.
diff --git a/chrome/installer/util/logging_installer.cc b/chrome/installer/util/logging_installer.cc
index 30ac80c..42c37dc 100644
--- a/chrome/installer/util/logging_installer.cc
+++ b/chrome/installer/util/logging_installer.cc
@@ -7,11 +7,12 @@
 #include <stdint.h>
 #include <windows.h>
 
+#include <tuple>
+
 #include "base/command_line.h"
 #include "base/files/file.h"
 #include "base/files/file_path.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/logging_win.h"
 #include "base/path_service.h"
@@ -126,7 +127,7 @@
 
   // Fallback to current directory if getting the temp directory fails.
   base::FilePath tmp_path;
-  ignore_result(base::PathService::Get(base::DIR_TEMP, &tmp_path));
+  std::ignore = base::PathService::Get(base::DIR_TEMP, &tmp_path);
   return tmp_path.Append(kLogFilename);
 }
 
diff --git a/chrome/service/cloud_print/print_system_win.cc b/chrome/service/cloud_print/print_system_win.cc
index d6ad50cb..77f3c99b 100644
--- a/chrome/service/cloud_print/print_system_win.cc
+++ b/chrome/service/cloud_print/print_system_win.cc
@@ -9,11 +9,11 @@
 #include <wrl/client.h>
 
 #include <memory>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/command_line.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/json/json_writer.h"
 #include "base/memory/free_deleter.h"
 #include "base/memory/raw_ptr.h"
@@ -448,7 +448,7 @@
                             /*autorotate=*/false, use_color,
                             printing::PdfRenderSettings::Mode::NORMAL))) {
         // The object will self-destruct when the child process dies.
-        ignore_result(utility_host.release());
+        std::ignore = utility_host.release();
       } else {
         client_task_runner->PostTask(
             FROM_HERE, base::BindOnce(&Core::PrintJobDone, this, false));
@@ -587,7 +587,7 @@
         this, client_task_runner.get());
     if (utility_host->StartGetPrinterCapsAndDefaults(printer_name_)) {
       // The object will self-destruct when the child process dies.
-      ignore_result(utility_host.release());
+      std::ignore = utility_host.release();
     } else {
       client_task_runner->PostTask(
           FROM_HERE, base::BindOnce(&PrinterCapsHandler::OnChildDied, this));
@@ -601,7 +601,7 @@
         this, client_task_runner.get());
     if (utility_host->StartGetPrinterSemanticCapsAndDefaults(printer_name_)) {
       // The object will self-destruct when the child process dies.
-      ignore_result(utility_host.release());
+      std::ignore = utility_host.release();
     } else {
       client_task_runner->PostTask(
           FROM_HERE, base::BindOnce(&PrinterCapsHandler::OnChildDied, this));
diff --git a/chrome/services/speech/soda/soda_client.cc b/chrome/services/speech/soda/soda_client.cc
index b48f456b..cd620fa 100644
--- a/chrome/services/speech/soda/soda_client.cc
+++ b/chrome/services/speech/soda/soda_client.cc
@@ -4,7 +4,8 @@
 
 #include "chrome/services/speech/soda/soda_client.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/logging.h"
 #include "base/metrics/histogram_functions.h"
 #include "build/build_config.h"
@@ -75,7 +76,7 @@
   // there have been no crashes on 10.15+, likely due to a change in the
   // __cxa_atexit implementation.
   if (base::mac::IsAtMostOS10_14())
-    ignore_result(lib_.release());
+    std::ignore = lib_.release();
 #endif  // defined(OS_MAC)
 }
 
diff --git a/chrome/test/BUILD.gn b/chrome/test/BUILD.gn
index 4ed72e1..02d3c6c 100644
--- a/chrome/test/BUILD.gn
+++ b/chrome/test/BUILD.gn
@@ -1071,7 +1071,6 @@
       "//base/test:test_support",
       "//build:branding_buildflags",
       "//build:chromeos_buildflags",
-      "//build:os_buildflags",
       "//chrome:packed_resources",
       "//chrome:resources",
       "//chrome:strings",
@@ -4825,7 +4824,6 @@
     "../browser/signin/chrome_signin_proxying_url_loader_factory_unittest.cc",
     "../browser/signin/chrome_signin_status_metrics_provider_delegate_unittest.cc",
     "../browser/signin/chrome_signin_url_loader_throttle_unittest.cc",
-    "../browser/signin/primary_account_policy_manager_unittest.cc",
     "../browser/signin/reauth_tab_helper_unittest.cc",
     "../browser/signin/reauth_util_unittest.cc",
     "../browser/signin/signin_profile_attributes_updater_unittest.cc",
diff --git a/chrome/test/base/js2gtest.js b/chrome/test/base/js2gtest.js
index 47d3488..67aeb4d5 100644
--- a/chrome/test/base/js2gtest.js
+++ b/chrome/test/base/js2gtest.js
@@ -168,7 +168,8 @@
     addSetPreloadInfo = true;
   }
   output(`
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "url/gurl.h"
 #include "testing/gtest/include/gtest/gtest.h"`);
   // Add includes specified by test fixture.
@@ -473,7 +474,7 @@
         }
         if (testServer) {
           output(`
-    ignore_result(embedded_test_server()->Start());`);
+    std::ignore = embedded_test_server()->Start();`);
         }
         output(`
   }`);
diff --git a/chrome/test/data/webui/BUILD.gn b/chrome/test/data/webui/BUILD.gn
index 32f8d0d..32f3f7a 100644
--- a/chrome/test/data/webui/BUILD.gn
+++ b/chrome/test/data/webui/BUILD.gn
@@ -134,7 +134,7 @@
       deps += [ ":modulize" ]
     }
 
-    if (is_chromeos_ash || is_win) {
+    if (is_chromeos_ash || is_win || is_mac) {
       sources += [ "inline_login/inline_login_browsertest.js" ]
       deps += [ "//build:chromeos_buildflags" ]
     }
@@ -670,6 +670,15 @@
 
 # TypeScript related targets
 
+checked_in_dts_files = [ "test_browser_proxy.d.ts" ]
+
+# Copies checked-in .d.ts files to the preprocess folder so that they are
+# discovered by TSC the same way generated .d.ts files are.
+copy("copy_checked_in_dts_files") {
+  sources = checked_in_dts_files
+  outputs = [ "$target_gen_dir/tsc/{{source_target_relative}}" ]
+}
+
 ts_definitions("generate_definitions") {
   root_dir = "./"
   out_dir = "$target_gen_dir/tsc"
@@ -679,10 +688,12 @@
     "mock_controller.js",
     "mock_timer.js",
     "mojo_webui_test_support.js",
-    "test_browser_proxy.js",
     "test_plural_string_proxy.js",
     "test_store.js",
     "test_util.js",
   ]
-  extra_deps = [ "//ui/webui/resources:generate_definitions" ]
+  extra_deps = [
+    ":copy_checked_in_dts_files",
+    "//ui/webui/resources:generate_definitions",
+  ]
 }
diff --git a/chrome/test/data/webui/chromeos/personalization_app/BUILD.gn b/chrome/test/data/webui/chromeos/personalization_app/BUILD.gn
index 19429b1..1a90624 100644
--- a/chrome/test/data/webui/chromeos/personalization_app/BUILD.gn
+++ b/chrome/test/data/webui/chromeos/personalization_app/BUILD.gn
@@ -39,8 +39,10 @@
     "personalization_breadcrumb_element_test.ts",
     "personalization_main_element_test.ts",
     "personalization_router_element_test.ts",
+    "personalization_theme_element_test.ts",
     "personalization_toast_element_test.ts",
     "test_personalization_store.ts",
+    "test_theme_interface_provider.ts",
     "test_wallpaper_interface_provider.ts",
     "user_subpage_element_test.ts",
     "wallpaper_collections_element_test.ts",
diff --git a/chrome/test/data/webui/chromeos/personalization_app/personalization_app_component_test.ts b/chrome/test/data/webui/chromeos/personalization_app/personalization_app_component_test.ts
index bd5f9c8f..0e47c38 100644
--- a/chrome/test/data/webui/chromeos/personalization_app/personalization_app_component_test.ts
+++ b/chrome/test/data/webui/chromeos/personalization_app/personalization_app_component_test.ts
@@ -12,6 +12,7 @@
 import {PersonalizationBreadcrumbTest} from './personalization_breadcrumb_element_test.js';
 import {PersonalizationMainTest} from './personalization_main_element_test.js';
 import {PersonalizationRouterTest} from './personalization_router_element_test.js';
+import {PersonalizationThemeTest} from './personalization_theme_element_test.js';
 import {PersonalizationToastTest} from './personalization_toast_element_test.js';
 import {UserSubpageTest} from './user_subpage_element_test.js';
 import {WallpaperCollectionsTest} from './wallpaper_collections_element_test.js';
@@ -33,6 +34,7 @@
   PersonalizationBreadcrumbTest,
   PersonalizationMainTest,
   PersonalizationRouterTest,
+  PersonalizationThemeTest,
   PersonalizationToastTest,
   UserSubpageTest,
   WallpaperCollectionsTest,
diff --git a/chrome/test/data/webui/chromeos/personalization_app/personalization_app_test_utils.ts b/chrome/test/data/webui/chromeos/personalization_app/personalization_app_test_utils.ts
index 7ce5122..8130f538 100644
--- a/chrome/test/data/webui/chromeos/personalization_app/personalization_app_test_utils.ts
+++ b/chrome/test/data/webui/chromeos/personalization_app/personalization_app_test_utils.ts
@@ -8,6 +8,7 @@
  */
 
 import {emptyState, PersonalizationState} from 'chrome://personalization/trusted/personalization_state.js';
+import {setThemeProviderForTesting} from 'chrome://personalization/trusted/theme/theme_interface_provider.js';
 import {setWallpaperProviderForTesting} from 'chrome://personalization/trusted/wallpaper/wallpaper_interface_provider.js';
 import {flush, PolymerElement} from 'chrome://resources/polymer/v3_0/polymer/polymer_bundled.min.js';
 
@@ -15,6 +16,7 @@
 import {flushTasks} from 'chrome://webui-test/test_util.js';
 
 import {TestPersonalizationStore} from './test_personalization_store.js';
+import {TestThemeProvider} from './test_theme_interface_provider.js';
 import {TestWallpaperProvider} from './test_wallpaper_interface_provider.js';
 
 /**
@@ -56,10 +58,12 @@
 export function baseSetup(initialState: PersonalizationState = emptyState()) {
   const wallpaperProvider = new TestWallpaperProvider();
   setWallpaperProviderForTesting(wallpaperProvider);
+  const themeProvider = new TestThemeProvider();
+  setThemeProviderForTesting(themeProvider);
   const personalizationStore = new TestPersonalizationStore(initialState);
   personalizationStore.replaceSingleton();
   document.body.innerHTML = '';
-  return {wallpaperProvider, personalizationStore};
+  return {themeProvider, wallpaperProvider, personalizationStore};
 }
 
 function getDebugString(w: any) {
diff --git a/chrome/test/data/webui/chromeos/personalization_app/personalization_theme_element_test.ts b/chrome/test/data/webui/chromeos/personalization_app/personalization_theme_element_test.ts
new file mode 100644
index 0000000..1d920ec
--- /dev/null
+++ b/chrome/test/data/webui/chromeos/personalization_app/personalization_theme_element_test.ts
@@ -0,0 +1,81 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+/** @fileoverview Test suite for theme-element component.  */
+
+import {emptyState} from 'chrome://personalization/trusted/personalization_state.js';
+import {PersonalizationThemeElement} from 'chrome://personalization/trusted/personalization_theme_element.js';
+import {ThemeActionName} from 'chrome://personalization/trusted/theme/theme_actions.js';
+import {assertDeepEquals, assertEquals, assertFalse, assertTrue} from 'chrome://webui-test/chai_assert.js';
+import {flushTasks, waitAfterNextRender} from 'chrome://webui-test/test_util.js';
+
+import {baseSetup, initElement} from './personalization_app_test_utils.js';
+import {TestPersonalizationStore} from './test_personalization_store.js';
+import {TestThemeProvider} from './test_theme_interface_provider.js';
+
+export function PersonalizationThemeTest() {
+  let personalizationThemeElement: PersonalizationThemeElement|null;
+  let themeProvider: TestThemeProvider;
+  let personalizationStore: TestPersonalizationStore;
+
+  setup(() => {
+    const mocks = baseSetup();
+    themeProvider = mocks.themeProvider;
+    personalizationStore = mocks.personalizationStore;
+  });
+
+  teardown(async () => {
+    if (personalizationThemeElement) {
+      personalizationThemeElement.remove();
+    }
+    personalizationThemeElement = null;
+    await flushTasks();
+  });
+
+  test('displays content', async () => {
+    personalizationStore.data.theme = {darkModeEnabled: false};
+    personalizationThemeElement = initElement(PersonalizationThemeElement);
+    await waitAfterNextRender(personalizationThemeElement);
+
+    assertEquals(
+        personalizationThemeElement.i18n('themeLabel'),
+        personalizationThemeElement.shadowRoot!.querySelector('h2')!.innerText);
+  });
+
+  test('sets color mode in store on first load', async () => {
+    personalizationStore.expectAction(ThemeActionName.SET_DARK_MODE_ENABLED);
+    personalizationThemeElement = initElement(PersonalizationThemeElement);
+    const action = await personalizationStore.waitForAction(
+        ThemeActionName.SET_DARK_MODE_ENABLED);
+    assertTrue(action.enabled);
+  });
+
+  test('sets theme data in store on changed', async () => {
+    // Make sure state starts as expected.
+    assertDeepEquals(emptyState(), personalizationStore.data);
+
+    personalizationThemeElement = initElement(PersonalizationThemeElement);
+
+    await themeProvider.whenCalled('setThemeObserver');
+
+    personalizationStore.expectAction(ThemeActionName.SET_DARK_MODE_ENABLED);
+    themeProvider.themeObserverRemote!.onColorModeChanged(
+        /*darkModeEnabled=*/ false);
+
+    const {enabled} = await personalizationStore.waitForAction(
+        ThemeActionName.SET_DARK_MODE_ENABLED);
+    assertFalse(enabled);
+  });
+
+  test('shows pressed button on load', async () => {
+    personalizationThemeElement = initElement(PersonalizationThemeElement);
+    personalizationStore.data.theme.darkModeEnabled = true;
+    personalizationStore.notifyObservers();
+    await waitAfterNextRender(personalizationThemeElement);
+    const radioButton =
+        personalizationThemeElement.shadowRoot!.getElementById('darkMode');
+    assertTrue(!!radioButton);
+    assertEquals(radioButton!.getAttribute('aria-pressed'), 'true');
+  });
+}
diff --git a/chrome/test/data/webui/chromeos/personalization_app/test_theme_interface_provider.ts b/chrome/test/data/webui/chromeos/personalization_app/test_theme_interface_provider.ts
new file mode 100644
index 0000000..286d232
--- /dev/null
+++ b/chrome/test/data/webui/chromeos/personalization_app/test_theme_interface_provider.ts
@@ -0,0 +1,34 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+import {ThemeObserverInterface, ThemeObserverRemote, ThemeProviderInterface} from 'chrome://personalization/trusted/personalization_app.mojom-webui.js';
+import {TestBrowserProxy} from 'chrome://webui-test/test_browser_proxy.js';
+
+/**
+ * @implements {ThemeProviderInterface}
+ * @extends {TestBrowserProxy}
+ */
+export class TestThemeProvider extends TestBrowserProxy implements
+    ThemeProviderInterface {
+  constructor() {
+    super([
+      'setThemeObserver',
+      'setColorModePref',
+    ]);
+  }
+
+  themeObserverRemote: ThemeObserverInterface|null = null;
+
+  setThemeObserver(remote: ThemeObserverRemote) {
+    this.methodCalled('setThemeObserver');
+    this.themeObserverRemote = remote;
+    window.setTimeout(() => {
+      this.themeObserverRemote!.onColorModeChanged(/*darkModeEnabled=*/ true);
+    }, 0);
+  }
+
+  setColorModePref(darkModeEnabled: boolean) {
+    this.methodCalled('setColorModePref', darkModeEnabled);
+  }
+}
diff --git a/chrome/test/data/webui/cr_components/most_visited_focus_test.ts b/chrome/test/data/webui/cr_components/most_visited_focus_test.ts
index bb3d1a8..1f1b7a6 100644
--- a/chrome/test/data/webui/cr_components/most_visited_focus_test.ts
+++ b/chrome/test/data/webui/cr_components/most_visited_focus_test.ts
@@ -47,8 +47,7 @@
   setup(() => {
     document.body.innerHTML = '';
 
-    const handler = TestBrowserProxy.fromClass(MostVisitedPageHandlerRemote) as
-        unknown as MostVisitedPageHandlerRemote;
+    const handler = TestBrowserProxy.fromClass(MostVisitedPageHandlerRemote);
     const callbackRouter = new MostVisitedPageCallbackRouter();
     MostVisitedBrowserProxy.setInstance(
         new MostVisitedBrowserProxy(handler, callbackRouter));
diff --git a/chrome/test/data/webui/cr_components/most_visited_test.ts b/chrome/test/data/webui/cr_components/most_visited_test.ts
index 4d7c5e0a..1c8c1284 100644
--- a/chrome/test/data/webui/cr_components/most_visited_test.ts
+++ b/chrome/test/data/webui/cr_components/most_visited_test.ts
@@ -81,9 +81,7 @@
 }
 
 function createBrowserProxy() {
-  handler = TestBrowserProxy.fromClass(MostVisitedPageHandlerRemote) as
-          unknown as MostVisitedPageHandlerRemote &
-      TestBrowserProxy;
+  handler = TestBrowserProxy.fromClass(MostVisitedPageHandlerRemote);
   const callbackRouter = new MostVisitedPageCallbackRouter();
   MostVisitedBrowserProxy.setInstance(
       new MostVisitedBrowserProxy(handler, callbackRouter));
@@ -115,9 +113,7 @@
 }
 
 function createWindowProxy() {
-  windowProxy = TestBrowserProxy.fromClass(MostVisitedWindowProxy) as unknown as
-          MostVisitedWindowProxy &
-      TestBrowserProxy;
+  windowProxy = TestBrowserProxy.fromClass(MostVisitedWindowProxy);
   windowProxy.setResultMapperFor('matchMedia', (query: string) => {
     const mediaListenerList = new FakeMediaQueryList(query);
     if (query === '(min-width: 672px)') {
diff --git a/chrome/test/data/webui/test_browser_proxy.d.ts b/chrome/test/data/webui/test_browser_proxy.d.ts
new file mode 100644
index 0000000..78edd4c
--- /dev/null
+++ b/chrome/test/data/webui/test_browser_proxy.d.ts
@@ -0,0 +1,16 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+export class TestBrowserProxy {
+  static fromClass<T>(clazz: {new(): T}): T&TestBrowserProxy;
+  constructor(methodNames?: Array<string>);
+  methodCalled(methodName: string, ...args: any[]): any;
+  whenCalled(methodName: string): Promise<any>;
+  resetResolver(methodName: string): void;
+  reset(): void;
+  getCallCount(methodName: string): number;
+  getArgs(methodName: string): Array<any>;
+  setResultMapperFor(methodName: string, resultMapper: Function): void;
+  setResultFor(methodName: string, value: any): void;
+}
diff --git a/chrome/test/media_router/media_router_cast_ui_for_test.cc b/chrome/test/media_router/media_router_cast_ui_for_test.cc
index 8619c0e..7efa64aa 100644
--- a/chrome/test/media_router/media_router_cast_ui_for_test.cc
+++ b/chrome/test/media_router/media_router_cast_ui_for_test.cc
@@ -6,7 +6,6 @@
 
 #include "base/memory/raw_ptr.h"
 #include "chrome/browser/media/router/media_router_feature.h"
-#include "chrome/browser/ui/media_router/media_router_file_dialog.h"
 #include "chrome/browser/ui/media_router/media_router_ui.h"
 #include "chrome/browser/ui/views/media_router/cast_dialog_sink_button.h"
 #include "chrome/browser/ui/views/media_router/media_router_dialog_controller_views.h"
@@ -27,41 +26,6 @@
                         ui::EF_LEFT_MOUSE_BUTTON, 0);
 }
 
-// File dialog with a preset file URL.
-class TestMediaRouterFileDialog : public MediaRouterFileDialog {
- public:
-  TestMediaRouterFileDialog(MediaRouterFileDialogDelegate* delegate, GURL url)
-      : MediaRouterFileDialog(nullptr), delegate_(delegate), file_url_(url) {}
-  ~TestMediaRouterFileDialog() override = default;
-
-  GURL GetLastSelectedFileUrl() override { return file_url_; }
-
-  void OpenFileDialog(Browser* browser) override {
-    delegate_->FileDialogFileSelected(ui::SelectedFileInfo());
-  }
-
- private:
-  raw_ptr<MediaRouterFileDialogDelegate> delegate_;
-  GURL file_url_;
-};
-
-// File dialog which fails on open.
-class TestFailMediaRouterFileDialog : public MediaRouterFileDialog {
- public:
-  TestFailMediaRouterFileDialog(MediaRouterFileDialogDelegate* delegate,
-                                const IssueInfo& issue)
-      : MediaRouterFileDialog(nullptr), delegate_(delegate), issue_(issue) {}
-  ~TestFailMediaRouterFileDialog() override = default;
-
-  void OpenFileDialog(Browser* browser) override {
-    delegate_->FileDialogSelectionFailed(issue_);
-  }
-
- private:
-  raw_ptr<MediaRouterFileDialogDelegate> delegate_;
-  const IssueInfo issue_;
-};
-
 }  // namespace
 
 // static
@@ -157,19 +121,6 @@
   ObserveDialog(WatchType::kDialogHidden);
 }
 
-void MediaRouterCastUiForTest::SetLocalFile(const GURL& file_url) {
-  dialog_controller_->ui()->set_media_router_file_dialog_for_test(
-      std::make_unique<TestMediaRouterFileDialog>(dialog_controller_->ui(),
-                                                  file_url));
-}
-
-void MediaRouterCastUiForTest::SetLocalFileSelectionIssue(
-    const IssueInfo& issue) {
-  dialog_controller_->ui()->set_media_router_file_dialog_for_test(
-      std::make_unique<TestFailMediaRouterFileDialog>(dialog_controller_->ui(),
-                                                      issue));
-}
-
 void MediaRouterCastUiForTest::OnDialogCreated() {
   MediaRouterUiForTestBase::OnDialogCreated();
   CastDialogView::GetInstance()->KeepShownForTesting();
diff --git a/chrome/test/media_router/media_router_cast_ui_for_test.h b/chrome/test/media_router/media_router_cast_ui_for_test.h
index 1654098..1b022b7 100644
--- a/chrome/test/media_router/media_router_cast_ui_for_test.h
+++ b/chrome/test/media_router/media_router_cast_ui_for_test.h
@@ -42,8 +42,6 @@
   void WaitForAnyRoute() override;
   void WaitForDialogShown() override;
   void WaitForDialogHidden() override;
-  void SetLocalFile(const GURL& file_url) override;
-  void SetLocalFileSelectionIssue(const IssueInfo& issue) override;
   void OnDialogCreated() override;
 
  private:
diff --git a/chrome/test/media_router/media_router_e2e_ui_browsertest.cc b/chrome/test/media_router/media_router_e2e_ui_browsertest.cc
index a40ddcf..2856388 100644
--- a/chrome/test/media_router/media_router_e2e_ui_browsertest.cc
+++ b/chrome/test/media_router/media_router_e2e_ui_browsertest.cc
@@ -16,53 +16,6 @@
 
 namespace media_router {
 
-// TODO(crbug.com/903016) Disabled due to flakiness.
-IN_PROC_BROWSER_TEST_P(MediaRouterE2EBrowserTest,
-                       DISABLED_OpenLocalMediaFileFullscreen) {
-  GURL file_url = ui_test_utils::GetTestUrl(
-      base::FilePath(base::FilePath::kCurrentDirectory),
-      base::FilePath(FILE_PATH_LITERAL("media/bigbuck.webm")));
-
-  // Start at a new tab, the file should open in the same tab.
-  ASSERT_TRUE(ui_test_utils::NavigateToURL(browser(),
-                                           GURL(chrome::kChromeUINewTabURL)));
-  // Make sure there is 1 tab.
-  ASSERT_EQ(1, browser()->tab_strip_model()->count());
-
-  content::WebContents* web_contents =
-      browser()->tab_strip_model()->GetActiveWebContents();
-
-  test_ui_->ShowDialog();
-  test_ui_->WaitForSinkAvailable(receiver_);
-
-  // Mock out file dialog operations, as those can't be simulated.
-  test_ui_->SetLocalFile(file_url);
-  // Click on the desired mode.
-  test_ui_->ChooseSourceType(CastDialogView::kLocalFile);
-  test_ui_->WaitForSinkAvailable(receiver_);
-  test_ui_->StartCasting(receiver_);
-
-  // Play the file for 10 seconds.
-  Wait(base::Seconds(10));
-
-  // Expect that the current tab has the file open in it.
-  ASSERT_EQ(file_url, web_contents->GetLastCommittedURL());
-
-  // Expect that fullscreen is active.
-  bool is_fullscreen = false;
-  std::string is_fullscreen_script =
-      "domAutomationController.send"
-      "(document.webkitCurrentFullScreenElement != null);";
-  CHECK(content::ExecuteScriptAndExtractBool(web_contents, is_fullscreen_script,
-                                             &is_fullscreen));
-
-  ASSERT_TRUE(is_fullscreen);
-  test_ui_->WaitForSink(receiver_);
-  test_ui_->StopCasting(receiver_);
-  // Wait 15s for Chromecast to back to home screen and ready to use status.
-  Wait(base::Seconds(15));
-}
-
 IN_PROC_BROWSER_TEST_P(MediaRouterE2EBrowserTest, MANUAL_MirrorHTML5Video) {
   MEDIA_ROUTER_INTEGRATION_BROWER_TEST_CAST_ONLY();
   content::WebContents* web_contents =
diff --git a/chrome/test/media_router/media_router_gmc_ui_for_test.cc b/chrome/test/media_router/media_router_gmc_ui_for_test.cc
index 5f08185..3f56865a 100644
--- a/chrome/test/media_router/media_router_gmc_ui_for_test.cc
+++ b/chrome/test/media_router/media_router_gmc_ui_for_test.cc
@@ -82,15 +82,6 @@
   NOTIMPLEMENTED();
 }
 
-void MediaRouterGmcUiForTest::SetLocalFile(const GURL& file_url) {
-  NOTIMPLEMENTED();
-}
-
-void MediaRouterGmcUiForTest::SetLocalFileSelectionIssue(
-    const IssueInfo& issue) {
-  NOTIMPLEMENTED();
-}
-
 MediaRouterGmcUiForTest::MediaRouterGmcUiForTest(
     content::WebContents* web_contents)
     : MediaRouterUiForTestBase(web_contents),
diff --git a/chrome/test/media_router/media_router_gmc_ui_for_test.h b/chrome/test/media_router/media_router_gmc_ui_for_test.h
index f1560f1..5a1dcea 100644
--- a/chrome/test/media_router/media_router_gmc_ui_for_test.h
+++ b/chrome/test/media_router/media_router_gmc_ui_for_test.h
@@ -45,8 +45,6 @@
   void WaitForAnyRoute() override;
   void WaitForDialogShown() override;
   void WaitForDialogHidden() override;
-  void SetLocalFile(const GURL& file_url) override;
-  void SetLocalFileSelectionIssue(const IssueInfo& issue) override;
 
  private:
   friend class content::WebContentsUserData<MediaRouterGmcUiForTest>;
diff --git a/chrome/test/media_router/media_router_integration_browsertest.cc b/chrome/test/media_router/media_router_integration_browsertest.cc
index e8cec315..bbf007e 100644
--- a/chrome/test/media_router/media_router_integration_browsertest.cc
+++ b/chrome/test/media_router/media_router_integration_browsertest.cc
@@ -20,7 +20,6 @@
 #include "chrome/browser/media/router/mojo/media_router_desktop.h"
 #include "chrome/browser/ui/browser_finder.h"
 #include "chrome/browser/ui/media_router/media_cast_mode.h"
-#include "chrome/browser/ui/media_router/media_router_file_dialog.h"
 #include "chrome/browser/ui/tabs/tab_strip_model.h"
 #include "chrome/browser/ui/views/frame/browser_view.h"
 #include "chrome/common/url_constants.h"
@@ -245,31 +244,6 @@
   return web_contents;
 }
 
-void MediaRouterIntegrationBrowserTest::OpenDialogAndCastFile() {
-  GURL file_url = net::FilePathToFileURL(
-      media::GetTestDataFilePath("butterfly-853x480.webm"));
-  test_ui_->ShowDialog();
-  // Mock out file dialog operations, as those can't be simulated.
-  test_ui_->SetLocalFile(file_url);
-  test_ui_->WaitForSink(receiver_);
-  test_ui_->ChooseSourceType(CastDialogView::kLocalFile);
-  ASSERT_EQ(CastDialogView::kLocalFile, test_ui_->GetChosenSourceType());
-  test_ui_->WaitForSinkAvailable(receiver_);
-  test_ui_->StartCasting(receiver_);
-  ASSERT_EQ(file_url, GetActiveWebContents()->GetVisibleURL());
-}
-
-void MediaRouterIntegrationBrowserTest::OpenDialogAndCastFileFails() {
-  GURL file_url =
-      net::FilePathToFileURL(media::GetTestDataFilePath("easy.webm"));
-  test_ui_->ShowDialog();
-  // Mock out file dialog operations, as those can't be simulated.
-  test_ui_->SetLocalFileSelectionIssue(IssueInfo());
-  test_ui_->WaitForSink(receiver_);
-  test_ui_->ChooseSourceType(CastDialogView::kLocalFile);
-  test_ui_->WaitForAnyIssue();
-}
-
 void MediaRouterIntegrationBrowserTest::OpenTestPage(
     base::FilePath::StringPieceType file_name) {
   base::FilePath full_path = GetResourceFile(file_name);
@@ -491,134 +465,6 @@
   RunBasicTest();
 }
 
-// Tests that creating a route with a local file opens the file in a new tab.
-//
-// This test was disabled because the test needs to wait until navigation is
-// complete before looking for the route, but it's not clear how to do that
-// without deadlocking the test.
-// This test passed locally when running with native test provider, so it
-// is updated to MANUAL and is allowed to run on private waterfall.
-IN_PROC_BROWSER_TEST_P(MediaRouterIntegrationBrowserTest,
-                       MANUAL_OpenLocalMediaFileInCurrentTab) {
-  MEDIA_ROUTER_INTEGRATION_BROWER_TEST_CAST_ONLY();
-  // Start at a new tab, the file should open in the same tab.
-  ASSERT_TRUE(ui_test_utils::NavigateToURL(browser(),
-                                           GURL(chrome::kChromeUINewTabURL)));
-  // Make sure there is 1 tab.
-  ASSERT_EQ(1, browser()->tab_strip_model()->count());
-
-  OpenDialogAndCastFile();
-
-  // Expect that no new tab has been opened.
-  ASSERT_EQ(1, browser()->tab_strip_model()->count());
-
-  // The dialog will close from navigating to the local file within the tab, so
-  // open it again after it closes.
-  test_ui_->WaitForDialogHidden();
-  test_ui_->ShowDialog();
-
-  // Wait for a route to be created.
-  test_ui_->WaitForAnyRoute();
-}
-
-// TODO(http://crbug.com/1095068): There maybe a crash on Linux and ChromeOS.
-#if defined(OS_LINUX) || defined(OS_CHROMEOS)
-#define MAYBE_OpenLocalMediaFileInNewTab MANUAL_OpenLocalMediaFileInNewTab
-#else
-#define MAYBE_OpenLocalMediaFileInNewTab OpenLocalMediaFileInNewTab
-#endif
-
-// Tests that creating a route with a local file opens the file in a new tab.
-IN_PROC_BROWSER_TEST_P(MediaRouterIntegrationBrowserTest,
-                       MAYBE_OpenLocalMediaFileInNewTab) {
-  MEDIA_ROUTER_INTEGRATION_BROWER_TEST_CAST_ONLY();
-  // Start at a tab with content in it, the file will open in a new tab.
-  ASSERT_TRUE(
-      ui_test_utils::NavigateToURL(browser(), GURL("https://google.com")));
-  // Make sure there is 1 tab.
-  ASSERT_EQ(1, browser()->tab_strip_model()->count());
-
-  OpenDialogAndCastFile();
-
-  // Expect that a new tab has been opened.
-  ASSERT_EQ(2, browser()->tab_strip_model()->count());
-
-  test_ui_->ShowDialog();
-
-  // Wait for a route to be created.
-  test_ui_->WaitForAnyRoute();
-}
-
-// Tests that failing to create a route with a local file shows an issue.
-// TODO(https://crbug.com/907539): Make the Views dialog show the issue.
-IN_PROC_BROWSER_TEST_P(MediaRouterIntegrationBrowserTest,
-                       DISABLED_OpenLocalMediaFileFailsAndShowsIssue) {
-  OpenDialogAndCastFileFails();
-  // Expect that the issue is showing.
-  ASSERT_TRUE(IsUIShowingIssue());
-}
-
-// Tests that creating a route with a local file opens in fullscreen.
-// TODO(https://crbug.com/903016) Disabled for being flaky in entering
-// fullscreen.
-IN_PROC_BROWSER_TEST_P(MediaRouterIntegrationBrowserTest,
-                       DISABLED_OpenLocalMediaFileFullscreen) {
-  // Start at a new tab, the file should open in the same tab.
-  ASSERT_TRUE(ui_test_utils::NavigateToURL(browser(),
-                                           GURL(chrome::kChromeUINewTabURL)));
-  // Make sure there is 1 tab.
-  ASSERT_EQ(1, browser()->tab_strip_model()->count());
-
-  OpenDialogAndCastFile();
-
-  // Increment web contents capturer count so it thinks capture has started.
-  // This will allow the file tab to go fullscreen.
-  content::WebContents* web_contents = GetActiveWebContents();
-  auto capture_handle =
-      web_contents->IncrementCapturerCount(gfx::Size(), /*stay_hidden=*/false,
-                                           /*stay_awake=*/true);
-
-  // Wait for capture poll timer to pick up change.
-  Wait(base::Seconds(3));
-
-  // Expect that fullscreen was entered.
-  ASSERT_TRUE(
-      web_contents->GetDelegate()->IsFullscreenForTabOrPending(web_contents));
-}
-
-// Flaky on MSan bots: http://crbug.com/879885
-#if defined(MEMORY_SANITIZER)
-#define MAYBE_OpenLocalMediaFileCastFailNoFullscreen \
-  MANUAL_OpenLocalMediaFileCastFailNoFullscreen
-#else
-#define MAYBE_OpenLocalMediaFileCastFailNoFullscreen \
-  OpenLocalMediaFileCastFailNoFullscreen
-#endif
-// Tests that failed route creation of local file does not enter fullscreen.
-IN_PROC_BROWSER_TEST_P(MediaRouterIntegrationBrowserTest,
-                       MAYBE_OpenLocalMediaFileCastFailNoFullscreen) {
-  MEDIA_ROUTER_INTEGRATION_BROWER_TEST_CAST_ONLY();
-  test_provider_->set_route_error_message("Unknown error");
-  // Start at a new tab, the file should open in the same tab.
-  ASSERT_TRUE(ui_test_utils::NavigateToURL(browser(),
-                                           GURL(chrome::kChromeUINewTabURL)));
-  // Make sure there is 1 tab.
-  ASSERT_EQ(1, browser()->tab_strip_model()->count());
-
-  OpenDialogAndCastFile();
-
-  // Wait for file to start playing (but not being captured).
-  Wait(base::Seconds(3));
-
-  // Expect no capture is ongoing.
-  content::WebContents* web_contents = GetActiveWebContents();
-  ASSERT_FALSE(web_contents->IsBeingCaptured());
-
-  // Expect that fullscreen is not entered.
-  ASSERT_FALSE(
-      web_contents->GetDelegate()->IsFullscreenForTabOrPending(web_contents));
-}
-
 // TODO(crbug.com/1238728): Test is flaky on Windows and Linux.
 #if defined(OS_LINUX) || defined(OS_WIN)
 #define MAYBE_SendAndOnMessage MANUAL_SendAndOnMessage
diff --git a/chrome/test/media_router/media_router_integration_browsertest.h b/chrome/test/media_router/media_router_integration_browsertest.h
index 7d2314cf..a413c2ad 100644
--- a/chrome/test/media_router/media_router_integration_browsertest.h
+++ b/chrome/test/media_router/media_router_integration_browsertest.h
@@ -116,17 +116,6 @@
   // |should_succeed| is true.
   virtual content::WebContents* StartSessionWithTestPageAndChooseSink();
 
-  // Opens the MR dialog and clicks through the motions of casting a
-  // file. Sets up the route provider to succeed or otherwise based on
-  // |route_success|. Note: The system dialog portion has to be mocked
-  // out as it cannot be simulated.
-  void OpenDialogAndCastFile();
-
-  // Opens the MR dialog and clicks through the motions of choosing to
-  // cast file, file returns an issue. Note: The system dialog portion
-  // has to be mocked out as it cannot be simulated.
-  void OpenDialogAndCastFileFails();
-
   void OpenTestPage(base::FilePath::StringPieceType file);
   void OpenTestPageInNewTab(base::FilePath::StringPieceType file);
   virtual GURL GetTestPageUrl(const base::FilePath& full_path);
diff --git a/chrome/test/media_router/media_router_ui_for_test_base.h b/chrome/test/media_router/media_router_ui_for_test_base.h
index 76d7521..6526888 100644
--- a/chrome/test/media_router/media_router_ui_for_test_base.h
+++ b/chrome/test/media_router/media_router_ui_for_test_base.h
@@ -56,11 +56,6 @@
   std::string GetStatusTextForSink(const std::string& sink_name) const;
   std::string GetIssueTextForSink(const std::string& sink_name) const;
 
-  // Sets up a mock file picker that returns |file_url| as the selected file.
-  virtual void SetLocalFile(const GURL& file_url) = 0;
-  // Sets up a mock file picker that fails with |issue|.
-  virtual void SetLocalFileSelectionIssue(const IssueInfo& issue) = 0;
-
   // Called by MediaRouterDialogControllerViews.
   virtual void OnDialogCreated();
 
diff --git a/chrome/test/v8/wasm_trap_handler_browsertest.cc b/chrome/test/v8/wasm_trap_handler_browsertest.cc
index f16210c..2092971 100644
--- a/chrome/test/v8/wasm_trap_handler_browsertest.cc
+++ b/chrome/test/v8/wasm_trap_handler_browsertest.cc
@@ -5,8 +5,9 @@
 // These tests focus on Wasm out of bounds behavior to make sure trap-based
 // bounds checks work when integrated with all of Chrome.
 
+#include <tuple>
+
 #include "base/base_switches.h"
-#include "base/ignore_result.h"
 #include "build/build_config.h"
 #include "chrome/browser/ui/browser.h"
 #include "chrome/browser/ui/tabs/tab_strip_model.h"
@@ -132,7 +133,7 @@
   // Sanitizers may prevent signal handler installation and thereby trap handler
   // setup. As there is no easy way to test if signal handler installation is
   // possible, we disable this test for sanitizers.
-  ignore_result(is_trap_handler_enabled);
+  std::ignore = is_trap_handler_enabled;
   return;
 #endif
 
diff --git a/chrome/utility/safe_browsing/mac/hfs_fuzzer.cc b/chrome/utility/safe_browsing/mac/hfs_fuzzer.cc
index 6ab1b80..c3764cb 100644
--- a/chrome/utility/safe_browsing/mac/hfs_fuzzer.cc
+++ b/chrome/utility/safe_browsing/mac/hfs_fuzzer.cc
@@ -6,9 +6,9 @@
 #include <stdint.h>
 
 #include <memory>
+#include <tuple>
 #include <vector>
 
-#include "base/ignore_result.h"
 #include "chrome/utility/safe_browsing/mac/hfs.h"
 #include "chrome/utility/safe_browsing/mac/read_stream.h"
 #include "testing/libfuzzer/libfuzzer_exports.h"
@@ -24,9 +24,9 @@
 
   while (hfs_iterator.Next()) {
     // Test accessing properties.
-    ignore_result(hfs_iterator.IsSymbolicLink());
-    ignore_result(hfs_iterator.IsDecmpfsCompressed());
-    ignore_result(hfs_iterator.GetPath());
+    std::ignore = hfs_iterator.IsSymbolicLink();
+    std::ignore = hfs_iterator.IsDecmpfsCompressed();
+    std::ignore = hfs_iterator.GetPath();
 
     if (hfs_iterator.IsDirectory() || hfs_iterator.IsHardLink())
       continue;
diff --git a/chromecast/browser/BUILD.gn b/chromecast/browser/BUILD.gn
index 16b530e..4b54bf4a 100644
--- a/chromecast/browser/BUILD.gn
+++ b/chromecast/browser/BUILD.gn
@@ -121,6 +121,8 @@
     "cast_content_gesture_handler.h",
     "cast_download_manager_delegate.cc",
     "cast_download_manager_delegate.h",
+    "cast_feature_update_observer.cc",
+    "cast_feature_update_observer.h",
     "cast_http_user_agent_settings.cc",
     "cast_http_user_agent_settings.h",
     "cast_media_blocker.cc",
diff --git a/chromecast/browser/cast_browser_main_parts.cc b/chromecast/browser/cast_browser_main_parts.cc
index eabc26f..507872f0 100644
--- a/chromecast/browser/cast_browser_main_parts.cc
+++ b/chromecast/browser/cast_browser_main_parts.cc
@@ -41,6 +41,7 @@
 #include "chromecast/browser/cast_content_browser_client.h"
 #include "chromecast/browser/cast_extension_url_loader_factory.h"
 #include "chromecast/browser/cast_feature_list_creator.h"
+#include "chromecast/browser/cast_feature_update_observer.h"
 #include "chromecast/browser/cast_system_memory_pressure_evaluator.h"
 #include "chromecast/browser/cast_system_memory_pressure_evaluator_adjuster.h"
 #include "chromecast/browser/cast_web_service.h"
@@ -769,6 +770,12 @@
 
   cast_browser_process_->cast_service()->Start();
 
+  if (base::CommandLine::ForCurrentProcess()->HasSwitch(
+          switches::kUseCastBrowserPrefConfig)) {
+    feature_update_observer_ = std::make_unique<CastFeatureUpdateObserver>(
+        connector(), cast_browser_process_->pref_service());
+  }
+
   return content::RESULT_CODE_NORMAL_EXIT;
 }
 
diff --git a/chromecast/browser/cast_browser_main_parts.h b/chromecast/browser/cast_browser_main_parts.h
index 9f02df6..d3b2f95 100644
--- a/chromecast/browser/cast_browser_main_parts.h
+++ b/chromecast/browser/cast_browser_main_parts.h
@@ -35,6 +35,7 @@
 #endif  // defined(USE_AURA)
 
 namespace chromecast {
+class CastFeatureUpdateObserver;
 class CastSystemMemoryPressureEvaluatorAdjuster;
 class CastWebService;
 class DisplaySettingsManager;
@@ -177,6 +178,8 @@
   std::unique_ptr<WaylandServerController> wayland_server_controller_;
 #endif
 
+  std::unique_ptr<CastFeatureUpdateObserver> feature_update_observer_;
+
 #if defined(USE_AURA) && !defined(OS_FUCHSIA)
   // Only used when running with --enable-ui-devtools.
   std::unique_ptr<CastUIDevTools> ui_devtools_;
diff --git a/chromecast/browser/cast_feature_update_observer.cc b/chromecast/browser/cast_feature_update_observer.cc
new file mode 100644
index 0000000..008cff2
--- /dev/null
+++ b/chromecast/browser/cast_feature_update_observer.cc
@@ -0,0 +1,52 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "chromecast/browser/cast_feature_update_observer.h"
+
+#include "base/bind.h"
+#include "base/check.h"
+#include "chromecast/base/pref_names.h"
+#include "chromecast/common/mojom/constants.mojom.h"
+#include "chromecast/external_mojo/external_service_support/external_connector.h"
+#include "components/prefs/pref_service.h"
+
+namespace chromecast {
+
+CastFeatureUpdateObserver::CastFeatureUpdateObserver(
+    external_service_support::ExternalConnector* connector,
+    PrefService* pref_service)
+    : connector_(connector), pref_service_(pref_service) {
+  DCHECK(connector_);
+  DCHECK(pref_service_);
+
+  BindFeatureUpdateService();
+}
+
+CastFeatureUpdateObserver::~CastFeatureUpdateObserver() = default;
+
+void CastFeatureUpdateObserver::BindFeatureUpdateService() {
+  feature_update_service_.reset();
+  receiver_.reset();
+  connector_->BindInterface(
+      mojom::kChromecastServiceName,
+      feature_update_service_.BindNewPipeAndPassReceiver());
+  feature_update_service_->RegisterFeatureUpdateObserver(
+      receiver_.BindNewPipeAndPassRemote());
+
+  // Right now we are in the process of making the `cast_service` manage the
+  // lifecycle of `cast_browser`. Until that is done, `cast_service` has a
+  // shorter lifecycle than `cast_browser`, so we need to handle disconnects
+  // here.
+  // TODO(crbug/1285360): remove once process lifecycles are inverted.
+  receiver_.set_disconnect_handler(
+      base::BindOnce(&CastFeatureUpdateObserver::BindFeatureUpdateService,
+                     base::Unretained(this)));
+}
+
+void CastFeatureUpdateObserver::OnFeaturesUpdated(base::Value features) {
+  pref_service_->Set(prefs::kLatestDCSFeatures, std::move(features));
+  pref_service_->CommitPendingWrite();
+}
+
+}  // namespace chromecast
diff --git a/chromecast/browser/cast_feature_update_observer.h b/chromecast/browser/cast_feature_update_observer.h
new file mode 100644
index 0000000..21d606f1
--- /dev/null
+++ b/chromecast/browser/cast_feature_update_observer.h
@@ -0,0 +1,47 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef CHROMECAST_BROWSER_CAST_FEATURE_UPDATE_OBSERVER_H_
+#define CHROMECAST_BROWSER_CAST_FEATURE_UPDATE_OBSERVER_H_
+
+#include "base/values.h"
+#include "chromecast/common/mojom/feature_update.mojom.h"
+#include "mojo/public/cpp/bindings/receiver.h"
+#include "mojo/public/cpp/bindings/remote.h"
+
+class PrefService;
+
+namespace chromecast {
+
+namespace external_service_support {
+class ExternalConnector;
+}  // namespace external_service_support
+
+class CastFeatureUpdateObserver
+    : public chromecast::mojom::FeatureUpdateObserver {
+ public:
+  CastFeatureUpdateObserver(
+      external_service_support::ExternalConnector* connector,
+      PrefService* pref_service);
+  CastFeatureUpdateObserver(const CastFeatureUpdateObserver&) = delete;
+  CastFeatureUpdateObserver& operator=(const CastFeatureUpdateObserver&) =
+      delete;
+  ~CastFeatureUpdateObserver() override;
+
+ private:
+  // chromecast::mojom::FeatureUpdateObserver implementation:
+  void OnFeaturesUpdated(base::Value features) override;
+
+  void BindFeatureUpdateService();
+
+  external_service_support::ExternalConnector* const connector_;
+  PrefService* const pref_service_;
+
+  mojo::Receiver<chromecast::mojom::FeatureUpdateObserver> receiver_{this};
+  mojo::Remote<chromecast::mojom::FeatureUpdateService> feature_update_service_;
+};
+
+}  // namespace chromecast
+
+#endif  // CHROMECAST_BROWSER_CAST_FEATURE_UPDATE_OBSERVER_H_
diff --git a/chromecast/common/mojom/BUILD.gn b/chromecast/common/mojom/BUILD.gn
index c4773a3..255fae0 100644
--- a/chromecast/common/mojom/BUILD.gn
+++ b/chromecast/common/mojom/BUILD.gn
@@ -15,6 +15,7 @@
     "cast_demo.mojom",
     "constants.mojom",
     "feature_manager.mojom",
+    "feature_update.mojom",
     "gesture.mojom",
     "identification_settings.mojom",
     "js_channel.mojom",
diff --git a/chromecast/common/mojom/feature_update.mojom b/chromecast/common/mojom/feature_update.mojom
new file mode 100644
index 0000000..1bb3ebd
--- /dev/null
+++ b/chromecast/common/mojom/feature_update.mojom
@@ -0,0 +1,23 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+module chromecast.mojom;
+
+import "mojo/public/mojom/base/values.mojom";
+
+// This interface is implemented by the clients of `FeatureUpdateService`.
+interface FeatureUpdateObserver {
+  // Triggered when there is an update to base::Feature configs because a
+  // DCS download is completed. `features` is a dictionary which is ready to be
+  // persisted to disk (via PrefService).
+  OnFeaturesUpdated(mojo_base.mojom.DictionaryValue features);
+};
+
+// This interface is implemented in the Cast Service process and allows the
+// observers to receive base::Feature state updates after base::Feature
+// overrides are downloaded successfully from the cloud service (DCS).
+interface FeatureUpdateService {
+  // Adds an observer to receive feature config updates.
+  RegisterFeatureUpdateObserver(pending_remote<FeatureUpdateObserver> observer);
+};
diff --git a/chromeos/CHROMEOS_LKGM b/chromeos/CHROMEOS_LKGM
index fc73a4d..20d0bdbc 100644
--- a/chromeos/CHROMEOS_LKGM
+++ b/chromeos/CHROMEOS_LKGM
@@ -1 +1 @@
-14436.0.0
\ No newline at end of file
+14443.0.0
\ No newline at end of file
diff --git a/chromeos/chromeos_strings.grd b/chromeos/chromeos_strings.grd
index 6029b9a..df7cab35 100644
--- a/chromeos/chromeos_strings.grd
+++ b/chromeos/chromeos_strings.grd
@@ -1959,6 +1959,15 @@
       <message name="IDS_PERSONALIZATION_APP_SET_AS_WALLPAPER" desc="Label for the button to confirm preview wallpaper">
         Set as wallpaper
       </message>
+      <message name="IDS_PERSONALIZATION_APP_THEME_LABEL" desc="Label for theme element in personalization hub">
+        Theme
+      </message>
+      <message name="IDS_PERSONALIZATION_APP_THEME_DARK_COLOR_MODE" desc="Label for dark color mode setting">
+        Dark
+      </message>
+      <message name="IDS_PERSONALIZATION_APP_THEME_LIGHT_COLOR_MODE" desc="Label for light color mode setting">
+        Light
+      </message>
 
       <!-- Traffic Counters UI -->
       <message name="IDS_TRAFFIC_COUNTERS_UNKNOWN" desc="Traffic counters related to an unknown source">
diff --git a/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_DARK_COLOR_MODE.png.sha1 b/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_DARK_COLOR_MODE.png.sha1
new file mode 100644
index 0000000..3123943
--- /dev/null
+++ b/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_DARK_COLOR_MODE.png.sha1
@@ -0,0 +1 @@
+df267d0c605415a09d35dd596bb1b1574148186c
\ No newline at end of file
diff --git a/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_LABEL.png.sha1 b/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_LABEL.png.sha1
new file mode 100644
index 0000000..3123943
--- /dev/null
+++ b/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_LABEL.png.sha1
@@ -0,0 +1 @@
+df267d0c605415a09d35dd596bb1b1574148186c
\ No newline at end of file
diff --git a/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_LIGHT_COLOR_MODE.png.sha1 b/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_LIGHT_COLOR_MODE.png.sha1
new file mode 100644
index 0000000..3123943
--- /dev/null
+++ b/chromeos/chromeos_strings_grd/IDS_PERSONALIZATION_APP_THEME_LIGHT_COLOR_MODE.png.sha1
@@ -0,0 +1 @@
+df267d0c605415a09d35dd596bb1b1574148186c
\ No newline at end of file
diff --git a/chromeos/dbus/fwupd/fwupd_client.cc b/chromeos/dbus/fwupd/fwupd_client.cc
index 9bcd331..7682587 100644
--- a/chromeos/dbus/fwupd/fwupd_client.cc
+++ b/chromeos/dbus/fwupd/fwupd_client.cc
@@ -101,8 +101,10 @@
     }
     writer.CloseContainer(&array_writer);
 
+  // TODO(michaelcheco): Investigate whether or not the estimated install time
+  // multiplied by some factor can be used in place of |TIMEOUT_INFINITE|.
     proxy_->CallMethodWithErrorResponse(
-        &method_call, dbus::ObjectProxy::TIMEOUT_USE_DEFAULT,
+        &method_call, dbus::ObjectProxy::TIMEOUT_INFINITE,
         base::BindOnce(&FwupdClientImpl::InstallUpdateCallback,
                        weak_ptr_factory_.GetWeakPtr()));
   }
diff --git a/chromeos/network/policy_applicator.cc b/chromeos/network/policy_applicator.cc
index 7d25520..bde95d0 100644
--- a/chromeos/network/policy_applicator.cc
+++ b/chromeos/network/policy_applicator.cc
@@ -309,13 +309,11 @@
       profile_, new_guid, &global_network_config_, new_policy_as_dict,
       user_settings);
 
-  if (features::IsESimPolicyEnabled()) {
-    // Copy over the value of ICCID and EID property from old entry to new shill
-    // properties since Shill requires ICCID and EID to create or update the
-    // existing service.
-    CopyRequiredCellularProperies(entry_properties_as_dict,
-                                  &new_shill_properties);
-  }
+  // Copy over the value of ICCID and EID property from old entry to new shill
+  // properties since Shill requires ICCID and EID to create or update the
+  // existing service.
+  CopyRequiredCellularProperies(entry_properties_as_dict,
+                                &new_shill_properties);
 
   // A new policy has to be applied to this profile entry. In order to keep
   // implicit state of Shill like "connected successfully before", keep the
diff --git a/components/app_restore/restore_data.cc b/components/app_restore/restore_data.cc
index d5477ba5..3b7ca26 100644
--- a/components/app_restore/restore_data.cc
+++ b/components/app_restore/restore_data.cc
@@ -17,38 +17,31 @@
 RestoreData::RestoreData() = default;
 
 RestoreData::RestoreData(std::unique_ptr<base::Value> restore_data_value) {
-  base::DictionaryValue* restore_data_dict = nullptr;
-  if (!restore_data_value || !restore_data_value->is_dict() ||
-      !restore_data_value->GetAsDictionary(&restore_data_dict) ||
-      !restore_data_dict) {
+  if (!restore_data_value || !restore_data_value->is_dict()) {
     DVLOG(0) << "Fail to parse full restore data. "
              << "Cannot find the full restore data dict.";
     return;
   }
 
-  for (base::DictionaryValue::Iterator iter(*restore_data_dict);
-       !iter.IsAtEnd(); iter.Advance()) {
-    const std::string& app_id = iter.key();
-    base::Value* value = restore_data_dict->FindDictKey(app_id);
-    base::DictionaryValue* data_dict = nullptr;
-    if (!value || !value->is_dict() || !value->GetAsDictionary(&data_dict) ||
-        !data_dict) {
+  for (auto iter : restore_data_value->DictItems()) {
+    const std::string& app_id = iter.first;
+    base::Value* value = restore_data_value->FindDictKey(app_id);
+    if (!value || !value->is_dict()) {
       DVLOG(0) << "Fail to parse full restore data. "
                << "Cannot find the app restore data dict.";
       continue;
     }
 
-    for (base::DictionaryValue::Iterator data_iter(*data_dict);
-         !data_iter.IsAtEnd(); data_iter.Advance()) {
+    for (auto data_iter : value->DictItems()) {
       int window_id = 0;
-      if (!base::StringToInt(data_iter.key(), &window_id)) {
+      if (!base::StringToInt(data_iter.first, &window_id)) {
         DVLOG(0) << "Fail to parse full restore data. "
                  << "Cannot find the valid id.";
         continue;
       }
       app_id_to_launch_list_[app_id][window_id] =
           std::make_unique<AppRestoreData>(
-              std::move(*data_dict->FindDictKey(data_iter.key())));
+              std::move(*value->FindDictKey(data_iter.first)));
     }
   }
 }
diff --git a/components/autofill/core/browser/BUILD.gn b/components/autofill/core/browser/BUILD.gn
index c812fc5..a5d0663 100644
--- a/components/autofill/core/browser/BUILD.gn
+++ b/components/autofill/core/browser/BUILD.gn
@@ -257,11 +257,14 @@
     "payments/payments_requests/select_challenge_option_request.h",
     "payments/payments_requests/unmask_card_request.cc",
     "payments/payments_requests/unmask_card_request.h",
+    "payments/payments_requests/update_virtual_card_enrollment_request.cc",
+    "payments/payments_requests/update_virtual_card_enrollment_request.h",
     "payments/payments_service_url.cc",
     "payments/payments_service_url.h",
     "payments/payments_util.cc",
     "payments/payments_util.h",
     "payments/risk_data_loader.h",
+    "payments/virtual_card_enrollment_flow.h",
     "payments/virtual_card_enrollment_manager.cc",
     "payments/virtual_card_enrollment_manager.h",
     "payments/wait_for_signal_or_timeout.cc",
diff --git a/components/autofill/core/browser/form_parsing/address_field.cc b/components/autofill/core/browser/form_parsing/address_field.cc
index a6a0d82..c41bd6e 100644
--- a/components/autofill/core/browser/form_parsing/address_field.cc
+++ b/components/autofill/core/browser/form_parsing/address_field.cc
@@ -28,6 +28,35 @@
   return true;
 }
 
+// Removes the |attribute| from all |patterns|.
+// TODO(crbug/1142936): This is necessary for
+// AddressField::ParseNameAndLabelSeparately().
+int WithoutAttribute(int match_type, MatchAttributes attribute) {
+  return match_type & ~attribute;
+}
+
+// Removes the |attribute| from all |patterns|.
+// TODO(crbug/1142936): This is necessary for
+// AddressField::ParseNameAndLabelSeparately().
+std::vector<MatchingPattern> WithoutAttribute(
+    std::vector<MatchingPattern> patterns,
+    MatchAttributes attribute) {
+  for (MatchingPattern& p : patterns)
+    p.match_field_attributes &= ~attribute;
+  return patterns;
+}
+
+// Adds the |field_type| to all |patterns|.
+// TODO(crbug/1142936): This is necessary for AddressField::ParseAddressLines()
+// and AddressField::Parse().
+std::vector<MatchingPattern> WithFieldType(
+    std::vector<MatchingPattern> patterns,
+    MatchFieldTypes field_type) {
+  for (MatchingPattern& p : patterns)
+    p.match_field_input_types |= field_type;
+  return patterns;
+}
+
 }  // namespace
 
 // Some sites use type="tel" for zip fields (to get a numerical input).
@@ -90,8 +119,8 @@
       // Ignore email addresses.
     } else if (ParseFieldSpecifics(
                    scanner, kEmailRe, MATCH_DEFAULT | MATCH_TEXT_AREA,
-                   email_patterns, nullptr, {log_manager, "kEmailRe"},
-                   {.augment_types = MATCH_TEXT_AREA})) {
+                   WithFieldType(email_patterns, MATCH_TEXT_AREA), nullptr,
+                   {log_manager, "kEmailRe"})) {
       continue;
     } else if (address_field->ParseAddress(scanner, page_language) ||
                address_field->ParseDependentLocalityCityStateCountryZipCode(
@@ -298,6 +327,10 @@
       PatternProvider::GetInstance().GetMatchPatterns("ADDRESS_LINE_1",
                                                       page_language);
 
+  // TODO(crbug.com/1121990): Remove duplicate calls when launching
+  // AutofillParsingPatternProvider. The old code calls ParseFieldSpecifics()
+  // for two different patterns, |pattern| and |label_pattern|. The new code
+  // handles both patterns at once in the |address_line1_patterns|.
   if (!ParseFieldSpecifics(scanner, pattern, MATCH_DEFAULT | MATCH_SEARCH,
                            address_line1_patterns, &address1_,
                            {log_manager_, "kAddressLine1Re"}) &&
@@ -305,17 +338,16 @@
                            MATCH_LABEL | MATCH_SEARCH | MATCH_TEXT,
                            address_line1_patterns, &address1_,
                            {log_manager_, "kAddressLine1LabelRe"}) &&
-      !ParseFieldSpecifics(scanner, pattern,
-                           MATCH_DEFAULT | MATCH_SEARCH | MATCH_TEXT_AREA,
-                           address_line1_patterns, &street_address_,
-                           {log_manager_, "kAddressLine1Re"},
-                           {.augment_types = MATCH_TEXT_AREA}) &&
-      !ParseFieldSpecifics(scanner, label_pattern,
-                           MATCH_LABEL | MATCH_SEARCH | MATCH_TEXT_AREA,
-                           address_line1_patterns, &street_address_,
-                           {log_manager_, "kAddressLine1LabelRe"},
-                           {.augment_types = MATCH_TEXT_AREA}))
+      !ParseFieldSpecifics(
+          scanner, pattern, MATCH_DEFAULT | MATCH_SEARCH | MATCH_TEXT_AREA,
+          WithFieldType(address_line1_patterns, MATCH_TEXT_AREA),
+          &street_address_, {log_manager_, "kAddressLine1Re"}) &&
+      !ParseFieldSpecifics(
+          scanner, label_pattern, MATCH_LABEL | MATCH_SEARCH | MATCH_TEXT_AREA,
+          WithFieldType(address_line1_patterns, MATCH_TEXT_AREA),
+          &street_address_, {log_manager_, "kAddressLine1LabelRe"})) {
     return false;
+  }
 
   if (street_address_)
     return true;
@@ -348,8 +380,9 @@
                   {log_manager_, "kAddressLinesExtraRe"}) &&
       !ParseFieldSpecifics(scanner, label_pattern, MATCH_LABEL | MATCH_TEXT,
                            address_line2_patterns, &address3_,
-                           {log_manager_, "kAddressLine2LabelRe"}))
+                           {log_manager_, "kAddressLine2LabelRe"})) {
     return true;
+  }
 
   // Try for surplus lines, which we will promptly discard. Some pages have 4
   // address lines (e.g. uk/ShoesDirect2.html)!
@@ -469,12 +502,12 @@
   AutofillField* cur_match = nullptr;
   size_t saved_cursor = scanner->SaveCursor();
   bool parsed_name = ParseFieldSpecifics(
-      scanner, pattern, match_type & ~MATCH_LABEL, patterns, &cur_match,
-      logging, {.restrict_attributes = MATCH_NAME});
+      scanner, pattern, WithoutAttribute(match_type, MATCH_LABEL),
+      WithoutAttribute(patterns, MATCH_LABEL), &cur_match, logging);
   scanner->RewindTo(saved_cursor);
   bool parsed_label = ParseFieldSpecifics(
-      scanner, pattern, match_type & ~MATCH_NAME, patterns, &cur_match, logging,
-      {.restrict_attributes = MATCH_LABEL});
+      scanner, pattern, WithoutAttribute(match_type, MATCH_NAME),
+      WithoutAttribute(patterns, MATCH_NAME), &cur_match, logging);
   if (parsed_name && parsed_label) {
     if (match)
       *match = cur_match;
diff --git a/components/autofill/core/browser/form_parsing/form_field.cc b/components/autofill/core/browser/form_parsing/form_field.cc
index eb0cbe3..3350480 100644
--- a/components/autofill/core/browser/form_parsing/form_field.cc
+++ b/components/autofill/core/browser/form_parsing/form_field.cc
@@ -277,20 +277,8 @@
     int match_type,
     const std::vector<MatchingPattern>& patterns,
     AutofillField** match,
-    const RegExLogging& logging,
-    MatchFieldBitmasks match_field_bitmasks) {
+    const RegExLogging& logging) {
   if (base::FeatureList::IsEnabled(features::kAutofillParsingPatternProvider)) {
-    // TODO(crbug/1142936): This hack is to allow
-    // AddressField::ParseNameAndLabelSeparately().
-    if (match_field_bitmasks.restrict_attributes != ~0 ||
-        match_field_bitmasks.augment_types != 0) {
-      std::vector<MatchingPattern> modified_patterns = patterns;
-      for (MatchingPattern& mp : modified_patterns) {
-        mp.match_field_attributes &= match_field_bitmasks.restrict_attributes;
-        mp.match_field_input_types |= match_field_bitmasks.augment_types;
-      }
-      return ParseFieldSpecifics(scanner, modified_patterns, match, logging);
-    }
     return ParseFieldSpecifics(scanner, patterns, match, logging);
   } else {
     return ParseFieldSpecificsWithLegacyPattern(scanner, pattern, match_type,
diff --git a/components/autofill/core/browser/form_parsing/form_field.h b/components/autofill/core/browser/form_parsing/form_field.h
index 4c4c86ff..33f3906b 100644
--- a/components/autofill/core/browser/form_parsing/form_field.h
+++ b/components/autofill/core/browser/form_parsing/form_field.h
@@ -127,20 +127,12 @@
       AutofillField** match,
       const RegExLogging& logging = {});
 
-  struct MatchFieldBitmasks {
-    int restrict_attributes = ~0;
-    int augment_types = 0;
-  };
-
   static bool ParseFieldSpecifics(AutofillScanner* scanner,
                                   base::StringPiece16 pattern,
                                   int match_type,
                                   const std::vector<MatchingPattern>& patterns,
                                   AutofillField** match,
-                                  const RegExLogging& logging,
-                                  MatchFieldBitmasks match_field_bitmasks = {
-                                      .restrict_attributes = ~0,
-                                      .augment_types = 0});
+                                  const RegExLogging& logging);
 
   // Attempts to parse a field with an empty label.  Returns true
   // on success and fills |match| with a pointer to the field.
diff --git a/components/autofill/core/browser/payments/payments_client.cc b/components/autofill/core/browser/payments/payments_client.cc
index d3258e9..a3e947f 100644
--- a/components/autofill/core/browser/payments/payments_client.cc
+++ b/components/autofill/core/browser/payments/payments_client.cc
@@ -30,6 +30,7 @@
 #include "components/autofill/core/browser/payments/payments_requests/payments_request.h"
 #include "components/autofill/core/browser/payments/payments_requests/select_challenge_option_request.h"
 #include "components/autofill/core/browser/payments/payments_requests/unmask_card_request.h"
+#include "components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.h"
 #include "components/autofill/core/browser/payments/payments_service_url.h"
 #include "components/autofill/core/common/autofill_features.h"
 #include "components/autofill/core/common/autofill_payments_features.h"
@@ -968,6 +969,14 @@
 PaymentsClient::GetDetailsForEnrollmentResponseDetails::
     ~GetDetailsForEnrollmentResponseDetails() = default;
 
+PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails::
+    UpdateVirtualCardEnrollmentRequestDetails() = default;
+PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails::
+    UpdateVirtualCardEnrollmentRequestDetails(
+        const UpdateVirtualCardEnrollmentRequestDetails&) = default;
+PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails::
+    ~UpdateVirtualCardEnrollmentRequestDetails() = default;
+
 PaymentsClient::PaymentsClient(
     scoped_refptr<network::SharedURLLoaderFactory> url_loader_factory,
     signin::IdentityManager* identity_manager,
@@ -1068,6 +1077,14 @@
                /*authenticate=*/true);
 }
 
+void PaymentsClient::UpdateVirtualCardEnrollment(
+    const UpdateVirtualCardEnrollmentRequestDetails& request_details,
+    base::OnceCallback<void(AutofillClient::PaymentsRpcResult)> callback) {
+  IssueRequest(std::make_unique<UpdateVirtualCardEnrollmentRequest>(
+                   request_details, std::move(callback)),
+               /*authenticate=*/true);
+}
+
 void PaymentsClient::CancelRequest() {
   request_.reset();
   resource_request_.reset();
diff --git a/components/autofill/core/browser/payments/payments_client.h b/components/autofill/core/browser/payments/payments_client.h
index a7252e5..85a4eba47 100644
--- a/components/autofill/core/browser/payments/payments_client.h
+++ b/components/autofill/core/browser/payments/payments_client.h
@@ -20,6 +20,7 @@
 #include "components/autofill/core/browser/data_model/credit_card.h"
 #include "components/autofill/core/browser/payments/card_unmask_challenge_option.h"
 #include "components/autofill/core/browser/payments/card_unmask_delegate.h"
+#include "components/autofill/core/browser/payments/virtual_card_enrollment_flow.h"
 #include "components/signin/public/identity_manager/access_token_fetcher.h"
 #include "components/signin/public/identity_manager/access_token_info.h"
 #include "google_apis/gaia/google_service_auth_error.h"
@@ -109,7 +110,7 @@
     // An opaque token used to chain consecutive payments requests together.
     std::string context_token;
     // The url origin of the website where the unmasking happened. Should be
-    // populated when the unmasking is for a virtual card.
+    // populated when the unmasking is for a virtual-card.
     absl::optional<GURL> last_committed_url_origin;
   };
 
@@ -133,11 +134,11 @@
     std::string real_pan;
     std::string dcvv;
     // The expiration month of the card. It falls in between 1 - 12. Should be
-    // populated when the card is a virtual card which does not necessarily have
+    // populated when the card is a virtual-card which does not necessarily have
     // the same expiration date as its related actual card.
     std::string expiration_month;
     // The four-digit expiration year of the card. Should be populated when the
-    // card is a virtual card which does not necessarily have the same
+    // card is a virtual-card which does not necessarily have the same
     // expiration date as its related actual card.
     std::string expiration_year;
     // Challenge required for enrolling user into FIDO authentication for future
@@ -285,7 +286,42 @@
     std::string server_id;
     // TODO(crbug.com/1281695): Add |virtual_card_enrollment_state| and
     //   |card_art_url| data members when integrating all of the logic for the
-    //   virtual card enrollment flow.
+    //   virtual-card enrollment flow.
+  };
+
+  // A collection of information needed for the
+  // UpdateVirtualCardEnrollmentRequest.
+  struct UpdateVirtualCardEnrollmentRequestDetails {
+    UpdateVirtualCardEnrollmentRequestDetails();
+    UpdateVirtualCardEnrollmentRequestDetails(
+        const UpdateVirtualCardEnrollmentRequestDetails&);
+    UpdateVirtualCardEnrollmentRequestDetails operator=(
+        const UpdateVirtualCardEnrollmentRequestDetails&) = delete;
+    ~UpdateVirtualCardEnrollmentRequestDetails();
+    // Denotes the source that the corresponding
+    // UpdateVirtualCardEnrollmentRequest for this
+    // UpdateVirtualCardEnrollmentRequestDetails originated from, i.e., a
+    // |virtual_card_enrollment_source| of kUpstream means the request happens
+    // after a user saved a card in the upstream flow.
+    VirtualCardEnrollmentSource virtual_card_enrollment_source =
+        VirtualCardEnrollmentSource::kNone;
+    // Denotes the type of this specific UpdateVirtualCardEnrollmentRequest,
+    // i.e., a type of VirtualCardEnrollmentRequestType::kEnroll would mean this
+    // is an enroll request.
+    VirtualCardEnrollmentRequestType virtual_card_enrollment_request_type =
+        VirtualCardEnrollmentRequestType::kNone;
+    // The billing customer number for the account this request is sent to. If
+    // |billing_customer_number| is non-zero, it means the user has a Google
+    // Payments account.
+    int64_t billing_customer_number = 0;
+    // Populated if it is an unenroll request. |instrument_id| lets the server
+    // know which card to unenroll from VCN.
+    absl::optional<int64_t> instrument_id;
+    // Populated if it is an enroll request. Based on the |vcn_context_token|
+    // the server is able to retrieve the instrument id, and using
+    // |vcn_context_token| for enroll allows the server to link a
+    // GetDetailsForEnroll call with the corresponding Enroll call.
+    absl::optional<std::string> vcn_context_token;
   };
 
   // TODO(crbug.com/1281695): Add GetDetailsForEnrollRequest.
@@ -303,10 +339,10 @@
     // and link this specific GetDetailsForEnroll call with its corresponding
     // enroll call.
     std::string vcn_context_token;
-    // Google's legal message lines in the virtual card enroll flow for this
+    // Google's legal message lines in the virtual-card enroll flow for this
     // specific card based on |vcn_context_token|.
     LegalMessageLines google_legal_message;
-    // The issuer's legal message lines in the virtual card enroll flow for this
+    // The issuer's legal message lines in the virtual-card enroll flow for this
     // specific card based on |vcn_context_token|.
     LegalMessageLines issuer_legal_message;
   };
@@ -402,6 +438,14 @@
       base::OnceCallback<void(AutofillClient::PaymentsRpcResult,
                               const std::string&)> callback);
 
+  // The user has chosen to change the virtual-card enrollment of a credit card.
+  // Send the necessary information for the server to identify the credit card
+  // for which virtual-card enrollment will be updated, as well as metadata so
+  // that the server understands the context for the request.
+  virtual void UpdateVirtualCardEnrollment(
+      const UpdateVirtualCardEnrollmentRequestDetails& request_details,
+      base::OnceCallback<void(AutofillClient::PaymentsRpcResult)> callback);
+
   // Cancels and clears the current |request_|.
   void CancelRequest();
 
diff --git a/components/autofill/core/browser/payments/payments_client_unittest.cc b/components/autofill/core/browser/payments/payments_client_unittest.cc
index 6f71767..b48076b 100644
--- a/components/autofill/core/browser/payments/payments_client_unittest.cc
+++ b/components/autofill/core/browser/payments/payments_client_unittest.cc
@@ -23,6 +23,7 @@
 #include "components/autofill/core/browser/payments/credit_card_save_manager.h"
 #include "components/autofill/core/browser/payments/local_card_migration_manager.h"
 #include "components/autofill/core/browser/payments/payments_client.h"
+#include "components/autofill/core/browser/payments/virtual_card_enrollment_flow.h"
 #include "components/autofill/core/browser/test_personal_data_manager.h"
 #include "components/autofill/core/common/autofill_clock.h"
 #include "components/autofill/core/common/autofill_features.h"
@@ -224,6 +225,11 @@
     context_token_ = updated_context_token;
   }
 
+  void OnDidGetUpdateVirtualCardEnrollmentResponse(
+      AutofillClient::PaymentsRpcResult result) {
+    result_ = result;
+  }
+
  protected:
   base::test::ScopedFeatureList scoped_feature_list_;
 
@@ -1597,5 +1603,129 @@
   EXPECT_EQ(AutofillClient::PaymentsRpcResult::kPermanentFailure, result_);
 }
 
+typedef std::tuple<VirtualCardEnrollmentSource,
+                   VirtualCardEnrollmentRequestType,
+                   AutofillClient::PaymentsRpcResult>
+    UpdateVirtualCardEnrollmentTestData;
+
+class UpdateVirtualCardEnrollmentTest
+    : public PaymentsClientTest,
+      public ::testing::WithParamInterface<
+          UpdateVirtualCardEnrollmentTestData> {
+ public:
+  UpdateVirtualCardEnrollmentTest() = default;
+  ~UpdateVirtualCardEnrollmentTest() override = default;
+
+  void TriggerFlow() {
+    VirtualCardEnrollmentSource virtual_card_enrollment_source =
+        std::get<0>(GetParam());
+    VirtualCardEnrollmentRequestType virtual_card_enrollment_request_type =
+        std::get<1>(GetParam());
+    StartUpdateVirtualCardEnrollment(virtual_card_enrollment_source,
+                                     virtual_card_enrollment_request_type);
+    IssueOAuthToken();
+
+    // |response_type_for_test| is the AutofillClient::PaymentsRpcResult
+    // response type we want to test for the combination of
+    // |virtual_card_enrollment_source| and
+    // |virtual_card_enrollment_request_type| we are currently on.
+    AutofillClient::PaymentsRpcResult response_type_for_test =
+        std::get<2>(GetParam());
+    switch (response_type_for_test) {
+      case AutofillClient::PaymentsRpcResult::kSuccess:
+        if (virtual_card_enrollment_request_type ==
+            VirtualCardEnrollmentRequestType::kEnroll) {
+          ReturnResponse(net::HTTP_OK,
+                         "{ \"enroll_result\": \"ENROLL_SUCCESS\" }");
+        } else if (virtual_card_enrollment_request_type ==
+                   VirtualCardEnrollmentRequestType::kUnenroll) {
+          ReturnResponse(net::HTTP_OK, "{}");
+        }
+        break;
+      case AutofillClient::PaymentsRpcResult::kVcnRetrievalTryAgainFailure:
+        ReturnResponse(
+            net::HTTP_OK,
+            "{ \"error\": { \"code\": \"ANYTHING_ELSE\", "
+            "\"api_error_reason\": \"virtual_card_temporary_error\"} }");
+        break;
+      case AutofillClient::PaymentsRpcResult::kTryAgainFailure:
+        ReturnResponse(net::HTTP_OK,
+                       "{ \"error\": { \"code\": \"INTERNAL\", "
+                       "\"api_error_reason\": \"ANYTHING_ELSE\"} }");
+        break;
+      case AutofillClient::PaymentsRpcResult::kVcnRetrievalPermanentFailure:
+        ReturnResponse(
+            net::HTTP_OK,
+            "{ \"error\": { \"code\": \"ANYTHING_ELSE\", "
+            "\"api_error_reason\": \"virtual_card_permanent_error\"} }");
+        break;
+      case AutofillClient::PaymentsRpcResult::kPermanentFailure:
+        ReturnResponse(net::HTTP_OK,
+                       "{ \"error\": { \"code\": \"ANYTHING_ELSE\" } }");
+        break;
+      case AutofillClient::PaymentsRpcResult::kNetworkError:
+        ReturnResponse(net::HTTP_REQUEST_TIMEOUT, "");
+        break;
+      case AutofillClient::PaymentsRpcResult::kNone:
+        NOTREACHED();
+        break;
+    }
+    EXPECT_EQ(response_type_for_test, result_);
+  }
+
+ private:
+  void StartUpdateVirtualCardEnrollment(
+      VirtualCardEnrollmentSource virtual_card_enrollment_source,
+      VirtualCardEnrollmentRequestType virtual_card_enrollment_request_type) {
+    PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails request_details;
+    request_details.virtual_card_enrollment_request_type =
+        virtual_card_enrollment_request_type;
+    request_details.virtual_card_enrollment_source =
+        virtual_card_enrollment_source;
+    request_details.billing_customer_number = 555666777888;
+    if (virtual_card_enrollment_request_type ==
+        VirtualCardEnrollmentRequestType::kEnroll) {
+      request_details.vcn_context_token = "fake context token";
+    } else if (virtual_card_enrollment_request_type ==
+               VirtualCardEnrollmentRequestType::kUnenroll) {
+      request_details.instrument_id = 12345678;
+    }
+    client_->UpdateVirtualCardEnrollment(
+        request_details,
+        base::BindOnce(
+            &PaymentsClientTest::OnDidGetUpdateVirtualCardEnrollmentResponse,
+            weak_ptr_factory_.GetWeakPtr()));
+  }
+};
+
+// Initializes the parameterized test suite with all possible values of
+// VirtualCardEnrollmentSource, VirtualCardEnrollmentRequestType, and
+// AutofillClient::PaymentsRpcResult.
+INSTANTIATE_TEST_SUITE_P(
+    ,
+    UpdateVirtualCardEnrollmentTest,
+    testing::Combine(
+        testing::Values(VirtualCardEnrollmentSource::kUpstream,
+                        VirtualCardEnrollmentSource::kDownstream,
+                        VirtualCardEnrollmentSource::kSettingsPage),
+        testing::Values(VirtualCardEnrollmentRequestType::kEnroll,
+                        VirtualCardEnrollmentRequestType::kUnenroll),
+        testing::Values(
+            AutofillClient::PaymentsRpcResult::kSuccess,
+            AutofillClient::PaymentsRpcResult::kVcnRetrievalTryAgainFailure,
+            AutofillClient::PaymentsRpcResult::kTryAgainFailure,
+            AutofillClient::PaymentsRpcResult::kVcnRetrievalPermanentFailure,
+            AutofillClient::PaymentsRpcResult::kPermanentFailure,
+            AutofillClient::PaymentsRpcResult::kNetworkError)));
+
+// Parameterized test that tests all combinations of
+// VirtualCardEnrollmentSource and VirtualCardEnrollmentRequestType against all
+// possible server responses in the UpdateVirtualCardEnrollmentFlow. This test
+// will be run once for each combination.
+TEST_P(UpdateVirtualCardEnrollmentTest,
+       UpdateVirtualCardEnrollmentTest_TestAllFlows) {
+  TriggerFlow();
+}
+
 }  // namespace payments
 }  // namespace autofill
diff --git a/components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.cc b/components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.cc
new file mode 100644
index 0000000..fc0b87d
--- /dev/null
+++ b/components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.cc
@@ -0,0 +1,181 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.h"
+
+#include <string>
+
+#include "base/json/json_writer.h"
+#include "base/values.h"
+#include "components/autofill/core/browser/payments/virtual_card_enrollment_flow.h"
+
+namespace autofill {
+namespace payments {
+
+namespace {
+const char kUpdateVirtualCardEnrollmentRequestPath[] =
+    "payments/apis/virtualcardservice/enroll";
+}  // namespace
+
+UpdateVirtualCardEnrollmentRequest::UpdateVirtualCardEnrollmentRequest(
+    const PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails&
+        request_details,
+    base::OnceCallback<void(AutofillClient::PaymentsRpcResult)> callback)
+    : request_details_(request_details), callback_(std::move(callback)) {}
+
+UpdateVirtualCardEnrollmentRequest::~UpdateVirtualCardEnrollmentRequest() =
+    default;
+
+std::string UpdateVirtualCardEnrollmentRequest::GetRequestUrlPath() {
+  return kUpdateVirtualCardEnrollmentRequestPath;
+}
+
+std::string UpdateVirtualCardEnrollmentRequest::GetRequestContentType() {
+  return "application/json";
+}
+
+std::string UpdateVirtualCardEnrollmentRequest::GetRequestContent() {
+  base::Value request_dict(base::Value::Type::DICTIONARY);
+
+  switch (request_details_.virtual_card_enrollment_request_type) {
+    case VirtualCardEnrollmentRequestType::kEnroll:
+      BuildEnrollRequestDictionary(&request_dict);
+      break;
+    case VirtualCardEnrollmentRequestType::kUnenroll:
+      BuildUnenrollRequestDictionary(&request_dict);
+      break;
+    case VirtualCardEnrollmentRequestType::kNone:
+      NOTREACHED();
+      break;
+  }
+
+  std::string request_content;
+  base::JSONWriter::Write(request_dict, &request_content);
+  VLOG(3) << "UpdateVirtualCardEnrollmentRequest Body: " << request_content;
+  return request_content;
+}
+
+void UpdateVirtualCardEnrollmentRequest::ParseResponse(
+    const base::Value& response) {
+  // Only enroll requests have a response to parse, unenroll request responses
+  // are empty except for possible errors which are parsed in PaymentsClient.
+  if (request_details_.virtual_card_enrollment_request_type ==
+      VirtualCardEnrollmentRequestType::kEnroll) {
+    auto* enroll_result =
+        response.FindKeyOfType("enroll_result", base::Value::Type::STRING);
+    if (enroll_result) {
+      enroll_result_ = enroll_result->GetString();
+    }
+  }
+}
+
+bool UpdateVirtualCardEnrollmentRequest::IsResponseComplete() {
+  switch (request_details_.virtual_card_enrollment_request_type) {
+    case VirtualCardEnrollmentRequestType::kEnroll:
+      // If it is an enroll request, we know the response is complete if the
+      // response has an enroll result that is ENROLL_SUCCESS, as that is the
+      // only field in an enroll response other than the possible error.
+      return enroll_result_.has_value() && enroll_result_ == "ENROLL_SUCCESS";
+    case VirtualCardEnrollmentRequestType::kUnenroll:
+      // Unenroll responses are empty except for having an error. In
+      // PaymentsClient, if the response has an error it will be handled before
+      // we check IsResponseComplete(), so if we ever reach this branch we know
+      // the response completed successfully as there is no error. Thus, we
+      // always return true.
+      return true;
+    case VirtualCardEnrollmentRequestType::kNone:
+      NOTREACHED();
+      return false;
+  }
+}
+
+void UpdateVirtualCardEnrollmentRequest::RespondToDelegate(
+    AutofillClient::PaymentsRpcResult result) {
+  std::move(callback_).Run(result);
+}
+
+void UpdateVirtualCardEnrollmentRequest::BuildEnrollRequestDictionary(
+    base::Value* request_dict) {
+  DCHECK(request_details_.virtual_card_enrollment_request_type ==
+         VirtualCardEnrollmentRequestType::kEnroll);
+
+  // If it is an enroll request, we should always have a context token from the
+  // previous GetDetailsForEnroll request and we should not have an instrument
+  // id set in |request_details_|.
+  DCHECK(request_details_.vcn_context_token.has_value() &&
+         !request_details_.instrument_id.has_value());
+
+  // Builds the context and channel_type for this enroll request.
+  base::Value context(base::Value::Type::DICTIONARY);
+  switch (request_details_.virtual_card_enrollment_source) {
+    case VirtualCardEnrollmentSource::kUpstream:
+      context.SetKey("billable_service",
+                     base::Value(kUploadCardBillableServiceNumber));
+      request_dict->SetKey("channel_type", base::Value("CHROME_UPSTREAM"));
+      break;
+    case VirtualCardEnrollmentSource::kDownstream:
+      // Downstream enroll is treated the same as settings page enroll because
+      // chrome client should already have a card synced from the server.
+      // Fall-through.
+    case VirtualCardEnrollmentSource::kSettingsPage:
+      context.SetKey("billable_service",
+                     base::Value(kUnmaskCardBillableServiceNumber));
+      request_dict->SetKey("channel_type", base::Value("CHROME_DOWNSTREAM"));
+      break;
+    case VirtualCardEnrollmentSource::kNone:
+      NOTREACHED();
+      break;
+  }
+  if (request_details_.billing_customer_number != 0) {
+    context.SetKey("customer_context",
+                   BuildCustomerContextDictionary(
+                       request_details_.billing_customer_number));
+  }
+  request_dict->SetKey("context", std::move(context));
+
+  // Sets the virtual_card_enrollment_flow field in this enroll request which
+  // lets the server know whether the enrollment is happening with ToS or not.
+  // Chrome client requests will always be ENROLL_WITH_TOS. This field is
+  // necessary because virtual card enroll through other platforms enrolls
+  // without ToS, for example Web Push Provisioning.
+  request_dict->SetKey("virtual_card_enrollment_flow",
+                       base::Value("ENROLL_WITH_TOS"));
+
+  // Sets the context_token field in this enroll request which is used by the
+  // server to link this enroll request to the previous
+  // GetDetailsForEnrollRequest, as well as to retrieve the specific credit card
+  // to enroll.
+  request_dict->SetKey("context_token",
+                       base::Value(request_details_.vcn_context_token.value()));
+}
+
+void UpdateVirtualCardEnrollmentRequest::BuildUnenrollRequestDictionary(
+    base::Value* request_dict) {
+  DCHECK(request_details_.virtual_card_enrollment_request_type ==
+         VirtualCardEnrollmentRequestType::kUnenroll);
+
+  // If it is an unenroll request, we should always have an instrument id and we
+  // should not have a context token set in |request_details_|.
+  DCHECK(request_details_.instrument_id.has_value() &&
+         !request_details_.vcn_context_token.has_value());
+
+  // Builds the context for this unenroll request if a billing customer number
+  // is present.
+  if (request_details_.billing_customer_number != 0) {
+    base::Value context(base::Value::Type::DICTIONARY);
+    context.SetKey("customer_context",
+                   BuildCustomerContextDictionary(
+                       request_details_.billing_customer_number));
+    request_dict->SetKey("context", std::move(context));
+  }
+
+  // Sets the instrument_id field in this unenroll request which is used by
+  // the server to get the appropriate credit card to unenroll.
+  request_dict->SetKey("instrument_id",
+                       base::Value(base::NumberToString(
+                           request_details_.instrument_id.value())));
+}
+
+}  // namespace payments
+}  // namespace autofill
diff --git a/components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.h b/components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.h
new file mode 100644
index 0000000..4438448
--- /dev/null
+++ b/components/autofill/core/browser/payments/payments_requests/update_virtual_card_enrollment_request.h
@@ -0,0 +1,64 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef COMPONENTS_AUTOFILL_CORE_BROWSER_PAYMENTS_PAYMENTS_REQUESTS_UPDATE_VIRTUAL_CARD_ENROLLMENT_REQUEST_H_
+#define COMPONENTS_AUTOFILL_CORE_BROWSER_PAYMENTS_PAYMENTS_REQUESTS_UPDATE_VIRTUAL_CARD_ENROLLMENT_REQUEST_H_
+
+#include <string>
+
+#include "base/callback.h"
+#include "components/autofill/core/browser/autofill_client.h"
+#include "components/autofill/core/browser/payments/payments_client.h"
+#include "components/autofill/core/browser/payments/payments_requests/payments_request.h"
+#include "third_party/abseil-cpp/absl/types/optional.h"
+
+namespace base {
+class Value;
+}  // namespace base
+
+namespace autofill {
+namespace payments {
+
+// Payments request to enroll or unenroll a credit card into a virtual card.
+// Virtual Card Numbers allow a user to check out online with a credit
+// card using a credit card number that is different from the credit card's
+// original number.
+class UpdateVirtualCardEnrollmentRequest : public PaymentsRequest {
+ public:
+  UpdateVirtualCardEnrollmentRequest(
+      const PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails&
+          request_details,
+      base::OnceCallback<void(AutofillClient::PaymentsRpcResult)> callback);
+  UpdateVirtualCardEnrollmentRequest(
+      const UpdateVirtualCardEnrollmentRequest&) = delete;
+  UpdateVirtualCardEnrollmentRequest& operator=(
+      const UpdateVirtualCardEnrollmentRequest&) = delete;
+  ~UpdateVirtualCardEnrollmentRequest() override;
+
+  // PaymentsRequest:
+  std::string GetRequestUrlPath() override;
+  std::string GetRequestContentType() override;
+  std::string GetRequestContent() override;
+  void ParseResponse(const base::Value& response) override;
+  bool IsResponseComplete() override;
+  void RespondToDelegate(AutofillClient::PaymentsRpcResult result) override;
+
+ private:
+  // Modifies the base::Value that |request_dict| points to by setting all of
+  // the fields needed for an Enroll request.
+  void BuildEnrollRequestDictionary(base::Value* request_dict);
+
+  // Modifies the base::Value that |request_dict| points to by setting all of
+  // the fields needed for an Unenroll request.
+  void BuildUnenrollRequestDictionary(base::Value* request_dict);
+
+  PaymentsClient::UpdateVirtualCardEnrollmentRequestDetails request_details_;
+  base::OnceCallback<void(AutofillClient::PaymentsRpcResult)> callback_;
+  absl::optional<std::string> enroll_result_;
+};
+
+}  // namespace payments
+}  // namespace autofill
+
+#endif  // COMPONENTS_AUTOFILL_CORE_BROWSER_PAYMENTS_PAYMENTS_REQUESTS_UPDATE_VIRTUAL_CARD_ENROLLMENT_REQUEST_H_
diff --git a/components/autofill/core/browser/payments/virtual_card_enrollment_flow.h b/components/autofill/core/browser/payments/virtual_card_enrollment_flow.h
new file mode 100644
index 0000000..9c66297c
--- /dev/null
+++ b/components/autofill/core/browser/payments/virtual_card_enrollment_flow.h
@@ -0,0 +1,43 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef COMPONENTS_AUTOFILL_CORE_BROWSER_PAYMENTS_VIRTUAL_CARD_ENROLLMENT_FLOW_H_
+#define COMPONENTS_AUTOFILL_CORE_BROWSER_PAYMENTS_VIRTUAL_CARD_ENROLLMENT_FLOW_H_
+
+namespace autofill {
+
+// This enum is used to denote the specific source that the virtual card
+// enrollment process originated from.
+enum class VirtualCardEnrollmentSource {
+  // Default value, should never be used.
+  kNone = 0,
+  // Offering VCN Enrollment after Upstream, i.e., saving a card to Google
+  // Payments.
+  kUpstream = 1,
+  // Offering VCN Enrollment after Downstream, i.e., unmasking a card from
+  // Google Payments.
+  kDownstream = 2,
+  // Offering VCN Enrollment from the payment methods settings page.
+  kSettingsPage = 3,
+  // Max value, needs to be updated every time a new enum is added.
+  kMaxValue = kSettingsPage,
+};
+
+// Denotes the request type for an UpdateVirtualCardEnrollmentRequest.
+enum class VirtualCardEnrollmentRequestType {
+  // Default value, should never be used.
+  kNone = 0,
+  // The corresponding UpdateVirtualCardEnrollmentRequest is an enroll
+  // request.
+  kEnroll = 1,
+  // The corresponding UpdateVirtualCardEnrollmentRequest is an unenroll
+  // request.
+  kUnenroll = 2,
+  // Max value, needs to be updated every time a new enum is added.
+  kMaxValue = kUnenroll,
+};
+
+}  // namespace autofill
+
+#endif  // COMPONENTS_AUTOFILL_CORE_BROWSER_PAYMENTS_VIRTUAL_CARD_ENROLLMENT_FLOW_H_
diff --git a/components/autofill/core/browser/payments/virtual_card_enrollment_manager.cc b/components/autofill/core/browser/payments/virtual_card_enrollment_manager.cc
index 56d1dc5..c381427 100644
--- a/components/autofill/core/browser/payments/virtual_card_enrollment_manager.cc
+++ b/components/autofill/core/browser/payments/virtual_card_enrollment_manager.cc
@@ -22,7 +22,7 @@
 
 void VirtualCardEnrollmentManager::OfferVirtualCardEnroll(
     raw_ptr<CreditCard> credit_card,
-    VirtualCardEnrollmentFlow virtual_card_enrollment_flow) {}
+    VirtualCardEnrollmentSource virtual_card_enrollment_source) {}
 
 void VirtualCardEnrollmentManager::Unenroll(int64_t instrument_id) {}
 
diff --git a/components/autofill/core/browser/payments/virtual_card_enrollment_manager.h b/components/autofill/core/browser/payments/virtual_card_enrollment_manager.h
index 9139271..3749bba8 100644
--- a/components/autofill/core/browser/payments/virtual_card_enrollment_manager.h
+++ b/components/autofill/core/browser/payments/virtual_card_enrollment_manager.h
@@ -10,28 +10,12 @@
 #include "base/memory/raw_ptr.h"
 #include "components/autofill/core/browser/autofill_client.h"
 #include "components/autofill/core/browser/payments/payments_client.h"
+#include "components/autofill/core/browser/payments/virtual_card_enrollment_flow.h"
 
 namespace autofill {
 
 class CreditCard;
 
-// This enum is used to denote the specific flow that the virtual card
-// enrollment process is a part of.
-enum class VirtualCardEnrollmentFlow {
-  // Default value, should never be used.
-  kNone = 0,
-  // Offering VCN Enrollment after Upstream flow, i.e., saving a card to
-  // Google Payments.
-  kUpstream = 1,
-  // Offering VCN Enrollment after Downstream flow, i.e., unmasking a card
-  // from Google Payments.
-  kDownstream = 2,
-  // Offering VCN Enrollment from the payment methods settings page.
-  kSettingsPage = 3,
-  // Max value, needs to be updated every time a new enum is added.
-  kMaxValue = kSettingsPage,
-};
-
 // This struct is passed into the controller when we show the
 // VirtualCardEnrollmentBubble, and it lets the controller customize the
 // bubble based on the fields in this struct. For example, we will show
@@ -52,9 +36,9 @@
   // The legal message lines for the footer of the
   // VirtualCardEnrollmentBubble.
   LegalMessageLines legal_message_lines;
-  // The flow for which the VirtualCardEnrollmentBubble will be shown.
-  VirtualCardEnrollmentFlow virtual_card_enrollment_flow =
-      VirtualCardEnrollmentFlow::kNone;
+  // The source for which the VirtualCardEnrollmentBubble will be shown.
+  VirtualCardEnrollmentSource virtual_card_enrollment_source =
+      VirtualCardEnrollmentSource::kNone;
 };
 
 // This struct is used to track the state of the virtual card enrollment
@@ -70,7 +54,7 @@
   // Only populated once the risk engine responded.
   absl::optional<std::string> risk_data;
   // |virtual_card_enrollment_fields|'s |credit_card| and
-  // |virtual_card_enrollment_flow| are populated in the beginning of the
+  // |virtual_card_enrollment_source| are populated in the beginning of the
   // virtual card enrollment flow, but the rest of the fields are only populated
   // before showing the VirtualCardEnrollmentBubble.
   VirtualCardEnrollmentFields virtual_card_enrollment_fields;
@@ -97,12 +81,12 @@
   // Starting point for the VCN enroll flow. The fields in |credit_card| will
   // be used throughout the flow, such as for request fields as well as credit
   // card specific fields for the bubble to display.
-  // |virtual_card_enrollment_flow| will be used by
+  // |virtual_card_enrollment_source| will be used by
   // ShowVirtualCardEnrollBubble() to differentiate different bubbles based on
-  // the flow we are in.
+  // the source we originated from.
   void OfferVirtualCardEnroll(
       raw_ptr<CreditCard> credit_card,
-      VirtualCardEnrollmentFlow virtual_card_enrollment_flow);
+      VirtualCardEnrollmentSource virtual_card_enrollment_source);
 
   // Unenrolls the card mapped to the given |instrument_id|.
   void Unenroll(int64_t instrument_id);
@@ -111,7 +95,7 @@
   // Called once the risk data is loaded. The |risk_data| will be used with
   // |state|'s |virtual_card_enrollment_fields|'s |credit_card|'s
   // |instrument_id_| field to make a GetDetailsForEnroll request, and
-  // |state|'s |virtual_card_enrollment_flow| will be passed down to when we
+  // |state|'s |virtual_card_enrollment_source| will be passed down to when we
   // show the bubble so that we show the correct bubble version.
   void OnRiskDataLoadedForVirtualCard(
       std::unique_ptr<VirtualCardEnrollmentProcessState> state,
@@ -123,7 +107,7 @@
   // |virtual_card_enrollment_fields|'s |credit_card|'s |instrument_id| are the
   // fields the server requires for the GetDetailsForEnrollRequest, and will be
   // used by |client_|'s |payments_client_|. |state|'s
-  // |virtual_card_enrollment_fields_|'s |virtual_card_enrollment_flow| is
+  // |virtual_card_enrollment_fields_|'s |virtual_card_enrollment_source| is
   // passed here so that it can be forwarded to ShowVirtualCardEnrollBubble.
   void GetDetailsForEnroll(
       std::unique_ptr<VirtualCardEnrollmentProcessState> state);
diff --git a/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialog.java b/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialog.java
index 05862c1..bc707af 100644
--- a/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialog.java
+++ b/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialog.java
@@ -142,11 +142,24 @@
             @Override
             public void onLayoutChange(View v, int left, int top, int right, int bottom,
                     int oldLeft, int oldTop, int oldRight, int oldBottom) {
+                // // If the layout size does not change (e.g. call due to #forceLayout), do nothing
+                // // because we don't want to dismiss the context menu.
+                if (left == oldLeft && right == oldRight && top == oldTop && bottom == oldBottom) {
+                    return;
+                }
+
                 if (mIsPopup) {
                     // If the menu is a popup, wait for the layout to be measured, then proceed with
                     // showing the popup window.
                     if (v.getMeasuredHeight() == 0) return;
 
+                    // If dialog is showing and the layout changes, we might lost the anchor point.
+                    // We'll dismiss the context menu and remove the listener.
+                    if (mPopupWindow != null && mPopupWindow.isShowing()) {
+                        dismiss();
+                        return;
+                    }
+
                     final int posX = (int) mTouchPointXPx;
                     final int posY = (int) (mTouchPointYPx + mTopContentOffsetPx);
                     final Rect rect = new Rect(posX, posY, posX, posY);
@@ -167,9 +180,9 @@
                     if (v.getMeasuredHeight() == 0) return;
 
                     startEnterAnimation();
+                    v.removeOnLayoutChangeListener(this);
+                    mOnLayoutChangeListener = null;
                 }
-                v.removeOnLayoutChangeListener(this);
-                mOnLayoutChangeListener = null;
             }
         };
         (mIsPopup ? mLayout : mContentView).addOnLayoutChangeListener(mOnLayoutChangeListener);
diff --git a/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialogUnitTest.java b/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialogUnitTest.java
index c31766e..a57f27999 100644
--- a/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialogUnitTest.java
+++ b/components/browser_ui/widget/android/java/src/org/chromium/components/browser_ui/widget/ContextMenuDialogUnitTest.java
@@ -71,6 +71,7 @@
         Mockito.doNothing()
                 .when(mSpyPopupWindow)
                 .showAtLocation(any(View.class), anyInt(), anyInt(), anyInt());
+        Mockito.doNothing().when(mSpyPopupWindow).dismiss();
     }
 
     @Test
@@ -111,7 +112,8 @@
     public void testShowPopupWindow() {
         mDialog = createContextMenuDialog(/*isPopup=*/true, /*shouldRemoveScrim=*/false);
         mDialog.show();
-        // Request layout so #onLayoutChange is triggered.
+        // Change layout params and request layout so #onLayoutChange is triggered.
+        mRootView.setRight(mRootView.getRight() + 1);
         mRootView.requestLayout();
 
         final ArgumentCaptor<Integer> gravityCaptor = ArgumentCaptor.forClass(Integer.class);
@@ -128,6 +130,25 @@
         Mockito.verify(mSpyPopupWindow).dismiss();
     }
 
+    @Test
+    public void testShowPopupWindow_2ndLayout() {
+        mDialog = createContextMenuDialog(/*isPopup=*/true, /*shouldRemoveScrim=*/false);
+        mDialog.show();
+        // Change layout params and request layout so #onLayoutChange is triggered.
+        mRootView.setRight(mRootView.getRight() + 1);
+        mRootView.requestLayout();
+        Mockito.verify(mSpyPopupWindow)
+                .showAtLocation(eq(mRootView.getRootView()), anyInt(), anyInt(), anyInt());
+
+        // Mock up popup window is showing.
+        Mockito.doReturn(true).when(mSpyPopupWindow).isShowing();
+
+        // Change layout params and request layout so #onLayoutChange is triggered.
+        mRootView.setRight(mRootView.getRight() - 1);
+        mRootView.requestLayout();
+        Mockito.verify(mSpyPopupWindow).dismiss();
+    }
+
     /**
      * Inspired by https://crbug.com/1281011. If popup context menu is dismissed before
      * #onLayoutRequest for the root view, popup menu should not get invoked.
diff --git a/components/browsing_data/content/cookie_helper_unittest.cc b/components/browsing_data/content/cookie_helper_unittest.cc
index 58d8a73..586ad6f 100644
--- a/components/browsing_data/content/cookie_helper_unittest.cc
+++ b/components/browsing_data/content/cookie_helper_unittest.cc
@@ -10,6 +10,7 @@
 #include "base/run_loop.h"
 #include "base/test/bind.h"
 #include "base/time/time.h"
+#include "build/build_config.h"
 #include "content/public/browser/cookie_access_details.h"
 #include "content/public/browser/storage_partition.h"
 #include "content/public/test/browser_task_environment.h"
@@ -591,7 +592,13 @@
                      base::Unretained(this)));
 }
 
-TEST_F(CookieHelperTest, CannedGetCookieCount) {
+#if defined(OS_LINUX) && defined(THREAD_SANITIZER)
+#define MAYBE_CannedGetCookieCount DISABLED_CannedGetCookieCount
+#else
+#define MAYBE_CannedGetCookieCount CannedGetCookieCount
+#endif
+// Flaky on Linux TSan: https://crbug.com/1285414.
+TEST_F(CookieHelperTest, MAYBE_CannedGetCookieCount) {
   // The URL in the omnibox is a frame URL. This is not necessarily the request
   // URL, since websites usually include other resources.
   GURL frame1_url("http://www.google.com");
diff --git a/components/browsing_data/content/service_worker_helper_unittest.cc b/components/browsing_data/content/service_worker_helper_unittest.cc
index c325b5b..534f101d 100644
--- a/components/browsing_data/content/service_worker_helper_unittest.cc
+++ b/components/browsing_data/content/service_worker_helper_unittest.cc
@@ -9,6 +9,7 @@
 #include "base/memory/scoped_refptr.h"
 #include "base/strings/utf_string_conversions.h"
 #include "base/threading/thread_task_runner_handle.h"
+#include "build/build_config.h"
 #include "content/public/browser/browser_context.h"
 #include "content/public/browser/storage_partition.h"
 #include "content/public/test/browser_task_environment.h"
@@ -30,7 +31,13 @@
   content::TestBrowserContext browser_context_;
 };
 
-TEST_F(CannedServiceWorkerHelperTest, Empty) {
+#if defined(OS_LINUX) && defined(THREAD_SANITIZER)
+#define MAYBE_Empty DISABLED_Empty
+#else
+#define MAYBE_Empty Empty
+#endif
+// Flaky on Linux TSan: https://crbug.com/1285414
+TEST_F(CannedServiceWorkerHelperTest, MAYBE_Empty) {
   const GURL origin("https://host1:1/");
   std::vector<GURL> scopes;
   scopes.push_back(GURL("https://host1:1/*"));
diff --git a/components/certificate_transparency/data/log_list.json b/components/certificate_transparency/data/log_list.json
index 8b87a8a..b697f47 100644
--- a/components/certificate_transparency/data/log_list.json
+++ b/components/certificate_transparency/data/log_list.json
@@ -1,6 +1,6 @@
 {
-  "version": "4.81",
-  "log_list_timestamp": "2022-01-06T01:34:23Z",
+  "version": "4.82",
+  "log_list_timestamp": "2022-01-07T01:35:26Z",
   "operators": [
     {
       "name": "Google",
diff --git a/components/enterprise/browser/reporting/report_scheduler.cc b/components/enterprise/browser/reporting/report_scheduler.cc
index 250f049..77cf5e9d 100644
--- a/components/enterprise/browser/reporting/report_scheduler.cc
+++ b/components/enterprise/browser/reporting/report_scheduler.cc
@@ -65,6 +65,21 @@
     LOG(ERROR) << "Extension request failed to be added to the pipeline.";
 }
 
+ReportType TriggerToReportType(ReportScheduler::ReportTrigger trigger) {
+  switch (trigger) {
+    case ReportScheduler::kTriggerNone:
+    case ReportScheduler::kTriggerExtensionRequestRealTime:
+      NOTREACHED();
+      [[fallthrough]];
+    case ReportScheduler::kTriggerTimer:
+      return ReportType::kFull;
+    case ReportScheduler::kTriggerUpdate:
+      return ReportType::kBrowserVersion;
+    case ReportScheduler::kTriggerNewVersion:
+      return ReportType::kBrowserVersion;
+  }
+}
+
 }  // namespace
 
 ReportScheduler::Delegate::Delegate() = default;
@@ -229,28 +244,11 @@
   }
 
   active_trigger_ = trigger;
-  ReportType report_type = ReportType::kFull;
-  switch (trigger) {
-    case kTriggerNone:
-    case kTriggerExtensionRequestRealTime:
-      NOTREACHED();
-      [[fallthrough]];
-    case kTriggerTimer:
-      VLOG(1) << "Generating enterprise report.";
-      break;
-    case kTriggerUpdate:
-      VLOG(1) << "Generating basic enterprise report upon update.";
-      report_type = ReportType::kBrowserVersion;
-      break;
-    case kTriggerNewVersion:
-      VLOG(1) << "Generating basic enterprise report upon new version.";
-      report_type = ReportType::kBrowserVersion;
-      break;
-  }
 
   report_generator_->Generate(
-      report_type, base::BindOnce(&ReportScheduler::OnReportGenerated,
-                                  base::Unretained(this)));
+      TriggerToReportType(trigger),
+      base::BindOnce(&ReportScheduler::OnReportGenerated,
+                     base::Unretained(this)));
 }
 
 void ReportScheduler::GenerateAndUploadRealtimeReport(
@@ -280,8 +278,9 @@
   }
   RecordUploadTrigger(active_trigger_);
   report_uploader_->SetRequestAndUpload(
-      std::move(requests), base::BindOnce(&ReportScheduler::OnReportUploaded,
-                                          base::Unretained(this)));
+      TriggerToReportType(active_trigger_), std::move(requests),
+      base::BindOnce(&ReportScheduler::OnReportUploaded,
+                     base::Unretained(this)));
 }
 
 void ReportScheduler::OnReportUploaded(ReportUploader::ReportStatus status) {
diff --git a/components/enterprise/browser/reporting/report_uploader.cc b/components/enterprise/browser/reporting/report_uploader.cc
index 73c6e4ef..b9488df0 100644
--- a/components/enterprise/browser/reporting/report_uploader.cc
+++ b/components/enterprise/browser/reporting/report_uploader.cc
@@ -9,6 +9,7 @@
 #include "base/metrics/histogram_functions.h"
 #include "base/time/time.h"
 #include "build/chromeos_buildflags.h"
+#include "components/enterprise/browser/reporting/report_type.h"
 #include "components/policy/core/common/cloud/cloud_policy_client.h"
 #include "device_management_backend.pb.h"
 
@@ -41,8 +42,10 @@
       maximum_number_of_retries_(maximum_number_of_retries) {}
 ReportUploader::~ReportUploader() = default;
 
-void ReportUploader::SetRequestAndUpload(ReportRequestQueue requests,
+void ReportUploader::SetRequestAndUpload(ReportType report_type,
+                                         ReportRequestQueue requests,
                                          ReportCallback callback) {
+  report_type_ = report_type;
   requests_ = std::move(requests);
   callback_ = std::move(callback);
   Upload();
@@ -52,17 +55,28 @@
   auto callback = base::BindRepeating(&ReportUploader::OnRequestFinished,
                                       weak_ptr_factory_.GetWeakPtr());
 
+  switch (report_type_) {
+    case ReportType::kFull:
+    case ReportType::kBrowserVersion: {
+      auto request = std::make_unique<ReportRequest::DeviceReportRequestProto>(
+          requests_.front()->GetDeviceReportRequest());
 #if BUILDFLAG(IS_CHROMEOS_ASH)
-  auto request =
-      std::make_unique<enterprise_management::ChromeOsUserReportRequest>(
-          requests_.front()->GetDeviceReportRequest());
-  client_->UploadChromeOsUserReport(std::move(request), std::move(callback));
+      client_->UploadChromeOsUserReport(std::move(request),
+                                        std::move(callback));
 #else
-  auto request =
-      std::make_unique<enterprise_management::ChromeDesktopReportRequest>(
-          requests_.front()->GetDeviceReportRequest());
-  client_->UploadChromeDesktopReport(std::move(request), std::move(callback));
+      client_->UploadChromeDesktopReport(std::move(request),
+                                         std::move(callback));
 #endif
+      break;
+    }
+    case ReportType::kProfileReport: {
+      client_->UploadChromeProfileReport(
+          std::make_unique<em::ChromeProfileReportRequest>(
+              requests_.front()->GetChromeProfileReportRequest()),
+          std::move(callback));
+      break;
+    }
+  }
 }  // BUILDFLAG(IS_CHROMEOS_ASH)
 
 void ReportUploader::OnRequestFinished(bool status) {
diff --git a/components/enterprise/browser/reporting/report_uploader.h b/components/enterprise/browser/reporting/report_uploader.h
index 7fb17e5..98d85289 100644
--- a/components/enterprise/browser/reporting/report_uploader.h
+++ b/components/enterprise/browser/reporting/report_uploader.h
@@ -53,7 +53,8 @@
 
   // Sets a list of requests and upload it. Request will be uploaded one after
   // another.
-  virtual void SetRequestAndUpload(ReportRequestQueue requests,
+  virtual void SetRequestAndUpload(ReportType report_type,
+                                   ReportRequestQueue requests,
                                    ReportCallback callback);
 
  private:
@@ -77,6 +78,7 @@
   raw_ptr<policy::CloudPolicyClient> client_;
   ReportCallback callback_;
   ReportRequestQueue requests_;
+  ReportType report_type_;
 
   net::BackoffEntry backoff_entry_;
   base::OneShotTimer backoff_request_timer_;
diff --git a/components/enterprise/browser/reporting/report_uploader_unittest.cc b/components/enterprise/browser/reporting/report_uploader_unittest.cc
index d71d481..f526eff 100644
--- a/components/enterprise/browser/reporting/report_uploader_unittest.cc
+++ b/components/enterprise/browser/reporting/report_uploader_unittest.cc
@@ -13,6 +13,7 @@
 #include "components/enterprise/browser/reporting/report_request.h"
 #include "components/enterprise/browser/reporting/report_type.h"
 #include "components/policy/core/common/cloud/mock_cloud_policy_client.h"
+#include "device_management_backend.pb.h"
 #include "testing/gmock/include/gmock/gmock.h"
 #include "testing/gtest/include/gtest/gtest.h"
 
@@ -59,19 +60,31 @@
         << "Please update kBrowserVersionNames above.";
     ReportRequestQueue requests;
     for (int i = 0; i < number_of_request; i++) {
-      auto request = std::make_unique<ReportRequest>(ReportType::kFull);
-      request->GetDeviceReportRequest()
-          .mutable_browser_report()
-          ->set_browser_version(kBrowserVersionNames[i]);
+      auto request = std::make_unique<ReportRequest>(GetReportType());
+      em::BrowserReport* browser_report;
+      switch (GetReportType()) {
+        case ReportType::kFull:
+        case ReportType::kBrowserVersion:
+          browser_report =
+              request->GetDeviceReportRequest().mutable_browser_report();
+          break;
+        case ReportType::kProfileReport:
+          browser_report =
+              request->GetChromeProfileReportRequest().mutable_browser_report();
+          break;
+      }
+      browser_report->set_browser_version(kBrowserVersionNames[i]);
       requests.push(std::move(request));
     }
     has_responded_ = false;
     uploader_->SetRequestAndUpload(
-        std::move(requests),
+        GetReportType(), std::move(requests),
         base::BindOnce(&ReportUploaderTest::OnReportUploaded,
                        base::Unretained(this), expected_status));
   }
 
+  virtual ReportType GetReportType() { return ReportType::kFull; }
+
   void OnReportUploaded(ReportUploader::ReportStatus expected_status,
                         ReportUploader::ReportStatus actuall_status) {
     EXPECT_EQ(expected_status, actuall_status);
@@ -104,7 +117,7 @@
   base::test::TaskEnvironment task_environment_;
 
   std::unique_ptr<ReportUploader> uploader_;
-  policy::MockCloudPolicyClient client_;
+  ::testing::StrictMock<policy::MockCloudPolicyClient> client_;
   bool has_responded_ = false;
   base::HistogramTester histogram_tester_;
 };
@@ -113,17 +126,12 @@
     : public ReportUploaderTest,
       public ::testing::WithParamInterface<policy::DeviceManagementStatus> {};
 
-TEST_F(ReportUploaderTest, Success) {
-  EXPECT_CALL(client_, UploadReportProxy(_, _))
-      .WillOnce(WithArgs<1>(policy::ScheduleStatusCallback(true)));
-  UploadReportAndSetExpectation(/*number_of_request=*/1,
-                                ReportUploader::kSuccess);
-  RunNextTask();
-  EXPECT_TRUE(has_responded_);
-  histogram_tester_.ExpectUniqueSample(
-      kResponseMetricsName, ReportResponseMetricsStatus::kSuccess, 1);
-  ::testing::Mock::VerifyAndClearExpectations(&client_);
-}
+class ReportUploaderTestWithReportType
+    : public ReportUploaderTest,
+      public ::testing::WithParamInterface<ReportType> {
+ public:
+  ReportType GetReportType() override { return GetParam(); }
+};
 
 TEST_F(ReportUploaderTest, PersistentError) {
   CreateUploader(/* retry_count = */ 1);
@@ -304,4 +312,32 @@
                       policy::DM_STATUS_TEMPORARY_UNAVAILABLE,
                       policy::DM_STATUS_SERVICE_TOO_MANY_REQUESTS));
 
+TEST_P(ReportUploaderTestWithReportType, Success) {
+  switch (GetReportType()) {
+    case ReportType::kFull:
+    case ReportType::kBrowserVersion:
+      EXPECT_CALL(client_, UploadReportProxy(_, _))
+          .WillOnce(WithArgs<1>(policy::ScheduleStatusCallback(true)));
+      break;
+    case ReportType::kProfileReport:
+      EXPECT_CALL(client_, UploadChromeProfileReportProxy(_, _))
+          .WillOnce(WithArgs<1>(policy::ScheduleStatusCallback(true)));
+      break;
+  }
+
+  UploadReportAndSetExpectation(/*number_of_request=*/1,
+                                ReportUploader::kSuccess);
+  RunNextTask();
+  EXPECT_TRUE(has_responded_);
+  histogram_tester_.ExpectUniqueSample(
+      kResponseMetricsName, ReportResponseMetricsStatus::kSuccess, 1);
+  ::testing::Mock::VerifyAndClearExpectations(&client_);
+}
+
+INSTANTIATE_TEST_SUITE_P(All,
+                         ReportUploaderTestWithReportType,
+                         ::testing::Values(ReportType::kFull,
+                                           ReportType::kBrowserVersion,
+                                           ReportType::kProfileReport));
+
 }  // namespace enterprise_reporting
diff --git a/components/exo/display_unittest.cc b/components/exo/display_unittest.cc
index 28e1a948..3469fdc 100644
--- a/components/exo/display_unittest.cc
+++ b/components/exo/display_unittest.cc
@@ -84,15 +84,15 @@
 };
 
 TEST_F(DisplayTest, CreateSurface) {
-  std::unique_ptr<Display> display(new Display);
+  Display display;
 
   // Creating a surface should succeed.
-  std::unique_ptr<Surface> surface = display->CreateSurface();
+  std::unique_ptr<Surface> surface = display.CreateSurface();
   EXPECT_TRUE(surface);
 }
 
 TEST_F(DisplayTest, CreateSharedMemory) {
-  std::unique_ptr<Display> display(new Display);
+  Display display;
 
   int shm_size = 8192;
   base::UnsafeSharedMemoryRegion shared_memory =
@@ -101,12 +101,12 @@
 
   // Creating a shared memory instance from a valid region should succeed.
   std::unique_ptr<SharedMemory> shm1 =
-      display->CreateSharedMemory(std::move(shared_memory));
+      display.CreateSharedMemory(std::move(shared_memory));
   EXPECT_TRUE(shm1);
 
   // Creating a shared memory instance from a invalid region should fail.
   std::unique_ptr<SharedMemory> shm2 =
-      display->CreateSharedMemory(base::UnsafeSharedMemoryRegion());
+      display.CreateSharedMemory(base::UnsafeSharedMemoryRegion());
   EXPECT_FALSE(shm2);
 }
 
@@ -115,7 +115,7 @@
 TEST_F(DisplayTest, DISABLED_CreateLinuxDMABufBuffer) {
   const gfx::Size buffer_size(256, 256);
 
-  std::unique_ptr<Display> display(new Display);
+  Display display;
   // Creating a prime buffer from a native pixmap handle should succeed.
   scoped_refptr<gfx::NativePixmap> pixmap =
       ui::OzonePlatform::GetInstance()
@@ -124,9 +124,9 @@
                                buffer_size, gfx::BufferFormat::RGBA_8888,
                                gfx::BufferUsage::GPU_READ);
   gfx::NativePixmapHandle native_pixmap_handle = pixmap->ExportHandle();
-  std::unique_ptr<Buffer> buffer1 = display->CreateLinuxDMABufBuffer(
-      buffer_size, gfx::BufferFormat::RGBA_8888,
-      std::move(native_pixmap_handle), false);
+  std::unique_ptr<Buffer> buffer1 =
+      display.CreateLinuxDMABufBuffer(buffer_size, gfx::BufferFormat::RGBA_8888,
+                                      std::move(native_pixmap_handle), false);
   EXPECT_TRUE(buffer1);
 
   // Create a handle without a file descriptor.
@@ -134,9 +134,9 @@
   native_pixmap_handle.planes[0].fd.reset();
 
   // Creating a prime buffer using an invalid fd should fail.
-  std::unique_ptr<Buffer> buffer2 = display->CreateLinuxDMABufBuffer(
-      buffer_size, gfx::BufferFormat::RGBA_8888,
-      std::move(native_pixmap_handle), false);
+  std::unique_ptr<Buffer> buffer2 =
+      display.CreateLinuxDMABufBuffer(buffer_size, gfx::BufferFormat::RGBA_8888,
+                                      std::move(native_pixmap_handle), false);
   EXPECT_FALSE(buffer2);
 }
 
@@ -146,37 +146,37 @@
 #endif
 
 TEST_F(DisplayTest, CreateShellSurface) {
-  std::unique_ptr<Display> display(new Display);
+  Display display;
 
   // Create two surfaces.
-  std::unique_ptr<Surface> surface1 = display->CreateSurface();
+  std::unique_ptr<Surface> surface1 = display.CreateSurface();
   ASSERT_TRUE(surface1);
-  std::unique_ptr<Surface> surface2 = display->CreateSurface();
+  std::unique_ptr<Surface> surface2 = display.CreateSurface();
   ASSERT_TRUE(surface2);
 
   // Create a shell surface for surface1.
   std::unique_ptr<ShellSurface> shell_surface1 =
-      display->CreateShellSurface(surface1.get());
+      display.CreateShellSurface(surface1.get());
   EXPECT_TRUE(shell_surface1);
 
   // Create a shell surface for surface2.
   std::unique_ptr<ShellSurface> shell_surface2 =
-      display->CreateShellSurface(surface2.get());
+      display.CreateShellSurface(surface2.get());
   EXPECT_TRUE(shell_surface2);
 }
 
 TEST_F(DisplayTest, CreateClientControlledShellSurface) {
-  std::unique_ptr<Display> display(new Display);
+  Display display;
 
   // Create two surfaces.
-  std::unique_ptr<Surface> surface1 = display->CreateSurface();
+  std::unique_ptr<Surface> surface1 = display.CreateSurface();
   ASSERT_TRUE(surface1);
-  std::unique_ptr<Surface> surface2 = display->CreateSurface();
+  std::unique_ptr<Surface> surface2 = display.CreateSurface();
   ASSERT_TRUE(surface2);
 
   // Create a remote shell surface for surface1.
   std::unique_ptr<ClientControlledShellSurface> shell_surface1 =
-      display->CreateOrGetClientControlledShellSurface(
+      display.CreateOrGetClientControlledShellSurface(
           surface1.get(), ash::kShellWindowId_SystemModalContainer,
           /*default_scale_factor=*/2.0,
           /*default_scale_cancellation=*/true);
@@ -185,7 +185,7 @@
 
   // Create a remote shell surface for surface2.
   std::unique_ptr<ShellSurfaceBase> shell_surface2 =
-      display->CreateOrGetClientControlledShellSurface(
+      display.CreateOrGetClientControlledShellSurface(
           surface2.get(), ash::desks_util::GetActiveDeskContainerId(),
           /*default_scale_factor=*/1.0,
           /*default_scale_cancellation=*/true);
@@ -193,25 +193,26 @@
 }
 
 TEST_F(DisplayTest, GetClientControlledShellSurface) {
-  std::unique_ptr<Display> display(new Display);
+  Display display;
 
   // Create a external surface, bind with a window id.
+  std::unique_ptr<Surface> surface = display.CreateSurface();
   ClientControlledShellSurface* external_shell_surface =
       new ClientControlledShellSurface(
-          new Surface,
+          surface.get(),
           /*can_minimize=*/true, ash::desks_util::GetActiveDeskContainerId(),
           /*default_scale_cancellation=*/true);
   property_resolver()->PutClientControlledShellSurface(
       /*window_session_id=*/10001, base::WrapUnique(external_shell_surface));
 
   // Create surface with specific window id.
-  std::unique_ptr<Surface> surface_with_id = display->CreateSurface();
+  std::unique_ptr<Surface> surface_with_id = display.CreateSurface();
   ASSERT_TRUE(surface_with_id);
   surface_with_id->SetWindowSessionId(10001);
 
   // Get a remote shell surface by external source.
   std::unique_ptr<ClientControlledShellSurface> shell_surface =
-      display->CreateOrGetClientControlledShellSurface(
+      display.CreateOrGetClientControlledShellSurface(
           surface_with_id.get(), ash::desks_util::GetActiveDeskContainerId(),
           /*default_scale_factor=*/2.0,
           /*default_scale_cancellation=*/true);
@@ -220,68 +221,68 @@
 }
 
 TEST_F(DisplayTest, CreateSubSurface) {
-  std::unique_ptr<Display> display(new Display);
+  Display display;
 
   // Create child, parent and toplevel surfaces.
-  std::unique_ptr<Surface> child = display->CreateSurface();
+  std::unique_ptr<Surface> child = display.CreateSurface();
   ASSERT_TRUE(child);
-  std::unique_ptr<Surface> parent = display->CreateSurface();
+  std::unique_ptr<Surface> parent = display.CreateSurface();
   ASSERT_TRUE(parent);
-  std::unique_ptr<Surface> toplevel = display->CreateSurface();
+  std::unique_ptr<Surface> toplevel = display.CreateSurface();
   ASSERT_TRUE(toplevel);
 
   // Attempting to create a sub surface for child with child as its parent
   // should fail.
-  EXPECT_FALSE(display->CreateSubSurface(child.get(), child.get()));
+  EXPECT_FALSE(display.CreateSubSurface(child.get(), child.get()));
 
   // Create a sub surface for child.
   std::unique_ptr<SubSurface> child_sub_surface =
-      display->CreateSubSurface(child.get(), toplevel.get());
+      display.CreateSubSurface(child.get(), toplevel.get());
   EXPECT_TRUE(child_sub_surface);
 
   // Attempting to create another sub surface when already assigned the role of
   // sub surface should fail.
-  EXPECT_FALSE(display->CreateSubSurface(child.get(), parent.get()));
+  EXPECT_FALSE(display.CreateSubSurface(child.get(), parent.get()));
 
   // Deleting the sub surface should allow a new sub surface to be created.
   child_sub_surface.reset();
-  child_sub_surface = display->CreateSubSurface(child.get(), parent.get());
+  child_sub_surface = display.CreateSubSurface(child.get(), parent.get());
   EXPECT_TRUE(child_sub_surface);
 
-  std::unique_ptr<Surface> sibling = display->CreateSurface();
+  std::unique_ptr<Surface> sibling = display.CreateSurface();
   ASSERT_TRUE(sibling);
 
   // Create a sub surface for sibiling.
   std::unique_ptr<SubSurface> sibling_sub_surface =
-      display->CreateSubSurface(sibling.get(), parent.get());
+      display.CreateSubSurface(sibling.get(), parent.get());
   EXPECT_TRUE(sibling_sub_surface);
 
   // Create a shell surface for toplevel surface.
   std::unique_ptr<ShellSurface> shell_surface =
-      display->CreateShellSurface(toplevel.get());
+      display.CreateShellSurface(toplevel.get());
   EXPECT_TRUE(shell_surface);
 
   // Attempting to create a sub surface when already assigned the role of
   // shell surface should fail.
-  EXPECT_FALSE(display->CreateSubSurface(toplevel.get(), parent.get()));
+  EXPECT_FALSE(display.CreateSubSurface(toplevel.get(), parent.get()));
 
-  std::unique_ptr<Surface> grandchild = display->CreateSurface();
+  std::unique_ptr<Surface> grandchild = display.CreateSurface();
   ASSERT_TRUE(grandchild);
   // Create a sub surface for grandchild.
   std::unique_ptr<SubSurface> grandchild_sub_surface =
-      display->CreateSubSurface(grandchild.get(), child.get());
+      display.CreateSubSurface(grandchild.get(), child.get());
   EXPECT_TRUE(grandchild_sub_surface);
 
   // Attempting to create a sub surface for parent with child as its parent
   // should fail.
-  EXPECT_FALSE(display->CreateSubSurface(parent.get(), child.get()));
+  EXPECT_FALSE(display.CreateSubSurface(parent.get(), child.get()));
 
   // Attempting to create a sub surface for parent with grandchild as its parent
   // should fail.
-  EXPECT_FALSE(display->CreateSubSurface(parent.get(), grandchild.get()));
+  EXPECT_FALSE(display.CreateSubSurface(parent.get(), grandchild.get()));
 
   // Create a sub surface for parent.
-  EXPECT_TRUE(display->CreateSubSurface(parent.get(), toplevel.get()));
+  EXPECT_TRUE(display.CreateSubSurface(parent.get(), toplevel.get()));
 }
 
 class TestDataDeviceDelegate : public DataDeviceDelegate {
diff --git a/components/external_intents/android/java/src/org/chromium/components/external_intents/RedirectHandler.java b/components/external_intents/android/java/src/org/chromium/components/external_intents/RedirectHandler.java
index 8e6f619..845de114 100644
--- a/components/external_intents/android/java/src/org/chromium/components/external_intents/RedirectHandler.java
+++ b/components/external_intents/android/java/src/org/chromium/components/external_intents/RedirectHandler.java
@@ -29,28 +29,51 @@
     public static final int INVALID_ENTRY_INDEX = -1;
     public static final long INVALID_TIME = -1;
 
-    private static final int NAVIGATION_TYPE_NONE = 0;
     private static final int NAVIGATION_TYPE_FROM_INTENT = 1;
     private static final int NAVIGATION_TYPE_FROM_USER_TYPING = 2;
     private static final int NAVIGATION_TYPE_FROM_LINK_WITHOUT_USER_GESTURE = 3;
     private static final int NAVIGATION_TYPE_FROM_RELOAD = 4;
     private static final int NAVIGATION_TYPE_OTHER = 5;
 
-    private Intent mInitialIntent;
-    // A resolver list which includes all resolvers of |mInitialIntent|.
-    private final HashSet<ComponentName> mCachedResolvers = new HashSet<ComponentName>();
-    private boolean mIsInitialIntentHeadingToChrome;
-    private boolean mIsCustomTabIntent;
+    private static class IntentState {
+        final Intent mInitialIntent;
+        final boolean mIsCustomTabIntent;
+        final boolean mIsInitialIntentHeadingToChrome;
+        final boolean mExternalIntentStartedTask;
+
+        // A resolver list which includes all resolvers of |mInitialIntent|.
+        HashSet<ComponentName> mCachedResolvers = new HashSet<ComponentName>();
+
+        IntentState(Intent initialIntent, boolean isInitialIntentHeadingToChrome,
+                boolean isCustomTabIntent, boolean externalIntentStartedTask) {
+            mInitialIntent = initialIntent;
+            mIsInitialIntentHeadingToChrome = isInitialIntentHeadingToChrome;
+            mIsCustomTabIntent = isCustomTabIntent;
+            mExternalIntentStartedTask = externalIntentStartedTask;
+        }
+    }
+
+    private static class NavigationState {
+        final int mInitialNavigationType;
+        final int mLastCommittedEntryIndexBeforeStartingNavigation;
+        final boolean mHasUserStartedNonInitialNavigation;
+        boolean mIsOnEffectiveRedirectChain;
+        boolean mShouldNotOverrideUrlLoadingOnCurrentRedirectChain;
+        boolean mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain;
+
+        NavigationState(int initialNavigationType,
+                int lastCommittedEntryIndexBeforeStartingNavigation,
+                boolean hasUserStartedNonInitialNavigation) {
+            mInitialNavigationType = initialNavigationType;
+            mLastCommittedEntryIndexBeforeStartingNavigation =
+                    lastCommittedEntryIndexBeforeStartingNavigation;
+            mHasUserStartedNonInitialNavigation = hasUserStartedNonInitialNavigation;
+        }
+    }
 
     private long mLastNewUrlLoadingTime = INVALID_TIME;
-    private boolean mIsOnEffectiveRedirectChain;
-    private int mInitialNavigationType;
-    private int mLastCommittedEntryIndexBeforeStartingNavigation;
-    private boolean mHasUserStartedNonInitialNavigation;
-
-    private boolean mShouldNotOverrideUrlLoadingOnCurrentRedirectChain;
-    private boolean mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain;
-    private boolean mExternalIntentStartedTask;
+    private IntentState mIntentState;
+    private NavigationState mNavigationState;
 
     public static RedirectHandler create() {
         return new RedirectHandler();
@@ -59,36 +82,31 @@
     protected RedirectHandler() {}
 
     /**
-     * Updates |mIntentHistory| and |mLastIntentUpdatedTime|. If |intent| comes from chrome and
-     * currently |mIsOnEffectiveIntentRedirectChain| is true, that means |intent| was sent from
-     * this tab because only the front tab or a new tab can receive an intent from chrome. In that
-     * case, |intent| is added to |mIntentHistory|.
-     * Otherwise, |mIntentHistory| and |mPreviousResolvers| are cleared, and then |intent| is put
-     * into |mIntentHistory|.
+     * Resets |mIntentState| for the newly received Intent.
      */
     public void updateIntent(Intent intent, boolean isCustomTabIntent, boolean sendToExternalApps,
             boolean isCCTExternalLinkHandlingEnabled, boolean externalIntentStartedTask) {
-        clear();
-
         if (intent == null || !Intent.ACTION_VIEW.equals(intent.getAction())) {
+            mIntentState = null;
             return;
         }
 
-        mIsCustomTabIntent = isCustomTabIntent;
-        mExternalIntentStartedTask = externalIntentStartedTask;
+        boolean isInitialIntentHeadingToChrome = false;
         boolean checkIsToChrome = true;
         // All custom tabs VIEW intents are by design explicit intents, so the presence of package
         // name doesn't imply they have to be handled by Chrome explicitly. Check if external apps
         // should be checked for handling the initial redirect chain.
-        if (mIsCustomTabIntent) {
+        if (isCustomTabIntent) {
             checkIsToChrome = !(sendToExternalApps && isCCTExternalLinkHandlingEnabled);
         }
 
-        if (checkIsToChrome) mIsInitialIntentHeadingToChrome = isIntentToChrome(intent);
+        if (checkIsToChrome) isInitialIntentHeadingToChrome = isIntentToChrome(intent);
 
         // A sanitized copy of the initial intent for detecting if resolvers have changed.
-        mInitialIntent = new Intent(intent);
-        ExternalNavigationHandler.sanitizeQueryIntentActivitiesIntent(mInitialIntent);
+        Intent initialIntent = new Intent(intent);
+        ExternalNavigationHandler.sanitizeQueryIntentActivitiesIntent(initialIntent);
+        mIntentState = new IntentState(initialIntent, isInitialIntentHeadingToChrome,
+                isCustomTabIntent, externalIntentStartedTask);
     }
 
     private static boolean isIntentToChrome(Intent intent) {
@@ -98,25 +116,12 @@
                         IntentUtils.safeGetStringExtra(intent, Browser.EXTRA_APPLICATION_ID));
     }
 
-    private void clearIntentHistory() {
-        mIsInitialIntentHeadingToChrome = false;
-        mIsCustomTabIntent = false;
-        mInitialIntent = null;
-        mExternalIntentStartedTask = false;
-        mCachedResolvers.clear();
-    }
-
     /**
      * Resets all variables except timestamps.
      */
     public void clear() {
-        clearIntentHistory();
-        mInitialNavigationType = NAVIGATION_TYPE_NONE;
-        mIsOnEffectiveRedirectChain = false;
-        mLastCommittedEntryIndexBeforeStartingNavigation = 0;
-        mHasUserStartedNonInitialNavigation = false;
-        mShouldNotOverrideUrlLoadingOnCurrentRedirectChain = false;
-        mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain = false;
+        mIntentState = null;
+        mNavigationState = null;
     }
 
     /**
@@ -124,7 +129,7 @@
      * occurs.
      */
     public void setShouldNotOverrideUrlLoadingOnCurrentRedirectChain() {
-        mShouldNotOverrideUrlLoadingOnCurrentRedirectChain = true;
+        mNavigationState.mShouldNotOverrideUrlLoadingOnCurrentRedirectChain = true;
     }
 
     /**
@@ -132,7 +137,7 @@
      * a new user-initiated navigation occurs.
      */
     public void setShouldNotBlockUrlLoadingOverrideOnCurrentRedirectionChain() {
-        mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain = true;
+        mNavigationState.mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain = true;
     }
 
     /**
@@ -142,7 +147,7 @@
      *         swiped away or timed out).
      */
     public boolean wasTaskStartedByExternalIntent() {
-        return mExternalIntentStartedTask;
+        return mIntentState != null && mIntentState.mExternalIntentStartedTask;
     }
 
     /**
@@ -185,42 +190,39 @@
                 isNewLoadingStartedByUser = true;
             }
         }
-
-        if (isNewLoadingStartedByUser) {
-            // Updates mInitialNavigationType for a new loading started by a user's gesture.
-            if (isFromIntent && mInitialIntent != null) {
-                mInitialNavigationType = NAVIGATION_TYPE_FROM_INTENT;
-            } else {
-                clearIntentHistory();
-                if (pageTransitionCore == PageTransition.TYPED) {
-                    mInitialNavigationType = NAVIGATION_TYPE_FROM_USER_TYPING;
-                } else if (pageTransitionCore == PageTransition.RELOAD
-                        || (pageTransType & PageTransition.FORWARD_BACK) != 0) {
-                    mInitialNavigationType = NAVIGATION_TYPE_FROM_RELOAD;
-                } else if (pageTransitionCore == PageTransition.LINK && !hasUserGesture) {
-                    mInitialNavigationType = NAVIGATION_TYPE_FROM_LINK_WITHOUT_USER_GESTURE;
-                } else {
-                    mInitialNavigationType = NAVIGATION_TYPE_OTHER;
-                }
-            }
-            mIsOnEffectiveRedirectChain = false;
-            mLastCommittedEntryIndexBeforeStartingNavigation = lastCommittedEntryIndex;
-            if (!isInitialNavigation) {
-                mHasUserStartedNonInitialNavigation = true;
-            }
-            mShouldNotOverrideUrlLoadingOnCurrentRedirectChain = false;
-            mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain = false;
-        } else if (mInitialNavigationType != NAVIGATION_TYPE_NONE) {
+        if (!isNewLoadingStartedByUser) {
             // Redirect chain starts from the second url loading.
-            mIsOnEffectiveRedirectChain = true;
+            mNavigationState.mIsOnEffectiveRedirectChain = true;
+            return;
         }
+
+        // Create the NavigationState for a new Navigation chain.
+        int mInitialNavigationType;
+        if (isFromIntent && mIntentState != null) {
+            mInitialNavigationType = NAVIGATION_TYPE_FROM_INTENT;
+        } else {
+            mIntentState = null;
+            if (pageTransitionCore == PageTransition.TYPED) {
+                mInitialNavigationType = NAVIGATION_TYPE_FROM_USER_TYPING;
+            } else if (pageTransitionCore == PageTransition.RELOAD
+                    || (pageTransType & PageTransition.FORWARD_BACK) != 0) {
+                mInitialNavigationType = NAVIGATION_TYPE_FROM_RELOAD;
+            } else if (pageTransitionCore == PageTransition.LINK && !hasUserGesture) {
+                mInitialNavigationType = NAVIGATION_TYPE_FROM_LINK_WITHOUT_USER_GESTURE;
+            } else {
+                mInitialNavigationType = NAVIGATION_TYPE_OTHER;
+            }
+        }
+        mNavigationState = new NavigationState(
+                mInitialNavigationType, lastCommittedEntryIndex, !isInitialNavigation);
     }
 
     /**
      * @return whether on effective intent redirect chain or not.
      */
     public boolean isOnEffectiveIntentRedirectChain() {
-        return mInitialNavigationType == NAVIGATION_TYPE_FROM_INTENT && mIsOnEffectiveRedirectChain;
+        return mNavigationState.mInitialNavigationType == NAVIGATION_TYPE_FROM_INTENT
+                && mNavigationState.mIsOnEffectiveRedirectChain;
     }
 
     /**
@@ -240,7 +242,8 @@
     public boolean shouldStayInApp(boolean hasExternalProtocol, boolean isForTrustedCallingApp) {
         // http://crbug/424029 : Need to stay in Chrome for an intent heading explicitly to Chrome.
         // http://crbug/881740 : Relax stay in Chrome restriction for Custom Tabs.
-        return (mIsInitialIntentHeadingToChrome && !hasExternalProtocol)
+        return (mIntentState != null && mIntentState.mIsInitialIntentHeadingToChrome
+                       && !hasExternalProtocol)
                 || shouldNavigationTypeStayInApp(isForTrustedCallingApp);
     }
 
@@ -253,35 +256,36 @@
 
     private boolean shouldNavigationTypeStayInApp(boolean isForTrustedCallingApp) {
         // http://crbug.com/162106: Never leave Chrome from a refresh.
-        if (mInitialNavigationType == NAVIGATION_TYPE_FROM_RELOAD) return true;
+        if (mNavigationState.mInitialNavigationType == NAVIGATION_TYPE_FROM_RELOAD) return true;
 
         // If the app we would navigate to is trusted and what launched Chrome, allow the
         // navigation.
         if (isForTrustedCallingApp) return false;
 
         // Otherwise allow navigation out of the app only with a user gesture.
-        return mInitialNavigationType == NAVIGATION_TYPE_FROM_LINK_WITHOUT_USER_GESTURE;
+        return mNavigationState.mInitialNavigationType
+                == NAVIGATION_TYPE_FROM_LINK_WITHOUT_USER_GESTURE;
     }
 
     /**
      * @return Whether this navigation is initiated by a Custom Tabs {@link Intent}.
      */
     public boolean isFromCustomTabIntent() {
-        return mIsCustomTabIntent;
+        return mIntentState != null && mIntentState.mIsCustomTabIntent;
     }
 
     /**
      * @return whether navigation is from a user's typing or not.
      */
     public boolean isNavigationFromUserTyping() {
-        return mInitialNavigationType == NAVIGATION_TYPE_FROM_USER_TYPING;
+        return mNavigationState.mInitialNavigationType == NAVIGATION_TYPE_FROM_USER_TYPING;
     }
 
     /**
      * @return whether we should stay in Chrome or not.
      */
     public boolean shouldNotOverrideUrlLoading() {
-        return mShouldNotOverrideUrlLoadingOnCurrentRedirectChain;
+        return mNavigationState.mShouldNotOverrideUrlLoadingOnCurrentRedirectChain;
     }
 
     /**
@@ -289,8 +293,8 @@
      * chain.
      */
     public boolean getAndClearShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain() {
-        boolean value = mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain;
-        mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain = false;
+        boolean value = mNavigationState.mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain;
+        mNavigationState.mShouldNotBlockOverrideUrlLoadingOnCurrentRedirectionChain = false;
         return value;
     }
 
@@ -298,21 +302,21 @@
      * @return whether on navigation or not.
      */
     public boolean isOnNavigation() {
-        return mInitialNavigationType != NAVIGATION_TYPE_NONE;
+        return mNavigationState != null;
     }
 
     /**
      * @return the last committed entry index which was saved before starting this navigation.
      */
     public int getLastCommittedEntryIndexBeforeStartingNavigation() {
-        return mLastCommittedEntryIndexBeforeStartingNavigation;
+        return mNavigationState.mLastCommittedEntryIndexBeforeStartingNavigation;
     }
 
     /**
      * @return whether the user has started a non-initial navigation.
      */
     public boolean hasUserStartedNonInitialNavigation() {
-        return mHasUserStartedNonInitialNavigation;
+        return mNavigationState != null && mNavigationState.mHasUserStartedNonInitialNavigation;
     }
 
     /**
@@ -320,19 +324,17 @@
      */
     public boolean hasNewResolver(List<ResolveInfo> resolvingInfos,
             Function<Intent, List<ResolveInfo>> queryIntentActivitiesFunction) {
-        if (mInitialIntent == null) {
-            return !resolvingInfos.isEmpty();
-        }
+        if (mIntentState == null) return !resolvingInfos.isEmpty();
 
-        if (mCachedResolvers.isEmpty()) {
-            for (ResolveInfo r : queryIntentActivitiesFunction.apply(mInitialIntent)) {
-                mCachedResolvers.add(
+        if (mIntentState.mCachedResolvers.isEmpty()) {
+            for (ResolveInfo r : queryIntentActivitiesFunction.apply(mIntentState.mInitialIntent)) {
+                mIntentState.mCachedResolvers.add(
                         new ComponentName(r.activityInfo.packageName, r.activityInfo.name));
             }
         }
-        if (resolvingInfos.size() > mCachedResolvers.size()) return true;
+        if (resolvingInfos.size() > mIntentState.mCachedResolvers.size()) return true;
         for (ResolveInfo r : resolvingInfos) {
-            if (!mCachedResolvers.contains(
+            if (!mIntentState.mCachedResolvers.contains(
                         new ComponentName(r.activityInfo.packageName, r.activityInfo.name))) {
                 return true;
             }
@@ -344,6 +346,6 @@
      * @return The initial intent of a redirect chain, if available.
      */
     public Intent getInitialIntent() {
-        return mInitialIntent;
+        return mIntentState != null ? mIntentState.mInitialIntent : null;
     }
 }
diff --git a/components/external_intents/android/javatests/src/org/chromium/components/external_intents/RedirectHandlerTest.java b/components/external_intents/android/javatests/src/org/chromium/components/external_intents/RedirectHandlerTest.java
index 4926f24..8ef164c 100644
--- a/components/external_intents/android/javatests/src/org/chromium/components/external_intents/RedirectHandlerTest.java
+++ b/components/external_intents/android/javatests/src/org/chromium/components/external_intents/RedirectHandlerTest.java
@@ -4,6 +4,7 @@
 
 package org.chromium.components.external_intents;
 
+import android.content.Context;
 import android.content.Intent;
 import android.content.pm.ActivityInfo;
 import android.content.pm.PackageManager;
@@ -14,17 +15,18 @@
 
 import androidx.test.filters.SmallTest;
 
+import org.junit.After;
 import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 import org.junit.runner.RunWith;
 
-import org.chromium.base.CommandLine;
 import org.chromium.base.ContextUtils;
 import org.chromium.base.Function;
 import org.chromium.base.PackageManagerUtils;
 import org.chromium.base.test.BaseJUnit4ClassRunner;
 import org.chromium.base.test.util.AdvancedMockContext;
+import org.chromium.base.test.util.Batch;
 import org.chromium.base.test.util.Feature;
 import org.chromium.ui.base.PageTransition;
 
@@ -36,6 +38,7 @@
  * Unittests for tab redirect handler.
  */
 @RunWith(BaseJUnit4ClassRunner.class)
+@Batch(Batch.UNIT_TESTS)
 public class RedirectHandlerTest {
     private static final int TRANS_TYPE_OF_LINK_FROM_INTENT =
             PageTransition.LINK | PageTransition.FROM_API;
@@ -47,6 +50,8 @@
     private Function<Intent, List<ResolveInfo>> mQueryIntentFunction =
             (Intent intent) -> queryIntentActivities(intent);
 
+    private Context mContextToRestore;
+
     static {
         try {
             sYtIntent = Intent.parseUri("http://youtube.com/", Intent.URI_INTENT_SCHEME);
@@ -59,10 +64,15 @@
 
     @Before
     public void setUp() {
-        CommandLine.init(new String[0]);
+        mContextToRestore = ContextUtils.getApplicationContext();
         ContextUtils.initApplicationContextForTests(new TestContext());
     }
 
+    @After
+    public void tearDown() {
+        ContextUtils.initApplicationContextForTests(mContextToRestore);
+    }
+
     private List<ResolveInfo> queryIntentActivities(Intent intent) {
         return PackageManagerUtils.queryIntentActivities(intent, 0);
     }
@@ -253,8 +263,6 @@
         fooIntent.putExtra(Browser.EXTRA_APPLICATION_ID, TEST_PACKAGE_NAME);
         handler.updateIntent(fooIntent, false, false, false, false);
         Assert.assertFalse(handler.isOnNavigation());
-        Assert.assertTrue(handler.shouldStayInApp(false));
-        Assert.assertFalse(handler.shouldStayInApp(true));
 
         handler.updateNewUrlLoading(TRANS_TYPE_OF_LINK_FROM_INTENT, false, false, 0, 0, false);
         Assert.assertTrue(handler.shouldStayInApp(false));
@@ -283,7 +291,6 @@
         RedirectHandler handler = RedirectHandler.create();
         handler.updateIntent(sYtIntent, false, false, false, false);
         Assert.assertFalse(handler.isOnNavigation());
-        Assert.assertFalse(handler.isNavigationFromUserTyping());
 
         handler.updateNewUrlLoading(PageTransition.TYPED, false, false, 0, 0, false);
         Assert.assertTrue(handler.isNavigationFromUserTyping());
@@ -311,8 +318,6 @@
         fooIntent.setPackage(TEST_PACKAGE_NAME);
         handler.updateIntent(fooIntent, false, false, false, false);
         Assert.assertFalse(handler.isOnNavigation());
-        Assert.assertTrue(handler.shouldStayInApp(false));
-        Assert.assertFalse(handler.shouldStayInApp(true));
 
         handler.updateNewUrlLoading(TRANS_TYPE_OF_LINK_FROM_INTENT, false, false, 0, 0, false);
         Assert.assertTrue(handler.shouldStayInApp(false));
@@ -343,9 +348,9 @@
         /////////////////////////////////////////////////////
         RedirectHandler handler = RedirectHandler.create();
         handler.updateIntent(sYtIntent, false, false, false, false);
-        Assert.assertFalse(handler.shouldNotOverrideUrlLoading());
 
         handler.updateNewUrlLoading(PageTransition.LINK, false, true, 0, 0, false);
+        Assert.assertFalse(handler.shouldNotOverrideUrlLoading());
         handler.setShouldNotOverrideUrlLoadingOnCurrentRedirectChain();
 
         handler.updateNewUrlLoading(PageTransition.LINK, true, false, 0, 0, false);
@@ -357,9 +362,9 @@
         /////////////////////////////////////////////////////
         handler = RedirectHandler.create();
         handler.updateIntent(sYtIntent, false, false, false, false);
-        Assert.assertFalse(handler.shouldNotOverrideUrlLoading());
 
         handler.updateNewUrlLoading(PageTransition.LINK, false, true, 0, 0, false);
+        Assert.assertFalse(handler.shouldNotOverrideUrlLoading());
         handler.setShouldNotOverrideUrlLoadingOnCurrentRedirectChain();
 
         // Effective redirection occurred.
@@ -384,8 +389,6 @@
         RedirectHandler handler = RedirectHandler.create();
         handler.updateIntent(sYtIntent, false, false, false, false);
         Assert.assertFalse(handler.isOnNavigation());
-        Assert.assertFalse(handler.shouldStayInApp(false));
-        Assert.assertFalse(handler.shouldStayInApp(true));
 
         long lastUserInteractionTime = SystemClock.elapsedRealtime();
         handler.updateNewUrlLoading(
@@ -417,8 +420,6 @@
         RedirectHandler handler = RedirectHandler.create();
         handler.updateIntent(sYtIntent, false, false, false, false);
         Assert.assertFalse(handler.isOnNavigation());
-        Assert.assertFalse(handler.shouldStayInApp(false));
-        Assert.assertFalse(handler.shouldStayInApp(true));
 
         long lastUserInteractionTime = SystemClock.elapsedRealtime();
         handler.updateNewUrlLoading(
@@ -450,15 +451,14 @@
         RedirectHandler handler = RedirectHandler.create();
         handler.updateIntent(sYtIntent, false, false, false, false);
         Assert.assertFalse(handler.isOnNavigation());
-        Assert.assertFalse(handler.shouldStayInApp(false));
-        Assert.assertFalse(handler.shouldStayInApp(true));
-        Assert.assertFalse(handler.hasUserStartedNonInitialNavigation());
 
         long lastUserInteractionTime = SystemClock.elapsedRealtime();
         handler.updateNewUrlLoading(PageTransition.FORM_SUBMIT | PageTransition.FORWARD_BACK, false,
                 true, lastUserInteractionTime, 0, false);
         Assert.assertTrue(handler.shouldStayInApp(false));
         Assert.assertTrue(handler.shouldStayInApp(true));
+        Assert.assertTrue(handler.hasUserStartedNonInitialNavigation());
+
         handler.updateNewUrlLoading(PageTransition.LINK, false, false, lastUserInteractionTime, 1,
                 false /* isInitialNavigation */);
         Assert.assertTrue(handler.shouldStayInApp(false));
diff --git a/components/history_clusters/core/BUILD.gn b/components/history_clusters/core/BUILD.gn
index 7437a17..01e2e92 100644
--- a/components/history_clusters/core/BUILD.gn
+++ b/components/history_clusters/core/BUILD.gn
@@ -41,6 +41,8 @@
       "content_annotations_cluster_processor.h",
       "content_visibility_cluster_finalizer.cc",
       "content_visibility_cluster_finalizer.h",
+      "keyword_cluster_finalizer.cc",
+      "keyword_cluster_finalizer.h",
       "noisy_cluster_finalizer.cc",
       "noisy_cluster_finalizer.h",
       "on_device_clustering_backend.cc",
@@ -63,7 +65,6 @@
     ":history_clusters_buildflags",
     "//base",
     "//components/history/core/browser",
-    "//components/history_clusters/core/proto",
     "//components/keyed_service/core",
     "//components/optimization_guide/core:entities",
     "//components/pref_registry",
@@ -91,6 +92,7 @@
       "clusterer_unittest.cc",
       "content_annotations_cluster_processor_unittest.cc",
       "content_visibility_cluster_finalizer_unittest.cc",
+      "keyword_cluster_finalizer_unittest.cc",
       "noisy_cluster_finalizer_unittest.cc",
       "on_device_clustering_backend_unittest.cc",
       "on_device_clustering_util_unittest.cc",
@@ -106,7 +108,6 @@
     "//base/test:test_support",
     "//components/history/core/browser",
     "//components/history/core/test",
-    "//components/history_clusters/core/proto",
     "//components/optimization_guide/core:entities",
     "//components/search_engines",
     "//services/network:test_support",
diff --git a/components/history_clusters/core/clusterer.cc b/components/history_clusters/core/clusterer.cc
index 6f7c087..292055f6 100644
--- a/components/history_clusters/core/clusterer.cc
+++ b/components/history_clusters/core/clusterer.cc
@@ -4,32 +4,11 @@
 
 #include "components/history_clusters/core/clusterer.h"
 
-#include "base/strings/utf_string_conversions.h"
 #include "components/history/core/browser/history_types.h"
 #include "components/history_clusters/core/on_device_clustering_features.h"
 
 namespace history_clusters {
 
-namespace {
-
-void AddKeywordsForVisitToCluster(history::Cluster& cluster,
-                                  const history::ClusterVisit& visit) {
-  base::flat_set<std::u16string> keywords_set(cluster.keywords.begin(),
-                                              cluster.keywords.end());
-  for (const auto& entity :
-       visit.annotated_visit.content_annotations.model_annotations.entities) {
-    keywords_set.insert(base::UTF8ToUTF16(entity.id));
-  }
-  for (const auto& category :
-       visit.annotated_visit.content_annotations.model_annotations.categories) {
-    keywords_set.insert(base::UTF8ToUTF16(category.id));
-  }
-  cluster.keywords =
-      std::vector<std::u16string>(keywords_set.begin(), keywords_set.end());
-}
-
-}  // namespace
-
 Clusterer::Clusterer() = default;
 Clusterer::~Clusterer() = default;
 
@@ -98,15 +77,12 @@
     default_scored_visit.score = 1.0;
     if (cluster_idx) {
       clusters[*cluster_idx].visits.push_back(default_scored_visit);
-      AddKeywordsForVisitToCluster(clusters[*cluster_idx],
-                                   default_scored_visit);
     } else {
       // Add to new cluster.
       cluster_idx = clusters.size();
 
       history::Cluster new_cluster;
       new_cluster.visits = {default_scored_visit};
-      AddKeywordsForVisitToCluster(new_cluster, default_scored_visit);
       clusters.push_back(std::move(new_cluster));
     }
     visit_id_to_cluster_map[visit.annotated_visit.visit_row.visit_id] =
diff --git a/components/history_clusters/core/content_annotations_cluster_processor.cc b/components/history_clusters/core/content_annotations_cluster_processor.cc
index 9835485e..08f9075 100644
--- a/components/history_clusters/core/content_annotations_cluster_processor.cc
+++ b/components/history_clusters/core/content_annotations_cluster_processor.cc
@@ -132,7 +132,7 @@
   CreateBoWsForClusters(clusters, &cluster_idx_to_entity_bows,
                         &cluster_idx_to_category_bows);
 
-  // Now cluster on the keywords in each BoW between clusters.
+  // Now cluster on the entries in each BoW between clusters.
   std::vector<history::Cluster> aggregated_clusters;
   base::flat_set<int> merged_cluster_indices;
   for (size_t i = 0; i < clusters.size(); i++) {
@@ -142,8 +142,6 @@
     // Greedily combine clusters by checking if this cluster is similar to any
     // other unmerged clusters.
     history::Cluster aggregated_cluster = clusters[i];
-    base::flat_set<std::u16string> aggregated_cluster_keywords(
-        clusters[i].keywords.begin(), clusters[i].keywords.end());
     for (size_t j = i + 1; j < clusters.size(); j++) {
       if (merged_cluster_indices.find(j) != merged_cluster_indices.end()) {
         continue;
@@ -153,18 +151,13 @@
       float category_similarity = CalculateSimilarityScore(
           cluster_idx_to_category_bows[i], cluster_idx_to_category_bows[j]);
       if (ShouldMergeClusters(entity_similarity, category_similarity)) {
-        // Add the visits and keywords to the aggregated cluster.
+        // Add the visits to the aggregated cluster.
         merged_cluster_indices.insert(j);
         aggregated_cluster.visits.insert(aggregated_cluster.visits.end(),
                                          clusters[j].visits.begin(),
                                          clusters[j].visits.end());
-        aggregated_cluster_keywords.insert(clusters[j].keywords.begin(),
-                                           clusters[j].keywords.end());
       }
     }
-    aggregated_cluster.keywords =
-        std::vector<std::u16string>({aggregated_cluster_keywords.begin(),
-                                     aggregated_cluster_keywords.end()});
     aggregated_clusters.push_back(std::move(aggregated_cluster));
   }
   return aggregated_clusters;
diff --git a/components/history_clusters/core/content_annotations_cluster_processor_unittest.cc b/components/history_clusters/core/content_annotations_cluster_processor_unittest.cc
index 7d5762c..38b7aa4 100644
--- a/components/history_clusters/core/content_annotations_cluster_processor_unittest.cc
+++ b/components/history_clusters/core/content_annotations_cluster_processor_unittest.cc
@@ -62,7 +62,6 @@
   cluster1.visits = {testing::CreateClusterVisit(visit),
                      testing::CreateClusterVisit(visit2),
                      testing::CreateClusterVisit(visit4)};
-  cluster1.keywords = {std::u16string(u"github"), std::u16string(u"google")};
   clusters.push_back(cluster1);
 
   // After the context clustering, visit5 will not be in the same cluster as
@@ -74,8 +73,6 @@
   visit5.content_annotations.model_annotations.categories = {{"category", 1}};
   history::Cluster cluster2;
   cluster2.visits = {testing::CreateClusterVisit(visit5)};
-  cluster2.keywords = {std::u16string(u"github"),
-                       std::u16string(u"otherkeyword")};
   clusters.push_back(cluster2);
 
   std::vector<history::Cluster> result_clusters = ProcessClusters(clusters);
@@ -85,10 +82,6 @@
           testing::VisitResult(1, 1.0), testing::VisitResult(2, 1.0),
           testing::VisitResult(4, 1.0), testing::VisitResult(10, 1.0))));
   ASSERT_EQ(result_clusters.size(), 1u);
-  EXPECT_THAT(
-      result_clusters.at(0).keywords,
-      UnorderedElementsAre(std::u16string(u"github"), std::u16string(u"google"),
-                           std::u16string(u"otherkeyword")));
 }
 
 TEST_F(ContentAnnotationsClusterProcessorTest, BelowThreshold) {
@@ -105,7 +98,6 @@
   history::Cluster cluster1;
   cluster1.visits = {testing::CreateClusterVisit(visit),
                      testing::CreateClusterVisit(visit2)};
-  cluster1.keywords = {std::u16string(u"github"), std::u16string(u"google")};
   clusters.push_back(cluster1);
 
   // After the context clustering, visit4 will not be in the same cluster as
@@ -117,7 +109,6 @@
   visit4.content_annotations.model_annotations.entities = {{"github", 1}};
   history::Cluster cluster2;
   cluster2.visits = {testing::CreateClusterVisit(visit4)};
-  cluster2.keywords = {std::u16string(u"github")};
   clusters.push_back(cluster2);
 
   // This visit has the same entities but no categories and shouldn't be
@@ -127,7 +118,6 @@
   visit5.content_annotations.model_annotations.entities = {{"github", 1}};
   history::Cluster cluster3;
   cluster3.visits = {testing::CreateClusterVisit(visit5)};
-  cluster3.keywords = {std::u16string(u"irrelevant")};
   clusters.push_back(cluster3);
 
   // This visit has the same categories but no entities and shouldn't be
@@ -137,7 +127,6 @@
   visit6.content_annotations.model_annotations.categories = {{"category", 1}};
   history::Cluster cluster4;
   cluster4.visits = {testing::CreateClusterVisit(visit6)};
-  cluster4.keywords = {std::u16string(u"category")};
   clusters.push_back(cluster4);
 
   // This visit has no content annotations and shouldn't be grouped with the
@@ -157,14 +146,6 @@
                           ElementsAre(testing::VisitResult(11, 1.0)),
                           ElementsAre(testing::VisitResult(12, 1.0))));
   EXPECT_THAT(result_clusters.size(), 4u);
-  EXPECT_THAT(result_clusters.at(0).keywords,
-              UnorderedElementsAre(std::u16string(u"github"),
-                                   std::u16string(u"google")));
-  EXPECT_THAT(result_clusters.at(1).keywords,
-              UnorderedElementsAre(std::u16string(u"irrelevant")));
-  EXPECT_THAT(result_clusters.at(2).keywords,
-              UnorderedElementsAre(std::u16string(u"category")));
-  EXPECT_TRUE(result_clusters.at(3).keywords.empty());
 }
 
 class ContentAnnotationsIntersectionMetricTest
@@ -199,7 +180,6 @@
   cluster1.visits = {testing::CreateClusterVisit(visit),
                      testing::CreateClusterVisit(visit2),
                      testing::CreateClusterVisit(visit4)};
-  cluster1.keywords = {std::u16string(u"github"), std::u16string(u"google")};
   clusters.push_back(cluster1);
 
   // After the context clustering, visit5 will not be in the same cluster as
@@ -216,8 +196,6 @@
   history::Cluster cluster2;
   cluster2.visits = {testing::CreateClusterVisit(visit5),
                      testing::CreateClusterVisit(visit6)};
-  cluster2.keywords = {std::u16string(u"github"), std::u16string(u"google"),
-                       std::u16string(u"otherkeyword")};
   clusters.push_back(cluster2);
 
   std::vector<history::Cluster> result_clusters = ProcessClusters(clusters);
@@ -227,10 +205,6 @@
                   testing::VisitResult(4, 1.0), testing::VisitResult(10, 1.0),
                   testing::VisitResult(11, 1.0))));
   ASSERT_EQ(result_clusters.size(), 1u);
-  EXPECT_THAT(
-      result_clusters.at(0).keywords,
-      UnorderedElementsAre(std::u16string(u"github"), std::u16string(u"google"),
-                           std::u16string(u"otherkeyword")));
 }
 
 TEST_F(ContentAnnotationsIntersectionMetricTest, BelowThreshold) {
@@ -251,7 +225,6 @@
   cluster1.visits = {testing::CreateClusterVisit(visit),
                      testing::CreateClusterVisit(visit2),
                      testing::CreateClusterVisit(visit4)};
-  cluster1.keywords = {std::u16string(u"github"), std::u16string(u"google")};
   clusters.push_back(cluster1);
 
   // After the context clustering, visit5 will not be in the same cluster as
@@ -263,15 +236,10 @@
   visit5.content_annotations.model_annotations.categories = {{"category", 1}};
   history::Cluster cluster2;
   cluster2.visits = {testing::CreateClusterVisit(visit5)};
-  cluster2.keywords = {std::u16string(u"github"), std::u16string(u"google"),
-                       std::u16string(u"otherkeyword")};
   clusters.push_back(cluster2);
 
   std::vector<history::Cluster> result_clusters = ProcessClusters(clusters);
   ASSERT_EQ(result_clusters.size(), 2u);
-  EXPECT_THAT(result_clusters.at(0).keywords,
-              UnorderedElementsAre(std::u16string(u"github"),
-                                   std::u16string(u"google")));
 }
 
 }  // namespace
diff --git a/components/history_clusters/core/keyword_cluster_finalizer.cc b/components/history_clusters/core/keyword_cluster_finalizer.cc
new file mode 100644
index 0000000..b4e43d2
--- /dev/null
+++ b/components/history_clusters/core/keyword_cluster_finalizer.cc
@@ -0,0 +1,42 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "components/history_clusters/core/keyword_cluster_finalizer.h"
+
+#include "base/containers/flat_set.h"
+#include "base/strings/utf_string_conversions.h"
+#include "components/history_clusters/core/on_device_clustering_features.h"
+#include "components/history_clusters/core/on_device_clustering_util.h"
+
+namespace history_clusters {
+
+KeywordClusterFinalizer::KeywordClusterFinalizer() = default;
+KeywordClusterFinalizer::~KeywordClusterFinalizer() = default;
+
+void KeywordClusterFinalizer::FinalizeCluster(history::Cluster& cluster) {
+  base::flat_set<std::u16string> keywords_set;
+  for (const auto& visit : cluster.visits) {
+    if (features::ShouldExcludeKeywordsFromNoisyVisits() &&
+        IsNoisyVisit(visit)) {
+      // Do not put keywords if user visits the page a lot and it's not a
+      // search-like visit.
+      continue;
+    }
+
+    for (const auto& entity :
+         visit.annotated_visit.content_annotations.model_annotations.entities) {
+      keywords_set.insert(base::UTF8ToUTF16(entity.id));
+    }
+    if (features::ShouldIncludeCategoriesInKeywords()) {
+      for (const auto& category : visit.annotated_visit.content_annotations
+                                      .model_annotations.categories) {
+        keywords_set.insert(base::UTF8ToUTF16(category.id));
+      }
+    }
+  }
+  cluster.keywords =
+      std::vector<std::u16string>(keywords_set.begin(), keywords_set.end());
+}
+
+}  // namespace history_clusters
diff --git a/components/history_clusters/core/keyword_cluster_finalizer.h b/components/history_clusters/core/keyword_cluster_finalizer.h
new file mode 100644
index 0000000..9781abf
--- /dev/null
+++ b/components/history_clusters/core/keyword_cluster_finalizer.h
@@ -0,0 +1,24 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef COMPONENTS_HISTORY_CLUSTERS_CORE_KEYWORD_CLUSTER_FINALIZER_H_
+#define COMPONENTS_HISTORY_CLUSTERS_CORE_KEYWORD_CLUSTER_FINALIZER_H_
+
+#include "components/history_clusters/core/cluster_finalizer.h"
+
+namespace history_clusters {
+
+// A cluster finalizer that determines the set of keywords for a given cluster.
+class KeywordClusterFinalizer : public ClusterFinalizer {
+ public:
+  KeywordClusterFinalizer();
+  ~KeywordClusterFinalizer() override;
+
+  // ClusterFinalizer:
+  void FinalizeCluster(history::Cluster& cluster) override;
+};
+
+}  // namespace history_clusters
+
+#endif  // COMPONENTS_HISTORY_CLUSTERS_CORE_KEYWORD_CLUSTER_FINALIZER_H_
diff --git a/components/history_clusters/core/keyword_cluster_finalizer_unittest.cc b/components/history_clusters/core/keyword_cluster_finalizer_unittest.cc
new file mode 100644
index 0000000..0143ce0
--- /dev/null
+++ b/components/history_clusters/core/keyword_cluster_finalizer_unittest.cc
@@ -0,0 +1,134 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "components/history_clusters/core/keyword_cluster_finalizer.h"
+
+#include "base/test/scoped_feature_list.h"
+#include "base/test/task_environment.h"
+#include "components/history_clusters/core/clustering_test_utils.h"
+#include "components/history_clusters/core/on_device_clustering_features.h"
+#include "testing/gmock/include/gmock/gmock.h"
+#include "testing/gtest/include/gtest/gtest.h"
+
+namespace history_clusters {
+namespace {
+
+using ::testing::UnorderedElementsAre;
+
+class KeywordClusterFinalizerTest : public ::testing::Test {
+ public:
+  void SetUp() override {
+    cluster_finalizer_ = std::make_unique<KeywordClusterFinalizer>();
+    scoped_feature_list_.InitAndEnableFeatureWithParameters(
+        features::kOnDeviceClustering,
+        {{"exclude_keywords_from_noisy_visits", "true"},
+         {"include_categories_in_keywords", "false"}});
+  }
+
+  void TearDown() override { cluster_finalizer_.reset(); }
+
+  void FinalizeCluster(history::Cluster& cluster) {
+    cluster_finalizer_->FinalizeCluster(cluster);
+  }
+
+ private:
+  base::test::ScopedFeatureList scoped_feature_list_;
+  std::unique_ptr<KeywordClusterFinalizer> cluster_finalizer_;
+  base::test::TaskEnvironment task_environment_;
+};
+
+TEST_F(KeywordClusterFinalizerTest, IncludesKeywordsBasedOnFeatureParameters) {
+  history::ClusterVisit visit = testing::CreateClusterVisit(
+      testing::CreateDefaultAnnotatedVisit(1, GURL("https://foo.com/")));
+  visit.engagement_score = 1.0;
+  visit.annotated_visit.content_annotations.model_annotations.entities = {
+      {"github", 1}};
+  visit.annotated_visit.content_annotations.model_annotations.categories = {
+      {"category", 1}};
+
+  history::ClusterVisit visit2 =
+      testing::CreateClusterVisit(testing::CreateDefaultAnnotatedVisit(
+          2, GURL("https://engagementtoohigh.com/")));
+  visit2.engagement_score = 25.0;
+  visit2.annotated_visit.content_annotations.model_annotations.entities = {
+      {"github", 1}, {"onlyinnoisyvisit", 1}};
+  visit2.annotated_visit.content_annotations.model_annotations.categories = {
+      {"category", 1}};
+
+  history::ClusterVisit visit3 = testing::CreateClusterVisit(
+      testing::CreateDefaultAnnotatedVisit(2, GURL("https://baz.com/")));
+  visit3.duplicate_visit_ids.push_back(1);
+  visit3.engagement_score = 1.0;
+  visit3.annotated_visit.content_annotations.model_annotations.entities = {
+      {"github", 1}, {"otherentity", 1}};
+  visit3.annotated_visit.content_annotations.model_annotations.categories = {
+      {"category", 1}};
+
+  history::Cluster cluster;
+  cluster.visits = {visit, visit2, visit3};
+  FinalizeCluster(cluster);
+  EXPECT_THAT(cluster.keywords,
+              UnorderedElementsAre(u"github", u"otherentity"));
+}
+
+class KeywordClusterFinalizerIncludeAllTest : public ::testing::Test {
+ public:
+  void SetUp() override {
+    cluster_finalizer_ = std::make_unique<KeywordClusterFinalizer>();
+    scoped_feature_list_.InitAndEnableFeatureWithParameters(
+        features::kOnDeviceClustering,
+        {{"exclude_keywords_from_noisy_visits", "false"},
+         {"include_categories_in_keywords", "true"}});
+  }
+
+  void TearDown() override { cluster_finalizer_.reset(); }
+
+  void FinalizeCluster(history::Cluster& cluster) {
+    cluster_finalizer_->FinalizeCluster(cluster);
+  }
+
+ private:
+  base::test::ScopedFeatureList scoped_feature_list_;
+  std::unique_ptr<KeywordClusterFinalizer> cluster_finalizer_;
+  base::test::TaskEnvironment task_environment_;
+};
+
+TEST_F(KeywordClusterFinalizerIncludeAllTest,
+       IncludesKeywordsBasedOnFeatureParameters) {
+  history::ClusterVisit visit = testing::CreateClusterVisit(
+      testing::CreateDefaultAnnotatedVisit(1, GURL("https://foo.com/")));
+  visit.engagement_score = 1.0;
+  visit.annotated_visit.content_annotations.model_annotations.entities = {
+      {"github", 1}};
+  visit.annotated_visit.content_annotations.model_annotations.categories = {
+      {"category", 1}};
+
+  history::ClusterVisit visit2 =
+      testing::CreateClusterVisit(testing::CreateDefaultAnnotatedVisit(
+          2, GURL("https://engagementtoohigh.com/")));
+  visit2.engagement_score = 25.0;
+  visit2.annotated_visit.content_annotations.model_annotations.entities = {
+      {"github", 1}, {"onlyinnoisyvisit", 1}};
+  visit2.annotated_visit.content_annotations.model_annotations.categories = {
+      {"category", 1}};
+
+  history::ClusterVisit visit3 = testing::CreateClusterVisit(
+      testing::CreateDefaultAnnotatedVisit(2, GURL("https://baz.com/")));
+  visit3.duplicate_visit_ids.push_back(1);
+  visit3.engagement_score = 1.0;
+  visit3.annotated_visit.content_annotations.model_annotations.entities = {
+      {"github", 1}, {"otherentity", 1}};
+  visit3.annotated_visit.content_annotations.model_annotations.categories = {
+      {"category", 1}};
+
+  history::Cluster cluster;
+  cluster.visits = {visit, visit2, visit3};
+  FinalizeCluster(cluster);
+  EXPECT_THAT(cluster.keywords,
+              UnorderedElementsAre(u"github", u"category", u"onlyinnoisyvisit",
+                                   u"otherentity"));
+}
+
+}  // namespace
+}  // namespace history_clusters
diff --git a/components/history_clusters/core/noisy_cluster_finalizer.cc b/components/history_clusters/core/noisy_cluster_finalizer.cc
index ff5b8ef..3bc2dae 100644
--- a/components/history_clusters/core/noisy_cluster_finalizer.cc
+++ b/components/history_clusters/core/noisy_cluster_finalizer.cc
@@ -15,8 +15,7 @@
 void NoisyClusterFinalizer::FinalizeCluster(history::Cluster& cluster) {
   size_t interesting_visit_cnt = 0;
   for (const auto& visit : cluster.visits) {
-    if (visit.engagement_score <
-        features::NoisyClusterVisitEngagementThreshold()) {
+    if (!IsNoisyVisit(visit)) {
       interesting_visit_cnt += 1;
     }
     if (interesting_visit_cnt >=
diff --git a/components/history_clusters/core/on_device_clustering_backend.cc b/components/history_clusters/core/on_device_clustering_backend.cc
index eefe333..b6db99b1 100644
--- a/components/history_clusters/core/on_device_clustering_backend.cc
+++ b/components/history_clusters/core/on_device_clustering_backend.cc
@@ -18,6 +18,7 @@
 #include "components/history/core/browser/history_types.h"
 #include "components/history_clusters/core/content_annotations_cluster_processor.h"
 #include "components/history_clusters/core/content_visibility_cluster_finalizer.h"
+#include "components/history_clusters/core/keyword_cluster_finalizer.h"
 #include "components/history_clusters/core/noisy_cluster_finalizer.h"
 #include "components/history_clusters/core/on_device_clustering_features.h"
 #include "components/history_clusters/core/on_device_clustering_util.h"
@@ -272,6 +273,7 @@
   if (engagement_score_provider_ && features::ShouldFilterNoisyClusters()) {
     cluster_finalizers.push_back(std::make_unique<NoisyClusterFinalizer>());
   }
+  cluster_finalizers.push_back(std::make_unique<KeywordClusterFinalizer>());
 
   // Group visits into clusters.
   std::vector<history::Cluster> clusters =
diff --git a/components/history_clusters/core/on_device_clustering_backend_unittest.cc b/components/history_clusters/core/on_device_clustering_backend_unittest.cc
index c1a5499..2f38753 100644
--- a/components/history_clusters/core/on_device_clustering_backend_unittest.cc
+++ b/components/history_clusters/core/on_device_clustering_backend_unittest.cc
@@ -72,7 +72,9 @@
         features::kOnDeviceClustering,
         {{"content_clustering_enabled", "false"},
          {"dedupe_similar_visits", "false"},
-         {"min_page_topics_model_version_for_visibility", "125"}});
+         {"min_page_topics_model_version_for_visibility", "125"},
+         {"include_categories_in_keywords", "true"},
+         {"exclude_keywords_from_noisy_visits", "false"}});
   }
 
   void SetUp() override {
@@ -356,8 +358,11 @@
  public:
   OnDeviceClusteringWithContentBackendTest() {
     scoped_feature_list_.InitAndEnableFeatureWithParameters(
-        features::kOnDeviceClustering, {{"content_clustering_enabled", "true"},
-                                        {"dedupe_similar_visits", "false"}});
+        features::kOnDeviceClustering,
+        {{"content_clustering_enabled", "true"},
+         {"dedupe_similar_visits", "false"},
+         {"include_categories_in_keywords", "true"},
+         {"exclude_keywords_from_noisy_visits", "false"}});
   }
 
  private:
diff --git a/components/history_clusters/core/on_device_clustering_features.cc b/components/history_clusters/core/on_device_clustering_features.cc
index 24f818f..e49f8428 100644
--- a/components/history_clusters/core/on_device_clustering_features.cc
+++ b/components/history_clusters/core/on_device_clustering_features.cc
@@ -125,5 +125,15 @@
       kOnDeviceClustering, "content_clustering_intersection_threshold", 2);
 }
 
+bool ShouldIncludeCategoriesInKeywords() {
+  return GetFieldTrialParamByFeatureAsBool(
+      kOnDeviceClustering, "include_categories_in_keywords", true);
+}
+
+bool ShouldExcludeKeywordsFromNoisyVisits() {
+  return GetFieldTrialParamByFeatureAsBool(
+      kOnDeviceClustering, "exclude_keywords_from_noisy_visits", false);
+}
+
 }  // namespace features
 }  // namespace history_clusters
diff --git a/components/history_clusters/core/on_device_clustering_features.h b/components/history_clusters/core/on_device_clustering_features.h
index 0b1d46de..4923484 100644
--- a/components/history_clusters/core/on_device_clustering_features.h
+++ b/components/history_clusters/core/on_device_clustering_features.h
@@ -92,6 +92,13 @@
 // when clustering based on intersection score.
 int ClusterIntersectionThreshold();
 
+// Whether to include category names in the keywords for a cluster.
+bool ShouldIncludeCategoriesInKeywords();
+
+// Whether to exclude keywords from visits that may be considered "noisy" to the
+// user (i.e. highly engaged, non-SRP).
+bool ShouldExcludeKeywordsFromNoisyVisits();
+
 }  // namespace features
 }  // namespace history_clusters
 
diff --git a/components/history_clusters/core/on_device_clustering_util.cc b/components/history_clusters/core/on_device_clustering_util.cc
index 3c7b7ca3..6621c0b 100644
--- a/components/history_clusters/core/on_device_clustering_util.cc
+++ b/components/history_clusters/core/on_device_clustering_util.cc
@@ -5,6 +5,7 @@
 #include "components/history_clusters/core/on_device_clustering_util.h"
 
 #include "base/containers/contains.h"
+#include "components/history_clusters/core/on_device_clustering_features.h"
 
 namespace history_clusters {
 
@@ -109,4 +110,10 @@
   });
 }
 
+bool IsNoisyVisit(const history::ClusterVisit& visit) {
+  return visit.engagement_score >
+             features::NoisyClusterVisitEngagementThreshold() &&
+         !visit.is_search_visit;
+}
+
 }  // namespace history_clusters
diff --git a/components/history_clusters/core/on_device_clustering_util.h b/components/history_clusters/core/on_device_clustering_util.h
index 38106938..a0c6355 100644
--- a/components/history_clusters/core/on_device_clustering_util.h
+++ b/components/history_clusters/core/on_device_clustering_util.h
@@ -23,6 +23,10 @@
 // by-score sorting of visits within clusters. Exposed for testing.
 void SortClusters(std::vector<history::Cluster>* clusters);
 
+// Whether the visit is considered a noisy visit (i.e. high engagement,
+// non-SRP).
+bool IsNoisyVisit(const history::ClusterVisit& visit);
+
 }  // namespace history_clusters
 
 #endif  // COMPONENTS_HISTORY_CLUSTERS_CORE_ON_DEVICE_CLUSTERING_UTIL_H_
diff --git a/components/history_clusters/core/on_device_clustering_util_unittest.cc b/components/history_clusters/core/on_device_clustering_util_unittest.cc
index 97998a416..00d7bc26 100644
--- a/components/history_clusters/core/on_device_clustering_util_unittest.cc
+++ b/components/history_clusters/core/on_device_clustering_util_unittest.cc
@@ -140,5 +140,33 @@
   EXPECT_FLOAT_EQ(visits[1].score, 0.5);
 }
 
+TEST_F(OnDeviceClusteringUtilTest, IsNoisyVisitSearchHighEngagementVisit) {
+  history::ClusterVisit visit;
+  visit.is_search_visit = true;
+  visit.engagement_score = 90.0;
+  EXPECT_FALSE(IsNoisyVisit(visit));
+}
+
+TEST_F(OnDeviceClusteringUtilTest, IsNoisyVisitNotSearchHighEngagementVisit) {
+  history::ClusterVisit visit;
+  visit.is_search_visit = false;
+  visit.engagement_score = 90.0;
+  EXPECT_TRUE(IsNoisyVisit(visit));
+}
+
+TEST_F(OnDeviceClusteringUtilTest, IsNoisyVisitNotSearchLowEngagementVisit) {
+  history::ClusterVisit visit;
+  visit.is_search_visit = false;
+  visit.engagement_score = 1.0;
+  EXPECT_FALSE(IsNoisyVisit(visit));
+}
+
+TEST_F(OnDeviceClusteringUtilTest, IsNoisyVisitSearchLowEngagementVisit) {
+  history::ClusterVisit visit;
+  visit.is_search_visit = true;
+  visit.engagement_score = 1.0;
+  EXPECT_FALSE(IsNoisyVisit(visit));
+}
+
 }  // namespace
 }  // namespace history_clusters
diff --git a/components/history_clusters/core/proto/BUILD.gn b/components/history_clusters/core/proto/BUILD.gn
deleted file mode 100644
index 20e7e6e..0000000
--- a/components/history_clusters/core/proto/BUILD.gn
+++ /dev/null
@@ -1,9 +0,0 @@
-# Copyright 2021 The Chromium Authors. All rights reserved.
-# Use of this source code is governed by a BSD-style license that can be
-# found in the LICENSE file.
-
-import("//third_party/protobuf/proto_library.gni")
-
-proto_library("proto") {
-  sources = [ "clusters.proto" ]
-}
diff --git a/components/history_clusters/core/proto/clusters.proto b/components/history_clusters/core/proto/clusters.proto
deleted file mode 100644
index 23faed2..0000000
--- a/components/history_clusters/core/proto/clusters.proto
+++ /dev/null
@@ -1,67 +0,0 @@
-// Copyright 2021 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-syntax = "proto3";
-
-option optimize_for = LITE_RUNTIME;
-
-package history_clusters.proto;
-
-// Below this line sourced from Google3 for debug (non-production) usage only.
-
-message GetClustersRequest {
-  // Represents a set of visits.
-  repeated AnnotatedVisit visits = 1;
-  // The experiment name that controls the clustering behavior served for
-  // this request.
-  string experiment_name = 2;
-}
-
-message GetClustersResponse {
-  // Represents a set of clusters calculated from the request.
-  repeated Cluster clusters = 1;
-}
-
-message AnnotatedVisit {
-  // The ID associated with this visit.
-  int64 visit_id = 1;
-  // The URL for the visit.
-  string url = 2;
-  // The origin for the visit.
-  string origin = 3;
-  // The amount of time the page load was in the foreground in seconds.
-  // TODO(tommycli): Kind of a misnomer. We are just using visit_duration,
-  //  which may or may not be in the foreground.
-  int64 foreground_time_secs = 4;
-  // Relative time of navigation for this page load.
-  int64 navigation_time_ms = 5;
-  // Site engagement score rounded to nearest ten.
-  int64 site_engagement_score = 6;
-  // The page end reason.
-  int64 page_end_reason = 7;
-  // Page transition.
-  int64 page_transition = 8;
-  // Whether the page load originated from Google Search.
-  bool is_from_google_search = 9;
-  // The visit ID that referred this visit, if not a new navigation.
-  int64 referring_visit_id = 10;
-}
-
-message ClusterVisit {
-  // The ID of the visit where visit_id corresponds to the visit in the history
-  // table.
-  int64 visit_id = 1;
-  // The score associated with this visit.
-  //
-  // Used for calculating ordering of visits within a cluster.
-  float score = 2;
-}
-
-message Cluster {
-  reserved 2;
-
-  // The keywords that the cluster contains/is related to.
-  repeated string keywords = 1;
-  // The visits that are attached to this cluster.
-  repeated ClusterVisit cluster_visits = 3;
-}
diff --git a/components/js_injection/browser/js_to_browser_messaging.cc b/components/js_injection/browser/js_to_browser_messaging.cc
index e2cc9cf..7867deb 100644
--- a/components/js_injection/browser/js_to_browser_messaging.cc
+++ b/components/js_injection/browser/js_to_browser_messaging.cc
@@ -56,6 +56,7 @@
     return render_frame_host_->GetLifecycleState() ==
            content::RenderFrameHost::LifecycleState::kInBackForwardCache;
   }
+  content::Page& GetPage() override { return render_frame_host_->GetPage(); }
 
  private:
   raw_ptr<content::RenderFrameHost> render_frame_host_;
diff --git a/components/js_injection/browser/web_message_reply_proxy.h b/components/js_injection/browser/web_message_reply_proxy.h
index 2eb52975..3b887ee 100644
--- a/components/js_injection/browser/web_message_reply_proxy.h
+++ b/components/js_injection/browser/web_message_reply_proxy.h
@@ -5,6 +5,10 @@
 #ifndef COMPONENTS_JS_INJECTION_BROWSER_WEB_MESSAGE_REPLY_PROXY_H_
 #define COMPONENTS_JS_INJECTION_BROWSER_WEB_MESSAGE_REPLY_PROXY_H_
 
+namespace content {
+class Page;
+}
+
 namespace js_injection {
 
 struct WebMessage;
@@ -18,6 +22,9 @@
   // forward cache.
   virtual bool IsInBackForwardCache() = 0;
 
+  // Returns the page the messages are sent to.
+  virtual content::Page& GetPage() = 0;
+
  protected:
   virtual ~WebMessageReplyProxy() = default;
 };
diff --git a/components/keep_alive_registry/keep_alive_types.cc b/components/keep_alive_registry/keep_alive_types.cc
index ea9bc27..950be06c 100644
--- a/components/keep_alive_registry/keep_alive_types.cc
+++ b/components/keep_alive_registry/keep_alive_types.cc
@@ -68,6 +68,8 @@
       return out << "CREDENTIAL_PROVIDER_SIGNIN_DIALOG";
     case KeepAliveOrigin::WEB_APP_INTENT_PICKER:
       return out << "WEB_APP_INTENT_PICKER";
+    case KeepAliveOrigin::WEB_APP_UNINSTALL:
+      return out << "WEB_APP_UNINSTALL";
     case KeepAliveOrigin::APP_MANIFEST_UPDATE:
       return out << "APP_MANIFEST_UPDATE";
     case KeepAliveOrigin::APP_START_URL_MIGRATION:
diff --git a/components/keep_alive_registry/keep_alive_types.h b/components/keep_alive_registry/keep_alive_types.h
index 9957017..15b4f9c 100644
--- a/components/keep_alive_registry/keep_alive_types.h
+++ b/components/keep_alive_registry/keep_alive_types.h
@@ -64,6 +64,9 @@
   CREDENTIAL_PROVIDER_SIGNIN_DIALOG,
   WEB_APP_INTENT_PICKER,
 
+  // c/b/ui/web_applications
+  WEB_APP_UNINSTALL,
+
   // c/b/web_applications
   APP_MANIFEST_UPDATE,
   APP_START_URL_MIGRATION,
diff --git a/components/management_strings.grdp b/components/management_strings.grdp
index b0c2cdb..ee4c67d 100644
--- a/components/management_strings.grdp
+++ b/components/management_strings.grdp
@@ -137,6 +137,9 @@
     <message name="IDS_MANAGEMENT_REPORT_LOGIN_LOGOUT" desc="Message stating that administrators can see device Login and Logout events.">
       Device login/logout history, including timestamps and failed attempts
     </message>
+    <message name="IDS_MANAGEMENT_REPORT_CRD_SESSIONS" desc="Message stating that administrators can see Chrome Remote Desktop events.">
+      Chrome Remote Desktop history, including timestamps, hosts and client session ids
+    </message>
     <message name="IDS_MANAGEMENT_CROSTINI" desc="Message stating that administrators can see Crostini usage">
       Linux apps installed and when they were last used
     </message>
diff --git a/components/management_strings_grdp/IDS_MANAGEMENT_REPORT_CRD_SESSIONS.png.sha1 b/components/management_strings_grdp/IDS_MANAGEMENT_REPORT_CRD_SESSIONS.png.sha1
new file mode 100644
index 0000000..52a082e
--- /dev/null
+++ b/components/management_strings_grdp/IDS_MANAGEMENT_REPORT_CRD_SESSIONS.png.sha1
@@ -0,0 +1 @@
+7dc395c7a54d4206cf4004cd34553177330f565d
\ No newline at end of file
diff --git a/components/messages/android/messages_feature.cc b/components/messages/android/messages_feature.cc
index 59e9117b..a8313df 100644
--- a/components/messages/android/messages_feature.cc
+++ b/components/messages/android/messages_feature.cc
@@ -18,7 +18,7 @@
     "MessagesForAndroidInfrastructure", base::FEATURE_ENABLED_BY_DEFAULT};
 
 const base::Feature kMessagesForAndroidNearOomReduction{
-    "MessagesForAndroidNearOomReduction", base::FEATURE_DISABLED_BY_DEFAULT};
+    "MessagesForAndroidNearOomReduction", base::FEATURE_ENABLED_BY_DEFAULT};
 
 const base::Feature kMessagesForAndroidNotificationBlocked{
     "MessagesForAndroidNotificationBlocked", base::FEATURE_DISABLED_BY_DEFAULT};
diff --git a/components/omnibox/browser/omnibox_edit_model.cc b/components/omnibox/browser/omnibox_edit_model.cc
index 83ecadd..c94ba46e 100644
--- a/components/omnibox/browser/omnibox_edit_model.cc
+++ b/components/omnibox/browser/omnibox_edit_model.cc
@@ -1202,9 +1202,10 @@
 
   // Send the textfield contents exactly as-is, as otherwise the verbatim
   // match can be wrong. The full page URL is anyways in set_current_url().
+  // Don't attempt to use https as the default scheme for these requests.
   input_ = AutocompleteInput(view_->GetText(), GetPageClassification(),
                              client_->GetSchemeClassifier(),
-                             client_->ShouldDefaultTypedNavigationsToHttps(),
+                             /*should_use_https_as_default_scheme=*/false,
                              client_->GetHttpsPortForTesting());
   input_.set_current_url(client_->GetURL());
   input_.set_current_title(client_->GetTitle());
diff --git a/components/optimization_guide/core/bert_model_executor.cc b/components/optimization_guide/core/bert_model_executor.cc
index 9e8e7b0..fcd4df0 100644
--- a/components/optimization_guide/core/bert_model_executor.cc
+++ b/components/optimization_guide/core/bert_model_executor.cc
@@ -7,7 +7,7 @@
 #include "base/trace_event/trace_event.h"
 #include "components/optimization_guide/core/model_util.h"
 #include "components/optimization_guide/core/tflite_op_resolver.h"
-#include "third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h"
+#include "third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
 
 namespace optimization_guide {
 
@@ -28,18 +28,21 @@
                GetStringNameForOptimizationTarget(optimization_target_),
                "input_length", input.size());
   *out_status = ExecutionStatus::kSuccess;
-  return static_cast<tflite::task::text::nlclassifier::BertNLClassifier*>(
-             execution_task)
+  return static_cast<tflite::task::text::BertNLClassifier*>(execution_task)
       ->Classify(input);
 }
 
 std::unique_ptr<BertModelExecutor::ModelExecutionTask>
 BertModelExecutor::BuildModelExecutionTask(base::MemoryMappedFile* model_file,
                                            ExecutionStatus* out_status) {
+  tflite::task::text::BertNLClassifierOptions options;
+  *options.mutable_base_options()
+       ->mutable_model_file()
+       ->mutable_file_content() = std::string(
+      reinterpret_cast<const char*>(model_file->data()), model_file->length());
   auto maybe_nl_classifier =
-      tflite::task::text::nlclassifier::BertNLClassifier::CreateFromBuffer(
-          reinterpret_cast<const char*>(model_file->data()),
-          model_file->length(), std::make_unique<TFLiteOpResolver>());
+      tflite::task::text::BertNLClassifier::CreateFromOptions(
+          std::move(options), std::make_unique<TFLiteOpResolver>());
   if (maybe_nl_classifier.ok())
     return std::move(maybe_nl_classifier.value());
   *out_status = ExecutionStatus::kErrorModelFileNotValid;
diff --git a/components/optimization_guide/core/model_validator.cc b/components/optimization_guide/core/model_validator.cc
index b936f747..65a9bd5f 100644
--- a/components/optimization_guide/core/model_validator.cc
+++ b/components/optimization_guide/core/model_validator.cc
@@ -64,7 +64,12 @@
 float ModelValidatorExecutor::Postprocess(
     const std::vector<const TfLiteTensor*>& output_tensors) {
   std::vector<float> data;
-  tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  absl::Status status =
+      tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  if (!status.ok()) {
+    NOTREACHED();
+    return -1;
+  }
   return data[0];
 }
 
diff --git a/components/optimization_guide/core/test_tflite_model_executor.cc b/components/optimization_guide/core/test_tflite_model_executor.cc
index 9b7ea803..09697f7d 100644
--- a/components/optimization_guide/core/test_tflite_model_executor.cc
+++ b/components/optimization_guide/core/test_tflite_model_executor.cc
@@ -11,14 +11,15 @@
 absl::Status TestTFLiteModelExecutor::Preprocess(
     const std::vector<TfLiteTensor*>& input_tensors,
     const std::vector<float>& input) {
-  tflite::task::core::PopulateTensor<float>(input, input_tensors[0]);
-  return absl::OkStatus();
+  return tflite::task::core::PopulateTensor<float>(input, input_tensors[0]);
 }
 
 std::vector<float> TestTFLiteModelExecutor::Postprocess(
     const std::vector<const TfLiteTensor*>& output_tensors) {
   std::vector<float> data;
-  tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  absl::Status status =
+      tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  DCHECK(status.ok());
   return data;
 }
 
diff --git a/components/payments/content/secure_payment_confirmation_app.cc b/components/payments/content/secure_payment_confirmation_app.cc
index 239801e..088234f0 100644
--- a/components/payments/content/secure_payment_confirmation_app.cc
+++ b/components/payments/content/secure_payment_confirmation_app.cc
@@ -218,8 +218,7 @@
   response->secure_payment_confirmation =
       mojom::SecurePaymentConfirmationResponse::New(
           response_->info.Clone(), response_->signature,
-          response_->has_transport, response_->transport,
-          response_->user_handle);
+          response_->authenticator_attachment, response_->user_handle);
   return response;
 }
 
diff --git a/components/permissions/prediction_service/prediction_model_executor.cc b/components/permissions/prediction_service/prediction_model_executor.cc
index 8cea2a3..1fd7298 100644
--- a/components/permissions/prediction_service/prediction_model_executor.cc
+++ b/components/permissions/prediction_service/prediction_model_executor.cc
@@ -28,43 +28,90 @@
       NOTREACHED();
   }
 
-  tflite::task::core::PopulateTensor<float>(
+  absl::Status status = tflite::task::core::PopulateTensor<float>(
       input.client_features().client_stats().avg_deny_rate(), input_tensors[0]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.client_features().client_stats().avg_dismiss_rate(),
       input_tensors[1]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.client_features().client_stats().avg_grant_rate(),
       input_tensors[2]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.client_features().client_stats().avg_ignore_rate(),
       input_tensors[3]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.permission_features()[0].permission_stats().avg_deny_rate(),
       input_tensors[4]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.permission_features()[0].permission_stats().avg_dismiss_rate(),
       input_tensors[5]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.permission_features()[0].permission_stats().avg_grant_rate(),
       input_tensors[6]);
-  tflite::task::core::PopulateTensor<float>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<float>(
       input.permission_features()[0].permission_stats().avg_ignore_rate(),
       input_tensors[7]);
-  tflite::task::core::PopulateTensor<int64_t>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<int64_t>(
       static_cast<int64_t>(
           input.permission_features()[0].permission_stats().prompts_count()),
       input_tensors[8]);
-  tflite::task::core::PopulateTensor<int64_t>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<int64_t>(
       static_cast<int64_t>(
           input.client_features().client_stats().prompts_count()),
       input_tensors[9]);
-  tflite::task::core::PopulateTensor<int64_t>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<int64_t>(
       static_cast<int64_t>(input.client_features().gesture_enum()),
       input_tensors[10]);
-  tflite::task::core::PopulateTensor<int64_t>(
+  if (!status.ok()) {
+    return status;
+  }
+
+  status = tflite::task::core::PopulateTensor<int64_t>(
       static_cast<int64_t>(input.client_features().platform_enum()),
       input_tensors[11]);
+  if (!status.ok()) {
+    return status;
+  }
 
   return absl::OkStatus();
 }
@@ -73,7 +120,10 @@
   DCHECK(request_type_ == RequestType::kNotifications ||
          request_type_ == RequestType::kGeolocation);
   std::vector<float> data;
-  tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  absl::Status status =
+      tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  DCHECK(status.ok());
+
   GeneratePredictionsResponse response;
   float threshold = request_type_ == RequestType::kNotifications
                         ? kNotificationPredictionsThreshold
diff --git a/components/policy/core/common/cloud/cloud_policy_util.cc b/components/policy/core/common/cloud/cloud_policy_util.cc
index 8dbf3f8..5008676 100644
--- a/components/policy/core/common/cloud/cloud_policy_util.cc
+++ b/components/policy/core/common/cloud/cloud_policy_util.cc
@@ -18,7 +18,8 @@
 #include <wincred.h>
 #endif
 
-#if defined(OS_LINUX) || BUILDFLAG(IS_CHROMEOS_LACROS) || defined(OS_APPLE)
+#if defined(OS_LINUX) || BUILDFLAG(IS_CHROMEOS_LACROS) || defined(OS_APPLE) || \
+    defined(OS_FUCHSIA)
 #include <pwd.h>
 #include <sys/types.h>
 #include <unistd.h>
@@ -64,11 +65,6 @@
 #include "base/mac/scoped_cftyperef.h"
 #include "base/strings/string_util.h"
 #include "base/strings/sys_string_conversions.h"
-#include "base/system/sys_info.h"
-#endif
-
-#if defined(OS_LINUX) || BUILDFLAG(IS_CHROMEOS_LACROS)
-#include "base/system/sys_info.h"
 #endif
 
 #if defined(OS_IOS)
@@ -80,7 +76,7 @@
 namespace em = enterprise_management;
 
 std::string GetMachineName() {
-#if defined(OS_LINUX) || BUILDFLAG(IS_CHROMEOS_LACROS)
+#if defined(OS_LINUX) || BUILDFLAG(IS_CHROMEOS_LACROS) || defined(OS_FUCHSIA)
   char hostname[HOST_NAME_MAX];
   if (gethostname(hostname, HOST_NAME_MAX) == 0)  // Success.
     return hostname;
@@ -126,13 +122,13 @@
     return result;
   }
   return std::string();
-#elif defined(OS_ANDROID) || defined(OS_FUCHSIA)
-  // TODO(crbug.com/1257674): This should be fully implemented when there is
-  // support in fuchsia.
+#elif defined(OS_ANDROID)
   return std::string();
-#else
+#elif defined(OS_CHROMEOS)
   NOTREACHED();
   return std::string();
+#else
+#error Unsupported platform
 #endif
 }
 
diff --git a/components/policy/core/common/cloud/mock_cloud_policy_client.h b/components/policy/core/common/cloud/mock_cloud_policy_client.h
index 7442f17..32231e2 100644
--- a/components/policy/core/common/cloud/mock_cloud_policy_client.h
+++ b/components/policy/core/common/cloud/mock_cloud_policy_client.h
@@ -13,6 +13,7 @@
 #include "components/policy/core/common/cloud/cloud_policy_client.h"
 #include "components/policy/core/common/cloud/device_management_service.h"
 #include "components/reporting/proto/synced/record.pb.h"
+#include "device_management_backend.pb.h"
 #include "testing/gmock/include/gmock/gmock.h"
 
 namespace network {
@@ -101,6 +102,17 @@
                void(enterprise_management::ChromeOsUserReportRequest*,
                     StatusCallback&));
 
+  void UploadChromeProfileReport(
+      std::unique_ptr<enterprise_management::ChromeProfileReportRequest>
+          request,
+      StatusCallback callback) override {
+    UploadChromeProfileReportProxy(request.get(), callback);
+  }
+  // Use Proxy function because unique_ptr can't be used in mock function.
+  MOCK_METHOD2(UploadChromeProfileReportProxy,
+               void(enterprise_management::ChromeProfileReportRequest*,
+                    StatusCallback&));
+
   void UploadSecurityEventReport(content::BrowserContext* context,
                                  bool include_device_info,
                                  base::Value value,
diff --git a/components/policy/resources/policy_templates.json b/components/policy/resources/policy_templates.json
index 32c3bde..00b8ed2 100644
--- a/components/policy/resources/policy_templates.json
+++ b/components/policy/resources/policy_templates.json
@@ -9453,7 +9453,7 @@
         'chrome_os:86-',
         'android:86-',
         'webview_android:86-',
-        'ios:91-',
+        'ios:98-',
       ],
       'features': {
         'dynamic_refresh': True,
@@ -9485,7 +9485,7 @@
         'chrome_os:86-',
         'android:86-',
         'webview_android:86-',
-        'ios:91-',
+        'ios:98-',
       ],
       'features': {
         'dynamic_refresh': True,
diff --git a/components/power_metrics/BUILD.gn b/components/power_metrics/BUILD.gn
index 96a8786..ecc0c9b 100644
--- a/components/power_metrics/BUILD.gn
+++ b/components/power_metrics/BUILD.gn
@@ -9,6 +9,9 @@
       "energy_impact_mac.mm",
       "iopm_power_source_sampling_event_source.cc",
       "iopm_power_source_sampling_event_source.h",
+      "m1_sensors_internal_types_mac.h",
+      "m1_sensors_mac.h",
+      "m1_sensors_mac.mm",
       "mach_time_mac.h",
       "mach_time_mac.mm",
       "resource_coalition_internal_types_mac.h",
diff --git a/components/power_metrics/m1_sensors_internal_types_mac.h b/components/power_metrics/m1_sensors_internal_types_mac.h
new file mode 100644
index 0000000..039d84c
--- /dev/null
+++ b/components/power_metrics/m1_sensors_internal_types_mac.h
@@ -0,0 +1,26 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef COMPONENTS_POWER_METRICS_M1_SENSORS_INTERNAL_TYPES_MAC_H_
+#define COMPONENTS_POWER_METRICS_M1_SENSORS_INTERNAL_TYPES_MAC_H_
+
+#include <stdint.h>
+
+// From:
+// https://opensource.apple.com/source/IOHIDFamily/IOHIDFamily-421.6/IOHIDFamily/IOHIDEventTypes.h.auto.html
+
+#define IOHIDEventFieldBase(type) (type << 16)
+
+constexpr int64_t kIOHIDEventTypeTemperature = 15;
+
+// From:
+// https://opensource.apple.com/source/IOHIDFamily/IOHIDFamily-421.6/IOHIDFamily/AppleHIDUsageTables.h
+
+// Usage pages
+constexpr int kHIDPage_AppleVendor = 0xff00;
+
+// Usage keys for `kHIDPage_AppleVendor`
+constexpr int kHIDUsage_AppleVendor_TemperatureSensor = 0x0005;
+
+#endif  // COMPONENTS_POWER_METRICS_M1_SENSORS_INTERNAL_TYPES_MAC_H_
diff --git a/components/power_metrics/m1_sensors_mac.h b/components/power_metrics/m1_sensors_mac.h
new file mode 100644
index 0000000..45703ad
--- /dev/null
+++ b/components/power_metrics/m1_sensors_mac.h
@@ -0,0 +1,48 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+// The Apple M1 chip has sensors to monitor its power consumption and
+// temperature. This file defines a class to retrieve data from these sensors.
+
+#ifndef COMPONENTS_POWER_METRICS_M1_SENSORS_MAC_H_
+#define COMPONENTS_POWER_METRICS_M1_SENSORS_MAC_H_
+
+#include <memory>
+
+#include <IOKit/hidsystem/IOHIDEventSystemClient.h>
+
+#include "base/mac/scoped_cftyperef.h"
+#include "third_party/abseil-cpp/absl/types/optional.h"
+
+namespace power_metrics {
+
+class M1SensorsReader {
+ public:
+  struct TemperaturesCelsius {
+    TemperaturesCelsius();
+    TemperaturesCelsius(const TemperaturesCelsius&) noexcept;
+    ~TemperaturesCelsius();
+
+    absl::optional<double> p_cores;
+    absl::optional<double> e_cores;
+  };
+
+  virtual ~M1SensorsReader();
+
+  // Creates an M1SensorsReader. Returns nullptr on failure.
+  static std::unique_ptr<M1SensorsReader> Create();
+
+  // Reads temperature sensors. Virtual for testing.
+  virtual TemperaturesCelsius ReadTemperatures();
+
+ protected:
+  M1SensorsReader(base::ScopedCFTypeRef<IOHIDEventSystemClientRef> system);
+
+ private:
+  base::ScopedCFTypeRef<IOHIDEventSystemClientRef> system_;
+};
+
+}  // namespace power_metrics
+
+#endif  // COMPONENTS_POWER_METRICS_M1_SENSORS_MAC_H_
diff --git a/components/power_metrics/m1_sensors_mac.mm b/components/power_metrics/m1_sensors_mac.mm
new file mode 100644
index 0000000..0477e77
--- /dev/null
+++ b/components/power_metrics/m1_sensors_mac.mm
@@ -0,0 +1,123 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "components/power_metrics/m1_sensors_mac.h"
+
+#import <Foundation/Foundation.h>
+#import <IOKit/hid/IOHIDDeviceKeys.h>
+#import <IOKit/hidsystem/IOHIDServiceClient.h>
+
+#include <utility>
+
+#include "base/mac/foundation_util.h"
+#include "base/memory/ptr_util.h"
+#include "components/power_metrics/m1_sensors_internal_types_mac.h"
+
+extern "C" {
+
+extern IOHIDEventSystemClientRef IOHIDEventSystemClientCreate(CFAllocatorRef);
+extern int IOHIDEventSystemClientSetMatching(IOHIDEventSystemClientRef client,
+                                             CFDictionaryRef match);
+extern CFTypeRef IOHIDServiceClientCopyEvent(IOHIDServiceClientRef,
+                                             int64_t,
+                                             int32_t,
+                                             int64_t);
+extern double IOHIDEventGetFloatValue(CFTypeRef, int32_t);
+}
+
+namespace power_metrics {
+
+namespace {
+
+absl::optional<double> GetEventFloatValue(IOHIDServiceClientRef service,
+                                          int64_t event_type) {
+  base::ScopedCFTypeRef<CFTypeRef> event(
+      IOHIDServiceClientCopyEvent(service, event_type, 0, 0));
+  if (!event)
+    return absl::nullopt;
+  return IOHIDEventGetFloatValue(event, IOHIDEventFieldBase(event_type));
+}
+
+}  // namespace
+
+M1SensorsReader::TemperaturesCelsius::TemperaturesCelsius() = default;
+M1SensorsReader::TemperaturesCelsius::TemperaturesCelsius(
+    const TemperaturesCelsius&) noexcept = default;
+M1SensorsReader::TemperaturesCelsius::~TemperaturesCelsius() = default;
+
+M1SensorsReader::~M1SensorsReader() = default;
+
+// static
+std::unique_ptr<M1SensorsReader> M1SensorsReader::Create() {
+  base::ScopedCFTypeRef<IOHIDEventSystemClientRef> system(
+      IOHIDEventSystemClientCreate(kCFAllocatorDefault));
+
+  if (system == nil)
+    return nullptr;
+
+  NSDictionary* filter = @{
+    @kIOHIDPrimaryUsagePageKey : [NSNumber numberWithInt:kHIDPage_AppleVendor],
+    @kIOHIDPrimaryUsageKey :
+        [NSNumber numberWithInt:kHIDUsage_AppleVendor_TemperatureSensor],
+  };
+  IOHIDEventSystemClientSetMatching(system, base::mac::NSToCFCast(filter));
+
+  return base::WrapUnique(new M1SensorsReader(std::move(system)));
+}
+
+M1SensorsReader::TemperaturesCelsius M1SensorsReader::ReadTemperatures() {
+  base::ScopedCFTypeRef<CFArrayRef> services(
+      IOHIDEventSystemClientCopyServices(system_.get()));
+
+  // There are multiple temperature sensors on P-Cores and E-Cores. Count and
+  // sum values to compute average later.
+  int num_p_core_temp = 0;
+  int num_e_core_temp = 0;
+  double sum_p_core_temp = 0;
+  double sum_e_core_temp = 0;
+
+  for (id service_obj in base::mac::CFToNSCast(services.get())) {
+    IOHIDServiceClientRef service = (IOHIDServiceClientRef)service_obj;
+
+    base::ScopedCFTypeRef<CFStringRef> product_cf(
+        base::mac::CFCast<CFStringRef>(
+            IOHIDServiceClientCopyProperty(service, CFSTR(kIOHIDProductKey))));
+    if (product_cf == nil)
+      continue;
+
+    if ([base::mac::CFToNSCast(product_cf.get())
+            hasPrefix:@"pACC MTR Temp Sensor"]) {
+      absl::optional<double> temp =
+          GetEventFloatValue(service, kIOHIDEventTypeTemperature);
+      if (temp.has_value()) {
+        num_p_core_temp += 1;
+        sum_p_core_temp += temp.value();
+      }
+    }
+
+    if ([base::mac::CFToNSCast(product_cf.get())
+            hasPrefix:@"eACC MTR Temp Sensor"]) {
+      absl::optional<double> temp =
+          GetEventFloatValue(service, kIOHIDEventTypeTemperature);
+      if (temp.has_value()) {
+        num_e_core_temp += 1;
+        sum_e_core_temp += temp.value();
+      }
+    }
+  }
+
+  TemperaturesCelsius temperatures;
+  if (num_p_core_temp > 0)
+    temperatures.p_cores = sum_p_core_temp / num_p_core_temp;
+  if (num_e_core_temp > 0)
+    temperatures.e_cores = sum_e_core_temp / num_e_core_temp;
+
+  return temperatures;
+}
+
+M1SensorsReader::M1SensorsReader(
+    base::ScopedCFTypeRef<IOHIDEventSystemClientRef> system)
+    : system_(std::move(system)) {}
+
+}  // namespace power_metrics
diff --git a/components/printing/test/print_render_frame_helper_browsertest.cc b/components/printing/test/print_render_frame_helper_browsertest.cc
index cf44f23c..4d1d51e 100644
--- a/components/printing/test/print_render_frame_helper_browsertest.cc
+++ b/components/printing/test/print_render_frame_helper_browsertest.cc
@@ -118,6 +118,29 @@
 // A web page to simulate the print preview page.
 const char kPrintPreviewHTML[] =
     "<body><p id=\"pdf-viewer\">Hello World!</p></body>";
+
+const char kHTMLWithManyLinesOfText[] =
+    "<html><head><style>"
+    "p { font-size: 24px; }"
+    "</style></head><body>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "<p>The quick brown fox jumped over the lazy dog.</p>"
+    "</body></html>";
 #endif  // BUILDFLAG(ENABLE_PRINT_PREVIEW)
 #endif  // !BUILDFLAG(IS_CHROMEOS_ASH)
 
@@ -1022,6 +1045,13 @@
               preview_ui()->has_custom_page_size_style());
   }
 
+  void SetLetterMediaSize() {
+    base::Value* media_size_value = print_settings().SetKey(
+        kSettingMediaSize, base::Value(base::Value::Type::DICTIONARY));
+    media_size_value->SetIntKey(kSettingMediaSizeWidthMicrons, 215900);
+    media_size_value->SetIntKey(kSettingMediaSizeHeightMicrons, 279400);
+  }
+
   base::Value& print_settings() { return print_settings_; }
 
  private:
@@ -1526,6 +1556,91 @@
   OnClosePrintPreviewDialog();
 }
 
+TEST_F(PrintRenderFrameHelperPreviewTest, PrintPreviewForManyLinesOfText) {
+  LoadHTML(kHTMLWithManyLinesOfText);
+
+  SetLetterMediaSize();
+
+  OnPrintPreview();
+
+  EXPECT_EQ(0u, preview_ui()->print_preview_pages_remaining());
+  VerifyDidPreviewPage(true, 0);
+  VerifyPreviewPageCount(1);
+  VerifyPrintPreviewCancelled(false);
+  VerifyPrintPreviewFailed(false);
+  VerifyPrintPreviewGenerated(true);
+  VerifyPagesPrinted(false);
+
+  OnClosePrintPreviewDialog();
+}
+
+TEST_F(PrintRenderFrameHelperPreviewTest,
+       PrintPreviewForManyLinesOfTextWithScaling) {
+  LoadHTML(kHTMLWithManyLinesOfText);
+
+  SetLetterMediaSize();
+  print_settings().SetIntKey(kSettingScaleFactor, 200);
+
+  OnPrintPreview();
+
+  constexpr int kExpectedPageCount = 3;
+  EXPECT_EQ(0u, preview_ui()->print_preview_pages_remaining());
+  for (int i = 0; i < kExpectedPageCount; ++i)
+    VerifyDidPreviewPage(true, i);
+  VerifyPreviewPageCount(kExpectedPageCount);
+  VerifyPrintPreviewCancelled(false);
+  VerifyPrintPreviewFailed(false);
+  VerifyPrintPreviewGenerated(true);
+  VerifyPagesPrinted(false);
+
+  OnClosePrintPreviewDialog();
+}
+
+TEST_F(PrintRenderFrameHelperPreviewTest,
+       PrintPreviewForManyLinesOfTextWithTextSelection) {
+  LoadHTML(kHTMLWithManyLinesOfText);
+  GetMainFrame()->ExecuteCommand("SelectAll");
+
+  SetLetterMediaSize();
+  print_settings().SetBoolKey(kSettingShouldPrintSelectionOnly, true);
+
+  OnPrintPreview();
+
+  EXPECT_EQ(0u, preview_ui()->print_preview_pages_remaining());
+  VerifyDidPreviewPage(true, 0);
+  VerifyPreviewPageCount(1);
+  VerifyPrintPreviewCancelled(false);
+  VerifyPrintPreviewFailed(false);
+  VerifyPrintPreviewGenerated(true);
+  VerifyPagesPrinted(false);
+
+  OnClosePrintPreviewDialog();
+}
+
+TEST_F(PrintRenderFrameHelperPreviewTest,
+       PrintPreviewForManyLinesOfTextWithTextSelectionAndScaling) {
+  LoadHTML(kHTMLWithManyLinesOfText);
+  GetMainFrame()->ExecuteCommand("SelectAll");
+
+  SetLetterMediaSize();
+  print_settings().SetBoolKey(kSettingShouldPrintSelectionOnly, true);
+  print_settings().SetIntKey(kSettingScaleFactor, 200);
+
+  OnPrintPreview();
+
+  EXPECT_EQ(0u, preview_ui()->print_preview_pages_remaining());
+  VerifyDidPreviewPage(true, 0);
+  // TODO(crbug.com/1023416): The preview should contain 3 pages, like the
+  // PrintPreviewForManyLinesOfTextWithScaling test case.
+  VerifyPreviewPageCount(1);
+  VerifyPrintPreviewCancelled(false);
+  VerifyPrintPreviewFailed(false);
+  VerifyPrintPreviewGenerated(true);
+  VerifyPagesPrinted(false);
+
+  OnClosePrintPreviewDialog();
+}
+
 // Tests that cancelling print preview works.
 TEST_F(PrintRenderFrameHelperPreviewTest, PrintPreviewCancel) {
   LoadHTML(kLongPageHTML);
diff --git a/components/reporting/proto/synced/metric_data.proto b/components/reporting/proto/synced/metric_data.proto
index 33dbe00..3108fdc3 100644
--- a/components/reporting/proto/synced/metric_data.proto
+++ b/components/reporting/proto/synced/metric_data.proto
@@ -268,6 +268,20 @@
   optional string input_device_name = 6;
 }
 
+// Boot Performance telemetry data
+message BootPerformanceTelemetry {
+  // Total time when to boot up.
+  optional int64 boot_up_seconds = 1;
+  // The Timestamp when power came on.
+  optional int64 boot_up_timestamp_seconds = 2;
+  // Total time since shutdown start to power off.
+  optional int64 shutdown_seconds = 3;
+  // Timestamp when shutdown.
+  optional int64 shutdown_timestamp_seconds = 4;
+  // Shutdown reason.
+  optional string shutdown_reason = 5;
+}
+
 // Data that can change over time, collected and reported every specific period
 // of time or when an event occur.
 message TelemetryData {
@@ -279,6 +293,8 @@
   optional AudioTelemetry audio_telemetry = 2;
   // Usb telemetry data
   optional UsbTelemetry usb_telemetry = 3;
+  // Boot Performance telemetry data.
+  optional BootPerformanceTelemetry boot_performance_telemetry = 4;
 }
 
 enum MetricEventType {
diff --git a/components/segmentation_platform/internal/execution/segmentation_model_executor.cc b/components/segmentation_platform/internal/execution/segmentation_model_executor.cc
index e03fd07..f4fa1fe 100644
--- a/components/segmentation_platform/internal/execution/segmentation_model_executor.cc
+++ b/components/segmentation_platform/internal/execution/segmentation_model_executor.cc
@@ -31,8 +31,7 @@
         "length of input data does not match length of tensor");
   }
 
-  tflite::task::core::PopulateTensor<float>(input, input_tensors[0]);
-  return absl::OkStatus();
+  return tflite::task::core::PopulateTensor<float>(input, input_tensors[0]);
 }
 
 float SegmentationModelExecutor::Postprocess(
@@ -43,7 +42,12 @@
   DCHECK_EQ(1u, output_tensors[0]->bytes / sizeof(output_tensors[0]->type));
 
   std::vector<float> data;
-  tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  absl::Status status =
+      tflite::task::core::PopulateVector<float>(output_tensors[0], &data);
+  if (!status.ok()) {
+    NOTREACHED();
+    return -1;
+  }
   DCHECK_EQ(1u, data.size());
   return data[0];
 }
diff --git a/components/signin/internal/identity_manager/BUILD.gn b/components/signin/internal/identity_manager/BUILD.gn
index 15d8659..08370fd 100644
--- a/components/signin/internal/identity_manager/BUILD.gn
+++ b/components/signin/internal/identity_manager/BUILD.gn
@@ -35,6 +35,7 @@
     "primary_account_manager.h",
     "primary_account_mutator_impl.cc",
     "primary_account_mutator_impl.h",
+    "primary_account_policy_manager.h",
     "profile_oauth2_token_service.cc",
     "profile_oauth2_token_service.h",
     "profile_oauth2_token_service_builder.cc",
@@ -99,6 +100,13 @@
   if (is_chromeos_ash) {
     deps += [ "//ash/constants" ]
     public_deps += [ "//ash/components/account_manager" ]
+  } else {
+    sources += [
+      "primary_account_policy_manager_impl.cc",
+      "primary_account_policy_manager_impl.h",
+    ]
+
+    public_deps += [ "//components/prefs" ]
   }
 
   if (!is_android && !is_ios) {
@@ -181,6 +189,8 @@
       "//ash/constants",
       "//components/account_manager_core:test_support",
     ]
+  } else {
+    sources += [ "primary_account_policy_manager_impl_unittest.cc" ]
   }
 
   if (is_ios) {
diff --git a/components/signin/internal/identity_manager/primary_account_manager.cc b/components/signin/internal/identity_manager/primary_account_manager.cc
index 89b922cc..741a2b97 100644
--- a/components/signin/internal/identity_manager/primary_account_manager.cc
+++ b/components/signin/internal/identity_manager/primary_account_manager.cc
@@ -17,6 +17,7 @@
 #include "components/prefs/pref_registry_simple.h"
 #include "components/prefs/pref_service.h"
 #include "components/signin/internal/identity_manager/account_tracker_service.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager.h"
 #include "components/signin/internal/identity_manager/profile_oauth2_token_service.h"
 #include "components/signin/public/base/account_consistency_method.h"
 #include "components/signin/public/base/signin_client.h"
@@ -29,10 +30,13 @@
 PrimaryAccountManager::PrimaryAccountManager(
     SigninClient* client,
     ProfileOAuth2TokenService* token_service,
-    AccountTrackerService* account_tracker_service)
+    AccountTrackerService* account_tracker_service,
+    std::unique_ptr<PrimaryAccountPolicyManager> policy_manager)
     : client_(client),
       token_service_(token_service),
-      account_tracker_service_(account_tracker_service) {
+      account_tracker_service_(account_tracker_service),
+      initialized_(false),
+      policy_manager_(std::move(policy_manager)) {
   DCHECK(client_);
   DCHECK(account_tracker_service_);
 }
@@ -115,6 +119,9 @@
     SetPrimaryAccountInternal(account_info, consented);
   }
 
+  if (policy_manager_) {
+    policy_manager_->InitializePolicy(local_state, this);
+  }
   // It is important to only load credentials after starting to observe the
   // token service.
   token_service_->AddObserver(this);
diff --git a/components/signin/internal/identity_manager/primary_account_manager.h b/components/signin/internal/identity_manager/primary_account_manager.h
index dab27fa..04671a7 100644
--- a/components/signin/internal/identity_manager/primary_account_manager.h
+++ b/components/signin/internal/identity_manager/primary_account_manager.h
@@ -18,6 +18,8 @@
 #ifndef COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_MANAGER_H_
 #define COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_MANAGER_H_
 
+#include <memory>
+
 #include "base/memory/raw_ptr.h"
 #include "base/observer_list.h"
 #include "base/observer_list_types.h"
@@ -31,6 +33,7 @@
 class AccountTrackerService;
 class PrefRegistrySimple;
 class PrefService;
+class PrimaryAccountPolicyManager;
 class ProfileOAuth2TokenService;
 
 namespace signin_metrics {
@@ -56,9 +59,11 @@
     kRemoveAllAccounts,
   };
 
-  PrimaryAccountManager(SigninClient* client,
-                        ProfileOAuth2TokenService* token_service,
-                        AccountTrackerService* account_tracker_service);
+  PrimaryAccountManager(
+      SigninClient* client,
+      ProfileOAuth2TokenService* token_service,
+      AccountTrackerService* account_tracker_service,
+      std::unique_ptr<PrimaryAccountPolicyManager> policy_manager);
 
   PrimaryAccountManager(const PrimaryAccountManager&) = delete;
   PrimaryAccountManager& operator=(const PrimaryAccountManager&) = delete;
@@ -179,6 +184,7 @@
   // this field.
   CoreAccountInfo primary_account_info_;
 
+  std::unique_ptr<PrimaryAccountPolicyManager> policy_manager_;
   base::ObserverList<Observer> observers_;
 };
 
diff --git a/components/signin/internal/identity_manager/primary_account_manager_unittest.cc b/components/signin/internal/identity_manager/primary_account_manager_unittest.cc
index 2100f76..d63af1fd92 100644
--- a/components/signin/internal/identity_manager/primary_account_manager_unittest.cc
+++ b/components/signin/internal/identity_manager/primary_account_manager_unittest.cc
@@ -23,6 +23,7 @@
 #include "components/signin/internal/identity_manager/account_fetcher_service.h"
 #include "components/signin/internal/identity_manager/account_tracker_service.h"
 #include "components/signin/internal/identity_manager/fake_profile_oauth2_token_service_delegate.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager.h"
 #include "components/signin/internal/identity_manager/profile_oauth2_token_service.h"
 #include "components/signin/public/base/signin_pref_names.h"
 #include "components/signin/public/base/signin_switches.h"
@@ -30,6 +31,10 @@
 #include "components/sync_preferences/testing_pref_service_syncable.h"
 #include "testing/gtest/include/gtest/gtest.h"
 
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
+#endif
+
 using signin::ConsentLevel;
 
 class PrimaryAccountManagerTest : public testing::Test,
@@ -74,8 +79,20 @@
 
   void CreatePrimaryAccountManager() {
     DCHECK(!manager_);
+    // Supply the primary account manager with a policy manager to reflect
+    // production usage: null on ChromeOS, a PrimaryAccountPolicyManagerImpl on
+    // other platforms.
+    std::unique_ptr<PrimaryAccountPolicyManager> policy_manager;
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+    policy_manager =
+        std::make_unique<PrimaryAccountPolicyManagerImpl>(&test_signin_client_);
+    policy_manager_ =
+        static_cast<PrimaryAccountPolicyManagerImpl*>(policy_manager.get());
+#endif
+
     manager_ = std::make_unique<PrimaryAccountManager>(
-        &test_signin_client_, &token_service_, &account_tracker_);
+        &test_signin_client_, &token_service_, &account_tracker_,
+        std::move(policy_manager));
     manager_->Initialize(&local_state_);
     manager_->AddObserver(this);
   }
@@ -122,6 +139,9 @@
   ProfileOAuth2TokenService token_service_;
   AccountTrackerService account_tracker_;
   AccountFetcherService account_fetcher_;
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+  raw_ptr<PrimaryAccountPolicyManagerImpl> policy_manager_;
+#endif
   std::unique_ptr<PrimaryAccountManager> manager_;
   std::vector<std::string> oauth_tokens_fetched_;
   std::vector<std::string> cookies_;
@@ -222,6 +242,33 @@
                                 signin_metrics::SignoutDelete::kIgnoreMetric);
   EXPECT_FALSE(manager_->HasPrimaryAccount(ConsentLevel::kSignin));
 }
+
+TEST_F(PrimaryAccountManagerTest, ProhibitedAtStartup) {
+  CoreAccountId account_id = AddToAccountTracker("gaia_id", "user@gmail.com");
+  user_prefs_.SetString(prefs::kGoogleServicesAccountId, account_id.ToString());
+  local_state_.SetString(prefs::kGoogleServicesUsernamePattern,
+                         ".*@google.com");
+  CreatePrimaryAccountManager();
+  // Currently signed in user is prohibited by policy, so should be signed out.
+  EXPECT_EQ("", manager_->GetPrimaryAccountInfo(ConsentLevel::kSync).email);
+  EXPECT_EQ(CoreAccountId(),
+            manager_->GetPrimaryAccountId(ConsentLevel::kSync));
+}
+
+TEST_F(PrimaryAccountManagerTest, ProhibitedAfterStartup) {
+  CoreAccountId account_id = AddToAccountTracker("gaia_id", "user@gmail.com");
+  user_prefs_.SetString(prefs::kGoogleServicesAccountId, account_id.ToString());
+  CreatePrimaryAccountManager();
+  EXPECT_EQ("user@gmail.com",
+            manager_->GetPrimaryAccountInfo(ConsentLevel::kSync).email);
+  EXPECT_EQ(account_id, manager_->GetPrimaryAccountId(ConsentLevel::kSync));
+  // Update the profile - user should be signed out.
+  local_state_.SetString(prefs::kGoogleServicesUsernamePattern,
+                         ".*@google.com");
+  EXPECT_EQ("", manager_->GetPrimaryAccountInfo(ConsentLevel::kSync).email);
+  EXPECT_EQ(CoreAccountId(),
+            manager_->GetPrimaryAccountId(ConsentLevel::kSync));
+}
 #endif
 
 // Regression test for https://crbug.com/1155519.
@@ -291,6 +338,19 @@
   EXPECT_EQ(account_id, manager_->GetPrimaryAccountId(ConsentLevel::kSync));
 }
 
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+TEST_F(PrimaryAccountManagerTest, SigninNotAllowed) {
+  std::string user("user@google.com");
+  CoreAccountId account_id = AddToAccountTracker("gaia_id", user);
+  user_prefs_.SetString(prefs::kGoogleServicesAccountId, account_id.ToString());
+  user_prefs_.SetBoolean(prefs::kSigninAllowed, false);
+  CreatePrimaryAccountManager();
+  // Currently signing in is prohibited by policy, so should be signed out.
+  EXPECT_EQ("", manager_->GetPrimaryAccountInfo(ConsentLevel::kSync).email);
+  EXPECT_TRUE(manager_->GetPrimaryAccountId(ConsentLevel::kSync).empty());
+}
+#endif
+
 TEST_F(PrimaryAccountManagerTest, GaiaIdMigration) {
 #if BUILDFLAG(IS_CHROMEOS_ASH)
   base::test::ScopedFeatureList scoped_feature_list;
diff --git a/components/signin/internal/identity_manager/primary_account_policy_manager.h b/components/signin/internal/identity_manager/primary_account_policy_manager.h
new file mode 100644
index 0000000..f5dedd0
--- /dev/null
+++ b/components/signin/internal/identity_manager/primary_account_policy_manager.h
@@ -0,0 +1,29 @@
+// Copyright 2014 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_POLICY_MANAGER_H_
+#define COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_POLICY_MANAGER_H_
+
+class PrefService;
+class PrimaryAccountManager;
+
+class PrimaryAccountPolicyManager {
+ public:
+  PrimaryAccountPolicyManager() = default;
+
+  PrimaryAccountPolicyManager(const PrimaryAccountPolicyManager&) = delete;
+  PrimaryAccountPolicyManager& operator=(const PrimaryAccountPolicyManager&) =
+      delete;
+
+  virtual ~PrimaryAccountPolicyManager() = default;
+
+  // On platforms where PrimaryAccountManager is responsible for dealing with
+  // invalid username policy updates, we need to check this during
+  // initialization and sign the user out.
+  virtual void InitializePolicy(
+      PrefService* local_state,
+      PrimaryAccountManager* primary_account_manager) = 0;
+};
+
+#endif  // COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_POLICY_MANAGER_H_
diff --git a/components/signin/internal/identity_manager/primary_account_policy_manager_impl.cc b/components/signin/internal/identity_manager/primary_account_policy_manager_impl.cc
new file mode 100644
index 0000000..9116698
--- /dev/null
+++ b/components/signin/internal/identity_manager/primary_account_policy_manager_impl.cc
@@ -0,0 +1,114 @@
+// Copyright 2019 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
+
+#include "base/bind.h"
+#include "base/logging.h"
+#include "build/build_config.h"
+#include "components/signin/internal/identity_manager/primary_account_manager.h"
+#include "components/signin/public/base/signin_client.h"
+#include "components/signin/public/base/signin_metrics.h"
+#include "components/signin/public/base/signin_pref_names.h"
+#include "components/signin/public/identity_manager/account_info.h"
+#include "components/signin/public/identity_manager/identity_utils.h"
+
+PrimaryAccountPolicyManagerImpl::PrimaryAccountPolicyManagerImpl(
+    SigninClient* client)
+    : client_(client) {}
+
+PrimaryAccountPolicyManagerImpl::~PrimaryAccountPolicyManagerImpl() {
+  local_state_pref_registrar_.RemoveAll();
+}
+
+void PrimaryAccountPolicyManagerImpl::InitializePolicy(
+    PrefService* local_state,
+    PrimaryAccountManager* primary_account_manager) {
+  // local_state can be null during unit tests.
+  if (local_state) {
+    local_state_pref_registrar_.Init(local_state);
+    local_state_pref_registrar_.Add(
+        prefs::kGoogleServicesUsernamePattern,
+        base::BindRepeating(&PrimaryAccountPolicyManagerImpl::
+                                OnGoogleServicesUsernamePatternChanged,
+                            weak_pointer_factory_.GetWeakPtr(),
+                            primary_account_manager));
+  }
+  signin_allowed_.Init(
+      prefs::kSigninAllowed, client_->GetPrefs(),
+      base::BindRepeating(
+          &PrimaryAccountPolicyManagerImpl::OnSigninAllowedPrefChanged,
+          base::Unretained(this), primary_account_manager));
+
+  CoreAccountInfo account_info = primary_account_manager->GetPrimaryAccountInfo(
+      signin::ConsentLevel::kSync);
+  if (!account_info.account_id.empty() &&
+      (!IsAllowedUsername(account_info.email) || !IsSigninAllowed())) {
+    // User is signed in, but the username is invalid or signin is no longer
+    // allowed, so the user must be sign out.
+    //
+    // This may happen in the following cases:
+    //   a. The user has toggled off signin allowed in settings.
+    //   b. The administrator changed the policy since the last signin.
+    //
+    // Note: The token service has not yet loaded its credentials, so accounts
+    // cannot be revoked here.
+    //
+    // On desktop, when PrimaryAccountManager is initializing, the profile was
+    // not yet marked with sign out allowed. Therefore sign out is not allowed
+    // and all calls to RevokeSyncConsent() and ClearPrimaryAccount() methods
+    // are no-op.
+    //
+    // TODO(msarda): RevokeSyncConsent() method do not guarantee that the sync
+    // consent can really be revoked (this depends on whether sign out is
+    // allowed). Add a check here on desktop to make it clear that
+    // RevokeSyncConsent() does not do anything.
+    primary_account_manager->RevokeSyncConsent(
+        signin_metrics::SIGNIN_PREF_CHANGED_DURING_SIGNIN,
+        signin_metrics::SignoutDelete::kIgnoreMetric);
+  }
+}
+
+void PrimaryAccountPolicyManagerImpl::OnGoogleServicesUsernamePatternChanged(
+    PrimaryAccountManager* primary_account_manager) {
+  if (primary_account_manager->HasPrimaryAccount(signin::ConsentLevel::kSync) &&
+      !IsAllowedUsername(
+          primary_account_manager
+              ->GetPrimaryAccountInfo(signin::ConsentLevel::kSync)
+              .email)) {
+    // Signed in user is invalid according to the current policy so sign
+    // the user out.
+    primary_account_manager->ClearPrimaryAccount(
+        signin_metrics::GOOGLE_SERVICE_NAME_PATTERN_CHANGED,
+        signin_metrics::SignoutDelete::kIgnoreMetric);
+  }
+}
+
+bool PrimaryAccountPolicyManagerImpl::IsSigninAllowed() const {
+  return signin_allowed_.GetValue();
+}
+
+void PrimaryAccountPolicyManagerImpl::OnSigninAllowedPrefChanged(
+    PrimaryAccountManager* primary_account_manager) {
+  if (!IsSigninAllowed() &&
+      primary_account_manager->HasPrimaryAccount(signin::ConsentLevel::kSync)) {
+    VLOG(0) << "IsSigninAllowed() set to false, signing out the user";
+    primary_account_manager->ClearPrimaryAccount(
+        signin_metrics::SIGNOUT_PREF_CHANGED,
+        signin_metrics::SignoutDelete::kIgnoreMetric);
+  }
+}
+
+bool PrimaryAccountPolicyManagerImpl::IsAllowedUsername(
+    const std::string& username) const {
+  const PrefService* local_state = local_state_pref_registrar_.prefs();
+
+  // TODO(crbug.com/908121): We need to deal for now with the fact that many
+  // unit tests have a null |local_state| passed to InitializePolicy(), in which
+  // case all usernames are considered 'allowed'.
+  if (!local_state)
+    return true;
+
+  return signin::IsUsernameAllowedByPatternFromPrefs(local_state, username);
+}
diff --git a/components/signin/internal/identity_manager/primary_account_policy_manager_impl.h b/components/signin/internal/identity_manager/primary_account_policy_manager_impl.h
new file mode 100644
index 0000000..fa720cc
--- /dev/null
+++ b/components/signin/internal/identity_manager/primary_account_policy_manager_impl.h
@@ -0,0 +1,66 @@
+// Copyright 2019 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_POLICY_MANAGER_IMPL_H_
+#define COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_POLICY_MANAGER_IMPL_H_
+
+#include <string>
+
+#include "base/gtest_prod_util.h"
+#include "base/memory/raw_ptr.h"
+#include "base/memory/weak_ptr.h"
+#include "components/prefs/pref_change_registrar.h"
+#include "components/prefs/pref_member.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager.h"
+
+class PrefService;
+class PrimaryAccountManager;
+class SigninClient;
+
+class PrimaryAccountPolicyManagerImpl : public PrimaryAccountPolicyManager {
+ public:
+  explicit PrimaryAccountPolicyManagerImpl(SigninClient* client);
+
+  PrimaryAccountPolicyManagerImpl(const PrimaryAccountPolicyManagerImpl&) =
+      delete;
+  PrimaryAccountPolicyManagerImpl& operator=(
+      const PrimaryAccountPolicyManagerImpl&) = delete;
+
+  ~PrimaryAccountPolicyManagerImpl() override;
+
+  // PrimaryAccountPolicyManager:
+  void InitializePolicy(
+      PrefService* local_state,
+      PrimaryAccountManager* primary_account_manager) override;
+
+ private:
+  FRIEND_TEST_ALL_PREFIXES(PrimaryAccountPolicyManagerImplTest, Prohibited);
+  FRIEND_TEST_ALL_PREFIXES(PrimaryAccountPolicyManagerImplTest,
+                           TestAlternateWildcard);
+
+  // Returns true if a signin to Chrome is allowed (by policy or pref).
+  bool IsSigninAllowed() const;
+
+  void OnSigninAllowedPrefChanged(
+      PrimaryAccountManager* primary_account_manager);
+  void OnGoogleServicesUsernamePatternChanged(
+      PrimaryAccountManager* primary_account_manager);
+
+  // Returns true if the passed username is allowed by policy.
+  bool IsAllowedUsername(const std::string& username) const;
+
+  raw_ptr<SigninClient> client_;
+
+  // Helper object to listen for changes to signin preferences stored in non-
+  // profile-specific local prefs (like kGoogleServicesUsernamePattern).
+  PrefChangeRegistrar local_state_pref_registrar_;
+
+  // Helper object to listen for changes to the signin allowed preference.
+  BooleanPrefMember signin_allowed_;
+
+  base::WeakPtrFactory<PrimaryAccountPolicyManagerImpl> weak_pointer_factory_{
+      this};
+};
+
+#endif  // COMPONENTS_SIGNIN_INTERNAL_IDENTITY_MANAGER_PRIMARY_ACCOUNT_POLICY_MANAGER_IMPL_H_
diff --git a/components/signin/internal/identity_manager/primary_account_policy_manager_impl_unittest.cc b/components/signin/internal/identity_manager/primary_account_policy_manager_impl_unittest.cc
new file mode 100644
index 0000000..83df3659
--- /dev/null
+++ b/components/signin/internal/identity_manager/primary_account_policy_manager_impl_unittest.cc
@@ -0,0 +1,74 @@
+// Copyright 2019 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
+
+#include <memory>
+#include <string>
+
+#include "base/test/task_environment.h"
+#include "components/prefs/testing_pref_service.h"
+#include "components/signin/internal/identity_manager/account_tracker_service.h"
+#include "components/signin/internal/identity_manager/fake_profile_oauth2_token_service_delegate.h"
+#include "components/signin/internal/identity_manager/primary_account_manager.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
+#include "components/signin/internal/identity_manager/profile_oauth2_token_service.h"
+#include "components/signin/public/base/account_consistency_method.h"
+#include "components/signin/public/base/signin_pref_names.h"
+#include "components/signin/public/base/test_signin_client.h"
+#include "components/sync_preferences/testing_pref_service_syncable.h"
+#include "testing/gtest/include/gtest/gtest.h"
+
+class PrimaryAccountPolicyManagerImplTest : public testing::Test {
+ public:
+  PrimaryAccountPolicyManagerImplTest()
+      : test_signin_client_(&user_prefs_),
+        token_service_(
+            &user_prefs_,
+            std::make_unique<FakeProfileOAuth2TokenServiceDelegate>()),
+        primary_account_manager_(&test_signin_client_,
+                                 &token_service_,
+                                 &account_tracker_,
+                                 nullptr /*policy_manager*/),
+        policy_manager_(&test_signin_client_) {
+    PrimaryAccountManager::RegisterProfilePrefs(user_prefs_.registry());
+    PrimaryAccountManager::RegisterPrefs(local_state_.registry());
+
+    policy_manager_.InitializePolicy(&local_state_, &primary_account_manager_);
+  }
+
+  ~PrimaryAccountPolicyManagerImplTest() override {
+    test_signin_client_.Shutdown();
+  }
+
+  base::test::TaskEnvironment task_environment_;
+  sync_preferences::TestingPrefServiceSyncable user_prefs_;
+  TestingPrefServiceSimple local_state_;
+  TestSigninClient test_signin_client_;
+  ProfileOAuth2TokenService token_service_;
+  AccountTrackerService account_tracker_;
+  PrimaryAccountManager primary_account_manager_;
+  PrimaryAccountPolicyManagerImpl policy_manager_;
+};
+
+TEST_F(PrimaryAccountPolicyManagerImplTest, Prohibited) {
+  local_state_.SetString(prefs::kGoogleServicesUsernamePattern,
+                         ".*@google.com");
+  EXPECT_TRUE(policy_manager_.IsAllowedUsername("test@google.com"));
+  EXPECT_TRUE(policy_manager_.IsAllowedUsername("happy@google.com"));
+  EXPECT_FALSE(policy_manager_.IsAllowedUsername("test@invalid.com"));
+  EXPECT_FALSE(policy_manager_.IsAllowedUsername("test@notgoogle.com"));
+  EXPECT_FALSE(policy_manager_.IsAllowedUsername(std::string()));
+}
+
+TEST_F(PrimaryAccountPolicyManagerImplTest, TestAlternateWildcard) {
+  // Test to make sure we accept "*@google.com" as a pattern (treat it as if
+  // the admin entered ".*@google.com").
+  local_state_.SetString(prefs::kGoogleServicesUsernamePattern, "*@google.com");
+  EXPECT_TRUE(policy_manager_.IsAllowedUsername("test@google.com"));
+  EXPECT_TRUE(policy_manager_.IsAllowedUsername("happy@google.com"));
+  EXPECT_FALSE(policy_manager_.IsAllowedUsername("test@invalid.com"));
+  EXPECT_FALSE(policy_manager_.IsAllowedUsername("test@notgoogle.com"));
+  EXPECT_FALSE(policy_manager_.IsAllowedUsername(std::string()));
+}
diff --git a/components/signin/public/identity_manager/access_token_fetcher_unittest.cc b/components/signin/public/identity_manager/access_token_fetcher_unittest.cc
index d622989..e9db325 100644
--- a/components/signin/public/identity_manager/access_token_fetcher_unittest.cc
+++ b/components/signin/public/identity_manager/access_token_fetcher_unittest.cc
@@ -14,6 +14,7 @@
 #include "components/prefs/testing_pref_service.h"
 #include "components/signin/internal/identity_manager/account_tracker_service.h"
 #include "components/signin/internal/identity_manager/fake_profile_oauth2_token_service.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
 #include "components/signin/internal/identity_manager/profile_oauth2_token_service_delegate.h"
 #include "components/signin/public/base/signin_pref_names.h"
 #include "components/signin/public/base/test_signin_client.h"
@@ -66,7 +67,8 @@
         account_tracker_(std::make_unique<AccountTrackerService>()),
         primary_account_manager_(&signin_client_,
                                  &token_service_,
-                                 account_tracker_.get()) {
+                                 account_tracker_.get(),
+                                 nullptr /* policy_manager */) {
     AccountTrackerService::RegisterPrefs(pref_service_.registry());
     PrimaryAccountManager::RegisterProfilePrefs(pref_service_.registry());
 
diff --git a/components/signin/public/identity_manager/identity_manager_builder.cc b/components/signin/public/identity_manager/identity_manager_builder.cc
index 4dc5694..f948d70 100644
--- a/components/signin/public/identity_manager/identity_manager_builder.cc
+++ b/components/signin/public/identity_manager/identity_manager_builder.cc
@@ -17,6 +17,7 @@
 #include "components/signin/internal/identity_manager/gaia_cookie_manager_service.h"
 #include "components/signin/internal/identity_manager/primary_account_manager.h"
 #include "components/signin/internal/identity_manager/primary_account_mutator_impl.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager.h"
 #include "components/signin/internal/identity_manager/profile_oauth2_token_service.h"
 #include "components/signin/internal/identity_manager/profile_oauth2_token_service_builder.h"
 #include "components/signin/public/base/account_consistency_method.h"
@@ -40,6 +41,10 @@
 #include "components/signin/internal/identity_manager/accounts_mutator_impl.h"
 #endif
 
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
+#endif
+
 namespace signin {
 
 namespace {
@@ -58,8 +63,13 @@
     ProfileOAuth2TokenService* token_service,
     PrefService* local_state) {
   std::unique_ptr<PrimaryAccountManager> primary_account_manager;
+  std::unique_ptr<PrimaryAccountPolicyManager> policy_manager;
+#if !BUILDFLAG(IS_CHROMEOS_ASH) && !defined(OS_IOS)
+  policy_manager = std::make_unique<PrimaryAccountPolicyManagerImpl>(client);
+#endif
   primary_account_manager = std::make_unique<PrimaryAccountManager>(
-      client, token_service, account_tracker_service);
+      client, token_service, account_tracker_service,
+      std::move(policy_manager));
   primary_account_manager->Initialize(local_state);
   return primary_account_manager;
 }
diff --git a/components/signin/public/identity_manager/identity_manager_unittest.cc b/components/signin/public/identity_manager/identity_manager_unittest.cc
index e04923c..7449b5fe4 100644
--- a/components/signin/public/identity_manager/identity_manager_unittest.cc
+++ b/components/signin/public/identity_manager/identity_manager_unittest.cc
@@ -31,6 +31,7 @@
 #include "components/signin/internal/identity_manager/gaia_cookie_manager_service.h"
 #include "components/signin/internal/identity_manager/primary_account_manager.h"
 #include "components/signin/internal/identity_manager/primary_account_mutator_impl.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
 #include "components/signin/internal/identity_manager/profile_oauth2_token_service_delegate.h"
 #include "components/signin/public/base/account_consistency_method.h"
 #include "components/signin/public/base/consent_level.h"
@@ -395,8 +396,14 @@
 
     DCHECK_EQ(account_consistency, AccountConsistencyMethod::kDisabled)
         << "AccountConsistency is not used by PrimaryAccountManager";
+    std::unique_ptr<PrimaryAccountPolicyManager> policy_manager;
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+    policy_manager =
+        std::make_unique<PrimaryAccountPolicyManagerImpl>(&signin_client_);
+#endif
     auto primary_account_manager = std::make_unique<PrimaryAccountManager>(
-        &signin_client_, token_service.get(), account_tracker_service.get());
+        &signin_client_, token_service.get(), account_tracker_service.get(),
+        std::move(policy_manager));
 
     // Passing this switch ensures that the new PrimaryAccountManager starts
     // with a clean slate. Otherwise PrimaryAccountManager::Initialize will use
diff --git a/components/signin/public/identity_manager/identity_test_environment.cc b/components/signin/public/identity_manager/identity_test_environment.cc
index ca66309..6275bcf 100644
--- a/components/signin/public/identity_manager/identity_test_environment.cc
+++ b/components/signin/public/identity_manager/identity_test_environment.cc
@@ -26,6 +26,7 @@
 #include "components/signin/internal/identity_manager/gaia_cookie_manager_service.h"
 #include "components/signin/internal/identity_manager/primary_account_manager.h"
 #include "components/signin/internal/identity_manager/primary_account_mutator_impl.h"
+#include "components/signin/internal/identity_manager/primary_account_policy_manager_impl.h"
 #include "components/signin/public/base/consent_level.h"
 #include "components/signin/public/base/test_signin_client.h"
 #include "components/signin/public/identity_manager/accounts_mutator.h"
@@ -336,9 +337,15 @@
       signin_client, token_service.get(), account_tracker_service.get(),
       std::make_unique<image_fetcher::FakeImageDecoder>());
 
+  std::unique_ptr<PrimaryAccountPolicyManager> policy_manager;
+#if !BUILDFLAG(IS_CHROMEOS_ASH)
+  policy_manager =
+      std::make_unique<PrimaryAccountPolicyManagerImpl>(signin_client);
+#endif
   std::unique_ptr<PrimaryAccountManager> primary_account_manager =
       std::make_unique<PrimaryAccountManager>(
-          signin_client, token_service.get(), account_tracker_service.get());
+          signin_client, token_service.get(), account_tracker_service.get(),
+          std::move(policy_manager));
   primary_account_manager->Initialize(pref_service);
 
   std::unique_ptr<GaiaCookieManagerService> gaia_cookie_manager_service =
diff --git a/components/translate/core/language_detection/language_detection_model.cc b/components/translate/core/language_detection/language_detection_model.cc
index b0f322fe..4435e064 100644
--- a/components/translate/core/language_detection/language_detection_model.cc
+++ b/components/translate/core/language_detection/language_detection_model.cc
@@ -4,7 +4,7 @@
 
 #include "components/translate/core/language_detection/language_detection_model.h"
 
-#include "base/files/memory_mapped_file.h"
+#include "base/cxx17_backports.h"
 #include "base/metrics/histogram_macros.h"
 #include "base/metrics/histogram_macros_local.h"
 #include "base/strings/utf_string_conversions.h"
@@ -73,19 +73,27 @@
   if (!model_file.IsValid())
     return;
 
-  if (!model_fb_.Initialize(std::move(model_file)))
-    return;
-
   recorder.set_state(
       LanguageDetectionModelState::kModelFileValidAndMemoryMapped);
 
-  auto statusor_classifier = tflite::task::text::nlclassifier::NLClassifier::
-      CreateFromBufferAndOptions(
-          reinterpret_cast<const char*>(model_fb_.data()), model_fb_.length(),
-          {.input_tensor_index = 0,
-           .output_score_tensor_index = 0,
-           .output_label_tensor_index = 2},
-          CreateLangIdResolver());
+  tflite::task::text::NLClassifierOptions options;
+  options.set_input_tensor_index(0);
+  options.set_output_score_tensor_index(0);
+  options.set_output_label_tensor_index(2);
+
+  std::string file_content(model_file.GetLength(), '\0');
+  int bytes_read =
+      model_file.Read(0, base::data(file_content), model_file.GetLength());
+  if (bytes_read != model_file.GetLength()) {
+    return;
+  }
+  *options.mutable_base_options()
+       ->mutable_model_file()
+       ->mutable_file_content() = std::move(file_content);
+
+  auto statusor_classifier =
+      tflite::task::text::nlclassifier::NLClassifier::CreateFromOptions(
+          options, CreateLangIdResolver());
   if (!statusor_classifier.ok()) {
     LOCAL_HISTOGRAM_BOOLEAN("LanguageDetection.TFLiteModel.InvalidModelFile",
                             true);
diff --git a/components/translate/core/language_detection/language_detection_model.h b/components/translate/core/language_detection/language_detection_model.h
index aa7ca26..5d28006 100644
--- a/components/translate/core/language_detection/language_detection_model.h
+++ b/components/translate/core/language_detection/language_detection_model.h
@@ -6,7 +6,8 @@
 #define COMPONENTS_TRANSLATE_CORE_LANGUAGE_DETECTION_LANGUAGE_DETECTION_MODEL_H_
 
 #include <string>
-#include "base/files/memory_mapped_file.h"
+
+#include "base/files/file.h"
 
 namespace tflite {
 namespace task {
@@ -70,11 +71,6 @@
   std::pair<std::string, float> DetectTopLanguage(
       const std::string& sampled_str) const;
 
-  // A memory-mapped file that contains the TFLite model used for
-  // determining the language of a page. This must be valid in order
-  // to evaluate the model owned by |this|.
-  base::MemoryMappedFile model_fb_;
-
   // The tflite classifier that can determine the language of text.
   std::unique_ptr<tflite::task::text::nlclassifier::NLClassifier>
       lang_detection_model_;
diff --git a/components/translate/core/language_detection/language_detection_model_unittest.cc b/components/translate/core/language_detection/language_detection_model_unittest.cc
index 1f70c31..d9e664a 100644
--- a/components/translate/core/language_detection/language_detection_model_unittest.cc
+++ b/components/translate/core/language_detection/language_detection_model_unittest.cc
@@ -55,8 +55,7 @@
       LanguageDetectionModelState::kModelFileInvalid, 1);
 }
 
-// TODO(crbug.com/1240561): Fix flaky test.
-TEST(LanguageDetectionModelTest, DISABLED_UnsupportedModelFileProvided) {
+TEST(LanguageDetectionModelTest, UnsupportedModelFileProvided) {
   base::HistogramTester histogram_tester;
 
   base::File file = CreateInvalidModelFile();
diff --git a/components/viz/service/display/overlay_processor_ozone.cc b/components/viz/service/display/overlay_processor_ozone.cc
index 2bda8ac5..341a536d 100644
--- a/components/viz/service/display/overlay_processor_ozone.cc
+++ b/components/viz/service/display/overlay_processor_ozone.cc
@@ -245,6 +245,12 @@
   return ToEnclosedRect(overlay.display_rect);
 }
 
+void OverlayProcessorOzone::RegisterOverlayRequirement(bool requires_overlay) {
+  // This can be null in unit tests.
+  if (overlay_candidates_)
+    overlay_candidates_->RegisterOverlayRequirement(requires_overlay);
+}
+
 bool OverlayProcessorOzone::SetNativePixmapForCandidate(
     ui::OverlaySurfaceCandidate* candidate,
     const gpu::Mailbox& mailbox,
diff --git a/components/viz/service/display/overlay_processor_ozone.h b/components/viz/service/display/overlay_processor_ozone.h
index c3112b6..337775b 100644
--- a/components/viz/service/display/overlay_processor_ozone.h
+++ b/components/viz/service/display/overlay_processor_ozone.h
@@ -36,6 +36,7 @@
       OverlayCandidateList* surfaces) override;
   gfx::Rect GetOverlayDamageRectForOutputSurface(
       const OverlayCandidate& candidate) const override;
+  void RegisterOverlayRequirement(bool requires_overlay) override;
 
  private:
   // Populates |native_pixmap| and |native_pixmap_unique_id| in |candidate|
diff --git a/components/viz/service/display/overlay_processor_using_strategy.cc b/components/viz/service/display/overlay_processor_using_strategy.cc
index a4b1cfc..58658cd 100644
--- a/components/viz/service/display/overlay_processor_using_strategy.cc
+++ b/components/viz/service/display/overlay_processor_using_strategy.cc
@@ -517,12 +517,15 @@
                                    render_pass, *candidates);
   }
 
+  bool has_required_overlay = false;
   for (auto&& candidate : proposed_candidates) {
     // Underlays change the material so we save it here to record proper UMA.
     DrawQuad::Material quad_material =
         candidate.strategy->GetUMAEnum() != OverlayStrategy::kUnknown
             ? candidate.quad_iter->material
             : DrawQuad::Material::kInvalid;
+    if (candidate.candidate.requires_overlay)
+      has_required_overlay = true;
 
     bool used_overlay = candidate.strategy->AttemptPrioritized(
         output_color_matrix, render_pass_backdrop_filters, resource_provider,
@@ -581,9 +584,11 @@
           UpdateDownscalingCapabilities(scale_factor, /*success=*/true);
         }
       }
+      RegisterOverlayRequirement(has_required_overlay);
       return true;
     }
   }
+  RegisterOverlayRequirement(has_required_overlay);
 
   if (proposed_candidates.size() == 0) {
     LogStrategyEnumUMA(num_proposed_pre_sort != 0
diff --git a/components/viz/service/display/overlay_processor_using_strategy.h b/components/viz/service/display/overlay_processor_using_strategy.h
index f2165277..a4220a74 100644
--- a/components/viz/service/display/overlay_processor_using_strategy.h
+++ b/components/viz/service/display/overlay_processor_using_strategy.h
@@ -183,6 +183,11 @@
       const OverlayProcessorInterface::OutputSurfaceOverlayPlane* primary_plane,
       OverlayCandidateList* candidate_list);
 
+  // This should be called during overlay processing to register whether or not
+  // there is a candidate that requires an overlay so that the manager can allow
+  // the overlay on the display with the requirement only.
+  virtual void RegisterOverlayRequirement(bool requires_overlay) {}
+
  protected:
   virtual gfx::Rect GetOverlayDamageRectForOutputSurface(
       const OverlayCandidate& overlay) const;
diff --git a/components/viz/service/frame_sinks/external_begin_frame_source_android.cc b/components/viz/service/frame_sinks/external_begin_frame_source_android.cc
index 49f8b53..e189e0fd 100644
--- a/components/viz/service/frame_sinks/external_begin_frame_source_android.cc
+++ b/components/viz/service/frame_sinks/external_begin_frame_source_android.cc
@@ -4,19 +4,215 @@
 
 #include "components/viz/service/frame_sinks/external_begin_frame_source_android.h"
 
+#include <dlfcn.h>
+#include <sys/types.h>
+
+#include "base/android/build_info.h"
 #include "base/android/jni_android.h"
+#include "base/logging.h"
+#include "base/trace_event/trace_event.h"
 #include "components/viz/service/service_jni_headers/ExternalBeginFrameSourceAndroid_jni.h"
 
+extern "C" {
+typedef struct AChoreographer AChoreographer;
+typedef void (*AChoreographer_frameCallback64)(int64_t, void*);
+typedef void (*AChoreographer_refreshRateCallback)(int64_t, void*);
+
+using pAChoreographer_getInstance = AChoreographer* (*)();
+using pAChoreographer_postFrameCallback64 =
+    void (*)(AChoreographer*, AChoreographer_frameCallback64, void*);
+using pAChoreographer_registerRefreshRateCallback =
+    void (*)(AChoreographer*, AChoreographer_refreshRateCallback, void*);
+using pAChoreographer_unregisterRefreshRateCallback =
+    void (*)(AChoreographer*, AChoreographer_refreshRateCallback, void*);
+}
+
+namespace {
+
+#define LOAD_FUNCTION(lib, func)                             \
+  do {                                                       \
+    func##Fn = reinterpret_cast<p##func>(dlsym(lib, #func)); \
+    if (!func##Fn) {                                         \
+      supported = false;                                     \
+      LOG(ERROR) << "Unable to load function " << #func;     \
+    }                                                        \
+  } while (0)
+
+struct AChoreographerMethods {
+  static const AChoreographerMethods& Get() {
+    static AChoreographerMethods instance;
+    return instance;
+  }
+
+  bool supported = true;
+  pAChoreographer_getInstance AChoreographer_getInstanceFn;
+  pAChoreographer_postFrameCallback64 AChoreographer_postFrameCallback64Fn;
+  pAChoreographer_registerRefreshRateCallback
+      AChoreographer_registerRefreshRateCallbackFn;
+  pAChoreographer_unregisterRefreshRateCallback
+      AChoreographer_unregisterRefreshRateCallbackFn;
+
+ private:
+  AChoreographerMethods() {
+    void* main_dl_handle = dlopen("libandroid.so", RTLD_NOW);
+    if (!main_dl_handle) {
+      LOG(ERROR) << "Couldnt load libandroid.so";
+      supported = false;
+      return;
+    }
+
+    LOAD_FUNCTION(main_dl_handle, AChoreographer_getInstance);
+    LOAD_FUNCTION(main_dl_handle, AChoreographer_postFrameCallback64);
+    LOAD_FUNCTION(main_dl_handle, AChoreographer_registerRefreshRateCallback);
+    LOAD_FUNCTION(main_dl_handle, AChoreographer_unregisterRefreshRateCallback);
+  }
+  ~AChoreographerMethods() = default;
+};
+
+}  // namespace
+
 namespace viz {
 
+class ExternalBeginFrameSourceAndroid::AChoreographerImpl {
+ public:
+  static std::unique_ptr<AChoreographerImpl> Create(
+      ExternalBeginFrameSourceAndroid* client);
+
+  AChoreographerImpl(ExternalBeginFrameSourceAndroid* client,
+                     AChoreographer* choreographer);
+  ~AChoreographerImpl();
+
+  void SetEnabled(bool enabled);
+
+ private:
+  static void FrameCallback64(int64_t frame_time_nanos, void* data);
+  static void RefershRateCallback(int64_t vsync_period_nanos, void* data);
+
+  void OnVSync(int64_t frame_time_nanos,
+               base::WeakPtr<AChoreographerImpl>* self);
+  void SetVsyncPeriod(int64_t vsync_period_nanos);
+  void RequestVsyncIfNeeded();
+
+  ExternalBeginFrameSourceAndroid* const client_;
+  AChoreographer* const achoreographer_;
+
+  base::TimeDelta vsync_period_;
+  bool vsync_notification_enabled_ = false;
+  // This is a heap-allocated WeakPtr to this object. The WeakPtr is either
+  // * passed to `postFrameCallback` if there is one (and exactly one) callback
+  //   pending. This is in case this is deleted before a pending callback
+  //   fires, in which case the callback is responsible for deleting the
+  //   WeakPtr.
+  // * or owned by this member variable when there is no pending callback.
+  // Thus whether this is nullptr also indicates whether there is a pending
+  // frame callback.
+  std::unique_ptr<base::WeakPtr<AChoreographerImpl>> self_for_frame_callback_;
+  base::WeakPtrFactory<AChoreographerImpl> weak_ptr_factory_{this};
+};
+
+// static
+std::unique_ptr<ExternalBeginFrameSourceAndroid::AChoreographerImpl>
+ExternalBeginFrameSourceAndroid::AChoreographerImpl::Create(
+    ExternalBeginFrameSourceAndroid* client) {
+  if (base::android::BuildInfo::GetInstance()->sdk_int() <
+      base::android::SDK_VERSION_R) {
+    return nullptr;
+  }
+  if (!AChoreographerMethods::Get().supported)
+    return nullptr;
+
+  AChoreographer* choreographer =
+      AChoreographerMethods::Get().AChoreographer_getInstanceFn();
+  if (!choreographer)
+    return nullptr;
+
+  return std::make_unique<AChoreographerImpl>(client, choreographer);
+}
+
+ExternalBeginFrameSourceAndroid::AChoreographerImpl::AChoreographerImpl(
+    ExternalBeginFrameSourceAndroid* client,
+    AChoreographer* choreographer)
+    : client_(client),
+      achoreographer_(choreographer),
+      vsync_period_(base::Microseconds(16666)) {
+  AChoreographerMethods::Get().AChoreographer_registerRefreshRateCallbackFn(
+      achoreographer_, &RefershRateCallback, this);
+  self_for_frame_callback_ =
+      std::make_unique<base::WeakPtr<AChoreographerImpl>>(
+          weak_ptr_factory_.GetWeakPtr());
+}
+
+ExternalBeginFrameSourceAndroid::AChoreographerImpl::~AChoreographerImpl() {
+  AChoreographerMethods::Get().AChoreographer_unregisterRefreshRateCallbackFn(
+      achoreographer_, &RefershRateCallback, this);
+}
+
+void ExternalBeginFrameSourceAndroid::AChoreographerImpl::SetEnabled(
+    bool enabled) {
+  if (vsync_notification_enabled_ == enabled)
+    return;
+  vsync_notification_enabled_ = enabled;
+  RequestVsyncIfNeeded();
+}
+
+// static
+void ExternalBeginFrameSourceAndroid::AChoreographerImpl::FrameCallback64(
+    int64_t frame_time_nanos,
+    void* data) {
+  TRACE_EVENT0("toplevel,viz", "VSync");
+  auto* self = static_cast<base::WeakPtr<AChoreographerImpl>*>(data);
+  if (!(*self)) {
+    delete self;
+    return;
+  }
+  (*self)->OnVSync(frame_time_nanos, self);
+}
+
+// static
+void ExternalBeginFrameSourceAndroid::AChoreographerImpl::RefershRateCallback(
+    int64_t vsync_period_nanos,
+    void* data) {
+  static_cast<AChoreographerImpl*>(data)->SetVsyncPeriod(vsync_period_nanos);
+}
+
+void ExternalBeginFrameSourceAndroid::AChoreographerImpl::OnVSync(
+    int64_t frame_time_nanos,
+    base::WeakPtr<AChoreographerImpl>* self) {
+  DCHECK(!self_for_frame_callback_);
+  DCHECK(self);
+  self_for_frame_callback_.reset(self);
+  if (vsync_notification_enabled_) {
+    client_->OnVSyncImpl(frame_time_nanos, vsync_period_);
+    RequestVsyncIfNeeded();
+  }
+}
+
+void ExternalBeginFrameSourceAndroid::AChoreographerImpl::SetVsyncPeriod(
+    int64_t vsync_period_nanos) {
+  vsync_period_ = base::Nanoseconds(vsync_period_nanos);
+}
+
+void ExternalBeginFrameSourceAndroid::AChoreographerImpl::
+    RequestVsyncIfNeeded() {
+  if (!vsync_notification_enabled_ || !self_for_frame_callback_)
+    return;
+  AChoreographerMethods::Get().AChoreographer_postFrameCallback64Fn(
+      achoreographer_, &FrameCallback64, self_for_frame_callback_.release());
+}
+
+// ============================================================================
+
 ExternalBeginFrameSourceAndroid::ExternalBeginFrameSourceAndroid(
     uint32_t restart_id,
     float refresh_rate)
-    : ExternalBeginFrameSource(this, restart_id),
-      j_object_(Java_ExternalBeginFrameSourceAndroid_Constructor(
-          base::android::AttachCurrentThread(),
-          reinterpret_cast<jlong>(this),
-          refresh_rate)) {}
+    : ExternalBeginFrameSource(this, restart_id) {
+  achoreographer_ = AChoreographerImpl::Create(this);
+  if (!achoreographer_) {
+    j_object_ = Java_ExternalBeginFrameSourceAndroid_Constructor(
+        base::android::AttachCurrentThread(), reinterpret_cast<jlong>(this),
+        refresh_rate);
+  }
+}
 
 ExternalBeginFrameSourceAndroid::~ExternalBeginFrameSourceAndroid() {
   SetEnabled(false);
@@ -27,6 +223,12 @@
     const base::android::JavaParamRef<jobject>& obj,
     jlong time_micros,
     jlong period_micros) {
+  OnVSyncImpl(time_micros * 1000, base::Microseconds(period_micros));
+}
+
+void ExternalBeginFrameSourceAndroid::OnVSyncImpl(
+    int64_t time_nanos,
+    base::TimeDelta vsync_period) {
   // Warning: It is generally unsafe to manufacture TimeTicks values. The
   // following assumption is being made, AND COULD EASILY BREAK AT ANY TIME:
   // Upstream, Java code is providing "System.nanos() / 1000," and this is the
@@ -34,8 +236,7 @@
   DCHECK_EQ(base::TimeTicks::GetClock(),
             base::TimeTicks::Clock::LINUX_CLOCK_MONOTONIC);
   base::TimeTicks frame_time =
-      base::TimeTicks() + base::Microseconds(time_micros);
-  base::TimeDelta vsync_period(base::Microseconds(period_micros));
+      base::TimeTicks() + base::Nanoseconds(time_nanos);
   // Calculate the next frame deadline:
   base::TimeTicks deadline = frame_time + vsync_period;
 
@@ -45,8 +246,10 @@
 }
 
 void ExternalBeginFrameSourceAndroid::UpdateRefreshRate(float refresh_rate) {
-  Java_ExternalBeginFrameSourceAndroid_updateRefreshRate(
-      base::android::AttachCurrentThread(), j_object_, refresh_rate);
+  if (j_object_) {
+    Java_ExternalBeginFrameSourceAndroid_updateRefreshRate(
+        base::android::AttachCurrentThread(), j_object_, refresh_rate);
+  }
 }
 
 void ExternalBeginFrameSourceAndroid::SetDynamicBeginFrameDeadlineOffsetSource(
@@ -62,8 +265,13 @@
 }
 
 void ExternalBeginFrameSourceAndroid::SetEnabled(bool enabled) {
-  Java_ExternalBeginFrameSourceAndroid_setEnabled(
-      base::android::AttachCurrentThread(), j_object_, enabled);
+  if (achoreographer_) {
+    achoreographer_->SetEnabled(enabled);
+  } else {
+    DCHECK(j_object_);
+    Java_ExternalBeginFrameSourceAndroid_setEnabled(
+        base::android::AttachCurrentThread(), j_object_, enabled);
+  }
 }
 
 }  // namespace viz
diff --git a/components/viz/service/frame_sinks/external_begin_frame_source_android.h b/components/viz/service/frame_sinks/external_begin_frame_source_android.h
index c8c7f7f..b7ed105 100644
--- a/components/viz/service/frame_sinks/external_begin_frame_source_android.h
+++ b/components/viz/service/frame_sinks/external_begin_frame_source_android.h
@@ -6,8 +6,10 @@
 #define COMPONENTS_VIZ_SERVICE_FRAME_SINKS_EXTERNAL_BEGIN_FRAME_SOURCE_ANDROID_H_
 
 #include <jni.h>
+#include <memory>
 
 #include "base/android/jni_weak_ref.h"
+#include "base/time/time.h"
 #include "components/viz/common/frame_sinks/begin_frame_source.h"
 #include "components/viz/service/viz_service_export.h"
 
@@ -40,11 +42,15 @@
           dynamic_begin_frame_deadline_offset_source) override;
 
  private:
+  class AChoreographerImpl;
+
   // ExternalBeginFrameSourceClient implementation.
   void OnNeedsBeginFrames(bool needs_begin_frames) override;
 
   void SetEnabled(bool enabled);
+  void OnVSyncImpl(int64_t time_nanos, base::TimeDelta vsync_period);
 
+  std::unique_ptr<AChoreographerImpl> achoreographer_;
   base::android::ScopedJavaGlobalRef<jobject> j_object_;
   BeginFrameArgsGenerator begin_frame_args_generator_;
 };
diff --git a/components/viz/service/surfaces/surface_saved_frame.cc b/components/viz/service/surfaces/surface_saved_frame.cc
index bb309039..3ebb6e43 100644
--- a/components/viz/service/surfaces/surface_saved_frame.cc
+++ b/components/viz/service/surfaces/surface_saved_frame.cc
@@ -82,6 +82,19 @@
 void SurfaceSavedFrame::RequestCopyOfOutput(Surface* surface) {
   DCHECK(surface->HasActiveFrame());
 
+  if (surface->GetActiveFrame().metadata.has_shared_element_resources) {
+    // TODO(khushalsagar) : This should be the only mode once renderer based SET
+    // lands.
+    copy_root_render_pass_ = false;
+    CopyUsingOriginalFrame(surface);
+  } else {
+    CopyUsingCleanFrame(surface);
+  }
+
+  DCHECK_EQ(copy_request_count_, ExpectedResultCount());
+}
+
+void SurfaceSavedFrame::CopyUsingCleanFrame(Surface* surface) {
   const auto& root_draw_data = GetRootRenderPassDrawData(surface);
   // Bind kRoot and root geometry information to the callback.
   auto root_request = std::make_unique<CopyOutputRequest>(
@@ -100,20 +113,6 @@
     return;
   }
 
-  if (surface->GetActiveFrame().metadata.has_shared_element_resources) {
-    // TODO(khushalsagar) : This should be the only mode once renderer based SET
-    // lands.
-    CopyUsingOriginalFrame(surface, std::move(root_request));
-  } else {
-    CopyUsingCleanFrame(surface, std::move(root_request));
-  }
-
-  DCHECK_EQ(copy_request_count_, ExpectedResultCount());
-}
-
-void SurfaceSavedFrame::CopyUsingCleanFrame(
-    Surface* surface,
-    std::unique_ptr<CopyOutputRequest> root_request) {
   // If the directive includes shared elements then we need to create a new
   // CompositorFrame with render passes that remove these elements. The strategy
   // is as follows :
@@ -187,9 +186,7 @@
   clean_surface_.emplace(surface, std::move(clean_frame));
 }
 
-void SurfaceSavedFrame::CopyUsingOriginalFrame(
-    Surface* surface,
-    std::unique_ptr<CopyOutputRequest> root_request) {
+void SurfaceSavedFrame::CopyUsingOriginalFrame(Surface* surface) {
   const auto& active_frame = surface->GetActiveFrame();
   for (const auto& render_pass : active_frame.render_pass_list) {
     if (auto request = CreateCopyRequestIfNeeded(
@@ -199,12 +196,6 @@
       copy_request_count_++;
     }
   }
-
-  // TODO(khushalsagar) : The root element should be an intermediate render pass
-  // in the renderer's frame. We could optimize it if there are no shared
-  // elements. See crbug.com/1265700.
-  surface->RequestCopyOfOutputOnRootRenderPass(std::move(root_request));
-  copy_request_count_++;
 }
 
 std::unique_ptr<CopyOutputRequest> SurfaceSavedFrame::CreateCopyRequestIfNeeded(
@@ -288,7 +279,7 @@
 
 size_t SurfaceSavedFrame::ExpectedResultCount() const {
   // Start with 1 for the root render pass.
-  size_t count = 1;
+  size_t count = copy_root_render_pass_ ? 1 : 0;
   for (auto& shared_element : directive_.shared_elements())
     count += !shared_element.render_pass_id.is_null();
   return count;
diff --git a/components/viz/service/surfaces/surface_saved_frame.h b/components/viz/service/surfaces/surface_saved_frame.h
index cac37b2..90f7ddfc 100644
--- a/components/viz/service/surfaces/surface_saved_frame.h
+++ b/components/viz/service/surfaces/surface_saved_frame.h
@@ -114,14 +114,12 @@
 
   // Queues copy requests by creating a copy of the CompositorFrame as specified
   // in ScopedCleanSurface.
-  void CopyUsingCleanFrame(Surface* surface,
-                           std::unique_ptr<CopyOutputRequest> root_request);
+  void CopyUsingCleanFrame(Surface* surface);
 
   // Queues copy requests from the original CompositorFrame. This mode is used
   // when the frame produced by the renderer already has independent render
   // passes for each shared element.
-  void CopyUsingOriginalFrame(Surface* surface,
-                              std::unique_ptr<CopyOutputRequest> root_request);
+  void CopyUsingOriginalFrame(Surface* surface);
 
   std::unique_ptr<CopyOutputRequest> CreateCopyRequestIfNeeded(
       const CompositorRenderPass& render_pass,
@@ -177,6 +175,9 @@
   // whether the SurfaceSavedFrame is "valid".
   size_t valid_result_count_ = 0;
 
+  // Tracks whether the root render pass should be copied.
+  bool copy_root_render_pass_ = true;
+
   absl::optional<ScopedCleanSurface> clean_surface_;
 
   base::WeakPtrFactory<SurfaceSavedFrame> weak_factory_{this};
diff --git a/components/viz/service/transitions/surface_animation_manager.cc b/components/viz/service/transitions/surface_animation_manager.cc
index 30749e3..3f4727c 100644
--- a/components/viz/service/transitions/surface_animation_manager.cc
+++ b/components/viz/service/transitions/surface_animation_manager.cc
@@ -1187,11 +1187,11 @@
         shared_element_quad.resource_id);
 
     if (texture_it != saved_textures_->element_id_to_resource.end()) {
-      resource_list->push_back(saved_textures_->element_id_to_resource.at(
-          shared_element_quad.resource_id));
+      const auto& transferable_resource = texture_it->second;
+      resource_list->push_back(transferable_resource);
 
       // GPU textures are flipped but software bitmaps are not.
-      bool y_flipped = !saved_textures_->root.resource.is_software;
+      bool y_flipped = !transferable_resource.is_software;
       ReplaceSharedElementWithTexture(&copy_pass, shared_element_quad,
                                       y_flipped, resource_list->back().id);
       return true;
diff --git a/content/app/content_main_runner_impl.cc b/content/app/content_main_runner_impl.cc
index 3999a567..b21e6cb 100644
--- a/content/app/content_main_runner_impl.cc
+++ b/content/app/content_main_runner_impl.cc
@@ -10,6 +10,7 @@
 
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -25,7 +26,6 @@
 #include "base/debug/stack_trace.h"
 #include "base/files/file_path.h"
 #include "base/i18n/icu_util.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/location.h"
 #include "base/logging.h"
@@ -1044,7 +1044,7 @@
       base::FieldTrialList* leaked_field_trial_list =
           SetUpFieldTrialsAndFeatureList().release();
       ANNOTATE_LEAKING_OBJECT_PTR(leaked_field_trial_list);
-      ignore_result(leaked_field_trial_list);
+      std::ignore = leaked_field_trial_list;
       delegate_->PostFieldTrialInitialization();
       mojo::core::InitFeatures();
     }
diff --git a/content/app_shim_remote_cocoa/ns_view_bridge_factory_impl.mm b/content/app_shim_remote_cocoa/ns_view_bridge_factory_impl.mm
index 6675ae22..2cd40c2 100644
--- a/content/app_shim_remote_cocoa/ns_view_bridge_factory_impl.mm
+++ b/content/app_shim_remote_cocoa/ns_view_bridge_factory_impl.mm
@@ -8,7 +8,6 @@
 #include <vector>
 
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "content/app_shim_remote_cocoa/render_widget_host_ns_view_bridge.h"
 #include "content/app_shim_remote_cocoa/render_widget_host_ns_view_host_helper.h"
 #include "content/app_shim_remote_cocoa/web_contents_ns_view_bridge.h"
@@ -154,10 +153,10 @@
 
   // Create a RenderWidgetHostNSViewBridgeOwner. The resulting object will be
   // destroyed when its underlying pipe is closed.
-  ignore_result(new RenderWidgetHostNSViewBridgeOwner(
+  std::ignore = new RenderWidgetHostNSViewBridgeOwner(
       std::move(host),
       mojo::PendingAssociatedReceiver<mojom::RenderWidgetHostNSView>(
-          std::move(view_receiver_handle))));
+          std::move(view_receiver_handle)));
 }
 
 void CreateWebContentsNSView(
diff --git a/content/app_shim_remote_cocoa/render_widget_host_view_cocoa.mm b/content/app_shim_remote_cocoa/render_widget_host_view_cocoa.mm
index 4d83201..050e234 100644
--- a/content/app_shim_remote_cocoa/render_widget_host_view_cocoa.mm
+++ b/content/app_shim_remote_cocoa/render_widget_host_view_cocoa.mm
@@ -5,13 +5,14 @@
 #import "content/app_shim_remote_cocoa/render_widget_host_view_cocoa.h"
 
 #include <Carbon/Carbon.h>  // for <HIToolbox/Events.h>
+
 #include <limits>
+#include <tuple>
 #include <utility>
 
 #include "base/containers/contains.h"
 #include "base/cxx17_backports.h"
 #include "base/debug/crash_logging.h"
-#include "base/ignore_result.h"
 #import "base/mac/foundation_util.h"
 #include "base/strings/sys_string_conversions.h"
 #import "content/browser/accessibility/browser_accessibility_cocoa.h"
@@ -619,7 +620,7 @@
 - (void)setHostDisconnected {
   // Set the host to be an abandoned message pipe, and set the hostHelper
   // to forward messages to that host.
-  ignore_result(_dummyHost.BindNewPipeAndPassReceiver());
+  std::ignore = _dummyHost.BindNewPipeAndPassReceiver();
   _dummyHostHelper = std::make_unique<DummyHostHelper>();
   _host = _dummyHost.get();
   _hostHelper = _dummyHostHelper.get();
diff --git a/content/browser/accessibility/touch_accessibility_aura_browsertest.cc b/content/browser/accessibility/touch_accessibility_aura_browsertest.cc
index 4622759d..baefdf0 100644
--- a/content/browser/accessibility/touch_accessibility_aura_browsertest.cc
+++ b/content/browser/accessibility/touch_accessibility_aura_browsertest.cc
@@ -2,7 +2,8 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/strings/string_number_conversions.h"
 #include "content/browser/accessibility/browser_accessibility.h"
 #include "content/browser/renderer_host/render_widget_host_view_child_frame.h"
@@ -58,7 +59,7 @@
     std::unique_ptr<ui::Event> mouse_move_event(
         new ui::MouseEvent(ui::ET_MOUSE_MOVED, location, location,
                            ui::EventTimeForNow(), flags, 0));
-    ignore_result(sink->OnEventFromSource(mouse_move_event.get()));
+    std::ignore = sink->OnEventFromSource(mouse_move_event.get());
   }
 };
 
diff --git a/content/browser/android/selection/selection_popup_controller.cc b/content/browser/android/selection/selection_popup_controller.cc
index 71d47433..8c72c07 100644
--- a/content/browser/android/selection/selection_popup_controller.cc
+++ b/content/browser/android/selection/selection_popup_controller.cc
@@ -214,7 +214,8 @@
     Java_SelectionPopupControllerImpl_onSelectAroundCaretFailure(env, obj);
   } else {
     Java_SelectionPopupControllerImpl_onSelectAroundCaretSuccess(
-        env, obj, result->extended_start_adjust, result->extended_end_adjust);
+        env, obj, result->extended_start_adjust, result->extended_end_adjust,
+        result->word_start_adjust, result->word_end_adjust);
   }
 }
 
diff --git a/content/browser/attribution_reporting/BUILD.gn b/content/browser/attribution_reporting/BUILD.gn
index fc6f3d3..ea116da 100644
--- a/content/browser/attribution_reporting/BUILD.gn
+++ b/content/browser/attribution_reporting/BUILD.gn
@@ -13,11 +13,19 @@
     {
       types = [
         {
+          mojom = "content.mojom.AttributionReportID"
+          cpp = "::content::EventAttributionReport::Id"
+        },
+        {
           mojom = "content.mojom.SourceType"
           cpp = "::content::StorableSource::SourceType"
         },
       ]
-      traits_headers = [ "attribution_internals_mojom_traits.h" ]
+      traits_headers = [
+        "attribution_internals_mojom_traits.h",
+        "event_attribution_report.h",
+      ]
+      traits_sources = [ "attribution_internals_mojom_traits.cc" ]
     },
   ]
 }
diff --git a/content/browser/attribution_reporting/attribution_internals.mojom b/content/browser/attribution_reporting/attribution_internals.mojom
index 4b272f86..b4bfc58 100644
--- a/content/browser/attribution_reporting/attribution_internals.mojom
+++ b/content/browser/attribution_reporting/attribution_internals.mojom
@@ -13,9 +13,16 @@
   kEvent,
 };
 
+struct AttributionReportID {
+  int64 value;
+};
+
 // Struct containing stored data that will be sent in a future attribution
 // report.
 struct WebUIAttributionReport {
+  // Allows the WebUI to issue commands for individual reports.
+  // Not intended to be displayed.
+  AttributionReportID? id;
   string attribution_destination;
   url.mojom.Url report_url;
   double trigger_time;
@@ -100,10 +107,10 @@
   // being sent.
   GetReports() => (array<WebUIAttributionReport> reports);
 
-  // Sends all stored reports, ignoring delay, returning when the
-  // operation has been completed and all reports have been cleared from
+  // Sends the given reports, ignoring delay, returning when the
+  // operation has been completed and the reports have been cleared from
   // storage.
-  SendPendingReports() => ();
+  SendReports(array<AttributionReportID> ids) => ();
 
   // Deletes all persisted data for the attribution reporting API, returning when the
   // operation has been completed.
diff --git a/content/browser/attribution_reporting/attribution_internals_browsertest.cc b/content/browser/attribution_reporting/attribution_internals_browsertest.cc
index 346a162..0367b26 100644
--- a/content/browser/attribution_reporting/attribution_internals_browsertest.cc
+++ b/content/browser/attribution_reporting/attribution_internals_browsertest.cc
@@ -39,6 +39,7 @@
 using DeactivatedSource = ::content::AttributionStorage::DeactivatedSource;
 
 using ::testing::_;
+using ::testing::ElementsAre;
 using ::testing::IsNull;
 using ::testing::Return;
 
@@ -389,22 +390,22 @@
       let table = document.querySelector("#report-table-wrapper tbody");
       let obs = new MutationObserver(() => {
         if (table.children.length === 7 &&
-            table.children[0].children[1].innerText === "https://conversion.test" &&
-            table.children[0].children[2].innerText ===
+            table.children[0].children[2].innerText === "https://conversion.test" &&
+            table.children[0].children[3].innerText ===
               "https://report.test/.well-known/attribution-reporting/report-attribution" &&
-            table.children[0].children[5].innerText === "13" &&
-            table.children[0].children[6].innerText === "yes" &&
-            table.children[0].children[7].innerText === "Pending" &&
-            table.children[1].children[5].innerText === "11" &&
-            table.children[1].children[7].innerText === "Dropped due to low priority" &&
-            table.children[2].children[5].innerText === "12" &&
-            table.children[2].children[7].innerText === "Dropped for noise" &&
-            table.children[3].children[5].innerText === "0" &&
-            table.children[3].children[6].innerText === "no" &&
-            table.children[3].children[7].innerText === "Sent: HTTP 200" &&
-            table.children[4].children[7].innerText === "Prohibited by browser policy" &&
-            table.children[5].children[7].innerText === "Network error" &&
-            table.children[6].children[7].innerText === "Dropped due to rate-limiting") {
+            table.children[0].children[6].innerText === "13" &&
+            table.children[0].children[7].innerText === "yes" &&
+            table.children[0].children[8].innerText === "Pending" &&
+            table.children[1].children[6].innerText === "11" &&
+            table.children[1].children[8].innerText === "Dropped due to low priority" &&
+            table.children[2].children[6].innerText === "12" &&
+            table.children[2].children[8].innerText === "Dropped for noise" &&
+            table.children[3].children[6].innerText === "0" &&
+            table.children[3].children[7].innerText === "no" &&
+            table.children[3].children[8].innerText === "Sent: HTTP 200" &&
+            table.children[4].children[8].innerText === "Prohibited by browser policy" &&
+            table.children[5].children[8].innerText === "Network error" &&
+            table.children[6].children[8].innerText === "Dropped due to rate-limiting") {
           document.title = $1;
         }
       });
@@ -421,22 +422,22 @@
       let table = document.querySelector("#report-table-wrapper tbody");
       let obs = new MutationObserver(() => {
         if (table.children.length === 7 &&
-            table.children[6].children[1].innerText === "https://conversion.test" &&
-            table.children[6].children[2].innerText ===
+            table.children[6].children[2].innerText === "https://conversion.test" &&
+            table.children[6].children[3].innerText ===
               "https://report.test/.well-known/attribution-reporting/report-attribution" &&
-            table.children[6].children[5].innerText === "13" &&
-            table.children[6].children[6].innerText === "yes" &&
-            table.children[6].children[7].innerText === "Pending" &&
-            table.children[5].children[5].innerText === "12" &&
-            table.children[5].children[7].innerText === "Dropped for noise" &&
-            table.children[4].children[5].innerText === "11" &&
-            table.children[4].children[7].innerText === "Dropped due to low priority" &&
-            table.children[3].children[5].innerText === "0" &&
-            table.children[3].children[6].innerText === "no" &&
-            table.children[3].children[7].innerText === "Sent: HTTP 200" &&
-            table.children[2].children[7].innerText === "Prohibited by browser policy" &&
-            table.children[1].children[7].innerText === "Network error" &&
-            table.children[0].children[7].innerText === "Dropped due to rate-limiting") {
+            table.children[6].children[6].innerText === "13" &&
+            table.children[6].children[7].innerText === "yes" &&
+            table.children[6].children[8].innerText === "Pending" &&
+            table.children[5].children[6].innerText === "12" &&
+            table.children[5].children[8].innerText === "Dropped for noise" &&
+            table.children[4].children[6].innerText === "11" &&
+            table.children[4].children[8].innerText === "Dropped due to low priority" &&
+            table.children[3].children[6].innerText === "0" &&
+            table.children[3].children[7].innerText === "no" &&
+            table.children[3].children[8].innerText === "Sent: HTTP 200" &&
+            table.children[2].children[8].innerText === "Prohibited by browser policy" &&
+            table.children[1].children[8].innerText === "Network error" &&
+            table.children[0].children[8].innerText === "Dropped due to rate-limiting") {
           document.title = $1;
         }
       });
@@ -446,7 +447,7 @@
     TitleWatcher title_watcher(shell()->web_contents(), kCompleteTitle2);
     // Sort by priority ascending.
     EXPECT_TRUE(ExecJsInWebUI(
-        "document.querySelectorAll('#report-table-wrapper th')[5].click();"));
+        "document.querySelectorAll('#report-table-wrapper th')[6].click();"));
     EXPECT_EQ(kCompleteTitle2, title_watcher.WaitAndGetTitle());
   }
 
@@ -455,22 +456,22 @@
       let table = document.querySelector("#report-table-wrapper tbody");
       let obs = new MutationObserver(() => {
         if (table.children.length === 7 &&
-            table.children[0].children[1].innerText === "https://conversion.test" &&
-            table.children[0].children[2].innerText ===
+            table.children[0].children[2].innerText === "https://conversion.test" &&
+            table.children[0].children[3].innerText ===
               "https://report.test/.well-known/attribution-reporting/report-attribution" &&
-            table.children[0].children[5].innerText === "13" &&
-            table.children[0].children[6].innerText === "yes" &&
-            table.children[0].children[7].innerText === "Pending" &&
-            table.children[1].children[5].innerText === "12" &&
-            table.children[1].children[7].innerText === "Dropped for noise" &&
-            table.children[2].children[5].innerText === "11" &&
-            table.children[2].children[7].innerText === "Dropped due to low priority" &&
-            table.children[3].children[5].innerText === "0" &&
-            table.children[3].children[6].innerText === "no" &&
-            table.children[3].children[7].innerText === "Sent: HTTP 200" &&
-            table.children[4].children[7].innerText === "Prohibited by browser policy" &&
-            table.children[5].children[7].innerText === "Network error" &&
-            table.children[6].children[7].innerText === "Dropped due to rate-limiting") {
+            table.children[0].children[6].innerText === "13" &&
+            table.children[0].children[7].innerText === "yes" &&
+            table.children[0].children[8].innerText === "Pending" &&
+            table.children[1].children[6].innerText === "12" &&
+            table.children[1].children[8].innerText === "Dropped for noise" &&
+            table.children[2].children[6].innerText === "11" &&
+            table.children[2].children[8].innerText === "Dropped due to low priority" &&
+            table.children[3].children[6].innerText === "0" &&
+            table.children[3].children[7].innerText === "no" &&
+            table.children[3].children[8].innerText === "Sent: HTTP 200" &&
+            table.children[4].children[8].innerText === "Prohibited by browser policy" &&
+            table.children[5].children[8].innerText === "Network error" &&
+            table.children[6].children[8].innerText === "Dropped due to rate-limiting") {
           document.title = $1;
         }
       });
@@ -480,7 +481,7 @@
     TitleWatcher title_watcher(shell()->web_contents(), kCompleteTitle3);
     // Sort by priority descending.
     EXPECT_TRUE(ExecJsInWebUI(
-        "document.querySelectorAll('#report-table-wrapper th')[5].click();"));
+        "document.querySelectorAll('#report-table-wrapper th')[6].click();"));
 
     EXPECT_EQ(kCompleteTitle3, title_watcher.WaitAndGetTitle());
   }
@@ -515,8 +516,8 @@
     let table = document.querySelector("#report-table-wrapper tbody");
     let obs = new MutationObserver(() => {
       if (table.children.length === 2 &&
-          table.children[0].children[5].innerText === "7" &&
-          table.children[1].children[7].innerText === "Sent: HTTP 200") {
+          table.children[0].children[6].innerText === "7" &&
+          table.children[1].children[8].innerText === "Sent: HTTP 200") {
         document.title = $1;
       }
     });
@@ -603,11 +604,16 @@
 
   EXPECT_CALL(manager_, GetPendingReportsForWebUI)
       .WillOnce(InvokeCallback<std::vector<EventAttributionReport>>(
-          {ReportBuilder(SourceBuilder().Build()).SetPriority(7).Build()}))
+          {ReportBuilder(SourceBuilder().Build())
+               .SetPriority(7)
+               .SetReportId(EventAttributionReport::Id(5))
+               .Build()}))
       .WillOnce(InvokeCallback<std::vector<EventAttributionReport>>({}));
 
-  EXPECT_CALL(manager_, SendReportsForWebUI)
-      .WillOnce([](base::OnceClosure done) { std::move(done).Run(); });
+  EXPECT_CALL(manager_, SendReportsForWebUI(
+                            ElementsAre(EventAttributionReport::Id(5)), _))
+      .WillOnce([](const std::vector<EventAttributionReport::Id>& ids,
+                   base::OnceClosure done) { std::move(done).Run(); });
 
   OverrideWebUIAttributionManager();
 
@@ -615,7 +621,7 @@
     let table = document.querySelector("#report-table-wrapper tbody");
     let obs = new MutationObserver(() => {
       if (table.children.length === 1 &&
-          table.children[0].children[5].innerText === "7") {
+          table.children[0].children[6].innerText === "7") {
         document.title = $1;
       }
     });
@@ -632,6 +638,8 @@
   TitleWatcher sent_title_watcher(shell()->web_contents(), kSentTitle);
   SetTitleOnReportsTableEmpty(kSentTitle);
 
+  EXPECT_TRUE(ExecJsInWebUI(
+      R"(document.querySelector('input[type="checkbox"]').click();)"));
   EXPECT_TRUE(
       ExecJsInWebUI("document.getElementById('send-reports').click();"));
 
diff --git a/content/browser/attribution_reporting/attribution_internals_handler_impl.cc b/content/browser/attribution_reporting/attribution_internals_handler_impl.cc
index 1efa8e62..49d90169 100644
--- a/content/browser/attribution_reporting/attribution_internals_handler_impl.cc
+++ b/content/browser/attribution_reporting/attribution_internals_handler_impl.cc
@@ -82,7 +82,8 @@
     int http_response_code,
     mojom::WebUIAttributionReport::Status status) {
   return mojom::WebUIAttributionReport::New(
-      report.source().ConversionDestination().Serialize(), report.ReportURL(),
+      report.report_id(), report.source().ConversionDestination().Serialize(),
+      report.ReportURL(),
       /*trigger_time=*/report.conversion_time().ToJsTime(),
       /*report_time=*/report.report_time().ToJsTime(), report.priority(),
       report.ReportBody(/*pretty_print=*/true),
@@ -154,11 +155,12 @@
   }
 }
 
-void AttributionInternalsHandlerImpl::SendPendingReports(
-    mojom::AttributionInternalsHandler::SendPendingReportsCallback callback) {
+void AttributionInternalsHandlerImpl::SendReports(
+    const std::vector<EventAttributionReport::Id>& ids,
+    mojom::AttributionInternalsHandler::SendReportsCallback callback) {
   if (AttributionManager* manager =
           manager_provider_->GetManager(web_ui_->GetWebContents())) {
-    manager->SendReportsForWebUI(std::move(callback));
+    manager->SendReportsForWebUI(ids, std::move(callback));
   } else {
     std::move(callback).Run();
   }
diff --git a/content/browser/attribution_reporting/attribution_internals_handler_impl.h b/content/browser/attribution_reporting/attribution_internals_handler_impl.h
index dfb1348..221e621 100644
--- a/content/browser/attribution_reporting/attribution_internals_handler_impl.h
+++ b/content/browser/attribution_reporting/attribution_internals_handler_impl.h
@@ -10,6 +10,7 @@
 #include "content/browser/attribution_reporting/attribution_internals.mojom.h"
 #include "content/browser/attribution_reporting/attribution_manager.h"
 #include "content/browser/attribution_reporting/attribution_storage.h"
+#include "content/browser/attribution_reporting/event_attribution_report.h"
 #include "mojo/public/cpp/bindings/pending_receiver.h"
 #include "mojo/public/cpp/bindings/receiver.h"
 #include "mojo/public/cpp/bindings/remote_set.h"
@@ -49,9 +50,9 @@
       override;
   void GetReports(
       mojom::AttributionInternalsHandler::GetReportsCallback callback) override;
-  void SendPendingReports(
-      mojom::AttributionInternalsHandler::SendPendingReportsCallback callback)
-      override;
+  void SendReports(const std::vector<EventAttributionReport::Id>& ids,
+                   mojom::AttributionInternalsHandler::SendReportsCallback
+                       callback) override;
   void ClearStorage(mojom::AttributionInternalsHandler::ClearStorageCallback
                         callback) override;
   void AddObserver(
diff --git a/content/browser/attribution_reporting/attribution_internals_mojom_traits.cc b/content/browser/attribution_reporting/attribution_internals_mojom_traits.cc
new file mode 100644
index 0000000..cbc8265
--- /dev/null
+++ b/content/browser/attribution_reporting/attribution_internals_mojom_traits.cc
@@ -0,0 +1,18 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "content/browser/attribution_reporting/attribution_internals_mojom_traits.h"
+
+namespace mojo {
+
+// static
+bool StructTraits<content::mojom::AttributionReportIDDataView,
+                  content::EventAttributionReport::Id>::
+    Read(content::mojom::AttributionReportIDDataView data,
+         content::EventAttributionReport::Id* out) {
+  *out = content::EventAttributionReport::Id(data.value());
+  return true;
+}
+
+}  // namespace mojo
diff --git a/content/browser/attribution_reporting/attribution_internals_mojom_traits.h b/content/browser/attribution_reporting/attribution_internals_mojom_traits.h
index 8750fc5..2d3187a8 100644
--- a/content/browser/attribution_reporting/attribution_internals_mojom_traits.h
+++ b/content/browser/attribution_reporting/attribution_internals_mojom_traits.h
@@ -5,9 +5,13 @@
 #ifndef CONTENT_BROWSER_ATTRIBUTION_REPORTING_ATTRIBUTION_INTERNALS_MOJOM_TRAITS_H_
 #define CONTENT_BROWSER_ATTRIBUTION_REPORTING_ATTRIBUTION_INTERNALS_MOJOM_TRAITS_H_
 
+#include <stdint.h>
+
 #include "content/browser/attribution_reporting/attribution_internals.mojom.h"
+#include "content/browser/attribution_reporting/event_attribution_report.h"
 #include "content/browser/attribution_reporting/storable_source.h"
 #include "mojo/public/cpp/bindings/enum_traits.h"
+#include "mojo/public/cpp/bindings/struct_traits.h"
 
 namespace mojo {
 
@@ -40,6 +44,18 @@
   }
 };
 
+template <>
+class StructTraits<content::mojom::AttributionReportIDDataView,
+                   content::EventAttributionReport::Id> {
+ public:
+  static int64_t value(const content::EventAttributionReport::Id& id) {
+    return *id;
+  }
+
+  static bool Read(content::mojom::AttributionReportIDDataView data,
+                   content::EventAttributionReport::Id* out);
+};
+
 }  // namespace mojo
 
 #endif  // CONTENT_BROWSER_ATTRIBUTION_REPORTING_ATTRIBUTION_INTERNALS_MOJOM_TRAITS_H_
diff --git a/content/browser/attribution_reporting/attribution_manager.h b/content/browser/attribution_reporting/attribution_manager.h
index 4e21516..5eb787768 100644
--- a/content/browser/attribution_reporting/attribution_manager.h
+++ b/content/browser/attribution_reporting/attribution_manager.h
@@ -91,9 +91,11 @@
       base::OnceCallback<void(std::vector<EventAttributionReport>)>
           callback) = 0;
 
-  // Sends all pending reports immediately, and runs |done| once they have all
+  // Sends the given reports immediately, and runs |done| once they have all
   // been sent.
-  virtual void SendReportsForWebUI(base::OnceClosure done) = 0;
+  virtual void SendReportsForWebUI(
+      const std::vector<EventAttributionReport::Id>& ids,
+      base::OnceClosure done) = 0;
 
   // Returns the AttributionPolicy that is used to control API policies such
   // as noise.
diff --git a/content/browser/attribution_reporting/attribution_manager_impl.cc b/content/browser/attribution_reporting/attribution_manager_impl.cc
index dd83689..8500138a 100644
--- a/content/browser/attribution_reporting/attribution_manager_impl.cc
+++ b/content/browser/attribution_reporting/attribution_manager_impl.cc
@@ -288,12 +288,13 @@
                       /*max_report_time=*/base::Time::Max(), /*limit=*/1000);
 }
 
-void AttributionManagerImpl::SendReportsForWebUI(base::OnceClosure done) {
-  GetAndHandleReports(
-      base::BindOnce(&AttributionManagerImpl::OnGetReportsToSendFromWebUI,
-                     weak_factory_.GetWeakPtr(), std::move(done)),
-      /*max_report_time=*/base::Time::Max(),
-      /*limit=*/-1);
+void AttributionManagerImpl::SendReportsForWebUI(
+    const std::vector<EventAttributionReport::Id>& ids,
+    base::OnceClosure done) {
+  attribution_storage_.AsyncCall(&AttributionStorage::GetReports)
+      .WithArgs(ids)
+      .Then(base::BindOnce(&AttributionManagerImpl::OnGetReportsToSendFromWebUI,
+                           weak_factory_.GetWeakPtr(), std::move(done)));
 }
 
 const AttributionPolicy& AttributionManagerImpl::GetAttributionPolicy() const {
diff --git a/content/browser/attribution_reporting/attribution_manager_impl.h b/content/browser/attribution_reporting/attribution_manager_impl.h
index 604132a5..a98245d 100644
--- a/content/browser/attribution_reporting/attribution_manager_impl.h
+++ b/content/browser/attribution_reporting/attribution_manager_impl.h
@@ -112,7 +112,8 @@
   void GetPendingReportsForWebUI(
       base::OnceCallback<void(std::vector<EventAttributionReport>)> callback)
       override;
-  void SendReportsForWebUI(base::OnceClosure done) override;
+  void SendReportsForWebUI(const std::vector<EventAttributionReport::Id>& ids,
+                           base::OnceClosure done) override;
   const AttributionPolicy& GetAttributionPolicy() const override;
   void ClearData(base::Time delete_begin,
                  base::Time delete_end,
diff --git a/content/browser/attribution_reporting/attribution_manager_impl_unittest.cc b/content/browser/attribution_reporting/attribution_manager_impl_unittest.cc
index 9128f50..17e6f71 100644
--- a/content/browser/attribution_reporting/attribution_manager_impl_unittest.cc
+++ b/content/browser/attribution_reporting/attribution_manager_impl_unittest.cc
@@ -738,9 +738,12 @@
   attribution_manager_->HandleSource(
       SourceBuilder().SetExpiry(kImpressionExpiry).Build());
   attribution_manager_->HandleTrigger(DefaultTrigger());
+  std::vector<EventAttributionReport> reports = StoredReports();
+  EXPECT_THAT(reports, SizeIs(1));
   EXPECT_THAT(network_sender_->calls(), IsEmpty());
 
-  attribution_manager_->SendReportsForWebUI(base::DoNothing());
+  attribution_manager_->SendReportsForWebUI({*reports.front().report_id()},
+                                            base::DoNothing());
   task_environment_.FastForwardBy(base::TimeDelta());
   EXPECT_THAT(network_sender_->calls(), SizeIs(1));
 }
@@ -753,9 +756,12 @@
       SourceBuilder().SetExpiry(kImpressionExpiry).Build());
   attribution_manager_->HandleTrigger(DefaultTrigger());
   attribution_manager_->HandleTrigger(DefaultTrigger());
+  std::vector<EventAttributionReport> reports = StoredReports();
+  EXPECT_THAT(reports, SizeIs(2));
   EXPECT_THAT(network_sender_->calls(), IsEmpty());
 
   attribution_manager_->SendReportsForWebUI(
+      {*reports.front().report_id(), *reports.back().report_id()},
       base::BindLambdaForTesting([&]() { callback_calls++; }));
   task_environment_.FastForwardBy(base::TimeDelta());
   EXPECT_THAT(network_sender_->calls(), SizeIs(2));
@@ -1163,7 +1169,8 @@
       SourceBuilder().SetExpiry(kImpressionExpiry).Build());
   attribution_manager_->HandleTrigger(DefaultTrigger());
 
-  attribution_manager_->SendReportsForWebUI(base::DoNothing());
+  attribution_manager_->SendReportsForWebUI({EventAttributionReport::Id(1)},
+                                            base::DoNothing());
   task_environment_.FastForwardBy(base::TimeDelta());
   EXPECT_THAT(network_sender_->calls(), SizeIs(1));
 
diff --git a/content/browser/attribution_reporting/attribution_storage.h b/content/browser/attribution_reporting/attribution_storage.h
index a64baea..2fdf6ee 100644
--- a/content/browser/attribution_reporting/attribution_storage.h
+++ b/content/browser/attribution_reporting/attribution_storage.h
@@ -222,6 +222,12 @@
   virtual absl::optional<base::Time> GetNextReportTime(base::Time time)
       WARN_UNUSED_RESULT = 0;
 
+  // Returns the reports with the given IDs. This call is logically const, and
+  // does not modify the underlying storage.
+  virtual std::vector<EventAttributionReport> GetReports(
+      const std::vector<EventAttributionReport::Id>& ids)
+      WARN_UNUSED_RESULT = 0;
+
   // Returns all active sources in storage. Active sources are all
   // sources that can still convert. Sources that: are past expiry,
   // reached the attribution limit, or was marked inactive due to having
diff --git a/content/browser/attribution_reporting/attribution_storage_sql.cc b/content/browser/attribution_reporting/attribution_storage_sql.cc
index 265f5d5..389845a 100644
--- a/content/browser/attribution_reporting/attribution_storage_sql.cc
+++ b/content/browser/attribution_reporting/attribution_storage_sql.cc
@@ -5,7 +5,9 @@
 #include "content/browser/attribution_reporting/attribution_storage_sql.h"
 
 #include <stdint.h>
+
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
@@ -15,7 +17,6 @@
 #include "base/containers/flat_set.h"
 #include "base/files/file_util.h"
 #include "base/guid.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/metrics/histogram_functions.h"
 #include "base/metrics/histogram_macros.h"
@@ -923,6 +924,21 @@
   return absl::nullopt;
 }
 
+std::vector<EventAttributionReport> AttributionStorageSql::GetReports(
+    const std::vector<EventAttributionReport::Id>& ids) {
+  DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
+  if (!LazyInit(DbCreationPolicy::kIgnoreIfAbsent))
+    return {};
+
+  std::vector<EventAttributionReport> reports;
+  for (EventAttributionReport::Id id : ids) {
+    absl::optional<EventAttributionReport> report = GetReport(id);
+    if (report.has_value())
+      reports.push_back(std::move(*report));
+  }
+  return reports;
+}
+
 absl::optional<EventAttributionReport> AttributionStorageSql::GetReport(
     EventAttributionReport::Id conversion_id) {
   static constexpr char kGetReportSql[] =
@@ -1697,7 +1713,7 @@
     // or hardware issues, not coding errors at the client level, so displaying
     // the error would probably lead to confusion.  The ignored call signals the
     // test-expectation framework that the error was handled.
-    ignore_result(sql::Database::IsExpectedSqliteError(extended_error));
+    std::ignore = sql::Database::IsExpectedSqliteError(extended_error);
     return;
   }
 
diff --git a/content/browser/attribution_reporting/attribution_storage_sql.h b/content/browser/attribution_reporting/attribution_storage_sql.h
index ec1fa86e3..89b3356 100644
--- a/content/browser/attribution_reporting/attribution_storage_sql.h
+++ b/content/browser/attribution_reporting/attribution_storage_sql.h
@@ -87,6 +87,8 @@
       base::Time max_report_time,
       int limit = -1) override;
   absl::optional<base::Time> GetNextReportTime(base::Time time) override;
+  std::vector<EventAttributionReport> GetReports(
+      const std::vector<EventAttributionReport::Id>& ids) override;
   std::vector<StorableSource> GetActiveSources(int limit = -1) override;
   bool DeleteReport(EventAttributionReport::Id report_id) override;
   bool UpdateReportForSendFailure(EventAttributionReport::Id report_id,
diff --git a/content/browser/attribution_reporting/attribution_storage_sql_migrations_unittest.cc b/content/browser/attribution_reporting/attribution_storage_sql_migrations_unittest.cc
index fc781ab..2b13614 100644
--- a/content/browser/attribution_reporting/attribution_storage_sql_migrations_unittest.cc
+++ b/content/browser/attribution_reporting/attribution_storage_sql_migrations_unittest.cc
@@ -8,7 +8,6 @@
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
 #include "base/guid.h"
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/strings/string_util.h"
 #include "base/test/metrics/histogram_tester.h"
@@ -46,9 +45,9 @@
         std::make_unique<ConfigurableStorageDelegate>());
 
     // We need to run an operation on storage to force the lazy initialization.
-    ignore_result(
+    std::ignore =
         static_cast<AttributionStorage*>(&storage)->GetAttributionsToReport(
-            base::Time::Min()));
+            base::Time::Min());
   }
 
   base::FilePath DbPath() {
diff --git a/content/browser/attribution_reporting/attribution_test_utils.h b/content/browser/attribution_reporting/attribution_test_utils.h
index 1352101..4ef2d5e8 100644
--- a/content/browser/attribution_reporting/attribution_test_utils.h
+++ b/content/browser/attribution_reporting/attribution_test_utils.h
@@ -178,7 +178,11 @@
       (base::OnceCallback<void(std::vector<EventAttributionReport>)> callback),
       (override));
 
-  MOCK_METHOD(void, SendReportsForWebUI, (base::OnceClosure done), (override));
+  MOCK_METHOD(void,
+              SendReportsForWebUI,
+              (const std::vector<EventAttributionReport::Id>& ids,
+               base::OnceClosure done),
+              (override));
 
   MOCK_METHOD(void,
               ClearData,
diff --git a/content/browser/bluetooth/frame_connected_bluetooth_devices_unittest.cc b/content/browser/bluetooth/frame_connected_bluetooth_devices_unittest.cc
index bbbdf5d..847c85d 100644
--- a/content/browser/bluetooth/frame_connected_bluetooth_devices_unittest.cc
+++ b/content/browser/bluetooth/frame_connected_bluetooth_devices_unittest.cc
@@ -4,7 +4,8 @@
 
 #include "content/browser/bluetooth/frame_connected_bluetooth_devices.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/memory/raw_ptr.h"
 #include "base/memory/ref_counted.h"
 #include "content/browser/bluetooth/web_bluetooth_service_impl.h"
@@ -44,7 +45,7 @@
 mojo::AssociatedRemote<blink::mojom::WebBluetoothServerClient>
 CreateServerClient() {
   mojo::AssociatedRemote<blink::mojom::WebBluetoothServerClient> client;
-  ignore_result(client.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore = client.BindNewEndpointAndPassDedicatedReceiver();
   return client;
 }
 
diff --git a/content/browser/browser_main_loop.cc b/content/browser/browser_main_loop.cc
index 44dc30b..6846ca3 100644
--- a/content/browser/browser_main_loop.cc
+++ b/content/browser/browser_main_loop.cc
@@ -9,6 +9,7 @@
 #include <algorithm>
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -17,7 +18,6 @@
 #include "base/command_line.h"
 #include "base/cxx17_backports.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/location.h"
 #include "base/logging.h"
 #include "base/memory/memory_pressure_monitor.h"
@@ -1178,15 +1178,15 @@
     if (audio_manager_ && !audio_manager_->Shutdown()) {
       // Intentionally leak AudioManager if shutdown failed.
       // We might run into various CHECK(s) in AudioManager destructor.
-      ignore_result(audio_manager_.release());
+      std::ignore = audio_manager_.release();
       // |user_input_monitor_| may be in use by stray streams in case
       // AudioManager shutdown failed.
-      ignore_result(user_input_monitor_.release());
+      std::ignore = user_input_monitor_.release();
     }
 
     // Leaking AudioSystem: we cannot correctly destroy it since Audio service
     // connection in there is bound to IO thread.
-    ignore_result(audio_system_.release());
+    std::ignore = audio_system_.release();
   }
 
   if (parts_) {
diff --git a/content/browser/child_process_launcher_helper_android.cc b/content/browser/child_process_launcher_helper_android.cc
index a90558b5..feb2d49 100644
--- a/content/browser/child_process_launcher_helper_android.cc
+++ b/content/browser/child_process_launcher_helper_android.cc
@@ -3,13 +3,13 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 
 #include "base/android/apk_assets.h"
 #include "base/android/application_status_listener.h"
 #include "base/android/jni_array.h"
 #include "base/bind.h"
 #include "base/i18n/icu_util.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/metrics/field_trial.h"
 #include "base/task/post_task.h"
@@ -133,7 +133,7 @@
     const auto& region = files_to_register->GetRegionAt(i);
     bool auto_close = files_to_register->OwnsFD(fd);
     if (auto_close) {
-      ignore_result(files_to_register->ReleaseFD(fd).release());
+      std::ignore = files_to_register->ReleaseFD(fd).release();
     }
 
     ScopedJavaLocalRef<jobject> j_file_info =
diff --git a/content/browser/content_security_policy_browsertest.cc b/content/browser/content_security_policy_browsertest.cc
index 22d3033f..eb4e163 100644
--- a/content/browser/content_security_policy_browsertest.cc
+++ b/content/browser/content_security_policy_browsertest.cc
@@ -2,8 +2,9 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
+
 #include "base/files/file_path.h"
-#include "base/ignore_result.h"
 #include "base/path_service.h"
 #include "base/threading/thread_restrictions.h"
 #include "content/browser/renderer_host/render_frame_host_impl.h"
@@ -200,7 +201,7 @@
     // On windows, if `document_url` contains the host part "localhost", the
     // actual committed URL does not. So we omit EXPECT_TRUE and ignore the
     // result value here.
-    ignore_result(NavigateToURL(shell(), document_url));
+    std::ignore = NavigateToURL(shell(), document_url);
 
     GURL element_url = net::FilePathToFileURL(TestFilePath(
         testCase.element_name == "iframe" ? "empty.html" : "blank.jpg"));
diff --git a/content/browser/file_system_access/file_system_access_directory_handle_impl_unittest.cc b/content/browser/file_system_access/file_system_access_directory_handle_impl_unittest.cc
index ef02afca..0f664820 100644
--- a/content/browser/file_system_access/file_system_access_directory_handle_impl_unittest.cc
+++ b/content/browser/file_system_access/file_system_access_directory_handle_impl_unittest.cc
@@ -6,11 +6,11 @@
 
 #include <iterator>
 #include <string>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/run_loop.h"
 #include "base/test/bind.h"
@@ -211,7 +211,7 @@
     // ignore any failures writing these files to disk.
     EXPECT_TRUE(success) << "Failed to create file " << file_path;
 #else
-    ignore_result(success);
+    std::ignore = success;
 #endif
   }
 
diff --git a/content/browser/find_request_manager.cc b/content/browser/find_request_manager.cc
index 4b3ad9b..57b78a3 100644
--- a/content/browser/find_request_manager.cc
+++ b/content/browser/find_request_manager.cc
@@ -174,6 +174,16 @@
                     rfh->GetLastCommittedOrigin());
 }
 
+// kMinKeystrokesWithoutDelay should be high enough that script in the page
+// can't provide every possible search result at the same time.
+constexpr int kMinKeystrokesWithoutDelay = 4;
+
+// The delay for very short queries, before sending find requests. This should
+// be higher than the duration in between two keystrokes. This is based on
+// WebCore.FindInPage.DurationBetweenKeystrokes metrics, this is higher than
+// 90% of them.
+constexpr int kDelayMs = 400;
+
 }  // namespace
 
 // Observes searched WebContentses for RenderFrameHost state updates, including
@@ -286,7 +296,8 @@
 
 void FindRequestManager::Find(int request_id,
                               const std::u16string& search_text,
-                              blink::mojom::FindOptionsPtr options) {
+                              blink::mojom::FindOptionsPtr options,
+                              bool skip_delay) {
   // Every find request must have a unique ID, and these IDs must strictly
   // increase so that newer requests always have greater IDs than older
   // requests.
@@ -311,6 +322,41 @@
     last_searched_text_ = search_text;
   }
 
+  if (skip_delay) {
+    delayed_find_task_.Cancel();
+    EmitFindRequest(request_id, search_text, std::move(options));
+    return;
+  }
+
+  if (!options->new_session) {
+    // If the user presses enter while we are waiting for a delayed find, then
+    // run the find now to improve responsiveness.
+    if (!delayed_find_task_.IsCancelled()) {
+      delayed_find_task_.callback().Run();
+    } else {
+      EmitFindRequest(request_id, search_text, std::move(options));
+    }
+    return;
+  }
+
+  if (search_text.length() < kMinKeystrokesWithoutDelay) {
+    delayed_find_task_.Reset(base::BindOnce(
+        &FindRequestManager::EmitFindRequest, weak_factory_.GetWeakPtr(),
+        request_id, search_text, std::move(options)));
+    base::ThreadTaskRunnerHandle::Get()->PostDelayedTask(
+        FROM_HERE, delayed_find_task_.callback(), base::Milliseconds(kDelayMs));
+    return;
+  }
+
+  // If we aren't going to delay, then clear any previous attempts to delay.
+  delayed_find_task_.Cancel();
+
+  EmitFindRequest(request_id, search_text, std::move(options));
+}
+
+void FindRequestManager::EmitFindRequest(int request_id,
+                                         const std::u16string& search_text,
+                                         blink::mojom::FindOptionsPtr options) {
   // If this is a new find session, clear any queued requests from last session.
   if (options->new_session)
     find_request_queue_ = base::queue<FindRequest>();
diff --git a/content/browser/find_request_manager.h b/content/browser/find_request_manager.h
index f9867fc..9e02495 100644
--- a/content/browser/find_request_manager.h
+++ b/content/browser/find_request_manager.h
@@ -10,6 +10,7 @@
 #include <unordered_set>
 #include <vector>
 
+#include "base/cancelable_callback.h"
 #include "base/containers/queue.h"
 #include "base/memory/raw_ptr.h"
 #include "build/build_config.h"
@@ -45,7 +46,8 @@
   // |options|. |request_id| uniquely identifies the find request.
   void Find(int request_id,
             const std::u16string& search_text,
-            blink::mojom::FindOptionsPtr options);
+            blink::mojom::FindOptionsPtr options,
+            bool skip_delay = false);
 
   // Stops the active find session and clears the general highlighting of the
   // matches. |action| determines whether the last active match (if any) will be
@@ -216,6 +218,10 @@
   // callback if the each RenderFrameHost is alive and active.
   void ForEachAddedFindInPageRenderFrameHost(FrameIterationCallback callback);
 
+  void EmitFindRequest(int request_id,
+                       const std::u16string& search_text,
+                       blink::mojom::FindOptionsPtr options);
+
 #if defined(OS_ANDROID)
   // Called when a nearest find result reply is no longer pending for a frame.
   void RemoveNearestFindResultPendingReply(RenderFrameHost* rfh);
@@ -364,8 +370,12 @@
   base::TimeTicks last_time_typed_;
   std::u16string last_searched_text_;
 
+  base::CancelableOnceClosure delayed_find_task_;
+
   CreateFindInPageClientFunction create_find_in_page_client_for_testing_ =
       nullptr;
+
+  base::WeakPtrFactory<FindRequestManager> weak_factory_{this};
 };
 
 }  // namespace content
diff --git a/content/browser/indexed_db/indexed_db_backing_store.cc b/content/browser/indexed_db/indexed_db_backing_store.cc
index bd4e676..a73549d 100644
--- a/content/browser/indexed_db/indexed_db_backing_store.cc
+++ b/content/browser/indexed_db/indexed_db_backing_store.cc
@@ -5,13 +5,13 @@
 #include "content/browser/indexed_db/indexed_db_backing_store.h"
 
 #include <algorithm>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/dcheck_is_on.h"
 #include "base/files/file_path.h"
 #include "base/format_macros.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/json/json_writer.h"
 #include "base/logging.h"
@@ -713,11 +713,11 @@
   if (!found) {
     // Initialize new backing store.
     db_schema_version = indexed_db::kLatestKnownSchemaVersion;
-    ignore_result(
-        PutInt(write_batch.get(), schema_version_key, db_schema_version));
+    std::ignore =
+        PutInt(write_batch.get(), schema_version_key, db_schema_version);
     db_data_version = latest_known_data_version;
-    ignore_result(
-        PutInt(write_batch.get(), data_version_key, db_data_version.Encode()));
+    std::ignore =
+        PutInt(write_batch.get(), data_version_key, db_data_version.Encode());
     // If a blob directory already exists for this database, blow it away.  It's
     // leftover from a partially-purged previous generation of data.
     if (filesystem_proxy_ &&
@@ -775,8 +775,8 @@
     // Up to date. Nothing to do.
   } else if (latest_known_data_version.IsAtLeast(db_data_version)) {
     db_data_version = latest_known_data_version;
-    ignore_result(
-        PutInt(write_batch.get(), data_version_key, db_data_version.Encode()));
+    std::ignore =
+        PutInt(write_batch.get(), data_version_key, db_data_version.Encode());
   } else {
     // |db_data_version| is in the future according to at least one component.
     INTERNAL_CONSISTENCY_ERROR(SET_UP_METADATA);
@@ -3071,7 +3071,7 @@
   const std::string data_version_key = DataVersionKey::Encode();
   Status s;
 
-  ignore_result(PutInt(write_batch, schema_version_key, db_schema_version));
+  std::ignore = PutInt(write_batch, schema_version_key, db_schema_version);
   const std::string start_key =
       DatabaseNameKey::EncodeMinKeyForOrigin(origin_identifier_);
   const std::string stop_key =
@@ -3094,8 +3094,8 @@
     }
     std::string version_key = DatabaseMetaDataKey::Encode(
         database_id, DatabaseMetaDataKey::USER_VERSION);
-    ignore_result(PutVarInt(write_batch, version_key,
-                            IndexedDBDatabaseMetadata::DEFAULT_VERSION));
+    std::ignore = PutVarInt(write_batch, version_key,
+                            IndexedDBDatabaseMetadata::DEFAULT_VERSION);
   }
 
   return s;
@@ -3109,9 +3109,9 @@
   const std::string data_version_key = DataVersionKey::Encode();
   Status s;
 
-  ignore_result(PutInt(write_batch, schema_version_key, db_schema_version));
-  ignore_result(PutInt(write_batch, data_version_key,
-                       IndexedDBDataFormatVersion::GetCurrent().Encode()));
+  std::ignore = PutInt(write_batch, schema_version_key, db_schema_version);
+  std::ignore = PutInt(write_batch, data_version_key,
+                       IndexedDBDataFormatVersion::GetCurrent().Encode());
   return s;
 }
 
@@ -3146,7 +3146,7 @@
     if (storage_key_.origin().host() != "docs.google.com")
       return InternalInconsistencyStatus();
   } else {
-    ignore_result(PutInt(write_batch, schema_version_key, db_schema_version));
+    std::ignore = PutInt(write_batch, schema_version_key, db_schema_version);
   }
 
   return s;
@@ -3165,7 +3165,7 @@
     INTERNAL_CONSISTENCY_ERROR(SET_UP_METADATA);
     return InternalInconsistencyStatus();
   }
-  ignore_result(PutInt(write_batch, schema_version_key, db_schema_version));
+  std::ignore = PutInt(write_batch, schema_version_key, db_schema_version);
 
   // Delete all empty files that resulted from the migration to v4. If this
   // fails it's not a big deal.
@@ -3196,7 +3196,7 @@
       return InternalInconsistencyStatus();
     }
   }
-  ignore_result(PutInt(write_batch, schema_version_key, db_schema_version));
+  std::ignore = PutInt(write_batch, schema_version_key, db_schema_version);
 
   return s;
 }
diff --git a/content/browser/indexed_db/indexed_db_backing_store_unittest.cc b/content/browser/indexed_db/indexed_db_backing_store_unittest.cc
index 0fe57acb..687607e0 100644
--- a/content/browser/indexed_db/indexed_db_backing_store_unittest.cc
+++ b/content/browser/indexed_db/indexed_db_backing_store_unittest.cc
@@ -8,6 +8,7 @@
 #include <stdint.h>
 
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/barrier_closure.h"
@@ -19,7 +20,6 @@
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
 #include "base/guid.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/notreached.h"
 #include "base/strings/string_number_conversions.h"
@@ -1786,7 +1786,7 @@
   // Set the schema to 2, which was before blob support.
   std::unique_ptr<LevelDBWriteBatch> write_batch = LevelDBWriteBatch::Create();
   const std::string schema_version_key = SchemaVersionKey::Encode();
-  ignore_result(indexed_db::PutInt(write_batch.get(), schema_version_key, 2));
+  std::ignore = indexed_db::PutInt(write_batch.get(), schema_version_key, 2);
   ASSERT_TRUE(backing_store()->db()->Write(write_batch.get()).ok());
   task_environment_.RunUntilIdle();
 
@@ -1902,7 +1902,7 @@
   // Set the schema to 2, which was before blob support.
   std::unique_ptr<LevelDBWriteBatch> write_batch = LevelDBWriteBatch::Create();
   const std::string schema_version_key = SchemaVersionKey::Encode();
-  ignore_result(indexed_db::PutInt(write_batch.get(), schema_version_key, 2));
+  std::ignore = indexed_db::PutInt(write_batch.get(), schema_version_key, 2);
   ASSERT_TRUE(backing_store()->db()->Write(write_batch.get()).ok());
 
   // Clean up on the IDB sequence.
diff --git a/content/browser/indexed_db/indexed_db_context_impl.cc b/content/browser/indexed_db/indexed_db_context_impl.cc
index 6a7d303..24577f10 100644
--- a/content/browser/indexed_db/indexed_db_context_impl.cc
+++ b/content/browser/indexed_db/indexed_db_context_impl.cc
@@ -870,8 +870,10 @@
     const blink::StorageKey& storage_key,
     mojo::PendingReceiver<blink::mojom::IDBFactory> receiver,
     storage::QuotaErrorOr<storage::BucketInfo> result) {
-  DCHECK(result.ok());
-  dispatcher_host_.AddReceiver(storage_key, std::move(receiver));
+  absl::optional<storage::BucketLocator> bucket =
+      result.ok() ? absl::make_optional(result->ToBucketLocator())
+                  : absl::nullopt;
+  dispatcher_host_.AddReceiver(storage_key, bucket, std::move(receiver));
 }
 
 void IndexedDBContextImpl::ShutdownOnIDBSequence() {
diff --git a/content/browser/indexed_db/indexed_db_context_unittest.cc b/content/browser/indexed_db/indexed_db_context_unittest.cc
index e1a6c10..8401f2c 100644
--- a/content/browser/indexed_db/indexed_db_context_unittest.cc
+++ b/content/browser/indexed_db/indexed_db_context_unittest.cc
@@ -2,9 +2,13 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <memory>
+
 #include "base/barrier_closure.h"
 #include "base/files/scoped_temp_dir.h"
 #include "base/run_loop.h"
+#include "base/test/bind.h"
+#include "base/test/gmock_callback_support.h"
 #include "base/test/task_environment.h"
 #include "base/threading/thread.h"
 #include "base/time/default_clock.h"
@@ -14,10 +18,13 @@
 #include "content/browser/indexed_db/indexed_db_context_impl.h"
 #include "content/browser/indexed_db/indexed_db_factory_impl.h"
 #include "content/browser/indexed_db/mock_indexed_db_callbacks.h"
+#include "content/browser/indexed_db/mock_mojo_indexed_db_callbacks.h"
+#include "content/browser/indexed_db/mock_mojo_indexed_db_database_callbacks.h"
 #include "mojo/public/cpp/bindings/remote.h"
 #include "storage/browser/test/mock_quota_manager.h"
 #include "storage/browser/test/mock_quota_manager_proxy.h"
 #include "storage/browser/test/quota_manager_proxy_sync.h"
+#include "testing/gmock/include/gmock/gmock.h"
 #include "testing/gtest/include/gtest/gtest.h"
 #include "third_party/blink/public/common/storage_key/storage_key.h"
 
@@ -103,4 +110,84 @@
   EXPECT_GT(result->id.value(), 0);
 }
 
+TEST_F(IndexedDBContextTest, GetDefaultBucketError) {
+  // Disable database so it will return errors when getting the default bucket.
+  quota_manager_->SetDisableDatabase(true);
+
+  mojo::Remote<blink::mojom::IDBFactory> example_remote;
+  indexed_db_context_->BindIndexedDB(
+      example_storage_key_, example_remote.BindNewPipeAndPassReceiver());
+
+  // IDBFactory::GetDatabaseInfo
+  base::RunLoop loop_1;
+  auto mock_callbacks =
+      std::make_unique<testing::StrictMock<MockMojoIndexedDBCallbacks>>();
+  EXPECT_CALL(*mock_callbacks,
+              Error(blink::mojom::IDBException::kUnknownError,
+                    std::u16string(
+                        u"Internal error retrieving bucket data directory.")))
+      .Times(1)
+      .WillOnce(base::test::RunClosure(loop_1.QuitClosure()));
+
+  example_remote->GetDatabaseInfo(mock_callbacks->CreateInterfacePtrAndBind());
+  loop_1.Run();
+
+  testing::Mock::VerifyAndClear(&mock_callbacks);
+
+  // IDBFactory::Open
+  base::RunLoop loop_2;
+  mock_callbacks =
+      std::make_unique<testing::StrictMock<MockMojoIndexedDBCallbacks>>();
+  auto database_callbacks =
+      std::make_unique<MockMojoIndexedDBDatabaseCallbacks>();
+  auto transaction_remote =
+      mojo::AssociatedRemote<blink::mojom::IDBTransaction>();
+  EXPECT_CALL(*mock_callbacks,
+              Error(blink::mojom::IDBException::kUnknownError,
+                    std::u16string(
+                        u"Internal error retrieving bucket data directory.")))
+      .Times(1)
+      .WillOnce(base::test::RunClosure(loop_2.QuitClosure()));
+
+  example_remote->Open(mock_callbacks->CreateInterfacePtrAndBind(),
+                       database_callbacks->CreateInterfacePtrAndBind(),
+                       u"database_name", /*version=*/1,
+                       transaction_remote.BindNewEndpointAndPassReceiver(),
+                       /*transaction_id=*/0);
+  loop_2.Run();
+
+  // IDBFactory::DeleteDatabase
+  base::RunLoop loop_3;
+  mock_callbacks =
+      std::make_unique<testing::StrictMock<MockMojoIndexedDBCallbacks>>();
+  EXPECT_CALL(*mock_callbacks,
+              Error(blink::mojom::IDBException::kUnknownError,
+                    std::u16string(
+                        u"Internal error retrieving bucket data directory.")))
+      .Times(1)
+      .WillOnce(base::test::RunClosure(loop_3.QuitClosure()));
+
+  example_remote->DeleteDatabase(mock_callbacks->CreateInterfacePtrAndBind(),
+                                 u"database_name", /*force_close=*/true);
+  loop_3.Run();
+
+  // IDBFactory::AbortTransactionsAndCompactDatabase
+  base::RunLoop loop_4;
+  example_remote->AbortTransactionsAndCompactDatabase(
+      base::BindLambdaForTesting([&](blink::mojom::IDBStatus status) {
+        EXPECT_EQ(status, blink::mojom::IDBStatus::NotFound);
+        loop_4.Quit();
+      }));
+  loop_4.Run();
+
+  // IDBFactory::AbortTransactionsForDatabase
+  base::RunLoop loop_5;
+  example_remote->AbortTransactionsForDatabase(
+      base::BindLambdaForTesting([&](blink::mojom::IDBStatus status) {
+        EXPECT_EQ(status, blink::mojom::IDBStatus::NotFound);
+        loop_5.Quit();
+      }));
+  loop_5.Run();
+}
+
 }  // namespace content
diff --git a/content/browser/indexed_db/indexed_db_dispatcher_host.cc b/content/browser/indexed_db/indexed_db_dispatcher_host.cc
index f36e6666..51ec8705 100644
--- a/content/browser/indexed_db/indexed_db_dispatcher_host.cc
+++ b/content/browser/indexed_db/indexed_db_dispatcher_host.cc
@@ -214,10 +214,13 @@
 
 void IndexedDBDispatcherHost::AddReceiver(
     const blink::StorageKey& storage_key,
+    absl::optional<storage::BucketLocator> bucket,
     mojo::PendingReceiver<blink::mojom::IDBFactory> pending_receiver) {
   DCHECK(IDBTaskRunner()->RunsTasksInCurrentSequence());
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
-  receivers_.Add(this, std::move(pending_receiver), storage_key);
+  if (bucket.has_value())
+    DCHECK_EQ(bucket->storage_key, storage_key);
+  receivers_.Add(this, std::move(pending_receiver), bucket);
 }
 
 void IndexedDBDispatcherHost::AddDatabaseBinding(
@@ -274,10 +277,23 @@
         pending_callbacks) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
 
-  const auto& storage_key = receivers_.current_context();
+  // Return error if failed to retrieve bucket from the QuotaManager.
+  if (!receivers_.current_context().has_value()) {
+    auto callbacks = base::MakeRefCounted<IndexedDBCallbacks>(
+        this->AsWeakPtr(), blink::StorageKey(), std::move(pending_callbacks),
+        IDBTaskRunner());
+    IndexedDBDatabaseError error = IndexedDBDatabaseError(
+        blink::mojom::IDBException::kUnknownError,
+        u"Internal error retrieving bucket data directory.");
+    callbacks->OnError(error);
+    return;
+  }
+
+  const auto storage_key = receivers_.current_context()->storage_key;
   auto callbacks = base::MakeRefCounted<IndexedDBCallbacks>(
       this->AsWeakPtr(), storage_key, std::move(pending_callbacks),
       IDBTaskRunner());
+
   base::FilePath indexed_db_path = indexed_db_context_->data_path();
   indexed_db_context_->GetIDBFactory()->GetDatabaseInfo(
       std::move(callbacks), storage_key, indexed_db_path);
@@ -294,7 +310,19 @@
     int64_t transaction_id) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
 
-  const auto& storage_key = receivers_.current_context();
+  // Return error if failed to retrieve bucket from the QuotaManager.
+  if (!receivers_.current_context().has_value()) {
+    auto callbacks = base::MakeRefCounted<IndexedDBCallbacks>(
+        this->AsWeakPtr(), blink::StorageKey(), std::move(pending_callbacks),
+        IDBTaskRunner());
+    IndexedDBDatabaseError error = IndexedDBDatabaseError(
+        blink::mojom::IDBException::kUnknownError,
+        u"Internal error retrieving bucket data directory.");
+    callbacks->OnError(error);
+    return;
+  }
+
+  const auto storage_key = receivers_.current_context()->storage_key;
   auto callbacks = base::MakeRefCounted<IndexedDBCallbacks>(
       this->AsWeakPtr(), storage_key, std::move(pending_callbacks),
       IDBTaskRunner());
@@ -310,6 +338,7 @@
       std::make_unique<IndexedDBPendingConnection>(
           std::move(callbacks), std::move(database_callbacks), transaction_id,
           version, std::move(create_transaction_callback));
+
   // TODO(dgrogan): Don't let a non-existing database be opened (and therefore
   // created) if this origin is already over quota.
   indexed_db_context_->GetIDBFactory()->Open(name, std::move(connection),
@@ -322,10 +351,23 @@
     bool force_close) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
 
-  const auto& storage_key = receivers_.current_context();
+  // Return error if failed to retrieve bucket from the QuotaManager.
+  if (!receivers_.current_context().has_value()) {
+    auto callbacks = base::MakeRefCounted<IndexedDBCallbacks>(
+        this->AsWeakPtr(), blink::StorageKey(), std::move(pending_callbacks),
+        IDBTaskRunner());
+    IndexedDBDatabaseError error = IndexedDBDatabaseError(
+        blink::mojom::IDBException::kUnknownError,
+        u"Internal error retrieving bucket data directory.");
+    callbacks->OnError(error);
+    return;
+  }
+
+  const auto storage_key = receivers_.current_context()->storage_key;
   auto callbacks = base::MakeRefCounted<IndexedDBCallbacks>(
       this->AsWeakPtr(), storage_key, std::move(pending_callbacks),
       IDBTaskRunner());
+
   base::FilePath indexed_db_path = indexed_db_context_->data_path();
   indexed_db_context_->GetIDBFactory()->DeleteDatabase(
       name, std::move(callbacks), storage_key, indexed_db_path, force_close);
@@ -335,9 +377,16 @@
     AbortTransactionsAndCompactDatabaseCallback mojo_callback) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
 
-  const auto& storage_key = receivers_.current_context();
+  // Return error if failed to retrieve bucket from the QuotaManager.
+  if (!receivers_.current_context().has_value()) {
+    std::move(mojo_callback).Run(blink::mojom::IDBStatus::NotFound);
+    return;
+  }
+
+  const auto storage_key = receivers_.current_context()->storage_key;
   base::OnceCallback<void(leveldb::Status)> callback_on_io = base::BindOnce(
       &CallCompactionStatusCallbackOnIDBThread, std::move(mojo_callback));
+
   indexed_db_context_->GetIDBFactory()->AbortTransactionsAndCompactDatabase(
       std::move(callback_on_io), storage_key);
 }
@@ -346,9 +395,16 @@
     AbortTransactionsForDatabaseCallback mojo_callback) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
 
-  const auto& storage_key = receivers_.current_context();
+  // Return error if failed to retrieve bucket from the QuotaManager.
+  if (!receivers_.current_context().has_value()) {
+    std::move(mojo_callback).Run(blink::mojom::IDBStatus::NotFound);
+    return;
+  }
+
+  const auto storage_key = receivers_.current_context()->storage_key;
   base::OnceCallback<void(leveldb::Status)> callback_on_io = base::BindOnce(
       &CallAbortStatusCallbackOnIDBThread, std::move(mojo_callback));
+
   indexed_db_context_->GetIDBFactory()->AbortTransactionsForDatabase(
       std::move(callback_on_io), storage_key);
 }
diff --git a/content/browser/indexed_db/indexed_db_dispatcher_host.h b/content/browser/indexed_db/indexed_db_dispatcher_host.h
index 4768706..c96115e 100644
--- a/content/browser/indexed_db/indexed_db_dispatcher_host.h
+++ b/content/browser/indexed_db/indexed_db_dispatcher_host.h
@@ -14,6 +14,7 @@
 #include <vector>
 
 #include "base/sequence_checker.h"
+#include "components/services/storage/public/cpp/buckets/bucket_locator.h"
 #include "components/services/storage/public/mojom/blob_storage_context.mojom-forward.h"
 #include "components/services/storage/public/mojom/file_system_access_context.mojom-forward.h"
 #include "content/browser/indexed_db/indexed_db_external_object.h"
@@ -51,6 +52,7 @@
 
   void AddReceiver(
       const blink::StorageKey& storage_key,
+      absl::optional<storage::BucketLocator> bucket,
       mojo::PendingReceiver<blink::mojom::IDBFactory> pending_receiver);
 
   void AddDatabaseBinding(
@@ -136,7 +138,9 @@
   // Shared task runner used to read blob files on.
   const scoped_refptr<base::TaskRunner> file_task_runner_;
 
-  mojo::ReceiverSet<blink::mojom::IDBFactory, blink::StorageKey> receivers_;
+  mojo::ReceiverSet<blink::mojom::IDBFactory,
+                    absl::optional<storage::BucketLocator>>
+      receivers_;
   mojo::UniqueAssociatedReceiverSet<blink::mojom::IDBDatabase>
       database_receivers_;
   mojo::UniqueAssociatedReceiverSet<blink::mojom::IDBCursor> cursor_receivers_;
diff --git a/content/browser/indexed_db/indexed_db_dispatcher_host_unittest.cc b/content/browser/indexed_db/indexed_db_dispatcher_host_unittest.cc
index c63e213..fc60b471 100644
--- a/content/browser/indexed_db/indexed_db_dispatcher_host_unittest.cc
+++ b/content/browser/indexed_db/indexed_db_dispatcher_host_unittest.cc
@@ -4,11 +4,12 @@
 
 #include "content/browser/indexed_db/indexed_db_dispatcher_host.h"
 
+#include <tuple>
+
 #include "base/barrier_closure.h"
 #include "base/bind.h"
 #include "base/callback.h"
 #include "base/files/scoped_temp_dir.h"
-#include "base/ignore_result.h"
 #include "base/memory/ref_counted.h"
 #include "base/run_loop.h"
 #include "base/strings/utf_string_conversions.h"
@@ -535,7 +536,7 @@
         mojo::PendingRemote<blink::mojom::Blob> blob;
         // Ignore the result of InitWithNewPipeAndPassReceiver, to end up with
         // an invalid blob.
-        ignore_result(blob.InitWithNewPipeAndPassReceiver());
+        std::ignore = blob.InitWithNewPipeAndPassReceiver();
         external_objects.push_back(
             blink::mojom::IDBExternalObject::NewBlobOrFile(
                 blink::mojom::IDBBlobInfo::New(std::move(blob), "fakeUUID",
diff --git a/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkey_fuzzer.cc b/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkey_fuzzer.cc
index c27e56f..c44f6252 100644
--- a/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkey_fuzzer.cc
+++ b/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkey_fuzzer.cc
@@ -5,14 +5,15 @@
 #include <stddef.h>
 #include <stdint.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "content/browser/indexed_db/indexed_db_leveldb_coding.h"
 #include "third_party/blink/public/common/indexeddb/indexeddb_key.h"
 
 extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size) {
   base::StringPiece key_str_piece(reinterpret_cast<const char*>(data), size);
   auto indexed_db_key = std::make_unique<blink::IndexedDBKey>();
-  ignore_result(content::DecodeIDBKey(&key_str_piece, &indexed_db_key));
+  std::ignore = content::DecodeIDBKey(&key_str_piece, &indexed_db_key);
 
   // Ensure that encoding |indexed_db_key| produces the same result.
   std::string result;
diff --git a/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkeypath_fuzzer.cc b/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkeypath_fuzzer.cc
index 739362c0..bbee894e 100644
--- a/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkeypath_fuzzer.cc
+++ b/content/browser/indexed_db/indexed_db_leveldb_coding_decodeidbkeypath_fuzzer.cc
@@ -5,7 +5,8 @@
 #include <stddef.h>
 #include <stdint.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "content/browser/indexed_db/indexed_db_leveldb_coding.h"
 #include "third_party/blink/public/common/indexeddb/indexeddb_key_path.h"
 
@@ -13,8 +14,8 @@
   base::StringPiece key_path_str_piece(reinterpret_cast<const char*>(data),
                                        size);
   blink::IndexedDBKeyPath indexed_db_key_path;
-  ignore_result(
-      content::DecodeIDBKeyPath(&key_path_str_piece, &indexed_db_key_path));
+  std::ignore =
+      content::DecodeIDBKeyPath(&key_path_str_piece, &indexed_db_key_path);
 
   // Ensure that encoding |indexed_db_key_path| produces the same result.
   std::string result;
diff --git a/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkey_fuzzer.cc b/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkey_fuzzer.cc
index 43bdf877..670e8e1 100644
--- a/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkey_fuzzer.cc
+++ b/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkey_fuzzer.cc
@@ -7,7 +7,8 @@
 
 #include <fuzzer/FuzzedDataProvider.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/strings/string_piece.h"
 #include "base/strings/utf_string_conversions.h"
 #include "content/browser/indexed_db/indexed_db_leveldb_coding.h"
@@ -100,7 +101,7 @@
   // Ensure that |result| can be decoded back into the original key.
   auto decoded_key = std::make_unique<IndexedDBKey>();
   auto result_str_piece = base::StringPiece(result);
-  ignore_result(content::DecodeIDBKey(&result_str_piece, &decoded_key));
+  std::ignore = content::DecodeIDBKey(&result_str_piece, &decoded_key);
   assert(decoded_key->Equals(key));
   return 0;
 }
diff --git a/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkeypath_fuzzer.cc b/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkeypath_fuzzer.cc
index 641ac7f..b48b541 100644
--- a/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkeypath_fuzzer.cc
+++ b/content/browser/indexed_db/indexed_db_leveldb_coding_encodeidbkeypath_fuzzer.cc
@@ -7,7 +7,8 @@
 
 #include <fuzzer/FuzzedDataProvider.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/strings/utf_string_conversions.h"
 #include "content/browser/indexed_db/indexed_db_leveldb_coding.h"
 #include "third_party/blink/public/common/indexeddb/indexeddb_key_path.h"
@@ -56,8 +57,7 @@
   // Ensure that |result| can be decoded back into the original key path.
   IndexedDBKeyPath decoded_key_path;
   auto result_str_piece = base::StringPiece(result);
-  ignore_result(
-      content::DecodeIDBKeyPath(&result_str_piece, &decoded_key_path));
+  std::ignore = content::DecodeIDBKeyPath(&result_str_piece, &decoded_key_path);
   assert(decoded_key_path == key_path);
   return 0;
 }
diff --git a/content/browser/isolated_origin_browsertest.cc b/content/browser/isolated_origin_browsertest.cc
index 2d859c2..81abc90 100644
--- a/content/browser/isolated_origin_browsertest.cc
+++ b/content/browser/isolated_origin_browsertest.cc
@@ -3,11 +3,11 @@
 // found in the LICENSE file.
 
 #include <sstream>
+#include <tuple>
 #include <vector>
 
 #include "base/bind.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/strings/string_util.h"
 #include "base/strings/stringprintf.h"
@@ -3437,7 +3437,7 @@
 
     // Bind the real DomStorage implementation.
     mojo::PendingRemote<blink::mojom::DomStorageClient> unused_client;
-    ignore_result(unused_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = unused_client.InitWithNewPipeAndPassReceiver();
     mojo::ReceiverId receiver_id = storage_partition->BindDomStorage(
         rph->GetID(), std::move(receiver), std::move(unused_client));
 
@@ -3559,11 +3559,11 @@
 
   content::RenderProcessHostBadIpcMessageWaiter kill_waiter(
       web_contents()->GetMainFrame()->GetProcess());
-  // Use ignore_result here, since on Android the renderer process is
+  // Use std::ignore here, since on Android the renderer process is
   // terminated, but ExecuteScript still returns true. It properly returns
   // false on all other platforms.
-  ignore_result(
-      ExecJs(web_contents()->GetMainFrame(), "sessionStorage.length;"));
+  std::ignore =
+      ExecJs(web_contents()->GetMainFrame(), "sessionStorage.length;");
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
 }
 
@@ -3634,7 +3634,7 @@
   EXPECT_EQ(1, EvalJs(web_contents()->GetMainFrame(), "sessionStorage.length"));
   content::RenderProcessHostBadIpcMessageWaiter kill_waiter(
       ChildFrameAt(shell(), 0)->GetProcess());
-  ignore_result(ExecJs(ChildFrameAt(shell(), 0), "sessionStorage.length"));
+  std::ignore = ExecJs(ChildFrameAt(shell(), 0), "sessionStorage.length");
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
   // The subframe has crashed, but the main frame should still be alive and
   // working.
@@ -3706,7 +3706,7 @@
   EXPECT_EQ(1, EvalJs(web_contents()->GetMainFrame(), "localStorage.length"));
   content::RenderProcessHostBadIpcMessageWaiter kill_waiter(
       ChildFrameAt(shell(), 0)->GetProcess());
-  ignore_result(ExecJs(ChildFrameAt(shell(), 0), "localStorage.length"));
+  std::ignore = ExecJs(ChildFrameAt(shell(), 0), "localStorage.length");
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
   // The subframe has crashed, but the main frame should still be alive and
   // working.
@@ -3733,11 +3733,11 @@
 
   content::RenderProcessHostBadIpcMessageWaiter kill_waiter(
       shell()->web_contents()->GetMainFrame()->GetProcess());
-  // Use ignore_result here, since on Android the renderer process is
+  // Use std::ignore here, since on Android the renderer process is
   // terminated, but ExecuteScript still returns true. It properly returns
   // false on all other platforms.
-  ignore_result(
-      ExecJs(shell()->web_contents()->GetMainFrame(), "localStorage.length;"));
+  std::ignore =
+      ExecJs(shell()->web_contents()->GetMainFrame(), "localStorage.length;");
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
 }
 
@@ -3774,11 +3774,11 @@
 
   content::RenderProcessHostBadIpcMessageWaiter kill_waiter(
       shell()->web_contents()->GetMainFrame()->GetProcess());
-  // Use ignore_result here, since on Android the renderer process is
+  // Use std::ignore here, since on Android the renderer process is
   // terminated, but ExecuteScript still returns true. It properly returns
   // false on all other platforms.
-  ignore_result(
-      ExecJs(shell()->web_contents()->GetMainFrame(), "localStorage.length;"));
+  std::ignore =
+      ExecJs(shell()->web_contents()->GetMainFrame(), "localStorage.length;");
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
 }
 
@@ -3801,11 +3801,11 @@
 
   content::RenderProcessHostBadIpcMessageWaiter kill_waiter(
       shell()->web_contents()->GetMainFrame()->GetProcess());
-  // Use ignore_result here, since on Android the renderer process is
+  // Use std::ignore here, since on Android the renderer process is
   // terminated, but ExecuteScript still returns true. It properly returns
   // false on all other platforms.
-  ignore_result(
-      ExecJs(shell()->web_contents()->GetMainFrame(), "localStorage.length;"));
+  std::ignore =
+      ExecJs(shell()->web_contents()->GetMainFrame(), "localStorage.length;");
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
 }
 
diff --git a/content/browser/media/forwarding_audio_stream_factory_unittest.cc b/content/browser/media/forwarding_audio_stream_factory_unittest.cc
index 935e6db6..4a337de 100644
--- a/content/browser/media/forwarding_audio_stream_factory_unittest.cc
+++ b/content/browser/media/forwarding_audio_stream_factory_unittest.cc
@@ -5,11 +5,11 @@
 #include "content/browser/media/forwarding_audio_stream_factory.h"
 
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/run_loop.h"
 #include "base/test/mock_callback.h"
@@ -277,7 +277,7 @@
                                        std::move(broker_factory_));
 
   EXPECT_CALL(*broker, CreateStream(NotNull()));
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateInputStream(main_rfh()->GetProcess()->GetID(),
                                     main_rfh()->GetRoutingID(), kInputDeviceId,
                                     kParams, kSharedMemoryCount, kEnableAgc,
@@ -301,7 +301,7 @@
       std::make_unique<MockBrokerFactory>());
 
   EXPECT_CALL(*broker, CreateStream(NotNull()));
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateLoopbackStream(
       main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
       source_factory.core(), kParams, kSharedMemoryCount, kMuteSource,
@@ -318,7 +318,7 @@
                                        std::move(broker_factory_));
 
   EXPECT_CALL(*broker, CreateStream(NotNull()));
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateOutputStream(
       main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
       kOutputDeviceId, kParams, std::move(client));
@@ -339,7 +339,7 @@
     EXPECT_CALL(*main_rfh_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateInputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kInputDeviceId, kParams, kSharedMemoryCount, kEnableAgc,
@@ -350,7 +350,7 @@
     EXPECT_CALL(*other_rfh_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateInputStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         kInputDeviceId, kParams, kSharedMemoryCount, kEnableAgc,
@@ -384,7 +384,7 @@
     EXPECT_CALL(*main_rfh_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateLoopbackStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         source_factory.core(), kParams, kSharedMemoryCount, kMuteSource,
@@ -395,7 +395,7 @@
     EXPECT_CALL(*other_rfh_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateLoopbackStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         source_factory.core(), kParams, kSharedMemoryCount, kMuteSource,
@@ -423,7 +423,7 @@
   {
     EXPECT_CALL(*main_rfh_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient> client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(client));
@@ -432,7 +432,7 @@
   {
     EXPECT_CALL(*other_rfh_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient> client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(client));
@@ -475,7 +475,7 @@
     EXPECT_CALL(*main_rfh_input_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         input_client;
-    ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = input_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateInputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kInputDeviceId, kParams, kSharedMemoryCount, kEnableAgc,
@@ -486,7 +486,7 @@
     EXPECT_CALL(*other_rfh_input_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         input_client;
-    ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = input_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateInputStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         kInputDeviceId, kParams, kSharedMemoryCount, kEnableAgc,
@@ -498,7 +498,7 @@
     EXPECT_CALL(*main_rfh_loopback_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         input_client;
-    ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = input_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateLoopbackStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         source_factory.core(), kParams, kSharedMemoryCount, kMuteSource,
@@ -509,7 +509,7 @@
     EXPECT_CALL(*other_rfh_loopback_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         input_client;
-    ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = input_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateLoopbackStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         source_factory.core(), kParams, kSharedMemoryCount, kMuteSource,
@@ -521,7 +521,7 @@
     EXPECT_CALL(*main_rfh_output_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient>
         output_client;
-    ignore_result(output_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = output_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(output_client));
@@ -531,7 +531,7 @@
     EXPECT_CALL(*other_rfh_output_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient>
         output_client;
-    ignore_result(output_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = output_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(output_client));
@@ -568,14 +568,14 @@
                                        std::move(broker_factory_));
 
   EXPECT_CALL(*input_broker, CreateStream(NotNull()));
-  ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+  std::ignore = input_client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateInputStream(main_rfh()->GetProcess()->GetID(),
                                     main_rfh()->GetRoutingID(), kInputDeviceId,
                                     kParams, kSharedMemoryCount, kEnableAgc,
                                     std::move(input_client));
 
   EXPECT_CALL(*output_broker, CreateStream(NotNull()));
-  ignore_result(output_client.InitWithNewPipeAndPassReceiver());
+  std::ignore = output_client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateOutputStream(
       main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
       kOutputDeviceId, kParams, std::move(output_client));
@@ -608,7 +608,7 @@
     EXPECT_CALL(*main_rfh_input_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         input_client;
-    ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = input_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateInputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kInputDeviceId, kParams, kSharedMemoryCount, kEnableAgc,
@@ -619,7 +619,7 @@
     EXPECT_CALL(*other_rfh_input_broker, CreateStream(NotNull()));
     mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
         input_client;
-    ignore_result(input_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = input_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateInputStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         kInputDeviceId, kParams, kSharedMemoryCount, kEnableAgc,
@@ -631,7 +631,7 @@
     EXPECT_CALL(*main_rfh_output_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient>
         output_client;
-    ignore_result(output_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = output_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(output_client));
@@ -641,7 +641,7 @@
     EXPECT_CALL(*other_rfh_output_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient>
         output_client;
-    ignore_result(output_client.InitWithNewPipeAndPassReceiver());
+    std::ignore = output_client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         other_rfh()->GetProcess()->GetID(), other_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(output_client));
@@ -697,7 +697,7 @@
                                        std::move(broker_factory_));
 
   EXPECT_CALL(*broker, CreateStream(NotNull()));
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateOutputStream(
       main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
       kOutputDeviceId, kParams, std::move(client));
@@ -738,7 +738,7 @@
   EXPECT_FALSE(stream_factory_.IsMuterConnected());
 
   EXPECT_CALL(*broker, CreateStream(NotNull()));
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory.core()->CreateOutputStream(
       main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
       kOutputDeviceId, kParams, std::move(client));
@@ -768,7 +768,7 @@
   {
     EXPECT_CALL(*broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient> client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(client));
@@ -787,7 +787,7 @@
   {
     EXPECT_CALL(*another_broker, CreateStream(NotNull()));
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient> client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     factory.core()->CreateOutputStream(
         main_rfh()->GetProcess()->GetID(), main_rfh()->GetRoutingID(),
         kOutputDeviceId, kParams, std::move(client));
diff --git a/content/browser/media/frameless_media_interface_proxy.cc b/content/browser/media/frameless_media_interface_proxy.cc
index 482d1827..fcaa137e 100644
--- a/content/browser/media/frameless_media_interface_proxy.cc
+++ b/content/browser/media/frameless_media_interface_proxy.cc
@@ -4,8 +4,9 @@
 
 #include "content/browser/media/frameless_media_interface_proxy.h"
 
+#include <tuple>
+
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "content/public/browser/media_service.h"
 #include "media/base/cdm_context.h"
@@ -114,7 +115,7 @@
   DCHECK(!interface_factory_remote_);
 
   mojo::PendingRemote<media::mojom::FrameInterfaceFactory> interfaces;
-  ignore_result(interfaces.InitWithNewPipeAndPassReceiver());
+  std::ignore = interfaces.InitWithNewPipeAndPassReceiver();
 
   GetMediaService().CreateInterfaceFactory(
       interface_factory_remote_.BindNewPipeAndPassReceiver(),
diff --git a/content/browser/media/key_system_support_impl.cc b/content/browser/media/key_system_support_impl.cc
index 5ff77df..f8684e5d 100644
--- a/content/browser/media/key_system_support_impl.cc
+++ b/content/browser/media/key_system_support_impl.cc
@@ -4,12 +4,12 @@
 
 #include "content/browser/media/key_system_support_impl.h"
 
+#include <tuple>
 #include <vector>
 
 #include "base/command_line.h"
 #include "base/containers/flat_set.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/metrics/histogram_functions.h"
 #include "base/strings/string_split.h"
@@ -265,9 +265,8 @@
   // parallel `IsKeySystemSupported()` calls from different renderer processes.
   // This is okay and won't cause collision or corruption of data.
   if (lazy_initialize) {
-    ignore_result(CdmRegistryImpl::GetInstance()->FinalizeCdmCapability(
-        key_system, CdmInfo::Robustness::kHardwareSecure,
-        hw_secure_capability));
+    std::ignore = CdmRegistryImpl::GetInstance()->FinalizeCdmCapability(
+        key_system, CdmInfo::Robustness::kHardwareSecure, hw_secure_capability);
   }
 
   auto capability = media::mojom::KeySystemCapability::New();
diff --git a/content/browser/media/media_interface_proxy.cc b/content/browser/media/media_interface_proxy.cc
index ecca0cb..84bc823 100644
--- a/content/browser/media/media_interface_proxy.cc
+++ b/content/browser/media/media_interface_proxy.cc
@@ -7,9 +7,9 @@
 #include <map>
 #include <memory>
 #include <string>
+#include <tuple>
 
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/memory/raw_ptr.h"
 #include "base/no_destructor.h"
@@ -118,7 +118,7 @@
   } else {
     // The embedder doesn't provide a secondary Media Service instance. Bind
     // permanently to a disconnected pipe which discards all calls.
-    ignore_result(remote->BindNewPipeAndPassReceiver());
+    std::ignore = remote->BindNewPipeAndPassReceiver();
   }
 }
 
diff --git a/content/browser/portal/portal_browsertest.cc b/content/browser/portal/portal_browsertest.cc
index 258c45e7..b2e4112 100644
--- a/content/browser/portal/portal_browsertest.cc
+++ b/content/browser/portal/portal_browsertest.cc
@@ -9,7 +9,6 @@
 #include "base/bind.h"
 #include "base/callback.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/memory/ptr_util.h"
 #include "base/memory/raw_ptr.h"
 #include "base/run_loop.h"
@@ -810,7 +809,7 @@
       portal));
   RenderProcessHostBadIpcMessageWaiter kill_waiter(main_frame->GetProcess());
   GURL a_url(embedded_test_server()->GetURL("a.com", "/title1.html"));
-  ignore_result(ExecJs(main_frame, JsReplace("portal.src = $1;", a_url)));
+  std::ignore = ExecJs(main_frame, JsReplace("portal.src = $1;", a_url));
 
   EXPECT_EQ(bad_message::RPH_MOJO_PROCESS_ERROR, kill_waiter.Wait());
 }
diff --git a/content/browser/prerender/prerender_browsertest.cc b/content/browser/prerender/prerender_browsertest.cc
index 701da2f..a75cf0a 100644
--- a/content/browser/prerender/prerender_browsertest.cc
+++ b/content/browser/prerender/prerender_browsertest.cc
@@ -3,6 +3,7 @@
 // found in the LICENSE file.
 
 #include <cstdint>
+#include <tuple>
 
 #include "base/barrier_closure.h"
 #include "base/base_switches.h"
@@ -11,7 +12,6 @@
 #include "base/containers/flat_set.h"
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/memory/weak_ptr.h"
 #include "base/metrics/metrics_hashes.h"
@@ -579,10 +579,10 @@
   // Fetch a subframe that requires authentication.
   const GURL kAuthIFrameUrl = GetUrl("/auth-basic");
   RenderFrameHost* prerender_rfh = GetPrerenderedMainFrameHost(host_id);
-  ignore_result(ExecJs(prerender_rfh,
-                       "var i = document.createElement('iframe'); i.src = '" +
-                           kAuthIFrameUrl.spec() +
-                           "'; document.body.appendChild(i);"));
+  std::ignore =
+      ExecJs(prerender_rfh,
+             "var i = document.createElement('iframe'); i.src = '" +
+                 kAuthIFrameUrl.spec() + "'; document.body.appendChild(i);");
 
   // The prerender should be destroyed.
   host_observer.WaitForDestroyed();
@@ -618,8 +618,8 @@
         imgElement.src = '/auth-basic/favicon.gif';
         document.body.appendChild(imgElement);
   )";
-  ignore_result(
-      ExecJs(GetPrerenderedMainFrameHost(host_id), fetch_subresource_script));
+  std::ignore =
+      ExecJs(GetPrerenderedMainFrameHost(host_id), fetch_subresource_script);
 
   // The prerender should be destroyed.
   host_observer.WaitForDestroyed();
@@ -2143,8 +2143,8 @@
         imgElement.src = '/load_image/image.png';
         document.body.appendChild(imgElement);
   )";
-  ignore_result(ExecJs(prerender_helper()->GetPrerenderedMainFrameHost(host_id),
-                       fetch_subresource_script));
+  std::ignore = ExecJs(prerender_helper()->GetPrerenderedMainFrameHost(host_id),
+                       fetch_subresource_script);
 
   // The prerender should be destroyed.
   host_observer.WaitForDestroyed();
@@ -2215,8 +2215,8 @@
   // server should ask for a client certificate or respond with an expired
   // certificate, which leads to the cancellation of prerendering.
   std::string resource_url = GetUrl("/workers/empty.js?intercept").spec();
-  ignore_result(ExecJs(prerender_helper()->GetPrerenderedMainFrameHost(host_id),
-                       JsReplace("fetch($1);", resource_url)));
+  std::ignore = ExecJs(prerender_helper()->GetPrerenderedMainFrameHost(host_id),
+                       JsReplace("fetch($1);", resource_url));
 
   // Check the prerender was destroyed.
   host_observer.WaitForDestroyed();
@@ -2609,8 +2609,8 @@
 
   // Executing `navigator.getGamepads()` to start binding the GamepadMonitor
   // interface.
-  ignore_result(EvalJs(prerender_render_frame_host, "navigator.getGamepads()",
-                       EvalJsOptions::EXECUTE_SCRIPT_NO_USER_GESTURE));
+  std::ignore = EvalJs(prerender_render_frame_host, "navigator.getGamepads()",
+                       EvalJsOptions::EXECUTE_SCRIPT_NO_USER_GESTURE);
   // Verify Mojo capability control cancels prerendering.
   EXPECT_FALSE(HasHostForUrl(kPrerenderingUrl));
   histogram_tester.ExpectUniqueSample(
@@ -2883,8 +2883,8 @@
   // Whether using the EXECUTE_SCRIPT_NO_USER_GESTURE flag or not does not
   // affect the test result. The purpose of using it is to simulate real
   // scenarios since prerendering pages cannot have user gestures.
-  ignore_result(ExecJs(prerender_rfh, "const context = new AudioContext();",
-                       EvalJsOptions::EXECUTE_SCRIPT_NO_USER_GESTURE));
+  std::ignore = ExecJs(prerender_rfh, "const context = new AudioContext();",
+                       EvalJsOptions::EXECUTE_SCRIPT_NO_USER_GESTURE);
   host_observer.WaitForDestroyed();
   EXPECT_FALSE(HasHostForUrl(kPrerenderingUrl));
   histogram_tester.ExpectUniqueSample(
diff --git a/content/browser/presentation/presentation_service_impl_unittest.cc b/content/browser/presentation/presentation_service_impl_unittest.cc
index 9ef865d..21e4306 100644
--- a/content/browser/presentation/presentation_service_impl_unittest.cc
+++ b/content/browser/presentation/presentation_service_impl_unittest.cc
@@ -10,12 +10,12 @@
 #include <iterator>
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 #include <vector>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/strings/stringprintf.h"
 #include "content/browser/presentation/presentation_test_utils.h"
@@ -251,8 +251,7 @@
 
   mojo::PendingRemote<PresentationConnection> presentation_connection_remote;
   mojo::Remote<PresentationConnection> controller_remote;
-  ignore_result(
-      presentation_connection_remote.InitWithNewPipeAndPassReceiver());
+  std::ignore = presentation_connection_remote.InitWithNewPipeAndPassReceiver();
   std::move(callback).Run(PresentationConnectionResult::New(
       blink::mojom::PresentationInfo::New(presentation_url2_, kPresentationId),
       std::move(presentation_connection_remote),
diff --git a/content/browser/renderer_host/frame_tree_browsertest.cc b/content/browser/renderer_host/frame_tree_browsertest.cc
index 42295e8..654cf4a 100644
--- a/content/browser/renderer_host/frame_tree_browsertest.cc
+++ b/content/browser/renderer_host/frame_tree_browsertest.cc
@@ -1778,15 +1778,8 @@
   EXPECT_TRUE(ExecJs(root, "localStorage[\"foo\"] = \"c\""));
   EXPECT_EQ("c", EvalJs(root, "localStorage[\"foo\"]"));
 
-  // TODO(crbug.com/1199077) This should return "a" once StorageKey starts
-  // using the nonce for partitioning. Also remove the shadowDOM specific check
-  // once nonce support is complete (for MPArch, possibly due to a separate
-  // process and incomplete nonce support, it is returning "a" on some
-  // platforms).
-  if (GetParam() ==
-      blink::features::FencedFramesImplementationType::kShadowDOM) {
-    EXPECT_EQ("c", EvalJs(fenced_frame, "localStorage[\"foo\"]"));
-  }
+  // This shouldn't impact the fenced frame's local storage:
+  EXPECT_EQ("a", EvalJs(fenced_frame, "localStorage[\"foo\"]"));
 }
 
 IN_PROC_BROWSER_TEST_P(FencedFrameTreeBrowserTest,
diff --git a/content/browser/renderer_host/input/autoscroll_browsertest.cc b/content/browser/renderer_host/input/autoscroll_browsertest.cc
index 8c8f189f..43f7768 100644
--- a/content/browser/renderer_host/input/autoscroll_browsertest.cc
+++ b/content/browser/renderer_host/input/autoscroll_browsertest.cc
@@ -2,8 +2,9 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
+
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "build/build_config.h"
 #include "content/browser/web_contents/web_contents_impl.h"
 #include "content/public/common/content_switches.h"
@@ -119,7 +120,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     MainThreadFrameObserver main_thread_sync(host);
     main_thread_sync.Wait();
diff --git a/content/browser/renderer_host/input/composited_scrolling_browsertest.cc b/content/browser/renderer_host/input/composited_scrolling_browsertest.cc
index d179bb16..ecb5ab8 100644
--- a/content/browser/renderer_host/input/composited_scrolling_browsertest.cc
+++ b/content/browser/renderer_host/input/composited_scrolling_browsertest.cc
@@ -2,11 +2,11 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/strings/utf_string_conversions.h"
 #include "base/test/metrics/histogram_tester.h"
@@ -107,7 +107,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     // Wait for the hit test data to be ready after initiating URL loading
     // before returning
diff --git a/content/browser/renderer_host/input/compositor_event_ack_browsertest.cc b/content/browser/renderer_host/input/compositor_event_ack_browsertest.cc
index 7ced1c5..9a4c91d 100644
--- a/content/browser/renderer_host/input/compositor_event_ack_browsertest.cc
+++ b/content/browser/renderer_host/input/compositor_event_ack_browsertest.cc
@@ -2,12 +2,12 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
 #include <utility>
 
 #include "base/auto_reset.h"
 #include "base/bind.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/strings/utf_string_conversions.h"
 #include "build/build_config.h"
@@ -137,7 +137,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     // SetSize triggers an animation of the size, leading to a a new
     // viz::LocalSurfaceId being generated. Since this was done right after
diff --git a/content/browser/renderer_host/input/fling_browsertest.cc b/content/browser/renderer_host/input/fling_browsertest.cc
index d6e2a62..91757d4b 100644
--- a/content/browser/renderer_host/input/fling_browsertest.cc
+++ b/content/browser/renderer_host/input/fling_browsertest.cc
@@ -2,8 +2,9 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
+
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/memory/raw_ptr.h"
 #include "base/test/scoped_feature_list.h"
 #include "build/build_config.h"
@@ -104,7 +105,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
     SynchronizeThreads();
   }
 
diff --git a/content/browser/renderer_host/input/input_event_browsertest.cc b/content/browser/renderer_host/input/input_event_browsertest.cc
index 6ecd6ed..abafe046 100644
--- a/content/browser/renderer_host/input/input_event_browsertest.cc
+++ b/content/browser/renderer_host/input/input_event_browsertest.cc
@@ -2,8 +2,9 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
+
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/strings/utf_string_conversions.h"
 #include "base/test/bind.h"
@@ -95,7 +96,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     // We need to wait until hit test data is available. We use our own
     // HitTestRegionObserver here because we have the RenderWidgetHostImpl
diff --git a/content/browser/renderer_host/input/main_thread_event_queue_browsertest.cc b/content/browser/renderer_host/input/main_thread_event_queue_browsertest.cc
index ac3ff27..2cff438 100644
--- a/content/browser/renderer_host/input/main_thread_event_queue_browsertest.cc
+++ b/content/browser/renderer_host/input/main_thread_event_queue_browsertest.cc
@@ -2,12 +2,12 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
 #include <utility>
 
 #include "base/auto_reset.h"
 #include "base/bind.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/strings/utf_string_conversions.h"
 #include "build/build_config.h"
@@ -105,7 +105,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     HitTestRegionObserver observer(host->GetFrameSinkId());
     observer.WaitForHitTestData();
diff --git a/content/browser/renderer_host/input/scroll_behavior_browsertest.cc b/content/browser/renderer_host/input/scroll_behavior_browsertest.cc
index bfb1458..f0ca2f6 100644
--- a/content/browser/renderer_host/input/scroll_behavior_browsertest.cc
+++ b/content/browser/renderer_host/input/scroll_behavior_browsertest.cc
@@ -3,9 +3,9 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "build/build_config.h"
 #include "cc/base/switches.h"
@@ -184,7 +184,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     HitTestRegionObserver observer(host->GetFrameSinkId());
     // Wait for the hit test data to be ready
diff --git a/content/browser/renderer_host/input/synthetic_input_browsertest.cc b/content/browser/renderer_host/input/synthetic_input_browsertest.cc
index d7f815b..daf4f1b 100644
--- a/content/browser/renderer_host/input/synthetic_input_browsertest.cc
+++ b/content/browser/renderer_host/input/synthetic_input_browsertest.cc
@@ -3,10 +3,10 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/callback.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/test/test_timeouts.h"
 #include "build/build_config.h"
@@ -58,7 +58,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     // Wait for the hit test data to be ready after initiating URL loading
     // before returning
diff --git a/content/browser/renderer_host/input/touch_action_browsertest.cc b/content/browser/renderer_host/input/touch_action_browsertest.cc
index af00296..32cc566d 100644
--- a/content/browser/renderer_host/input/touch_action_browsertest.cc
+++ b/content/browser/renderer_host/input/touch_action_browsertest.cc
@@ -2,13 +2,13 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
+#include <tuple>
 #include <utility>
 
 #include "base/auto_reset.h"
 #include "base/bind.h"
 #include "base/callback_helpers.h"
 #include "base/command_line.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/run_loop.h"
 #include "base/strings/stringprintf.h"
@@ -170,7 +170,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     // We need to wait until hit test data is available. We use our own
     // HitTestRegionObserver here because we have the RenderWidgetHostImpl
diff --git a/content/browser/renderer_host/input/wheel_event_listener_browsertest.cc b/content/browser/renderer_host/input/wheel_event_listener_browsertest.cc
index c40c2607..91ada9d 100644
--- a/content/browser/renderer_host/input/wheel_event_listener_browsertest.cc
+++ b/content/browser/renderer_host/input/wheel_event_listener_browsertest.cc
@@ -2,7 +2,8 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/test/scoped_feature_list.h"
 #include "content/browser/web_contents/web_contents_impl.h"
 #include "content/public/common/content_features.h"
@@ -79,7 +80,7 @@
 
     std::u16string ready_title(u"ready");
     TitleWatcher watcher(shell()->web_contents(), ready_title);
-    ignore_result(watcher.WaitAndGetTitle());
+    std::ignore = watcher.WaitAndGetTitle();
 
     MainThreadFrameObserver main_thread_sync(host);
     main_thread_sync.Wait();
diff --git a/content/browser/renderer_host/media/media_devices_dispatcher_host.cc b/content/browser/renderer_host/media/media_devices_dispatcher_host.cc
index 073b8291..15a05c73 100644
--- a/content/browser/renderer_host/media/media_devices_dispatcher_host.cc
+++ b/content/browser/renderer_host/media/media_devices_dispatcher_host.cc
@@ -278,6 +278,7 @@
               // so we execute directly.
               bad_message::ReceivedBadMessage(render_process_id,
                                               bad_message::MDDH_NOT_TOP_LEVEL);
+              return;
             }
             rfhi->delegate()->SetCaptureHandleConfig(std::move(config));
           },
diff --git a/content/browser/renderer_host/media/render_frame_audio_input_stream_factory_unittest.cc b/content/browser/renderer_host/media/render_frame_audio_input_stream_factory_unittest.cc
index 6966c4b..214da21 100644
--- a/content/browser/renderer_host/media/render_frame_audio_input_stream_factory_unittest.cc
+++ b/content/browser/renderer_host/media/render_frame_audio_input_stream_factory_unittest.cc
@@ -5,11 +5,11 @@
 #include "content/browser/renderer_host/media/render_frame_audio_input_stream_factory.h"
 
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "build/build_config.h"
 #include "build/chromeos_buildflags.h"
@@ -217,7 +217,7 @@
 
   mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
       client;
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory_remote->CreateStream(std::move(client), session_id, kParams, kAGC,
                                kSharedMemoryCount);
 
@@ -245,7 +245,7 @@
 
   mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
       client;
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory_remote->CreateStream(std::move(client), session_id, kParams, kAGC,
                                kSharedMemoryCount);
 
@@ -274,7 +274,7 @@
   source_contents.reset();
   mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
       client;
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory_remote->CreateStream(std::move(client), session_id, kParams, kAGC,
                                kSharedMemoryCount);
 
@@ -293,7 +293,7 @@
   base::UnguessableToken session_id = base::UnguessableToken::Create();
   mojo::PendingRemote<blink::mojom::RendererAudioInputStreamFactoryClient>
       client;
-  ignore_result(client.InitWithNewPipeAndPassReceiver());
+  std::ignore = client.InitWithNewPipeAndPassReceiver();
   factory_remote->CreateStream(std::move(client), session_id, kParams, kAGC,
                                kSharedMemoryCount);
 
diff --git a/content/browser/renderer_host/media/render_frame_audio_output_stream_factory_unittest.cc b/content/browser/renderer_host/media/render_frame_audio_output_stream_factory_unittest.cc
index 1ba8195..d924cb10 100644
--- a/content/browser/renderer_host/media/render_frame_audio_output_stream_factory_unittest.cc
+++ b/content/browser/renderer_host/media/render_frame_audio_output_stream_factory_unittest.cc
@@ -6,11 +6,11 @@
 
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/test/mock_callback.h"
 #include "base/test/task_environment.h"
@@ -217,7 +217,7 @@
       kDefaultDeviceId, mock_callback.Get());
   {
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient> client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     provider_remote->Acquire(kParams, std::move(client));
   }
 
@@ -256,7 +256,7 @@
   // Now factory is destructed. Trying to create a stream should fail.
   {
     mojo::PendingRemote<media::mojom::AudioOutputStreamProviderClient> client;
-    ignore_result(client.InitWithNewPipeAndPassReceiver());
+    std::ignore = client.InitWithNewPipeAndPassReceiver();
     provider_remote->Acquire(kParams, std::move(client));
   }
 
diff --git a/content/browser/renderer_host/pepper/quota_reservation.cc b/content/browser/renderer_host/pepper/quota_reservation.cc
index 286b832..f768ce1 100644
--- a/content/browser/renderer_host/pepper/quota_reservation.cc
+++ b/content/browser/renderer_host/pepper/quota_reservation.cc
@@ -5,10 +5,10 @@
 #include "content/browser/renderer_host/pepper/quota_reservation.h"
 
 #include <memory>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/callback.h"
-#include "base/ignore_result.h"
 #include "content/public/browser/browser_task_traits.h"
 #include "content/public/browser/browser_thread.h"
 #include "storage/browser/file_system/file_system_operation_runner.h"
@@ -75,7 +75,7 @@
       files_.insert(std::make_pair(id, file_handle.get()));
   if (insert_result.second) {
     int64_t max_written_offset = file_handle->GetMaxWrittenOffset();
-    ignore_result(file_handle.release());
+    std::ignore = file_handle.release();
     return max_written_offset;
   }
   NOTREACHED();
diff --git a/content/browser/renderer_host/render_frame_host_impl.cc b/content/browser/renderer_host/render_frame_host_impl.cc
index 0d42081..4d44187a 100644
--- a/content/browser/renderer_host/render_frame_host_impl.cc
+++ b/content/browser/renderer_host/render_frame_host_impl.cc
@@ -6,6 +6,7 @@
 
 #include <algorithm>
 #include <memory>
+#include <tuple>
 #include <unordered_map>
 #include <utility>
 
@@ -17,7 +18,6 @@
 #include "base/debug/crash_logging.h"
 #include "base/debug/dump_without_crashing.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/memory/memory_pressure_monitor.h"
 #include "base/memory/ptr_util.h"
@@ -2454,8 +2454,7 @@
     } else {
       // The channel may not be initialized in some tests environments. In this
       // case we set up a dummy interface provider.
-      ignore_result(
-          remote_interfaces.BindNewEndpointAndPassDedicatedReceiver());
+      std::ignore = remote_interfaces.BindNewEndpointAndPassDedicatedReceiver();
     }
     remote_associated_interfaces_ =
         std::make_unique<blink::AssociatedInterfaceProvider>(
diff --git a/content/browser/renderer_host/render_frame_host_impl_browsertest.cc b/content/browser/renderer_host/render_frame_host_impl_browsertest.cc
index 1356a72..51b5031 100644
--- a/content/browser/renderer_host/render_frame_host_impl_browsertest.cc
+++ b/content/browser/renderer_host/render_frame_host_impl_browsertest.cc
@@ -7,12 +7,12 @@
 #include <memory>
 #include <set>
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
 #include "base/files/file_path.h"
-#include "base/ignore_result.h"
 #include "base/memory/ptr_util.h"
 #include "base/memory/raw_ptr.h"
 #include "base/path_service.h"
@@ -3133,7 +3133,7 @@
   // soon, let's wait until the document.readyState finalizes. We don't really
   // care if that succeeds since, in the failing case, the renderer is crashing.
   EXPECT_TRUE(NavigateToURL(shell(), url));
-  ignore_result(WaitForRenderFrameReady(web_contents()->GetMainFrame()));
+  std::ignore = WaitForRenderFrameReady(web_contents()->GetMainFrame());
 
   EXPECT_TRUE(crash_observer.did_exit_normally());
 }
diff --git a/content/browser/renderer_host/render_frame_proxy_host.cc b/content/browser/renderer_host/render_frame_proxy_host.cc
index 71ead2f..0c456ae 100644
--- a/content/browser/renderer_host/render_frame_proxy_host.cc
+++ b/content/browser/renderer_host/render_frame_proxy_host.cc
@@ -5,6 +5,7 @@
 #include "content/browser/renderer_host/render_frame_proxy_host.h"
 
 #include <memory>
+#include <tuple>
 #include <unordered_map>
 #include <utility>
 #include <vector>
@@ -13,7 +14,6 @@
 #include "base/containers/circular_deque.h"
 #include "base/containers/contains.h"
 #include "base/hash/hash.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/no_destructor.h"
 #include "base/stl_util.h"
@@ -345,8 +345,7 @@
     } else {
       // The channel may not be initialized in some tests environments. In this
       // case we set up a dummy interface provider.
-      ignore_result(
-          remote_interfaces.BindNewEndpointAndPassDedicatedReceiver());
+      std::ignore = remote_interfaces.BindNewEndpointAndPassDedicatedReceiver();
     }
     remote_associated_interfaces_ =
         std::make_unique<blink::AssociatedInterfaceProvider>(
diff --git a/content/browser/renderer_host/render_widget_host_view_mac.mm b/content/browser/renderer_host/render_widget_host_view_mac.mm
index 9b276a3..86da1b5 100644
--- a/content/browser/renderer_host/render_widget_host_view_mac.mm
+++ b/content/browser/renderer_host/render_widget_host_view_mac.mm
@@ -8,13 +8,13 @@
 
 #include <limits>
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/auto_reset.h"
 #include "base/bind.h"
 #include "base/command_line.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/mac/mac_util.h"
 #include "base/mac/scoped_cftyperef.h"
@@ -226,7 +226,7 @@
     // first to rebaseline some unreliable web tests.
     // NOTE: This will not be run for child frame widgets, which do not have
     // an owner delegate and won't get a RenderViewHost here.
-    ignore_result(owner_delegate->GetWebkitPreferencesForWidget());
+    std::ignore = owner_delegate->GetWebkitPreferencesForWidget();
   }
 
   cursor_manager_ = std::make_unique<CursorManager>(this);
diff --git a/content/browser/resources/attribution_reporting/attribution_internals.html b/content/browser/resources/attribution_reporting/attribution_internals.html
index 0287749..09f9caf 100644
--- a/content/browser/resources/attribution_reporting/attribution_internals.html
+++ b/content/browser/resources/attribution_reporting/attribution_internals.html
@@ -33,7 +33,7 @@
   <h2> Sent and Pending Reports </h2>
   <div class="content">
     <div>
-      <button id="send-reports">Send All Pending Reports</button>
+      <button id="send-reports" disabled>Send Selected Pending Reports</button>
     </div>
     <div>
       <span id="debug-mode-content"></span>
diff --git a/content/browser/resources/attribution_reporting/attribution_internals.js b/content/browser/resources/attribution_reporting/attribution_internals.js
index b6d91aff..faf237b 100644
--- a/content/browser/resources/attribution_reporting/attribution_internals.js
+++ b/content/browser/resources/attribution_reporting/attribution_internals.js
@@ -27,9 +27,34 @@
 
 /**
  * @template T
- * @template V
+ * @abstract
  */
 class Column {
+  constructor() {
+    /** @type {?function(!T, !T): number} */
+    this.compare;
+  }
+
+  /**
+   * @param {!Element} td
+   * @param {!T} row
+   * @abstract
+   */
+  render(td, row) {}
+
+  /**
+   * @param {!Element} th
+   * @abstract
+   */
+  renderHeader(th) {}
+}
+
+/**
+ * @template T
+ * @template V
+ * @extends {Column<T>}
+ */
+class ValueColumn extends Column {
   /**
    * @param {string} header
    * @param {function(!T): !V} getValue
@@ -38,6 +63,8 @@
   constructor(
       header, getValue,
       compare = (a, b) => compareDefault(getValue(a), getValue(b))) {
+    super();
+
     this.header = header;
 
     /** @protected */
@@ -46,20 +73,22 @@
     this.compare = compare;
   }
 
-  /**
-   * @param {!Element} td
-   * @param {!T} row
-   */
+  /** @override */
   render(td, row) {
     td.innerText = this.getValue(row);
   }
+
+  /** @override */
+  renderHeader(th) {
+    th.innerText = this.header;
+  }
 }
 
 /**
  * @template T
- * @extends {Column<T, Date>}
+ * @extends {ValueColumn<T, Date>}
  */
-class DateColumn extends Column {
+class DateColumn extends ValueColumn {
   /**
    * @param {string} header
    * @param {function(!T): Date} getValue
@@ -76,9 +105,9 @@
 
 /**
  * @template T
- * @extends {Column<T, string>}
+ * @extends {ValueColumn<T, string>}
  */
-class CodeColumn extends Column {
+class CodeColumn extends ValueColumn {
   /**
    * @param {string} header
    * @param {function(!T): string} getValue
@@ -105,10 +134,7 @@
  */
 class TableModel {
   constructor() {
-    /** @type {?Table<T>} */
-    this.table;
-
-    /** @type {!Array<Column<T, ?>>} */
+    /** @type {!Array<Column<T>>} */
     this.cols;
 
     /** @type {string} */
@@ -116,6 +142,9 @@
 
     /** @type {number} */
     this.sortIdx = -1;
+
+    /** @type {!Set<function()>} */
+    this.rowsChangedListeners = new Set();
   }
 
   /**
@@ -129,6 +158,95 @@
    * @return {!Array<!T>}
    */
   getRows() {}
+
+  notifyRowsChanged() {
+    this.rowsChangedListeners.forEach((f) => f());
+  }
+}
+
+class Selectable {
+  constructor() {
+    this.input = document.createElement('input');
+    this.input.type = 'checkbox';
+  }
+}
+
+/**
+ * @template T
+ * @extends {Column<T>}
+ */
+class SelectionColumn extends Column {
+  /**
+   * @param {!TableModel<T>} model
+   */
+  constructor(model) {
+    super();
+
+    this.model = model;
+
+    this.selectAll = document.createElement('input');
+    this.selectAll.type = 'checkbox';
+    this.selectAll.addEventListener('input', () => {
+      const checked = this.selectAll.checked;
+      this.model.getRows().forEach((row) => {
+        if (!row.input.disabled) {
+          row.input.checked = checked;
+        }
+      });
+      this.notifySelectionChanged(checked);
+    });
+
+    this.listener = () => this.onChange();
+    this.model.rowsChangedListeners.add(this.listener);
+
+    /** @type {!Set<function(boolean)>} */
+    this.selectionChangedListeners = new Set();
+  }
+
+  /** @override */
+  render(td, row) {
+    td.appendChild(row.input);
+  }
+
+  /** @override */
+  renderHeader(th) {
+    th.appendChild(this.selectAll);
+  }
+
+  onChange() {
+    let anySelectable = false;
+    let anySelected = false;
+    let anyUnselected = false;
+
+    this.model.getRows().forEach((row) => {
+      // addEventListener deduplicates, so only one event will be fired per
+      // input.
+      row.input.addEventListener('input', this.listener);
+
+      if (row.input.disabled) {
+        return;
+      }
+
+      anySelectable = true;
+
+      if (row.input.checked) {
+        anySelected = true;
+      } else {
+        anyUnselected = true;
+      }
+    });
+
+    this.selectAll.disabled = !anySelectable;
+    this.selectAll.checked = anySelected && !anyUnselected;
+    this.selectAll.indeterminate = anySelected && anyUnselected;
+
+    this.notifySelectionChanged(anySelected);
+  }
+
+  /** @param {boolean} anySelected */
+  notifySelectionChanged(anySelected) {
+    this.selectionChangedListeners.forEach((f) => f(anySelected));
+  }
 }
 
 /**
@@ -162,8 +280,6 @@
     self.__proto__ = Table.prototype;
     self = /** @type {!Table} */ (self);
 
-    model.table = self;
-
     self.model = model;
     self.sortDesc = false;
 
@@ -171,7 +287,7 @@
     self.model.cols.forEach((col, idx) => {
       const th = self.ownerDocument.createElement('th');
       th.scope = 'col';
-      th.innerText = col.header;
+      col.renderHeader(th);
 
       if (col.compare) {
         th.role = 'button';
@@ -193,6 +309,8 @@
     table.appendChild(self.tbody);
 
     self.appendChild(table);
+
+    self.model.rowsChangedListeners.add(() => self.updateTbody());
   }
 
   /**
@@ -319,16 +437,16 @@
     super();
 
     this.cols = [
-      new Column('Source Event ID', (e) => e.sourceEventId),
-      new Column('Source Origin', (e) => e.impressionOrigin),
-      new Column('Destination', (e) => e.attributionDestination),
-      new Column('Report To', (e) => e.reportingOrigin),
+      new ValueColumn('Source Event ID', (e) => e.sourceEventId),
+      new ValueColumn('Source Origin', (e) => e.impressionOrigin),
+      new ValueColumn('Destination', (e) => e.attributionDestination),
+      new ValueColumn('Report To', (e) => e.reportingOrigin),
       new DateColumn('Source Registration Time', (e) => e.impressionTime),
       new DateColumn('Expiry Time', (e) => e.expiryTime),
-      new Column('Source Type', (e) => e.sourceType),
-      new Column('Priority', (e) => e.priority),
-      new Column('Dedup Keys', (e) => e.dedupKeys, /*compare=*/ null),
-      new Column('Status', (e) => e.status),
+      new ValueColumn('Source Type', (e) => e.sourceType),
+      new ValueColumn('Priority', (e) => e.priority),
+      new ValueColumn('Dedup Keys', (e) => e.dedupKeys, /*compare=*/ null),
+      new ValueColumn('Status', (e) => e.status),
     ];
 
     this.emptyRowText = 'No sources.';
@@ -351,7 +469,7 @@
   /** @param {!Array<!Source>} storedSources */
   setStoredSources(storedSources) {
     this.storedSources = storedSources;
-    this.table.updateTbody();
+    this.notifyRowsChanged();
   }
 
   /** @param {!Source} source */
@@ -363,21 +481,24 @@
     }
 
     this.deactivatedSources.push(source);
-    this.table.updateTbody();
+    this.notifyRowsChanged();
   }
 
   clear() {
     this.storedSources = [];
     this.deactivatedSources = [];
-    this.table.updateTbody();
+    this.notifyRowsChanged();
   }
 }
 
-class Report {
+class Report extends Selectable {
   /**
    * @param {!WebUIAttributionReport} mojo
    */
   constructor(mojo) {
+    super();
+
+    this.id = mojo.id;
     this.reportBody = mojo.reportBody;
     this.attributionDestination = mojo.attributionDestination;
     this.reportUrl = mojo.reportUrl.url;
@@ -386,6 +507,12 @@
     this.reportPriority = mojo.priority;
     this.attributedTruthfully = mojo.attributedTruthfully;
 
+    // Only pending reports are selectable.
+    if (this.id === null ||
+        mojo.status !== WebUIAttributionReport_Status.kPending) {
+      this.input.disabled = true;
+    }
+
     switch (mojo.status) {
       case WebUIAttributionReport_Status.kSent:
         this.status = `Sent: HTTP ${mojo.httpResponseCode}`;
@@ -418,21 +545,25 @@
   constructor() {
     super();
 
+    this.selectionColumn = new SelectionColumn(this);
+
     this.cols = [
+      this.selectionColumn,
       new CodeColumn('Report Body', (e) => e.reportBody),
-      new Column('Destination', (e) => e.attributionDestination),
-      new Column('Report URL', (e) => e.reportUrl),
+      new ValueColumn('Destination', (e) => e.attributionDestination),
+      new ValueColumn('Report URL', (e) => e.reportUrl),
       new DateColumn('Trigger Time', (e) => e.triggerTime),
       new DateColumn('Report Time', (e) => e.reportTime),
-      new Column('Report Priority', (e) => e.reportPriority),
-      new Column('Fake Report', (e) => e.attributedTruthfully ? 'no' : 'yes'),
-      new Column('Status', (e) => e.status),
+      new ValueColumn('Report Priority', (e) => e.reportPriority),
+      new ValueColumn(
+          'Fake Report', (e) => e.attributedTruthfully ? 'no' : 'yes'),
+      new ValueColumn('Status', (e) => e.status),
     ];
 
     this.emptyRowText = 'No sent or pending reports.';
 
     // Sort by report time by default.
-    this.sortIdx = 4;
+    this.sortIdx = 5;
 
     /** @type {!Array<!Report>} */
     this.sentOrDroppedReports = [];
@@ -456,7 +587,7 @@
   /** @param {!Array<!Report>} storedReports */
   setStoredReports(storedReports) {
     this.storedReports = storedReports;
-    this.table.updateTbody();
+    this.notifyRowsChanged();
   }
 
   /** @param {!Report} report */
@@ -468,13 +599,13 @@
     }
 
     this.sentOrDroppedReports.push(report);
-    this.table.updateTbody();
+    this.notifyRowsChanged();
   }
 
   clear() {
     this.storedReports = [];
     this.sentOrDroppedReports = [];
-    this.table.updateTbody();
+    this.notifyRowsChanged();
   }
 }
 
@@ -605,13 +736,24 @@
  * the data on completion.
  */
 function sendReports() {
+  const ids = [];
+  reportTableModel.storedReports.forEach((report) => {
+    if (!report.input.disabled && report.input.checked && report.id !== null) {
+      ids.push(report.id);
+    }
+  });
+
+  if (ids.length === 0) {
+    return;
+  }
+
   const button = $('send-reports');
   const previousText = $('send-reports').innerText;
 
   button.disabled = true;
   button.innerText = 'Sending...';
-  pageHandler.sendPendingReports().then(() => {
-    button.disabled = false;
+
+  pageHandler.sendReports(ids).then(() => {
     button.innerText = previousText;
   });
 }
@@ -653,7 +795,13 @@
 
   $('refresh').addEventListener('click', updatePageData);
   $('clear-data').addEventListener('click', clearStorage);
-  $('send-reports').addEventListener('click', sendReports);
+
+  const sendReportsButton = $('send-reports');
+  sendReportsButton.addEventListener('click', sendReports);
+  reportTableModel.selectionColumn.selectionChangedListeners.add(
+      (anySelected) => {
+        sendReportsButton.disabled = !anySelected;
+      });
 
   Table.decorate(getRequiredElement('source-table-wrapper'), sourceTableModel);
   Table.decorate(getRequiredElement('report-table-wrapper'), reportTableModel);
diff --git a/content/browser/security_exploit_browsertest.cc b/content/browser/security_exploit_browsertest.cc
index 90e22cb..dc3cbbd 100644
--- a/content/browser/security_exploit_browsertest.cc
+++ b/content/browser/security_exploit_browsertest.cc
@@ -4,11 +4,12 @@
 
 #include <stdint.h>
 
+#include <tuple>
+
 #include "base/bind.h"
 #include "base/command_line.h"
 #include "base/feature_list.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/memory/ptr_util.h"
 #include "base/memory/raw_ptr.h"
 #include "base/strings/stringprintf.h"
@@ -510,8 +511,8 @@
       shell()->web_contents()->GetMainFrame()->GetProcess());
   // ExecJs will sometimes finish before the renderer gets killed, so we must
   // ignore the result.
-  ignore_result(ExecJs(shell()->web_contents()->GetMainFrame(),
-                       "history.pushState({}, '', location.href);"));
+  std::ignore = ExecJs(shell()->web_contents()->GetMainFrame(),
+                       "history.pushState({}, '', location.href);");
   EXPECT_EQ(bad_message::RFH_INVALID_ORIGIN_ON_COMMIT, kill_waiter.Wait());
 }
 
@@ -538,7 +539,7 @@
   RenderProcessHostBadIpcMessageWaiter kill_waiter(subframe->GetProcess());
   // ExecJs will sometimes finish before the renderer gets killed, so we must
   // ignore the result.
-  ignore_result(ExecJs(subframe, "location.hash='foo';"));
+  std::ignore = ExecJs(subframe, "location.hash='foo';");
   EXPECT_EQ(bad_message::RFH_INVALID_ORIGIN_ON_COMMIT, kill_waiter.Wait());
 }
 
@@ -568,8 +569,8 @@
       shell()->web_contents()->GetMainFrame()->GetProcess());
   // ExecJs will sometimes finish before the renderer gets killed, so we must
   // ignore the result.
-  ignore_result(ExecJs(shell()->web_contents()->GetMainFrame(),
-                       "history.pushState({}, '', location.href);"));
+  std::ignore = ExecJs(shell()->web_contents()->GetMainFrame(),
+                       "history.pushState({}, '', location.href);");
   EXPECT_EQ(bad_message::RFH_INVALID_ORIGIN_ON_COMMIT, kill_waiter.Wait());
 }
 
@@ -763,7 +764,7 @@
 
   // The renderer should always get killed, but sometimes ExecuteScript returns
   // true anyway, so just ignore the result.
-  ignore_result(ExecJs(rfh, "URL.createObjectURL(new Blob(['foo']))"));
+  std::ignore = ExecJs(rfh, "URL.createObjectURL(new Blob(['foo']))");
 
   // If the process is killed, this test passes.
   EXPECT_EQ(
@@ -1689,8 +1690,8 @@
   //
   // It also can't EXPECT_TRUE or EXPECT_FALSE: sometimes the ExecJs call will
   // finish before the renderer gets killed, and sometimes it won't.
-  ignore_result(
-      ExecJs(child, JsReplace("location.href=$1;", GURL("/title2.html"))));
+  std::ignore =
+      ExecJs(child, JsReplace("location.href=$1;", GURL("/title2.html")));
 
   EXPECT_THAT(kill_waiter.Wait(),
               Optional(HasSubstr("Permissions Policy feature is absent")));
@@ -1735,8 +1736,8 @@
   //
   // It also can't EXPECT_TRUE or EXPECT_FALSE: sometimes the ExecJs call will
   // finish before the renderer gets killed, and sometimes it won't.
-  ignore_result(
-      ExecJs(child, JsReplace("location.href=$1;", GURL("/title2.html"))));
+  std::ignore =
+      ExecJs(child, JsReplace("location.href=$1;", GURL("/title2.html")));
 
   EXPECT_THAT(kill_waiter.Wait(),
               Optional(HasSubstr("Permissions Policy feature is absent")));
@@ -1763,8 +1764,8 @@
   // Can't use NavigateToURL here because it would hang. Additionally, we can't
   // EXPECT_TRUE or EXPECT_FALSE: sometimes the ExecJs call will finish
   // before the renderer gets killed, and sometimes it won't.
-  ignore_result(ExecJs(compromised_renderer,
-                       JsReplace("location.href=$1", GURL("/title2.html"))));
+  std::ignore = ExecJs(compromised_renderer,
+                       JsReplace("location.href=$1", GURL("/title2.html")));
 
   EXPECT_THAT(kill_waiter.Wait(),
               Optional(HasSubstr("Trust Token params in main frame nav")));
@@ -1844,10 +1845,10 @@
       compromised_renderer->GetProcess());
   replacer.Activate();
 
-  ignore_result(ExecJs(
+  std::ignore = ExecJs(
       compromised_renderer,
       JsReplace("location.href=$1",
-                embedded_test_server()->GetURL("/fenced_frames/title1.html"))));
+                embedded_test_server()->GetURL("/fenced_frames/title1.html")));
 
   absl::optional<std::string> result = kill_waiter.Wait();
   EXPECT_THAT(result,
diff --git a/content/browser/service_worker/service_worker_subresource_filter_browsertest.cc b/content/browser/service_worker/service_worker_subresource_filter_browsertest.cc
deleted file mode 100644
index 4e4aec9..0000000
--- a/content/browser/service_worker/service_worker_subresource_filter_browsertest.cc
+++ /dev/null
@@ -1,194 +0,0 @@
-// Copyright 2021 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#include "base/strings/strcat.h"
-#include "content/public/test/browser_test.h"
-#include "content/public/test/browser_test_utils.h"
-#include "content/public/test/content_browser_test.h"
-#include "content/public/test/content_browser_test_utils.h"
-#include "content/public/test/url_loader_interceptor.h"
-#include "content/shell/browser/shell.h"
-#include "testing/gtest/include/gtest/gtest.h"
-
-namespace content {
-namespace {
-
-constexpr char kBaseDataDir[] = "content/test/data/";
-
-// Generate token with the command:
-// generate_token.py https://service-worker-subresource-filter.test:443
-// ServiceWorkerSubresourceFilter
-// --expire-timestamp=2000000000
-base::StringPiece origin_trial_token =
-    "A1CKeg8m2+M4knvICqx+5ELaI1Bh17J1+2cAfNSKCgL4zmPh4hXikI4YGxbR/QQo"
-    "zQyH6JOw/fqwNdWxman2RgQAAACDeyJvcmlnaW4iOiAiaHR0cHM6Ly9zZXJ2aWNl"
-    "LXdvcmtlci1zdWJyZXNvdXJjZS1maWx0ZXIudGVzdDo0NDMiLCAiZmVhdHVyZSI6"
-    "ICJTZXJ2aWNlV29ya2VyU3VicmVzb3VyY2VGaWx0ZXIiLCAiZXhwaXJ5IjogMjAw"
-    "MDAwMDAwMH0=";
-
-const std::string script = R"(
-      (async () => {
-        const saw_message = new Promise(resolve => {
-          navigator.serviceWorker.onmessage = event => {
-            resolve(event.data);
-          };
-        });
-        const registration = await navigator.serviceWorker.ready;
-        registration.active.postMessage('');
-        return await saw_message;
-      })();
-  )";
-
-class ServiceWorkerSubresourceFilterBrowserTest
-    : public ContentBrowserTest,
-      public testing::WithParamInterface<bool> {
- protected:
-  ServiceWorkerSubresourceFilterBrowserTest() {}
-
-  void SetUpOnMainThread() override {
-    ContentBrowserTest::SetUpOnMainThread();
-
-    // We use a URLLoaderInterceptor, rather than the EmbeddedTestServer, since
-    // the origin trial token in the response is associated with a fixed origin,
-    // whereas EmbeddedTestServer serves content on a random port.
-    url_loader_interceptor_.emplace(base::BindRepeating(
-        &ServiceWorkerSubresourceFilterBrowserTest::InterceptRequest,
-        base::Unretained(this)));
-  }
-
-  void TearDownOnMainThread() override { url_loader_interceptor_.reset(); }
-
-  void NavigateAndFetch(std::string url, bool expect_only_matching_filter) {
-    EXPECT_TRUE(NavigateToURL(
-        shell(), GetUrl("/service_worker/create_service_worker.html")));
-    EXPECT_EQ(
-        "DONE",
-        EvalJs(
-            shell(),
-            "register('/service_worker/fetch_event_pass_through.js', '/');"));
-
-    GURL page_url = GetUrl(url);
-    GURL fetch_url = GetUrl("/echo");
-    GURL fetch_url_with_fragment = GetUrl("/echo#foo");
-    GURL fetch_url_with_fragment_substring = GetUrl("/echo#afooz");
-    GURL fetch_url_with_other_fragment = GetUrl("/echo#bar");
-
-    EXPECT_TRUE(NavigateToURL(shell(), page_url));
-    EXPECT_EQ("Echo",
-              EvalJs(shell(), JsReplace("fetch_from_page($1)", fetch_url)));
-    EXPECT_EQ("Echo", EvalJs(shell(), JsReplace("fetch_from_page($1)",
-                                                fetch_url_with_fragment)));
-    EXPECT_EQ("Echo",
-              EvalJs(shell(), JsReplace("fetch_from_page($1)",
-                                        fetch_url_with_fragment_substring)));
-    EXPECT_EQ("Echo",
-              EvalJs(shell(), JsReplace("fetch_from_page($1)",
-                                        fetch_url_with_other_fragment)));
-
-    base::Value list(base::Value::Type::LIST);
-    if (expect_only_matching_filter) {
-      list.Append(page_url.spec());
-      list.Append(fetch_url_with_fragment.spec());
-      list.Append(fetch_url_with_fragment_substring.spec());
-    } else {
-      list.Append(page_url.spec());
-      list.Append(fetch_url.spec());
-      list.Append(fetch_url_with_fragment.spec());
-      list.Append(fetch_url_with_fragment_substring.spec());
-      list.Append(fetch_url_with_other_fragment.spec());
-    }
-
-    EXPECT_EQ(list, EvalJs(shell(), script));
-  }
-
-  bool FeatureIsEnabled() { return GetParam(); }
-
- private:
-  static GURL GetUrl(const std::string& path) {
-    return GURL("https://service-worker-subresource-filter.test/")
-        .Resolve(path);
-  }
-
-  bool InterceptRequest(URLLoaderInterceptor::RequestParams* params) {
-    std::string headers =
-        "HTTP/1.1 200 OK\n"
-        "Content-Type: text/html\n";
-
-    if (params->url_request.url.path() == "/echo") {
-      URLLoaderInterceptor::WriteResponse(headers, std::string("Echo"),
-                                          params->client.get(),
-                                          absl::optional<net::SSLInfo>());
-      return true;
-    }
-
-    if (FeatureIsEnabled()) {
-      base::StrAppend(&headers, {"Origin-Trial: ", origin_trial_token, "\n"});
-      headers += '\n';
-    }
-
-    if (params->url_request.url.path() == "/filter") {
-      base::StrAppend(&headers, {"Service-Worker-Subresource-Filter: foo"});
-      headers += '\n';
-      URLLoaderInterceptor::WriteResponse(
-          base::StrCat({kBaseDataDir, "/service_worker/fetch_from_page.html"}),
-          params->client.get(), &headers, absl::optional<net::SSLInfo>());
-
-      return true;
-    }
-
-    if (params->url_request.url.path() == "/nofilter") {
-      // Do not add any additional headers, but intercept the request.
-      URLLoaderInterceptor::WriteResponse(
-          base::StrCat({kBaseDataDir, "/service_worker/fetch_from_page.html"}),
-          params->client.get(), &headers, absl::optional<net::SSLInfo>());
-
-      return true;
-    }
-
-    if (params->url_request.url.path() == "/emptyfilter") {
-      base::StrAppend(&headers, {"Service-Worker-Subresource-Filter:"});
-      headers += '\n';
-      URLLoaderInterceptor::WriteResponse(
-          base::StrCat({kBaseDataDir, "/service_worker/fetch_from_page.html"}),
-          params->client.get(), &headers, absl::optional<net::SSLInfo>());
-
-      return true;
-    }
-
-    URLLoaderInterceptor::WriteResponse(
-        base::StrCat({kBaseDataDir, params->url_request.url.path_piece()}),
-        params->client.get());
-    return true;
-  }
-
-  absl::optional<URLLoaderInterceptor> url_loader_interceptor_;
-};
-
-INSTANTIATE_TEST_SUITE_P(EnabledDisabled,
-                         ServiceWorkerSubresourceFilterBrowserTest,
-                         testing::Bool());
-
-IN_PROC_BROWSER_TEST_P(ServiceWorkerSubresourceFilterBrowserTest, WithFilter) {
-  // If the feature is disabled, all URLs should be seen by the Service Worker.
-  // If the feature is enabled, only the initial navigation URL and URLs
-  // matching the filter should be seen by the Service Worker.
-  NavigateAndFetch("/filter", FeatureIsEnabled());
-}
-
-IN_PROC_BROWSER_TEST_P(ServiceWorkerSubresourceFilterBrowserTest,
-                       WithoutFilter) {
-  // All URLs should be seen by the Service Worker regardless of whether or not
-  // the feature is enabled.
-  NavigateAndFetch("/nofilter", false);
-}
-
-IN_PROC_BROWSER_TEST_P(ServiceWorkerSubresourceFilterBrowserTest,
-                       WithEmptyFilter) {
-  // All URLs should be seen by the Service Worker regardless of whether or not
-  // the feature is enabled.
-  NavigateAndFetch("/emptyfilter", false);
-}
-
-}  // namespace
-}  // namespace content
\ No newline at end of file
diff --git a/content/browser/site_per_process_browsertest.cc b/content/browser/site_per_process_browsertest.cc
index 4a9baa42..c594526a 100644
--- a/content/browser/site_per_process_browsertest.cc
+++ b/content/browser/site_per_process_browsertest.cc
@@ -25,7 +25,6 @@
 #include "base/containers/contains.h"
 #include "base/cxx17_backports.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/location.h"
 #include "base/memory/ptr_util.h"
@@ -4309,7 +4308,7 @@
       main_frame.BindNewEndpointAndPassReceiver();
 
   mojo::AssociatedRemote<blink::mojom::RemoteMainFrameHost> main_frame_host;
-  ignore_result(main_frame_host.BindNewEndpointAndPassReceiver());
+  std::ignore = main_frame_host.BindNewEndpointAndPassReceiver();
   remote_main_frame_interfaces->main_frame_host = main_frame_host.Unbind();
 
   // Send the message to create a proxy for B's new child frame in A.  This
@@ -4389,7 +4388,7 @@
     mojom::CreateFrameParamsPtr params = mojom::CreateFrameParams::New();
     params->routing_id = frame_routing_id;
     params->frame = pending_frame.InitWithNewEndpointAndPassReceiver();
-    ignore_result(params->interface_broker.InitWithNewPipeAndPassReceiver());
+    std::ignore = params->interface_broker.InitWithNewPipeAndPassReceiver();
     params->previous_routing_id = previous_routing_id;
     params->opener_frame_token = absl::nullopt;
     params->parent_routing_id =
@@ -4472,7 +4471,7 @@
     mojom::CreateFrameParamsPtr params = mojom::CreateFrameParams::New();
     params->routing_id = frame_routing_id;
     params->frame = pending_frame.InitWithNewEndpointAndPassReceiver();
-    ignore_result(params->interface_broker.InitWithNewPipeAndPassReceiver());
+    std::ignore = params->interface_broker.InitWithNewPipeAndPassReceiver();
     params->previous_routing_id = IPC::mojom::kRoutingIdNone;
     params->opener_frame_token = absl::nullopt;
     params->parent_routing_id = parent_routing_id;
@@ -4484,10 +4483,10 @@
         blink_frame_widget.InitWithNewEndpointAndPassReceiver();
     params->widget_params->widget =
         blink_widget.InitWithNewEndpointAndPassReceiver();
-    ignore_result(params->widget_params->frame_widget_host
-                      .InitWithNewEndpointAndPassReceiver());
-    ignore_result(params->widget_params->widget_host
-                      .InitWithNewEndpointAndPassReceiver());
+    std::ignore = params->widget_params->frame_widget_host
+                      .InitWithNewEndpointAndPassReceiver();
+    std::ignore =
+        params->widget_params->widget_host.InitWithNewEndpointAndPassReceiver();
     params->widget_params->visual_properties.screen_infos =
         display::ScreenInfos(display::ScreenInfo());
     params->replication_state = blink::mojom::FrameReplicationState::New();
diff --git a/content/browser/storage_service_restart_browsertest.cc b/content/browser/storage_service_restart_browsertest.cc
index a9cedde4..9c811d4 100644
--- a/content/browser/storage_service_restart_browsertest.cc
+++ b/content/browser/storage_service_restart_browsertest.cc
@@ -2,7 +2,8 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/run_loop.h"
 #include "base/test/bind.h"
 #include "base/test/scoped_feature_list.h"
@@ -115,8 +116,8 @@
   // operation after a Storage Service crash.
   EXPECT_TRUE(
       NavigateToURL(shell(), GetTestUrl("dom_storage", "crash_recovery.html")));
-  ignore_result(
-      EvalJs(shell()->web_contents(), R"(setSessionStorageValue("foo", 42))"));
+  std::ignore =
+      EvalJs(shell()->web_contents(), R"(setSessionStorageValue("foo", 42))");
 
   // Note that for Session Storage we don't need to wait for a commit. This is
   // racy, but that's the point: whether or not a commit happens in time, the
@@ -140,8 +141,8 @@
   // after a Storage Service crash.
   EXPECT_TRUE(
       NavigateToURL(shell(), GetTestUrl("dom_storage", "crash_recovery.html")));
-  ignore_result(
-      EvalJs(shell()->web_contents(), R"(setLocalStorageValue("foo", 42))"));
+  std::ignore =
+      EvalJs(shell()->web_contents(), R"(setLocalStorageValue("foo", 42))");
 
   // We wait for the above storage request to be fully committed to disk. This
   // ensures that renderer gets the correct value when recovering from the
diff --git a/content/browser/storage_service_sandbox_browsertest.cc b/content/browser/storage_service_sandbox_browsertest.cc
index 98d389f..7883888a 100644
--- a/content/browser/storage_service_sandbox_browsertest.cc
+++ b/content/browser/storage_service_sandbox_browsertest.cc
@@ -2,7 +2,8 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/run_loop.h"
 #include "base/test/bind.h"
 #include "base/test/scoped_feature_list.h"
@@ -96,8 +97,8 @@
 
 IN_PROC_BROWSER_TEST_F(StorageServiceSandboxBrowserTest, PRE_DomStorage) {
   EXPECT_TRUE(NavigateToURL(shell(), GetTestUrl(nullptr, "empty.html")));
-  ignore_result(
-      EvalJs(shell()->web_contents(), R"(window.localStorage.yeet = 42)"));
+  std::ignore =
+      EvalJs(shell()->web_contents(), R"(window.localStorage.yeet = 42)");
   WaitForAnyLocalStorageData();
   FlushLocalStorage();
 }
diff --git a/content/browser/tracing/tracing_controller_impl_data_endpoint.cc b/content/browser/tracing/tracing_controller_impl_data_endpoint.cc
index 59642db..314a3734 100644
--- a/content/browser/tracing/tracing_controller_impl_data_endpoint.cc
+++ b/content/browser/tracing/tracing_controller_impl_data_endpoint.cc
@@ -3,11 +3,11 @@
 // found in the LICENSE file.
 
 #include <memory>
+#include <tuple>
 #include <utility>
 
 #include "base/bind.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/json/json_writer.h"
 #include "base/memory/raw_ptr.h"
 #include "base/memory/ref_counted_memory.h"
@@ -89,7 +89,7 @@
   void ReceiveTraceChunkOnBlockingThread(std::unique_ptr<std::string> chunk) {
     if (!OpenFileIfNeededOnBlockingThread())
       return;
-    ignore_result(fwrite(chunk->c_str(), chunk->size(), 1, file_));
+    std::ignore = fwrite(chunk->c_str(), chunk->size(), 1, file_);
   }
 
   bool OpenFileIfNeededOnBlockingThread() {
diff --git a/content/browser/web_contents/web_contents_impl.cc b/content/browser/web_contents/web_contents_impl.cc
index e6d5b77..daec329 100644
--- a/content/browser/web_contents/web_contents_impl.cc
+++ b/content/browser/web_contents/web_contents_impl.cc
@@ -5263,7 +5263,8 @@
 
 void WebContentsImpl::Find(int request_id,
                            const std::u16string& search_text,
-                           blink::mojom::FindOptionsPtr options) {
+                           blink::mojom::FindOptionsPtr options,
+                           bool skip_delay) {
   OPTIONAL_TRACE_EVENT0("content", "WebContentsImpl::Find");
   // Cowardly refuse to search for no text.
   if (search_text.empty()) {
@@ -5272,7 +5273,7 @@
   }
 
   GetOrCreateFindRequestManager()->Find(request_id, search_text,
-                                        std::move(options));
+                                        std::move(options), skip_delay);
 }
 
 void WebContentsImpl::StopFinding(StopFindAction action) {
diff --git a/content/browser/web_contents/web_contents_impl.h b/content/browser/web_contents/web_contents_impl.h
index 2633685..eea51b44 100644
--- a/content/browser/web_contents/web_contents_impl.h
+++ b/content/browser/web_contents/web_contents_impl.h
@@ -527,7 +527,8 @@
       WebContents::ImageDownloadCallback callback) override;
   void Find(int request_id,
             const std::u16string& search_text,
-            blink::mojom::FindOptionsPtr options) override;
+            blink::mojom::FindOptionsPtr options,
+            bool skip_delay = false) override;
   void StopFinding(StopFindAction action) override;
   bool WasEverAudible() override;
   bool IsFullscreen() override;
diff --git a/content/browser/web_contents/web_contents_impl_browsertest.cc b/content/browser/web_contents/web_contents_impl_browsertest.cc
index 8bd037d8..c3b8ade 100644
--- a/content/browser/web_contents/web_contents_impl_browsertest.cc
+++ b/content/browser/web_contents/web_contents_impl_browsertest.cc
@@ -4,6 +4,7 @@
 
 #include <algorithm>
 #include <array>
+#include <tuple>
 #include <utility>
 #include <vector>
 
@@ -13,7 +14,6 @@
 #include "base/containers/contains.h"
 #include "base/feature_list.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/memory/ptr_util.h"
 #include "base/memory/raw_ptr.h"
 #include "base/memory/ref_counted.h"
@@ -4959,7 +4959,7 @@
 
     web_contents->UpdateWindowControlsOverlay(bounding_client_rect);
     TitleWatcher title_watcher(web_contents, u"ongeometrychange");
-    ignore_result(title_watcher.WaitAndGetTitle());
+    std::ignore = title_watcher.WaitAndGetTitle();
   }
 
  private:
@@ -5039,7 +5039,7 @@
   gfx::Rect bounding_client_rect = gfx::Rect(2, 3, 4, 5);
   web_contents->UpdateWindowControlsOverlay(bounding_client_rect);
   TitleWatcher title_watcher(web_contents, u"ongeometrychange1");
-  ignore_result(title_watcher.WaitAndGetTitle());
+  std::ignore = title_watcher.WaitAndGetTitle();
 
   // Expect the "geometrychange" event to have fired once.
   EXPECT_EQ(1, EvalJs(web_contents, "geometrychangeCount"));
@@ -5082,7 +5082,7 @@
              "}"));
   content::HostZoomMap::SetZoomLevel(web_contents, 1.5);
   TitleWatcher title_watcher(web_contents, u"ongeometrychangefromzoomlevel");
-  ignore_result(title_watcher.WaitAndGetTitle());
+  std::ignore = title_watcher.WaitAndGetTitle();
 
   // Validate the event payload.
   double zoom_factor = blink::PageZoomLevelToZoomFactor(
@@ -5435,8 +5435,8 @@
   // now disabled.
   {
     PCScanReadyToCommitObserver observer(shell()->web_contents());
-    ignore_result(ExecJs(shell()->web_contents()->GetMainFrame(),
-                         JsReplace("location = $1", prendering_url)));
+    std::ignore = ExecJs(shell()->web_contents()->GetMainFrame(),
+                         JsReplace("location = $1", prendering_url));
     observer.Wait();
     EXPECT_FALSE(observer.WasPCScanEnabled());
   }
diff --git a/content/browser/webauth/authenticator_common.cc b/content/browser/webauth/authenticator_common.cc
index a4cb8fb..126ab52 100644
--- a/content/browser/webauth/authenticator_common.cc
+++ b/content/browser/webauth/authenticator_common.cc
@@ -45,6 +45,7 @@
 #include "device/fido/fido_constants.h"
 #include "device/fido/fido_parsing_utils.h"
 #include "device/fido/fido_transport_protocol.h"
+#include "device/fido/fido_types.h"
 #include "device/fido/filter.h"
 #include "device/fido/get_assertion_request_handler.h"
 #include "device/fido/make_credential_request_handler.h"
@@ -1290,14 +1291,15 @@
       DCHECK(response_data.has_value());
       DCHECK(authenticator);
 
-      transport_ = authenticator->AuthenticatorTransport();
+      absl::optional<device::FidoTransportProtocol> transport =
+          authenticator->AuthenticatorTransport();
       bool is_transport_used_internal = false;
       bool is_transport_used_cable = false;
-      if (transport_) {
+      if (transport) {
         is_transport_used_internal =
-            *transport_ == device::FidoTransportProtocol::kInternal;
+            *transport == device::FidoTransportProtocol::kInternal;
         is_transport_used_cable =
-            *transport_ ==
+            *transport ==
             device::FidoTransportProtocol::kCloudAssistedBluetoothLowEnergy;
       }
 
@@ -1505,7 +1507,6 @@
     case device::GetAssertionStatus::kSuccess:
       DCHECK(response_data.has_value());
       DCHECK(authenticator);
-      transport_ = authenticator->AuthenticatorTransport();
 
       // Show an account picker for requests with empty allow lists.
       // Authenticators may omit the identifying information in the user entity
@@ -1614,6 +1615,12 @@
   common_info->id = Base64UrlEncode(common_info->raw_id);
   response->info = std::move(common_info);
 
+  response->authenticator_attachment =
+      response_data.transport_used()
+          ? device::AuthenticatorAttachmentFromTransport(
+                *response_data.transport_used())
+          : device::AuthenticatorAttachment::kAny;
+
   // The transport list must not contain duplicates but the order doesn't matter
   // because Blink will sort the resulting strings before returning them.
   std::vector<device::FidoTransportProtocol> transports;
@@ -1631,9 +1638,6 @@
   }
 
   response->transports = std::move(transports);
-  response->has_transport = transport_.has_value();
-  if (response->has_transport)
-    response->transport = *transport_;
 
   bool did_create_hmac_secret = false;
   bool did_store_cred_blob = false;
@@ -1759,9 +1763,11 @@
   response->info->authenticator_data =
       response_data.authenticator_data.SerializeToByteArray();
   response->signature = response_data.signature;
-  response->has_transport = transport_.has_value();
-  if (response->has_transport)
-    response->transport = *transport_;
+  response->authenticator_attachment =
+      response_data.transport_used
+          ? device::AuthenticatorAttachmentFromTransport(
+                *response_data.transport_used)
+          : device::AuthenticatorAttachment::kAny;
   response_data.user_entity
       ? response->user_handle.emplace(response_data.user_entity->id)
       : response->user_handle.emplace();
diff --git a/content/browser/webauth/authenticator_common.h b/content/browser/webauth/authenticator_common.h
index fc9c50f..193a6ca 100644
--- a/content/browser/webauth/authenticator_common.h
+++ b/content/browser/webauth/authenticator_common.h
@@ -234,9 +234,6 @@
   blink::mojom::Authenticator::GetAssertionCallback
       get_assertion_response_callback_;
   std::string client_data_json_;
-  // Transport used during authentication. May be empty if unknown, e.g. on old
-  // Windows.
-  absl::optional<device::FidoTransportProtocol> transport_;
   // empty_allow_list_ is true iff a GetAssertion is currently pending and the
   // request did not list any credential IDs in the allow list.
   bool empty_allow_list_ = false;
diff --git a/content/browser/webauth/authenticator_impl_unittest.cc b/content/browser/webauth/authenticator_impl_unittest.cc
index dfcf3e7..738354e 100644
--- a/content/browser/webauth/authenticator_impl_unittest.cc
+++ b/content/browser/webauth/authenticator_impl_unittest.cc
@@ -62,6 +62,7 @@
 #include "device/fido/fido_authenticator.h"
 #include "device/fido/fido_constants.h"
 #include "device/fido/fido_test_data.h"
+#include "device/fido/fido_transport_protocol.h"
 #include "device/fido/fido_types.h"
 #include "device/fido/filter.h"
 #include "device/fido/hid/fake_hid_impl_for_testing.h"
@@ -4150,6 +4151,10 @@
         device::FidoTransportProtocol::kBluetoothLowEnergy,
         device::FidoTransportProtocol::kNearFieldCommunication,
         device::FidoTransportProtocol::kInternal}) {
+    device::AuthenticatorAttachment attachment =
+        (transport == device::FidoTransportProtocol::kInternal
+             ? device::AuthenticatorAttachment::kPlatform
+             : device::AuthenticatorAttachment::kCrossPlatform);
     ResetVirtualDevice();
     virtual_device_factory_->SetSupportedProtocol(
         device::ProtocolVersion::kCtap2);
@@ -4161,7 +4166,7 @@
     MakeCredentialResult create_result =
         AuthenticatorMakeCredential(std::move(create_options));
     ASSERT_EQ(create_result.status, AuthenticatorStatus::SUCCESS);
-    EXPECT_EQ(create_result.response->transport, transport);
+    EXPECT_EQ(create_result.response->authenticator_attachment, attachment);
 
     PublicKeyCredentialRequestOptionsPtr get_options =
         GetTestPublicKeyCredentialRequestOptions();
@@ -4172,7 +4177,7 @@
     GetAssertionResult get_result =
         AuthenticatorGetAssertion(std::move(get_options));
     ASSERT_EQ(get_result.status, AuthenticatorStatus::SUCCESS);
-    EXPECT_EQ(get_result.response->transport, transport);
+    EXPECT_EQ(get_result.response->authenticator_attachment, attachment);
   }
 }
 
diff --git a/content/browser/webrtc/webrtc_internals.cc b/content/browser/webrtc/webrtc_internals.cc
index c9da582..513c74b 100644
--- a/content/browser/webrtc/webrtc_internals.cc
+++ b/content/browser/webrtc/webrtc_internals.cc
@@ -193,7 +193,7 @@
 
   auto it = FindRecord(frame_id, lid);
   if (it != peer_connection_data_.GetList().end()) {
-    MaybeClosePeerConnection(&*it);
+    MaybeClosePeerConnection(*it);
     peer_connection_data_.EraseListIter(it);
   }
 
@@ -217,13 +217,13 @@
 
   if (type == "iceconnectionstatechange") {
     if (value == "connected" || value == "checking" || value == "completed") {
-      MaybeMarkPeerConnectionAsConnected(&*it);
+      MaybeMarkPeerConnectionAsConnected(*it);
     } else if (value == "failed" || value == "disconnected" ||
                value == "closed" || value == "new") {
-      MaybeMarkPeerConnectionAsNotConnected(&*it);
+      MaybeMarkPeerConnectionAsNotConnected(*it);
     }
   } else if (type == "close") {
-    MaybeClosePeerConnection(&*it);
+    MaybeClosePeerConnection(*it);
   } else if (type == "setConfiguration") {
     // Update the configuration we have for this connection.
     it->SetStringKey("rtcConfiguration", value);
@@ -605,13 +605,11 @@
   // by the exiting renderer.
   base::Value::ListView peer_conn_view = peer_connection_data_.GetList();
   for (int i = peer_conn_view.size() - 1; i >= 0; --i) {
-    base::DictionaryValue* record = nullptr;
     DCHECK(peer_conn_view[i].is_dict());
-    peer_conn_view[i].GetAsDictionary(&record);
 
     absl::optional<int> this_rid, this_lid;
-    this_rid = record->FindIntKey("rid");
-    this_lid = record->FindIntKey("lid");
+    this_rid = peer_conn_view[i].FindIntKey("rid");
+    this_lid = peer_conn_view[i].FindIntKey("lid");
 
     if (this_rid.value_or(0) == render_process_id) {
       if (!observers_.empty()) {
@@ -620,7 +618,7 @@
         update.SetIntKey("lid", this_lid.value_or(0));
         SendUpdate("remove-peer-connection", std::move(update));
       }
-      MaybeClosePeerConnection(record);
+      MaybeClosePeerConnection(peer_conn_view[i]);
       peer_connection_data_.EraseListIter(peer_conn_view.begin() + i);
     }
   }
@@ -632,11 +630,10 @@
   base::Value::ListView get_user_media_requests_view =
       get_user_media_requests_.GetList();
   for (int i = get_user_media_requests_view.size() - 1; i >= 0; --i) {
-    base::DictionaryValue* record = nullptr;
     DCHECK(get_user_media_requests_view[i].is_dict());
-    get_user_media_requests_view[i].GetAsDictionary(&record);
 
-    absl::optional<int> this_rid = record->FindIntKey("rid");
+    absl::optional<int> this_rid =
+        get_user_media_requests_view[i].FindIntKey("rid");
 
     if (this_rid.value_or(0) == render_process_id) {
       get_user_media_requests_.EraseListIter(
@@ -669,21 +666,21 @@
   }
 }
 
-void WebRTCInternals::MaybeClosePeerConnection(base::Value* record) {
-  absl::optional<bool> is_open = record->FindBoolKey("isOpen");
+void WebRTCInternals::MaybeClosePeerConnection(base::Value& record) {
+  absl::optional<bool> is_open = record.FindBoolKey("isOpen");
   DCHECK(is_open.has_value());
   if (!*is_open)
     return;
 
-  record->SetBoolKey("isOpen", false);
+  record.SetBoolKey("isOpen", false);
   MaybeMarkPeerConnectionAsNotConnected(record);
 }
 
-void WebRTCInternals::MaybeMarkPeerConnectionAsConnected(base::Value* record) {
-  bool was_connected = record->FindBoolKey("connected").value_or(true);
+void WebRTCInternals::MaybeMarkPeerConnectionAsConnected(base::Value& record) {
+  bool was_connected = record.FindBoolKey("connected").value_or(true);
   if (!was_connected) {
     ++num_connected_connections_;
-    record->SetBoolKey("connected", true);
+    record.SetBoolKey("connected", true);
     UpdateWakeLock();
     for (auto& observer : connections_observers_)
       observer.OnConnectionsCountChange(num_connected_connections_);
@@ -691,10 +688,10 @@
 }
 
 void WebRTCInternals::MaybeMarkPeerConnectionAsNotConnected(
-    base::Value* record) {
-  bool was_connected = record->FindBoolKey("connected").value_or(false);
+    base::Value& record) {
+  bool was_connected = record.FindBoolKey("connected").value_or(false);
   if (was_connected) {
-    record->SetBoolKey("connected", false);
+    record.SetBoolKey("connected", false);
     --num_connected_connections_;
     DCHECK_GE(num_connected_connections_, 0);
     UpdateWakeLock();
@@ -753,12 +750,10 @@
 
   base::Value::ListView peer_conn_view = peer_connection_data_.GetList();
   for (auto it = peer_conn_view.begin(); it != peer_conn_view.end(); ++it) {
-    base::DictionaryValue* record = nullptr;
     DCHECK(it->is_dict());
-    it->GetAsDictionary(&record);
 
-    int this_rid = record->FindIntKey("rid").value_or(0);
-    int this_lid = record->FindIntKey("lid").value_or(0);
+    int this_rid = it->FindIntKey("rid").value_or(0);
+    int this_lid = it->FindIntKey("lid").value_or(0);
 
     if (this_rid == frame_id.child_id && this_lid == lid)
       return it;
diff --git a/content/browser/webrtc/webrtc_internals.h b/content/browser/webrtc/webrtc_internals.h
index 8f484fb..530b8b9 100644
--- a/content/browser/webrtc/webrtc_internals.h
+++ b/content/browser/webrtc/webrtc_internals.h
@@ -167,10 +167,10 @@
 
   // Updates the number of open PeerConnections. Called when a PeerConnection
   // is stopped or removed.
-  void MaybeClosePeerConnection(base::Value* record);
+  void MaybeClosePeerConnection(base::Value& record);
 
-  void MaybeMarkPeerConnectionAsConnected(base::Value* record);
-  void MaybeMarkPeerConnectionAsNotConnected(base::Value* record);
+  void MaybeMarkPeerConnectionAsConnected(base::Value& record);
+  void MaybeMarkPeerConnectionAsNotConnected(base::Value& record);
 
   // Called whenever a PeerConnection is created or stopped in order to
   // request/cancel a wake lock on suspending the current application for power
diff --git a/content/child/child_thread_impl.cc b/content/child/child_thread_impl.cc
index 35850e1..f9026fd5 100644
--- a/content/child/child_thread_impl.cc
+++ b/content/child/child_thread_impl.cc
@@ -8,6 +8,7 @@
 
 #include <memory>
 #include <string>
+#include <tuple>
 #include <utility>
 
 #include "base/base_switches.h"
@@ -19,7 +20,6 @@
 #include "base/debug/leak_annotations.h"
 #include "base/debug/profiler.h"
 #include "base/files/file.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/location.h"
 #include "base/logging.h"
@@ -154,7 +154,7 @@
   // delegate object alive for the lifetime of the process.
   WaitAndExitDelegate* leaking_delegate = delegate.release();
   ANNOTATE_LEAKING_OBJECT_PTR(leaking_delegate);
-  ignore_result(leaking_delegate);
+  std::ignore = leaking_delegate;
   return true;
 }
 #endif
diff --git a/content/child/field_trial.cc b/content/child/field_trial.cc
index 93f12ea..21847d0 100644
--- a/content/child/field_trial.cc
+++ b/content/child/field_trial.cc
@@ -3,11 +3,13 @@
 // found in the LICENSE file.
 
 #include "content/child/field_trial.h"
+
+#include <tuple>
+
 #include "base/base_switches.h"
 #include "base/command_line.h"
 #include "base/debug/leak_annotations.h"
 #include "base/feature_list.h"
-#include "base/ignore_result.h"
 #include "base/metrics/field_trial.h"
 #include "build/build_config.h"
 #include "content/public/common/content_descriptors.h"
@@ -30,7 +32,7 @@
   base::FieldTrialList* leaked_field_trial_list =
       new base::FieldTrialList(nullptr);
   ANNOTATE_LEAKING_OBJECT_PTR(leaked_field_trial_list);
-  ignore_result(leaked_field_trial_list);
+  std::ignore = leaked_field_trial_list;
 
   // Ensure any field trials in browser are reflected into the child process.
   base::FieldTrialList::CreateTrialsFromCommandLine(command_line,
diff --git a/content/common/child_process_host_impl.cc b/content/common/child_process_host_impl.cc
index e573e26..1a63031 100644
--- a/content/common/child_process_host_impl.cc
+++ b/content/common/child_process_host_impl.cc
@@ -5,6 +5,7 @@
 #include "content/common/child_process_host_impl.h"
 
 #include <limits>
+#include <tuple>
 
 #include "base/atomic_sequence_num.h"
 #include "base/clang_profiling_buildflags.h"
@@ -12,7 +13,6 @@
 #include "base/files/file.h"
 #include "base/files/file_path.h"
 #include "base/hash/hash.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/memory/ptr_util.h"
 #include "base/metrics/histogram_macros.h"
@@ -123,7 +123,7 @@
   if (ipc_mode_ == IpcMode::kLegacy) {
     // In legacy mode, we only have an IPC Channel. Bind ChildProcess to a
     // disconnected pipe so it quietly discards messages.
-    ignore_result(child_process_.BindNewPipeAndPassReceiver());
+    std::ignore = child_process_.BindNewPipeAndPassReceiver();
     channel_ = IPC::ChannelMojo::Create(
         mojo_invitation_->AttachMessagePipe(
             kChildProcessReceiverAttachmentName),
diff --git a/content/public/android/java/src/org/chromium/content/browser/selection/SelectionPopupControllerImpl.java b/content/public/android/java/src/org/chromium/content/browser/selection/SelectionPopupControllerImpl.java
index 2693d46..6b20051 100644
--- a/content/public/android/java/src/org/chromium/content/browser/selection/SelectionPopupControllerImpl.java
+++ b/content/public/android/java/src/org/chromium/content/browser/selection/SelectionPopupControllerImpl.java
@@ -1501,10 +1501,11 @@
     }
 
     @CalledByNative
-    private void onSelectAroundCaretSuccess(int extendedStartAdjust, int extendedEndAdjust) {
+    private void onSelectAroundCaretSuccess(int extendedStartAdjust, int extendedEndAdjust,
+            int wordStartAdjust, int wordEndAdjust) {
         if (mSelectionClient != null) {
-            SelectAroundCaretResult result =
-                    new SelectAroundCaretResult(extendedStartAdjust, extendedEndAdjust);
+            SelectAroundCaretResult result = new SelectAroundCaretResult(
+                    extendedStartAdjust, extendedEndAdjust, wordStartAdjust, wordEndAdjust);
             mSelectionClient.selectAroundCaretAck(result);
         }
     }
diff --git a/content/public/android/java/src/org/chromium/content_public/browser/SelectAroundCaretResult.java b/content/public/android/java/src/org/chromium/content_public/browser/SelectAroundCaretResult.java
index f4532bf..aba1950 100644
--- a/content/public/android/java/src/org/chromium/content_public/browser/SelectAroundCaretResult.java
+++ b/content/public/android/java/src/org/chromium/content_public/browser/SelectAroundCaretResult.java
@@ -11,32 +11,57 @@
 public class SelectAroundCaretResult {
     private final int mExtendedStartAdjust;
     private final int mExtendedEndAdjust;
+    private final int mWordStartAdjust;
+    private final int mWordEndAdjust;
 
     /**
-     * @return The start offset difference between the extended selection (if
-     * not using Word granularity) and the previous selection (caret).
+     * @return The start offset difference between the extended selection and the initial selection
+     *         (caret).
      */
     public int getExtendedStartAdjust() {
         return mExtendedStartAdjust;
     }
 
     /**
-     * @return The end offset difference between the extended selection (if not
-     * using Word granularity) and the previous selection (caret).
+     * @return The end offset difference between the extended selection and the initial selection
+     *         (caret).
      */
     public int getExtendedEndAdjust() {
         return mExtendedEndAdjust;
     }
 
     /**
+     * @return The start offset difference between the word selection (regardless of the extended
+     *         selection granularity) and the initial selection (caret).
+     */
+    public int getWordStartAdjust() {
+        return mWordStartAdjust;
+    }
+
+    /**
+     * @return The end offset difference between the word selection (regardless of the extended
+     *         selection granularity) and the initial selection (caret).
+     */
+    public int getWordEndAdjust() {
+        return mWordEndAdjust;
+    }
+
+    /**
      * Create {@link SelectAroundCaretResult} instance.
      * @param extendedStartAdjust The start offset difference between the extended selection and the
-     *         previous selection (caret).
+     *         initial selection (caret).
      * @param extendedEndAdjust The end offset difference between the extended selection and the
-     *         previous selection (caret).
+     *         initial selection (caret).
+     * @param wordStartAdjust The start offset difference between the word selection (regardless of
+     *         the extended selection granularity) and the initial selection (caret).
+     * @param wordEndAdjust The end offset difference between the word selection (regardless of the
+     *         extended selection granularity) and the initial selection (caret).
      */
-    public SelectAroundCaretResult(int extendedStartAdjust, int extendedEndAdjust) {
+    public SelectAroundCaretResult(int extendedStartAdjust, int extendedEndAdjust,
+            int wordStartAdjust, int wordEndAdjust) {
         mExtendedStartAdjust = extendedStartAdjust;
         mExtendedEndAdjust = extendedEndAdjust;
+        mWordStartAdjust = wordStartAdjust;
+        mWordEndAdjust = wordEndAdjust;
     }
 }
\ No newline at end of file
diff --git a/content/public/android/javatests/src/org/chromium/content/browser/accessibility/WebContentsAccessibilityTreeTest.java b/content/public/android/javatests/src/org/chromium/content/browser/accessibility/WebContentsAccessibilityTreeTest.java
index c1c8e798..54686b30 100644
--- a/content/public/android/javatests/src/org/chromium/content/browser/accessibility/WebContentsAccessibilityTreeTest.java
+++ b/content/public/android/javatests/src/org/chromium/content/browser/accessibility/WebContentsAccessibilityTreeTest.java
@@ -454,6 +454,7 @@
 
     @Test
     @SmallTest
+    @DisabledTest(message = "https://crbug.com/1282189")
     public void test_ariaHiddenIframe() {
         performAriaTest("aria-hidden-iframe.html");
     }
diff --git a/content/public/browser/web_contents.h b/content/public/browser/web_contents.h
index 3e209a6..6dd28a6 100644
--- a/content/public/browser/web_contents.h
+++ b/content/public/browser/web_contents.h
@@ -1121,10 +1121,13 @@
       bool bypass_cache,
       ImageDownloadCallback callback) = 0;
 
-  // Finds text on a page. |search_text| should not be empty.
+  // Finds text on a page. |search_text| should not be empty. |skip_delay|
+  // indicates that the find request should be sent to the renderer immediately
+  // instead of waiting for privacy/performance mitigations.
   virtual void Find(int request_id,
                     const std::u16string& search_text,
-                    blink::mojom::FindOptionsPtr options) = 0;
+                    blink::mojom::FindOptionsPtr options,
+                    bool skip_delay = false) = 0;
 
   // Notifies the renderer that the user has closed the FindInPage window
   // (and what action to take regarding the selection).
diff --git a/content/public/common/content_features.cc b/content/public/common/content_features.cc
index 7a0026d..98857a4 100644
--- a/content/public/common/content_features.cc
+++ b/content/public/common/content_features.cc
@@ -813,14 +813,6 @@
                                       base::FEATURE_DISABLED_BY_DEFAULT};
 #endif
 
-// Experiment allowing control over what requests are intercepted by Service
-// Worker fetch events. By setting a Service-Worker-Subresource-Filter HTTP
-// header on the document to some string, only requests which contain a fragment
-// matching the header string will be intercepted. When not set, Service Workers
-// will intercept all requests, as normal.
-const base::Feature kServiceWorkerSubresourceFilter{
-    "ServiceWorkerSubresourceFilter", base::FEATURE_DISABLED_BY_DEFAULT};
-
 // Controls whether to isolate sites of documents that specify an eligible
 // Cross-Origin-Opener-Policy header.  Note that this is only intended to be
 // used on Android, which does not use strict site isolation. See
diff --git a/content/public/common/content_features.h b/content/public/common/content_features.h
index 4bb2105..af6d6dfb 100644
--- a/content/public/common/content_features.h
+++ b/content/public/common/content_features.h
@@ -202,7 +202,6 @@
 #endif  // defined(OS_CHROMEOS)
 CONTENT_EXPORT extern const base::Feature kWebOTP;
 CONTENT_EXPORT extern const base::Feature kWebOTPAssertionFeaturePolicy;
-CONTENT_EXPORT extern const base::Feature kServiceWorkerSubresourceFilter;
 CONTENT_EXPORT extern const base::Feature kSpareRendererForSitePerProcess;
 CONTENT_EXPORT extern const base::Feature kStopVideoCaptureOnScreenLock;
 CONTENT_EXPORT extern const base::Feature kStorageServiceOutOfProcess;
diff --git a/content/public/common/custom_handlers/protocol_handler.cc b/content/public/common/custom_handlers/protocol_handler.cc
index 3488c18..b2b64c85 100644
--- a/content/public/common/custom_handlers/protocol_handler.cc
+++ b/content/public/common/custom_handlers/protocol_handler.cc
@@ -61,7 +61,7 @@
 bool ProtocolHandler::IsValidDict(const base::DictionaryValue* value) {
   // Note that "title" parameter is ignored.
   // The |last_modified| field is optional as it was introduced in M68.
-  return value->HasKey("protocol") && value->HasKey("url");
+  return value->FindKey("protocol") && value->FindKey("url");
 }
 
 bool ProtocolHandler::IsValid() const {
@@ -105,23 +105,26 @@
   base::Time time;
   blink::ProtocolHandlerSecurityLevel security_level =
       blink::ProtocolHandlerSecurityLevel::kStrict;
-  value->GetString("protocol", &protocol);
-  value->GetString("url", &url);
+  if (const std::string* protocol_in = value->FindStringKey("protocol"))
+    protocol = *protocol_in;
+  if (const std::string* url_in = value->FindStringKey("url"))
+    url = *url_in;
   absl::optional<base::Time> time_value =
       base::ValueToTime(value->FindKey("last_modified"));
   // Treat invalid times as the default value.
   if (time_value)
     time = *time_value;
   absl::optional<int> security_level_value =
-      value->FindIntPath("security_level");
+      value->FindIntKey("security_level");
   if (security_level_value) {
     security_level =
         blink::ProtocolHandlerSecurityLevelFrom(*security_level_value);
   }
 
-  if (value->HasKey("app_id")) {
+  if (const base::Value* app_id_val = value->FindKey("app_id")) {
     std::string app_id;
-    value->GetString("app_id", &app_id);
+    if (app_id_val->is_string())
+      app_id = app_id_val->GetString();
     return ProtocolHandler(protocol, GURL(url), app_id, time, security_level);
   }
 
diff --git a/content/public/test/mock_render_process_host.cc b/content/public/test/mock_render_process_host.cc
index 29d3de6..f94ee55 100644
--- a/content/public/test/mock_render_process_host.cc
+++ b/content/public/test/mock_render_process_host.cc
@@ -5,12 +5,12 @@
 #include "content/public/test/mock_render_process_host.h"
 
 #include <algorithm>
+#include <tuple>
 #include <utility>
 #include <vector>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/location.h"
 #include "base/no_destructor.h"
@@ -456,8 +456,8 @@
   if (!renderer_interface_) {
     renderer_interface_ =
         std::make_unique<mojo::AssociatedRemote<mojom::Renderer>>();
-    ignore_result(
-        renderer_interface_->BindNewEndpointAndPassDedicatedReceiver());
+    std::ignore =
+        renderer_interface_->BindNewEndpointAndPassDedicatedReceiver();
   }
   return renderer_interface_->get();
 }
diff --git a/content/public/test/mock_render_thread.cc b/content/public/test/mock_render_thread.cc
index 87aa32b..0daad07 100644
--- a/content/public/test/mock_render_thread.cc
+++ b/content/public/test/mock_render_thread.cc
@@ -5,8 +5,8 @@
 #include "content/public/test/mock_render_thread.h"
 
 #include <memory>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/task/single_thread_task_runner.h"
 #include "base/threading/thread_task_runner_handle.h"
@@ -310,13 +310,13 @@
       blink_frame_widget_receiver =
           blink_frame_widget.BindNewEndpointAndPassDedicatedReceiver();
   mojo::AssociatedRemote<blink::mojom::FrameWidgetHost> blink_frame_widget_host;
-  ignore_result(
-      blink_frame_widget_host.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore =
+      blink_frame_widget_host.BindNewEndpointAndPassDedicatedReceiver();
   mojo::AssociatedRemote<blink::mojom::Widget> blink_widget;
   mojo::PendingAssociatedReceiver<blink::mojom::Widget> blink_widget_receiver =
       blink_widget.BindNewEndpointAndPassDedicatedReceiver();
   mojo::AssociatedRemote<blink::mojom::WidgetHost> blink_widget_host;
-  ignore_result(blink_widget_host.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore = blink_widget_host.BindNewEndpointAndPassDedicatedReceiver();
 
   widget_params->frame_widget = std::move(blink_frame_widget_receiver);
   widget_params->frame_widget_host = blink_frame_widget_host.Unbind();
diff --git a/content/public/test/policy_container_utils.cc b/content/public/test/policy_container_utils.cc
index 3cab2d5..2c85ec0 100644
--- a/content/public/test/policy_container_utils.cc
+++ b/content/public/test/policy_container_utils.cc
@@ -4,7 +4,8 @@
 
 #include "content/public/test/policy_container_utils.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "third_party/blink/public/mojom/frame/policy_container.mojom.h"
 
 namespace content {
@@ -12,8 +13,8 @@
 blink::mojom::PolicyContainerPtr CreateStubPolicyContainer() {
   mojo::PendingAssociatedRemote<blink::mojom::PolicyContainerHost>
       stub_policy_container_remote;
-  ignore_result(
-      stub_policy_container_remote.InitWithNewEndpointAndPassReceiver());
+  std::ignore =
+      stub_policy_container_remote.InitWithNewEndpointAndPassReceiver();
   return blink::mojom::PolicyContainer::New(
       blink::mojom::PolicyContainerPolicies::New(),
       std::move(stub_policy_container_remote));
diff --git a/content/public/test/prerender_test_util.cc b/content/public/test/prerender_test_util.cc
index db730e5..262f11b 100644
--- a/content/public/test/prerender_test_util.cc
+++ b/content/public/test/prerender_test_util.cc
@@ -4,8 +4,9 @@
 
 #include "content/public/test/prerender_test_util.h"
 
+#include <tuple>
+
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/trace_event/typed_macros.h"
 #include "content/browser/prerender/prerender_host_registry.h"
 #include "content/browser/renderer_host/frame_tree.h"
@@ -346,8 +347,8 @@
   // approach just to ignore it instead of fixing the timing issue. When
   // ExecJs() actually fails, the remaining test steps should fail, so it
   // should be safe to ignore it.
-  ignore_result(
-      ExecJs(prerender_render_frame_host, JsReplace("location = $1", gurl)));
+  std::ignore =
+      ExecJs(prerender_render_frame_host, JsReplace("location = $1", gurl));
 }
 
 // static
@@ -380,8 +381,8 @@
   // approach just to ignore it instead of fixing the timing issue. When
   // ExecJs() actually fails, the remaining test steps should fail, so it
   // should be safe to ignore it.
-  ignore_result(
-      ExecJs(web_contents.GetMainFrame(), JsReplace("location = $1", gurl)));
+  std::ignore =
+      ExecJs(web_contents.GetMainFrame(), JsReplace("location = $1", gurl));
   observer.Wait();
 }
 
diff --git a/content/public/test/referrer_unittest.cc b/content/public/test/referrer_unittest.cc
index 1962891..fc78f84 100644
--- a/content/public/test/referrer_unittest.cc
+++ b/content/public/test/referrer_unittest.cc
@@ -4,7 +4,8 @@
 
 #include "content/public/common/referrer.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/test/gtest_util.h"
 #include "net/url_request/referrer_policy.h"
 #include "testing/gtest/include/gtest/gtest.h"
@@ -16,16 +17,18 @@
 using ReferrerSanitizerTest = testing::Test;
 
 TEST_F(ReferrerSanitizerTest, SanitizesPolicyForEmptyReferrers) {
-  EXPECT_DCHECK_DEATH(ignore_result(Referrer::SanitizeForRequest(
-      GURL("https://a"),
-      Referrer(GURL(), static_cast<network::mojom::ReferrerPolicy>(200)))));
+  EXPECT_DCHECK_DEATH(
+      std::ignore = Referrer::SanitizeForRequest(
+          GURL("https://a"),
+          Referrer(GURL(), static_cast<network::mojom::ReferrerPolicy>(200))));
 }
 
 TEST_F(ReferrerSanitizerTest, SanitizesPolicyForNonEmptyReferrers) {
-  EXPECT_DCHECK_DEATH(ignore_result(Referrer::SanitizeForRequest(
-      GURL("https://a"),
-      Referrer(GURL("http://b"),
-               static_cast<network::mojom::ReferrerPolicy>(200)))));
+  EXPECT_DCHECK_DEATH(
+      std::ignore = Referrer::SanitizeForRequest(
+          GURL("https://a"),
+          Referrer(GURL("http://b"),
+                   static_cast<network::mojom::ReferrerPolicy>(200))));
 }
 
 TEST_F(ReferrerSanitizerTest, SanitizeOriginForRequest) {
diff --git a/content/public/test/render_view_test.cc b/content/public/test/render_view_test.cc
index 3e83516..9cd9b18f 100644
--- a/content/public/test/render_view_test.cc
+++ b/content/public/test/render_view_test.cc
@@ -7,10 +7,10 @@
 #include <stddef.h>
 
 #include <cctype>
+#include <tuple>
 
 #include "base/bind.h"
 #include "base/callback_helpers.h"
-#include "base/ignore_result.h"
 #include "base/location.h"
 #include "base/memory/raw_ptr.h"
 #include "base/run_loop.h"
@@ -514,8 +514,8 @@
   main_frame_params->routing_id = render_thread_->GetNextRoutingID();
   main_frame_params->frame = TestRenderFrame::CreateStubFrameReceiver();
   // Ignoring the returned PendingReceiver because it is not bound to anything
-  ignore_result(
-      main_frame_params->interface_broker.InitWithNewPipeAndPassReceiver());
+  std::ignore =
+      main_frame_params->interface_broker.InitWithNewPipeAndPassReceiver();
   policy_container_host_ = std::make_unique<MockPolicyContainerHost>();
   main_frame_params->policy_container =
       policy_container_host_->CreatePolicyContainerForBlink();
@@ -561,7 +561,7 @@
   mojo::Remote<blink::mojom::LeakDetector> leak_detector;
   mojo::GenericPendingReceiver receiver(
       leak_detector.BindNewPipeAndPassReceiver());
-  ignore_result(binders_.TryBind(&receiver));
+  std::ignore = binders_.TryBind(&receiver);
 
   // Close the main |view_| as well as any other windows that might have been
   // opened by the test.
diff --git a/content/public/test/test_storage_partition.cc b/content/public/test/test_storage_partition.cc
index bc39c16..2e8e73f 100644
--- a/content/public/test/test_storage_partition.cc
+++ b/content/public/test/test_storage_partition.cc
@@ -4,7 +4,8 @@
 
 #include "content/public/test/test_storage_partition.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "components/leveldb_proto/public/proto_database_provider.h"
 #include "content/public/browser/file_system_access_entry_factory.h"
 #include "services/network/public/mojom/cookie_manager.mojom.h"
@@ -89,7 +90,7 @@
   // Bind and throw away the receiver. If testing is required, then add a method
   // to set the remote.
   if (!local_storage_control_.is_bound())
-    ignore_result(local_storage_control_.BindNewPipeAndPassReceiver());
+    std::ignore = local_storage_control_.BindNewPipeAndPassReceiver();
   return local_storage_control_.get();
 }
 
@@ -97,7 +98,7 @@
   // Bind and throw away the receiver. If testing is required, then add a method
   // to set the remote.
   if (!indexed_db_control_.is_bound())
-    ignore_result(indexed_db_control_.BindNewPipeAndPassReceiver());
+    std::ignore = indexed_db_control_.BindNewPipeAndPassReceiver();
   return *indexed_db_control_;
 }
 
@@ -127,7 +128,7 @@
   // Bind and throw away the receiver. If testing is required, then add a method
   // to set the remote.
   if (!cache_storage_control_.is_bound())
-    ignore_result(cache_storage_control_.BindNewPipeAndPassReceiver());
+    std::ignore = cache_storage_control_.BindNewPipeAndPassReceiver();
   return cache_storage_control_.get();
 }
 
diff --git a/content/renderer/BUILD.gn b/content/renderer/BUILD.gn
index 01fcc4b..d669f97 100644
--- a/content/renderer/BUILD.gn
+++ b/content/renderer/BUILD.gn
@@ -237,7 +237,6 @@
     "//base:i18n",
     "//build:chromecast_buildflags",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//cc",
     "//cc/animation",
     "//cc/mojo_embedder",
diff --git a/content/renderer/media/android/stream_texture_proxy_unittest.cc b/content/renderer/media/android/stream_texture_proxy_unittest.cc
index ba1f57d..c35005a 100644
--- a/content/renderer/media/android/stream_texture_proxy_unittest.cc
+++ b/content/renderer/media/android/stream_texture_proxy_unittest.cc
@@ -2,7 +2,8 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/memory/ptr_util.h"
 #include "base/memory/scoped_refptr.h"
 #include "base/test/task_environment.h"
@@ -46,7 +47,7 @@
     // Create the StreamTextureHost with a valid |channel_|. Note that route_id
     // does not matter here for the test we are writing.
     mojo::PendingAssociatedRemote<gpu::mojom::StreamTexture> texture;
-    ignore_result(texture.InitWithNewEndpointAndPassReceiver());
+    std::ignore = texture.InitWithNewEndpointAndPassReceiver();
     texture.EnableUnassociatedUsage();
     auto host = std::make_unique<StreamTextureHost>(channel_, 1 /* route_id */,
                                                     std::move(texture));
diff --git a/content/renderer/media/media_factory.cc b/content/renderer/media/media_factory.cc
index a973c8d2..57641a53 100644
--- a/content/renderer/media/media_factory.cc
+++ b/content/renderer/media/media_factory.cc
@@ -19,7 +19,6 @@
 #include "build/build_config.h"
 #include "build/buildflag.h"
 #include "build/chromecast_buildflags.h"
-#include "build/os_buildflags.h"
 #include "cc/trees/layer_tree_settings.h"
 #include "content/public/common/content_client.h"
 #include "content/public/common/content_switches.h"
diff --git a/content/renderer/mock_agent_scheduling_group.cc b/content/renderer/mock_agent_scheduling_group.cc
index 23a9327..e74b84701 100644
--- a/content/renderer/mock_agent_scheduling_group.cc
+++ b/content/renderer/mock_agent_scheduling_group.cc
@@ -4,7 +4,8 @@
 
 #include "content/renderer/mock_agent_scheduling_group.h"
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "content/renderer/render_thread_impl.h"
 #include "third_party/blink/public/mojom/browser_interface_broker.mojom.h"
 
@@ -57,11 +58,11 @@
 void MockAgentSchedulingGroup::Init() {
   mojo::AssociatedRemote<mojom::AgentSchedulingGroupHost>
       agent_scheduling_group_host;
-  ignore_result(
-      agent_scheduling_group_host.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore =
+      agent_scheduling_group_host.BindNewEndpointAndPassDedicatedReceiver();
   mojo::AssociatedRemote<mojom::RouteProvider> browser_route_provider;
-  ignore_result(
-      browser_route_provider.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore =
+      browser_route_provider.BindNewEndpointAndPassDedicatedReceiver();
 
   BindAssociatedInterfaces(
       agent_scheduling_group_host.Unbind(), browser_route_provider.Unbind(),
diff --git a/content/renderer/render_frame_impl.cc b/content/renderer/render_frame_impl.cc
index 8f5d497..4a82485 100644
--- a/content/renderer/render_frame_impl.cc
+++ b/content/renderer/render_frame_impl.cc
@@ -2951,17 +2951,6 @@
                 new_loader_factories->Clone()));
   }
 
-  WebString subresource_filter = navigation_params->response.HttpHeaderField(
-      WebString::FromUTF8("Service-Worker-Subresource-Filter"));
-  if (!subresource_filter.IsEmpty()) {
-    ServiceWorkerNetworkProviderForFrame* provider =
-        static_cast<ServiceWorkerNetworkProviderForFrame*>(
-            navigation_params->service_worker_network_provider.get());
-    DCHECK(provider);
-
-    provider->context()->SetSubresourceFilter(subresource_filter.Utf8());
-  }
-
   DCHECK(!pending_loader_factories_);
   pending_loader_factories_ = std::move(new_loader_factories);
   pending_code_cache_host_ = std::move(code_cache_host);
diff --git a/content/renderer/render_frame_impl_browsertest.cc b/content/renderer/render_frame_impl_browsertest.cc
index a7c256b5..0f5d9f2 100644
--- a/content/renderer/render_frame_impl_browsertest.cc
+++ b/content/renderer/render_frame_impl_browsertest.cc
@@ -3,6 +3,7 @@
 // found in the LICENSE file.
 
 #include <stdint.h>
+
 #include <tuple>
 #include <utility>
 
@@ -10,7 +11,6 @@
 #include "base/callback_helpers.h"
 #include "base/command_line.h"
 #include "base/debug/leak_annotations.h"
-#include "base/ignore_result.h"
 #include "base/run_loop.h"
 #include "base/strings/stringprintf.h"
 #include "base/strings/utf_string_conversions.h"
@@ -138,7 +138,7 @@
         main_frame.BindNewEndpointAndPassDedicatedReceiver();
 
     mojo::AssociatedRemote<blink::mojom::RemoteMainFrameHost> main_frame_host;
-    ignore_result(main_frame_host.BindNewEndpointAndPassDedicatedReceiver());
+    std::ignore = main_frame_host.BindNewEndpointAndPassDedicatedReceiver();
     remote_main_frame_interfaces->main_frame_host = main_frame_host.Unbind();
 
     RenderFrameImpl::FromWebFrame(
diff --git a/content/renderer/render_view_browsertest.cc b/content/renderer/render_view_browsertest.cc
index 55156ed..5ed5981 100644
--- a/content/renderer/render_view_browsertest.cc
+++ b/content/renderer/render_view_browsertest.cc
@@ -13,7 +13,6 @@
 #include "base/callback_helpers.h"
 #include "base/command_line.h"
 #include "base/cxx17_backports.h"
-#include "base/ignore_result.h"
 #include "base/json/json_reader.h"
 #include "base/json/json_writer.h"
 #include "base/location.h"
@@ -273,7 +272,7 @@
   interfaces->main_frame = main_frame.BindNewEndpointAndPassDedicatedReceiver();
 
   mojo::AssociatedRemote<blink::mojom::RemoteMainFrameHost> main_frame_host;
-  ignore_result(main_frame_host.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore = main_frame_host.BindNewEndpointAndPassDedicatedReceiver();
   interfaces->main_frame_host = main_frame_host.Unbind();
 
   return interfaces;
@@ -1107,7 +1106,7 @@
       blink_widget.BindNewEndpointAndPassDedicatedReceiver();
 
   mojo::AssociatedRemote<blink::mojom::WidgetHost> blink_widget_host;
-  ignore_result(blink_widget_host.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore = blink_widget_host.BindNewEndpointAndPassDedicatedReceiver();
 
   mojo::AssociatedRemote<blink::mojom::FrameWidget> blink_frame_widget;
   mojo::PendingAssociatedReceiver<blink::mojom::FrameWidget>
@@ -1115,8 +1114,8 @@
           blink_frame_widget.BindNewEndpointAndPassDedicatedReceiver();
 
   mojo::AssociatedRemote<blink::mojom::FrameWidgetHost> blink_frame_widget_host;
-  ignore_result(
-      blink_frame_widget_host.BindNewEndpointAndPassDedicatedReceiver());
+  std::ignore =
+      blink_frame_widget_host.BindNewEndpointAndPassDedicatedReceiver();
 
   widget_params->frame_widget = std::move(blink_frame_widget_receiver);
   widget_params->frame_widget_host = blink_frame_widget_host.Unbind();
diff --git a/content/renderer/service_worker/service_worker_network_provider_for_frame.cc b/content/renderer/service_worker/service_worker_network_provider_for_frame.cc
index ce87ff6b..554b919d 100644
--- a/content/renderer/service_worker/service_worker_network_provider_for_frame.cc
+++ b/content/renderer/service_worker/service_worker_network_provider_for_frame.cc
@@ -138,21 +138,6 @@
   if (request.GetSkipServiceWorker())
     return nullptr;
 
-  if (observer_ && observer_->render_frame()
-                       ->GetWebFrame()
-                       ->ServiceWorkerSubresourceFilterEnabled()) {
-    const std::string subresource_filter = context()->subresource_filter();
-    // If the document has a subresource filter set and the requested URL does
-    // not match it, do not intercept the request.
-    if (!subresource_filter.empty() &&
-        gurl.ref().find(subresource_filter) == std::string::npos) {
-      observer_->ReportFeatureUsage(
-          blink::mojom::WebFeature::
-              kServiceWorkerSubresourceFilterBypassedRequest);
-      return nullptr;
-    }
-  }
-
   // Record use counter for intercepting requests from opaque stylesheets.
   // TODO(crbug.com/898497): Remove this feature usage once we have enough data.
   if (observer_ && request.IsFromOriginDirtyStyleSheet()) {
diff --git a/content/renderer/service_worker/service_worker_provider_context.h b/content/renderer/service_worker/service_worker_provider_context.h
index b2045274..bc9a84b 100644
--- a/content/renderer/service_worker/service_worker_provider_context.h
+++ b/content/renderer/service_worker/service_worker_provider_context.h
@@ -201,11 +201,6 @@
       const override;
   const blink::WebString client_id() const override;
 
-  std::string subresource_filter() const { return subresource_filter_; }
-  void SetSubresourceFilter(const std::string& filter) {
-    subresource_filter_ = filter;
-  }
-
  private:
   friend class base::DeleteHelper<ServiceWorkerProviderContext>;
   friend class base::RefCountedThreadSafe<ServiceWorkerProviderContext,
@@ -336,8 +331,6 @@
 
   bool sent_execution_ready_ = false;
 
-  std::string subresource_filter_;
-
   // Contains pending receivers whose corresponding requests are still
   // in-flight. The pending receivers are taken by
   // TakePendingWorkerTimingReceiver() when the request is completed.
diff --git a/content/shell/app/shell_main_delegate.cc b/content/shell/app/shell_main_delegate.cc
index 62aeb5e..dd80654 100644
--- a/content/shell/app/shell_main_delegate.cc
+++ b/content/shell/app/shell_main_delegate.cc
@@ -5,6 +5,7 @@
 #include "content/shell/app/shell_main_delegate.h"
 
 #include <iostream>
+#include <tuple>
 #include <utility>
 
 #include "base/base_paths.h"
@@ -13,7 +14,6 @@
 #include "base/cpu.h"
 #include "base/files/file.h"
 #include "base/files/file_path.h"
-#include "base/ignore_result.h"
 #include "base/lazy_instance.h"
 #include "base/logging.h"
 #include "base/path_service.h"
@@ -262,7 +262,7 @@
       main_runner->Initialize(std::move(main_function_params));
   DCHECK_LT(initialize_exit_code, 0)
       << "BrowserMainRunner::Initialize failed in ShellMainDelegate";
-  ignore_result(main_runner.release());
+  std::ignore = main_runner.release();
   // Return 0 as BrowserMain() should not be called after this, bounce up to
   // the system message loop for ContentShell, and we're already done thanks
   // to the |ui_task| for browser tests.
diff --git a/content/test/BUILD.gn b/content/test/BUILD.gn
index 8e92405..b9a7341 100644
--- a/content/test/BUILD.gn
+++ b/content/test/BUILD.gn
@@ -1284,7 +1284,6 @@
     "../browser/service_worker/service_worker_no_best_effort_tasks_browsertest.cc",
     "../browser/service_worker/service_worker_offline_capability_check_browsertest.cc",
     "../browser/service_worker/service_worker_process_browsertest.cc",
-    "../browser/service_worker/service_worker_subresource_filter_browsertest.cc",
     "../browser/service_worker/service_worker_version_browsertest.cc",
     "../browser/session_history_browsertest.cc",
     "../browser/shape_detection/shape_detection_browsertest.cc",
diff --git a/content/test/test_navigation_url_loader.cc b/content/test/test_navigation_url_loader.cc
index 76b0861..4ccb572 100644
--- a/content/test/test_navigation_url_loader.cc
+++ b/content/test/test_navigation_url_loader.cc
@@ -4,9 +4,9 @@
 
 #include "content/test/test_navigation_url_loader.h"
 
+#include <tuple>
 #include <utility>
 
-#include "base/ignore_result.h"
 #include "content/browser/loader/navigation_early_hints_manager.h"
 #include "content/browser/loader/navigation_url_loader_delegate.h"
 #include "content/browser/navigation_subresource_loader_params.h"
@@ -97,7 +97,7 @@
   // purpose of this is not to violate some DCHECKs when the navigation commits.
   mojo::PendingRemote<network::mojom::URLLoaderClient> url_loader_client_remote;
   mojo::PendingRemote<network::mojom::URLLoader> url_loader_remote;
-  ignore_result(url_loader_remote.InitWithNewPipeAndPassReceiver());
+  std::ignore = url_loader_remote.InitWithNewPipeAndPassReceiver();
   auto url_loader_client_endpoints =
       network::mojom::URLLoaderClientEndpoints::New(
           std::move(url_loader_remote),
diff --git a/content/test/test_render_view_host.cc b/content/test/test_render_view_host.cc
index 6a097ce..b2b2e5e 100644
--- a/content/test/test_render_view_host.cc
+++ b/content/test/test_render_view_host.cc
@@ -5,8 +5,8 @@
 #include "content/test/test_render_view_host.h"
 
 #include <memory>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "base/strings/utf_string_conversions.h"
 #include "build/build_config.h"
 #include "components/viz/common/surfaces/parent_local_surface_id_allocator.h"
@@ -406,7 +406,7 @@
     // Pretend that mojo connections of the RemoteFrame is transferred to
     // renderer process and bound in blink.
     mojo::AssociatedRemote<blink::mojom::RemoteMainFrame> remote_main_frame;
-    ignore_result(remote_main_frame.BindNewEndpointAndPassDedicatedReceiver());
+    std::ignore = remote_main_frame.BindNewEndpointAndPassDedicatedReceiver();
     proxy_host->BindRemoteMainFrameInterfaces(
         remote_main_frame.Unbind(),
         mojo::AssociatedRemote<blink::mojom::RemoteMainFrameHost>()
diff --git a/content/web_test/renderer/gc_controller.cc b/content/web_test/renderer/gc_controller.cc
index a343bbf..1c20b29 100644
--- a/content/web_test/renderer/gc_controller.cc
+++ b/content/web_test/renderer/gc_controller.cc
@@ -4,8 +4,9 @@
 
 #include "content/web_test/renderer/gc_controller.h"
 
+#include <tuple>
+
 #include "base/bind.h"
-#include "base/ignore_result.h"
 #include "gin/arguments.h"
 #include "gin/handle.h"
 #include "gin/object_template_builder.h"
@@ -103,7 +104,7 @@
       isolate, v8::MicrotasksScope::kDoNotRunMicrotasks);
   auto result = func->Call(context, context->Global(), 0, nullptr);
   // Swallow potential exception.
-  ignore_result(result);
+  std::ignore = result;
 }
 
 void GCController::MinorCollect(const gin::Arguments& args) {
diff --git a/content/zygote/zygote_linux.cc b/content/zygote/zygote_linux.cc
index a93ff40..be67fab 100644
--- a/content/zygote/zygote_linux.cc
+++ b/content/zygote/zygote_linux.cc
@@ -14,11 +14,11 @@
 #include <sys/types.h>
 #include <sys/wait.h>
 
+#include <tuple>
 #include <utility>
 
 #include "base/command_line.h"
 #include "base/files/file_util.h"
-#include "base/ignore_result.h"
 #include "base/linux_util.h"
 #include "base/logging.h"
 #include "base/pickle.h"
@@ -591,7 +591,7 @@
 
     // Pass ownership of file descriptors from fds to GlobalDescriptors.
     for (base::ScopedFD& fd : fds)
-      ignore_result(fd.release());
+      std::ignore = fd.release();
     base::GlobalDescriptors::GetInstance()->Reset(mapping);
 
     // Reset the process-wide command line to our new command line.
diff --git a/device/fido/appid_exclude_probe_task.cc b/device/fido/appid_exclude_probe_task.cc
index 065fded7..d36ea64 100644
--- a/device/fido/appid_exclude_probe_task.cc
+++ b/device/fido/appid_exclude_probe_task.cc
@@ -65,7 +65,8 @@
       device(), std::move(request),
       base::BindOnce(&AppIdExcludeProbeTask::HandleResponseToSilentSignRequest,
                      weak_factory_.GetWeakPtr()),
-      base::BindOnce(&ReadCTAPGetAssertionResponse),
+      base::BindOnce(&ReadCTAPGetAssertionResponse,
+                     device()->DeviceTransport()),
       /*string_fixup_predicate=*/nullptr);
   silent_sign_operation_->Start();
 }
diff --git a/device/fido/authenticator_get_assertion_response.h b/device/fido/authenticator_get_assertion_response.h
index cd6df48..0b29f28f3 100644
--- a/device/fido/authenticator_get_assertion_response.h
+++ b/device/fido/authenticator_get_assertion_response.h
@@ -69,6 +69,10 @@
   // Whether a large blob was successfully written as part of this GetAssertion
   // request.
   bool large_blob_written = false;
+
+  // The transport used to generate this response. This is unknown when using
+  // the Windows WebAuthn API.
+  absl::optional<FidoTransportProtocol> transport_used;
 };
 
 }  // namespace device
diff --git a/device/fido/cable/v2_authenticator.cc b/device/fido/cable/v2_authenticator.cc
index a10ada9..b195c28f 100644
--- a/device/fido/cable/v2_authenticator.cc
+++ b/device/fido/cable/v2_authenticator.cc
@@ -394,19 +394,11 @@
           return;
         }
 
-        // It should be the case that all post-handshake messages fall into
-        // a single padding bucket. (It doesn't have to be the smallest one.)
-        //
-        // This check should be:
-        // DCHECK_EQ(post_handshake_msg_bytes->size(),
-        //          kPostHandshakeMsgPaddingGranularity);
-        //
-        // ... but we're waiting to roll out a protocol change that allows it.
-        // For now, check that the messages fit within the future padding
-        // granularity, which will also highlight this when that constant is
-        // rename to remove "Future".
-        DCHECK_LE(post_handshake_msg_bytes->size(),
-                  kFuturePostHandshakeMsgPaddingGranularity);
+        // All post-handshake messages should fit into the same padding bucket.
+        // It doesn't have to be the smallest one, but that's currently true
+        // which yields this easy check:
+        DCHECK_EQ(post_handshake_msg_bytes->size(),
+                  kPostHandshakeMsgPaddingGranularity);
 
         if (!crypter_->Encrypt(&post_handshake_msg_bytes.value())) {
           FIDO_LOG(ERROR) << "failed to encrypt post-handshake message";
diff --git a/device/fido/cable/v2_constants.h b/device/fido/cable/v2_constants.h
index 12ad128..a212231 100644
--- a/device/fido/cable/v2_constants.h
+++ b/device/fido/cable/v2_constants.h
@@ -64,11 +64,7 @@
 // kPostHandshakeMsgPaddingGranularity is the granularity of the padding added
 // to the post-handshake message. This should be sufficiently large to pad away
 // all information about the contents of this message.
-constexpr size_t kPostHandshakeMsgPaddingGranularity = 256;
-// kFuturePostHandshakeMsgPaddingGranularity will be the granularity of the
-// padding added to the post-handshake message. This is currently only used for
-// testing.
-constexpr size_t kFuturePostHandshakeMsgPaddingGranularity = 512;
+constexpr size_t kPostHandshakeMsgPaddingGranularity = 512;
 
 }  // namespace cablev2
 }  // namespace device
diff --git a/device/fido/cable/v2_handshake.cc b/device/fido/cable/v2_handshake.cc
index 0fec587a..5e33bb6a 100644
--- a/device/fido/cable/v2_handshake.cc
+++ b/device/fido/cable/v2_handshake.cc
@@ -569,6 +569,15 @@
 
 absl::optional<std::vector<uint8_t>> EncodePaddedCBORMap(
     cbor::Value::MapValue map) {
+  // The number of padding bytes is a uint16_t, so the granularity cannot be
+  // larger than that.
+  static_assert(kPostHandshakeMsgPaddingGranularity > 0, "");
+  static_assert(kPostHandshakeMsgPaddingGranularity - 1 <=
+                std::numeric_limits<uint16_t>::max());
+  // The granularity must also be a power of two.
+  static_assert((kPostHandshakeMsgPaddingGranularity &
+                 (kPostHandshakeMsgPaddingGranularity - 1)) == 0);
+
   absl::optional<std::vector<uint8_t>> cbor_bytes =
       cbor::Writer::Write(cbor::Value(std::move(map)));
   if (!cbor_bytes) {
@@ -576,60 +585,39 @@
   }
 
   base::CheckedNumeric<size_t> padded_size_checked = cbor_bytes->size();
-  padded_size_checked += 1;  // padding-length byte
-  padded_size_checked = (padded_size_checked + 255) & ~255;
+  padded_size_checked += sizeof(uint16_t);  // padding-length bytes
+  padded_size_checked =
+      (padded_size_checked + kPostHandshakeMsgPaddingGranularity - 1) &
+      ~(kPostHandshakeMsgPaddingGranularity - 1);
   if (!padded_size_checked.IsValid()) {
     return absl::nullopt;
   }
 
   const size_t padded_size = padded_size_checked.ValueOrDie();
-  DCHECK_GT(padded_size, cbor_bytes->size());
-  const size_t extra_padding = padded_size - cbor_bytes->size();
+  DCHECK_GE(padded_size, cbor_bytes->size() + sizeof(uint16_t));
+  const size_t extra_bytes = padded_size - cbor_bytes->size();
+  const size_t num_padding_bytes =
+      extra_bytes - sizeof(uint16_t) /* length of padding length */;
 
   cbor_bytes->resize(padded_size);
-  DCHECK_LE(extra_padding, 256u);
-  cbor_bytes->at(padded_size - 1) = static_cast<uint8_t>(extra_padding - 1);
+  const uint16_t num_padding_bytes16 =
+      base::checked_cast<uint16_t>(num_padding_bytes);
+  memcpy(&cbor_bytes.value()[padded_size - sizeof(num_padding_bytes16)],
+         &num_padding_bytes16, sizeof(num_padding_bytes16));
 
   return *cbor_bytes;
 }
 
-// DecodePaddedCBORMap16 is the future replacement for |DecodePaddedCBORMap|,
-// below. It parses a slightly different format that allows for more padding.
-// (This is needed because some structures ended up larger than initially
-// expected.) In order to transition, |DecodePaddedCBORMap| calls this function
-// if it fails to parse. In the future we can drop supporting the old format and
-// start sending new-format messages. This works because CBOR parsing doesn't
-// depend on the length of the input (other than to fail on truncation) so
-// there's no ambiguity about the parse.
-absl::optional<cbor::Value> DecodePaddedCBORMap16(
-    base::span<const uint8_t> input) {
-  if (input.size() < sizeof(uint16_t)) {
-    return absl::nullopt;
-  }
+namespace {
 
-  uint16_t padding_length16;
-  memcpy(&padding_length16, &input[input.size() - sizeof(padding_length16)],
-         sizeof(padding_length16));
-  const size_t padding_length = padding_length16;
-  if (padding_length + sizeof(uint16_t) > input.size()) {
-    FIDO_LOG(DEBUG) << "Invalid padding in caBLE handshake message";
-    return absl::nullopt;
-  }
-  input = input.subspan(0, input.size() - padding_length - sizeof(uint16_t));
-
-  absl::optional<cbor::Value> payload = cbor::Reader::Read(input);
-  if (!payload || !payload->is_map()) {
-    FIDO_LOG(DEBUG) << "CBOR parse failure in caBLE handshake message";
-    return absl::nullopt;
-  }
-
-  return payload;
-}
-
-absl::optional<cbor::Value> DecodePaddedCBORMap(
+// DecodePaddedCBORMap8 performs the actions of |DecodePaddedCBORMap| using the
+// old padding format. We still support this format for backwards compatibility.
+// See comment in |DecodePaddedCBORMap|.
+//
+// TODO(agl): remove support for this padding format. (Chromium started sending
+// the new format with M99.)
+absl::optional<cbor::Value> DecodePaddedCBORMap8(
     const base::span<const uint8_t> input) {
-  // TODO: replace this with the body of |DecodePaddedCBORMap16| once M92 is
-  // everywhere.
   if (input.empty()) {
     return absl::nullopt;
   }
@@ -642,12 +630,54 @@
 
   absl::optional<cbor::Value> payload = cbor::Reader::Read(unpadded_input);
   if (!payload || !payload->is_map()) {
-    return DecodePaddedCBORMap16(input);
+    return absl::nullopt;
   }
 
   return payload;
 }
 
+// DecodePaddedCBORMap16 performs the actions of |DecodePaddedCBORMap| using the
+// new padding format. See comment in |DecodePaddedCBORMap|.
+absl::optional<cbor::Value> DecodePaddedCBORMap16(
+    base::span<const uint8_t> input) {
+  if (input.size() < sizeof(uint16_t)) {
+    return absl::nullopt;
+  }
+
+  uint16_t padding_length16;
+  memcpy(&padding_length16, &input[input.size() - sizeof(padding_length16)],
+         sizeof(padding_length16));
+  const size_t padding_length = padding_length16;
+  if (padding_length + sizeof(uint16_t) > input.size()) {
+    return absl::nullopt;
+  }
+  input = input.subspan(0, input.size() - padding_length - sizeof(uint16_t));
+
+  absl::optional<cbor::Value> payload = cbor::Reader::Read(input);
+  if (!payload || !payload->is_map()) {
+    return absl::nullopt;
+  }
+
+  return payload;
+}
+
+}  // namespace
+
+absl::optional<cbor::Value> DecodePaddedCBORMap(
+    base::span<const uint8_t> input) {
+  // Two padding formats are currently in use. They are unambiguous so we try
+  // each, new first. Eventually the old format can be removed once enough time
+  // has passed since M99.
+  absl::optional<cbor::Value> result = DecodePaddedCBORMap16(input);
+  if (!result) {
+    result = DecodePaddedCBORMap8(input);
+  }
+  if (!result) {
+    FIDO_LOG(DEBUG) << "Invalid padding in caBLE handshake message";
+  }
+  return result;
+}
+
 Crypter::Crypter(base::span<const uint8_t, 32> read_key,
                  base::span<const uint8_t, 32> write_key)
     : read_key_(fido_parsing_utils::Materialize(read_key)),
diff --git a/device/fido/cable/v2_handshake_unittest.cc b/device/fido/cable/v2_handshake_unittest.cc
index 1795f13..132f661 100644
--- a/device/fido/cable/v2_handshake_unittest.cc
+++ b/device/fido/cable/v2_handshake_unittest.cc
@@ -115,20 +115,11 @@
   EXPECT_EQ(1u, decoded->GetMap().size());
 }
 
-// FutureEncodePaddedCBORMapFunction is the future replacement for
-// |EncodePaddedCBORMap|. See comment on |DecodePaddedCBORMap16|.
-absl::optional<std::vector<uint8_t>> FutureEncodePaddedCBORMapFunction(
+// EncodePaddedCBORMapOld is the old padding function that used to be used.
+// We should still be compatible with it until M99 has been out in the world
+// for long enough.
+absl::optional<std::vector<uint8_t>> EncodePaddedCBORMapOld(
     cbor::Value::MapValue map) {
-  // TODO: when promoting this function, update comment on
-  // |kPostHandshakeMsgPaddingGranularity|.
-
-  // The number of padding bytes is a uint16_t, so the granularity cannot be
-  // larger than that.
-  static_assert(kFuturePostHandshakeMsgPaddingGranularity > 0, "");
-  static_assert(kFuturePostHandshakeMsgPaddingGranularity - 1 <=
-                    std::numeric_limits<uint16_t>::max(),
-                "");
-
   absl::optional<std::vector<uint8_t>> cbor_bytes =
       cbor::Writer::Write(cbor::Value(std::move(map)));
   if (!cbor_bytes) {
@@ -136,41 +127,33 @@
   }
 
   base::CheckedNumeric<size_t> padded_size_checked = cbor_bytes->size();
-  padded_size_checked += sizeof(uint16_t);  // padding-length bytes
-  padded_size_checked =
-      (padded_size_checked + kFuturePostHandshakeMsgPaddingGranularity - 1) &
-      ~(kFuturePostHandshakeMsgPaddingGranularity - 1);
+  padded_size_checked += 1;  // padding-length byte
+  padded_size_checked = (padded_size_checked + 255) & ~255;
   if (!padded_size_checked.IsValid()) {
     return absl::nullopt;
   }
 
   const size_t padded_size = padded_size_checked.ValueOrDie();
-  DCHECK_GE(padded_size, cbor_bytes->size() + sizeof(uint16_t));
-  const size_t extra_bytes = padded_size - cbor_bytes->size();
-  const size_t num_padding_bytes =
-      extra_bytes - sizeof(uint16_t) /* length of padding length */;
+  DCHECK_GT(padded_size, cbor_bytes->size());
+  const size_t extra_padding = padded_size - cbor_bytes->size();
 
   cbor_bytes->resize(padded_size);
-  const uint16_t num_padding_bytes16 =
-      base::checked_cast<uint16_t>(num_padding_bytes);
-  memcpy(&cbor_bytes.value()[padded_size - sizeof(num_padding_bytes16)],
-         &num_padding_bytes16, sizeof(num_padding_bytes16));
+  DCHECK_LE(extra_padding, 256u);
+  cbor_bytes->at(padded_size - 1) = static_cast<uint8_t>(extra_padding - 1);
 
   return *cbor_bytes;
 }
 
-TEST(CableV2Encoding, FuturePaddedCBOR) {
-  // Test that we can decode messages padded by the encoding function that
-  // will be used in the future.
+TEST(CableV2Encoding, OldPaddedCBOR) {
+  // Test that we can decode messages padded by the old encoding function.
   for (size_t i = 0; i < 512; i++) {
     SCOPED_TRACE(i);
 
-    // Check that new->old direction works.
     const std::vector<uint8_t> dummy_array(i);
     cbor::Value::MapValue map;
     map.emplace(1, dummy_array);
     absl::optional<std::vector<uint8_t>> encoded =
-        FutureEncodePaddedCBORMapFunction(std::move(map));
+        EncodePaddedCBORMapOld(std::move(map));
     ASSERT_TRUE(encoded);
 
     absl::optional<cbor::Value> decoded = DecodePaddedCBORMap(*encoded);
diff --git a/device/fido/cros/authenticator.cc b/device/fido/cros/authenticator.cc
index 716812859..39b5f15 100644
--- a/device/fido/cros/authenticator.cc
+++ b/device/fido/cros/authenticator.cc
@@ -18,6 +18,7 @@
 #include "device/fido/attestation_statement_formats.h"
 #include "device/fido/authenticator_data.h"
 #include "device/fido/fido_parsing_utils.h"
+#include "device/fido/fido_transport_protocol.h"
 #include "device/fido/opaque_attestation_statement.h"
 #include "third_party/cros_system_api/dbus/u2f/dbus-constants.h"
 
@@ -255,6 +256,7 @@
                                  assertion.signature().end());
   AuthenticatorGetAssertionResponse authenticator_response(
       std::move(*authenticator_data), std::move(signature));
+  authenticator_response.transport_used = FidoTransportProtocol::kInternal;
   const std::string& credential_id = assertion.credential_id();
   authenticator_response.credential = PublicKeyCredentialDescriptor(
       CredentialType::kPublicKey,
diff --git a/device/fido/ctap_response_fuzzer.cc b/device/fido/ctap_response_fuzzer.cc
index 600884831..46aeb20a 100644
--- a/device/fido/ctap_response_fuzzer.cc
+++ b/device/fido/ctap_response_fuzzer.cc
@@ -47,25 +47,25 @@
   }
 
   std::array<uint8_t, 32> relying_party_id_hash = {};
-  auto response = device::ReadCTAPMakeCredentialResponse(
+  auto response = ReadCTAPMakeCredentialResponse(
       FidoTransportProtocol::kUsbHumanInterfaceDevice, input_cbor);
   if (response)
     response->EraseAttestationStatement(AttestationObject::AAGUID::kErase);
 
-  response = device::AuthenticatorMakeCredentialResponse::
-      CreateFromU2fRegisterResponse(
-          FidoTransportProtocol::kUsbHumanInterfaceDevice,
-          relying_party_id_hash, input);
+  response = AuthenticatorMakeCredentialResponse::CreateFromU2fRegisterResponse(
+      FidoTransportProtocol::kUsbHumanInterfaceDevice, relying_party_id_hash,
+      input);
   if (response)
     response->EraseAttestationStatement(AttestationObject::AAGUID::kErase);
 
-  device::ReadCTAPGetAssertionResponse(input_cbor);
+  ReadCTAPGetAssertionResponse(FidoTransportProtocol::kUsbHumanInterfaceDevice,
+                               input_cbor);
   std::vector<uint8_t> u2f_response_data(data, data + size);
   std::vector<uint8_t> key_handle(data, data + size);
-  device::AuthenticatorGetAssertionResponse::CreateFromU2fSignResponse(
+  AuthenticatorGetAssertionResponse::CreateFromU2fSignResponse(
       relying_party_id_hash, u2f_response_data, key_handle);
 
-  device::ReadCTAPGetInfoResponse(input);
+  ReadCTAPGetInfoResponse(input);
   return 0;
 }
 
diff --git a/device/fido/ctap_response_unittest.cc b/device/fido/ctap_response_unittest.cc
index 1bdbdae..c2d0d696 100644
--- a/device/fido/ctap_response_unittest.cc
+++ b/device/fido/ctap_response_unittest.cc
@@ -16,6 +16,7 @@
 #include "device/fido/fido_constants.h"
 #include "device/fido/fido_parsing_utils.h"
 #include "device/fido/fido_test_data.h"
+#include "device/fido/fido_transport_protocol.h"
 #include "device/fido/fido_types.h"
 #include "device/fido/opaque_attestation_statement.h"
 #include "device/fido/p256_public_key.h"
@@ -519,8 +520,11 @@
 // https://fidoalliance.org/specs/fido-v2.0-rd-20170927/fido-client-to-authenticator-protocol-v2.0-rd-20170927.html
 TEST(CTAPResponseTest, TestReadGetAssertionResponse) {
   auto get_assertion_response = ReadCTAPGetAssertionResponse(
+      FidoTransportProtocol::kBluetoothLowEnergy,
       DecodeCBOR(test_data::kDeviceGetAssertionResponse));
   ASSERT_TRUE(get_assertion_response);
+  EXPECT_EQ(*get_assertion_response->transport_used,
+            FidoTransportProtocol::kBluetoothLowEnergy);
   ASSERT_TRUE(get_assertion_response->num_credentials);
   EXPECT_EQ(*get_assertion_response->num_credentials, 1u);
 
diff --git a/device/fido/device_response_converter.cc b/device/fido/device_response_converter.cc
index eb8736f7..beccd103 100644
--- a/device/fido/device_response_converter.cc
+++ b/device/fido/device_response_converter.cc
@@ -118,6 +118,7 @@
 }
 
 absl::optional<AuthenticatorGetAssertionResponse> ReadCTAPGetAssertionResponse(
+    FidoTransportProtocol transport_used,
     const absl::optional<cbor::Value>& cbor) {
   if (!cbor || !cbor->is_map())
     return absl::nullopt;
@@ -141,6 +142,8 @@
   AuthenticatorGetAssertionResponse response(std::move(*auth_data),
                                              std::move(signature));
 
+  response.transport_used = transport_used;
+
   it = response_map.find(CBOR(0x01));
   if (it != response_map.end()) {
     auto credential =
diff --git a/device/fido/device_response_converter.h b/device/fido/device_response_converter.h
index 3ef3109..72d2e64 100644
--- a/device/fido/device_response_converter.h
+++ b/device/fido/device_response_converter.h
@@ -40,6 +40,7 @@
 // |AuthenticatorGetAssertionResponse|.
 COMPONENT_EXPORT(DEVICE_FIDO)
 absl::optional<AuthenticatorGetAssertionResponse> ReadCTAPGetAssertionResponse(
+    FidoTransportProtocol transport_used,
     const absl::optional<cbor::Value>& cbor);
 
 // De-serializes CBOR encoded response to AuthenticatorGetInfo request to
diff --git a/device/fido/fido_device_authenticator.cc b/device/fido/fido_device_authenticator.cc
index e4fbbc49..4a13c36 100644
--- a/device/fido/fido_device_authenticator.cc
+++ b/device/fido/fido_device_authenticator.cc
@@ -206,7 +206,7 @@
 void FidoDeviceAuthenticator::GetNextAssertion(GetAssertionCallback callback) {
   RunOperation<CtapGetNextAssertionRequest, AuthenticatorGetAssertionResponse>(
       CtapGetNextAssertionRequest(), std::move(callback),
-      base::BindOnce(&ReadCTAPGetAssertionResponse),
+      base::BindOnce(&ReadCTAPGetAssertionResponse, device_->DeviceTransport()),
       GetAssertionTask::StringFixupPredicate);
 }
 
diff --git a/device/fido/fido_transport_protocol.cc b/device/fido/fido_transport_protocol.cc
index c3fbbce..8f8c25d 100644
--- a/device/fido/fido_transport_protocol.cc
+++ b/device/fido/fido_transport_protocol.cc
@@ -28,7 +28,6 @@
     return absl::nullopt;
 }
 
-COMPONENT_EXPORT(DEVICE_FIDO)
 base::StringPiece ToString(FidoTransportProtocol protocol) {
   switch (protocol) {
     case FidoTransportProtocol::kUsbHumanInterfaceDevice:
@@ -48,4 +47,18 @@
   }
 }
 
+AuthenticatorAttachment AuthenticatorAttachmentFromTransport(
+    FidoTransportProtocol transport) {
+  switch (transport) {
+    case FidoTransportProtocol::kInternal:
+      return AuthenticatorAttachment::kPlatform;
+    case FidoTransportProtocol::kUsbHumanInterfaceDevice:
+    case FidoTransportProtocol::kNearFieldCommunication:
+    case FidoTransportProtocol::kBluetoothLowEnergy:
+    case FidoTransportProtocol::kCloudAssistedBluetoothLowEnergy:
+    case FidoTransportProtocol::kAndroidAccessory:
+      return AuthenticatorAttachment::kCrossPlatform;
+  }
+}
+
 }  // namespace device
diff --git a/device/fido/fido_transport_protocol.h b/device/fido/fido_transport_protocol.h
index 971c85a6..39c28a0 100644
--- a/device/fido/fido_transport_protocol.h
+++ b/device/fido/fido_transport_protocol.h
@@ -7,6 +7,7 @@
 
 #include "base/component_export.h"
 #include "base/strings/string_piece.h"
+#include "device/fido/fido_types.h"
 #include "third_party/abseil-cpp/absl/types/optional.h"
 
 namespace device {
@@ -40,6 +41,10 @@
 COMPONENT_EXPORT(DEVICE_FIDO)
 base::StringPiece ToString(FidoTransportProtocol protocol);
 
+COMPONENT_EXPORT(DEVICE_FIDO)
+AuthenticatorAttachment AuthenticatorAttachmentFromTransport(
+    FidoTransportProtocol transport);
+
 }  // namespace device
 
 #endif  // DEVICE_FIDO_FIDO_TRANSPORT_PROTOCOL_H_
diff --git a/device/fido/get_assertion_task.cc b/device/fido/get_assertion_task.cc
index 5a78af9..d04bd97 100644
--- a/device/fido/get_assertion_task.cc
+++ b/device/fido/get_assertion_task.cc
@@ -173,7 +173,9 @@
         device(), request_,
         base::BindOnce(&GetAssertionTask::HandleResponse,
                        weak_factory_.GetWeakPtr(), request_.allow_list),
-        base::BindOnce(&ReadCTAPGetAssertionResponse), StringFixupPredicate);
+        base::BindOnce(&ReadCTAPGetAssertionResponse,
+                       device()->DeviceTransport()),
+        StringFixupPredicate);
     sign_operation_->Start();
     return;
   }
@@ -214,7 +216,9 @@
         device(), std::move(request),
         base::BindOnce(&GetAssertionTask::HandleResponse,
                        weak_factory_.GetWeakPtr(), request.allow_list),
-        base::BindOnce(&ReadCTAPGetAssertionResponse), StringFixupPredicate);
+        base::BindOnce(&ReadCTAPGetAssertionResponse,
+                       device()->DeviceTransport()),
+        StringFixupPredicate);
     sign_operation_->Start();
     return;
   }
@@ -228,7 +232,8 @@
           device(), NextSilentRequest(),
           base::BindOnce(&GetAssertionTask::HandleResponseToSilentRequest,
                          weak_factory_.GetWeakPtr()),
-          base::BindOnce(&ReadCTAPGetAssertionResponse),
+          base::BindOnce(&ReadCTAPGetAssertionResponse,
+                         device()->DeviceTransport()),
           /*string_fixup_predicate=*/nullptr);
   sign_operation_->Start();
 }
@@ -339,7 +344,8 @@
         device(), std::move(request),
         base::BindOnce(&GetAssertionTask::HandleResponse,
                        weak_factory_.GetWeakPtr(), request.allow_list),
-        base::BindOnce(&ReadCTAPGetAssertionResponse),
+        base::BindOnce(&ReadCTAPGetAssertionResponse,
+                       device()->DeviceTransport()),
         /*string_fixup_predicate=*/nullptr);
     sign_operation_->Start();
     return;
@@ -353,7 +359,8 @@
         device(), NextSilentRequest(),
         base::BindOnce(&GetAssertionTask::HandleResponseToSilentRequest,
                        weak_factory_.GetWeakPtr()),
-        base::BindOnce(&ReadCTAPGetAssertionResponse),
+        base::BindOnce(&ReadCTAPGetAssertionResponse,
+                       device()->DeviceTransport()),
         /*string_fixup_predicate=*/nullptr);
     sign_operation_->Start();
     return;
diff --git a/device/fido/mac/get_assertion_operation.mm b/device/fido/mac/get_assertion_operation.mm
index f444e1a..f525650 100644
--- a/device/fido/mac/get_assertion_operation.mm
+++ b/device/fido/mac/get_assertion_operation.mm
@@ -6,6 +6,7 @@
 
 #include <set>
 #include <string>
+#include "device/fido/fido_transport_protocol.h"
 
 #import <Foundation/Foundation.h>
 
@@ -140,6 +141,7 @@
   }
   AuthenticatorGetAssertionResponse response(std::move(authenticator_data),
                                              std::move(*signature));
+  response.transport_used = FidoTransportProtocol::kInternal;
   response.credential = PublicKeyCredentialDescriptor(
       CredentialType::kPublicKey, credential.credential_id);
   response.user_entity = metadata->ToPublicKeyCredentialUserEntity();
diff --git a/device/fido/make_credential_task.cc b/device/fido/make_credential_task.cc
index fbb45d7..33fbccc 100644
--- a/device/fido/make_credential_task.cc
+++ b/device/fido/make_credential_task.cc
@@ -247,7 +247,8 @@
           device(), NextSilentRequest(),
           base::BindOnce(&MakeCredentialTask::HandleResponseToSilentSignRequest,
                          weak_factory_.GetWeakPtr()),
-          base::BindOnce(&ReadCTAPGetAssertionResponse),
+          base::BindOnce(&ReadCTAPGetAssertionResponse,
+                         device()->DeviceTransport()),
           /*string_fixup_predicate=*/nullptr);
   silent_sign_operation_->Start();
 }
@@ -301,7 +302,8 @@
         device(), NextSilentRequest(),
         base::BindOnce(&MakeCredentialTask::HandleResponseToSilentSignRequest,
                        weak_factory_.GetWeakPtr()),
-        base::BindOnce(&ReadCTAPGetAssertionResponse),
+        base::BindOnce(&ReadCTAPGetAssertionResponse,
+                       device()->DeviceTransport()),
         /*string_fixup_predicate=*/nullptr);
     silent_sign_operation_->Start();
     return;
diff --git a/extensions/browser/guest_view/web_view/web_view_find_helper.cc b/extensions/browser/guest_view/web_view/web_view_find_helper.cc
index 2a7cbf1..95e4d52 100644
--- a/extensions/browser/guest_view/web_view/web_view_find_helper.cc
+++ b/extensions/browser/guest_view/web_view/web_view_find_helper.cc
@@ -137,7 +137,7 @@
   }
 
   guest_web_contents->Find(current_find_request_id_, search_text,
-                           std::move(full_options));
+                           std::move(full_options), /*skip_delay=*/true);
 }
 
 void WebViewFindHelper::FindReply(int request_id,
diff --git a/gpu/command_buffer/service/shared_image_backing_factory_gl_image.cc b/gpu/command_buffer/service/shared_image_backing_factory_gl_image.cc
index b1148ea..f1185617 100644
--- a/gpu/command_buffer/service/shared_image_backing_factory_gl_image.cc
+++ b/gpu/command_buffer/service/shared_image_backing_factory_gl_image.cc
@@ -265,12 +265,6 @@
   *allow_legacy_mailbox = gr_context_type == GrContextType::kGL;
   return true;
 #else
-#if BUILDFLAG(IS_CHROMEOS_ASH)
-  // On ChromeOS Ash, use only for SHARED_MEMORY gmb
-  if (gmb_type != gfx::SHARED_MEMORY_BUFFER) {
-    return false;
-  }
-#endif
   // Doesn't support contexts other than GL for OOPR Canvas
   if (gr_context_type != GrContextType::kGL &&
       ((usage & SHARED_IMAGE_USAGE_DISPLAY) ||
@@ -289,7 +283,6 @@
     // return false if it needs interop factory
     return false;
   }
-
   *allow_legacy_mailbox = gr_context_type == GrContextType::kGL;
   return true;
 #endif
diff --git a/gpu/command_buffer/service/shared_image_backing_factory_ozone.cc b/gpu/command_buffer/service/shared_image_backing_factory_ozone.cc
index c46ab80..396c079 100644
--- a/gpu/command_buffer/service/shared_image_backing_factory_ozone.cc
+++ b/gpu/command_buffer/service/shared_image_backing_factory_ozone.cc
@@ -15,7 +15,6 @@
 #include "gpu/command_buffer/service/shared_image_backing_ozone.h"
 #include "gpu/command_buffer/service/shared_memory_region_wrapper.h"
 #include "gpu/vulkan/vulkan_device_queue.h"
-#include "ui/gfx/buffer_types.h"
 #include "ui/gfx/gpu_memory_buffer.h"
 #include "ui/gfx/native_pixmap.h"
 #include "ui/gl/buildflags.h"
@@ -190,6 +189,21 @@
       gmb_type != gfx::SHARED_MEMORY_BUFFER) {
     return false;
   }
+  // TODO(crbug.com/969114): Not all shared image factory implementations
+  // support concurrent read/write usage.
+  if (usage & SHARED_IMAGE_USAGE_CONCURRENT_READ_WRITE) {
+    return false;
+  }
+
+  // TODO(hitawala): Until SharedImageBackingOzone supports all use cases prefer
+  // using SharedImageBackingGLImage instead
+  bool needs_interop_factory = (gr_context_type == GrContextType::kVulkan &&
+                                (usage & SHARED_IMAGE_USAGE_DISPLAY)) ||
+                               (usage & SHARED_IMAGE_USAGE_WEBGPU) ||
+                               (usage & SHARED_IMAGE_USAGE_VIDEO_DECODE);
+  if (!needs_interop_factory) {
+    return false;
+  }
 
   *allow_legacy_mailbox = false;
   return true;
diff --git a/gpu/command_buffer/service/shared_image_factory.cc b/gpu/command_buffer/service/shared_image_factory.cc
index 4b956e1..0a4bf25 100644
--- a/gpu/command_buffer/service/shared_image_factory.cc
+++ b/gpu/command_buffer/service/shared_image_factory.cc
@@ -251,9 +251,12 @@
   }
 
 #if BUILDFLAG(IS_CHROMEOS_ASH)
-  auto ozone_factory =
-      std::make_unique<SharedImageBackingFactoryOzone>(context_state);
-  factories_.push_back(std::move(ozone_factory));
+  if (gpu_preferences.enable_webgpu ||
+      gr_context_type_ == GrContextType::kVulkan) {
+    auto ozone_factory =
+        std::make_unique<SharedImageBackingFactoryOzone>(context_state);
+    factories_.push_back(std::move(ozone_factory));
+  }
 #endif  // IS_CHROMEOS_ASH
 
 #if defined(OS_FUCHSIA)
diff --git a/gpu/command_buffer/service/shared_image_representation_gl_ozone.cc b/gpu/command_buffer/service/shared_image_representation_gl_ozone.cc
index 5879bc2..1d05d407 100644
--- a/gpu/command_buffer/service/shared_image_representation_gl_ozone.cc
+++ b/gpu/command_buffer/service/shared_image_representation_gl_ozone.cc
@@ -217,6 +217,7 @@
   GLuint internal_format = image->GetInternalFormat();
   GLenum gl_format = image->GetDataFormat();
   GLenum gl_type = image->GetDataType();
+
   scoped_refptr<gles2::TexturePassthrough> texture_passthrough =
       base::MakeRefCounted<gpu::gles2::TexturePassthrough>(
           *gl_texture_service_id, target, internal_format,
diff --git a/infra/config/generated/builders/ci/GPU FYI Android arm Builder/properties.textpb b/infra/config/generated/builders/ci/GPU FYI Android arm Builder/properties.textpb
index 1c9949f..c01b8ac 100644
--- a/infra/config/generated/builders/ci/GPU FYI Android arm Builder/properties.textpb
+++ b/infra/config/generated/builders/ci/GPU FYI Android arm Builder/properties.textpb
@@ -1,7 +1,7 @@
 {
   "$build/reclient": {
     "instance": "rbe-chromium-trusted",
-    "jobs": 250,
+    "jobs": 500,
     "metrics_project": "chromium-reclient-metrics"
   },
   "$recipe_engine/resultdb/test_presentation": {
diff --git a/infra/config/generated/builders/ci/GPU FYI Android arm64 Builder/properties.textpb b/infra/config/generated/builders/ci/GPU FYI Android arm64 Builder/properties.textpb
index 1c9949f..c01b8ac 100644
--- a/infra/config/generated/builders/ci/GPU FYI Android arm64 Builder/properties.textpb
+++ b/infra/config/generated/builders/ci/GPU FYI Android arm64 Builder/properties.textpb
@@ -1,7 +1,7 @@
 {
   "$build/reclient": {
     "instance": "rbe-chromium-trusted",
-    "jobs": 250,
+    "jobs": 500,
     "metrics_project": "chromium-reclient-metrics"
   },
   "$recipe_engine/resultdb/test_presentation": {
diff --git "a/infra/config/generated/builders/ci/GPU Linux Builder \050dbg\051/properties.textpb" "b/infra/config/generated/builders/ci/GPU Linux Builder \050dbg\051/properties.textpb"
index 94f3cb4..94d4601 100644
--- "a/infra/config/generated/builders/ci/GPU Linux Builder \050dbg\051/properties.textpb"
+++ "b/infra/config/generated/builders/ci/GPU Linux Builder \050dbg\051/properties.textpb"
@@ -1,9 +1,8 @@
 {
-  "$build/goma": {
-    "enable_ats": true,
-    "rpc_extra_params": "?prod",
-    "server_host": "goma.chromium.org",
-    "use_luci_auth": true
+  "$build/reclient": {
+    "instance": "rbe-chromium-trusted",
+    "jobs": 250,
+    "metrics_project": "chromium-reclient-metrics"
   },
   "$recipe_engine/resultdb/test_presentation": {
     "column_keys": [],
diff --git "a/infra/config/generated/builders/ci/Linux CFI \050reclient shadow\051/properties.textpb" "b/infra/config/generated/builders/ci/Linux CFI \050reclient shadow\051/properties.textpb"
index dabc646..052ac08 100644
--- "a/infra/config/generated/builders/ci/Linux CFI \050reclient shadow\051/properties.textpb"
+++ "b/infra/config/generated/builders/ci/Linux CFI \050reclient shadow\051/properties.textpb"
@@ -3,7 +3,10 @@
     "ensure_verified": true,
     "instance": "rbe-chromium-trusted",
     "jobs": 400,
-    "metrics_project": "chromium-reclient-metrics"
+    "metrics_project": "chromium-reclient-metrics",
+    "rewrapper_env": {
+      "RBE_compare": "true"
+    }
   },
   "$recipe_engine/resultdb/test_presentation": {
     "column_keys": [],
diff --git a/infra/config/generated/builders/ci/Linux FYI GPU TSAN Release/properties.textpb b/infra/config/generated/builders/ci/Linux FYI GPU TSAN Release/properties.textpb
index def7636..1c9949f 100644
--- a/infra/config/generated/builders/ci/Linux FYI GPU TSAN Release/properties.textpb
+++ b/infra/config/generated/builders/ci/Linux FYI GPU TSAN Release/properties.textpb
@@ -1,9 +1,8 @@
 {
-  "$build/goma": {
-    "enable_ats": true,
-    "rpc_extra_params": "?prod",
-    "server_host": "goma.chromium.org",
-    "use_luci_auth": true
+  "$build/reclient": {
+    "instance": "rbe-chromium-trusted",
+    "jobs": 250,
+    "metrics_project": "chromium-reclient-metrics"
   },
   "$recipe_engine/resultdb/test_presentation": {
     "column_keys": [],
diff --git a/infra/config/generated/builders/ci/Linux Viz/properties.textpb b/infra/config/generated/builders/ci/Linux Viz/properties.textpb
index fc3bce3..b232002 100644
--- a/infra/config/generated/builders/ci/Linux Viz/properties.textpb
+++ b/infra/config/generated/builders/ci/Linux Viz/properties.textpb
@@ -1,9 +1,8 @@
 {
-  "$build/goma": {
-    "enable_ats": true,
-    "rpc_extra_params": "?prod",
-    "server_host": "goma.chromium.org",
-    "use_luci_auth": true
+  "$build/reclient": {
+    "instance": "rbe-chromium-trusted",
+    "jobs": 250,
+    "metrics_project": "chromium-reclient-metrics"
   },
   "$recipe_engine/resultdb/test_presentation": {
     "column_keys": [],
diff --git a/infra/config/generated/builders/ci/Win11 Tests x64/properties.textpb b/infra/config/generated/builders/ci/Win11 Tests x64/properties.textpb
new file mode 100644
index 0000000..ef42b767
--- /dev/null
+++ b/infra/config/generated/builders/ci/Win11 Tests x64/properties.textpb
@@ -0,0 +1,11 @@
+{
+  "$recipe_engine/resultdb/test_presentation": {
+    "column_keys": [],
+    "grouping_keys": [
+      "status",
+      "v.test_suite"
+    ]
+  },
+  "builder_group": "chromium.fyi",
+  "recipe": "chromium"
+}
\ No newline at end of file
diff --git a/infra/config/generated/builders/try/win11-x64-fyi-rel/properties.textpb b/infra/config/generated/builders/try/win11-x64-fyi-rel/properties.textpb
new file mode 100644
index 0000000..b8b797a
--- /dev/null
+++ b/infra/config/generated/builders/try/win11-x64-fyi-rel/properties.textpb
@@ -0,0 +1,24 @@
+{
+  "$build/code_coverage": {
+    "coverage_test_types": [
+      "unit",
+      "overall"
+    ],
+    "use_clang_coverage": true
+  },
+  "$build/goma": {
+    "enable_ats": false,
+    "rpc_extra_params": "?prod",
+    "server_host": "goma.chromium.org",
+    "use_luci_auth": true
+  },
+  "$recipe_engine/resultdb/test_presentation": {
+    "column_keys": [],
+    "grouping_keys": [
+      "status",
+      "v.test_suite"
+    ]
+  },
+  "builder_group": "tryserver.chromium.win",
+  "recipe": "chromium_trybot"
+}
\ No newline at end of file
diff --git a/infra/config/generated/luci/commit-queue.cfg b/infra/config/generated/luci/commit-queue.cfg
index 235db8a4..fe30bb16 100644
--- a/infra/config/generated/luci/commit-queue.cfg
+++ b/infra/config/generated/luci/commit-queue.cfg
@@ -627,10 +627,6 @@
         location_regexp: ".+/[+]/infra/config/.+"
       }
       builders {
-        name: "chromium/try/cast-binary-size"
-        includable_only: true
-      }
-      builders {
         name: "chromium/try/cast_shell_android"
         location_regexp: ".*"
         location_regexp_exclude: ".+/[+]/docs/.+"
@@ -1910,6 +1906,10 @@
         includable_only: true
       }
       builders {
+        name: "chromium/try/win11-x64-fyi-rel"
+        includable_only: true
+      }
+      builders {
         name: "chromium/try/win32-official"
         includable_only: true
       }
diff --git a/infra/config/generated/luci/cr-buildbucket.cfg b/infra/config/generated/luci/cr-buildbucket.cfg
index a2381400d..1e2ac93 100644
--- a/infra/config/generated/luci/cr-buildbucket.cfg
+++ b/infra/config/generated/luci/cr-buildbucket.cfg
@@ -22652,6 +22652,89 @@
       }
     }
     builders {
+      name: "Win11 Tests x64"
+      swarming_host: "chromium-swarm.appspot.com"
+      dimensions: "builderless:1"
+      dimensions: "cores:8"
+      dimensions: "cpu:x86-64"
+      dimensions: "os:Windows-10"
+      dimensions: "pool:luci.chromium.ci"
+      dimensions: "ssd:0"
+      exe {
+        cipd_package: "infra/chromium/bootstrapper/${platform}"
+        cipd_version: "latest"
+        cmd: "bootstrapper"
+      }
+      properties:
+        '{'
+        '  "$bootstrap/exe": {'
+        '    "exe": {'
+        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
+        '      "cipd_version": "refs/heads/main",'
+        '      "cmd": ['
+        '        "luciexe"'
+        '      ]'
+        '    }'
+        '  },'
+        '  "$bootstrap/properties": {'
+        '    "properties_file": "infra/config/generated/builders/ci/Win11 Tests x64/properties.textpb",'
+        '    "top_level_project": {'
+        '      "ref": "refs/heads/main",'
+        '      "repo": {'
+        '        "host": "chromium.googlesource.com",'
+        '        "project": "chromium/src"'
+        '      }'
+        '    }'
+        '  },'
+        '  "builder_group": "chromium.fyi",'
+        '  "led_builder_is_bootstrapped": true,'
+        '  "recipe": "chromium"'
+        '}'
+      execution_timeout_secs: 36000
+      build_numbers: YES
+      service_account: "chromium-ci-builder@chops-service-accounts.iam.gserviceaccount.com"
+      experiments {
+        key: "luci.recipes.use_python3"
+        value: 100
+      }
+      experiments {
+        key: "luci.use_realms"
+        value: 100
+      }
+      resultdb {
+        enable: true
+        bq_exports {
+          project: "chrome-luci-data"
+          dataset: "chromium"
+          table: "ci_test_results"
+          test_results {}
+        }
+        bq_exports {
+          project: "chrome-luci-data"
+          dataset: "chromium"
+          table: "gpu_ci_test_results"
+          test_results {
+            predicate {
+              test_id_regexp: "ninja://(chrome/test:|content/test:fuchsia_)telemetry_gpu_integration_test[^/]*/.+"
+            }
+          }
+        }
+        bq_exports {
+          project: "chrome-luci-data"
+          dataset: "chromium"
+          table: "blink_web_tests_ci_test_results"
+          test_results {
+            predicate {
+              test_id_regexp: "ninja://[^/]*blink_web_tests/.+"
+            }
+          }
+        }
+        history_options {
+          use_invocation_timestamp: true
+        }
+      }
+    }
+    builders {
       name: "Win7 (32) Tests"
       swarming_host: "chromium-swarm.appspot.com"
       dimensions: "builderless:1"
@@ -23700,6 +23783,10 @@
       build_numbers: YES
       service_account: "chromium-cipd-builder@chops-service-accounts.iam.gserviceaccount.com"
       experiments {
+        key: "luci.recipes.use_python3"
+        value: 100
+      }
+      experiments {
         key: "luci.use_realms"
         value: 100
       }
@@ -54685,97 +54772,6 @@
       }
     }
     builders {
-      name: "cast-binary-size"
-      swarming_host: "chromium-swarm.appspot.com"
-      dimensions: "builderless:1"
-      dimensions: "cores:8"
-      dimensions: "cpu:x86-64"
-      dimensions: "os:Ubuntu-18.04"
-      dimensions: "pool:luci.chromium.try"
-      dimensions: "ssd:0"
-      exe {
-        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
-        cipd_version: "refs/heads/main"
-        cmd: "luciexe"
-      }
-      properties:
-        '{'
-        '  "$build/binary_size": {'
-        '    "analyze_targets": ['
-        '      "//chromecast:cast_shell"'
-        '    ],'
-        '    "compile_targets": ['
-        '      "cast_shell"'
-        '    ]'
-        '  },'
-        '  "$build/goma": {'
-        '    "enable_ats": true,'
-        '    "rpc_extra_params": "?prod",'
-        '    "server_host": "goma.chromium.org",'
-        '    "use_luci_auth": true'
-        '  },'
-        '  "$recipe_engine/resultdb/test_presentation": {'
-        '    "column_keys": [],'
-        '    "grouping_keys": ['
-        '      "status",'
-        '      "v.test_suite"'
-        '    ]'
-        '  },'
-        '  "builder_group": "tryserver.chromium.linux",'
-        '  "recipe": "binary_size_cast_trybot"'
-        '}'
-      execution_timeout_secs: 14400
-      expiration_secs: 7200
-      grace_period {
-        seconds: 120
-      }
-      caches {
-        name: "win_toolchain"
-        path: "win_toolchain"
-      }
-      build_numbers: YES
-      service_account: "chromium-try-builder@chops-service-accounts.iam.gserviceaccount.com"
-      task_template_canary_percentage {
-        value: 5
-      }
-      experiments {
-        key: "luci.use_realms"
-        value: 100
-      }
-      resultdb {
-        enable: true
-        bq_exports {
-          project: "chrome-luci-data"
-          dataset: "chromium"
-          table: "try_test_results"
-          test_results {}
-        }
-        bq_exports {
-          project: "chrome-luci-data"
-          dataset: "chromium"
-          table: "gpu_try_test_results"
-          test_results {
-            predicate {
-              test_id_regexp: "ninja://(chrome/test:|content/test:fuchsia_)telemetry_gpu_integration_test[^/]*/.+"
-            }
-          }
-        }
-        bq_exports {
-          project: "chrome-luci-data"
-          dataset: "chromium"
-          table: "blink_web_tests_try_test_results"
-          test_results {
-            predicate {
-              test_id_regexp: "ninja://[^/]*blink_web_tests/.+"
-            }
-          }
-        }
-        history_options {
-          use_invocation_timestamp: true
-        }
-      }
-    }
-    builders {
       name: "cast_shell_android"
       swarming_host: "chromium-swarm.appspot.com"
       dimensions: "builder:cast_shell_android"
@@ -68514,7 +68510,7 @@
       }
       experiments {
         key: "luci.recipes.use_python3"
-        value: 25
+        value: 100
       }
       experiments {
         key: "luci.use_realms"
@@ -77238,7 +77234,7 @@
       }
       experiments {
         key: "luci.recipes.use_python3"
-        value: 25
+        value: 100
       }
       experiments {
         key: "luci.use_realms"
@@ -78810,6 +78806,100 @@
       }
     }
     builders {
+      name: "win11-x64-fyi-rel"
+      swarming_host: "chromium-swarm.appspot.com"
+      dimensions: "builderless:1"
+      dimensions: "cores:8"
+      dimensions: "cpu:x86-64"
+      dimensions: "os:Windows-10"
+      dimensions: "pool:luci.chromium.try"
+      dimensions: "ssd:0"
+      exe {
+        cipd_package: "infra/chromium/bootstrapper/${platform}"
+        cipd_version: "latest"
+        cmd: "bootstrapper"
+      }
+      properties:
+        '{'
+        '  "$bootstrap/exe": {'
+        '    "exe": {'
+        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
+        '      "cipd_version": "refs/heads/main",'
+        '      "cmd": ['
+        '        "luciexe"'
+        '      ]'
+        '    }'
+        '  },'
+        '  "$bootstrap/properties": {'
+        '    "properties_file": "infra/config/generated/builders/try/win11-x64-fyi-rel/properties.textpb",'
+        '    "top_level_project": {'
+        '      "ref": "refs/heads/main",'
+        '      "repo": {'
+        '        "host": "chromium.googlesource.com",'
+        '        "project": "chromium/src"'
+        '      }'
+        '    }'
+        '  },'
+        '  "builder_group": "tryserver.chromium.win",'
+        '  "led_builder_is_bootstrapped": true,'
+        '  "recipe": "chromium_trybot"'
+        '}'
+      execution_timeout_secs: 14400
+      expiration_secs: 7200
+      grace_period {
+        seconds: 120
+      }
+      caches {
+        name: "win_toolchain"
+        path: "win_toolchain"
+      }
+      build_numbers: YES
+      service_account: "chromium-try-builder@chops-service-accounts.iam.gserviceaccount.com"
+      task_template_canary_percentage {
+        value: 5
+      }
+      experiments {
+        key: "luci.recipes.use_python3"
+        value: 100
+      }
+      experiments {
+        key: "luci.use_realms"
+        value: 100
+      }
+      resultdb {
+        enable: true
+        bq_exports {
+          project: "chrome-luci-data"
+          dataset: "chromium"
+          table: "try_test_results"
+          test_results {}
+        }
+        bq_exports {
+          project: "chrome-luci-data"
+          dataset: "chromium"
+          table: "gpu_try_test_results"
+          test_results {
+            predicate {
+              test_id_regexp: "ninja://(chrome/test:|content/test:fuchsia_)telemetry_gpu_integration_test[^/]*/.+"
+            }
+          }
+        }
+        bq_exports {
+          project: "chrome-luci-data"
+          dataset: "chromium"
+          table: "blink_web_tests_try_test_results"
+          test_results {
+            predicate {
+              test_id_regexp: "ninja://[^/]*blink_web_tests/.+"
+            }
+          }
+        }
+        history_options {
+          use_invocation_timestamp: true
+        }
+      }
+    }
+    builders {
       name: "win32-official"
       swarming_host: "chromium-swarm.appspot.com"
       dimensions: "builderless:1"
@@ -80472,33 +80562,26 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Android Builder/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80523,33 +80606,26 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Android Builder (dbg)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80574,33 +80650,26 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Android Builder ARM64 (dbg)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80625,33 +80694,20 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Android Tests (dbg) (M Nexus5X)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80676,33 +80732,20 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Android Tests (dbg) (N Nexus5X)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80727,33 +80770,26 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Linux Builder/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80778,33 +80814,26 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Linux Builder (dbg)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80829,33 +80858,20 @@
       dimensions: "os:Ubuntu-16.04|Ubuntu-18.04"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Linux Tester/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80880,33 +80896,25 @@
       dimensions: "os:Mac"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Mac Builder/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80931,33 +80939,25 @@
       dimensions: "os:Mac"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Mac Builder (dbg)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -80982,33 +80982,20 @@
       dimensions: "os:Mac"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Mac Tester/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -81033,33 +81020,26 @@
       dimensions: "os:Windows-10"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Win Builder/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -81084,33 +81064,26 @@
       dimensions: "os:Windows-10"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
+        '  "$build/goma": {'
+        '    "enable_ats": true,'
+        '    "rpc_extra_params": "?prod",'
+        '    "server_host": "goma.chromium.org",'
+        '    "use_luci_auth": true'
         '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Win Builder (dbg)/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -81135,33 +81108,20 @@
       dimensions: "os:Windows-10"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Win10 Tester/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -81186,33 +81146,20 @@
       dimensions: "os:Windows-10"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Win7 Tester/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
@@ -81237,33 +81184,20 @@
       dimensions: "os:Windows-10"
       dimensions: "pool:luci.chromium.webrtc.fyi"
       exe {
-        cipd_package: "infra/chromium/bootstrapper/${platform}"
-        cipd_version: "latest"
-        cmd: "bootstrapper"
+        cipd_package: "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build"
+        cipd_version: "refs/heads/main"
+        cmd: "luciexe"
       }
       properties:
         '{'
-        '  "$bootstrap/exe": {'
-        '    "exe": {'
-        '      "cipd_package": "infra/recipe_bundles/chromium.googlesource.com/chromium/tools/build",'
-        '      "cipd_version": "refs/heads/main",'
-        '      "cmd": ['
-        '        "luciexe"'
-        '      ]'
-        '    }'
-        '  },'
-        '  "$bootstrap/properties": {'
-        '    "properties_file": "infra/config/generated/builders/webrtc.fyi/WebRTC Chromium FYI Win8 Tester/properties.textpb",'
-        '    "top_level_project": {'
-        '      "ref": "refs/heads/main",'
-        '      "repo": {'
-        '        "host": "chromium.googlesource.com",'
-        '        "project": "chromium/src"'
-        '      }'
-        '    }'
+        '  "$recipe_engine/resultdb/test_presentation": {'
+        '    "column_keys": [],'
+        '    "grouping_keys": ['
+        '      "status",'
+        '      "v.test_suite"'
+        '    ]'
         '  },'
         '  "builder_group": "chromium.webrtc.fyi",'
-        '  "led_builder_is_bootstrapped": true,'
         '  "recipe": "chromium"'
         '}'
       execution_timeout_secs: 7200
diff --git a/infra/config/generated/luci/luci-milo.cfg b/infra/config/generated/luci/luci-milo.cfg
index 2618c5e..3cebf77 100644
--- a/infra/config/generated/luci/luci-milo.cfg
+++ b/infra/config/generated/luci/luci-milo.cfg
@@ -6448,6 +6448,10 @@
     category: "win10"
   }
   builders {
+    name: "buildbucket/luci.chromium.ci/Win11 Tests x64"
+    category: "win11"
+  }
+  builders {
     name: "buildbucket/luci.chromium.ci/win32-arm64-rel"
     category: "win32|arm64"
   }
@@ -14130,9 +14134,6 @@
     name: "buildbucket/luci.chromium.try/branch-config-verifier"
   }
   builders {
-    name: "buildbucket/luci.chromium.try/cast-binary-size"
-  }
-  builders {
     name: "buildbucket/luci.chromium.try/cast_shell_android"
   }
   builders {
@@ -14919,6 +14920,9 @@
     name: "buildbucket/luci.chromium.try/win10_chromium_x64_rel_ng_rts"
   }
   builders {
+    name: "buildbucket/luci.chromium.try/win11-x64-fyi-rel"
+  }
+  builders {
     name: "buildbucket/luci.chromium.try/win32-official"
   }
   builders {
@@ -15452,9 +15456,6 @@
   id: "tryserver.chromium.linux"
   name: "tryserver.chromium.linux"
   builders {
-    name: "buildbucket/luci.chromium.try/cast-binary-size"
-  }
-  builders {
     name: "buildbucket/luci.chromium.try/cast_shell_audio_linux"
   }
   builders {
@@ -16061,6 +16062,9 @@
     name: "buildbucket/luci.chromium.try/win10_chromium_x64_rel_ng_rts"
   }
   builders {
+    name: "buildbucket/luci.chromium.try/win11-x64-fyi-rel"
+  }
+  builders {
     name: "buildbucket/luci.chromium.try/win7-rel"
   }
   builders {
diff --git a/infra/config/generated/luci/luci-scheduler.cfg b/infra/config/generated/luci/luci-scheduler.cfg
index 409ebba..d5a4f9f90 100644
--- a/infra/config/generated/luci/luci-scheduler.cfg
+++ b/infra/config/generated/luci/luci-scheduler.cfg
@@ -3903,6 +3903,20 @@
   }
 }
 job {
+  id: "Win11 Tests x64"
+  realm: "ci"
+  acls {
+    role: TRIGGERER
+    granted_to: "chromium-ci-builder@chops-service-accounts.iam.gserviceaccount.com"
+  }
+  acl_sets: "ci"
+  buildbucket {
+    server: "cr-buildbucket.appspot.com"
+    bucket: "luci.chromium.ci"
+    builder: "Win11 Tests x64"
+  }
+}
+job {
   id: "Win7 (32) Tests"
   realm: "ci"
   acls {
diff --git a/infra/config/generators/scheduler-noop-jobs.star b/infra/config/generators/scheduler-noop-jobs.star
index 4bee49e..7e7f8ed 100644
--- a/infra/config/generators/scheduler-noop-jobs.star
+++ b/infra/config/generators/scheduler-noop-jobs.star
@@ -23,6 +23,11 @@
     # the branches
     "mac-osxbeta-rel": branches.DESKTOP_EXTENDED_STABLE_MILESTONE,
 
+    # This tester is triggered by 'Win x64 Builder', but it is an FYI builder
+    # and not mirrored by any branched try builders, so we do not need to run it
+    # on the branches
+    "Win11 Tests x64": branches.STANDARD_MILESTONE,
+
     # These Android testers are triggered by 'Android arm Builder (dbg)', but we
     # don't have sufficient capacity of devices with older Android versions, so
     # we do not run them on the branches
diff --git a/infra/config/recipes.star b/infra/config/recipes.star
index 9abf88c0..53dbab08 100644
--- a/infra/config/recipes.star
+++ b/infra/config/recipes.star
@@ -81,6 +81,7 @@
 
 build_recipe(
     name = "recipe:android/androidx_packager",
+    use_python3 = True,
 )
 
 build_recipe(
@@ -112,10 +113,6 @@
 )
 
 build_recipe(
-    name = "recipe:binary_size_cast_trybot",
-)
-
-build_recipe(
     name = "recipe:binary_size_fuchsia_trybot",
 )
 
@@ -176,9 +173,7 @@
 
 build_recipe(
     name = "recipe:chromium_libfuzzer_trybot",
-    experiments = {
-        "luci.recipes.use_python3": 25,
-    },
+    use_python3 = True,
 )
 
 build_recipe(
diff --git a/infra/config/subprojects/chromium/ci/chromium.fyi.star b/infra/config/subprojects/chromium/ci/chromium.fyi.star
index d6023cdf..530c822 100644
--- a/infra/config/subprojects/chromium/ci/chromium.fyi.star
+++ b/infra/config/subprojects/chromium/ci/chromium.fyi.star
@@ -38,6 +38,7 @@
             "network",
             "viz",
             "win10",
+            "win11",
             "win32",
             "paeverywhere",
             "backuprefptr",
@@ -86,7 +87,10 @@
     console_view_entry = consoles.console_view_entry(
         category = "viz",
     ),
+    goma_backend = None,
     os = os.LINUX_BIONIC_SWITCH_TO_DEFAULT,
+    reclient_jobs = rbe_jobs.DEFAULT,
+    reclient_instance = rbe_instance.DEFAULT,
 )
 
 ci.builder(
@@ -646,6 +650,7 @@
     reclient_jobs = 400,
     reclient_instance = rbe_instance.DEFAULT,
     reclient_ensure_verified = True,
+    reclient_rewrapper_env = {"RBE_compare": "true"},
 )
 # End - Reclient migration, phase 2, block 1 shadow builders
 
@@ -1143,6 +1148,18 @@
 )
 
 ci.builder(
+    name = "Win11 Tests x64",
+    builderless = True,
+    console_view_entry = consoles.console_view_entry(
+        category = "win11",
+    ),
+    goma_backend = None,
+    main_console_view = None,
+    os = os.WINDOWS_10,
+    triggered_by = ["ci/Win x64 Builder"],
+)
+
+ci.builder(
     name = "win32-arm64-rel",
     console_view_entry = consoles.console_view_entry(
         category = "win32|arm64",
diff --git a/infra/config/subprojects/chromium/ci/chromium.gpu.fyi.star b/infra/config/subprojects/chromium/ci/chromium.gpu.fyi.star
index 89fa9f4..a07efb0 100644
--- a/infra/config/subprojects/chromium/ci/chromium.gpu.fyi.star
+++ b/infra/config/subprojects/chromium/ci/chromium.gpu.fyi.star
@@ -153,7 +153,7 @@
         short_name = "arm",
     ),
     goma_backend = None,
-    reclient_jobs = rbe_jobs.DEFAULT,
+    reclient_jobs = rbe_jobs.HIGH_JOBS_FOR_CI,
     reclient_instance = rbe_instance.DEFAULT,
 )
 
@@ -164,7 +164,7 @@
         short_name = "arm64",
     ),
     goma_backend = None,
-    reclient_jobs = rbe_jobs.DEFAULT,
+    reclient_jobs = rbe_jobs.HIGH_JOBS_FOR_CI,
     reclient_instance = rbe_instance.DEFAULT,
 )
 
@@ -204,6 +204,9 @@
         category = "Linux",
         short_name = "tsn",
     ),
+    goma_backend = None,
+    reclient_jobs = rbe_jobs.DEFAULT,
+    reclient_instance = rbe_instance.DEFAULT,
 )
 
 # Builder + tester.
diff --git a/infra/config/subprojects/chromium/ci/chromium.gpu.star b/infra/config/subprojects/chromium/ci/chromium.gpu.star
index 7863d35..06cd6c8 100644
--- a/infra/config/subprojects/chromium/ci/chromium.gpu.star
+++ b/infra/config/subprojects/chromium/ci/chromium.gpu.star
@@ -56,6 +56,9 @@
         category = "Linux",
     ),
     tree_closing = False,
+    goma_backend = None,
+    reclient_jobs = rbe_jobs.DEFAULT,
+    reclient_instance = rbe_instance.DEFAULT,
 )
 
 ci.gpu.mac_builder(
diff --git a/infra/config/subprojects/chromium/try/tryserver.chromium.linux.star b/infra/config/subprojects/chromium/try/tryserver.chromium.linux.star
index 2bd0b52..86606fcb 100644
--- a/infra/config/subprojects/chromium/try/tryserver.chromium.linux.star
+++ b/infra/config/subprojects/chromium/try/tryserver.chromium.linux.star
@@ -61,22 +61,6 @@
 )
 
 try_.builder(
-    name = "cast-binary-size",
-    builderless = True,
-    executable = "recipe:binary_size_cast_trybot",
-    properties = {
-        "$build/binary_size": {
-            "analyze_targets": [
-                "//chromecast:cast_shell",
-            ],
-            "compile_targets": [
-                "cast_shell",
-            ],
-        },
-    },
-)
-
-try_.builder(
     name = "fuchsia-binary-size",
     branch_selector = branches.STANDARD_MILESTONE,
     builderless = True,
diff --git a/infra/config/subprojects/chromium/try/tryserver.chromium.win.star b/infra/config/subprojects/chromium/try/tryserver.chromium.win.star
index 6f7b91a..118156e 100644
--- a/infra/config/subprojects/chromium/try/tryserver.chromium.win.star
+++ b/infra/config/subprojects/chromium/try/tryserver.chromium.win.star
@@ -106,6 +106,14 @@
 )
 
 try_.builder(
+    name = "win11-x64-fyi-rel",
+    builderless = True,
+    use_clang_coverage = True,
+    coverage_test_types = ["unit", "overall"],
+    os = os.WINDOWS_10,
+)
+
+try_.builder(
     name = "win10_chromium_inverse_fieldtrials_x64_fyi_rel_ng",
     os = os.WINDOWS_10,
 )
diff --git a/infra/config/subprojects/webrtc/webrtc.fyi.star b/infra/config/subprojects/webrtc/webrtc.fyi.star
index 8845f563..66b30e2a 100644
--- a/infra/config/subprojects/webrtc/webrtc.fyi.star
+++ b/infra/config/subprojects/webrtc/webrtc.fyi.star
@@ -2,7 +2,7 @@
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
-load("//lib/builders.star", "builder", "cpu", "defaults", "goma", "os", "xcode")
+load("//lib/builders.star", "cpu", "defaults", "goma", "os", "xcode", base_builder = "builder")
 
 luci.bucket(
     name = "webrtc.fyi",
@@ -33,6 +33,10 @@
     refs = ["refs/heads/main"],
 )
 
+def builder(**kwargs):
+    kwargs.setdefault("bootstrap", False)
+    return base_builder(**kwargs)
+
 defaults.bucket.set("webrtc.fyi")
 defaults.builder_group.set("chromium.webrtc.fyi")
 defaults.builderless.set(None)
diff --git a/infra/inclusive_language_presubmit_exempt_dirs.txt b/infra/inclusive_language_presubmit_exempt_dirs.txt
index 7e34076..e41e9de 100644
--- a/infra/inclusive_language_presubmit_exempt_dirs.txt
+++ b/infra/inclusive_language_presubmit_exempt_dirs.txt
@@ -734,15 +734,30 @@
 third_party/tensorflow-text/src/tensorflow_text/python/metrics 1 1
 third_party/tensorflow-text/src/tensorflow_text/python/ops/test_data 1 1
 third_party/test_fonts 15 1
+third_party/tflite_support/patches 8 2
+third_party/tflite_support/src 1 1
+third_party/tflite_support/src/tensorflow_lite_support/acceleration 3 1
+third_party/tflite_support/src/tensorflow_lite_support/c 2 2
+third_party/tflite_support/src/tensorflow_lite_support/cc/port/default 1 1
 third_party/tflite_support/src/tensorflow_lite_support/cc/task 4 1
-third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision 9 4
-third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto 4 2
+third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio 1 1
+third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto 2 1
+third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision 13 5
+third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto 12 4
+third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text 5 3
 third_party/tflite_support/src/tensorflow_lite_support/codegen 1 1
 third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece 2 1
 third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/testdata 1 1
 third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python 2 1
-third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop 4 2
+third_party/tflite_support/src/tensorflow_lite_support/custom_ops/testdata 5 1
+third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop 8 3
+third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python 12 3
+third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops 1 1
+third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier 1 1
+third_party/tflite_support/src/tensorflow_lite_support/metadata 5 1
 third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata 3 1
+third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier 2 1
+third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image 1 1
 third_party/tlslite 1 1
 third_party/tlslite/patches 7 3
 third_party/tlslite/tlslite 3 2
diff --git a/ios/chrome/browser/policy/reporting/report_scheduler_ios_unittest.mm b/ios/chrome/browser/policy/reporting/report_scheduler_ios_unittest.mm
index 636d5d4..edc6e6a 100644
--- a/ios/chrome/browser/policy/reporting/report_scheduler_ios_unittest.mm
+++ b/ios/chrome/browser/policy/reporting/report_scheduler_ios_unittest.mm
@@ -72,7 +72,8 @@
   MockReportUploader& operator=(const MockReportUploader&) = delete;
   ~MockReportUploader() override = default;
 
-  MOCK_METHOD2(SetRequestAndUpload, void(ReportRequestQueue, ReportCallback));
+  MOCK_METHOD3(SetRequestAndUpload,
+               void(ReportType, ReportRequestQueue, ReportCallback));
 };
 
 class ReportSchedulerIOSTest : public PlatformTest {
@@ -193,8 +194,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -214,8 +215,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kTransientError));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kTransientError));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -235,8 +236,8 @@
   EXPECT_CALL_SetupRegistrationWithSetDMToken();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kPersistentError));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kPersistentError));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -261,7 +262,7 @@
   EXPECT_CALL_SetupRegistrationWithSetDMToken();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(0)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _)).Times(0);
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _, _)).Times(0);
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -289,8 +290,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -309,8 +310,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
@@ -346,8 +347,8 @@
   EXPECT_CALL_SetupRegistration();
   EXPECT_CALL(*generator_, OnGenerate(ReportType::kFull, _))
       .WillOnce(WithArgs<1>(ScheduleGeneratorCallback(1)));
-  EXPECT_CALL(*uploader_, SetRequestAndUpload(_, _))
-      .WillOnce(RunOnceCallback<1>(ReportUploader::kSuccess));
+  EXPECT_CALL(*uploader_, SetRequestAndUpload(ReportType::kFull, _, _))
+      .WillOnce(RunOnceCallback<2>(ReportUploader::kSuccess));
 
   CreateScheduler();
   EXPECT_TRUE(scheduler_->IsNextReportScheduledForTesting());
diff --git a/ios/chrome/browser/providers/BUILD.gn b/ios/chrome/browser/providers/BUILD.gn
index de7ee7f..0c486d0 100644
--- a/ios/chrome/browser/providers/BUILD.gn
+++ b/ios/chrome/browser/providers/BUILD.gn
@@ -15,7 +15,6 @@
     "//ios/chrome/browser/voice:voice_search_language",
     "//ios/chrome/browser/web:feature_flags",
     "//ios/public/provider/chrome/browser",
-    "//ios/public/provider/chrome/browser:font_size_java_script_feature",
     "//ios/public/provider/chrome/browser/discover_feed",
     "//ios/public/provider/chrome/browser/follow",
     "//ios/public/provider/chrome/browser/signin",
diff --git a/ios/chrome/browser/providers/text_zoom/BUILD.gn b/ios/chrome/browser/providers/text_zoom/BUILD.gn
index efe34d2..393de26 100644
--- a/ios/chrome/browser/providers/text_zoom/BUILD.gn
+++ b/ios/chrome/browser/providers/text_zoom/BUILD.gn
@@ -7,7 +7,7 @@
   sources = [ "chromium_text_zoom.mm" ]
   deps = [
     "//ios/chrome/browser/web:feature_flags",
-    "//ios/public/provider/chrome/browser:font_size_java_script_feature",
+    "//ios/chrome/browser/web/font_size",
     "//ios/public/provider/chrome/browser/text_zoom:text_zoom_api",
     "//ui/base",
   ]
diff --git a/ios/chrome/browser/providers/text_zoom/chromium_text_zoom.mm b/ios/chrome/browser/providers/text_zoom/chromium_text_zoom.mm
index 68c532a..b108ef4 100644
--- a/ios/chrome/browser/providers/text_zoom/chromium_text_zoom.mm
+++ b/ios/chrome/browser/providers/text_zoom/chromium_text_zoom.mm
@@ -3,7 +3,7 @@
 // found in the LICENSE file.
 
 #include "ios/chrome/browser/web/features.h"
-#import "ios/public/provider/chrome/browser/font_size_java_script_feature.h"
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
 #import "ios/public/provider/chrome/browser/text_zoom/text_zoom_api.h"
 #include "ui/base/device_form_factor.h"
 
diff --git a/ios/chrome/browser/ssl/ios_captive_portal_blocking_page.mm b/ios/chrome/browser/ssl/ios_captive_portal_blocking_page.mm
index 5333f0ea..f6511ec 100644
--- a/ios/chrome/browser/ssl/ios_captive_portal_blocking_page.mm
+++ b/ios/chrome/browser/ssl/ios_captive_portal_blocking_page.mm
@@ -44,6 +44,8 @@
   load_time_data->SetStringKey("iconClass", "icon-offline");
   load_time_data->SetStringKey("type", "CAPTIVE_PORTAL");
   load_time_data->SetBoolKey("overridable", false);
+  load_time_data->SetBoolKey("hide_primary_button", false);
+
   load_time_data->SetStringKey(
       "primaryButtonText",
       l10n_util::GetStringUTF16(IDS_CAPTIVE_PORTAL_BUTTON_OPEN_LOGIN_PAGE));
diff --git a/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.h b/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.h
index 689603d..82ff8af 100644
--- a/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.h
+++ b/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.h
@@ -18,9 +18,6 @@
 class ManagedBookmarkService;
 }  // namespace bookmarks
 class Browser;
-namespace base {
-class ScopedTempDir;
-}  // namespace base
 class TestChromeBrowserState;
 
 // Provides common bookmark testing infrastructure.
@@ -39,11 +36,6 @@
       NSString* title);
   void ChangeTitle(NSString* title, const bookmarks::BookmarkNode* node);
 
-  // A state directory that outlives |task_environment_| is needed because
-  // CreateHistoryService/CreateBookmarkModel use the directory to host
-  // databases. See https://crbug.com/546640 for more details.
-  std::unique_ptr<base::ScopedTempDir> state_dir_;
-
   web::WebTaskEnvironment task_environment_;
   IOSChromeScopedTestingLocalState local_state_;
   std::unique_ptr<Browser> browser_;
diff --git a/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.mm b/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.mm
index 575fb620..bc93173 100644
--- a/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.mm
+++ b/ios/chrome/browser/ui/bookmarks/bookmark_ios_unittest.mm
@@ -33,9 +33,6 @@
       AuthenticationServiceFactory::GetInstance(),
       base::BindRepeating(
           &AuthenticationServiceFake::CreateAuthenticationService));
-  state_dir_ = std::make_unique<base::ScopedTempDir>();
-  ASSERT_TRUE(state_dir_->CreateUniqueTempDir());
-  test_cbs_builder.SetPath(state_dir_->GetPath());
 
   chrome_browser_state_ = test_cbs_builder.Build();
   chrome_browser_state_->CreateBookmarkModel(true);
diff --git a/ios/chrome/browser/ui/recent_tabs/recent_tabs_menu_helper.mm b/ios/chrome/browser/ui/recent_tabs/recent_tabs_menu_helper.mm
index b77623b..03b3790 100644
--- a/ios/chrome/browser/ui/recent_tabs/recent_tabs_menu_helper.mm
+++ b/ios/chrome/browser/ui/recent_tabs/recent_tabs_menu_helper.mm
@@ -7,6 +7,7 @@
 #import "base/ios/ios_util.h"
 #include "base/metrics/histogram_functions.h"
 #include "base/metrics/histogram_macros.h"
+#import "ios/chrome/browser/net/crurl.h"
 #import "ios/chrome/browser/ui/coordinators/chrome_coordinator.h"
 #import "ios/chrome/browser/ui/menu/browser_action_factory.h"
 #import "ios/chrome/browser/ui/menu/menu_histograms.h"
@@ -73,10 +74,14 @@
     NSMutableArray<UIMenuElement*>* menuElements =
         [[NSMutableArray alloc] init];
 
+    GURL gurl;
+    if (item.URL) {
+      gurl = item.URL.gurl;
+    }
     [menuElements
         addObject:
             [actionFactory
-                actionToOpenInNewTabWithURL:item.URL
+                actionToOpenInNewTabWithURL:gurl
                                  completion:^{
                                    [weakSelf.recentTabsPresentationDelegate
                                            showActiveRegularTabFromRecentTabs];
@@ -85,16 +90,16 @@
     if (base::ios::IsMultipleScenesSupported()) {
       [menuElements
           addObject:[actionFactory
-                        actionToOpenInNewWindowWithURL:item.URL
+                        actionToOpenInNewWindowWithURL:gurl
                                         activityOrigin:
                                             WindowActivityRecentTabsOrigin]];
     }
 
-    [menuElements addObject:[actionFactory actionToCopyURL:item.URL]];
+    [menuElements addObject:[actionFactory actionToCopyURL:gurl]];
 
     [menuElements addObject:[actionFactory actionToShareWithBlock:^{
                     [weakSelf.contextMenuDelegate
-                        shareURL:item.URL
+                        shareURL:gurl
                            title:item.title
                         scenario:ActivityScenario::RecentTabsEntry
                         fromView:view];
diff --git a/ios/chrome/browser/ui/recent_tabs/recent_tabs_table_view_controller.mm b/ios/chrome/browser/ui/recent_tabs/recent_tabs_table_view_controller.mm
index 44de30c6..2925cdc5 100644
--- a/ios/chrome/browser/ui/recent_tabs/recent_tabs_table_view_controller.mm
+++ b/ios/chrome/browser/ui/recent_tabs/recent_tabs_table_view_controller.mm
@@ -358,7 +358,8 @@
     TableViewURLItem* recentlyClosedTab =
         [[TableViewURLItem alloc] initWithType:ItemTypeRecentlyClosed];
     recentlyClosedTab.title = base::SysUTF16ToNSString(navigationEntry.title());
-    recentlyClosedTab.URL = navigationEntry.virtual_url();
+    recentlyClosedTab.URL =
+        [[CrURL alloc] initWithGURL:navigationEntry.virtual_url()];
     [self.tableViewModel addItem:recentlyClosedTab
          toSectionWithIdentifier:SectionIdentifierRecentlyClosedTabs];
   }
@@ -437,7 +438,7 @@
     TableViewURLItem* sessionTabItem =
         [[TableViewURLItem alloc] initWithType:ItemTypeSessionTabData];
     sessionTabItem.title = title;
-    sessionTabItem.URL = sessionTab->virtual_url;
+    sessionTabItem.URL = [[CrURL alloc] initWithGURL:sessionTab->virtual_url];
     [model addItem:sessionTabItem
         toSectionWithIdentifier:[self sectionIdentifierForSession:session]];
   }
@@ -970,7 +971,10 @@
       TableViewItem* item = [self.tableViewModel itemAtIndexPath:indexPath];
       TableViewURLItem* URLItem =
           base::mac::ObjCCastStrict<TableViewURLItem>(item);
-      return [[URLInfo alloc] initWithURL:URLItem.URL title:URLItem.title];
+      GURL gurl;
+      if (URLItem.URL)
+        gurl = URLItem.URL.gurl;
+      return [[URLInfo alloc] initWithURL:gurl title:URLItem.title];
     }
 
     case ItemTypeRecentlyClosedHeader:
@@ -1027,9 +1031,8 @@
   TableViewURLCell* URLCell = base::mac::ObjCCastStrict<TableViewURLCell>(cell);
 
   NSString* itemIdentifier = URLItem.uniqueIdentifier;
-  CrURL* crurl = [[CrURL alloc] initWithGURL:URLItem.URL];
   [self.imageDataSource
-      faviconForURL:crurl
+      faviconForURL:URLItem.URL
          completion:^(FaviconAttributes* attributes) {
            // Only set favicon if the cell hasn't been reused.
            if ([URLCell.cellUniqueIdentifier isEqualToString:itemIdentifier]) {
diff --git a/ios/chrome/browser/ui/settings/table_cell_catalog_view_controller.mm b/ios/chrome/browser/ui/settings/table_cell_catalog_view_controller.mm
index f98be8473..ae4d0a3 100644
--- a/ios/chrome/browser/ui/settings/table_cell_catalog_view_controller.mm
+++ b/ios/chrome/browser/ui/settings/table_cell_catalog_view_controller.mm
@@ -558,35 +558,36 @@
   TableViewURLItem* item =
       [[TableViewURLItem alloc] initWithType:ItemTypeURLNoMetadata];
   item.title = @"Google Design";
-  item.URL = GURL("https://design.google.com");
+  item.URL = [[CrURL alloc] initWithGURL:GURL("https://design.google.com")];
   [model addItem:item toSectionWithIdentifier:SectionIdentifierURL];
 
   item = [[TableViewURLItem alloc] initWithType:ItemTypeURLNoMetadata];
-  item.URL = GURL("https://notitle.google.com");
+  item.URL = [[CrURL alloc] initWithGURL:GURL("https://notitle.google.com")];
   [model addItem:item toSectionWithIdentifier:SectionIdentifierURL];
 
   item = [[TableViewURLItem alloc] initWithType:ItemTypeURLWithTimestamp];
   item.title = @"Google";
-  item.URL = GURL("https://www.google.com");
+  item.URL = [[CrURL alloc] initWithGURL:GURL("https://www.google.com")];
   item.metadata = @"3:42 PM";
   [model addItem:item toSectionWithIdentifier:SectionIdentifierURL];
 
   item = [[TableViewURLItem alloc] initWithType:ItemTypeURLWithSize];
   item.title = @"World Series 2017: Houston Astros Defeat Someone Else";
-  item.URL = GURL("https://m.bbc.com");
+  item.URL = [[CrURL alloc] initWithGURL:GURL("https://m.bbc.com")];
   item.metadata = @"176 KB";
   [model addItem:item toSectionWithIdentifier:SectionIdentifierURL];
 
   item =
       [[TableViewURLItem alloc] initWithType:ItemTypeURLWithSupplementalText];
   item.title = @"Chrome | Google Blog";
-  item.URL = GURL("https://blog.google/products/chrome/");
+  item.URL =
+      [[CrURL alloc] initWithGURL:GURL("https://blog.google/products/chrome/")];
   item.supplementalURLText = @"Read 4 days ago";
   [model addItem:item toSectionWithIdentifier:SectionIdentifierURL];
 
   item = [[TableViewURLItem alloc] initWithType:ItemTypeURLWithBadgeImage];
   item.title = @"Photos - Google Photos";
-  item.URL = GURL("https://photos.google.com/");
+  item.URL = [[CrURL alloc] initWithGURL:GURL("https://photos.google.com/")];
   item.badgeImage = [UIImage imageNamed:@"table_view_cell_check_mark"];
   [model addItem:item toSectionWithIdentifier:SectionIdentifierURL];
 }
diff --git a/ios/chrome/browser/ui/table_view/cells/BUILD.gn b/ios/chrome/browser/ui/table_view/cells/BUILD.gn
index f1eda1b0..62fe2da 100644
--- a/ios/chrome/browser/ui/table_view/cells/BUILD.gn
+++ b/ios/chrome/browser/ui/table_view/cells/BUILD.gn
@@ -116,6 +116,7 @@
     ":cells_constants",
     "//base",
     "//base/test:test_support",
+    "//ios/chrome/browser/net:crurl",
     "//ios/chrome/browser/ui/icons",
     "//ios/chrome/browser/ui/table_view:styler",
     "//ios/chrome/common/ui/colors",
diff --git a/ios/chrome/browser/ui/table_view/cells/table_view_url_item.h b/ios/chrome/browser/ui/table_view/cells/table_view_url_item.h
index c54ac6e..088a7819 100644
--- a/ios/chrome/browser/ui/table_view/cells/table_view_url_item.h
+++ b/ios/chrome/browser/ui/table_view/cells/table_view_url_item.h
@@ -10,7 +10,7 @@
 #import "ios/chrome/browser/ui/table_view/cells/table_view_cell.h"
 #import "ios/chrome/browser/ui/table_view/cells/table_view_item.h"
 
-class GURL;
+@class CrURL;
 @class FaviconView;
 @class TableViewURLCellFaviconBadgeView;
 
@@ -19,8 +19,8 @@
 
 // The title of the page at |URL|.
 @property(nonatomic, readwrite, copy) NSString* title;
-// GURL from which the cell will retrieve a favicon and display the host name.
-@property(nonatomic, assign) GURL URL;
+// CrURL from which the cell will retrieve a favicon and display the host name.
+@property(nonatomic, readwrite, strong) CrURL* URL;
 // Supplemental text used to describe the URL.
 @property(nonatomic, readwrite, copy) NSString* supplementalURLText;
 // Delimiter used to separate the URL hostname and the supplemental text.
diff --git a/ios/chrome/browser/ui/table_view/cells/table_view_url_item.mm b/ios/chrome/browser/ui/table_view/cells/table_view_url_item.mm
index a3223627..9e27e6e 100644
--- a/ios/chrome/browser/ui/table_view/cells/table_view_url_item.mm
+++ b/ios/chrome/browser/ui/table_view/cells/table_view_url_item.mm
@@ -6,6 +6,7 @@
 
 #include "base/mac/foundation_util.h"
 #include "base/strings/sys_string_conversions.h"
+#import "ios/chrome/browser/net/crurl.h"
 #import "ios/chrome/browser/ui/elements/favicon_container_view.h"
 #import "ios/chrome/browser/ui/table_view/cells/table_view_cells_constants.h"
 #import "ios/chrome/browser/ui/table_view/cells/table_view_url_cell_favicon_badge_view.h"
@@ -71,21 +72,24 @@
 }
 
 - (NSString*)uniqueIdentifier {
-  return base::SysUTF8ToNSString(self.URL.host());
+  if (!self.URL)
+    return @"";
+  return base::SysUTF8ToNSString(self.URL.gurl.host());
 }
 
 #pragma mark Private
 
 // Returns the text to use when configuring a TableViewURLCell's title label.
 - (NSString*)titleLabelText {
-  if (self.title.length) {
+  if (self.title.length)
     return self.title;
-  } else if (base::SysUTF8ToNSString(self.URL.host()).length) {
-    return base::SysUTF8ToNSString(self.URL.host());
-  } else {
-    // Backup in case host returns nothing (e.g. about:blank).
-    return base::SysUTF8ToNSString(self.URL.spec());
-  }
+  if (!self.URL)
+    return @"";
+  NSString* hostname = base::SysUTF8ToNSString(self.URL.gurl.host());
+  if (hostname.length)
+    return hostname;
+  // Backup in case host returns nothing (e.g. about:blank).
+  return base::SysUTF8ToNSString(self.URL.gurl.spec());
 }
 
 // Returns the text to use when configuring a TableViewURLCell's URL label.
@@ -96,7 +100,9 @@
     return self.supplementalURLText;
 
   // Append the hostname with the supplemental text.
-  NSString* hostname = base::SysUTF8ToNSString(self.URL.host());
+  if (!self.URL)
+    return @"";
+  NSString* hostname = base::SysUTF8ToNSString(self.URL.gurl.host());
   if (self.supplementalURLText.length) {
     NSString* delimeter =
         self.supplementalURLTextDelimiter.length
diff --git a/ios/chrome/browser/ui/table_view/cells/table_view_url_item_unittest.mm b/ios/chrome/browser/ui/table_view/cells/table_view_url_item_unittest.mm
index 46c00fd..fe9056e 100644
--- a/ios/chrome/browser/ui/table_view/cells/table_view_url_item_unittest.mm
+++ b/ios/chrome/browser/ui/table_view/cells/table_view_url_item_unittest.mm
@@ -6,6 +6,7 @@
 
 #include "base/mac/foundation_util.h"
 #include "base/strings/sys_string_conversions.h"
+#import "ios/chrome/browser/net/crurl.h"
 #import "ios/chrome/browser/ui/table_view/chrome_table_view_styler.h"
 #include "net/base/mac/url_conversions.h"
 #include "testing/gtest/include/gtest/gtest.h"
@@ -30,7 +31,7 @@
 
   TableViewURLItem* item = [[TableViewURLItem alloc] initWithType:0];
   item.title = titleText;
-  item.URL = net::GURLWithNSURL([NSURL URLWithString:URLText]);
+  item.URL = [[CrURL alloc] initWithNSURL:[NSURL URLWithString:URLText]];
   item.metadata = metadataText;
 
   id cell = [[[item cellClass] alloc] init];
@@ -91,7 +92,7 @@
 
   TableViewURLItem* item = [[TableViewURLItem alloc] initWithType:0];
   item.title = kTitle;
-  item.URL = kURL;
+  item.URL = [[CrURL alloc] initWithGURL:kURL];
   item.supplementalURLText = kSupplementalURLText;
   item.supplementalURLTextDelimiter = kSupplementalURLTextDelimiter;
 
@@ -110,7 +111,7 @@
   NSString* const kSupplementalURLText = @"supplement";
 
   TableViewURLItem* item = [[TableViewURLItem alloc] initWithType:0];
-  item.URL = kURL;
+  item.URL = [[CrURL alloc] initWithGURL:kURL];
   item.supplementalURLText = kSupplementalURLText;
 
   id cell = [[[item cellClass] alloc] init];
diff --git a/ios/chrome/browser/web/BUILD.gn b/ios/chrome/browser/web/BUILD.gn
index 15be8c73..f7ae60a 100644
--- a/ios/chrome/browser/web/BUILD.gn
+++ b/ios/chrome/browser/web/BUILD.gn
@@ -245,6 +245,7 @@
     "//ios/chrome/browser/ui/reading_list:reading_list_javascript_feature",
     "//ios/chrome/browser/ui/util",
     "//ios/chrome/browser/web:feature_flags",
+    "//ios/chrome/browser/web/font_size",
     "//ios/chrome/browser/web/image_fetch",
     "//ios/chrome/browser/web/java_script_console",
     "//ios/chrome/browser/web/print",
@@ -254,7 +255,6 @@
     "//ios/components/security_interstitials/lookalikes",
     "//ios/components/webui:url_constants",
     "//ios/net",
-    "//ios/public/provider/chrome/browser:font_size_java_script_feature",
     "//ios/public/provider/chrome/browser/url_rewriters:url_rewriters_api",
     "//ios/web",
     "//ios/web/common",
diff --git a/ios/chrome/browser/web/chrome_web_client.mm b/ios/chrome/browser/web/chrome_web_client.mm
index 97acf5e..c68d57b 100644
--- a/ios/chrome/browser/web/chrome_web_client.mm
+++ b/ios/chrome/browser/web/chrome_web_client.mm
@@ -49,6 +49,7 @@
 #include "ios/chrome/browser/web/error_page_controller_bridge.h"
 #import "ios/chrome/browser/web/error_page_util.h"
 #include "ios/chrome/browser/web/features.h"
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
 #include "ios/chrome/browser/web/image_fetch/image_fetch_java_script_feature.h"
 #import "ios/chrome/browser/web/java_script_console/java_script_console_feature.h"
 #import "ios/chrome/browser/web/java_script_console/java_script_console_feature_factory.h"
@@ -62,7 +63,6 @@
 #import "ios/components/security_interstitials/lookalikes/lookalike_url_error.h"
 #include "ios/components/webui/web_ui_url_constants.h"
 #import "ios/net/protocol_handler_util.h"
-#import "ios/public/provider/chrome/browser/font_size_java_script_feature.h"
 #include "ios/public/provider/chrome/browser/url_rewriters/url_rewriters_api.h"
 #include "ios/web/common/features.h"
 #include "ios/web/common/user_agent.h"
diff --git a/ios/chrome/browser/web/font_size/BUILD.gn b/ios/chrome/browser/web/font_size/BUILD.gn
index b0493ed..f618ea8 100644
--- a/ios/chrome/browser/web/font_size/BUILD.gn
+++ b/ios/chrome/browser/web/font_size/BUILD.gn
@@ -7,6 +7,8 @@
 source_set("font_size") {
   configs += [ "//build/config/compiler:enable_arc" ]
   sources = [
+    "font_size_java_script_feature.h",
+    "font_size_java_script_feature.mm",
     "font_size_tab_helper.h",
     "font_size_tab_helper.mm",
   ]
@@ -22,10 +24,10 @@
     "//ios/chrome/browser/browser_state",
     "//ios/chrome/browser/web:feature_flags",
     "//ios/components/ui_util",
-    "//ios/public/provider/chrome/browser:font_size_java_script_feature",
     "//ios/public/provider/chrome/browser/text_zoom:text_zoom_api",
     "//services/metrics/public/cpp:ukm_builders",
   ]
+  public_deps = [ "//ios/web/public/js_messaging" ]
 }
 
 js_compile_bundle("font_size_js") {
@@ -59,7 +61,6 @@
     "//ios/chrome/browser/web:test_support",
     "//ios/chrome/test/fakes",
     "//ios/public/provider/chrome/browser",
-    "//ios/public/provider/chrome/browser:font_size_java_script_feature",
     "//ios/web/public/js_messaging",
     "//ios/web/public/test",
     "//testing/gtest",
diff --git a/ios/chrome/browser/web/font_size/font_size_java_script_feature.h b/ios/chrome/browser/web/font_size/font_size_java_script_feature.h
new file mode 100644
index 0000000..94d6d5a
--- /dev/null
+++ b/ios/chrome/browser/web/font_size/font_size_java_script_feature.h
@@ -0,0 +1,38 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef IOS_CHROME_BROWSER_WEB_FONT_SIZE_FONT_SIZE_JAVA_SCRIPT_FEATURE_H_
+#define IOS_CHROME_BROWSER_WEB_FONT_SIZE_FONT_SIZE_JAVA_SCRIPT_FEATURE_H_
+
+#include "base/no_destructor.h"
+#include "ios/web/public/js_messaging/java_script_feature.h"
+
+namespace web {
+class WebFrame;
+class WebState;
+}  // namespace web
+
+// Feature which adjusts the font size on a page.
+class FontSizeJavaScriptFeature : public web::JavaScriptFeature {
+ public:
+  static FontSizeJavaScriptFeature* GetInstance();
+
+  // Adjusts the font size in all frames of |web_state| by |size| percentage.
+  void AdjustFontSize(web::WebState* web_state, int size);
+
+  // Adjusts the font size in |web_frame| by |size| percentage.
+  void AdjustFontSize(web::WebFrame* web_frame, int size);
+
+ private:
+  friend class base::NoDestructor<FontSizeJavaScriptFeature>;
+
+  FontSizeJavaScriptFeature();
+  ~FontSizeJavaScriptFeature() override;
+
+  FontSizeJavaScriptFeature(const FontSizeJavaScriptFeature&) = delete;
+  FontSizeJavaScriptFeature& operator=(const FontSizeJavaScriptFeature&) =
+      delete;
+};
+
+#endif  // IOS_CHROME_BROWSER_WEB_FONT_SIZE_FONT_SIZE_JAVA_SCRIPT_FEATURE_H_
diff --git a/ios/chrome/browser/web/font_size/font_size_java_script_feature.mm b/ios/chrome/browser/web/font_size/font_size_java_script_feature.mm
new file mode 100644
index 0000000..bc4522c
--- /dev/null
+++ b/ios/chrome/browser/web/font_size/font_size_java_script_feature.mm
@@ -0,0 +1,50 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
+
+#include "base/no_destructor.h"
+#include "base/values.h"
+#import "ios/web/public/js_messaging/web_frame.h"
+#include "ios/web/public/js_messaging/web_frames_manager.h"
+#import "ios/web/public/web_state.h"
+
+#if !defined(__has_feature) || !__has_feature(objc_arc)
+#error "This file requires ARC support."
+#endif
+
+namespace {
+const char kFontSizeScript[] = "font_size_js";
+}  // namespace
+
+// static
+FontSizeJavaScriptFeature* FontSizeJavaScriptFeature::GetInstance() {
+  static base::NoDestructor<FontSizeJavaScriptFeature> instance;
+  return instance.get();
+}
+
+void FontSizeJavaScriptFeature::AdjustFontSize(web::WebState* web_state,
+                                               int size) {
+  for (web::WebFrame* frame :
+       web_state->GetWebFramesManager()->GetAllWebFrames()) {
+    AdjustFontSize(frame, size);
+  }
+}
+
+void FontSizeJavaScriptFeature::AdjustFontSize(web::WebFrame* web_frame,
+                                               int size) {
+  std::vector<base::Value> parameters;
+  parameters.push_back(base::Value(size));
+  CallJavaScriptFunction(web_frame, "font_size.adjustFontSize", parameters);
+}
+
+FontSizeJavaScriptFeature::FontSizeJavaScriptFeature()
+    : web::JavaScriptFeature(
+          web::JavaScriptFeature::ContentWorld::kAnyContentWorld,
+          {FeatureScript::CreateWithFilename(
+              kFontSizeScript,
+              FeatureScript::InjectionTime::kDocumentStart,
+              FeatureScript::TargetFrames::kAllFrames)}) {}
+
+FontSizeJavaScriptFeature::~FontSizeJavaScriptFeature() = default;
diff --git a/ios/chrome/browser/web/font_size/font_size_tab_helper.mm b/ios/chrome/browser/web/font_size/font_size_tab_helper.mm
index 62e6367..eb5cc41 100644
--- a/ios/chrome/browser/web/font_size/font_size_tab_helper.mm
+++ b/ios/chrome/browser/web/font_size/font_size_tab_helper.mm
@@ -21,8 +21,8 @@
 #include "ios/chrome/browser/browser_state/chrome_browser_state.h"
 #include "ios/chrome/browser/pref_names.h"
 #include "ios/chrome/browser/web/features.h"
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
 #include "ios/components/ui_util/dynamic_type_util.h"
-#import "ios/public/provider/chrome/browser/font_size_java_script_feature.h"
 #import "ios/public/provider/chrome/browser/text_zoom/text_zoom_api.h"
 #include "services/metrics/public/cpp/ukm_builders.h"
 
diff --git a/ios/chrome/browser/web/font_size/font_size_tab_helper_unittest.mm b/ios/chrome/browser/web/font_size/font_size_tab_helper_unittest.mm
index 122a22e..6ac3509 100644
--- a/ios/chrome/browser/web/font_size/font_size_tab_helper_unittest.mm
+++ b/ios/chrome/browser/web/font_size/font_size_tab_helper_unittest.mm
@@ -17,7 +17,7 @@
 #include "ios/chrome/browser/prefs/browser_prefs.h"
 #import "ios/chrome/browser/web/chrome_web_test.h"
 #include "ios/chrome/browser/web/features.h"
-#import "ios/public/provider/chrome/browser/font_size_java_script_feature.h"
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
 #import "ios/web/public/test/fakes/fake_web_client.h"
 #import "ios/web/public/test/fakes/fake_web_state.h"
 #include "testing/gtest/include/gtest/gtest.h"
diff --git a/ios/google_internal/frameworks/chrome_internal_dynamic_framework.ios.zip.sha1 b/ios/google_internal/frameworks/chrome_internal_dynamic_framework.ios.zip.sha1
index 13e8e75..de37135 100644
--- a/ios/google_internal/frameworks/chrome_internal_dynamic_framework.ios.zip.sha1
+++ b/ios/google_internal/frameworks/chrome_internal_dynamic_framework.ios.zip.sha1
@@ -1 +1 @@
-4a9c4a2f9de0a11ac8862ceffccf0547bdea32a9
\ No newline at end of file
+ca93720d6b740f7e6d1289bf31fea01877c34cb1
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/chrome_internal_dynamic_framework.iossimulator.zip.sha1 b/ios/google_internal/frameworks/chrome_internal_dynamic_framework.iossimulator.zip.sha1
index fc3c814..fdbabf5 100644
--- a/ios/google_internal/frameworks/chrome_internal_dynamic_framework.iossimulator.zip.sha1
+++ b/ios/google_internal/frameworks/chrome_internal_dynamic_framework.iossimulator.zip.sha1
@@ -1 +1 @@
-4e179a5f43ee114d4d0543c5238f9ecb46f5ce39
\ No newline at end of file
+88d82a87b45efce403881ae4ac0a02af8deccd45
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.ios.zip.sha1 b/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.ios.zip.sha1
index 6f0d7aa..5da96400 100644
--- a/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.ios.zip.sha1
+++ b/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.ios.zip.sha1
@@ -1 +1 @@
-47bc9b9e48c04637a36c8ee671420f10dd502f61
\ No newline at end of file
+032600b608568fa6962a3a17d6f7291704285d4a
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.iossimulator.zip.sha1 b/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.iossimulator.zip.sha1
index a49f05b..c956986 100644
--- a/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.iossimulator.zip.sha1
+++ b/ios/google_internal/frameworks/chrome_sso_internal_dynamic_framework.iossimulator.zip.sha1
@@ -1 +1 @@
-f0182ca3707e7afbbed2244c5386fdc84318432d
\ No newline at end of file
+e15736feae9e035632b4c618d86630b9d1544c7d
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.ios.zip.sha1 b/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.ios.zip.sha1
index 41126d5..70b2b93 100644
--- a/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.ios.zip.sha1
+++ b/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.ios.zip.sha1
@@ -1 +1 @@
-f2ad453581118d1e7ab25a8893eca776da2e3f0f
\ No newline at end of file
+612c1689789139c4a762e36d0c87bc1b875f21d1
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.iossimulator.zip.sha1 b/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.iossimulator.zip.sha1
index dcb7abc..4f2750875 100644
--- a/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.iossimulator.zip.sha1
+++ b/ios/google_internal/frameworks/remoting_dogfood_internal_dynamic_framework.iossimulator.zip.sha1
@@ -1 +1 @@
-ba5a3c5dc830eb462773263d1c82f05ef1960852
\ No newline at end of file
+2bfdcfb0cedc351b47fe6320d9c160878c986509
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/remoting_internal_dynamic_framework.ios.zip.sha1 b/ios/google_internal/frameworks/remoting_internal_dynamic_framework.ios.zip.sha1
index f11b6d2..c27eb11 100644
--- a/ios/google_internal/frameworks/remoting_internal_dynamic_framework.ios.zip.sha1
+++ b/ios/google_internal/frameworks/remoting_internal_dynamic_framework.ios.zip.sha1
@@ -1 +1 @@
-faf8a5a0eb5af30818b9833493f2cd79041953ee
\ No newline at end of file
+b3f895acd5dd8cb0d5191dbfb85b0d8030b687d7
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/remoting_internal_dynamic_framework.iossimulator.zip.sha1 b/ios/google_internal/frameworks/remoting_internal_dynamic_framework.iossimulator.zip.sha1
index 1a07fa9..ff7208a 100644
--- a/ios/google_internal/frameworks/remoting_internal_dynamic_framework.iossimulator.zip.sha1
+++ b/ios/google_internal/frameworks/remoting_internal_dynamic_framework.iossimulator.zip.sha1
@@ -1 +1 @@
-8c503cf9981878c59055ea6145e3d8c0a0c3b5fe
\ No newline at end of file
+b29bffbf6b2071a663b7b0b10b279b000105cfa4
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.ios.zip.sha1 b/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.ios.zip.sha1
index be64e98e..c5b23e89 100644
--- a/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.ios.zip.sha1
+++ b/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.ios.zip.sha1
@@ -1 +1 @@
-d06247d0cca73ffa0f0199a5b64a5c842dc34e6b
\ No newline at end of file
+02ef5930e78b5dc56a2fb214899af0c0aa5080db
\ No newline at end of file
diff --git a/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.iossimulator.zip.sha1 b/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.iossimulator.zip.sha1
index d2e1f5c..de5579c 100644
--- a/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.iossimulator.zip.sha1
+++ b/ios/google_internal/frameworks/web_view_shell_internal_dynamic_framework.iossimulator.zip.sha1
@@ -1 +1 @@
-0c9e00a30b130501474d3fb894e085ae8fa34e23
\ No newline at end of file
+34f718cc00bc8b61f2c74138dd89d76d27f8a91c
\ No newline at end of file
diff --git a/ios/public/provider/chrome/browser/BUILD.gn b/ios/public/provider/chrome/browser/BUILD.gn
index 16c0eba..e7c72802 100644
--- a/ios/public/provider/chrome/browser/BUILD.gn
+++ b/ios/public/provider/chrome/browser/BUILD.gn
@@ -11,7 +11,6 @@
     "chrome_browser_provider.mm",
   ]
   deps = [
-    ":font_size_java_script_feature",
     "//base",
     "//components/metrics",
     "//ios/public/provider/chrome/browser/mailto",
@@ -25,15 +24,8 @@
 
 source_set("font_size_java_script_feature") {
   configs += [ "//build/config/compiler:enable_arc" ]
-  sources = [
-    "font_size_java_script_feature.h",
-    "font_size_java_script_feature.mm",
-  ]
-  deps = [
-    "//base",
-    "//ios/web/public",
-  ]
-  public_deps = [ "//ios/web/public/js_messaging" ]
+  sources = [ "font_size_java_script_feature.h" ]
+  public_deps = [ "//ios/chrome/browser/web/font_size" ]
 }
 
 group("provider_api") {
diff --git a/ios/public/provider/chrome/browser/DEPS b/ios/public/provider/chrome/browser/DEPS
index 4099d13..65f0b72 100644
--- a/ios/public/provider/chrome/browser/DEPS
+++ b/ios/public/provider/chrome/browser/DEPS
@@ -12,3 +12,9 @@
   # provider is not allowed to depends on //ios/chrome.
   "-ios/public/provider/chrome/browser/browser_state/chrome_browser_state.h",
 ]
+
+specific_include_rules = {
+  "font_size_java_script_feature.h": [
+    "+ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
+  ]
+}
diff --git a/ios/public/provider/chrome/browser/font_size_java_script_feature.h b/ios/public/provider/chrome/browser/font_size_java_script_feature.h
index abf9a8b..75dc7f2 100644
--- a/ios/public/provider/chrome/browser/font_size_java_script_feature.h
+++ b/ios/public/provider/chrome/browser/font_size_java_script_feature.h
@@ -1,38 +1,13 @@
-// Copyright 2021 The Chromium Authors. All rights reserved.
+// Copyright 2022 The Chromium Authors. All rights reserved.
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
 #ifndef IOS_PUBLIC_PROVIDER_CHROME_BROWSER_FONT_SIZE_JAVA_SCRIPT_FEATURE_H_
 #define IOS_PUBLIC_PROVIDER_CHROME_BROWSER_FONT_SIZE_JAVA_SCRIPT_FEATURE_H_
 
-#include "base/no_destructor.h"
-#include "ios/web/public/js_messaging/java_script_feature.h"
-
-namespace web {
-class WebFrame;
-class WebState;
-}  // namespace web
-
-// Feature which adjusts the font size on a page.
-class FontSizeJavaScriptFeature : public web::JavaScriptFeature {
- public:
-  static FontSizeJavaScriptFeature* GetInstance();
-
-  // Adjusts the font size in all frames of |web_state| by |size| percentage.
-  void AdjustFontSize(web::WebState* web_state, int size);
-
-  // Adjusts the font size in |web_frame| by |size| percentage.
-  void AdjustFontSize(web::WebFrame* web_frame, int size);
-
- private:
-  friend class base::NoDestructor<FontSizeJavaScriptFeature>;
-
-  FontSizeJavaScriptFeature();
-  ~FontSizeJavaScriptFeature() override;
-
-  FontSizeJavaScriptFeature(const FontSizeJavaScriptFeature&) = delete;
-  FontSizeJavaScriptFeature& operator=(const FontSizeJavaScriptFeature&) =
-      delete;
-};
+// This is a forwarding header to allow renaming this file without breaking
+// the internal build. It will be removed once the internal repository has
+// been converted to use the new path.
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
 
 #endif  // IOS_PUBLIC_PROVIDER_CHROME_BROWSER_FONT_SIZE_JAVA_SCRIPT_FEATURE_H_
diff --git a/ios/public/provider/chrome/browser/font_size_java_script_feature.mm b/ios/public/provider/chrome/browser/font_size_java_script_feature.mm
deleted file mode 100644
index 2fb16a8..0000000
--- a/ios/public/provider/chrome/browser/font_size_java_script_feature.mm
+++ /dev/null
@@ -1,49 +0,0 @@
-// Copyright 2021 The Chromium Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style license that can be
-// found in the LICENSE file.
-
-#import "ios/public/provider/chrome/browser/font_size_java_script_feature.h"
-
-#include "base/no_destructor.h"
-#include "base/values.h"
-#import "ios/web/public/js_messaging/web_frame.h"
-#include "ios/web/public/js_messaging/web_frames_manager.h"
-#import "ios/web/public/web_state.h"
-
-#if !defined(__has_feature) || !__has_feature(objc_arc)
-#error "This file requires ARC support."
-#endif
-
-namespace {
-const char kFontSizeScript[] = "font_size_js";
-}  // namespace
-
-// static
-FontSizeJavaScriptFeature* FontSizeJavaScriptFeature::GetInstance() {
-  static base::NoDestructor<FontSizeJavaScriptFeature> instance;
-  return instance.get();
-}
-
-void FontSizeJavaScriptFeature::AdjustFontSize(web::WebState* web_state,
-                                               int size) {
-  for (web::WebFrame* frame :
-       web_state->GetWebFramesManager()->GetAllWebFrames()) {
-    AdjustFontSize(frame, size);
-  }
-}
-
-void FontSizeJavaScriptFeature::AdjustFontSize(web::WebFrame* web_frame,
-                                               int size) {
-  std::vector<base::Value> parameters;
-  parameters.push_back(base::Value(size));
-  CallJavaScriptFunction(web_frame, "font_size.adjustFontSize", parameters);
-}
-
-FontSizeJavaScriptFeature::FontSizeJavaScriptFeature()
-    : web::JavaScriptFeature(
-          web::JavaScriptFeature::ContentWorld::kAnyContentWorld,
-          {FeatureScript::CreateWithFilename(
-              kFontSizeScript,
-              FeatureScript::InjectionTime::kDocumentStart,
-              FeatureScript::TargetFrames::kAllFrames)}) {}
-FontSizeJavaScriptFeature::~FontSizeJavaScriptFeature() = default;
diff --git a/ios/public/provider/chrome/browser/text_zoom/BUILD.gn b/ios/public/provider/chrome/browser/text_zoom/BUILD.gn
index c339c5d..1e0c235 100644
--- a/ios/public/provider/chrome/browser/text_zoom/BUILD.gn
+++ b/ios/public/provider/chrome/browser/text_zoom/BUILD.gn
@@ -13,6 +13,6 @@
   sources = [ "test_text_zoom.mm" ]
   deps = [
     ":text_zoom_api",
-    "//ios/public/provider/chrome/browser:font_size_java_script_feature",
+    "//ios/chrome/browser/web/font_size",
   ]
 }
diff --git a/ios/public/provider/chrome/browser/text_zoom/DEPS b/ios/public/provider/chrome/browser/text_zoom/DEPS
new file mode 100644
index 0000000..2c0e1b6
--- /dev/null
+++ b/ios/public/provider/chrome/browser/text_zoom/DEPS
@@ -0,0 +1,7 @@
+include_rules = []
+
+specific_include_rules = {
+  "test_text_zoom.mm": [
+    "+ios/chrome/browser/web/font_size/font_size_java_script_feature.h",
+  ]
+}
diff --git a/ios/public/provider/chrome/browser/text_zoom/test_text_zoom.mm b/ios/public/provider/chrome/browser/text_zoom/test_text_zoom.mm
index 4777b3b..a3c02693 100644
--- a/ios/public/provider/chrome/browser/text_zoom/test_text_zoom.mm
+++ b/ios/public/provider/chrome/browser/text_zoom/test_text_zoom.mm
@@ -2,7 +2,7 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#import "ios/public/provider/chrome/browser/font_size_java_script_feature.h"
+#import "ios/chrome/browser/web/font_size/font_size_java_script_feature.h"
 #import "ios/public/provider/chrome/browser/text_zoom/text_zoom_api.h"
 
 #if !defined(__has_feature) || !__has_feature(objc_arc)
diff --git a/ios/web/security/crw_cert_verification_controller_unittest.mm b/ios/web/security/crw_cert_verification_controller_unittest.mm
index e4fbf16..4d8852cc 100644
--- a/ios/web/security/crw_cert_verification_controller_unittest.mm
+++ b/ios/web/security/crw_cert_verification_controller_unittest.mm
@@ -4,7 +4,7 @@
 
 #import "ios/web/security/crw_cert_verification_controller.h"
 
-#include "base/mac/foundation_util.h"
+#include "base/mac/bridging.h"
 #import "base/test/ios/wait_util.h"
 #include "ios/web/public/test/web_test.h"
 #include "ios/web/public/thread/web_thread.h"
@@ -45,10 +45,10 @@
             cert_.get()));
     ASSERT_TRUE(chain);
     valid_trust_ = web::CreateServerTrustFromChain(
-        base::mac::CFToNSCast(chain.get()), kHostName);
+        base::mac::CFToNSPtrCast(chain.get()), kHostName);
     web::EnsureFutureTrustEvaluationSucceeds(valid_trust_.get());
     invalid_trust_ = web::CreateServerTrustFromChain(
-        base::mac::CFToNSCast(chain.get()), kHostName);
+        base::mac::CFToNSPtrCast(chain.get()), kHostName);
   }
 
   // Synchronously returns result of
diff --git a/ios/web/security/crw_ssl_status_updater_unittest.mm b/ios/web/security/crw_ssl_status_updater_unittest.mm
index e804b515..3f4bd667 100644
--- a/ios/web/security/crw_ssl_status_updater_unittest.mm
+++ b/ios/web/security/crw_ssl_status_updater_unittest.mm
@@ -6,7 +6,7 @@
 
 #import <WebKit/WebKit.h>
 
-#include "base/mac/foundation_util.h"
+#include "base/mac/bridging.h"
 #include "base/strings/sys_string_conversions.h"
 #import "ios/web/navigation/navigation_manager_impl.h"
 #import "ios/web/public/navigation/navigation_item.h"
@@ -108,7 +108,7 @@
         net::x509_util::CreateSecCertificateArrayForX509Certificate(
             cert.get()));
     ASSERT_TRUE(chain);
-    trust_ = CreateServerTrustFromChain(base::mac::CFToNSCast(chain.get()),
+    trust_ = CreateServerTrustFromChain(base::mac::CFToNSPtrCast(chain.get()),
                                         kHostName);
   }
 
diff --git a/ios/web/security/wk_web_view_security_util_unittest.mm b/ios/web/security/wk_web_view_security_util_unittest.mm
index 4fde904b..7c6d32d 100644
--- a/ios/web/security/wk_web_view_security_util_unittest.mm
+++ b/ios/web/security/wk_web_view_security_util_unittest.mm
@@ -9,7 +9,7 @@
 
 #include <memory>
 
-#include "base/mac/foundation_util.h"
+#include "base/mac/bridging.h"
 #include "base/mac/scoped_cftyperef.h"
 #include "crypto/rsa_private_key.h"
 #include "net/cert/x509_certificate.h"
@@ -60,7 +60,7 @@
 base::ScopedCFTypeRef<SecTrustRef> CreateTestTrust(NSArray* cert_chain) {
   base::ScopedCFTypeRef<SecPolicyRef> policy(SecPolicyCreateBasicX509());
   SecTrustRef trust = nullptr;
-  SecTrustCreateWithCertificates(base::mac::NSToCFCast(cert_chain), policy,
+  SecTrustCreateWithCertificates(base::mac::NSToCFPtrCast(cert_chain), policy,
                                  &trust);
   return base::ScopedCFTypeRef<SecTrustRef>(trust);
 }
diff --git a/ios/web/web_view/error_translation_util_unittest.mm b/ios/web/web_view/error_translation_util_unittest.mm
index ce79526..b08c553b 100644
--- a/ios/web/web_view/error_translation_util_unittest.mm
+++ b/ios/web/web_view/error_translation_util_unittest.mm
@@ -6,7 +6,7 @@
 
 #import <Foundation/Foundation.h>
 
-#include "base/mac/foundation_util.h"
+#include "base/mac/bridging.h"
 #import "ios/net/protocol_handler_util.h"
 #include "ios/web/test/test_url_constants.h"
 #import "net/base/mac/url_conversions.h"
@@ -74,7 +74,7 @@
 // underlying error.
 TEST_F(ErrorTranslationUtilTest, UnknownCFNetworkError) {
   NSError* error = [[NSError alloc]
-      initWithDomain:base::mac::CFToNSCast(kCFErrorDomainCFNetwork)
+      initWithDomain:base::mac::CFToNSPtrCast(kCFErrorDomainCFNetwork)
                 code:kCFURLErrorUnknown
             userInfo:nil];
   NSError* net_error = NetErrorFromError(error);
diff --git a/ipc/BUILD.gn b/ipc/BUILD.gn
index 833da0a6..1ac4c2c 100644
--- a/ipc/BUILD.gn
+++ b/ipc/BUILD.gn
@@ -284,7 +284,6 @@
       "//base",
       "//base:i18n",
       "//base/test:test_support",
-      "//build:os_buildflags",
       "//crypto",
       "//mojo/core/test:test_support",
       "//testing/gtest",
diff --git a/ipc/ipc_message_attachment_set_posix_unittest.cc b/ipc/ipc_message_attachment_set_posix_unittest.cc
index e0ed3b5..da20449 100644
--- a/ipc/ipc_message_attachment_set_posix_unittest.cc
+++ b/ipc/ipc_message_attachment_set_posix_unittest.cc
@@ -12,7 +12,6 @@
 
 #include "base/posix/eintr_wrapper.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "ipc/ipc_platform_file_attachment_posix.h"
 #include "testing/gtest/include/gtest/gtest.h"
 
diff --git a/ipc/ipc_send_fds_test.cc b/ipc/ipc_send_fds_test.cc
index 0523d9b..dad1710 100644
--- a/ipc/ipc_send_fds_test.cc
+++ b/ipc/ipc_send_fds_test.cc
@@ -2,7 +2,7 @@
 // Use of this source code is governed by a BSD-style license that can be
 // found in the LICENSE file.
 
-#include "build/os_buildflags.h"
+#include "build/build_config.h"
 
 #if BUILDFLAG(IS_MAC)
 extern "C" {
diff --git a/media/audio/BUILD.gn b/media/audio/BUILD.gn
index 5e1b1f5..b19e098 100644
--- a/media/audio/BUILD.gn
+++ b/media/audio/BUILD.gn
@@ -406,7 +406,6 @@
     "//base",
     "//base/test:test_support",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//media:test_support",
     "//testing/gmock",
     "//testing/gtest",
diff --git a/media/audio/audio_input_unittest.cc b/media/audio/audio_input_unittest.cc
index ce2f2589..34a16e8 100644
--- a/media/audio/audio_input_unittest.cc
+++ b/media/audio/audio_input_unittest.cc
@@ -17,7 +17,6 @@
 #include "base/test/test_message_loop.h"
 #include "base/threading/platform_thread.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "media/audio/audio_device_description.h"
 #include "media/audio/audio_device_info_accessor_for_tests.h"
 #include "media/audio/audio_io.h"
diff --git a/media/formats/BUILD.gn b/media/formats/BUILD.gn
index d24a03d..212c2559 100644
--- a/media/formats/BUILD.gn
+++ b/media/formats/BUILD.gn
@@ -189,6 +189,8 @@
     "hls/parse_context.cc",
     "hls/parse_context.h",
     "hls/parse_status.h",
+    "hls/tags.cc",
+    "hls/tags.h",
     "hls/types.cc",
     "hls/types.h",
   ]
@@ -302,6 +304,7 @@
   # TODO(https://crbug.com/1266991): This should be gated behind `enable_hls_demuxer`, once that's enabled by default.
   sources += [
     "hls/items_unittest.cc",
+    "hls/tags_unittest.cc",
     "hls/types_unittest.cc",
   ]
 }
diff --git a/media/formats/hls/parse_context.cc b/media/formats/hls/parse_context.cc
index 2905749..dfbc05f 100644
--- a/media/formats/hls/parse_context.cc
+++ b/media/formats/hls/parse_context.cc
@@ -18,6 +18,10 @@
   return SourceString(line, 1, str);
 }
 
+SourceString SourceString::CreateForTesting(base::StringPiece str) {
+  return SourceString::CreateForTesting(1, 1, str);
+}
+
 SourceString SourceString::CreateForTesting(size_t line,
                                             size_t column,
                                             base::StringPiece str) {
diff --git a/media/formats/hls/parse_context.h b/media/formats/hls/parse_context.h
index 53ad33e..9518e1f 100644
--- a/media/formats/hls/parse_context.h
+++ b/media/formats/hls/parse_context.h
@@ -23,6 +23,7 @@
   static SourceString Create(base::PassKey<SourceLineIterator>,
                              size_t line,
                              base::StringPiece str);
+  static SourceString CreateForTesting(base::StringPiece str);
   static SourceString CreateForTesting(size_t line,
                                        size_t column,
                                        base::StringPiece str);
diff --git a/media/formats/hls/parse_status.h b/media/formats/hls/parse_status.h
index 43673a8..43bce92 100644
--- a/media/formats/hls/parse_status.h
+++ b/media/formats/hls/parse_status.h
@@ -17,6 +17,7 @@
   kFailedToParseDecimalInteger,
   kFailedToParseDecimalFloatingPoint,
   kFailedToParseSignedDecimalFloatingPoint,
+  kInvalidPlaylistVersion,
   kPlaylistMissingM3uTag,
   kMediaSegmentMissingInfTag,
 };
diff --git a/media/formats/hls/tags.cc b/media/formats/hls/tags.cc
new file mode 100644
index 0000000..ebbf6d5
--- /dev/null
+++ b/media/formats/hls/tags.cc
@@ -0,0 +1,67 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "media/formats/hls/tags.h"
+
+#include <cstddef>
+#include "media/formats/hls/parse_status.h"
+
+namespace media {
+namespace hls {
+
+ParseStatus::Or<M3uTag> M3uTag::Parse(TagItem tag) {
+  DCHECK(tag.kind == TagKind::kM3u);
+  if (!tag.content.Str().empty()) {
+    return ParseStatusCode::kMalformedTag;
+  }
+
+  return M3uTag{};
+}
+
+ParseStatus::Or<XVersionTag> XVersionTag::Parse(TagItem tag) {
+  DCHECK(tag.kind == TagKind::kXVersion);
+
+  auto value_result = types::ParseDecimalInteger(tag.content);
+  if (value_result.has_error()) {
+    return ParseStatus(ParseStatusCode::kMalformedTag)
+        .AddCause(std::move(value_result).error());
+  }
+
+  // Reject invalid version numbers.
+  // For valid version numbers, caller will decide if the version is supported.
+  auto value = std::move(value_result).value();
+  if (value == 0) {
+    return ParseStatusCode::kInvalidPlaylistVersion;
+  }
+
+  return XVersionTag{.version = value};
+}
+
+ParseStatus::Or<InfTag> InfTag::Parse(TagItem tag) {
+  DCHECK(tag.kind == TagKind::kInf);
+
+  // Inf tags have the form #EXTINF:<duration>,[<title>]
+  // Find the comma.
+  auto comma = tag.content.Str().find_first_of(',');
+  if (comma == base::StringPiece::npos) {
+    return ParseStatusCode::kMalformedTag;
+  }
+
+  auto duration_str = tag.content.Substr(0, comma);
+  auto title_str = tag.content.Substr(comma + 1);
+
+  // Extract duration
+  // TODO(crbug.com/1284763): Below version 3 this should be rounded to an
+  // integer
+  auto duration = types::ParseDecimalFloatingPoint(duration_str);
+  if (duration.has_error()) {
+    return ParseStatus(ParseStatusCode::kMalformedTag)
+        .AddCause(std::move(duration).error());
+  }
+
+  return InfTag{.duration = std::move(duration).value(), .title = title_str};
+}
+
+}  // namespace hls
+}  // namespace media
diff --git a/media/formats/hls/tags.h b/media/formats/hls/tags.h
new file mode 100644
index 0000000..053c1618
--- /dev/null
+++ b/media/formats/hls/tags.h
@@ -0,0 +1,45 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef MEDIA_FORMATS_HLS_TAGS_H_
+#define MEDIA_FORMATS_HLS_TAGS_H_
+
+#include "media/base/media_export.h"
+#include "media/formats/hls/items.h"
+#include "media/formats/hls/parse_status.h"
+#include "media/formats/hls/types.h"
+
+namespace media {
+namespace hls {
+
+// Represents the contents of the #EXTM3U tag
+struct M3uTag {
+  static constexpr TagKind kKind = TagKind::kM3u;
+  static MEDIA_EXPORT ParseStatus::Or<M3uTag> Parse(TagItem);
+};
+
+// Represents the contents of the #EXT-X-VERSION tag
+struct XVersionTag {
+  static constexpr TagKind kKind = TagKind::kXVersion;
+  static MEDIA_EXPORT ParseStatus::Or<XVersionTag> Parse(TagItem);
+
+  types::DecimalInteger version;
+};
+
+// Represents the contents of the #EXTINF tag
+struct InfTag {
+  static constexpr TagKind kKind = TagKind::kInf;
+  static MEDIA_EXPORT ParseStatus::Or<InfTag> Parse(TagItem);
+
+  // Target duration of the media segment, in seconds.
+  types::DecimalFloatingPoint duration;
+
+  // Human-readable title of the media segment.
+  SourceString title;
+};
+
+}  // namespace hls
+}  // namespace media
+
+#endif  // MEDIA_FORMATS_HLS_TAGS_H_
diff --git a/media/formats/hls/tags_unittest.cc b/media/formats/hls/tags_unittest.cc
new file mode 100644
index 0000000..dc2f97a
--- /dev/null
+++ b/media/formats/hls/tags_unittest.cc
@@ -0,0 +1,126 @@
+// Copyright 2022 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "media/formats/hls/tags.h"
+#include "media/formats/hls/parse_context.h"
+#include "testing/gtest/include/gtest/gtest.h"
+
+namespace media {
+namespace hls {
+
+template <typename T>
+void ErrorTest(SourceString content, ParseStatusCode expected_status) {
+  auto tag = TagItem{.kind = T::kKind, .content = content};
+  auto result = T::Parse(tag);
+  EXPECT_TRUE(result.has_error());
+  auto error = std::move(result).error();
+  EXPECT_EQ(error.code(), expected_status);
+}
+
+template <typename T>
+T OkTest(SourceString content) {
+  auto tag = TagItem{.kind = T::kKind, .content = content};
+  auto result = T::Parse(tag);
+  EXPECT_TRUE(result.has_value());
+  return std::move(result).value();
+}
+
+TEST(HlsFormatParserTest, ParseM3uTagTest) {
+  // Empty content is the only allowed content
+  OkTest<M3uTag>(SourceString::CreateForTesting(""));
+
+  // Test with non-empty content
+  ErrorTest<M3uTag>(SourceString::CreateForTesting(" "),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<M3uTag>(SourceString::CreateForTesting("a"),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<M3uTag>(SourceString::CreateForTesting("1234"),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<M3uTag>(SourceString::CreateForTesting("\t"),
+                    ParseStatusCode::kMalformedTag);
+}
+
+TEST(HlsFormatParserTest, ParseXVersionTagTest) {
+  // Test valid versions
+  XVersionTag tag = OkTest<XVersionTag>(SourceString::CreateForTesting("1"));
+  EXPECT_EQ(tag.version, 1u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("2"));
+  EXPECT_EQ(tag.version, 2u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("3"));
+  EXPECT_EQ(tag.version, 3u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("4"));
+  EXPECT_EQ(tag.version, 4u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("5"));
+  EXPECT_EQ(tag.version, 5u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("6"));
+  EXPECT_EQ(tag.version, 6u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("7"));
+  EXPECT_EQ(tag.version, 7u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("8"));
+  EXPECT_EQ(tag.version, 8u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("9"));
+  EXPECT_EQ(tag.version, 9u);
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("10"));
+  EXPECT_EQ(tag.version, 10u);
+
+  // While unsupported playlist versions are rejected, that's NOT the
+  // responsibility of this tag parsing function. The playlist should be
+  // rejected at a higher level.
+  tag = OkTest<XVersionTag>(SourceString::CreateForTesting("99999"));
+  EXPECT_EQ(tag.version, 99999u);
+
+  // Test invalid versions
+  ErrorTest<XVersionTag>(SourceString::CreateForTesting(""),
+                         ParseStatusCode::kMalformedTag);
+  ErrorTest<XVersionTag>(SourceString::CreateForTesting("0"),
+                         ParseStatusCode::kInvalidPlaylistVersion);
+  ErrorTest<XVersionTag>(SourceString::CreateForTesting("-1"),
+                         ParseStatusCode::kMalformedTag);
+  ErrorTest<XVersionTag>(SourceString::CreateForTesting("1.0"),
+                         ParseStatusCode::kMalformedTag);
+  ErrorTest<XVersionTag>(SourceString::CreateForTesting("asdf"),
+                         ParseStatusCode::kMalformedTag);
+  ErrorTest<XVersionTag>(SourceString::CreateForTesting("  1 "),
+                         ParseStatusCode::kMalformedTag);
+}
+
+TEST(HlsFormatParserTest, ParseInfTagTest) {
+  // Test some valid tags
+  InfTag tag = OkTest<InfTag>(SourceString::CreateForTesting("1234,"));
+  EXPECT_EQ(tag.duration, 1234.0);
+  EXPECT_EQ(tag.title.Str(), "");
+
+  tag = OkTest<InfTag>(SourceString::CreateForTesting("1.234,"));
+  EXPECT_EQ(tag.duration, 1.234);
+  EXPECT_EQ(tag.title.Str(), "");
+
+  // The spec implies that whitespace characters like this usually aren't
+  // permitted, but "\t" is a common occurrence for the title value.
+  tag = OkTest<InfTag>(SourceString::CreateForTesting("99.5,\t"));
+  EXPECT_EQ(tag.duration, 99.5);
+  EXPECT_EQ(tag.title.Str(), "\t");
+
+  tag = OkTest<InfTag>(SourceString::CreateForTesting("9.5,,,,"));
+  EXPECT_EQ(tag.duration, 9.5);
+  EXPECT_EQ(tag.title.Str(), ",,,");
+
+  tag = OkTest<InfTag>(SourceString::CreateForTesting("12,asdfsdf   "));
+  EXPECT_EQ(tag.duration, 12.0);
+  EXPECT_EQ(tag.title.Str(), "asdfsdf   ");
+
+  // Test some invalid tags
+  ErrorTest<InfTag>(SourceString::CreateForTesting(""),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<InfTag>(SourceString::CreateForTesting(","),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<InfTag>(SourceString::CreateForTesting("-123,"),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<InfTag>(SourceString::CreateForTesting("123"),
+                    ParseStatusCode::kMalformedTag);
+  ErrorTest<InfTag>(SourceString::CreateForTesting("asdf,"),
+                    ParseStatusCode::kMalformedTag);
+}
+
+}  // namespace hls
+}  // namespace media
diff --git a/mojo/public/rust/OWNERS b/mojo/public/rust/OWNERS
new file mode 100644
index 0000000..3ba9ffb
--- /dev/null
+++ b/mojo/public/rust/OWNERS
@@ -0,0 +1,3 @@
+file://build/rust/OWNERS
+
+collinbaker@chromium.org
\ No newline at end of file
diff --git a/mojo/public/rust/bindings/decoding.rs b/mojo/public/rust/bindings/decoding.rs
new file mode 100644
index 0000000..304817b
--- /dev/null
+++ b/mojo/public/rust/bindings/decoding.rs
@@ -0,0 +1,398 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use bindings::encoding::{
+    Bits, Context, DataHeader, DataHeaderValue, MojomNumeric, DATA_HEADER_SIZE,
+};
+use bindings::mojom::{MojomEncodable, MOJOM_NULL_POINTER, UNION_SIZE};
+use bindings::util;
+
+use std::mem;
+use std::ptr;
+use std::vec::Vec;
+
+use system;
+use system::{CastHandle, Handle, UntypedHandle};
+
+#[derive(Debug, Eq, PartialEq)]
+pub enum ValidationError {
+    DifferentSizedArraysInMap,
+    IllegalHandle,
+    IllegalMemoryRange,
+    IllegalPointer,
+    MessageHeaderInvalidFlags,
+    MessageHeaderMissingRequestId,
+    MessageHeaderUnknownMethod,
+    MisalignedObject,
+    UnexpectedArrayHeader,
+    UnexpectedInvalidHandle,
+    UnexpectedNullPointer,
+    UnexpectedNullUnion,
+    UnexpectedStructHeader,
+}
+
+impl ValidationError {
+    pub fn as_str(self) -> &'static str {
+        match self {
+            ValidationError::DifferentSizedArraysInMap => {
+                "VALIDATION_ERROR_DIFFERENT_SIZED_ARRAYS_IN_MAP"
+            }
+            ValidationError::IllegalHandle => "VALIDATION_ERROR_ILLEGAL_HANDLE",
+            ValidationError::IllegalMemoryRange => "VALIDATION_ERROR_ILLEGAL_MEMORY_RANGE",
+            ValidationError::IllegalPointer => "VALIDATION_ERROR_ILLEGAL_POINTER",
+            ValidationError::MessageHeaderInvalidFlags => {
+                "VALIDATION_ERROR_MESSAGE_HEADER_INVALID_FLAGS"
+            }
+            ValidationError::MessageHeaderMissingRequestId => {
+                "VALIDATION_ERROR_MESSAGE_HEADER_MISSING_REQUEST_ID"
+            }
+            ValidationError::MessageHeaderUnknownMethod => {
+                "VALIDATION_ERROR_MESSAGE_HEADER_UNKNOWN_METHOD"
+            }
+            ValidationError::MisalignedObject => "VALIDATION_ERROR_MISALIGNED_OBJECT",
+            ValidationError::UnexpectedArrayHeader => "VALIDATION_ERROR_UNEXPECTED_ARRAY_HEADER",
+            ValidationError::UnexpectedInvalidHandle => {
+                "VALIDATION_ERROR_UNEXPECTED_INVALID_HANDLE"
+            }
+            ValidationError::UnexpectedNullPointer => "VALIDATION_ERROR_UNEXPECTED_NULL_POINTER",
+            ValidationError::UnexpectedNullUnion => "VALIDATION_ERROR_UNEXPECTED_NULL_UNION",
+            ValidationError::UnexpectedStructHeader => "VALIDATION_ERROR_UNEXPECTED_STRUCT_HEADER",
+        }
+    }
+}
+
+/// An decoding state represents the decoding logic for a single
+/// Mojom object that is NOT inlined, such as a struct or an array.
+pub struct DecodingState<'slice> {
+    /// The buffer the state may write to.
+    data: &'slice [u8],
+
+    /// The offset of this serialized object into the overall buffer.
+    global_offset: usize,
+
+    /// The current offset within 'data'.
+    offset: usize,
+
+    /// The current bit offset within 'data'.
+    bit_offset: Bits,
+}
+
+impl<'slice> DecodingState<'slice> {
+    /// Create a new decoding state.
+    pub fn new(buffer: &'slice [u8], offset: usize) -> DecodingState<'slice> {
+        DecodingState { data: buffer, global_offset: offset, offset: 0, bit_offset: Bits(0) }
+    }
+
+    /// Align the decoding state to the next byte.
+    pub fn align_to_byte(&mut self) {
+        if self.bit_offset > Bits(0) {
+            self.offset += 1;
+            self.bit_offset = Bits(0);
+        }
+    }
+
+    /// Align the decoding state to the next 'bytes' boundary.
+    pub fn align_to_bytes(&mut self, bytes: usize) {
+        if self.offset != 0 {
+            self.offset = util::align_bytes(self.offset, bytes);
+        }
+    }
+
+    /// Read a primitive from the buffer without incrementing the offset.
+    fn read_in_place<T: MojomNumeric>(&mut self) -> T {
+        let mut value: T = Default::default();
+        debug_assert!(mem::size_of::<T>() + self.offset <= self.data.len());
+        let ptr = (&self.data[self.offset..]).as_ptr();
+        unsafe {
+            ptr::copy_nonoverlapping(
+                mem::transmute::<*const u8, *const T>(ptr),
+                &mut value as *mut T,
+                1,
+            );
+        }
+        value
+    }
+
+    /// Read a primitive from the buffer and increment the offset.
+    fn read<T: MojomNumeric>(&mut self) -> T {
+        let value = self.read_in_place::<T>();
+        self.bit_offset = Bits(0);
+        self.offset += mem::size_of::<T>();
+        value
+    }
+
+    /// Decode a primitive from the buffer, naturally aligning before we read.
+    pub fn decode<T: MojomNumeric>(&mut self) -> T {
+        self.align_to_byte();
+        self.align_to_bytes(mem::size_of::<T>());
+        self.read::<T>()
+    }
+
+    /// Decode a boolean value from the buffer as one bit.
+    pub fn decode_bool(&mut self) -> bool {
+        let offset = self.offset;
+        // Check the bit by getting the set bit and checking if its non-zero
+        let value = (self.data[offset] & self.bit_offset.as_set_bit()) > 0;
+        self.bit_offset += Bits(1);
+        let (bits, bytes) = self.bit_offset.as_bits_and_bytes();
+        self.offset += bytes;
+        self.bit_offset = bits;
+        value
+    }
+
+    /// If we encounter a null pointer, increment past it.
+    ///
+    /// Returns if we skipped or not.
+    pub fn skip_if_null_pointer(&mut self) -> bool {
+        self.align_to_byte();
+        self.align_to_bytes(8);
+        let ptr = self.read_in_place::<u64>();
+        if ptr == MOJOM_NULL_POINTER {
+            self.offset += 8;
+        }
+        (ptr == MOJOM_NULL_POINTER)
+    }
+
+    /// If we encounter a null union, increment past it.
+    ///
+    /// Returns if we skipped or not.
+    pub fn skip_if_null_union(&mut self) -> bool {
+        self.align_to_byte();
+        self.align_to_bytes(8);
+        let size = self.read_in_place::<u32>();
+        if size == 0 {
+            self.offset += UNION_SIZE;
+        }
+        (size == 0)
+    }
+
+    /// If we encounter a null handle, increment past it.
+    ///
+    /// Returns if we skipped or not.
+    pub fn skip_if_null_handle(&mut self) -> bool {
+        self.align_to_byte();
+        self.align_to_bytes(4);
+        let index = self.read_in_place::<i32>();
+        if index < 0 {
+            self.offset += 4;
+        }
+        (index < 0)
+    }
+
+    /// If we encounter a null interface, increment past it.
+    ///
+    /// Returns if we skipped or not.
+    pub fn skip_if_null_interface(&mut self) -> bool {
+        self.align_to_byte();
+        self.align_to_bytes(4);
+        let index = self.read_in_place::<i32>();
+        if index < 0 {
+            self.offset += 8;
+        }
+        (index < 0)
+    }
+
+    /// Decode a pointer from the buffer as a global offset into the buffer.
+    ///
+    /// The pointer in the buffer is an offset relative to the pointer to another
+    /// location in the buffer. We convert that to an absolute offset with respect
+    /// to the buffer before returning. This is our defintion of a pointer.
+    pub fn decode_pointer(&mut self) -> Option<u64> {
+        self.align_to_byte();
+        self.align_to_bytes(8);
+        let current_location = (self.global_offset + self.offset) as u64;
+        let offset = self.read::<u64>();
+        if offset == MOJOM_NULL_POINTER {
+            Some(MOJOM_NULL_POINTER)
+        } else {
+            offset.checked_add(current_location)
+        }
+    }
+
+    /// A routine for decoding an array header.
+    ///
+    /// Must be called with offset zero (that is, it must be the first thing
+    /// decoded). Performs numerous validation checks.
+    pub fn decode_array_header<T>(&mut self) -> Result<DataHeader, ValidationError>
+    where
+        T: MojomEncodable,
+    {
+        debug_assert_eq!(self.offset, 0);
+        // Make sure we can read the size first...
+        if self.data.len() < mem::size_of::<u32>() {
+            return Err(ValidationError::UnexpectedArrayHeader);
+        }
+        let bytes = self.decode::<u32>();
+        if (bytes as usize) < DATA_HEADER_SIZE {
+            return Err(ValidationError::UnexpectedArrayHeader);
+        }
+        let elems = self.decode::<u32>();
+        match T::embed_size(&Default::default()).checked_mul(elems as usize) {
+            Some(value) => {
+                if (bytes as usize) < value.as_bytes() + DATA_HEADER_SIZE {
+                    return Err(ValidationError::UnexpectedArrayHeader);
+                }
+            }
+            None => return Err(ValidationError::UnexpectedArrayHeader),
+        }
+        Ok(DataHeader::new(bytes as usize, DataHeaderValue::Elements(elems)))
+    }
+
+    /// A routine for decoding an struct header.
+    ///
+    /// Must be called with offset zero (that is, it must be the first thing
+    /// decoded). Performs numerous validation checks.
+    pub fn decode_struct_header(
+        &mut self,
+        versions: &[(u32, u32)],
+    ) -> Result<DataHeader, ValidationError> {
+        debug_assert_eq!(self.offset, 0);
+        // Make sure we can read the size first...
+        if self.data.len() < mem::size_of::<u32>() {
+            return Err(ValidationError::UnexpectedStructHeader);
+        }
+        let bytes = self.decode::<u32>();
+        if (bytes as usize) < DATA_HEADER_SIZE {
+            return Err(ValidationError::UnexpectedStructHeader);
+        }
+        let version = self.decode::<u32>();
+        // Versioning validation: versions are generated as a sorted array of tuples, so
+        // to find the version we are given by the header we use a binary search.
+        match versions.binary_search_by(|val| val.0.cmp(&version)) {
+            Ok(idx) => {
+                let (_, size) = versions[idx];
+                if bytes != size {
+                    return Err(ValidationError::UnexpectedStructHeader);
+                }
+            }
+            Err(idx) => {
+                if idx == 0 {
+                    panic!(
+                        "Should be earliest version? \
+                            Versions: {:?}, \
+                            Version: {}, \
+                            Size: {}",
+                        versions, version, bytes
+                    );
+                }
+                let len = versions.len();
+                let (latest_version, _) = versions[len - 1];
+                let (_, size) = versions[idx - 1];
+                // If this is higher than any version we know, its okay for the size to be bigger,
+                // but if its a version we know about, it must match the size.
+                if (version > latest_version && bytes < size)
+                    || (version <= latest_version && bytes != size)
+                {
+                    return Err(ValidationError::UnexpectedStructHeader);
+                }
+            }
+        }
+        Ok(DataHeader::new(bytes as usize, DataHeaderValue::Version(version)))
+    }
+}
+
+/// A struct that will encode a given Mojom object and convert it into
+/// bytes and a vector of handles.
+pub struct Decoder<'slice> {
+    bytes: usize,
+    buffer: Option<&'slice [u8]>,
+    states: Vec<DecodingState<'slice>>,
+    handles: Vec<UntypedHandle>,
+    handles_claimed: usize, // A length that claims all handles were claimed up to this index
+    max_offset: usize,      // Represents the maximum value an offset may have
+}
+
+impl<'slice> Decoder<'slice> {
+    /// Create a new Decoder.
+    pub fn new(buffer: &'slice [u8], handles: Vec<UntypedHandle>) -> Decoder<'slice> {
+        let max_offset = buffer.len();
+        Decoder {
+            bytes: 0,
+            buffer: Some(buffer),
+            states: Vec::new(),
+            handles: handles,
+            handles_claimed: 0,
+            max_offset: max_offset,
+        }
+    }
+
+    /// Claim space in the buffer to start decoding some object.
+    ///
+    /// Creates a new decoding state for the object and returns a context.
+    pub fn claim(&mut self, offset: usize) -> Result<Context, ValidationError> {
+        // Check if the layout order is sane
+        if offset < self.bytes {
+            return Err(ValidationError::IllegalMemoryRange);
+        }
+        // Check for 8-byte alignment
+        if offset & 7 != 0 {
+            return Err(ValidationError::MisalignedObject);
+        }
+        // Bounds check on offset
+        if offset > self.max_offset {
+            return Err(ValidationError::IllegalPointer);
+        }
+        let mut buffer = self.buffer.take().expect("No buffer?");
+        let space = offset - self.bytes;
+        buffer = &buffer[space..];
+        // Make sure we can even read the bytes in the header
+        if buffer.len() < mem::size_of::<u32>() {
+            return Err(ValidationError::IllegalMemoryRange);
+        }
+        // Read the number of bytes in the memory region according to the data header
+        let mut read_size: u32 = 0;
+        unsafe {
+            ptr::copy_nonoverlapping(
+                mem::transmute::<*const u8, *const u32>(buffer.as_ptr()),
+                &mut read_size as *mut u32,
+                mem::size_of::<u32>(),
+            );
+        }
+        let size = u32::from_le(read_size) as usize;
+        // Make sure the size we read is sane...
+        if size > buffer.len() {
+            return Err(ValidationError::IllegalMemoryRange);
+        }
+        // TODO(mknyszek): Check size for validation
+        let (claimed, unclaimed) = buffer.split_at(size);
+        self.states.push(DecodingState::new(claimed, offset));
+        self.buffer = Some(unclaimed);
+        self.bytes += space + size;
+        Ok(Context::new(self.states.len() - 1))
+    }
+
+    /// Claims a handle at some particular index in the given handles array.
+    ///
+    /// Returns the handle with all type information in-tact.
+    pub fn claim_handle<T: Handle + CastHandle>(
+        &mut self,
+        index: i32,
+    ) -> Result<T, ValidationError> {
+        let real_index = if index >= 0 {
+            index as usize
+        } else {
+            return Err(ValidationError::UnexpectedInvalidHandle);
+        };
+        // If the index exceeds our number of handles or if we have already claimed that handle
+        if real_index >= self.handles.len() || real_index < self.handles_claimed {
+            return Err(ValidationError::IllegalHandle);
+        }
+        self.handles_claimed = real_index + 1;
+        let raw_handle = self.handles[real_index].get_native_handle();
+        unsafe {
+            self.handles[real_index].invalidate();
+            Ok(T::from_untyped(system::acquire(raw_handle)))
+        }
+    }
+
+    /// Immutably borrow a decoding state via Context.
+    pub fn get(&self, context: &Context) -> &DecodingState<'slice> {
+        &self.states[context.id()]
+    }
+
+    /// Mutably borrow a decoding state via Context.
+    pub fn get_mut(&mut self, context: &Context) -> &mut DecodingState<'slice> {
+        &mut self.states[context.id()]
+    }
+}
diff --git a/mojo/public/rust/bindings/encoding.rs b/mojo/public/rust/bindings/encoding.rs
new file mode 100644
index 0000000..39e0744
--- /dev/null
+++ b/mojo/public/rust/bindings/encoding.rs
@@ -0,0 +1,399 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use bindings::mojom::MOJOM_NULL_POINTER;
+use bindings::util;
+
+use std::mem;
+use std::ops::{Add, AddAssign, Div, Mul, Rem, Sub};
+use std::ptr;
+use std::vec::Vec;
+
+use system::UntypedHandle;
+
+/// Represents some count of bits.
+///
+/// Used to distinguish when we have a bit and a byte
+/// count. The byte count will go in a usize, while we
+/// can use this structure to safely count bits without
+/// running into some subtle bugs or crazy errors.
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd)]
+pub struct Bits(pub usize);
+
+impl Bits {
+    /// Convert bit representation to bytes, rounding up to the nearest byte.
+    pub fn as_bytes(self) -> usize {
+        util::bits_to_bytes(self.0)
+    }
+
+    /// Convert to a number of bytes plus the number of bits leftover
+    /// that could not fit in a full byte.
+    pub fn as_bits_and_bytes(self) -> (Bits, usize) {
+        (Bits(self.0 & 7), self.0 >> 3)
+    }
+
+    /// Return 1 left-shifted by the amount of bits stored here.
+    ///
+    /// Only guaranteed to work for up to 8 bits.
+    pub fn as_set_bit(self) -> u8 {
+        debug_assert!(self.0 < 8);
+        1 << (self.0 & 7)
+    }
+
+    pub fn checked_mul(self, val: usize) -> Option<Bits> {
+        match val.checked_mul(self.0) {
+            Some(result) => Some(Bits(result)),
+            None => None,
+        }
+    }
+
+    /// Align the bits to some number of bytes.
+    pub fn align_to_bytes(&mut self, bytes: usize) {
+        self.0 = util::align_bytes(self.0, 8 * bytes);
+    }
+}
+
+impl Add for Bits {
+    type Output = Self;
+    fn add(self, rhs: Self) -> Self {
+        Bits(self.0 + rhs.0)
+    }
+}
+
+impl AddAssign for Bits {
+    fn add_assign(&mut self, rhs: Self) {
+        self.0 += rhs.0
+    }
+}
+
+impl Mul<usize> for Bits {
+    type Output = Self;
+    fn mul(self, rhs: usize) -> Self {
+        Bits(self.0 * rhs)
+    }
+}
+
+/// This trait is intended to be used by Mojom primitive values
+/// in order to be identified in generic contexts.
+pub trait MojomNumeric:
+    Copy
+    + Clone
+    + Sized
+    + Add<Self>
+    + Sub<Self, Output = Self>
+    + Mul<Self>
+    + Div<Self, Output = Self>
+    + Rem<Self, Output = Self>
+    + PartialEq<Self>
+    + Default
+{
+    /// Converts the primitive to a little-endian representation (the mojom endianness).
+    fn to_mojom_endian(self) -> Self;
+}
+
+macro_rules! impl_mojom_numeric_for_prim {
+    ($($t:ty),*) => {
+        $(
+        impl MojomNumeric for $t {
+            fn to_mojom_endian(self) -> $t { self.to_le() }
+        }
+        )*
+    }
+}
+
+impl_mojom_numeric_for_prim!(i8, i16, i32, i64, u8, u16, u32, u64);
+
+impl MojomNumeric for f32 {
+    fn to_mojom_endian(self) -> f32 {
+        unsafe { mem::transmute::<u32, f32>(mem::transmute::<f32, u32>(self).to_le()) }
+    }
+}
+
+impl MojomNumeric for f64 {
+    fn to_mojom_endian(self) -> f64 {
+        unsafe { mem::transmute::<u64, f64>(mem::transmute::<f64, u64>(self).to_le()) }
+    }
+}
+
+/// Align to the Mojom default of 8 bytes.
+pub fn align_default(bytes: usize) -> usize {
+    util::align_bytes(bytes, 8)
+}
+
+/// The size in bytes of any data header.
+pub const DATA_HEADER_SIZE: usize = 8;
+
+/// A value that goes in the second u32 of a
+/// a data header.
+///
+/// Since the data header can head many types,
+/// this enum represents all the kinds of data
+/// that can end up in a data header.
+#[derive(Clone, Copy)]
+pub enum DataHeaderValue {
+    Elements(u32),
+    Version(u32),
+    UnionTag(u32),
+}
+
+impl DataHeaderValue {
+    /// Get the raw u32 value.
+    fn as_raw(self) -> u32 {
+        match self {
+            DataHeaderValue::Elements(v) => v,
+            DataHeaderValue::Version(v) => v,
+            DataHeaderValue::UnionTag(v) => v,
+        }
+    }
+}
+
+/// A data header is placed at the beginning of every serialized
+/// Mojom object, providing its size as well as some extra meta-data.
+///
+/// The meta-data should always come from a DataHeaderValue.
+pub struct DataHeader {
+    size: u32,
+    data: u32,
+}
+
+impl DataHeader {
+    /// Create a new DataHeader.
+    pub fn new(size: usize, data: DataHeaderValue) -> DataHeader {
+        DataHeader { size: size as u32, data: data.as_raw() }
+    }
+
+    /// Getter for size.
+    pub fn size(&self) -> u32 {
+        self.size
+    }
+
+    /// Getter for extra meta-data.
+    pub fn data(&self) -> u32 {
+        self.data
+    }
+}
+
+/// This context object represents an encoding/decoding context.
+#[derive(Clone, Default)]
+pub struct Context {
+    /// An index representing an encoding state.
+    id: usize,
+
+    /// Whether or not our current context is directly inside of
+    /// a union.
+    is_union: bool,
+}
+
+impl Context {
+    /// Create a new context with all data default.
+    pub fn new(id: usize) -> Context {
+        Context { id: id, is_union: false }
+    }
+
+    /// Getter for the encoding state ID.
+    pub fn id(&self) -> usize {
+        self.id
+    }
+
+    /// Getter for whether or not we are in a union.
+    pub fn is_union(&self) -> bool {
+        self.is_union
+    }
+
+    /// Change whether or not we are inside of a union and create that
+    /// as a new context.
+    pub fn set_is_union(&self, value: bool) -> Context {
+        let mut new_context = self.clone();
+        new_context.is_union = value;
+        new_context
+    }
+}
+
+/// An encoding state represents the encoding logic for a single
+/// Mojom object that is NOT inlined, such as a struct or an array.
+pub struct EncodingState<'slice> {
+    /// The buffer the state may write to.
+    data: &'slice mut [u8],
+
+    /// The offset of this serialized object into the overall buffer.
+    global_offset: usize,
+
+    /// The current offset within 'data'.
+    offset: usize,
+
+    /// The current bit offset within 'data'.
+    bit_offset: Bits,
+}
+
+impl<'slice> EncodingState<'slice> {
+    /// Create a new encoding state.
+    ///
+    /// Note: the encoder will not allocate a buffer for you, rather
+    /// a pre-allocated buffer must be passed in.
+    pub fn new(
+        buffer: &'slice mut [u8],
+        header: &DataHeader,
+        offset: usize,
+    ) -> EncodingState<'slice> {
+        let mut state =
+            EncodingState { data: buffer, global_offset: offset, offset: 0, bit_offset: Bits(0) };
+        state.write(header.size());
+        state.write(header.data());
+        state
+    }
+
+    /// Align the encoding state to the next byte.
+    pub fn align_to_byte(&mut self) {
+        if self.bit_offset > Bits(0) {
+            self.offset += 1;
+            self.bit_offset = Bits(0);
+        }
+    }
+
+    /// Align the encoding state to the next 'bytes' boundary.
+    pub fn align_to_bytes(&mut self, bytes: usize) {
+        self.offset = util::align_bytes(self.offset, bytes);
+    }
+
+    /// Write a primitive into the buffer.
+    fn write<T: MojomNumeric>(&mut self, data: T) {
+        let num_bytes = mem::size_of::<T>();
+        let bytes = data.to_mojom_endian();
+        debug_assert!(num_bytes + self.offset <= self.data.len());
+        unsafe {
+            ptr::copy_nonoverlapping(
+                mem::transmute::<&T, *const u8>(&bytes),
+                (&mut self.data[self.offset..]).as_mut_ptr(),
+                num_bytes,
+            );
+        }
+        self.bit_offset = Bits(0);
+        self.offset += num_bytes;
+    }
+
+    /// Encode a primitive into the buffer, naturally aligning it.
+    pub fn encode<T: MojomNumeric>(&mut self, data: T) {
+        self.align_to_byte();
+        self.align_to_bytes(mem::size_of::<T>());
+        self.write(data);
+    }
+
+    /// Encode a boolean value into the buffer as one bit.
+    pub fn encode_bool(&mut self, data: bool) {
+        let offset = self.offset;
+        if data {
+            self.data[offset] |= self.bit_offset.as_set_bit();
+        }
+        self.bit_offset += Bits(1);
+        let (bits, bytes) = self.bit_offset.as_bits_and_bytes();
+        self.offset += bytes;
+        self.bit_offset = bits;
+    }
+
+    /// Encode a null union into the buffer.
+    pub fn encode_null_union(&mut self) {
+        self.align_to_byte();
+        self.align_to_bytes(8);
+        self.write(0 as u32); // Size
+        self.write(0 as u32); // Tag
+        self.write(0 as u64); // Data
+    }
+
+    /// Encode a null pointer into the buffer.
+    pub fn encode_null_pointer(&mut self) {
+        self.align_to_byte();
+        self.align_to_bytes(8);
+        self.encode(MOJOM_NULL_POINTER);
+    }
+
+    /// Encode a null handle into the buffer.
+    pub fn encode_null_handle(&mut self) {
+        self.align_to_byte();
+        self.align_to_bytes(4);
+        self.encode(-1 as i32);
+    }
+
+    /// Encode a non-null pointer into the buffer.
+    ///
+    /// 'location' is an absolute location in the global buffer, but
+    /// Mojom pointers are offsets relative to the pointer, so we
+    /// perform that conversion here before writing.
+    pub fn encode_pointer(&mut self, location: u64) {
+        self.align_to_byte();
+        self.align_to_bytes(8);
+        let current_location = (self.global_offset + self.offset) as u64;
+        debug_assert!(location >= current_location);
+        self.encode(location - current_location);
+    }
+}
+
+/// A struct that will encode a given Mojom object and convert it into
+/// bytes and a vector of handles.
+pub struct Encoder<'slice> {
+    bytes: usize,
+    buffer: Option<&'slice mut [u8]>,
+    states: Vec<EncodingState<'slice>>,
+    handles: Vec<UntypedHandle>,
+}
+
+impl<'slice> Encoder<'slice> {
+    /// Create a new Encoder.
+    pub fn new(buffer: &'slice mut [u8]) -> Encoder<'slice> {
+        Encoder { bytes: 0, buffer: Some(buffer), states: Vec::new(), handles: Vec::new() }
+    }
+
+    /// Get the current encoded size (useful for writing pointers).
+    pub fn size(&self) -> usize {
+        self.bytes
+    }
+
+    /// Start encoding a new object with its data header.
+    ///
+    /// Creates a new encoding state for the object.
+    pub fn add(&mut self, header: &DataHeader) -> Option<Context> {
+        let buf = self.buffer.take().unwrap();
+        if buf.len() < (header.size() as usize) {
+            self.buffer = Some(buf);
+            return None;
+        }
+        let obj_bytes = header.size() as usize;
+        let (claimed, rest) = buf.split_at_mut(obj_bytes);
+        self.states.push(EncodingState::new(claimed, header, self.bytes));
+        self.bytes += obj_bytes;
+        let padding_bytes = align_default(obj_bytes) - obj_bytes;
+        if padding_bytes <= rest.len() {
+            let (_, new_buffer) = rest.split_at_mut(padding_bytes);
+            self.bytes += padding_bytes;
+            self.buffer = Some(new_buffer);
+        } else {
+            self.buffer = Some(rest);
+        }
+        Some(Context::new(self.states.len() - 1))
+    }
+
+    /// Adds a handle and returns an offset to that handle in the
+    /// final handle vector.
+    pub fn add_handle(&mut self, handle: UntypedHandle) -> usize {
+        self.handles.push(handle);
+        self.handles.len() - 1
+    }
+
+    /// Immutably borrow an encoding state via Context.
+    pub fn get(&self, context: &Context) -> &EncodingState<'slice> {
+        &self.states[context.id()]
+    }
+
+    /// Mutably borrow an encoding state via Context.
+    pub fn get_mut(&mut self, context: &Context) -> &mut EncodingState<'slice> {
+        &mut self.states[context.id()]
+    }
+
+    /// Signal to finish encoding by destroying the Encoder and returning the final
+    /// handle vector.
+    ///
+    /// Note: No byte buffer is returned as that is pre-allocated.
+    pub fn unwrap(self) -> Vec<UntypedHandle> {
+        self.handles
+    }
+}
diff --git a/mojo/public/rust/bindings/macros.rs b/mojo/public/rust/bindings/macros.rs
new file mode 100644
index 0000000..63848a5
--- /dev/null
+++ b/mojo/public/rust/bindings/macros.rs
@@ -0,0 +1,160 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+/// This macro provides a common implementation of MojomEncodable
+/// for MojomPointer types.
+///
+/// Note: it does not implement compute_size();
+///
+/// The Rust type system currently lacks the facilities to do this
+/// generically (need mutually excludable traits) but this macro
+/// should be replaced as soon as this is possible.
+#[macro_export]
+macro_rules! impl_encodable_for_pointer {
+    () => {
+        fn mojom_alignment() -> usize {
+            8 // All mojom pointers are 8 bytes in length, and thus are 8-byte aligned
+        }
+        fn mojom_type() -> $crate::bindings::mojom::MojomType {
+            $crate::bindings::mojom::MojomType::Pointer
+        }
+        fn embed_size(
+            _context: &$crate::bindings::encoding::Context,
+        ) -> $crate::bindings::encoding::Bits {
+            $crate::bindings::mojom::POINTER_BIT_SIZE
+        }
+        fn encode(
+            self,
+            encoder: &mut $crate::bindings::encoding::Encoder,
+            context: $crate::bindings::encoding::Context,
+        ) {
+            let loc = encoder.size() as u64;
+            {
+                let state = encoder.get_mut(&context);
+                state.encode_pointer(loc);
+            }
+            self.encode_new(encoder, context);
+        }
+        fn decode(
+            decoder: &mut $crate::bindings::decoding::Decoder,
+            context: $crate::bindings::encoding::Context,
+        ) -> Result<Self, ValidationError> {
+            let ptr = {
+                let state = decoder.get_mut(&context);
+                match state.decode_pointer() {
+                    Some(ptr) => ptr,
+                    None => return Err(ValidationError::IllegalPointer),
+                }
+            };
+            if ptr == $crate::bindings::mojom::MOJOM_NULL_POINTER {
+                Err(ValidationError::UnexpectedNullPointer)
+            } else {
+                Self::decode_new(decoder, context, ptr)
+            }
+        }
+    };
+}
+
+/// This macro provides a common implementation of MojomEncodable
+/// for MojomUnion types.
+///
+/// Note: it does not implement compute_size();
+///
+/// The Rust type system currently lacks the facilities to do this
+/// generically (need mutually excludable traits) but this macro
+/// should be replaced as soon as this is possible.
+#[macro_export]
+macro_rules! impl_encodable_for_union {
+    () => {
+        fn mojom_alignment() -> usize {
+            8
+        }
+        fn mojom_type() -> $crate::bindings::mojom::MojomType {
+            $crate::bindings::mojom::MojomType::Union
+        }
+        fn embed_size(
+            context: &$crate::bindings::encoding::Context,
+        ) -> $crate::bindings::encoding::Bits {
+            if context.is_union() {
+                Self::nested_embed_size()
+            } else {
+                Self::inline_embed_size()
+            }
+        }
+        fn encode(
+            self,
+            encoder: &mut $crate::bindings::encoding::Encoder,
+            context: $crate::bindings::encoding::Context,
+        ) {
+            if context.is_union() {
+                self.nested_encode(encoder, context);
+            } else {
+                self.inline_encode(encoder, context.set_is_union(true));
+            }
+        }
+        fn decode(
+            decoder: &mut $crate::bindings::decoding::Decoder,
+            context: $crate::bindings::encoding::Context,
+        ) -> Result<Self, ValidationError> {
+            if context.is_union() {
+                Self::nested_decode(decoder, context)
+            } else {
+                Self::inline_decode(decoder, context.set_is_union(true))
+            }
+        }
+    };
+}
+
+/// This macro provides a common implementation of MojomEncodable
+/// for MojomInterface types.
+///
+/// Note: it does not implement compute_size();
+///
+/// The Rust type system currently lacks the facilities to do this
+/// generically (need mutually excludable traits) but this macro
+/// should be replaced as soon as this is possible.
+#[macro_export]
+macro_rules! impl_encodable_for_interface {
+    () => {
+        fn mojom_alignment() -> usize {
+            4
+        }
+        fn mojom_type() -> $crate::bindings::mojom::MojomType {
+            $crate::bindings::mojom::MojomType::Interface
+        }
+        fn embed_size(
+            _context: &$crate::bindings::encoding::Context,
+        ) -> $crate::bindings::encoding::Bits {
+            use std::mem;
+            $crate::bindings::encoding::Bits(2 * 8 * mem::size_of::<u32>())
+        }
+        fn compute_size(&self, _context: $crate::bindings::encoding::Context) -> usize {
+            0 // Indicates that this type is inlined and it adds nothing external to the size
+        }
+        fn encode(
+            self,
+            encoder: &mut $crate::bindings::encoding::Encoder,
+            context: $crate::bindings::encoding::Context,
+        ) {
+            let version = self.version();
+            let pos = encoder.add_handle(self.as_untyped());
+            let mut state = encoder.get_mut(&context);
+            state.encode(pos as i32);
+            state.encode(version as u32);
+        }
+        fn decode(
+            decoder: &mut $crate::bindings::decoding::Decoder,
+            context: $crate::bindings::encoding::Context,
+        ) -> Result<Self, ValidationError> {
+            let (handle_index, version) = {
+                let mut state = decoder.get_mut(&context);
+                (state.decode::<i32>(), state.decode::<u32>())
+            };
+            let handle =
+                try!(decoder
+                    .claim_handle::<$crate::system::message_pipe::MessageEndpoint>(handle_index));
+            Ok(Self::with_version(handle, version))
+        }
+    };
+}
diff --git a/mojo/public/rust/bindings/message.rs b/mojo/public/rust/bindings/message.rs
new file mode 100644
index 0000000..9e1a830
--- /dev/null
+++ b/mojo/public/rust/bindings/message.rs
@@ -0,0 +1,99 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use bindings::decoding::{Decoder, ValidationError};
+use bindings::encoding;
+use bindings::encoding::{Context, DataHeaderValue, Encoder, DATA_HEADER_SIZE};
+use bindings::mojom::{MojomEncodable, MojomPointer, MojomStruct};
+
+/// A flag for the message header indicating that no flag has been set.
+pub const MESSAGE_HEADER_NO_FLAG: u32 = 0;
+
+/// A flag for the message header indicating that this message expects
+/// a response.
+pub const MESSAGE_HEADER_EXPECT_RESPONSE: u32 = 1;
+
+/// A flag for the message header indicating that this message is
+/// a response.
+pub const MESSAGE_HEADER_IS_RESPONSE: u32 = 2;
+
+const MESSAGE_HEADER_VERSIONS: [(u32, u32); 2] = [(0, 16), (1, 24)];
+
+/// A message header object implemented as a Mojom struct.
+pub struct MessageHeader {
+    pub version: u32,
+    pub name: u32,
+    pub flags: u32,
+    pub request_id: u64,
+}
+
+impl MessageHeader {
+    /// Create a new MessageHeader.
+    pub fn new(version: u32, name: u32, flags: u32) -> MessageHeader {
+        MessageHeader { version: version, name: name, flags: flags, request_id: 0 }
+    }
+}
+
+impl MojomPointer for MessageHeader {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(self.version)
+    }
+
+    /// Get the serialized size.
+    ///
+    /// This value differs based on whether or not
+    /// a request_id is necessary.
+    fn serialized_size(&self, _context: &Context) -> usize {
+        let mut size = DATA_HEADER_SIZE + 8;
+        if self.flags != MESSAGE_HEADER_NO_FLAG {
+            size += 8;
+        }
+        encoding::align_default(size)
+    }
+
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.name, encoder, context.clone());
+        MojomEncodable::encode(self.flags, encoder, context.clone());
+        if self.version > 0 {
+            MojomEncodable::encode(self.request_id, encoder, context.clone());
+        }
+    }
+
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let mut state = decoder.get_mut(&context);
+        let version = match state.decode_struct_header(&MESSAGE_HEADER_VERSIONS) {
+            Ok(header) => header.data(),
+            Err(err) => return Err(err),
+        };
+        let name = state.decode::<u32>();
+        let flags = state.decode::<u32>();
+        if flags > MESSAGE_HEADER_IS_RESPONSE {
+            return Err(ValidationError::MessageHeaderInvalidFlags);
+        }
+        if version == 0 {
+            if flags == MESSAGE_HEADER_IS_RESPONSE || flags == MESSAGE_HEADER_EXPECT_RESPONSE {
+                return Err(ValidationError::MessageHeaderMissingRequestId);
+            }
+            Ok(MessageHeader { version: version, name: name, flags: flags, request_id: 0 })
+        } else if version == 1 {
+            Ok(MessageHeader {
+                version: version,
+                name: name,
+                flags: flags,
+                request_id: state.decode::<u64>(),
+            })
+        } else {
+            return Err(ValidationError::UnexpectedStructHeader);
+        }
+    }
+}
+
+impl MojomEncodable for MessageHeader {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        self.serialized_size(&context)
+    }
+}
+
+impl MojomStruct for MessageHeader {}
diff --git a/mojo/public/rust/bindings/mod.rs b/mojo/public/rust/bindings/mod.rs
new file mode 100644
index 0000000..b8475b47
--- /dev/null
+++ b/mojo/public/rust/bindings/mod.rs
@@ -0,0 +1,13 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#[macro_use]
+mod macros;
+mod util;
+
+pub mod decoding;
+pub mod encoding;
+pub mod message;
+pub mod mojom;
+pub mod run_loop;
diff --git a/mojo/public/rust/bindings/mojom.rs b/mojo/public/rust/bindings/mojom.rs
new file mode 100644
index 0000000..9ea3f99
--- /dev/null
+++ b/mojo/public/rust/bindings/mojom.rs
@@ -0,0 +1,913 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use bindings::decoding::{Decoder, ValidationError};
+use bindings::encoding;
+use bindings::encoding::{Bits, Context, DataHeader, DataHeaderValue, Encoder, DATA_HEADER_SIZE};
+use bindings::message::MessageHeader;
+
+use std::cmp::Eq;
+use std::collections::HashMap;
+use std::hash::Hash;
+use std::mem;
+use std::panic;
+use std::ptr;
+use std::vec::Vec;
+
+use system::data_pipe;
+use system::message_pipe;
+use system::shared_buffer;
+use system::wait_set;
+use system::{CastHandle, Handle, MojoResult, UntypedHandle};
+
+/// The size of a Mojom map plus header in bytes.
+const MAP_SIZE: usize = 24;
+
+/// The sorted set of versions for a map.
+const MAP_VERSIONS: [(u32, u32); 1] = [(0, MAP_SIZE as u32)];
+
+/// The size of a Mojom union in bytes (header included).
+pub const UNION_SIZE: usize = 16;
+
+/// The size of a Mojom pointer in bits.
+pub const POINTER_BIT_SIZE: Bits = Bits(64);
+
+/// The value of a Mojom null pointer.
+pub const MOJOM_NULL_POINTER: u64 = 0;
+
+/// An enumeration of all the possible low-level Mojom types.
+pub enum MojomType {
+    Simple,
+    Pointer,
+    Union,
+    Handle,
+    Interface,
+}
+
+/// Whatever implements this trait can be serialized in the Mojom format.
+pub trait MojomEncodable: Sized {
+    /// Get the Mojom type.
+    fn mojom_type() -> MojomType;
+
+    /// Get this type's Mojom alignment.
+    fn mojom_alignment() -> usize;
+
+    /// The amount of space in bits the type takes up when inlined
+    /// into another type at serialization time.
+    fn embed_size(context: &Context) -> Bits;
+
+    /// Recursively computes the size of the complete Mojom archive
+    /// starting from this type.
+    fn compute_size(&self, context: Context) -> usize;
+
+    /// Encodes this type into the encoder given a context.
+    fn encode(self, encoder: &mut Encoder, context: Context);
+
+    /// Using a decoder, decodes itself out of a byte buffer.
+    fn decode(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError>;
+}
+
+/// Whatever implements this trait is a Mojom pointer type which means
+/// that on encode, a pointer is inlined and the implementer is
+/// serialized elsewhere in the output buffer.
+pub trait MojomPointer: MojomEncodable {
+    /// Get the DataHeader meta-data for this pointer type.
+    fn header_data(&self) -> DataHeaderValue;
+
+    /// Get the size of only this type when serialized.
+    fn serialized_size(&self, context: &Context) -> usize;
+
+    /// Encodes the actual values of the type into the encoder.
+    fn encode_value(self, encoder: &mut Encoder, context: Context);
+
+    /// Decodes the actual values of the type into the decoder.
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError>;
+
+    /// Writes a pointer inlined into the current context before calling
+    /// encode_value.
+    fn encode_new(self, encoder: &mut Encoder, context: Context) {
+        let data_size = self.serialized_size(&context);
+        let data_header = DataHeader::new(data_size, self.header_data());
+        let new_context = encoder.add(&data_header).unwrap();
+        self.encode_value(encoder, new_context);
+    }
+
+    /// Reads a pointer inlined into the current context before calling
+    /// decode_value.
+    fn decode_new(
+        decoder: &mut Decoder,
+        _context: Context,
+        pointer: u64,
+    ) -> Result<Self, ValidationError> {
+        match decoder.claim(pointer as usize) {
+            Ok(new_context) => Self::decode_value(decoder, new_context),
+            Err(err) => Err(err),
+        }
+    }
+}
+
+/// Whatever implements this trait is a Mojom union type which means that
+/// on encode it is inlined, but if the union is nested inside of another
+/// union type, it is treated as a pointer type.
+pub trait MojomUnion: MojomEncodable {
+    /// Get the union's current tag.
+    fn get_tag(&self) -> u32;
+
+    /// Encode the actual value of the union.
+    fn encode_value(self, encoder: &mut Encoder, context: Context);
+
+    /// Decode the actual value of the union.
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError>;
+
+    /// The embed_size for when the union acts as a pointer type.
+    fn nested_embed_size() -> Bits {
+        POINTER_BIT_SIZE
+    }
+
+    /// The encoding routine for when the union acts as a pointer type.
+    fn nested_encode(self, encoder: &mut Encoder, context: Context) {
+        let loc = encoder.size() as u64;
+        {
+            let state = encoder.get_mut(&context);
+            state.encode_pointer(loc);
+        }
+        let tag = DataHeaderValue::UnionTag(self.get_tag());
+        let data_header = DataHeader::new(UNION_SIZE, tag);
+        let new_context = encoder.add(&data_header).unwrap();
+        self.encode_value(encoder, new_context.set_is_union(true));
+    }
+
+    /// The decoding routine for when the union acts as a pointer type.
+    fn nested_decode(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let global_offset = {
+            let state = decoder.get_mut(&context);
+            match state.decode_pointer() {
+                Some(ptr) => ptr as usize,
+                None => return Err(ValidationError::IllegalPointer),
+            }
+        };
+        if global_offset == (MOJOM_NULL_POINTER as usize) {
+            return Err(ValidationError::UnexpectedNullPointer);
+        }
+        match decoder.claim(global_offset as usize) {
+            Ok(new_context) => Self::decode_value(decoder, new_context),
+            Err(err) => Err(err),
+        }
+    }
+
+    /// The embed_size for when the union is inlined into the current context.
+    fn inline_embed_size() -> Bits {
+        Bits(8 * (UNION_SIZE as usize))
+    }
+
+    /// The encoding routine for when the union is inlined into the current context.
+    fn inline_encode(self, encoder: &mut Encoder, context: Context) {
+        {
+            let mut state = encoder.get_mut(&context);
+            state.align_to_bytes(8);
+            state.encode(UNION_SIZE as u32);
+            state.encode(self.get_tag());
+        }
+        self.encode_value(encoder, context.clone());
+        {
+            let mut state = encoder.get_mut(&context);
+            state.align_to_bytes(8);
+            state.align_to_byte();
+        }
+    }
+
+    /// The decoding routine for when the union is inlined into the current context.
+    fn inline_decode(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        {
+            let mut state = decoder.get_mut(&context);
+            state.align_to_byte();
+            state.align_to_bytes(8);
+        }
+        let value = Self::decode_value(decoder, context.clone());
+        {
+            let mut state = decoder.get_mut(&context);
+            state.align_to_byte();
+            state.align_to_bytes(8);
+        }
+        value
+    }
+}
+
+/// A marker trait that marks Mojo handles as encodable.
+pub trait MojomHandle: CastHandle + MojomEncodable {}
+
+/// Whatever implements this trait is considered to be a Mojom
+/// interface, that is, a message pipe which conforms to some
+/// messaging interface.
+///
+/// We force an underlying message pipe to be used via the pipe()
+/// and unwrap() routines.
+pub trait MojomInterface: MojomEncodable {
+    /// Get the service name for this interface.
+    fn service_name() -> &'static str;
+
+    /// Get the version for this interface.
+    fn version(&self) -> u32;
+
+    /// Access the underlying message pipe for this interface.
+    fn pipe(&self) -> &message_pipe::MessageEndpoint;
+
+    /// Unwrap the interface into its underlying message pipe.
+    fn unwrap(self) -> message_pipe::MessageEndpoint;
+}
+
+/// An error that may occur when sending data over a Mojom interface.
+#[derive(Debug)]
+pub enum MojomSendError {
+    /// Failed to write to the underlying message pipe.
+    FailedWrite(MojoResult),
+
+    /// The version is too old to write the attempted message.
+    OldVersion(u32, u32),
+}
+
+/// Whatever implements this trait is considered to be a Mojom
+/// interface that may send messages of some generic type.
+///
+/// When implementing this trait, the correct way is to specify
+/// a tighter trait bound than MojomMessage that limits the types
+/// available for sending to those that are valid messages available
+/// to the interface.
+///
+/// TODO(mknyszek): Add sending control messages
+pub trait MojomInterfaceSend<R: MojomMessage>: MojomInterface {
+    /// Creates a message.
+    fn create_request(&self, req_id: u64, payload: R) -> (Vec<u8>, Vec<UntypedHandle>) {
+        let mut header = R::create_header();
+        header.request_id = req_id;
+        let header_size = header.compute_size(Default::default());
+        let size = header_size + payload.compute_size(Default::default());
+        let mut buffer: Vec<u8> = Vec::with_capacity(size);
+        buffer.resize(size, 0);
+        let handles = {
+            let (header_buf, rest_buf) = buffer.split_at_mut(header_size);
+            let mut handles = header.serialize(header_buf);
+            handles.extend(payload.serialize(rest_buf).into_iter());
+            handles
+        };
+        (buffer, handles)
+    }
+
+    /// Creates and sends a message, and returns its request ID.
+    fn send_request(&self, req_id: u64, payload: R) -> Result<(), MojomSendError> {
+        if self.version() < R::min_version() {
+            return Err(MojomSendError::OldVersion(self.version(), R::min_version()));
+        }
+        let (buffer, handles) = self.create_request(req_id, payload);
+        match self.pipe().write(&buffer, handles, mpflags!(Write::None)) {
+            MojoResult::Okay => Ok(()),
+            err => Err(MojomSendError::FailedWrite(err)),
+        }
+    }
+}
+
+/// An error that may occur when attempting to recieve a message over a
+/// Mojom interface.
+#[derive(Debug)]
+pub enum MojomRecvError {
+    /// Failed to read from the underlying message pipe.
+    FailedRead(MojoResult),
+
+    /// Failed to validate the buffer during decode.
+    FailedValidation(ValidationError),
+}
+
+/// Whatever implements this trait is considered to be a Mojom
+/// interface that may recieve messages for some interface.
+///
+/// When implementing this trait, specify the container "union" type
+/// which can contain any of the potential messages that may be recieved.
+/// This way, we can return that type and let the user multiplex over
+/// what message was received.
+///
+/// TODO(mknyszek): Add responding to control messages
+pub trait MojomInterfaceRecv: MojomInterface {
+    type Container: MojomMessageOption;
+
+    /// Tries to read a message from a pipe and decodes it.
+    fn recv_response(&self) -> Result<(u64, Self::Container), MojomRecvError> {
+        match self.pipe().read(mpflags!(Read::None)) {
+            Ok((buffer, handles)) => match Self::Container::decode_message(buffer, handles) {
+                Ok((req_id, val)) => Ok((req_id, val)),
+                Err(err) => Err(MojomRecvError::FailedValidation(err)),
+            },
+            Err(err) => Err(MojomRecvError::FailedRead(err)),
+        }
+    }
+}
+
+/// Whatever implements this trait is considered to be a Mojom struct.
+///
+/// Mojom structs are always the root of any Mojom message. Thus, we
+/// provide convenience functions for serialization here.
+pub trait MojomStruct: MojomPointer {
+    /// Given a pre-allocated buffer, the struct serializes itself.
+    fn serialize(self, buffer: &mut [u8]) -> Vec<UntypedHandle> {
+        let mut encoder = Encoder::new(buffer);
+        self.encode_new(&mut encoder, Default::default());
+        encoder.unwrap()
+    }
+
+    /// The struct computes its own size, allocates a buffer, and then
+    /// serializes itself into that buffer.
+    fn auto_serialize(self) -> (Vec<u8>, Vec<UntypedHandle>) {
+        let size = self.compute_size(Default::default());
+        let mut buf = Vec::with_capacity(size);
+        buf.resize(size, 0);
+        let handles = self.serialize(&mut buf);
+        (buf, handles)
+    }
+
+    /// Decode the type from a byte array and a set of handles.
+    fn deserialize(buffer: &[u8], handles: Vec<UntypedHandle>) -> Result<Self, ValidationError> {
+        let mut decoder = Decoder::new(buffer, handles);
+        Self::decode_new(&mut decoder, Default::default(), 0)
+    }
+}
+
+/// Marks a MojomStruct as being capable of being sent across some
+/// Mojom interface.
+pub trait MojomMessage: MojomStruct {
+    fn min_version() -> u32;
+    fn create_header() -> MessageHeader;
+}
+
+/// The trait for a "container" type intended to be used in MojomInterfaceRecv.
+///
+/// This trait contains the decode logic which decodes based on the message header
+/// and returns itself: a union type which may contain any of the possible messages
+/// that may be sent across this interface.
+pub trait MojomMessageOption: Sized {
+    /// Decodes the actual payload of the message.
+    ///
+    /// Implemented by a code generator.
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError>;
+
+    /// Decodes the message header and then the payload, returning a new
+    /// copy of itself and the request ID found in the header.
+    fn decode_message(
+        buffer: Vec<u8>,
+        handles: Vec<UntypedHandle>,
+    ) -> Result<(u64, Self), ValidationError> {
+        let header = try!(MessageHeader::deserialize(&buffer[..], Vec::new()));
+        let payload_buffer = &buffer[header.serialized_size(&Default::default())..];
+        let req_id = header.request_id;
+        let ret = try!(Self::decode_payload(header, payload_buffer, handles));
+        Ok((req_id, ret))
+    }
+}
+
+// ********************************************** //
+// ****** IMPLEMENTATIONS FOR COMMON TYPES ****** //
+// ********************************************** //
+
+macro_rules! impl_encodable_for_prim {
+    ($($prim_type:ty),*) => {
+        $(
+        impl MojomEncodable for $prim_type {
+            fn mojom_type() -> MojomType {
+                MojomType::Simple
+            }
+            fn mojom_alignment() -> usize {
+                mem::size_of::<$prim_type>()
+            }
+            fn embed_size(_context: &Context) -> Bits {
+                Bits(8 * mem::size_of::<$prim_type>())
+            }
+            fn compute_size(&self, _context: Context) -> usize {
+                0 // Indicates that this type is inlined and it adds nothing external to the size
+            }
+            fn encode(self, encoder: &mut Encoder, context: Context) {
+                let mut state = encoder.get_mut(&context);
+                state.encode(self);
+            }
+            fn decode(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+                let mut state = decoder.get_mut(&context);
+                Ok(state.decode::<Self>())
+            }
+        }
+        )*
+    }
+}
+
+impl_encodable_for_prim!(i8, i16, i32, i64, u8, u16, u32, u64, f32, f64);
+
+impl MojomEncodable for bool {
+    fn mojom_alignment() -> usize {
+        panic!("Should never check_decode mojom_alignment of bools (they're bit-aligned)!");
+    }
+    fn mojom_type() -> MojomType {
+        MojomType::Simple
+    }
+    fn embed_size(_context: &Context) -> Bits {
+        Bits(1)
+    }
+    fn compute_size(&self, _context: Context) -> usize {
+        0 // Indicates that this type is inlined and it adds nothing external to the size
+    }
+    fn encode(self, encoder: &mut Encoder, context: Context) {
+        let mut state = encoder.get_mut(&context);
+        state.encode_bool(self);
+    }
+    fn decode(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let mut state = decoder.get_mut(&context);
+        Ok(state.decode_bool())
+    }
+}
+
+// Options should be considered to represent nullability the Mojom IDL.
+// Any type wrapped in an Option type is nullable.
+
+impl<T: MojomEncodable> MojomEncodable for Option<T> {
+    fn mojom_alignment() -> usize {
+        T::mojom_alignment()
+    }
+    fn mojom_type() -> MojomType {
+        T::mojom_type()
+    }
+    fn embed_size(context: &Context) -> Bits {
+        T::embed_size(context)
+    }
+    fn compute_size(&self, context: Context) -> usize {
+        match *self {
+            Some(ref value) => value.compute_size(context),
+            None => 0,
+        }
+    }
+    fn encode(self, encoder: &mut Encoder, context: Context) {
+        match self {
+            Some(value) => value.encode(encoder, context),
+            None => {
+                let mut state = encoder.get_mut(&context);
+                match T::mojom_type() {
+                    MojomType::Pointer => state.encode_null_pointer(),
+                    MojomType::Union => state.encode_null_union(),
+                    MojomType::Handle => state.encode_null_handle(),
+                    MojomType::Interface => {
+                        state.encode_null_handle();
+                        state.encode(0 as u32);
+                    }
+                    MojomType::Simple => panic!("Unexpected simple type in Option!"),
+                }
+            }
+        }
+    }
+    fn decode(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let skipped = {
+            let mut state = decoder.get_mut(&context);
+            match T::mojom_type() {
+                MojomType::Pointer => state.skip_if_null_pointer(),
+                MojomType::Union => state.skip_if_null_union(),
+                MojomType::Handle => state.skip_if_null_handle(),
+                MojomType::Interface => state.skip_if_null_interface(),
+                MojomType::Simple => panic!("Unexpected simple type in Option!"),
+            }
+        };
+        if skipped {
+            Ok(None)
+        } else {
+            match T::decode(decoder, context) {
+                Ok(value) => Ok(Some(value)),
+                Err(err) => Err(err),
+            }
+        }
+    }
+}
+
+macro_rules! impl_pointer_for_array {
+    () => {
+        fn header_data(&self) -> DataHeaderValue {
+            DataHeaderValue::Elements(self.len() as u32)
+        }
+        fn serialized_size(&self, context: &Context) -> usize {
+            DATA_HEADER_SIZE
+                + if self.len() > 0 { (T::embed_size(context) * self.len()).as_bytes() } else { 0 }
+        }
+    };
+}
+
+macro_rules! impl_encodable_for_array {
+    () => {
+        impl_encodable_for_pointer!();
+        fn compute_size(&self, context: Context) -> usize {
+            let mut size = encoding::align_default(self.serialized_size(&context));
+            for elem in self.iter() {
+                size += elem.compute_size(context.clone());
+            }
+            size
+        }
+    };
+}
+
+impl<T: MojomEncodable> MojomPointer for Vec<T> {
+    impl_pointer_for_array!();
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        for elem in self.into_iter() {
+            elem.encode(encoder, context.clone());
+        }
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Vec<T>, ValidationError> {
+        let elems = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_array_header::<T>() {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let mut value = Vec::with_capacity(elems as usize);
+        for _ in 0..elems {
+            match T::decode(decoder, context.clone()) {
+                Ok(elem) => value.push(elem),
+                Err(err) => return Err(err),
+            }
+        }
+        Ok(value)
+    }
+}
+
+impl<T: MojomEncodable> MojomEncodable for Vec<T> {
+    impl_encodable_for_array!();
+}
+
+macro_rules! impl_encodable_for_fixed_array {
+    ($($len:expr),*) => {
+        $(
+        impl<T: MojomEncodable> MojomPointer for [T; $len] {
+            impl_pointer_for_array!();
+            fn encode_value(mut self, encoder: &mut Encoder, context: Context) {
+                let mut panic_error = None;
+                let mut moves = 0;
+                unsafe {
+                    // In order to move elements out of an array we need to replace the
+                    // value with uninitialized memory.
+                    for elem in self.iter_mut() {
+                        let owned_elem = mem::replace(elem, mem::uninitialized());
+                        // We need to handle if an unwinding panic happens to prevent use of
+                        // uninitialized memory...
+                        let next_context = context.clone();
+                        // We assert everything going into this closure is unwind safe. If anything
+                        // is added, PLEASE make sure it is also unwind safe...
+                        let result = panic::catch_unwind(panic::AssertUnwindSafe(|| {
+                            owned_elem.encode(encoder, next_context);
+                        }));
+                        if let Err(err) = result {
+                            panic_error = Some(err);
+                            break;
+                        }
+                        moves += 1;
+                    }
+                    if let Some(err) = panic_error {
+                        for i in moves..self.len() {
+                            ptr::drop_in_place(&mut self[i] as *mut T);
+                        }
+                        // Forget the array to prevent a drop
+                        mem::forget(self);
+                        // Continue unwinding
+                        panic::resume_unwind(err);
+                    }
+                    // We cannot risk drop() getting run on the array values, so we just
+                    // forget self.
+                    mem::forget(self);
+                }
+            }
+            fn decode_value(decoder: &mut Decoder, context: Context) -> Result<[T; $len], ValidationError> {
+                let elems = {
+                    let mut state = decoder.get_mut(&context);
+                    match state.decode_array_header::<T>() {
+                        Ok(header) => header.data(),
+                        Err(err) => return Err(err),
+                    }
+                };
+                if elems != $len {
+                    return Err(ValidationError::UnexpectedArrayHeader);
+                }
+                let mut array: [T; $len];
+                let mut panic_error = None;
+                let mut inits = 0;
+                let mut error = None;
+                unsafe {
+                    // Since we don't force Clone to be implemented on Mojom types
+                    // (mainly due to handles) we need to create this array as uninitialized
+                    // and initialize it manually.
+                    array = mem::uninitialized();
+                    for elem in &mut array[..] {
+                        // When a panic unwinds it may try to read and drop uninitialized
+                        // memory, so we need to catch this. However, we pass mutable state!
+                        // This could be bad as we could observe a broken invariant inside
+                        // of decoder and access it as usual, but we do NOT access decoder
+                        // here, nor do we ever unwind through one of decoder's methods.
+                        // Therefore, it should be safe to assert that decoder is unwind safe.
+                        let next_context = context.clone();
+                        // We assert everything going into this closure is unwind safe. If anything
+                        // is added, PLEASE make sure it is also unwind safe...
+                        let result = panic::catch_unwind(panic::AssertUnwindSafe(|| {
+                            T::decode(decoder, next_context)
+                        }));
+                        match result {
+                            Ok(non_panic_value) => match non_panic_value {
+                                Ok(value) => ptr::write(elem, value),
+                                Err(err) => {
+                                    error = Some(err);
+                                    break;
+                                },
+                            },
+                            Err(err) => {
+                                panic_error = Some(err);
+                                break;
+                            },
+                        }
+                        inits += 1;
+                    }
+                    if panic_error.is_some() || error.is_some() {
+                        // Drop everything that was initialized
+                        for i in 0..inits {
+                            ptr::drop_in_place(&mut array[i] as *mut T);
+                        }
+                        // Forget the array to prevent a drop
+                        mem::forget(array);
+                        if let Some(err) = panic_error {
+                            panic::resume_unwind(err);
+                        }
+                        return Err(error.take().expect("Corrupted stack?"));
+                    }
+                }
+                Ok(array)
+            }
+        }
+        impl<T: MojomEncodable> MojomEncodable for [T; $len] {
+            impl_encodable_for_array!();
+        }
+        )*
+    }
+}
+
+// Unfortunately, we cannot be generic over the length of a fixed array
+// even though its part of the type (this will hopefully be added in the
+// future) so for now we implement encodable for only the first 33 fixed
+// size array types.
+impl_encodable_for_fixed_array!(
+    0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
+    26, 27, 28, 29, 30, 31, 32
+);
+
+impl<T: MojomEncodable> MojomPointer for Box<[T]> {
+    impl_pointer_for_array!();
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        for elem in self.into_vec().into_iter() {
+            elem.encode(encoder, context.clone());
+        }
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Box<[T]>, ValidationError> {
+        match Vec::<T>::decode_value(decoder, context) {
+            Ok(vec) => Ok(vec.into_boxed_slice()),
+            Err(err) => Err(err),
+        }
+    }
+}
+
+impl<T: MojomEncodable> MojomEncodable for Box<[T]> {
+    impl_encodable_for_array!();
+}
+
+// We can represent a Mojom string as just a Rust String type
+// since both are UTF-8.
+impl MojomPointer for String {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Elements(self.len() as u32)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        DATA_HEADER_SIZE + self.len()
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        for byte in self.as_bytes() {
+            byte.encode(encoder, context.clone());
+        }
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<String, ValidationError> {
+        let mut state = decoder.get_mut(&context);
+        let elems = match state.decode_array_header::<u8>() {
+            Ok(header) => header.data(),
+            Err(err) => return Err(err),
+        };
+        let mut value = Vec::with_capacity(elems as usize);
+        for _ in 0..elems {
+            value.push(state.decode::<u8>());
+        }
+        match String::from_utf8(value) {
+            Ok(string) => Ok(string),
+            Err(err) => panic!("Error decoding String: {}", err),
+        }
+    }
+}
+
+impl MojomEncodable for String {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+    }
+}
+
+/// Helper function to clean up duplicate code in HashMap.
+fn array_claim_and_decode_header<T: MojomEncodable>(
+    decoder: &mut Decoder,
+    offset: usize,
+) -> Result<(Context, usize), ValidationError> {
+    let context = match decoder.claim(offset) {
+        Ok(new_context) => new_context,
+        Err(err) => return Err(err),
+    };
+    let elems = {
+        let state = decoder.get_mut(&context);
+        match state.decode_array_header::<T>() {
+            Ok(header) => header.data(),
+            Err(err) => return Err(err),
+        }
+    };
+    Ok((context, elems as usize))
+}
+
+impl<K: MojomEncodable + Eq + Hash, V: MojomEncodable> MojomPointer for HashMap<K, V> {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        MAP_SIZE
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        let elems = self.len();
+        let meta_value = DataHeaderValue::Elements(elems as u32);
+        // We need to move values into this vector because we can't copy the keys.
+        // (Handles are not copyable so MojomEncodable cannot be copyable!)
+        let mut vals_vec = Vec::with_capacity(elems);
+        // Key setup
+        // Write a pointer to the keys array.
+        let keys_loc = encoder.size() as u64;
+        {
+            let state = encoder.get_mut(&context);
+            state.encode_pointer(keys_loc);
+        }
+        // Create the keys data header
+        let keys_bytes = DATA_HEADER_SIZE + (K::embed_size(&context) * elems).as_bytes();
+        let keys_data_header = DataHeader::new(keys_bytes, meta_value);
+        // Claim space for the keys array in the encoder
+        let keys_context = encoder.add(&keys_data_header).unwrap();
+        // Encode keys, setup vals
+        for (key, value) in self.into_iter() {
+            key.encode(encoder, keys_context.clone());
+            vals_vec.push(value);
+        }
+        // Encode vals
+        vals_vec.encode(encoder, context.clone())
+    }
+    fn decode_value(
+        decoder: &mut Decoder,
+        context: Context,
+    ) -> Result<HashMap<K, V>, ValidationError> {
+        let (keys_offset, vals_offset) = {
+            let state = decoder.get_mut(&context);
+            match state.decode_struct_header(&MAP_VERSIONS) {
+                Ok(_) => (),
+                Err(err) => return Err(err),
+            };
+            // Decode the keys pointer and check for overflow
+            let keys_offset = match state.decode_pointer() {
+                Some(ptr) => ptr,
+                None => return Err(ValidationError::IllegalPointer),
+            };
+            // Decode the keys pointer and check for overflow
+            let vals_offset = match state.decode_pointer() {
+                Some(ptr) => ptr,
+                None => return Err(ValidationError::IllegalPointer),
+            };
+            if keys_offset == MOJOM_NULL_POINTER || vals_offset == MOJOM_NULL_POINTER {
+                return Err(ValidationError::UnexpectedNullPointer);
+            }
+            (keys_offset as usize, vals_offset as usize)
+        };
+        let (keys_context, keys_elems) =
+            match array_claim_and_decode_header::<K>(decoder, keys_offset) {
+                Ok((context, elems)) => (context, elems),
+                Err(err) => return Err(err),
+            };
+        let mut keys_vec: Vec<K> = Vec::with_capacity(keys_elems as usize);
+        for _ in 0..keys_elems {
+            let key = match K::decode(decoder, keys_context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            };
+            keys_vec.push(key);
+        }
+        let (vals_context, vals_elems) =
+            match array_claim_and_decode_header::<V>(decoder, vals_offset) {
+                Ok((context, elems)) => (context, elems),
+                Err(err) => return Err(err),
+            };
+        if keys_elems != vals_elems {
+            return Err(ValidationError::DifferentSizedArraysInMap);
+        }
+        let mut map = HashMap::with_capacity(keys_elems as usize);
+        for key in keys_vec.into_iter() {
+            let val = match V::decode(decoder, vals_context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            };
+            map.insert(key, val);
+        }
+        Ok(map)
+    }
+}
+
+impl<K: MojomEncodable + Eq + Hash, V: MojomEncodable> MojomEncodable for HashMap<K, V> {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        let mut size = encoding::align_default(self.serialized_size(&context));
+        // The size of the one array
+        size += DATA_HEADER_SIZE;
+        size += (K::embed_size(&context) * self.len()).as_bytes();
+        size = encoding::align_default(size);
+        // Any extra space used by the keys
+        for (key, _) in self {
+            size += key.compute_size(context.clone());
+        }
+        // Need to re-align after this for the next array
+        size = encoding::align_default(size);
+        // The size of the one array
+        size += DATA_HEADER_SIZE;
+        size += (V::embed_size(&context) * self.len()).as_bytes();
+        size = encoding::align_default(size);
+        // Any extra space used by the values
+        for (_, value) in self {
+            size += value.compute_size(context.clone());
+        }
+        // Align one more time at the end to keep the next object aligned.
+        encoding::align_default(size)
+    }
+}
+
+impl<T: MojomEncodable + CastHandle + Handle> MojomHandle for T {}
+
+macro_rules! impl_encodable_for_handle {
+    ($handle_type:path) => {
+        fn mojom_alignment() -> usize {
+            4
+        }
+        fn mojom_type() -> MojomType {
+            MojomType::Handle
+        }
+        fn embed_size(_context: &Context) -> Bits {
+            Bits(8 * mem::size_of::<u32>())
+        }
+        fn compute_size(&self, _context: Context) -> usize {
+            0
+        }
+        fn encode(self, encoder: &mut Encoder, context: Context) {
+            let pos = encoder.add_handle(self.as_untyped());
+            let mut state = encoder.get_mut(&context);
+            state.encode(pos as i32);
+        }
+        fn decode(
+            decoder: &mut Decoder,
+            context: Context,
+        ) -> Result<$handle_type, ValidationError> {
+            let handle_index = {
+                let mut state = decoder.get_mut(&context);
+                state.decode::<i32>()
+            };
+            decoder.claim_handle::<$handle_type>(handle_index)
+        }
+    };
+}
+
+impl MojomEncodable for UntypedHandle {
+    impl_encodable_for_handle!(UntypedHandle);
+}
+
+impl MojomEncodable for message_pipe::MessageEndpoint {
+    impl_encodable_for_handle!(message_pipe::MessageEndpoint);
+}
+
+impl MojomEncodable for shared_buffer::SharedBuffer {
+    impl_encodable_for_handle!(shared_buffer::SharedBuffer);
+}
+
+impl<T> MojomEncodable for data_pipe::Consumer<T> {
+    impl_encodable_for_handle!(data_pipe::Consumer<T>);
+}
+
+impl<T> MojomEncodable for data_pipe::Producer<T> {
+    impl_encodable_for_handle!(data_pipe::Producer<T>);
+}
+
+impl MojomEncodable for wait_set::WaitSet {
+    impl_encodable_for_handle!(wait_set::WaitSet);
+}
diff --git a/mojo/public/rust/bindings/run_loop.rs b/mojo/public/rust/bindings/run_loop.rs
new file mode 100644
index 0000000..1f50e03
--- /dev/null
+++ b/mojo/public/rust/bindings/run_loop.rs
@@ -0,0 +1,668 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! This module contains a thread-local run-loop.
+//!
+//! The run-loop may have handles and handlers pre-registers
+//! (and in fact, must) in order to keep running. The run-loop
+//! executes until it has no more handles or handlers on itself,
+//! or until it is told to quit via stop().
+//!
+//! The run-loop waits until some signals on some handle is satisfied,
+//! at which point it wakes up and executes the appropriate handler
+//! method. This handler method may then be used to further populate
+//! or de-populate the run-loop.
+//!
+//! As of yet, the run-loop is NOT thread-safe. Although it is useful
+//! to be able to register tasks or handles from one thread onto
+//! another thread's run-loop, this is as-of-yet unsupported, and
+//! Rust should complain loudly when you try to do any threading here.
+
+use std::cell::RefCell;
+use std::cmp::{Eq, Ord, Ordering, PartialEq, PartialOrd};
+use std::collections::BinaryHeap;
+use std::collections::HashMap;
+use std::i64;
+use std::u32;
+use std::vec::Vec;
+
+use system;
+use system::core;
+use system::wait_set;
+use system::{Handle, MojoResult, MOJO_INDEFINITE};
+
+/// Define the equivalent of MOJO_INDEFINITE for absolute deadlines
+const MOJO_INDEFINITE_ABSOLUTE: system::MojoTimeTicks = 0;
+
+// TODO(mknyszek): The numbers below are arbitrary and come from the C++ bindings,
+// and should probably be changed at some point
+
+/// Initial size of the result buffer.
+const INITIAL_WAIT_SET_NUM_RESULTS: usize = 16;
+
+/// Maximum size of the result buffer.
+const MAXIMUM_WAIT_SET_NUM_RESULTS: usize = 256;
+
+/// Thread-local data structure for keeping track of handles to wait on.
+thread_local!(static TL_RUN_LOOP: RefCell<RunLoop<'static, 'static>> = RefCell::new(RunLoop::new()));
+
+/// Token representing handle/callback to wait on for this thread only. This
+/// token only has meaning on the thread in which the handle was registered.
+#[derive(Clone, Debug, PartialEq, Eq, Hash)]
+pub struct Token(u64);
+
+impl Token {
+    /// Get the wait token's "cookie" form, suitable for use in a wait set.
+    fn as_cookie(&self) -> u64 {
+        self.0
+    }
+}
+
+/// Represents the possible error cases that may occur when waiting
+/// on a handle in a RunLoop.
+#[derive(Clone, Debug, PartialEq, Eq)]
+pub enum WaitError {
+    /// The handle has been closed or is otherwise no longer valid.
+    HandleClosed,
+
+    /// The handle is currently busy in some transaction.
+    HandleBusy,
+
+    /// It has been determined that the signals provided will never
+    /// be satisfied for this handle.
+    Unsatisfiable,
+}
+
+/// A trait which defines an interface to be a handler usable by
+/// a RunLoop.
+pub trait Handler {
+    /// Called after a successful wait.
+    fn on_ready(&mut self, runloop: &mut RunLoop, token: Token);
+
+    /// Called after the given deadline expires.
+    fn on_timeout(&mut self, runloop: &mut RunLoop, token: Token);
+
+    /// Called when an unexpected error occurs.
+    fn on_error(&mut self, runloop: &mut RunLoop, token: Token, error: WaitError);
+}
+
+/// A wrapper struct for carrying the handler as well as various information
+/// about it.
+struct HandlerInfo<'h> {
+    /// The handle for which we are waiting.
+    ///
+    /// We keep this handle around so that we may easily re-register.
+    handle: system::MojoHandle,
+
+    /// The handler, boxed up.
+    ///
+    /// The handler is in an Option type because if it is currently being
+    /// used in a callback, we must take ownership to avoid mutability
+    /// cycles. The easiest way to do this is to take() from the Option then
+    /// put it back.
+    handler: Option<Box<Handler + 'h>>,
+
+    /// An absolute deadline in terms of time ticks.
+    ///
+    /// This is the most recently updated deadline that
+    /// we should be watching out for. All others for this
+    /// token may be considered "stale".
+    deadline: system::MojoTimeTicks,
+}
+
+impl<'h> HandlerInfo<'h> {
+    /// Take the handler out of its Option type.
+    pub fn take(&mut self) -> Option<Box<Handler + 'h>> {
+        self.handler.take()
+    }
+
+    /// Put a new handler into the Option type.
+    pub fn give(&mut self, handler: Box<Handler + 'h>) {
+        self.handler = Some(handler);
+    }
+
+    /// Getter for the system::MojoHandle held inside.
+    pub fn handle(&self) -> system::MojoHandle {
+        self.handle
+    }
+
+    /// Getter for the current absolute deadline held inside.
+    pub fn deadline(&self) -> system::MojoTimeTicks {
+        self.deadline
+    }
+
+    /// Setter to update the current absolute deadline.
+    pub fn set_deadline(&mut self, deadline: system::MojoTimeTicks) {
+        self.deadline = deadline
+    }
+}
+
+/// A wrapper struct for carrying the task as well as some information about
+/// it.
+struct TaskInfo<'t> {
+    /// The task, boxed up.
+    closure: Box<FnMut(&mut RunLoop) + 't>,
+
+    /// An absolute deadline in terms of time ticks.
+    ///
+    /// This is the most recently updated deadline that
+    /// we should be watching out for. All others for this
+    /// token may be considered "stale".
+    deadline: system::MojoTimeTicks,
+}
+
+impl<'t> TaskInfo<'t> {
+    /// Executes the task within the info object, consuming it
+    /// in the process.
+    pub fn execute_task(mut self, run_loop: &mut RunLoop) {
+        (*self.closure)(run_loop);
+    }
+
+    /// Getter for the current absolute deadline held inside.
+    pub fn deadline(&self) -> system::MojoTimeTicks {
+        self.deadline
+    }
+}
+
+impl<'t> PartialEq for TaskInfo<'t> {
+    /// Equality for TaskInfo in terms of its deadline
+    fn eq(&self, other: &TaskInfo) -> bool {
+        self.deadline == other.deadline
+    }
+}
+
+impl<'t> Eq for TaskInfo<'t> {}
+
+impl<'t> PartialOrd for TaskInfo<'t> {
+    /// Partial comparison for TaskInfo in terms of its deadline
+    ///
+    /// Reverses the comparison because the Rust std library only
+    /// offers a max-heap, and we need a min-heap.
+    fn partial_cmp(&self, other: &TaskInfo) -> Option<Ordering> {
+        other.deadline.partial_cmp(&self.deadline)
+    }
+}
+
+impl<'t> Ord for TaskInfo<'t> {
+    /// Implement comparisons for Task Info.
+    ///
+    /// Reverses the comparison because the Rust std library only
+    /// offers a max-heap, and we need a min-heap.
+    fn cmp(&self, other: &Self) -> Ordering {
+        other.deadline.cmp(&self.deadline)
+    }
+}
+
+/// Wrapper struct intended to be used in a priority queue
+/// for efficiently retrieving the next closest deadline.
+#[derive(Clone)]
+struct DeadlineInfo {
+    /// The ID of the associated Handler struct in the RunLoop's
+    /// hash map.
+    token: Token,
+
+    /// An absolute deadline in terms of time ticks.
+    deadline: system::MojoTimeTicks,
+}
+
+impl DeadlineInfo {
+    /// Getter for an immutable borrow for the token inside.
+    pub fn token(&self) -> &Token {
+        &self.token
+    }
+
+    /// Getter for the absolute deadline inside.
+    pub fn deadline(&self) -> system::MojoTimeTicks {
+        self.deadline
+    }
+}
+
+impl PartialEq for DeadlineInfo {
+    /// Equality for DeadlineInfo in terms of its deadline
+    fn eq(&self, other: &DeadlineInfo) -> bool {
+        self.deadline == other.deadline
+    }
+}
+
+impl Eq for DeadlineInfo {}
+
+impl PartialOrd for DeadlineInfo {
+    /// Partial comparison for DeadlineInfo in terms of its deadline
+    ///
+    /// Reverses the comparison because the Rust std library only
+    /// offers a max-heap, and we need a min-heap.
+    fn partial_cmp(&self, other: &DeadlineInfo) -> Option<Ordering> {
+        other.deadline.partial_cmp(&self.deadline)
+    }
+}
+
+impl Ord for DeadlineInfo {
+    /// Implement comparisons for Deadline Info.
+    ///
+    /// Reverses the comparison because the Rust std library only
+    /// offers a max-heap, and we need a min-heap.
+    fn cmp(&self, other: &Self) -> Ordering {
+        other.deadline.cmp(&self.deadline)
+    }
+}
+
+/// Convert a mojo deadline (which is a relative deadline to "now") to
+/// an absolute deadline based on time ticks.
+fn absolute_deadline(deadline: system::MojoDeadline) -> system::MojoTimeTicks {
+    if deadline == MOJO_INDEFINITE {
+        return MOJO_INDEFINITE_ABSOLUTE;
+    }
+    let mut converted = MOJO_INDEFINITE_ABSOLUTE;
+    let max_time_ticks = i64::MAX as system::MojoDeadline;
+    if deadline <= max_time_ticks {
+        let now = core::get_time_ticks_now();
+        if deadline <= (max_time_ticks - (now as u64)) {
+            converted = (deadline as system::MojoTimeTicks) + now
+        }
+    }
+    converted
+}
+
+/// Convert an absolute deadline to a mojo deadline which is relative to some
+/// notion of "now".
+///
+/// If the deadline is earlier than "now", this routine rounds up to "now".
+fn relative_deadline(
+    deadline: system::MojoTimeTicks,
+    now: system::MojoTimeTicks,
+) -> system::MojoDeadline {
+    if deadline == MOJO_INDEFINITE_ABSOLUTE {
+        MOJO_INDEFINITE
+    } else if now >= deadline {
+        0
+    } else {
+        (deadline - now) as system::MojoDeadline
+    }
+}
+
+/// This structure contains all information necessary to wait on handles
+/// asynchronously.
+///
+/// Ultimately, it should only be a singleton living in
+/// thread-local storage.
+pub struct RunLoop<'h, 't> {
+    /// Running count of the next available token slot.
+    token_count: u64,
+
+    /// A map of handlers.
+    ///
+    /// TODO(mknyszek): Try out a Slab allocator instead of a hashmap.
+    handlers: HashMap<Token, HandlerInfo<'h>>,
+
+    /// A min-heap of delayed tasks in order to pull the soonest task to
+    /// execute efficiently.
+    tasks: BinaryHeap<TaskInfo<'t>>,
+
+    /// A min-heap containing deadlines in order to pull out the soonest
+    /// deadline efficiently.
+    ///
+    /// Warning: may contain "stale" deadlines which are not kept in the
+    /// map!
+    deadlines: BinaryHeap<DeadlineInfo>,
+
+    /// The Mojo structure keeping track of handles and signals.
+    ///
+    /// This structure must be kept in sync with handlers.
+    handle_set: wait_set::WaitSet,
+
+    /// A flag that tells the RunLoop whether it should quit.
+    should_quit: bool,
+
+    /// A flag that indicates whether the RunLoop is running or now
+    running: bool,
+}
+
+impl<'h, 't> RunLoop<'h, 't> {
+    /// Create a new RunLoop.
+    pub fn new() -> RunLoop<'h, 't> {
+        RunLoop {
+            token_count: 0,
+            handlers: HashMap::new(),
+            tasks: BinaryHeap::new(),
+            deadlines: BinaryHeap::new(),
+            handle_set: wait_set::WaitSet::new(wsflags!(Create::None)).unwrap(),
+            should_quit: false,
+            running: false,
+        }
+    }
+
+    /// Generate a new Token for this RunLoop
+    fn generate_token(&mut self) -> Token {
+        self.token_count = self.token_count.wrapping_add(1);
+        Token(self.token_count)
+    }
+
+    /// Adds a new entry to the runloop queue.
+    pub fn register<H>(
+        &mut self,
+        handle: &Handle,
+        signals: system::HandleSignals,
+        deadline: system::MojoDeadline,
+        handler: H,
+    ) -> Token
+    where
+        H: Handler + 'h,
+    {
+        let token = self.generate_token();
+        let abs_deadline = absolute_deadline(deadline);
+        self.handle_set.add(handle, signals, token.as_cookie(), wsflags!(Add::None));
+        self.deadlines.push(DeadlineInfo { token: token.clone(), deadline: abs_deadline });
+        debug_assert!(!self.handlers.contains_key(&token));
+        self.handlers.insert(
+            token.clone(),
+            HandlerInfo {
+                handle: handle.get_native_handle(),
+                handler: Some(Box::new(handler)),
+                deadline: abs_deadline,
+            },
+        );
+        token
+    }
+
+    /// Updates the signals and deadline of an existing handler in the
+    /// runloop via token. The token remains unchanged and valid.
+    ///
+    /// Returns true on a successful update and false if the token was not
+    /// found.
+    pub fn reregister(
+        &mut self,
+        token: &Token,
+        signals: system::HandleSignals,
+        deadline: system::MojoDeadline,
+    ) -> bool {
+        match self.handlers.get_mut(&token) {
+            Some(info) => {
+                let _result = self.handle_set.remove(token.as_cookie());
+                debug_assert_eq!(_result, MojoResult::Okay);
+                let abs_deadline = absolute_deadline(deadline);
+                // Update what deadline we should be looking for, rendering
+                // all previously set deadlines "stale".
+                info.set_deadline(abs_deadline);
+                // Add a new deadline
+                self.deadlines.push(DeadlineInfo { token: token.clone(), deadline: abs_deadline });
+                // Acquire the raw handle held by the HandlerInfo in order to
+                // call the wait_set's add method. Invalidate it immediately after
+                // in order to prevent the handle from being closed.
+                //
+                // It's perfectly okay for the handle to be invalid, so although this
+                // is all unsafe, the whole system should just call the handler with an
+                // error.
+                let mut dummy = unsafe { system::acquire(info.handle()) };
+                self.handle_set.add(&dummy, signals, token.as_cookie(), wsflags!(Add::None));
+                unsafe {
+                    dummy.invalidate();
+                }
+                true
+            }
+            None => false,
+        }
+    }
+
+    /// Removes an entry from the runloop.
+    ///
+    /// Since we cannot remove from the deadlines heap, we just leave the deadline
+    /// in there as "stale", and we handle those when trying to find the next closest
+    /// deadline.
+    pub fn deregister(&mut self, token: Token) -> bool {
+        match self.handlers.remove(&token) {
+            Some(_) => {
+                let _result = self.handle_set.remove(token.as_cookie());
+                debug_assert_eq!(_result, MojoResult::Okay);
+                true
+            }
+            None => false,
+        }
+    }
+
+    /// Adds a task to be run by the runloop after some delay.
+    ///
+    /// Returns a token if the delay is valid, otherwise returns None.
+    pub fn post_task<F>(&mut self, task: F, delay: system::MojoTimeTicks) -> Result<(), ()>
+    where
+        F: FnMut(&mut RunLoop) + 't,
+    {
+        let now = core::get_time_ticks_now();
+        if delay > i64::MAX - now {
+            return Err(());
+        }
+        let deadline = now + delay;
+        self.tasks.push(TaskInfo { closure: Box::new(task), deadline: deadline });
+        Ok(())
+    }
+
+    /// Uses the binary heaps to get the next closest deadline.
+    ///
+    /// Removes stale deadline entries as they are found, but
+    /// does not otherwise modify the heap of deadlines.
+    fn get_next_deadline(&mut self) -> system::MojoTimeTicks {
+        debug_assert!(!self.handlers.is_empty());
+        let top_task_deadline = match self.tasks.peek() {
+            Some(info) => info.deadline(),
+            None => MOJO_INDEFINITE_ABSOLUTE,
+        };
+        let mut top = match self.deadlines.peek() {
+            Some(info) => info.clone(),
+            None => return MOJO_INDEFINITE_ABSOLUTE,
+        };
+        while !self.handlers.contains_key(top.token()) {
+            self.deadlines.pop();
+            top = match self.deadlines.peek() {
+                Some(info) => info.clone(),
+                None => return MOJO_INDEFINITE_ABSOLUTE,
+            }
+        }
+        if top_task_deadline != MOJO_INDEFINITE_ABSOLUTE && top_task_deadline < top.deadline() {
+            top_task_deadline
+        } else {
+            top.deadline()
+        }
+    }
+
+    /// Gets a handler by token to be manipulated in a consistent environment.
+    ///
+    /// This method provides a method of accessing a handler in order to manipulate
+    /// it in a manner that avoids a borrow cycle, that is, it take()s the handler
+    /// out of the HashMap, and returns it when manipulation has completed.
+    fn get_handler_with<F>(&mut self, token: &Token, invoker: F)
+    where
+        F: FnOnce(&mut Self, &mut Box<Handler + 'h>, Token, system::MojoTimeTicks),
+    {
+        // Logic for pulling out the handler as well as its current deadline.
+        //
+        // Unfortunately, pulling out the handler value here and "onto the stack"
+        // (it probably won't actually end up on the stack thanks to optimizations)
+        // is necessary since otherwise the borrow checker complains that we pass
+        // a mutable reference to the RunLoop and the handler (as &mut self) to
+        // the callbacks at the same time. This is understandably unsafe since
+        // modifying the hashmap with register and deregister can invalidate the
+        // reference to self in the callback. In the C++ bindings and in other Rust
+        // event loops this is exactly what happens, but I avoided this. The downside
+        // is that we can no longer nest event loop run() calls. Once we put a handler
+        // onto the stack here, we can no longer call its callback in a nested manner
+        // from the RunLoop. I could just enable nesting with this one restriction, that
+        // the handler calling run() will always be ignored, but this is unintuitive.
+        let (mut handler, deadline) = match self.handlers.get_mut(&token) {
+            Some(ref_info) => (
+                match ref_info.take() {
+                    Some(handler) => handler,
+                    None => return,
+                },
+                ref_info.deadline(),
+            ),
+            None => return,
+        };
+        // Call the closure that will invoke the callbacks.
+        invoker(self, &mut handler, token.clone(), deadline);
+        // Restore the handler to its location in the HashMap
+        if let Some(ref_info) = self.handlers.get_mut(&token) {
+            ref_info.give(handler);
+        }
+    }
+
+    /// For all the results we received, we notify the respective handle
+    /// owners of the results by calling their given callbacks.
+    ///
+    /// We do NOT dequeue notified handles.
+    fn notify_of_results(&mut self, results: &Vec<system::WaitSetResult>) {
+        debug_assert!(!self.handlers.is_empty());
+        for wsr in results.iter() {
+            let token = Token(wsr.cookie());
+            self.get_handler_with(&token, move |runloop, boxed_handler, token, _dl| {
+                let handler = boxed_handler.as_mut();
+                match wsr.result() {
+                    MojoResult::Okay => handler.on_ready(runloop, token),
+                    MojoResult::Cancelled => {
+                        handler.on_error(runloop, token, WaitError::HandleClosed)
+                    }
+                    MojoResult::Busy => handler.on_error(runloop, token, WaitError::HandleBusy),
+                    MojoResult::FailedPrecondition => {
+                        handler.on_error(runloop, token, WaitError::Unsatisfiable)
+                    }
+                    other => panic!("Unexpected result received after waiting: {}", other),
+                }
+            });
+            // In order to quit as soon as possible, we should check to quit after every
+            // potential handler call, as any of them could have signaled to quit.
+            if self.should_quit {
+                break;
+            }
+        }
+    }
+
+    /// Since the deadline expired, we notify the relevant handle
+    /// owners of the expiration by calling their given callbacks.
+    ///
+    /// We do NOT dequeue notified handles.
+    fn notify_of_expired(&mut self, expired_deadline: system::MojoTimeTicks) {
+        debug_assert!(!self.handlers.is_empty());
+        let mut top = match self.deadlines.peek() {
+            Some(info) => info.clone(),
+            None => panic!("Should not be in notify_of_expired without at least one deadline!"),
+        };
+        while expired_deadline >= top.deadline() {
+            let next_deadline = top.deadline();
+            self.get_handler_with(
+                top.token(),
+                move |runloop, boxed_handler, token, expected_dl| {
+                    let handler = boxed_handler.as_mut();
+                    if next_deadline == expected_dl {
+                        handler.on_timeout(runloop, token);
+                    }
+                },
+            );
+            // In order to quit as soon as possible, we should check to quit after every
+            // potential handler call, as any of them could have signaled to quit.
+            if self.should_quit {
+                break;
+            }
+            // Remove the deadline
+            self.deadlines.pop();
+            // Break if the next deadline has not yet expired.
+            top = match self.deadlines.peek() {
+                Some(info) => info.clone(),
+                None => break,
+            };
+        }
+    }
+
+    /// Iterates through all tasks whose deadline has passed and executes
+    /// them, consuming their information object.
+    ///
+    /// These tasks all have access to the RunLoop so that they may reschedule
+    /// themselves or manipulate the RunLoop in some other way.
+    fn execute_ready_tasks(&mut self) {
+        let now = core::get_time_ticks_now();
+        let mut deadline = match self.tasks.peek() {
+            Some(info) => info.deadline(),
+            None => return,
+        };
+        while deadline < now {
+            let top = self.tasks.pop().expect("Sudden change to heap?");
+            top.execute_task(self);
+            if self.should_quit {
+                return;
+            }
+            deadline = match self.tasks.peek() {
+                Some(info) => info.deadline(),
+                None => return,
+            };
+        }
+    }
+
+    /// Blocks on handle_set.wait_on_set using the information contained
+    /// within itself.
+    ///
+    /// This method blocks for only as long as the shortest deadline among all
+    /// handles this thread has registered. This method returns immediately as
+    /// soon as any one handle has its signals satisfied, fails to ever have its
+    /// signals satisfied, or reaches its deadline.
+    fn wait(&mut self, results_buffer: &mut Vec<system::WaitSetResult>) {
+        debug_assert!(!self.handlers.is_empty());
+        self.execute_ready_tasks();
+        // If after executing a task we quit or there are no handles,
+        // we have no reason to continue.
+        if self.handlers.is_empty() || self.should_quit {
+            return;
+        }
+        let deadline = self.get_next_deadline();
+        let until_deadline = relative_deadline(deadline, core::get_time_ticks_now());
+        // Perform the wait
+        match self.handle_set.wait_on_set(until_deadline, results_buffer) {
+            Ok(max_results) => {
+                self.notify_of_results(results_buffer);
+                // Clear the buffer since we don't need the results anymore.
+                // Helps prevent a copy if we resize the buffer.
+                results_buffer.clear();
+                // Increase the size of the buffer if there are more results
+                // we could be holding.
+                let capacity = results_buffer.capacity();
+                if capacity < MAXIMUM_WAIT_SET_NUM_RESULTS && capacity < (max_results) as usize {
+                    results_buffer.reserve(capacity);
+                }
+            }
+            Err(result) => {
+                assert_eq!(result, MojoResult::DeadlineExceeded);
+                self.notify_of_expired(deadline);
+            }
+        }
+    }
+
+    /// Loop forever until a callback tells us to quit.
+    pub fn run(&mut self) {
+        // It's an error it already be running...
+        if self.running {
+            panic!("RunLoop is already running!");
+        }
+        self.running = true;
+        self.should_quit = false;
+        let mut buffer: Vec<system::WaitSetResult> =
+            Vec::with_capacity(INITIAL_WAIT_SET_NUM_RESULTS);
+        // Loop while we haven't been signaled to quit, and there's something to wait on.
+        while !self.should_quit && !self.handlers.is_empty() {
+            self.wait(&mut buffer)
+        }
+        self.running = false;
+    }
+
+    /// Set a flag to quit at the next available moment.
+    pub fn quit(&mut self) {
+        self.should_quit = true;
+    }
+}
+
+/// Provides a scope to modify the current thread's runloop.
+pub fn with_current<F>(modifier: F)
+where
+    F: FnOnce(&mut RunLoop),
+{
+    TL_RUN_LOOP.with(|ref_runloop| {
+        let mut runloop = ref_runloop.borrow_mut();
+        modifier(&mut *runloop);
+    });
+}
diff --git a/mojo/public/rust/bindings/util.rs b/mojo/public/rust/bindings/util.rs
new file mode 100644
index 0000000..208a5d7
--- /dev/null
+++ b/mojo/public/rust/bindings/util.rs
@@ -0,0 +1,49 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! This module contains some useful functions for encoding.
+
+/// Given some size value, the size is aligned to some number in bytes.
+///
+/// Neither the size nor bytes may be zero (those are always aligned) and
+/// bytes must be a power of two (other alignments don't make sense).
+pub fn align_bytes(size: usize, bytes: usize) -> usize {
+    debug_assert!(bytes != 0);
+    debug_assert!((bytes & (!bytes + 1)) == bytes);
+    (size + bytes - 1) & (!(bytes - 1))
+}
+
+/// Converts some number of bits into however many bytes are needed to
+/// represent that bit size.
+pub fn bits_to_bytes(bits: usize) -> usize {
+    ((bits + 7) >> 3)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::align_bytes;
+    use super::bits_to_bytes;
+
+    #[test]
+    fn check_align_bytes() {
+        assert_eq!(align_bytes(12, 8), 16);
+        assert_eq!(align_bytes(16, 4), 16);
+        assert_eq!(align_bytes(1, 1), 1);
+    }
+
+    #[test]
+    #[should_panic]
+    fn check_bad_align_bytes() {
+        assert_eq!(align_bytes(15, 7), 21);
+        assert_eq!(align_bytes(2, 0), 0);
+    }
+
+    #[test]
+    fn check_bits_to_bytes() {
+        assert_eq!(bits_to_bytes(8), 1);
+        assert_eq!(bits_to_bytes(0), 0);
+        assert_eq!(bits_to_bytes(1), 1);
+        assert_eq!(bits_to_bytes(21), 3);
+    }
+}
diff --git a/mojo/public/rust/lib.rs b/mojo/public/rust/lib.rs
new file mode 100644
index 0000000..f28143d
--- /dev/null
+++ b/mojo/public/rust/lib.rs
@@ -0,0 +1,143 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#[macro_use]
+mod macros {
+    /// This macro must be used at the top-level in any
+    /// Rust Mojo application. It defines and abstracts away the
+    /// hook needed by Mojo in order to set up the basic
+    /// functionality (see mojo::system::ffi). It must take the
+    /// name of a function who returns a MojoResult and takes
+    /// exactly one argument: a mojo::handle::Handle, or on in
+    /// other words, an untyped handle.
+    #[macro_export]
+    macro_rules! set_mojo_main {
+        ( $fn_main:ident ) => {
+            #[allow(bad_style)]
+            #[no_mangle]
+            pub fn MojoMain(app_request_handle: mojo::system::MojoHandle) -> mojo::MojoResult {
+                use mojo::system::CastHandle;
+                use std::panic;
+                let handle = unsafe {
+                    mojo::system::message_pipe::MessageEndpoint::from_untyped(
+                        mojo::system::acquire(app_request_handle),
+                    )
+                };
+                let result = panic::catch_unwind(|| $fn_main(handle));
+                match result {
+                    Ok(value) => value,
+                    Err(_) => mojo::MojoResult::Aborted,
+                }
+            }
+        };
+    }
+
+    /// This macro assists in generating flags for
+    /// functions and methods found in mojo::system::message_pipe.
+    ///
+    /// See mojo::system::message_pipe for the available flags
+    /// that may be passed.
+    ///
+    /// # Examples
+    ///
+    /// # mpflags!(Create::None);
+    /// # mpflags!(Read::MayDiscard);
+    #[macro_export]
+    macro_rules! mpflags {
+        ( $( $flag:path ),* ) => {{
+            use $crate::system::message_pipe::*;
+            $(
+                ($flag as u32)
+            )|*
+        }}
+    }
+
+    /// This macro assists in generating flags for
+    /// functions and methods found in mojo::system::data_pipe.
+    ///
+    /// See mojo::system::data_pipe for the available flags
+    /// that may be passed.
+    ///
+    /// # Examples
+    ///
+    /// # dpflags!(Create::None);
+    /// # dpflags!(Read::AllOrNone, Read::Discard);
+    #[macro_export]
+    macro_rules! dpflags {
+        ( $( $flag:path ),* ) => {{
+            use $crate::system::data_pipe::*;
+            $(
+                ($flag as u32)
+            )|*
+        }}
+    }
+
+    /// This macro assists in generating flags for
+    /// functions and methods found in mojo::system::shared_buffer.
+    ///
+    /// See mojo::system::shared_buffer for the available flags
+    /// that may be passed.
+    ///
+    /// # Examples
+    ///
+    /// # sbflags!(Create::None);
+    /// # sbflags!(Map::None);
+    #[macro_export]
+    macro_rules! sbflags {
+        ( $( $flag:path ),* ) => {{
+            use $crate::system::shared_buffer::*;
+            $(
+                ($flag as u32)
+            )|*
+        }}
+    }
+
+    /// This macro assists in generating flags for
+    /// functions and methods found in mojo::system::wait_set.
+    ///
+    /// See mojo::system::wait_set for the available flags
+    /// that may be passed.
+    ///
+    /// # Examples
+    ///
+    /// # wsflags!(Create::None);
+    /// # wsflags!(Add::None);
+    #[macro_export]
+    macro_rules! wsflags {
+        ( $( $flag:path ),* ) => {{
+            use $crate::system::wait_set::*;
+            $(
+                ($flag as u32)
+            )|*
+        }}
+    }
+
+    /// This macro assists in generating MojoSignals to be
+    /// used in wait() and wait_many(), part of mojo::system::core.
+    ///
+    /// See mojo::system::handle for the available signals
+    /// that may be checked for by wait() and wait_many().
+    ///
+    /// # Examples
+    ///
+    /// # signals!(Signals::Readable, Signals::Writable);
+    /// # signals!(Signals::PeerClosed);
+    #[macro_export]
+    macro_rules! signals {
+        ( $( $flag:path ),* ) => {{
+            use $crate::system::Signals;
+            $crate::system::HandleSignals::new(
+            $(
+                ($flag as u32)
+            )|*
+            )
+        }}
+    }
+}
+
+#[macro_use]
+pub mod bindings;
+pub mod system;
+
+pub use system::MojoResult;
diff --git a/mojo/public/rust/system/core.rs b/mojo/public/rust/system/core.rs
new file mode 100644
index 0000000..9a958ea
--- /dev/null
+++ b/mojo/public/rust/system/core.rs
@@ -0,0 +1,66 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use std::ptr;
+use std::u32;
+use std::vec;
+
+use system::ffi;
+// This full import is intentional; nearly every type in mojo_types needs to be used.
+use system::handle;
+use system::mojo_types::*;
+
+/// Get the time ticks now according to the Mojo IPC. As
+/// can be seen in the documentation for the Mojo C API,
+/// time ticks are meaningless in an absolute sense. Instead,
+/// one should compare the results of two of these calls to
+/// get a proper notion of time passing.
+pub fn get_time_ticks_now() -> MojoTimeTicks {
+    unsafe { ffi::MojoGetTimeTicksNow() }
+}
+
+/// Waits on many handles (or rather any structures that wrap
+/// handles) until the signals declared in 'signals' for each handle
+/// are triggered, waiting for a maximum global time of 'deadline'.
+/// This function blocks.
+pub fn wait_many(
+    handles: &[&handle::Handle],
+    signals: &[HandleSignals],
+    states: &mut [SignalsState],
+    deadline: MojoDeadline,
+) -> (i32, MojoResult) {
+    assert_eq!(handles.len(), signals.len());
+    assert!(states.len() == handles.len() || states.len() == 0);
+    let num_inputs = handles.len();
+    if num_inputs == 0 {
+        let result = MojoResult::from_code(unsafe {
+            ffi::MojoWaitMany(
+                ptr::null(),
+                ptr::null(),
+                0,
+                deadline,
+                ptr::null_mut(),
+                ptr::null_mut(),
+            )
+        });
+        return (-1, result);
+    }
+    let states_ptr = if states.len() != 0 { states.as_mut_ptr() } else { ptr::null_mut() };
+    let mut index: u32 = u32::MAX;
+    let result = unsafe {
+        let mut raw_handles: vec::Vec<MojoHandle> = vec::Vec::with_capacity(num_inputs);
+        for handle in handles.iter() {
+            raw_handles.push(handle.get_native_handle())
+        }
+        MojoResult::from_code(ffi::MojoWaitMany(
+            raw_handles.as_ptr(),
+            signals.as_ptr(),
+            num_inputs as u32,
+            deadline,
+            &mut index as *mut u32,
+            states_ptr,
+        ))
+    };
+    (index as i32, result)
+}
diff --git a/mojo/public/rust/system/data_pipe.rs b/mojo/public/rust/system/data_pipe.rs
new file mode 100644
index 0000000..d9a4061
--- /dev/null
+++ b/mojo/public/rust/system/data_pipe.rs
@@ -0,0 +1,449 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use std::marker;
+use std::mem;
+use std::ops;
+use std::ptr;
+use std::slice;
+use std::vec;
+
+use system::ffi;
+// This full import is intentional; nearly every type in mojo_types needs to be used.
+use system::handle;
+use system::handle::{CastHandle, Handle};
+use system::mojo_types::*;
+
+#[repr(u32)]
+/// Create flags for data pipes
+pub enum Create {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Write flags for data pipes
+pub enum Write {
+    None = 0,
+
+    /// Write all the data to the pipe if possible or none at all
+    AllOrNone = 1 << 0,
+}
+
+#[repr(u32)]
+/// Read flags for data pipes
+pub enum Read {
+    None = 0,
+
+    /// Read all the data from the pipe if possible, or none at all
+    AllOrNone = 1 << 0,
+
+    /// Dequeue the message recieved rather than reading it
+    Discard = 1 << 1,
+
+    /// Get information about the queue on the pipe but do not perform the
+    /// read
+    Query = 1 << 2,
+
+    /// Read data off the pipe's queue but do not dequeue it
+    Peek = 1 << 3,
+}
+
+/// Intermediary structure in a two-phase read.
+/// Reads of the requested buffer must be done directly
+/// through this data structure which must then be committed.
+pub struct ReadDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    buffer: &'b [T],
+
+    /// Contains a reference to parent to end commit
+    /// and prevent it from outliving its parent handle.
+    parent: &'p Consumer<T>,
+}
+
+impl<'b, 'p, T> ReadDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    /// Attempts to commit the read, that is, end the two-phase read
+    /// started by the parent Consumer<T> object. On a successful
+    /// commit, consumes self, otherwise returns self to try again.
+    pub fn commit(self, bytes_read: usize) -> Option<(Self, MojoResult)> {
+        let result = unsafe { self.parent.end_read(bytes_read) };
+        if result == MojoResult::Okay {
+            None
+        } else {
+            Some((self, result))
+        }
+    }
+
+    /// Returns the length of the underlying buffer
+    pub fn len(&self) -> usize {
+        self.buffer.len()
+    }
+}
+
+impl<'b, 'p, T> ops::Index<usize> for ReadDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    type Output = T;
+
+    /// Overloads the indexing ([]) operator for reads.
+    ///
+    /// Part of reimplementing the array interface to be
+    /// able to use the structure naturally.
+    fn index(&self, index: usize) -> &T {
+        &self.buffer[index]
+    }
+}
+
+/// Intermediary structure in a two-phase write.
+/// Writes to the requested buffer must be done directly
+/// through this data structure which must then be committed.
+pub struct WriteDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    buffer: &'b mut [T],
+
+    /// Contains a reference to parent to end commit
+    /// and prevent it from outliving its parent handle.
+    parent: &'p Producer<T>,
+}
+
+impl<'b, 'p, T> WriteDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    /// Attempts to commit the write, that is, end the two-phase
+    /// write started by a Producer. On a successful
+    /// commit, consumes self, otherwise returns self to try again.
+    pub fn commit(self, bytes_written: usize) -> Option<(Self, MojoResult)> {
+        let result = unsafe { self.parent.end_write(bytes_written) };
+        if result == MojoResult::Okay {
+            None
+        } else {
+            Some((self, result))
+        }
+    }
+
+    /// Returns the length of the underlying buffer
+    pub fn len(&self) -> usize {
+        self.buffer.len()
+    }
+}
+
+impl<'b, 'p, T> ops::Index<usize> for WriteDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    type Output = T;
+
+    /// Overloads the indexing ([]) operator for reads.
+    ///
+    /// Part of reimplementing the array interface to be
+    /// able to use the structure naturally.
+    fn index(&self, index: usize) -> &T {
+        &self.buffer[index]
+    }
+}
+
+impl<'b, 'p, T> ops::IndexMut<usize> for WriteDataBuffer<'b, 'p, T>
+where
+    'p: 'b,
+    T: 'p,
+{
+    /// Overloads the indexing ([]) operator for writes.
+    ///
+    /// Part of reimplementing the array interface to be
+    /// able to use the structure naturally.
+    fn index_mut(&mut self, index: usize) -> &mut T {
+        &mut self.buffer[index]
+    }
+}
+
+/// Creates a data pipe, represented as a consumer
+/// and a producer. Additionally, we associate a type
+/// T with the data pipe, as data pipes operate in terms
+/// of elements. In this way we can enforce type safety.
+///
+/// Capacity, as an input, must be given in number of elements.
+/// Use a capacity of 0 in order to use some system-dependent
+/// default capacity.
+pub fn create<T>(
+    flags: CreateFlags,
+    capacity: u32,
+) -> Result<(Consumer<T>, Producer<T>), MojoResult> {
+    let elem_size = mem::size_of::<T>() as u32;
+    let opts = ffi::MojoCreateDataPipeOptions {
+        struct_size: mem::size_of::<ffi::MojoCreateDataPipeOptions>() as u32,
+        flags: flags,
+        element_num_bytes: elem_size,
+        capacity_num_bytes: capacity * elem_size,
+        _align: [],
+    };
+    // TODO(mknyszek): Make sure handles are valid
+    let mut chandle: MojoHandle = 0;
+    let mut phandle: MojoHandle = 0;
+    let raw_opts = &opts as *const ffi::MojoCreateDataPipeOptions;
+    let r = MojoResult::from_code(unsafe {
+        ffi::MojoCreateDataPipe(
+            raw_opts,
+            &mut phandle as *mut MojoHandle,
+            &mut chandle as *mut MojoHandle,
+        )
+    });
+    if r != MojoResult::Okay {
+        Err(r)
+    } else {
+        Ok((
+            Consumer::<T> {
+                handle: unsafe { handle::acquire(chandle) },
+                _elem_type: marker::PhantomData,
+            },
+            Producer::<T> {
+                handle: unsafe { handle::acquire(phandle) },
+                _elem_type: marker::PhantomData,
+            },
+        ))
+    }
+}
+
+/// Creates a data pipe, represented as a consumer
+/// and a producer, using the default Mojo options.
+pub fn create_default() -> Result<(Consumer<u8>, Producer<u8>), MojoResult> {
+    create::<u8>(Create::None as u32, 0)
+}
+
+/// Represents the consumer half of a data pipe.
+/// This data structure wraps a handle and acts
+/// effectively as a typed handle.
+///
+/// The purpose of the _elem_type field is to associate
+/// a type with the consumer, as a data pipe works
+/// in elements.
+pub struct Consumer<T> {
+    handle: handle::UntypedHandle,
+    _elem_type: marker::PhantomData<T>,
+}
+
+impl<T> Consumer<T> {
+    /// Perform a read operation on the consumer end of the data pipe. As
+    /// a result, we get an std::vec::Vec filled with whatever was written.
+    pub fn read(&self, flags: ReadFlags) -> Result<vec::Vec<T>, MojoResult> {
+        let mut num_bytes: u32 = 0;
+        let r_prelim = unsafe {
+            ffi::MojoReadData(
+                self.handle.get_native_handle(),
+                ptr::null_mut() as *mut ffi::c_void,
+                &mut num_bytes as *mut u32,
+                1 << 2 as ReadFlags,
+            )
+        };
+        if r_prelim != 0 || num_bytes == 0 {
+            return Err(MojoResult::from_code(r_prelim));
+        }
+        let elem_size: u32 = mem::size_of::<T>() as u32;
+        // TODO(mknyszek): make sure elem_size divides into num_bytes
+        let mut buf: vec::Vec<T> = vec::Vec::with_capacity((num_bytes / elem_size) as usize);
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoReadData(
+                self.handle.get_native_handle(),
+                buf.as_mut_ptr() as *const ffi::c_void,
+                &mut num_bytes as *mut u32,
+                flags,
+            )
+        });
+        unsafe { buf.set_len((num_bytes / elem_size) as usize) }
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            Ok(buf)
+        }
+    }
+
+    /// Start two-phase read and return a ReadDataBuffer to perform
+    /// read and commit.
+    pub fn begin(&self, flags: ReadFlags) -> Result<ReadDataBuffer<T>, MojoResult> {
+        let wrapped_result = unsafe { self.begin_read(flags) };
+        match wrapped_result {
+            Ok(arr) => Ok(ReadDataBuffer::<T> { buffer: arr, parent: self }),
+            Err(r) => Err(r),
+        }
+    }
+
+    /// A private function that performs the first half of two-phase reading.
+    /// Kept private because it is unsafe to use (the array received may not
+    /// be valid if end_read is performed).
+    unsafe fn begin_read(&self, flags: ReadFlags) -> Result<&[T], MojoResult> {
+        let mut buf_num_bytes: u32 = 0;
+        let mut pbuf: *mut ffi::c_void = mem::uninitialized();
+        let r = MojoResult::from_code(ffi::MojoBeginReadData(
+            self.handle.get_native_handle(),
+            &mut pbuf,
+            &mut buf_num_bytes as *mut u32,
+            flags,
+        ));
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            let buf_elems = (buf_num_bytes as usize) / mem::size_of::<T>();
+            let buf = slice::from_raw_parts(pbuf as *mut T, buf_elems);
+            Ok(buf)
+        }
+    }
+
+    /// A private function that performs the second half of two-phase reading.
+    /// Kept private because it is unsafe to use (the array received from start_read
+    /// may not be valid if end_read is performed).
+    ///
+    /// Also assumes loads/stores aren't reordered such that a load/store may be
+    /// optimized to be run AFTER MojoEndReadData(). In general, this is true as long
+    /// as raw pointers are used, but Rust's memory model is still undefined. If you're
+    /// getting a bad/strange runtime error, it might be for this reason.
+    unsafe fn end_read(&self, elems_read: usize) -> MojoResult {
+        let elem_size = mem::size_of::<T>();
+        MojoResult::from_code(ffi::MojoEndReadData(
+            self.handle.get_native_handle(),
+            (elems_read * elem_size) as u32,
+        ))
+    }
+}
+
+impl<T> CastHandle for Consumer<T> {
+    /// Generates a Consumer from an untyped handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    unsafe fn from_untyped(handle: handle::UntypedHandle) -> Self {
+        Consumer::<T> { handle: handle, _elem_type: marker::PhantomData }
+    }
+
+    /// Consumes this object and produces a plain handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    fn as_untyped(self) -> handle::UntypedHandle {
+        self.handle
+    }
+}
+
+impl<T> Handle for Consumer<T> {
+    /// Returns the native handle wrapped by this structure.
+    ///
+    /// See mojo::system::handle for information on handle wrappers
+    fn get_native_handle(&self) -> MojoHandle {
+        self.handle.get_native_handle()
+    }
+}
+
+/// Represents the consumer half of a data pipe.
+/// This data structure wraps a handle and acts
+/// effectively as a typed handle.
+///
+/// The purpose of the _elem_type field is to associate
+/// a type with the consumer, as a data pipe works
+/// in elements.
+pub struct Producer<T> {
+    handle: handle::UntypedHandle,
+    _elem_type: marker::PhantomData<T>,
+}
+
+impl<T> Producer<T> {
+    /// Perform a write operation on the producer end of the data pipe.
+    /// Returns the number of elements actually written.
+    pub fn write(&self, data: &[T], flags: WriteFlags) -> Result<usize, MojoResult> {
+        let mut num_bytes = (data.len() * mem::size_of::<T>()) as u32;
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoWriteData(
+                self.handle.get_native_handle(),
+                data.as_ptr() as *const ffi::c_void,
+                &mut num_bytes as *mut u32,
+                flags,
+            )
+        });
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            Ok(num_bytes as usize)
+        }
+    }
+
+    /// Start two-phase write and return a WriteDataBuffer to perform
+    /// write and commit.
+    ///
+    /// Borrows self as mutable so that no other operation may happen on
+    /// the producer until the two-phase write is committed.
+    pub fn begin(&self, flags: WriteFlags) -> Result<WriteDataBuffer<T>, MojoResult> {
+        let wrapped_result = unsafe { self.begin_write(flags) };
+        match wrapped_result {
+            Ok(arr) => Ok(WriteDataBuffer::<T> { buffer: arr, parent: self }),
+            Err(r) => Err(r),
+        }
+    }
+
+    /// A private function that performs the first half of two-phase writing.
+    /// Kept private because it is unsafe to use (the array received may not
+    /// be valid if end_write is performed).
+    unsafe fn begin_write(&self, flags: WriteFlags) -> Result<&mut [T], MojoResult> {
+        let mut buf_num_bytes: u32 = 0;
+        let mut pbuf: *mut ffi::c_void = mem::uninitialized();
+        let r = MojoResult::from_code(ffi::MojoBeginWriteData(
+            self.handle.get_native_handle(),
+            &mut pbuf,
+            &mut buf_num_bytes as *mut u32,
+            flags,
+        ));
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            let buf_elems = (buf_num_bytes as usize) / mem::size_of::<T>();
+            let buf = slice::from_raw_parts_mut(pbuf as *mut T, buf_elems);
+            Ok(buf)
+        }
+    }
+
+    /// A private function that performs the second half of two-phase writing.
+    /// Kept private because it is unsafe to use (the array received from start_write
+    /// may not be valid if end_write is performed).
+    ///
+    /// Also assumes loads/stores aren't reordered such that a load/store may be
+    /// optimized to be run AFTER MojoEndWriteData(). In general, this is true as long
+    /// as raw pointers are used, but Rust's memory model is still undefined. If you're
+    /// getting a bad/strange runtime error, it might be for this reason.
+    unsafe fn end_write(&self, elems_written: usize) -> MojoResult {
+        let elem_size = mem::size_of::<T>();
+        MojoResult::from_code(ffi::MojoEndWriteData(
+            self.handle.get_native_handle(),
+            (elems_written * elem_size) as u32,
+        ))
+    }
+}
+
+impl<T> CastHandle for Producer<T> {
+    /// Generates a Consumer from an untyped handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    unsafe fn from_untyped(handle: handle::UntypedHandle) -> Self {
+        Producer::<T> { handle: handle, _elem_type: marker::PhantomData }
+    }
+
+    /// Consumes this object and produces a plain handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    fn as_untyped(self) -> handle::UntypedHandle {
+        self.handle
+    }
+}
+
+impl<T> Handle for Producer<T> {
+    /// Returns the native handle wrapped by this structure.
+    ///
+    /// See mojo::system::handle for information on handle wrappers
+    fn get_native_handle(&self) -> MojoHandle {
+        self.handle.get_native_handle()
+    }
+}
diff --git a/mojo/public/rust/system/ffi.rs b/mojo/public/rust/system/ffi.rs
new file mode 100644
index 0000000..12615bf0
--- /dev/null
+++ b/mojo/public/rust/system/ffi.rs
@@ -0,0 +1,252 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! This ffi module is used to interact with the
+//! Mojo C bindings API. The structures below are
+//! undocumented because they are pulled exactly
+//! from the header files of the Mojo C bindings
+//! API which can be found in the Mojo repository[1]
+//! under //mojo/public/c/include/mojo/system. Very
+//! clear documentation on these structures and
+//! functions can be found there. It is not worth
+//! elaborating on these all again here.
+//!
+//! [1] https://github.com/domokit/mojo
+
+// This full import is intentional; nearly every type in mojo_types needs to be used.
+use system::mojo_types::*;
+
+#[allow(bad_style)]
+/// This empty enum is used solely to provide
+/// a notion of void from C. The truth is, the
+/// correct move here is to use the libc Rust
+/// package but, as it turns out, that's the only
+/// part of libc we actually need. Rather than
+/// force ourselves to pull in a dependency, we
+/// instead implement libc's notion of c_void
+/// here.
+pub enum c_void {}
+
+pub mod types {
+    //! Defines some C-compatible types for the ffi layer of
+    //! the bindings.
+
+    pub type MojoCreateSharedBufferOptionsFlags = u32;
+    pub type MojoDuplicateBufferHandleOptionsFlags = u32;
+    pub type MojoBufferInfoFlags = u32;
+    pub type MojoMapBufferFlags = u32;
+    pub type MojoCreateDataPipeOptionsFlags = u32;
+    pub type MojoWriteDataFlags = u32;
+    pub type MojoReadDataFlags = u32;
+    pub type MojoHandleSignals = u32;
+    pub type MojoCreateMessagePipeOptionsFlags = u32;
+    pub type MojoWriteMessageFlags = u32;
+    pub type MojoReadMessageFlags = u32;
+    pub type MojoCreateWaitSetOptionsFlags = u32;
+    pub type MojoWaitSetAddOptionsFlags = u32;
+    pub type MojoResultCode = u32;
+}
+
+use system::ffi::types::*;
+
+#[repr(C)]
+pub struct MojoCreateSharedBufferOptions {
+    pub struct_size: u32,
+    pub flags: MojoCreateSharedBufferOptionsFlags,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[repr(C)]
+pub struct MojoDuplicateBufferHandleOptions {
+    pub struct_size: u32,
+    pub flags: MojoDuplicateBufferHandleOptionsFlags,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[repr(C)]
+pub struct MojoBufferInformation {
+    pub struct_size: u32,
+    pub flags: MojoBufferInfoFlags,
+    pub num_bytes: u64,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[repr(C)]
+pub struct MojoCreateDataPipeOptions {
+    pub struct_size: u32,
+    pub flags: MojoCreateDataPipeOptionsFlags,
+    pub element_num_bytes: u32,
+    pub capacity_num_bytes: u32,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[repr(C)]
+pub struct MojoCreateMessagePipeOptions {
+    pub struct_size: u32,
+    pub flags: MojoCreateMessagePipeOptionsFlags,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[repr(C)]
+pub struct MojoCreateWaitSetOptions {
+    pub struct_size: u32,
+    pub flags: MojoCreateWaitSetOptionsFlags,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[repr(C)]
+pub struct MojoWaitSetAddOptions {
+    pub struct_size: u32,
+    pub flags: MojoWaitSetAddOptionsFlags,
+    pub _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+#[link]
+extern "C" {
+    // From //mojo/public/c/include/mojo/system/buffer.h
+    pub fn MojoCreateSharedBuffer(
+        options: *const MojoCreateSharedBufferOptions,
+        num_bytes: u64,
+        shared_buffer_handle: *mut MojoHandle,
+    ) -> MojoResultCode;
+
+    pub fn MojoDuplicateBufferHandle(
+        handle: MojoHandle,
+        options: *const MojoDuplicateBufferHandleOptions,
+        new_buffer_handle: *mut MojoHandle,
+    ) -> MojoResultCode;
+
+    pub fn MojoGetBufferInformation(
+        buffer_handle: MojoHandle,
+        info: *mut MojoBufferInformation,
+        info_num_bytes: u32,
+    ) -> MojoResultCode;
+
+    pub fn MojoMapBuffer(
+        buffer_handle: MojoHandle,
+        offset: u64,
+        num_bytes: u64,
+        buffer: *mut *mut c_void,
+        flags: MojoMapBufferFlags,
+    ) -> MojoResultCode;
+
+    pub fn MojoUnmapBuffer(buffer: *const c_void) -> MojoResultCode;
+
+    // From //mojo/public/c/include/mojo/system/data_pipe.h
+    pub fn MojoCreateDataPipe(
+        options: *const MojoCreateDataPipeOptions,
+        data_pipe_producer_handle: *mut MojoHandle,
+        data_pipe_consumer_handle: *mut MojoHandle,
+    ) -> MojoResultCode;
+
+    pub fn MojoWriteData(
+        data_pipe_producer_handle: MojoHandle,
+        elements: *const c_void,
+        num_bytes: *mut u32,
+        flags: MojoWriteDataFlags,
+    ) -> MojoResultCode;
+
+    pub fn MojoBeginWriteData(
+        data_pipe_producer_handle: MojoHandle,
+        buffer: *mut *mut c_void,
+        buffer_num_bytes: *mut u32,
+        flags: MojoWriteDataFlags,
+    ) -> MojoResultCode;
+
+    pub fn MojoEndWriteData(
+        data_pipe_producer_handle: MojoHandle,
+        num_bytes_written: u32,
+    ) -> MojoResultCode;
+
+    pub fn MojoReadData(
+        data_pipe_consumer_handle: MojoHandle,
+        elements: *const c_void,
+        num_bytes: *mut u32,
+        flags: MojoReadDataFlags,
+    ) -> MojoResultCode;
+
+    pub fn MojoBeginReadData(
+        data_pipe_consumer_handle: MojoHandle,
+        buffer: *mut *mut c_void,
+        buffer_num_bytes: *mut u32,
+        flags: MojoReadDataFlags,
+    ) -> MojoResultCode;
+
+    pub fn MojoEndReadData(
+        data_pipe_consumer_handle: MojoHandle,
+        num_bytes_written: u32,
+    ) -> MojoResultCode;
+
+    // From //mojo/public/c/include/mojo/system/handle.h
+    pub fn MojoClose(handle: MojoHandle) -> MojoResultCode;
+
+    // From //mojo/public/c/include/mojo/system/message_pipe.h
+    pub fn MojoCreateMessagePipe(
+        options: *const MojoCreateMessagePipeOptions,
+        message_pipe_handle0: *mut MojoHandle,
+        message_pipe_handle1: *mut MojoHandle,
+    ) -> MojoResultCode;
+
+    pub fn MojoWriteMessage(
+        message_pipe_handle: MojoHandle,
+        bytes: *const c_void,
+        num_bytes: u32,
+        handles: *const MojoHandle,
+        num_handles: u32,
+        flags: MojoWriteMessageFlags,
+    ) -> MojoResultCode;
+
+    pub fn MojoReadMessage(
+        message_pipe_handle: MojoHandle,
+        bytes: *mut c_void,
+        num_bytes: *mut u32,
+        handles: *mut MojoHandle,
+        num_handles: *mut u32,
+        flags: MojoWriteMessageFlags,
+    ) -> MojoResultCode;
+
+    // From //mojo/public/c/include/mojo/system/time.h
+    pub fn MojoGetTimeTicksNow() -> MojoTimeTicks;
+
+    // From //mojo/public/c/include/mojo/system/wait.h
+    pub fn MojoWait(
+        handle: MojoHandle,
+        signals: HandleSignals,
+        deadline: MojoDeadline,
+        signals_state: *mut SignalsState,
+    ) -> MojoResultCode;
+
+    pub fn MojoWaitMany(
+        handles: *const MojoHandle,
+        signals: *const HandleSignals,
+        num_handles: u32,
+        deadline: MojoDeadline,
+        result_index: *mut u32,
+        signals_states: *mut SignalsState,
+    ) -> MojoResultCode;
+
+    // From //mojo/public/c/include/mojo/system/wait_set.h
+    pub fn MojoCreateWaitSet(
+        options: *const MojoCreateWaitSetOptions,
+        handle: *mut MojoHandle,
+    ) -> MojoResultCode;
+
+    pub fn MojoWaitSetAdd(
+        wait_set_handle: MojoHandle,
+        handle: MojoHandle,
+        signals: HandleSignals,
+        cookie: u64,
+        options: *const MojoWaitSetAddOptions,
+    ) -> MojoResultCode;
+
+    pub fn MojoWaitSetRemove(wait_set_handle: MojoHandle, cookie: u64) -> MojoResultCode;
+
+    pub fn MojoWaitSetWait(
+        wait_set_handle: MojoHandle,
+        deadline: MojoDeadline,
+        num_results: *mut u32,
+        results: *mut WaitSetResult,
+        max_results: *mut u32,
+    ) -> MojoResultCode;
+}
diff --git a/mojo/public/rust/system/handle.rs b/mojo/public/rust/system/handle.rs
new file mode 100644
index 0000000..7cd8e3a
--- /dev/null
+++ b/mojo/public/rust/system/handle.rs
@@ -0,0 +1,124 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! The way Mojo handles are handled in Rust is very similar
+//! to Go, though more type-safe. Here we define an "untyped"
+//! handle which means that what the handle actually represents
+//! is unknown. This is the basic handle wrapper, and it handles
+//! closing the handle once the wrapper goes out of scope, therefore
+//! preventing any resources from being leaked. "Typed" handles
+//! are MessageEndpoints or Consumers/Producers in this library
+//! and they represent handles which represent parts of message pipes,
+//! data pipes, and shared buffers. Typed handles wrap untyped handles
+//! but act much the same as untyped handles.
+
+use system::ffi;
+// This full import is intentional; nearly every type in mojo_types needs to be used.
+use system::mojo_types::*;
+
+/// The CastHandle trait defines an interface to convert between
+/// typed and untyped handles. These are only used internally for
+/// typed handles.
+pub trait CastHandle {
+    /// Passes an ownership of an untyped handle and produces a
+    /// typed handle which owns that untyped handle
+    ///
+    /// Casting to a typed handle is unsafe because the handle may
+    /// not necessarily be a handle to the typed primitive being
+    /// casted to internally in Mojo
+    unsafe fn from_untyped(handle: UntypedHandle) -> Self;
+
+    /// Consumes a typed handle and releases ownership of the
+    /// untyped handle it owned
+    fn as_untyped(self) -> UntypedHandle;
+}
+
+/// The Handle trait simply means that we can extract
+/// the native integer-based Mojo handle from the typed handle.
+pub trait Handle {
+    /// Returns the native handle wrapped by whatever structure
+    /// implements this trait.
+    fn get_native_handle(&self) -> MojoHandle;
+
+    /// Waits on the handle wrapped in the current struct until the signals
+    /// declared in 'signals' are triggered, waiting for a maximum time of
+    /// 'deadline'. This method blocks.
+    ///
+    /// Returns the satisfied and satisfiable signals respectively for this
+    /// handle when waiting is done.
+    fn wait(&self, signals: HandleSignals, deadline: MojoDeadline) -> (SignalsState, MojoResult) {
+        let mut state: SignalsState = Default::default();
+        let r = unsafe {
+            ffi::MojoWait(
+                self.get_native_handle(),
+                signals,
+                deadline,
+                &mut state as *mut SignalsState,
+            )
+        };
+        (state, MojoResult::from_code(r))
+    }
+}
+
+/// The basic untyped handle that wraps a MojoHandle (a u32)
+pub struct UntypedHandle {
+    /// The native Mojo handle
+    value: MojoHandle,
+}
+
+impl UntypedHandle {
+    /// Invalidates the Handle by setting its native handle to
+    /// zero, the canonical invalid handle in Mojo.
+    ///
+    /// This function is unsafe because clearing a native handle
+    /// without closing it is a resource leak.
+    pub unsafe fn invalidate(&mut self) {
+        self.value = 0
+    }
+
+    /// Checks if the native handle is valid (0 = canonical invalid handle).
+    pub fn is_valid(&self) -> bool {
+        self.value != 0
+    }
+}
+
+impl Handle for UntypedHandle {
+    /// Pulls out a copy of the native handle wrapped by this structure.
+    fn get_native_handle(&self) -> MojoHandle {
+        self.value
+    }
+}
+
+impl CastHandle for UntypedHandle {
+    /// Casting an untyped handle is a no-op, but we include
+    /// this to eliminate code duplication.
+    unsafe fn from_untyped(handle: UntypedHandle) -> Self {
+        handle
+    }
+
+    /// Casting to an untyped handle is a no-op, but we include
+    /// this to eliminate code duplication.
+    fn as_untyped(self) -> UntypedHandle {
+        self
+    }
+}
+
+impl Drop for UntypedHandle {
+    /// The destructor for an untyped handle which closes the native handle
+    /// it wraps.
+    fn drop(&mut self) {
+        if self.is_valid() {
+            let result = MojoResult::from_code(unsafe { ffi::MojoClose(self.get_native_handle()) });
+            if result != MojoResult::Okay {
+                panic!("Failed to close handle! Reason: {}", result);
+            }
+        }
+    }
+}
+
+/// Acquires a native handle by wrapping it in an untyped handle, allowing
+/// us to track the resource and free it appropriately
+pub unsafe fn acquire(handle: MojoHandle) -> UntypedHandle {
+    UntypedHandle { value: handle }
+}
diff --git a/mojo/public/rust/system/message_pipe.rs b/mojo/public/rust/system/message_pipe.rs
new file mode 100644
index 0000000..19f46c2
--- /dev/null
+++ b/mojo/public/rust/system/message_pipe.rs
@@ -0,0 +1,220 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use std::mem;
+use std::ptr;
+use std::vec;
+
+use system::ffi;
+use system::handle;
+use system::handle::{CastHandle, Handle};
+// This full import is intentional; nearly every type in mojo_types needs to be used.
+use system::mojo_types::*;
+
+#[repr(u32)]
+/// Create flags for message pipes
+pub enum Create {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Write flags for message pipes
+pub enum Write {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Read flags for message pipes
+pub enum Read {
+    None = 0,
+
+    /// If the message is unable to be
+    /// read for whatever reason, dequeue
+    /// it anyway
+    MayDiscard = 1 << 0,
+}
+
+/// Creates a message pipe in Mojo and gives back two
+/// MessageEndpoints which represent the endpoints of the
+/// message pipe
+pub fn create(flags: CreateFlags) -> Result<(MessageEndpoint, MessageEndpoint), MojoResult> {
+    let mut handle0: MojoHandle = 0;
+    let mut handle1: MojoHandle = 0;
+    let opts = ffi::MojoCreateMessagePipeOptions {
+        struct_size: mem::size_of::<ffi::MojoCreateMessagePipeOptions>() as u32,
+        flags: flags,
+        _align: [],
+    };
+    let raw_opts = &opts as *const ffi::MojoCreateMessagePipeOptions;
+    let r = MojoResult::from_code(unsafe {
+        ffi::MojoCreateMessagePipe(
+            raw_opts,
+            &mut handle0 as *mut MojoHandle,
+            &mut handle1 as *mut MojoHandle,
+        )
+    });
+    if r != MojoResult::Okay {
+        Err(r)
+    } else {
+        Ok((
+            MessageEndpoint { handle: unsafe { handle::acquire(handle0) } },
+            MessageEndpoint { handle: unsafe { handle::acquire(handle1) } },
+        ))
+    }
+}
+
+/// Represents the one endpoint of a message pipe.
+/// This data structure wraps a handle and acts
+/// effectively as a typed handle.
+pub struct MessageEndpoint {
+    handle: handle::UntypedHandle,
+}
+
+impl MessageEndpoint {
+    /// Read the next message from the endpoint. Messages in Mojo
+    /// are some set of bytes plus a bunch of handles, so we
+    /// return both a vector of bytes and a vector of untyped handles.
+    ///
+    /// Because the handles are untyped, it is up to the user of this
+    /// library to know what type the handle actually is and to use
+    /// from_untyped in order to convert the handle to the correct type.
+    /// This is abstracted away, however, when using the Mojo bindings
+    /// generator where you may specify your interface in Mojom.
+    ///
+    /// If an empty message (that is, it has neither data nor handles)
+    /// is received, it will show up as an Err() containing MojoResult::Okay.
+    pub fn read(
+        &self,
+        flags: ReadFlags,
+    ) -> Result<(vec::Vec<u8>, vec::Vec<handle::UntypedHandle>), MojoResult> {
+        let mut num_bytes: u32 = 0;
+        let mut num_handles: u32 = 0;
+        let result_prelim = MojoResult::from_code(unsafe {
+            ffi::MojoReadMessage(
+                self.handle.get_native_handle(),
+                ptr::null_mut(),
+                &mut num_bytes as *mut u32,
+                ptr::null_mut(),
+                &mut num_handles as *mut u32,
+                flags,
+            )
+        });
+        if result_prelim != MojoResult::ResourceExhausted {
+            return Err(result_prelim);
+        }
+        let mut buf: vec::Vec<u8> = vec::Vec::with_capacity(num_bytes as usize);
+        let mut raw_handles: vec::Vec<MojoHandle> = vec::Vec::with_capacity(num_handles as usize);
+        let buf_ptr;
+        if num_bytes == 0 {
+            buf_ptr = ptr::null_mut();
+        } else {
+            buf_ptr = buf.as_mut_ptr() as *mut ffi::c_void;
+        }
+        let raw_handles_ptr;
+        if num_handles == 0 {
+            raw_handles_ptr = ptr::null_mut();
+        } else {
+            raw_handles_ptr = raw_handles.as_mut_ptr();
+        }
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoReadMessage(
+                self.handle.get_native_handle(),
+                buf_ptr,
+                &mut num_bytes as *mut u32,
+                raw_handles_ptr,
+                &mut num_handles as *mut u32,
+                flags,
+            )
+        });
+        unsafe {
+            buf.set_len(num_bytes as usize);
+            raw_handles.set_len(num_handles as usize);
+        }
+        let mut handles: vec::Vec<handle::UntypedHandle> =
+            vec::Vec::with_capacity(num_handles as usize);
+        for raw_handle in raw_handles.iter() {
+            handles.push(unsafe { handle::acquire(*raw_handle) });
+        }
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            Ok((buf, handles))
+        }
+    }
+
+    /// Write a message to the endpoint. Messages in Mojo
+    /// are some set of bytes plus a bunch of handles, so we
+    /// return both a vector of bytes and a vector of untyped handles.
+    ///
+    /// Because the handles are untyped, it is up to the user of this
+    /// library to know what type the handle actually is and to use
+    /// from_untyped in order to convert the handle to the correct type.
+    /// This is abstracted away, however, when using the Mojo bindings
+    /// generator where you may specify your interface in Mojom.
+    ///
+    /// Additionally, the handles passed in are consumed. This is because
+    /// Mojo handles operate on move semantics much like Rust data types.
+    /// When a handle is sent through a message pipe it is invalidated and
+    /// may not even be represented by the same integer on the other side,
+    /// so care must be taken to design your application with this in mind.
+    pub fn write(
+        &self,
+        bytes: &[u8],
+        mut handles: vec::Vec<handle::UntypedHandle>,
+        flags: WriteFlags,
+    ) -> MojoResult {
+        let bytes_ptr;
+        if bytes.len() == 0 {
+            bytes_ptr = ptr::null();
+        } else {
+            bytes_ptr = bytes.as_ptr() as *const ffi::c_void;
+        }
+        let mut raw_handles: vec::Vec<MojoHandle> = vec::Vec::with_capacity(handles.len());
+        for handle in handles.iter_mut() {
+            unsafe {
+                raw_handles.push(handle.get_native_handle());
+                handle.invalidate();
+            }
+        }
+        let raw_handles_ptr;
+        if raw_handles.len() == 0 {
+            raw_handles_ptr = ptr::null();
+        } else {
+            raw_handles_ptr = raw_handles.as_ptr();
+        }
+        return MojoResult::from_code(unsafe {
+            ffi::MojoWriteMessage(
+                self.handle.get_native_handle(),
+                bytes_ptr,
+                bytes.len() as u32,
+                raw_handles_ptr,
+                raw_handles.len() as u32,
+                flags,
+            )
+        });
+    }
+}
+
+impl CastHandle for MessageEndpoint {
+    /// Generates a MessageEndpoint from an untyped handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    unsafe fn from_untyped(handle: handle::UntypedHandle) -> Self {
+        MessageEndpoint { handle: handle }
+    }
+
+    /// Consumes this object and produces a plain handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    fn as_untyped(self) -> handle::UntypedHandle {
+        self.handle
+    }
+}
+
+impl Handle for MessageEndpoint {
+    /// Returns the native handle wrapped by this structure.
+    ///
+    /// See mojo::system::handle for information on handle wrappers
+    fn get_native_handle(&self) -> MojoHandle {
+        self.handle.get_native_handle()
+    }
+}
diff --git a/mojo/public/rust/system/mod.rs b/mojo/public/rust/system/mod.rs
new file mode 100644
index 0000000..0258e79
--- /dev/null
+++ b/mojo/public/rust/system/mod.rs
@@ -0,0 +1,18 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+mod ffi;
+mod handle;
+mod mojo_types;
+
+pub mod core;
+pub mod data_pipe;
+pub mod message_pipe;
+pub mod shared_buffer;
+pub mod wait_set;
+
+// In order to keep the interface clean, we re-export basic Mojo and handle
+// types and traits here in the system module.
+pub use system::handle::*;
+pub use system::mojo_types::*;
diff --git a/mojo/public/rust/system/mojo_types.rs b/mojo/public/rust/system/mojo_types.rs
new file mode 100644
index 0000000..1e9a67b
--- /dev/null
+++ b/mojo/public/rust/system/mojo_types.rs
@@ -0,0 +1,274 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! This module contains a variety of types which are used
+//! for representing representing flag arguments a little bit
+//! better than just as u32 and some other basic Mojo types that
+//! we need to expose.
+//!
+//! This module also provides MojoResult which is the canonical
+//! result coding system used by Mojo.
+//!
+//! Many places in the system code directly import this module as
+//! a whole because it is intended to be used that way. It contains
+//! all of the basic types needed by all system-level Mojo bindings.
+
+use std::fmt;
+use std::u64;
+use system::ffi::types::*;
+
+/// A MojoHandle is represented as a plain 32-bit unsigned int.
+pub type MojoHandle = u32;
+
+/// Represents time ticks as specified by Mojo. A time tick value
+/// is meaningless when not used relative to another time tick.
+pub type MojoTimeTicks = i64;
+
+/// Represents a deadline for wait() calls.
+pub type MojoDeadline = u64;
+pub static MOJO_INDEFINITE: MojoDeadline = u64::MAX;
+
+pub type CreateFlags = u32;
+pub type DuplicateFlags = u32;
+pub type InfoFlags = u32;
+pub type MapFlags = u32;
+pub type WriteFlags = u32;
+pub type ReadFlags = u32;
+pub type AddFlags = u32;
+
+/// MojoResult represents anything that can happen
+/// as a result of performing some operation in Mojo.
+///
+/// It's implementation matches exactly that found in
+/// the Mojo C API so this enum can be used across the
+/// FFI boundary simply by using "as u32".
+#[derive(Copy, Clone, Debug, PartialEq)]
+#[repr(u32)]
+pub enum MojoResult {
+    Okay = 0x0,
+    Cancelled = 0x1,
+    Unknown = 0x2,
+    InvalidArgument = 0x3,
+    DeadlineExceeded = 0x4,
+    NotFound = 0x5,
+    AlreadyExists = 0x6,
+    PermissionDenied = 0x7,
+    ResourceExhausted = 0x8,
+    FailedPrecondition = 0x9,
+    Aborted = 0xa,
+    OutOfRange = 0xb,
+    Unimplemented = 0xc,
+    Internal = 0xd,
+    Unavailable = 0xe,
+    DataLoss = 0xf,
+    Busy = 0x0019,
+    ShouldWait = 0x001e,
+    InvalidResult,
+}
+
+impl MojoResult {
+    /// Convert a raw u32 code given by the C Mojo functions
+    /// into a MojoResult.
+    pub fn from_code(code: MojoResultCode) -> MojoResult {
+        match code as u32 {
+            0x0 => MojoResult::Okay,
+            0x1 => MojoResult::Cancelled,
+            0x2 => MojoResult::Unknown,
+            0x3 => MojoResult::InvalidArgument,
+            0x4 => MojoResult::DeadlineExceeded,
+            0x5 => MojoResult::NotFound,
+            0x6 => MojoResult::AlreadyExists,
+            0x7 => MojoResult::PermissionDenied,
+            0x8 => MojoResult::ResourceExhausted,
+            0x9 => MojoResult::FailedPrecondition,
+            0xa => MojoResult::Aborted,
+            0xb => MojoResult::OutOfRange,
+            0xc => MojoResult::Unimplemented,
+            0xd => MojoResult::Internal,
+            0xe => MojoResult::Unavailable,
+            0xf => MojoResult::DataLoss,
+            0x0019 => MojoResult::Busy,
+            0x001e => MojoResult::ShouldWait,
+            _ => MojoResult::InvalidResult,
+        }
+    }
+
+    pub fn to_str(&self) -> &'static str {
+        match *self {
+            MojoResult::Okay => "OK",
+            MojoResult::Cancelled => "Cancelled",
+            MojoResult::Unknown => "Unknown",
+            MojoResult::InvalidArgument => "Invalid Argument",
+            MojoResult::DeadlineExceeded => "Deadline Exceeded",
+            MojoResult::NotFound => "Not Found",
+            MojoResult::AlreadyExists => "Already Exists",
+            MojoResult::PermissionDenied => "Permission Denied",
+            MojoResult::ResourceExhausted => "Resource Exhausted",
+            MojoResult::FailedPrecondition => "Failed Precondition",
+            MojoResult::Aborted => "Aborted",
+            MojoResult::OutOfRange => "Out Of Range",
+            MojoResult::Unimplemented => "Unimplemented",
+            MojoResult::Internal => "Internal",
+            MojoResult::Unavailable => "Unavailable",
+            MojoResult::DataLoss => "Data Loss",
+            MojoResult::Busy => "Busy",
+            MojoResult::ShouldWait => "Should Wait",
+            MojoResult::InvalidResult => "Something went very wrong",
+        }
+    }
+}
+
+impl fmt::Display for MojoResult {
+    /// Allow a MojoResult to be displayed in a sane manner.
+    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
+        write!(f, "{}", self.to_str())
+    }
+}
+
+/// This tuple struct represents a bit vector configuration of possible
+/// Mojo signals. Used in wait() and wait_many() primarily as a convenience.
+///
+/// One invariant must be true for this data structure and it is that:
+///     sizeof(HandleSignals) == sizeof(MojoHandleSignals)
+/// If this is ever not the case or there is a way in Rust to ensure that,
+/// this data structure must be updated to reflect that.
+#[repr(C)]
+#[derive(Clone, Copy, Default, PartialEq)]
+pub struct HandleSignals(MojoHandleSignals);
+
+impl HandleSignals {
+    /// Create a new HandleSignals given the raw MojoHandleSignals
+    pub fn new(s: MojoHandleSignals) -> HandleSignals {
+        HandleSignals(s)
+    }
+
+    /// Check if the readable flag is set
+    pub fn is_readable(&self) -> bool {
+        (self.0 & (Signals::Readable as u32)) != 0
+    }
+
+    /// Check if the writable flag is set
+    pub fn is_writable(&self) -> bool {
+        (self.0 & (Signals::Writable as u32)) != 0
+    }
+
+    /// Check if the peer-closed flag is set
+    pub fn is_peer_closed(&self) -> bool {
+        (self.0 & (Signals::PeerClosed as u32)) != 0
+    }
+
+    /// Check if the read threshold flag is set
+    pub fn is_read_threshold(&self) -> bool {
+        (self.0 & (Signals::ReadThreshold as u32)) != 0
+    }
+
+    /// Check if the write threshold flag is set
+    pub fn is_write_threshold(&self) -> bool {
+        (self.0 & (Signals::WriteThreshold as u32)) != 0
+    }
+
+    /// Pull the raw MojoHandleSignals out of the data structure
+    pub fn get_bits(&self) -> MojoHandleSignals {
+        self.0
+    }
+}
+
+/// Represents the signals state of a handle: which signals are satisfied,
+/// and which are satisfiable.
+///
+/// One invariant must be true for this data structure and it is that:
+///     sizeof(SignalsState) == sizeof(MojoSignalsState) (defined in handle.h)
+/// If this is ever not the case or there is a way in Rust to ensure that,
+/// this data structure must be updated to reflect that.
+#[repr(C)]
+#[derive(Default)]
+pub struct SignalsState {
+    satisfied: HandleSignals,
+    satisfiable: HandleSignals,
+    _align: [u32; 0], // Hack to align to a 4-byte boundary
+}
+
+impl SignalsState {
+    /// Generates a new SignalsState
+    pub fn new(satisfied: HandleSignals, satisfiable: HandleSignals) -> SignalsState {
+        SignalsState { satisfied: satisfied, satisfiable: satisfiable, _align: [] }
+    }
+    /// Gets a reference to the satisfied signals
+    pub fn satisfied(&self) -> &HandleSignals {
+        &self.satisfied
+    }
+    /// Gets a reference to the satisfiable signals
+    pub fn satisfiable(&self) -> &HandleSignals {
+        &self.satisfiable
+    }
+    /// Consume the SignalsState and release its tender interior
+    ///
+    /// Returns (satisfied, satisfiable)
+    pub fn unwrap(self) -> (HandleSignals, HandleSignals) {
+        (self.satisfied, self.satisfiable)
+    }
+}
+
+/// The different signals options that can be
+/// used by wait() and wait_many(). You may use
+/// these directly to build a bit-vector, but
+/// the signals! macro will already do it for you.
+/// See the root of the library for more information.
+#[repr(u32)]
+pub enum Signals {
+    None = 0,
+    /// Wait for the handle to be readable
+    Readable = 1 << 0,
+
+    /// Wait for the handle to be writable
+    Writable = 1 << 1,
+
+    /// Wait for the handle to be closed by the peer
+    /// (for message pipes and data pipes, this is
+    /// the counterpart handle to the pipe)
+    PeerClosed = 1 << 2,
+
+    /// Wait for the handle to have at least some
+    /// readable data
+    ReadThreshold = 1 << 3,
+
+    /// Wait for the handle to allow for at least
+    /// some data to be writable
+    WriteThreshold = 1 << 4,
+}
+
+/// The result struct used by the wait_set module
+/// to return wait result information. Should remain
+/// semantically identical to the implementation of
+/// this struct in wait_set.h in the C bindings.
+///
+/// This struct should never be constructed by anything
+/// but the Mojo system in MojoWaitSetWait.
+#[repr(C)]
+pub struct WaitSetResult {
+    cookie: u64,
+    result: MojoResultCode,
+    reserved: u32,
+    signals_state: SignalsState,
+    _align: [u64; 0], // Hack to align struct to 8 byte boundary
+}
+
+impl WaitSetResult {
+    /// Getter for the cookie corresponding to the handle
+    /// which just finished waiting.
+    pub fn cookie(&self) -> u64 {
+        self.cookie
+    }
+
+    /// Getter for the wait result.
+    pub fn result(&self) -> MojoResult {
+        MojoResult::from_code(self.result)
+    }
+
+    /// Getter for the signals state that comes with any
+    /// wait result.
+    pub fn state(&self) -> &SignalsState {
+        &self.signals_state
+    }
+}
diff --git a/mojo/public/rust/system/shared_buffer.rs b/mojo/public/rust/system/shared_buffer.rs
new file mode 100644
index 0000000..1b893772
--- /dev/null
+++ b/mojo/public/rust/system/shared_buffer.rs
@@ -0,0 +1,245 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use std::mem;
+use std::ptr;
+use std::slice;
+
+use system::ffi;
+// This full import is intentional; nearly every type in mojo_types needs to be used.
+use system::handle;
+use system::handle::{CastHandle, Handle};
+use system::mojo_types::*;
+
+#[repr(u32)]
+/// Create flags for shared buffers
+pub enum Create {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Duplicate flags for shared buffers
+pub enum Duplicate {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Map flags for shared buffers
+pub enum Map {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Map flags for shared buffers
+pub enum Info {
+    None = 0,
+}
+
+/// A MappedBuffer represents the result of
+/// calling map_buffer on a shared buffer handle.
+///
+/// The C API allocates a buffer which can then be
+/// read or written to through this data structure.
+///
+/// The importance of this data structure is that
+/// we bind the lifetime of the slice given to us
+/// from the C API to this structure. Additionally,
+/// reads and writes to this data structure are guaranteed
+/// to be able to propagate through Mojo as they are
+/// volatile. Language optimization backends are generally
+/// unaware of other address spaces, and since this structure
+/// represents some buffer from another address space, we
+/// need to make sure loads and stores are volatile.
+///
+/// Changes to this data structure are propagated through Mojo
+/// on the next Mojo operation (that is, Mojo operations are
+/// considered barriers). So, unmapping the buffer, sending a
+/// message across a pipe, duplicating a shared buffer handle,
+/// etc. are all valid ways of propagating changes. The read
+/// and write methods do NOT guarantee changes to propagate.
+///
+/// This structure also prevents resource leaks by
+/// unmapping the buffer it contains on destruction.
+pub struct MappedBuffer<'a> {
+    buffer: &'a mut [u8],
+}
+
+impl<'a> MappedBuffer<'a> {
+    /// Returns the length of the wrapped buffer.
+    ///
+    /// Part of reimplementing the array interface to be
+    /// able to use the structure naturally.
+    pub fn len(&self) -> usize {
+        self.buffer.len()
+    }
+
+    /// Read safely from the shared buffer. Makes sure a real load
+    /// is performed by marking the read as volatile.
+    pub fn read(&self, index: usize) -> u8 {
+        unsafe { ptr::read_volatile((&self.buffer[index]) as *const u8) }
+    }
+
+    /// Write safely to the shared buffer. Makes sure a real store
+    /// is performed by marking the store as volatile.
+    pub fn write(&mut self, index: usize, value: u8) {
+        unsafe {
+            ptr::write_volatile((&mut self.buffer[index]) as *mut u8, value);
+        }
+    }
+
+    /// Returns the slice this buffer wraps.
+    ///
+    /// The reason this method is unsafe is because the way Rust maps
+    /// reads and writes down to loads and stores may not be to real
+    /// loads and stores which are required to allow changes to propagate
+    /// through Mojo. If you are not careful, some writes and reads may be
+    /// to incorrect data! Use at your own risk.
+    pub unsafe fn as_slice(&'a mut self) -> &'a mut [u8] {
+        self.buffer
+    }
+}
+
+impl<'a> Drop for MappedBuffer<'a> {
+    /// The destructor for MappedBuffer. Unmaps the buffer it
+    /// encloses by using the original, raw pointer to the mapped
+    /// memory region.
+    fn drop(&mut self) {
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoUnmapBuffer(self.buffer.as_ptr() as *const ffi::c_void)
+        });
+        if r != MojoResult::Okay {
+            panic!("Failed to unmap buffer. Mojo Error: {}", r);
+        }
+    }
+}
+
+/// Creates a shared buffer in Mojo and returns a SharedBuffer
+/// structure which represents a handle to the shared buffer.
+pub fn create(flags: CreateFlags, num_bytes: u64) -> Result<SharedBuffer, MojoResult> {
+    let opts = ffi::MojoCreateSharedBufferOptions {
+        struct_size: mem::size_of::<ffi::MojoCreateSharedBufferOptions>() as u32,
+        flags: flags,
+        _align: [],
+    };
+    let raw_opts = &opts as *const ffi::MojoCreateSharedBufferOptions;
+    let mut h: MojoHandle = 0;
+    let r = MojoResult::from_code(unsafe {
+        ffi::MojoCreateSharedBuffer(raw_opts, num_bytes, &mut h as *mut MojoHandle)
+    });
+    if r != MojoResult::Okay {
+        Err(r)
+    } else {
+        Ok(SharedBuffer { handle: unsafe { handle::acquire(h) } })
+    }
+}
+
+/// Represents a handle to a shared buffer in Mojo.
+/// This data structure wraps a handle and acts
+/// effectively as a typed handle.
+pub struct SharedBuffer {
+    handle: handle::UntypedHandle,
+}
+
+impl SharedBuffer {
+    /// Duplicates the shared buffer handle. This is NOT the same
+    /// as cloning the structure which is illegal since cloning could
+    /// lead to resource leaks. Instead this uses Mojo to duplicate the
+    /// buffer handle (though the handle itself may not be represented by
+    /// the same number) that maps to the same shared buffer as the original.
+    pub fn duplicate(&self, flags: DuplicateFlags) -> Result<SharedBuffer, MojoResult> {
+        let opts = ffi::MojoDuplicateBufferHandleOptions {
+            struct_size: mem::size_of::<ffi::MojoDuplicateBufferHandleOptions>() as u32,
+            flags: flags,
+            _align: [],
+        };
+        let raw_opts = &opts as *const ffi::MojoDuplicateBufferHandleOptions;
+        let mut dup_h: MojoHandle = 0;
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoDuplicateBufferHandle(
+                self.handle.get_native_handle(),
+                raw_opts,
+                &mut dup_h as *mut MojoHandle,
+            )
+        });
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            Ok(SharedBuffer { handle: unsafe { handle::acquire(dup_h) } })
+        }
+    }
+
+    /// Map the shared buffer into local memory. Generates a MappedBuffer
+    /// structure. See MappedBuffer for more information on how to use it.
+    pub fn map<'a>(
+        &self,
+        offset: u64,
+        num_bytes: u64,
+        flags: MapFlags,
+    ) -> Result<MappedBuffer<'a>, MojoResult> {
+        unsafe {
+            let mut ptr: *mut ffi::c_void = mem::uninitialized();
+            let r = MojoResult::from_code(ffi::MojoMapBuffer(
+                self.handle.get_native_handle(),
+                offset,
+                num_bytes,
+                &mut ptr,
+                flags,
+            ));
+            if r != MojoResult::Okay {
+                Err(r)
+            } else {
+                let mut buf = slice::from_raw_parts_mut(ptr as *mut u8, num_bytes as usize);
+                Ok(MappedBuffer { buffer: buf })
+            }
+        }
+    }
+
+    /// Retrieves information about a shared buffer the this handle. The return
+    /// value is a set of flags (a bit vector in a u32) representing different
+    /// aspects of the shared buffer and the size of the shared buffer.
+    pub fn get_info(&self) -> Result<(InfoFlags, u64), MojoResult> {
+        let info_size = mem::size_of::<ffi::MojoBufferInformation>() as u32;
+        let mut info = ffi::MojoBufferInformation {
+            struct_size: info_size,
+            flags: 0,
+            num_bytes: 0,
+            _align: [],
+        };
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoGetBufferInformation(
+                self.handle.get_native_handle(),
+                &mut info as *mut ffi::MojoBufferInformation,
+                info_size,
+            )
+        });
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            Ok((info.flags, info.num_bytes))
+        }
+    }
+}
+
+impl CastHandle for SharedBuffer {
+    /// Generates a SharedBuffer from an untyped handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    unsafe fn from_untyped(handle: handle::UntypedHandle) -> Self {
+        SharedBuffer { handle: handle }
+    }
+
+    /// Consumes this object and produces a plain handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    fn as_untyped(self) -> handle::UntypedHandle {
+        self.handle
+    }
+}
+
+impl Handle for SharedBuffer {
+    /// Returns the native handle wrapped by this structure.
+    ///
+    /// See mojo::system::handle for information on handle wrappers
+    fn get_native_handle(&self) -> MojoHandle {
+        self.handle.get_native_handle()
+    }
+}
diff --git a/mojo/public/rust/system/wait_set.rs b/mojo/public/rust/system/wait_set.rs
new file mode 100644
index 0000000..27117838
--- /dev/null
+++ b/mojo/public/rust/system/wait_set.rs
@@ -0,0 +1,161 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+use std::mem;
+use std::ptr;
+
+use system::ffi;
+use system::handle;
+use system::handle::{CastHandle, Handle};
+use system::mojo_types;
+use system::mojo_types::MojoResult;
+
+#[repr(u32)]
+/// Create flags for wait sets
+pub enum Create {
+    None = 0,
+}
+
+#[repr(u32)]
+/// Add flags for wait sets
+pub enum Add {
+    None = 0,
+}
+
+/// This struct represents a handle to a wait set in the Mojo system.
+///
+/// The primary purpose of a wait set is to provide an abstraction for
+/// efficiently waiting asynchronously (and cooperatively) on a set of
+/// handles which are registered with it.
+pub struct WaitSet {
+    handle: handle::UntypedHandle,
+}
+
+impl WaitSet {
+    /// Creates a new WaitSet object in the Mojo system, and returns a wrapper
+    /// for it. If creation fails, returns the result code.
+    pub fn new(flags: mojo_types::CreateFlags) -> Result<WaitSet, MojoResult> {
+        let mut raw_handle: mojo_types::MojoHandle = 0;
+        let opts = ffi::MojoCreateWaitSetOptions {
+            struct_size: mem::size_of::<ffi::MojoCreateWaitSetOptions>() as u32,
+            flags: flags,
+            _align: [],
+        };
+        let raw_opts = &opts as *const ffi::MojoCreateWaitSetOptions;
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoCreateWaitSet(raw_opts, &mut raw_handle as *mut mojo_types::MojoHandle)
+        });
+        if r != MojoResult::Okay {
+            Err(r)
+        } else {
+            Ok(WaitSet { handle: unsafe { handle::acquire(raw_handle) } })
+        }
+    }
+
+    /// Adds a handle to the underlying wait set.
+    ///
+    /// The handle that is added may go invalid, at which point the result
+    /// returned from wait_on_set for this handle will be `Cancelled'.
+    ///
+    /// One can pass in a unique cookie value which is used to identify the
+    /// handle in the wait result. Currently there are no supported flags,
+    /// but the argument is kept for future usage.
+    pub fn add(
+        &mut self,
+        handle: &Handle,
+        signals: mojo_types::HandleSignals,
+        cookie: u64,
+        flags: mojo_types::AddFlags,
+    ) -> MojoResult {
+        let opts = ffi::MojoWaitSetAddOptions {
+            struct_size: mem::size_of::<ffi::MojoWaitSetAddOptions>() as u32,
+            flags: flags,
+            _align: [],
+        };
+        let raw_opts = &opts as *const ffi::MojoWaitSetAddOptions;
+        MojoResult::from_code(unsafe {
+            ffi::MojoWaitSetAdd(
+                self.handle.get_native_handle(),
+                handle.get_native_handle(),
+                signals,
+                cookie,
+                raw_opts,
+            )
+        })
+    }
+
+    /// Removes a handle from the underlying wait set by cookie value.
+    pub fn remove(&mut self, cookie: u64) -> MojoResult {
+        MojoResult::from_code(unsafe { ffi::MojoWaitSetRemove(self.get_native_handle(), cookie) })
+    }
+
+    /// Waits on this wait set.
+    ///
+    /// The conditions for the wait to end include:
+    /// * A handle has its requested signals satisfied.
+    /// * A handle is determined to never be able to have its requested
+    ///   signals satisfied.
+    /// * The deadline expires.
+    /// * This wait set handle becomes invalid (Fatal error in this bindings).
+    ///
+    /// On a successful wait, we return the maximum number of results that could
+    /// possibly be returned (similar to the total number of registered handles).
+    /// Additionally, populates the output vector with the results of each handle
+    /// that completed waiting.
+    ///
+    /// On a failed wait, we return the result code.
+    pub fn wait_on_set(
+        &self,
+        deadline: mojo_types::MojoDeadline,
+        output: &mut Vec<mojo_types::WaitSetResult>,
+    ) -> Result<u32, MojoResult> {
+        assert!((output.capacity() as u64) <= ((1 as u64) << 32));
+        let mut num_results = output.capacity() as u32;
+        let mut max_results: u32 = 0;
+        let mut output_ptr = output.as_mut_ptr();
+        if num_results == 0 {
+            output_ptr = ptr::null_mut();
+        }
+        let r = MojoResult::from_code(unsafe {
+            ffi::MojoWaitSetWait(
+                self.handle.get_native_handle(),
+                deadline,
+                &mut num_results as *mut u32,
+                output_ptr,
+                &mut max_results as *mut u32,
+            )
+        });
+        unsafe {
+            output.set_len(num_results as usize);
+        }
+        if r == MojoResult::Okay {
+            Ok(max_results)
+        } else {
+            Err(r)
+        }
+    }
+}
+
+impl CastHandle for WaitSet {
+    /// Generates a WaitSet from an untyped handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    unsafe fn from_untyped(handle: handle::UntypedHandle) -> Self {
+        WaitSet { handle: handle }
+    }
+
+    /// Consumes this object and produces a plain handle wrapper
+    /// See mojo::system::handle for information on untyped vs. typed
+    fn as_untyped(self) -> handle::UntypedHandle {
+        self.handle
+    }
+}
+
+impl Handle for WaitSet {
+    /// Returns the native handle wrapped by this structure.
+    ///
+    /// See mojo::system::handle for information on handle wrappers
+    fn get_native_handle(&self) -> mojo_types::MojoHandle {
+        self.handle.get_native_handle()
+    }
+}
diff --git a/mojo/public/rust/tests/encoding.rs b/mojo/public/rust/tests/encoding.rs
new file mode 100644
index 0000000..45d2f3b
--- /dev/null
+++ b/mojo/public/rust/tests/encoding.rs
@@ -0,0 +1,705 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! Tests encoding and decoding functionality in the bindings package
+//!
+//! Test failure is defined as the function returning via panicking
+//! and the result being caught in the test! macro. If a test function
+//! returns without panicking, it is assumed to pass.
+
+#[macro_use]
+extern crate mojo;
+
+use mojo::bindings::encoding::Context;
+use mojo::bindings::message::MessageHeader;
+use mojo::bindings::mojom::{MojomInterface, MojomPointer, MojomStruct, MojomUnion};
+
+use mojo::system;
+use mojo::system::Handle;
+
+use std::collections::HashMap;
+
+#[macro_use]
+mod util;
+
+use util::mojom_validation::*;
+
+/// This macro is a wrapper for the tests! macro as it takes advantage of the
+/// shared code between tests.
+///
+/// Given a test name, it will generate a test function. In this test function
+/// we perform the following steps:
+///   1. Decode the header of the validation input.
+///   2. Verify the decoded header is what we expect.
+///   3. Decode the payload of the validation input.
+///   4. Verify the decoded payload is what we expect.
+///   5. Take the decoded payload and re-encode.
+///   6. Decode this re-encoded payload.
+///   7. Verify the re-decoded payload is what we expect.
+///
+/// Each test should sufficiently verify the operation of the encoding and decoding
+/// frameworks as we first verify the decoder works correctly on the "golden files",
+/// then verify that the encoder works by encoding the decoded output, and decoding
+/// that once again.
+macro_rules! encoding_tests {
+    ($($name:ident { MessageHeader => $header_cls:expr, $req_type:ident => $cls:expr } )*) => {
+        tests! {
+            $(
+            fn $name() {
+                let data = include_str!(concat!("../../interfaces/bindings/tests/data/validation/",
+                                                stringify!($name),
+                                                ".data"));
+                match util::parse_validation_test(data) {
+                    Ok((mut data, num_handles)) => {
+                        let mut mock_handles = Vec::with_capacity(num_handles);
+                        for _ in 0..num_handles {
+                            mock_handles.push(unsafe { system::acquire(0) });
+                        }
+                        println!("{}: Decoding header", stringify!($name));
+                        let header = MessageHeader::deserialize(&mut data[..], Vec::new()).expect("Should not error");
+                        let ctxt: Context = Default::default();
+                        let header_size = header.serialized_size(&ctxt);
+                        let header_cls = $header_cls;
+                        println!("{}: Verifying decoded header", stringify!($name));
+                        header_cls(header);
+                        let payload_buffer = &mut data[header_size..];
+                        let cls = $cls;
+                        println!("{}: Decoding payload", stringify!($name));
+                        let decoded_payload = $req_type::deserialize(payload_buffer, mock_handles).expect("Should not error");
+                        println!("{}: Verifying decoded payload", stringify!($name));
+                        cls(&decoded_payload);
+                        println!("{}: Re-encoding payload", stringify!($name));
+                        let (mut encoded_payload, handles) = decoded_payload.auto_serialize();
+                        println!("{}: Decoding payload again", stringify!($name));
+                        let redecoded_payload = $req_type::deserialize(&mut encoded_payload[..], handles).expect("Should not error");
+                        println!("{}: Verifying decoded payload again", stringify!($name));
+                        cls(&redecoded_payload);
+                    },
+                    Err(msg) => panic!("Error: {}", msg),
+                }
+            }
+            )*
+        }
+    }
+}
+
+encoding_tests! {
+    conformance_mthd0_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 0);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod0Request => {
+            |payload: &ConformanceTestInterfaceMethod0Request| {
+                assert_eq!(payload.param0, -1.0);
+            }
+        }
+    }
+    conformance_mthd1_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 1);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod1Request => {
+            |payload: &ConformanceTestInterfaceMethod1Request| {
+                assert_eq!(payload.param0.i, 1234);
+            }
+        }
+    }
+    conformance_mthd2_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 2);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod2Request => {
+            |payload: &ConformanceTestInterfaceMethod2Request| {
+                assert_eq!(payload.param0.struct_a.i, 12345);
+                assert_eq!(payload.param1.i, 67890);
+            }
+        }
+    }
+    conformance_mthd3_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 3);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod3Request => {
+            |payload: &ConformanceTestInterfaceMethod3Request| {
+                assert_eq!(payload.param0, vec![true, false, true, false,
+                                                true, false, true, false,
+                                                true, true,  true, true]);
+            }
+        }
+    }
+    conformance_mthd4_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 4);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod4Request => {
+            |payload: &ConformanceTestInterfaceMethod4Request| {
+                assert_eq!(payload.param0.data, vec![0, 1, 2]);
+                assert_eq!(payload.param1, vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);
+            }
+        }
+    }
+    conformance_mthd5_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 5);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod5Request => {
+            |payload: &ConformanceTestInterfaceMethod5Request| {
+                assert_eq!(payload.param0.struct_d.message_pipes.len(), 2);
+                for h in payload.param0.struct_d.message_pipes.iter() {
+                    assert_eq!(h.get_native_handle(), 0);
+                }
+                assert_eq!(payload.param0.data_pipe_consumer.get_native_handle(), 0);
+                assert_eq!(payload.param1.get_native_handle(), 0);
+            }
+        }
+    }
+    conformance_mthd6_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 6);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod6Request => {
+            |payload: &ConformanceTestInterfaceMethod6Request| {
+                assert_eq!(payload.param0, vec![vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]);
+            }
+        }
+    }
+    conformance_mthd7_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 7);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod7Request => {
+            |payload: &ConformanceTestInterfaceMethod7Request| {
+                assert_eq!(payload.param0.fixed_size_array, [0, 1, 2]);
+                assert_eq!(payload.param1, [None, Some([0, 1, 2])]);
+            }
+        }
+    }
+    conformance_mthd8_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 8);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod8Request => {
+            |payload: &ConformanceTestInterfaceMethod8Request| {
+                assert_eq!(payload.param0,
+                    vec![None, Some(vec![String::from_utf8(vec![0, 1, 2, 3, 4]).unwrap()]), None]);
+            }
+        }
+    }
+    conformance_mthd9_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 9);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod9Request => {
+            |payload: &ConformanceTestInterfaceMethod9Request| {
+                assert!(payload.param0.is_some());
+                if let Some(ref v) = payload.param0 {
+                    assert_eq!(v.len(), 2);
+                    assert_eq!(v[0].len(), 2);
+                    assert_eq!(v[1].len(), 3);
+                    assert!(v[0][0].is_some());
+                    assert!(v[0][1].is_none());
+                    assert!(v[1][0].is_some());
+                    assert!(v[1][1].is_none());
+                    assert!(v[1][2].is_some());
+                    assert_eq!(v[0][0].as_ref().unwrap().get_native_handle(), 0);
+                    assert_eq!(v[1][0].as_ref().unwrap().get_native_handle(), 0);
+                    assert_eq!(v[1][2].as_ref().unwrap().get_native_handle(), 0);
+                }
+            }
+        }
+    }
+    conformance_mthd9_good_null_array {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 9);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod9Request => {
+            |payload: &ConformanceTestInterfaceMethod9Request| {
+                assert!(payload.param0.is_none());
+            }
+        }
+    }
+    conformance_mthd10_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 10);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod10Request => {
+            |payload: &ConformanceTestInterfaceMethod10Request| {
+                let mut map = HashMap::with_capacity(2);
+                map.insert(String::from_utf8(vec![0, 1, 2, 3, 4]).unwrap(), 1);
+                map.insert(String::from_utf8(vec![5, 6, 7, 8, 9]).unwrap(), 2);
+                assert_eq!(payload.param0, map);
+            }
+        }
+    }
+    // Non-unique keys are strange...
+    // Right now, we handle them by silently overwriting.
+    // Maybe this will be an error in the future.
+    // The insert calls below reflect the duplicate keys that the
+    // test provides, and an example as to how overwriting happens.
+    conformance_mthd10_good_non_unique_keys {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 10);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod10Request => {
+            |payload: &ConformanceTestInterfaceMethod10Request| {
+                let mut map = HashMap::with_capacity(2);
+                map.insert(String::from_utf8(vec![0, 1, 2, 3, 4]).unwrap(), 1);
+                map.insert(String::from_utf8(vec![0, 1, 2, 3, 4]).unwrap(), 2);
+                assert_eq!(payload.param0, map);
+            }
+        }
+    }
+    conformance_mthd11_good_version0 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 11);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod11Request => {
+            |payload: &ConformanceTestInterfaceMethod11Request| {
+                assert_eq!(payload.param0.i, 123);
+                assert_eq!(payload.param0.b, false);
+                assert!(payload.param0.struct_a.is_none());
+                assert!(payload.param0.str.is_none());
+            }
+        }
+    }
+    conformance_mthd11_good_version1 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 11);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod11Request => {
+            |payload: &ConformanceTestInterfaceMethod11Request| {
+                assert_eq!(payload.param0.i, 123);
+                assert_eq!(payload.param0.b, false);
+                assert!(payload.param0.struct_a.is_none());
+                assert!(payload.param0.str.is_none());
+            }
+        }
+    }
+    conformance_mthd11_good_version2 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 11);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod11Request => {
+            |payload: &ConformanceTestInterfaceMethod11Request| {
+                assert_eq!(payload.param0.i, 123);
+                assert_eq!(payload.param0.b, false);
+                assert!(payload.param0.struct_a.is_none());
+                assert!(payload.param0.str.is_none());
+            }
+        }
+    }
+    conformance_mthd11_good_version3 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 11);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod11Request => {
+            |payload: &ConformanceTestInterfaceMethod11Request| {
+                assert_eq!(payload.param0.i, 123);
+                assert_eq!(payload.param0.b, true);
+                assert!(payload.param0.struct_a.is_none());
+                assert_eq!(payload.param0.str, Some(String::from_utf8(vec![0, 1]).unwrap()));
+            }
+        }
+    }
+    conformance_mthd11_good_version_newer_than_known_1 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 11);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod11Request => {
+            |payload: &ConformanceTestInterfaceMethod11Request| {
+                assert_eq!(payload.param0.i, 123);
+                assert_eq!(payload.param0.b, true);
+                assert!(payload.param0.struct_a.is_none());
+                assert_eq!(payload.param0.str, Some(String::from_utf8(vec![0, 1]).unwrap()));
+            }
+        }
+    }
+    conformance_mthd11_good_version_newer_than_known_2 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 11);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod11Request => {
+            |payload: &ConformanceTestInterfaceMethod11Request| {
+                assert_eq!(payload.param0.i, 123);
+                assert_eq!(payload.param0.b, true);
+                assert!(payload.param0.struct_a.is_none());
+                assert_eq!(payload.param0.str, Some(String::from_utf8(vec![0, 1]).unwrap()));
+            }
+        }
+    }
+    conformance_mthd13_good_1 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 13);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod13Request => {
+            |payload: &ConformanceTestInterfaceMethod13Request| {
+                assert!(payload.param0.is_none());
+                assert_eq!(payload.param1, 65535);
+                assert!(payload.param2.is_none());
+            }
+        }
+    }
+    conformance_mthd13_good_2 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 13);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod13Request => {
+            |payload: &ConformanceTestInterfaceMethod13Request| {
+                assert!(payload.param0.is_some());
+                assert_eq!(payload.param0.as_ref().unwrap().pipe().get_native_handle(), 0);
+                assert_eq!(payload.param1, 65535);
+                assert!(payload.param2.is_some());
+                assert_eq!(payload.param2.as_ref().unwrap().pipe().get_native_handle(), 0);
+            }
+        }
+    }
+    conformance_mthd14_good_1 {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::a(ref val) => assert_eq!(*val, 54),
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_array_in_union {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::d(ref val) => assert_eq!(*val, Some(vec![0, 1, 2])),
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_map_in_union {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                let mut map = HashMap::with_capacity(2);
+                map.insert(String::from_utf8(vec![0, 1, 2, 3, 4]).unwrap(), 1);
+                map.insert(String::from_utf8(vec![5, 6, 7, 8, 9]).unwrap(), 2);
+                match payload.param0 {
+                    UnionA::e(ref val) => assert_eq!(*val, Some(map)),
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_nested_union {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::f(ref val) => {
+                        assert!(val.is_some());
+                        let inner = val.as_ref().unwrap();
+                        match *inner {
+                            UnionB::b(inner_val) => assert_eq!(inner_val, 10),
+                            _ => panic!("Incorrect inner union variant! Tag found: {}", inner.get_tag()),
+                        }
+                    },
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_null_array_in_union {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::d(ref val) => assert_eq!(*val, None),
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_null_map_in_union {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::e(ref val) => assert_eq!(*val, None),
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_struct_in_union {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::c(ref val) => {
+                        let struct_val = val.as_ref().unwrap();
+                        assert_eq!(struct_val.i, 20);
+                    },
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd14_good_unknown_union_tag {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 14);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod14Request => {
+            |payload: &ConformanceTestInterfaceMethod14Request| {
+                match payload.param0 {
+                    UnionA::_Unknown(ref val) => assert_eq!(*val, 54),
+                    _ => panic!("Incorrect union variant! Tag found: {}", payload.param0.get_tag()),
+                }
+            }
+        }
+    }
+    conformance_mthd15_good_union_in_array {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 15);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod15Request => {
+            |payload: &ConformanceTestInterfaceMethod15Request| {
+                assert_eq!(payload.param0.a, true);
+                assert_eq!(payload.param0.b, 22);
+                assert!(payload.param0.c.is_none());
+                assert!(payload.param0.d.is_some());
+                assert!(payload.param0.e.is_none());
+                let array = payload.param0.d.as_ref().unwrap();
+                assert_eq!(array.len(), 3);
+                for u in array.iter() {
+                    match *u {
+                        UnionA::b(ref val) => assert_eq!(*val, 10),
+                        _ => panic!("Incorrect union variant! Tag found: {}", u.get_tag()),
+                    }
+                }
+            }
+        }
+    }
+    conformance_mthd15_good_union_in_map {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 15);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod15Request => {
+            |payload: &ConformanceTestInterfaceMethod15Request| {
+                assert_eq!(payload.param0.a, true);
+                assert_eq!(payload.param0.b, 22);
+                assert!(payload.param0.c.is_none());
+                assert!(payload.param0.d.is_none());
+                assert!(payload.param0.e.is_some());
+                let map = payload.param0.e.as_ref().unwrap();
+                assert_eq!(map.len(), 3);
+                let mut expect_keys = HashMap::with_capacity(3);
+                expect_keys.insert(8, false);
+                expect_keys.insert(7, false);
+                expect_keys.insert(1, false);
+                for (key, value) in map.iter() {
+                    expect_keys.insert(*key, true);
+                    match *value {
+                        UnionA::b(ref val) => assert_eq!(*val, 10),
+                        _ => panic!("Incorrect union variant! Tag found: {}", value.get_tag()),
+                    }
+                }
+                for (key, value) in expect_keys.iter() {
+                    if *value == false {
+                        panic!("Expected key `{}`, but not found!", *key);
+                    }
+                }
+            }
+        }
+    }
+    conformance_mthd15_good_union_in_struct {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 0);
+                assert_eq!(header.name, 15);
+                assert_eq!(header.flags, 0);
+            }
+        },
+        ConformanceTestInterfaceMethod15Request => {
+            |payload: &ConformanceTestInterfaceMethod15Request| {
+                assert_eq!(payload.param0.a, true);
+                assert_eq!(payload.param0.b, 22);
+                assert!(payload.param0.c.is_some());
+                assert!(payload.param0.d.is_none());
+                assert!(payload.param0.e.is_none());
+                let union_val = payload.param0.c.as_ref().unwrap();
+                match *union_val {
+                    UnionA::b(ref val) => assert_eq!(*val, 54),
+                    _ => panic!("Incorrect union variant! Tag found: {}", union_val.get_tag()),
+                }
+            }
+        }
+    }
+    integration_intf_rqst_mthd0_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 1);
+                assert_eq!(header.name, 0);
+                assert_eq!(header.flags, 1);
+                assert_eq!(header.request_id, 7);
+            }
+        },
+        IntegrationTestInterfaceMethod0Request => {
+            |payload: &IntegrationTestInterfaceMethod0Request| {
+                assert_eq!(payload.param0.a, -1);
+            }
+        }
+    }
+    integration_intf_resp_mthd0_good {
+        MessageHeader => {
+            |header: MessageHeader| {
+                assert_eq!(header.version, 1);
+                assert_eq!(header.name, 0);
+                assert_eq!(header.flags, 2);
+                assert_eq!(header.request_id, 1);
+            }
+        },
+        IntegrationTestInterfaceMethod0Response => {
+            |payload: &IntegrationTestInterfaceMethod0Response| {
+                assert_eq!(payload.param0, vec![0]);
+            }
+        }
+    }
+}
diff --git a/mojo/public/rust/tests/integration.rs b/mojo/public/rust/tests/integration.rs
new file mode 100644
index 0000000..3f551f8
--- /dev/null
+++ b/mojo/public/rust/tests/integration.rs
@@ -0,0 +1,67 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! Tests some higher-level functionality of Mojom interfaces.
+//!
+//! Test failure is defined as the function returning via panicking
+//! and the result being caught in the test! macro. If a test function
+//! returns without panicking, it is assumed to pass.
+
+#[macro_use]
+extern crate mojo;
+
+#[macro_use]
+mod util;
+
+use mojo::bindings::mojom::{MojomInterface, MojomInterfaceRecv, MojomInterfaceSend};
+use mojo::system::message_pipe;
+use mojo::system::{Handle, MOJO_INDEFINITE};
+
+use std::thread;
+
+use util::mojom_validation::*;
+
+tests! {
+    // Tests basic client and server interaction over a thread
+    fn send_and_recv() {
+        let (endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        // Client and server handles
+        let client = IntegrationTestInterfaceClient::new(endpt0);
+        let server = IntegrationTestInterfaceServer::with_version(endpt1, 0);
+        // Client thread
+        let handle = thread::spawn(move || {
+            // Send request
+            client.send_request(5, IntegrationTestInterfaceMethod0Request {
+                param0: BasicStruct {
+                    a: -1,
+                },
+            }).unwrap();
+            // Wait for response
+            client.pipe().wait(signals!(Signals::Readable), MOJO_INDEFINITE);
+            // Decode response
+            let (req_id, options) = client.recv_response().unwrap();
+            assert_eq!(req_id, 5);
+            match options {
+                IntegrationTestInterfaceResponseOption::IntegrationTestInterfaceMethod0(msg) => {
+                    assert_eq!(msg.param0, vec![1, 2, 3]);
+                },
+            }
+        });
+        // Wait for request
+        server.pipe().wait(signals!(Signals::Readable), MOJO_INDEFINITE);
+        // Decode request
+        let (req_id, options) = server.recv_response().unwrap();
+        assert_eq!(req_id, 5);
+        match options {
+            IntegrationTestInterfaceRequestOption::IntegrationTestInterfaceMethod0(msg) => {
+                assert_eq!(msg.param0.a, -1);
+            },
+        }
+        // Send response
+        server.send_request(5, IntegrationTestInterfaceMethod0Response {
+            param0: vec![1, 2, 3],
+        }).unwrap();
+        let _ = handle.join();
+    }
+}
diff --git a/mojo/public/rust/tests/regression.rs b/mojo/public/rust/tests/regression.rs
new file mode 100644
index 0000000..9b10159
--- /dev/null
+++ b/mojo/public/rust/tests/regression.rs
@@ -0,0 +1,106 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! Tests validation functionality in the bindings package
+//!
+//! Test failure is defined as the function returning via panicking
+//! and the result being caught in the test! macro. If a test function
+//! returns without panicking, it is assumed to pass.
+
+#[macro_use]
+extern crate mojo;
+
+use mojo::bindings::decoding::{Decoder, ValidationError};
+use mojo::bindings::encoding;
+use mojo::bindings::encoding::{Context, DataHeaderValue, Encoder};
+use mojo::bindings::mojom::{MojomEncodable, MojomPointer, MojomStruct};
+use mojo::system;
+use mojo::system::UntypedHandle;
+
+#[macro_use]
+mod util;
+
+const STRUCT_A_VERSIONS: [(u32, u32); 1] = [(0, 16)];
+
+struct StructA<T: MojomEncodable> {
+    param0: [T; 3],
+}
+
+impl<T: MojomEncodable> MojomPointer for StructA<T> {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let _version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&STRUCT_A_VERSIONS) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <[T; 3]>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(StructA { param0: param0 })
+    }
+}
+
+impl<T: MojomEncodable> MojomEncodable for StructA<T> {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl<T: MojomEncodable> MojomStruct for StructA<T> {}
+
+tests! {
+    // Fixed size arrays have complex and unsafe semantics to ensure
+    // there are no memory leaks. We test this behavior here to make
+    // sure memory isn't becoming corrupted.
+    fn regression_fixed_size_array_error_propagates_safely() {
+        let handle1 = unsafe { system::acquire(0) };
+        let handle2 = unsafe { system::acquire(0) };
+        let handle3 = unsafe { system::acquire(0) };
+        let val = StructA {
+            param0: [handle1, handle2, handle3],
+        };
+        let (mut buffer, mut handles) = val.auto_serialize();
+        handles.truncate(1);
+        let new_val = <StructA<UntypedHandle>>::deserialize(&mut buffer[..], handles);
+        match new_val {
+            Ok(_) => panic!("Value should not be okay!"),
+            Err(err) => assert_eq!(err, ValidationError::IllegalHandle),
+        }
+    }
+
+    // Same as the above test, but verifies that drop() is called.
+    // For the only handle that should drop, we make the handle some
+    // random number which is potentially a valid handle. When on
+    // drop() we try to close it, we should panic.
+    #[should_panic]
+    fn regression_fixed_size_array_verify_drop() {
+        let handle1 = unsafe { system::acquire(42) };
+        let handle2 = unsafe { system::acquire(0) };
+        let handle3 = unsafe { system::acquire(0) };
+        let val = StructA {
+            param0: [handle1, handle2, handle3],
+        };
+        let (mut buffer, mut handles) = val.auto_serialize();
+        handles.truncate(1);
+        let new_val = <StructA<UntypedHandle>>::deserialize(&mut buffer[..], handles);
+        match new_val {
+            Ok(_) => panic!("Value should not be okay!"),
+            Err(err) => assert_eq!(err, ValidationError::IllegalHandle),
+        }
+    }
+}
diff --git a/mojo/public/rust/tests/run_loop.rs b/mojo/public/rust/tests/run_loop.rs
new file mode 100644
index 0000000..47aed22
--- /dev/null
+++ b/mojo/public/rust/tests/run_loop.rs
@@ -0,0 +1,400 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! Tests all functionality in the system package
+//!
+//! Test failure is defined as the function returning via panicking
+//! and the result being caught in the test! macro. If a test function
+//! returns without panicking, it is assumed to pass.
+
+#[macro_use]
+extern crate mojo;
+
+#[macro_use]
+mod util;
+
+use mojo::bindings::run_loop;
+use mojo::bindings::run_loop::{Handler, RunLoop, Token, WaitError};
+use mojo::system::message_pipe;
+use mojo::system::MOJO_INDEFINITE;
+
+use std::cell::Cell;
+use std::rc::Rc;
+
+struct HandlerExpectReady {}
+
+impl Handler for HandlerExpectReady {
+    fn on_ready(&mut self, runloop: &mut RunLoop, token: Token) {
+        runloop.deregister(token);
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected ready");
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected ready");
+    }
+}
+
+struct HandlerExpectTimeout {}
+
+impl Handler for HandlerExpectTimeout {
+    fn on_ready(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Ready when expected timeout");
+    }
+    fn on_timeout(&mut self, runloop: &mut RunLoop, token: Token) {
+        runloop.deregister(token);
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected timeout");
+    }
+}
+
+struct HandlerExpectError {}
+
+impl Handler for HandlerExpectError {
+    fn on_ready(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Ready when expected error");
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected error");
+    }
+    fn on_error(&mut self, runloop: &mut RunLoop, token: Token, error: WaitError) {
+        assert_eq!(error, WaitError::Unsatisfiable);
+        runloop.deregister(token);
+    }
+}
+
+struct HandlerQuit {}
+
+impl Handler for HandlerQuit {
+    fn on_ready(&mut self, runloop: &mut RunLoop, _token: Token) {
+        runloop.quit();
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected error");
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected ready");
+    }
+}
+
+struct HandlerRegister {}
+
+impl Handler for HandlerRegister {
+    fn on_ready(&mut self, runloop: &mut RunLoop, token: Token) {
+        let (_, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        let _ = runloop.register(
+            &endpt1,
+            signals!(Signals::Writable),
+            MOJO_INDEFINITE,
+            HandlerDeregisterOther { other: token },
+        );
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected error");
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected ready");
+    }
+}
+
+struct HandlerDeregisterOther {
+    other: Token,
+}
+
+impl Handler for HandlerDeregisterOther {
+    fn on_ready(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Ready when expected error");
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected error");
+    }
+    fn on_error(&mut self, runloop: &mut RunLoop, token: Token, error: WaitError) {
+        assert_eq!(error, WaitError::HandleClosed);
+        runloop.deregister(token);
+        runloop.deregister(self.other.clone());
+    }
+}
+
+struct HandlerReregister {
+    count: u64,
+}
+
+impl Handler for HandlerReregister {
+    fn on_ready(&mut self, runloop: &mut RunLoop, token: Token) {
+        runloop.deregister(token);
+    }
+    fn on_timeout(&mut self, runloop: &mut RunLoop, token: Token) {
+        if self.count < 10 {
+            runloop.reregister(&token, signals!(Signals::Readable), 0);
+            self.count += 1;
+        } else {
+            runloop.reregister(&token, signals!(Signals::Writable), MOJO_INDEFINITE);
+        }
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected ready");
+    }
+}
+
+struct HandlerNesting {
+    count: u64,
+}
+
+impl Handler for HandlerNesting {
+    fn on_ready(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Ready when expected timeout");
+    }
+    fn on_timeout(&mut self, runloop: &mut RunLoop, token: Token) {
+        let mut nested_runloop = run_loop::RunLoop::new();
+        if self.count < 10 {
+            let handler = HandlerNesting { count: self.count + 1 };
+            let (endpt0, _endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+            let _ = nested_runloop.register(&endpt0, signals!(Signals::Readable), 0, handler);
+            nested_runloop.run();
+        } else {
+            let handler = HandlerNesting { count: self.count + 1 };
+            let (endpt0, _) = message_pipe::create(mpflags!(Create::None)).unwrap();
+            let _ = nested_runloop.register(&endpt0, signals!(Signals::Readable), 0, handler);
+            nested_runloop.run();
+        }
+        runloop.deregister(token);
+    }
+    fn on_error(&mut self, runloop: &mut RunLoop, token: Token, error: WaitError) {
+        assert_eq!(error, WaitError::Unsatisfiable);
+        assert_eq!(self.count, 11);
+        runloop.deregister(token);
+    }
+}
+
+struct HandlerBadNesting {}
+
+impl Handler for HandlerBadNesting {
+    fn on_ready(&mut self, runloop: &mut RunLoop, _token: Token) {
+        runloop.quit();
+    }
+    fn on_timeout(&mut self, runloop: &mut RunLoop, _token: Token) {
+        runloop.run();
+    }
+    fn on_error(&mut self, runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        runloop.quit();
+    }
+}
+
+struct HandlerTasks {
+    count: Rc<Cell<u64>>,
+}
+
+impl Handler for HandlerTasks {
+    fn on_ready(&mut self, runloop: &mut RunLoop, token: Token) {
+        let r = self.count.clone();
+        let _ = runloop.post_task(
+            move |_runloop| {
+                let val = (*r).get();
+                (*r).set(val + 1);
+            },
+            10,
+        );
+        if (*self.count).get() > 10 {
+            runloop.deregister(token);
+        }
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected error");
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected ready");
+    }
+}
+
+struct NestedTasks {
+    count: Rc<Cell<u64>>,
+    quitter: bool,
+}
+
+impl Handler for NestedTasks {
+    fn on_ready(&mut self, runloop: &mut RunLoop, token: Token) {
+        let r = self.count.clone();
+        let quit = self.quitter;
+        let _ = runloop.post_task(
+            move |runloop| {
+                let r2 = r.clone();
+                let tk = token.clone();
+                if (*r).get() < 10 {
+                    let _ = runloop.post_task(
+                        move |_runloop| {
+                            let val = (*r2).get();
+                            (*r2).set(val + 1);
+                        },
+                        0,
+                    );
+                } else {
+                    if quit {
+                        runloop.quit();
+                    } else {
+                        runloop.deregister(tk);
+                    }
+                }
+            },
+            0,
+        );
+    }
+    fn on_timeout(&mut self, _runloop: &mut RunLoop, _token: Token) {
+        panic!("Timed-out when expected error");
+    }
+    fn on_error(&mut self, _runloop: &mut RunLoop, _token: Token, _error: WaitError) {
+        panic!("Error when expected ready");
+    }
+}
+
+tests! {
+    // Verifies that after adding and removing, we can run, exit and be
+    // left in a consistent state.
+    fn add_remove() {
+        run_loop::with_current(|runloop| {
+            let (endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+            let token0 = runloop.register(&endpt0, signals!(Signals::Writable), 0, HandlerExpectReady {});
+            let token1 = runloop.register(&endpt1, signals!(Signals::Writable), 0, HandlerExpectReady {});
+            runloop.deregister(token1);
+            runloop.deregister(token0);
+            runloop.run();
+        })
+    }
+
+    // Verifies that generated tokens are unique.
+    fn tokens() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        let mut vec = Vec::new();
+        run_loop::with_current(|runloop| {
+            for _ in 0..10 {
+                vec.push(runloop.register(&endpt1, signals!(Signals::None), 0, HandlerExpectReady {}));
+            }
+            for i in 0..10 {
+                for j in 0..10 {
+                    if i != j {
+                        assert!(vec[i] != vec[j]);
+                    }
+                }
+            }
+        });
+    }
+
+    // Verifies that the handler's "on_ready" function is called.
+    fn notify_results() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Writable), MOJO_INDEFINITE, HandlerExpectReady {});
+            runloop.run();
+        });
+    }
+
+    // Verifies that the handler's "on_timeout" function is called.
+    fn notify_timeout() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Readable), 0, HandlerExpectTimeout {});
+            runloop.run();
+        });
+    }
+
+    // Verifies that the handler's "on_error" function is called.
+    fn notify_error() {
+        // Drop the first endpoint immediately
+        let (_, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Readable), 0, HandlerExpectError {});
+            runloop.run();
+        });
+    }
+
+    // Verifies that the handler's "on_ready" function is called which only quits.
+    fn notify_ready_quit() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Writable), MOJO_INDEFINITE, HandlerQuit {});
+            runloop.run();
+        });
+    }
+
+    // Tests more complex behavior, i.e. the interaction between two handlers.
+    fn register_deregister() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Writable), MOJO_INDEFINITE, HandlerRegister {});
+            runloop.run();
+        });
+    }
+
+    // Tests reregistering.
+    fn reregister() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Readable), 0, HandlerReregister { count: 0 });
+            runloop.run();
+        });
+    }
+
+    // Tests nesting run loops by having a handler create a new one.
+    fn nesting() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Readable), 0, HandlerNesting { count: 0 });
+            runloop.run();
+        });
+    }
+
+    // Tests to make sure nesting with the SAME runloop fails.
+    #[should_panic]
+    fn bad_nesting() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Readable), 0, HandlerBadNesting {});
+            runloop.run();
+        });
+    }
+
+    // Tests adding a simple task that adds a handler.
+    fn simple_task() {
+        run_loop::with_current(|runloop| {
+            let _ = runloop.post_task(|runloop| {
+                let (_, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+                let _ = runloop.register(&endpt1, signals!(Signals::Readable), 0, HandlerExpectError {});
+            }, 0);
+            runloop.run();
+        });
+    }
+
+    // Tests using a handler that adds a bunch of tasks.
+    fn handler_tasks() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        let r = Rc::new(Cell::new(0));
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Writable), 0, HandlerTasks { count: r.clone() });
+            runloop.run();
+            assert!((*r).get() >= 11);
+        });
+    }
+
+    // Tests using a handler that adds a bunch of tasks.
+    fn nested_tasks() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        let r = Rc::new(Cell::new(0));
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Writable), 0, NestedTasks { count: r.clone(), quitter: false });
+            runloop.run();
+            assert!((*r).get() >= 10);
+        });
+    }
+
+    // Tests using a handler that adds a bunch of tasks.
+    fn nested_tasks_quit() {
+        let (_endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        let r = Rc::new(Cell::new(0));
+        run_loop::with_current(|runloop| {
+            let _ = runloop.register(&endpt1, signals!(Signals::Writable), 0, NestedTasks { count: r.clone(), quitter: true });
+            runloop.run();
+            assert!((*r).get() >= 10);
+        });
+    }
+}
diff --git a/mojo/public/rust/tests/system.rs b/mojo/public/rust/tests/system.rs
new file mode 100644
index 0000000..bf4f1f7c
--- /dev/null
+++ b/mojo/public/rust/tests/system.rs
@@ -0,0 +1,264 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! Tests all functionality in the system package
+//!
+//! Test failure is defined as the function returning via panicking
+//! and the result being caught in the test! macro. If a test function
+//! returns without panicking, it is assumed to pass.
+
+#[macro_use]
+extern crate mojo;
+
+#[macro_use]
+mod util;
+
+use mojo::system;
+use mojo::system::core;
+use mojo::system::data_pipe;
+use mojo::system::message_pipe;
+use mojo::system::shared_buffer;
+use mojo::system::wait_set;
+use mojo::system::{CastHandle, Handle};
+
+use std::string::String;
+use std::thread;
+use std::vec::Vec;
+
+tests! {
+    fn get_time_ticks_now() {
+        let x = core::get_time_ticks_now();
+        assert!(x >= 10);
+    }
+
+    fn handle() {
+        let sb = shared_buffer::create(sbflags!(Create::None), 1).unwrap();
+        let handle = sb.as_untyped();
+        unsafe {
+            assert_eq!((handle.get_native_handle() != 0), handle.is_valid());
+            assert!(handle.get_native_handle() != 0 && handle.is_valid());
+            let mut h2 = system::acquire(handle.get_native_handle());
+            assert!(h2.is_valid());
+            h2.invalidate();
+            assert!(!h2.is_valid());
+        }
+    }
+
+    fn shared_buffer() {
+        let bufsize = 100;
+        let sb1;
+        {
+            let mut buf;
+            {
+                let sb_c = shared_buffer::create(sbflags!(Create::None), bufsize).unwrap();
+                // Extract original handle to check against
+                let sb_h = sb_c.get_native_handle();
+                // Test casting of handle types
+                let sb_u = sb_c.as_untyped();
+                assert_eq!(sb_u.get_native_handle(), sb_h);
+                let sb = unsafe { shared_buffer::SharedBuffer::from_untyped(sb_u) };
+                assert_eq!(sb.get_native_handle(), sb_h);
+                // Test map
+                buf = sb.map(0, bufsize, sbflags!(Map::None)).unwrap();
+                assert_eq!(buf.len(), bufsize as usize);
+                // Test get info
+                let (flags, size) = sb.get_info().unwrap();
+                assert_eq!(flags, sbflags!(Info::None));
+                assert_eq!(size, bufsize);
+                buf.write(50, 34);
+                // Test duplicate
+                sb1 = sb.duplicate(sbflags!(Duplicate::None)).unwrap();
+            }
+            // sb gets closed
+            buf.write(51, 35);
+        }
+        // buf just got closed
+        // remap to buf1 from sb1
+        let buf1 = sb1.map(50, 50, sbflags!(Map::None)).unwrap();
+        assert_eq!(buf1.len(), 50);
+        // verify buffer contents
+        assert_eq!(buf1.read(0), 34);
+        assert_eq!(buf1.read(1), 35);
+    }
+
+    fn message_pipe() {
+        let (endpt, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        // Extract original handle to check against
+        let endpt_h = endpt.get_native_handle();
+        // Test casting of handle types
+        let endpt_u = endpt.as_untyped();
+        assert_eq!(endpt_u.get_native_handle(), endpt_h);
+        {
+            let endpt0 = unsafe { message_pipe::MessageEndpoint::from_untyped(endpt_u) };
+            assert_eq!(endpt0.get_native_handle(), endpt_h);
+            {
+                let (s, r) = endpt0.wait(signals!(Signals::Readable), 0);
+                assert_eq!(r, mojo::MojoResult::DeadlineExceeded);
+                assert!(s.satisfied().is_writable());
+                assert!(s.satisfiable().is_readable());
+                assert!(s.satisfiable().is_writable());
+                assert!(s.satisfiable().is_peer_closed());
+            }
+            {
+                let (s, r) = endpt0.wait(signals!(Signals::Writable), system::MOJO_INDEFINITE);
+                assert_eq!(r, mojo::MojoResult::Okay);
+                assert!(s.satisfied().is_writable());
+                assert!(s.satisfiable().is_readable());
+                assert!(s.satisfiable().is_writable());
+                assert!(s.satisfiable().is_peer_closed());
+            }
+            match endpt0.read(mpflags!(Read::None)) {
+                Ok((_msg, _handles)) => panic!("Read should not have succeeded."),
+                Err(r) => assert_eq!(r, mojo::MojoResult::ShouldWait),
+            }
+            let hello = "hello".to_string().into_bytes();
+            let write_result = endpt1.write(&hello, Vec::new(), mpflags!(Write::None));
+            assert_eq!(write_result, mojo::MojoResult::Okay);
+            {
+                let (s, r) = endpt0.wait(signals!(Signals::Readable), system::MOJO_INDEFINITE);
+                assert_eq!(r, mojo::MojoResult::Okay);
+                assert!(s.satisfied().is_readable(), s.satisfied().is_writable());
+                assert!(s.satisfiable().is_readable());
+                assert!(s.satisfiable().is_writable());
+                assert!(s.satisfiable().is_peer_closed());
+            }
+            let hello_data;
+            match endpt0.read(mpflags!(Read::None)) {
+                Ok((msg, _handles)) => hello_data = msg,
+                Err(r) => panic!("Failed to read message on endpt0, error: {}", r),
+            }
+            assert_eq!(String::from_utf8(hello_data).unwrap(), "hello".to_string());
+            {
+                let handles: Vec<&Handle> = vec![&endpt0];
+                let signals: Vec<system::HandleSignals> = vec![signals!(Signals::Readable)];
+                let mut states: Vec<system::SignalsState> = vec![Default::default()];
+                let (idx, r) = core::wait_many(&handles, &signals, &mut states, 10);
+                assert_eq!(r, mojo::MojoResult::DeadlineExceeded);
+                assert_eq!(idx, -1);
+                assert_eq!(states.len(), 1);
+                assert!(states[0].satisfied().is_writable());
+                assert!(states[0].satisfiable().is_readable());
+                assert!(states[0].satisfiable().is_writable());
+                assert!(states[0].satisfiable().is_peer_closed());
+            }
+        }
+        let (s, r) = endpt1.wait(signals!(Signals::Readable, Signals::Writable),
+                                 system::MOJO_INDEFINITE);
+        assert_eq!(r, mojo::MojoResult::FailedPrecondition);
+        assert!(s.satisfied().is_peer_closed());
+        assert_eq!(s.satisfiable().get_bits(), system::Signals::PeerClosed as u32);
+    }
+
+    fn data_pipe() {
+        let (cons0, prod0) = data_pipe::create_default().unwrap();
+        // Extract original handle to check against
+        let cons_h = cons0.get_native_handle();
+        let prod_h = prod0.get_native_handle();
+        // Test casting of handle types
+        let cons_u = cons0.as_untyped();
+        let prod_u = prod0.as_untyped();
+        assert_eq!(cons_u.get_native_handle(), cons_h);
+        assert_eq!(prod_u.get_native_handle(), prod_h);
+        let cons = unsafe { data_pipe::Consumer::<u8>::from_untyped(cons_u) };
+        let prod = unsafe { data_pipe::Producer::<u8>::from_untyped(prod_u) };
+        assert_eq!(cons.get_native_handle(), cons_h);
+        assert_eq!(prod.get_native_handle(), prod_h);
+        // Test waiting on consumer
+        {
+            let (_s, r) = cons.wait(signals!(Signals::Readable), 0);
+            assert_eq!(r, mojo::MojoResult::DeadlineExceeded);
+        }
+        // Test waiting on producer
+        {
+            let (_s, r) = prod.wait(signals!(Signals::Writable), system::MOJO_INDEFINITE);
+            assert_eq!(r, mojo::MojoResult::Okay);
+        }
+        // Test one-phase read/write.
+        // Writing.
+        let hello = "hello".to_string().into_bytes();
+        let bytes_written = prod.write(&hello, dpflags!(Write::None)).unwrap();
+        assert_eq!(bytes_written, hello.len());
+        // Reading.
+        {
+            let (_s, r) = cons.wait(signals!(Signals::Readable), system::MOJO_INDEFINITE);
+            assert_eq!(r, mojo::MojoResult::Okay);
+        }
+        let data_string = String::from_utf8(cons.read(dpflags!(Read::None)).unwrap()).unwrap();
+        assert_eq!(data_string, "hello".to_string());
+        {
+            // Test two-phase read/write.
+            // Writing.
+            let goodbye = "goodbye".to_string().into_bytes();
+            let mut write_buf = match prod.begin(dpflags!(Write::None)) {
+                Ok(buf) => buf,
+                Err(err) => panic!("Error on write begin: {}", err),
+            };
+            assert!(write_buf.len() >= goodbye.len());
+            for i in 0..goodbye.len() {
+                write_buf[i] = goodbye[i];
+            }
+            {
+                let (_s, r) = cons.wait(signals!(Signals::Readable), 0);
+                assert_eq!(r, mojo::MojoResult::DeadlineExceeded);
+            }
+            match write_buf.commit(goodbye.len()) {
+                Some((_buf, _err)) => assert!(false),
+                None => (),
+            }
+            // Reading.
+            {
+                let (_s, r) = cons.wait(signals!(Signals::Readable), system::MOJO_INDEFINITE);
+                assert_eq!(r, mojo::MojoResult::Okay);
+            }
+            let mut data_goodbye: Vec<u8> = Vec::with_capacity(goodbye.len());
+            {
+                let read_buf = match cons.begin(dpflags!(Read::None)) {
+                    Ok(buf) => buf,
+                    Err(err) => panic!("Error on read begin: {}", err),
+                };
+                for i in 0..read_buf.len() {
+                    data_goodbye.push(read_buf[i]);
+                }
+                match cons.read(dpflags!(Read::None)) {
+                    Ok(_bytes) => assert!(false),
+                    Err(r) => assert_eq!(r, mojo::MojoResult::Busy),
+                }
+                match read_buf.commit(data_goodbye.len()) {
+                    Some((_buf, _err)) => assert!(false),
+                    None => (),
+                }
+            }
+            assert_eq!(data_goodbye.len(), goodbye.len());
+            assert_eq!(String::from_utf8(data_goodbye).unwrap(), "goodbye".to_string());
+        }
+    }
+
+    fn wait_set() {
+        let set0 = wait_set::WaitSet::new(wsflags!(Create::None)).unwrap();
+        let set_h = set0.get_native_handle();
+        let set_u = set0.as_untyped();
+        assert_eq!(set_u.get_native_handle(), set_h);
+        let mut set = unsafe { wait_set::WaitSet::from_untyped(set_u) };
+        let (endpt0, endpt1) = message_pipe::create(mpflags!(Create::None)).unwrap();
+        let signals = signals!(Signals::Readable);
+        let flags = wsflags!(Add::None);
+        assert_eq!(set.add(&endpt0, signals, 245, flags), mojo::MojoResult::Okay);
+        assert_eq!(set.add(&endpt0, signals, 245, flags), mojo::MojoResult::AlreadyExists);
+        assert_eq!(set.remove(245), mojo::MojoResult::Okay);
+        assert_eq!(set.remove(245), mojo::MojoResult::NotFound);
+        assert_eq!(set.add(&endpt0, signals, 123, flags), mojo::MojoResult::Okay);
+        thread::spawn(move || {
+            let hello = "hello".to_string().into_bytes();
+            let write_result = endpt1.write(&hello, Vec::new(), mpflags!(Write::None));
+            assert_eq!(write_result, mojo::MojoResult::Okay);
+        });
+        let mut output = Vec::with_capacity(1);
+        let max = set.wait_on_set(system::MOJO_INDEFINITE, &mut output).unwrap();
+        assert_eq!(output.len(), 1);
+        assert_eq!(output[0].cookie(), 123);
+        assert_eq!(output[0].result(), mojo::MojoResult::Okay);
+        assert!(output[0].state().satisfied().is_readable());
+        assert_eq!(max, 1);
+    }
+}
diff --git a/mojo/public/rust/tests/util/mod.rs b/mojo/public/rust/tests/util/mod.rs
new file mode 100644
index 0000000..cb1b719
--- /dev/null
+++ b/mojo/public/rust/tests/util/mod.rs
@@ -0,0 +1,98 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! This module contains useful functions and macros for testing.
+
+pub mod mojom_validation;
+
+use std::ffi::{CStr, CString};
+use std::os::raw::c_char;
+use std::ptr;
+use std::slice;
+
+/// This macro sets up tests by adding in Mojo embedder
+/// initialization.
+macro_rules! tests {
+    ( $( $( #[ $attr:meta ] )* fn $i:ident() $b:block)* ) => {
+        use std::sync::{Once, ONCE_INIT};
+        static START: Once = ONCE_INIT;
+        $(
+            #[test]
+            $(
+            #[ $attr ]
+            )*
+            fn $i() {
+                START.call_once(|| unsafe {
+                    util::InitializeMojoEmbedder();
+                });
+                $b
+            }
+        )*
+    }
+}
+
+#[link(name = "stdc++")]
+extern "C" {}
+
+#[link(name = "c")]
+extern "C" {
+    fn free(ptr: *mut u8);
+}
+
+#[link(name = "rust_embedder")]
+extern "C" {
+    pub fn InitializeMojoEmbedder();
+}
+
+#[link(name = "validation_parser")]
+extern "C" {
+    #[allow(dead_code)]
+    fn ParseValidationTest(
+        input: *const c_char,
+        num_handles: *mut usize,
+        data: *mut *mut u8,
+        data_len: *mut usize,
+    ) -> *mut c_char;
+}
+
+#[allow(dead_code)]
+pub fn parse_validation_test(input: &str) -> Result<(Vec<u8>, usize), String> {
+    let input_c = CString::new(input.to_string()).unwrap();
+    let mut num_handles: usize = 0;
+    let mut data: *mut u8 = ptr::null_mut();
+    let mut data_len: usize = 0;
+    let error = unsafe {
+        ParseValidationTest(
+            input_c.as_ptr(),
+            &mut num_handles as *mut usize,
+            &mut data as *mut *mut u8,
+            &mut data_len as *mut usize,
+        )
+    };
+    if error == ptr::null_mut() {
+        if data == ptr::null_mut() || data_len == 0 {
+            // We assume we were just given an empty file
+            Ok((Vec::new(), 0))
+        } else {
+            // Make a copy of the buffer
+            let buffer;
+            unsafe {
+                buffer = slice::from_raw_parts(data, data_len).to_vec();
+                free(data);
+            }
+            Ok((buffer, num_handles))
+        }
+    } else {
+        let err_str;
+        unsafe {
+            // Copy the error string
+            err_str = CStr::from_ptr(error)
+                .to_str()
+                .expect("Could not convert error message to UTF-8!")
+                .to_owned();
+            free(error as *mut u8);
+        }
+        Err(err_str)
+    }
+}
diff --git a/mojo/public/rust/tests/util/mojom_validation.rs b/mojo/public/rust/tests/util/mojom_validation.rs
new file mode 100644
index 0000000..00d3f0c
--- /dev/null
+++ b/mojo/public/rust/tests/util/mojom_validation.rs
@@ -0,0 +1,3215 @@
+//! This file was auto-generated by the Rust bindings generator.
+#![allow(bad_style)]
+#![allow(unused_imports)]
+#![allow(unused_variables)]
+#![allow(dead_code)]
+
+use mojo::bindings::decoding;
+use mojo::bindings::decoding::{Decoder, ValidationError};
+use mojo::bindings::encoding;
+use mojo::bindings::encoding::{Context, DataHeaderValue, Encoder, DATA_HEADER_SIZE};
+use mojo::bindings::message;
+use mojo::bindings::message::MessageHeader;
+use mojo::bindings::mojom;
+use mojo::bindings::mojom::{
+    MojomEncodable, MojomInterface, MojomInterfaceRecv, MojomInterfaceSend, MojomMessage,
+    MojomMessageOption, MojomPointer, MojomStruct, MojomUnion, UNION_SIZE,
+};
+
+use mojo::system;
+use mojo::system::message_pipe;
+use mojo::system::{CastHandle, UntypedHandle};
+
+use std::collections::HashMap;
+use std::vec::Vec;
+
+// Top-level constants:
+
+// Structs:
+// -- StructA --
+
+// Constants
+// Enums
+// Struct version information
+const StructAVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct StructA {
+    pub i: u64,
+}
+
+impl MojomPointer for StructA {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.i, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructAVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let i = match <u64>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(StructA { i: i })
+    }
+}
+
+impl MojomEncodable for StructA {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.i.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructA {}
+// -- StructB --
+
+// Constants
+// Enums
+// Struct version information
+const StructBVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct StructB {
+    pub struct_a: StructA,
+}
+
+impl MojomPointer for StructB {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.struct_a, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructBVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let struct_a = match <StructA>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(StructB { struct_a: struct_a })
+    }
+}
+
+impl MojomEncodable for StructB {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.struct_a.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructB {}
+// -- StructC --
+
+// Constants
+// Enums
+// Struct version information
+const StructCVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct StructC {
+    pub data: Vec<u8>,
+}
+
+impl MojomPointer for StructC {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.data, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructCVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let data = match <Vec<u8>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(StructC { data: data })
+    }
+}
+
+impl MojomEncodable for StructC {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.data.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructC {}
+// -- StructD --
+
+// Constants
+// Enums
+// Struct version information
+const StructDVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct StructD {
+    pub message_pipes: Vec<message_pipe::MessageEndpoint>,
+}
+
+impl MojomPointer for StructD {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.message_pipes, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructDVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let message_pipes =
+            match <Vec<message_pipe::MessageEndpoint>>::decode(decoder, context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            };
+        Ok(StructD { message_pipes: message_pipes })
+    }
+}
+
+impl MojomEncodable for StructD {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.message_pipes.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructD {}
+// -- StructE --
+
+// Constants
+// Enums
+// Struct version information
+const StructEVersions: [(u32, u32); 1] = [(0, 24)];
+
+// Struct definition
+pub struct StructE {
+    pub struct_d: StructD,
+    pub data_pipe_consumer: system::data_pipe::Consumer<u8>,
+}
+
+impl MojomPointer for StructE {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        24
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.struct_d, encoder, context.clone());
+        MojomEncodable::encode(self.data_pipe_consumer, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructEVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let struct_d = match <StructD>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let data_pipe_consumer =
+            match <system::data_pipe::Consumer<u8>>::decode(decoder, context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            };
+        Ok(StructE { struct_d: struct_d, data_pipe_consumer: data_pipe_consumer })
+    }
+}
+
+impl MojomEncodable for StructE {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.struct_d.compute_size(context.clone())
+            + self.data_pipe_consumer.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructE {}
+// -- StructF --
+
+// Constants
+// Enums
+// Struct version information
+const StructFVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct StructF {
+    pub fixed_size_array: [u8; 3],
+}
+
+impl MojomPointer for StructF {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.fixed_size_array, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructFVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let fixed_size_array = match <[u8; 3]>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(StructF { fixed_size_array: fixed_size_array })
+    }
+}
+
+impl MojomEncodable for StructF {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.fixed_size_array.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructF {}
+// -- StructG --
+
+// Constants
+// Enums
+// Struct version information
+const StructGVersions: [(u32, u32); 3] = [(0, 16), (1, 24), (3, 32)];
+
+// Struct definition
+pub struct StructG {
+    pub i: i32,
+    pub b: bool,
+    pub struct_a: Option<StructA>,
+    pub str: Option<String>,
+}
+
+impl MojomPointer for StructG {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(3)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        32
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.i, encoder, context.clone());
+        MojomEncodable::encode(self.b, encoder, context.clone());
+        MojomEncodable::encode(self.struct_a, encoder, context.clone());
+        MojomEncodable::encode(self.str, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructGVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let i = match <i32>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let b = if version >= 3 {
+            match <bool>::decode(decoder, context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            }
+        } else {
+            Default::default()
+        };
+        let struct_a = if version >= 1 {
+            match <Option<StructA>>::decode(decoder, context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            }
+        } else {
+            Default::default()
+        };
+        let str = if version >= 3 {
+            match <Option<String>>::decode(decoder, context.clone()) {
+                Ok(value) => value,
+                Err(err) => return Err(err),
+            }
+        } else {
+            Default::default()
+        };
+        Ok(StructG { i: i, b: b, struct_a: struct_a, str: str })
+    }
+}
+
+impl MojomEncodable for StructG {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.i.compute_size(context.clone())
+            + self.b.compute_size(context.clone())
+            + self.struct_a.compute_size(context.clone())
+            + self.str.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructG {}
+// -- StructH --
+
+// Constants
+// Enums
+// Struct version information
+const StructHVersions: [(u32, u32); 1] = [(0, 48)];
+
+// Struct definition
+pub struct StructH {
+    pub a: bool,
+    pub b: u8,
+    pub c: Option<UnionA>,
+    pub d: Option<Vec<UnionA>>,
+    pub e: Option<HashMap<u8, UnionA>>,
+}
+
+impl MojomPointer for StructH {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        48
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.a, encoder, context.clone());
+        MojomEncodable::encode(self.b, encoder, context.clone());
+        MojomEncodable::encode(self.c, encoder, context.clone());
+        MojomEncodable::encode(self.d, encoder, context.clone());
+        MojomEncodable::encode(self.e, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructHVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let a = match <bool>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let b = match <u8>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let c = match <Option<UnionA>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let d = match <Option<Vec<UnionA>>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let e = match <Option<HashMap<u8, UnionA>>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(StructH { a: a, b: b, c: c, d: d, e: e })
+    }
+}
+
+impl MojomEncodable for StructH {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.a.compute_size(context.clone())
+            + self.b.compute_size(context.clone())
+            + self.c.compute_size(context.clone())
+            + self.d.compute_size(context.clone())
+            + self.e.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for StructH {}
+// -- BasicStruct --
+
+// Constants
+// Enums
+// Struct version information
+const BasicStructVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct BasicStruct {
+    pub a: i32,
+}
+
+impl MojomPointer for BasicStruct {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.a, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&BasicStructVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let a = match <i32>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(BasicStruct { a: a })
+    }
+}
+
+impl MojomEncodable for BasicStruct {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.a.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for BasicStruct {}
+// -- StructWithEnum --
+
+// Constants
+// Enums
+type StructWithEnumEnumWithin = i32;
+const StructWithEnumEnumWithin_A: StructWithEnumEnumWithin = 0;
+const StructWithEnumEnumWithin_B: StructWithEnumEnumWithin = 1;
+const StructWithEnumEnumWithin_C: StructWithEnumEnumWithin = 2;
+const StructWithEnumEnumWithin_D: StructWithEnumEnumWithin = 3;
+
+const StructWithEnumEnumWithin__UNKNOWN: StructWithEnumEnumWithin = 0x7FFFFFFF;
+
+// Struct version information
+const StructWithEnumVersions: [(u32, u32); 1] = [(0, 8)];
+
+// Struct definition
+pub struct StructWithEnum {}
+
+impl MojomPointer for StructWithEnum {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        8
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {}
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&StructWithEnumVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        Ok(StructWithEnum {})
+    }
+}
+
+impl MojomEncodable for StructWithEnum {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+    }
+}
+
+impl MojomStruct for StructWithEnum {}
+
+// Mojom Unions:
+// -- UnionA --
+
+type UnionATag = u32;
+const UnionATag_a: UnionATag = 0;
+const UnionATag_b: UnionATag = 1;
+const UnionATag_c: UnionATag = 2;
+const UnionATag_d: UnionATag = 3;
+const UnionATag_e: UnionATag = 4;
+const UnionATag_f: UnionATag = 5;
+const UnionATag_g: UnionATag = 6;
+const UnionATag_h: UnionATag = 7;
+const UnionATag_i: UnionATag = 8;
+const UnionATag_j: UnionATag = 9;
+
+const UnionATag__UNKNOWN: UnionATag = 0xFFFFFFFF;
+
+pub enum UnionA {
+    a(u16),
+    b(u32),
+    c(Option<StructA>),
+    d(Option<Vec<u8>>),
+    e(Option<HashMap<String, u8>>),
+    f(Option<UnionB>),
+    g(StructA),
+    h(Vec<u8>),
+    i(HashMap<String, u8>),
+    j(UnionB),
+    _Unknown(u64),
+}
+
+impl MojomUnion for UnionA {
+    fn get_tag(&self) -> u32 {
+        match *self {
+            UnionA::a(_) => UnionATag_a,
+            UnionA::b(_) => UnionATag_b,
+            UnionA::c(_) => UnionATag_c,
+            UnionA::d(_) => UnionATag_d,
+            UnionA::e(_) => UnionATag_e,
+            UnionA::f(_) => UnionATag_f,
+            UnionA::g(_) => UnionATag_g,
+            UnionA::h(_) => UnionATag_h,
+            UnionA::i(_) => UnionATag_i,
+            UnionA::j(_) => UnionATag_j,
+            UnionA::_Unknown(_) => UnionATag__UNKNOWN,
+        }
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        match self {
+            UnionA::a(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::b(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::c(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::d(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::e(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::f(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::g(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::h(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::i(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::j(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionA::_Unknown(val) => MojomEncodable::encode(val, encoder, context.clone()),
+        }
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let tag = {
+            let mut state = decoder.get_mut(&context);
+            let bytes = state.decode::<u32>();
+            if (bytes as usize) != UNION_SIZE {
+                return Err(ValidationError::UnexpectedNullUnion);
+            }
+            state.decode::<u32>()
+        };
+        Ok(match tag {
+            UnionATag_a => UnionA::a({
+                match <u16>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_b => UnionA::b({
+                match <u32>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_c => UnionA::c({
+                match <Option<StructA>>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_d => UnionA::d({
+                match <Option<Vec<u8>>>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_e => UnionA::e({
+                match <Option<HashMap<String, u8>>>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_f => UnionA::f({
+                match <Option<UnionB>>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_g => UnionA::g({
+                match <StructA>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_h => UnionA::h({
+                match <Vec<u8>>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_i => UnionA::i({
+                match <HashMap<String, u8>>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionATag_j => UnionA::j({
+                match <UnionB>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            _ => UnionA::_Unknown(u64::decode(decoder, context.clone()).unwrap()),
+        })
+    }
+}
+
+impl MojomEncodable for UnionA {
+    impl_encodable_for_union!();
+    fn compute_size(&self, context: Context) -> usize {
+        UNION_SIZE
+            + match *self {
+                UnionA::a(ref val) => val.compute_size(context.clone()),
+                UnionA::b(ref val) => val.compute_size(context.clone()),
+                UnionA::c(ref val) => val.compute_size(context.clone()),
+                UnionA::d(ref val) => val.compute_size(context.clone()),
+                UnionA::e(ref val) => val.compute_size(context.clone()),
+                UnionA::f(ref val) => val.compute_size(context.clone()),
+                UnionA::g(ref val) => val.compute_size(context.clone()),
+                UnionA::h(ref val) => val.compute_size(context.clone()),
+                UnionA::i(ref val) => val.compute_size(context.clone()),
+                UnionA::j(ref val) => val.compute_size(context.clone()),
+                UnionA::_Unknown(ref val) => 0,
+            }
+    }
+}
+
+// -- UnionB --
+
+type UnionBTag = u32;
+const UnionBTag_a: UnionBTag = 0;
+const UnionBTag_b: UnionBTag = 1;
+const UnionBTag_c: UnionBTag = 2;
+const UnionBTag_d: UnionBTag = 3;
+
+const UnionBTag__UNKNOWN: UnionBTag = 0xFFFFFFFF;
+
+pub enum UnionB {
+    a(u16),
+    b(u32),
+    c(u64),
+    d(u32),
+    _Unknown(u64),
+}
+
+impl MojomUnion for UnionB {
+    fn get_tag(&self) -> u32 {
+        match *self {
+            UnionB::a(_) => UnionBTag_a,
+            UnionB::b(_) => UnionBTag_b,
+            UnionB::c(_) => UnionBTag_c,
+            UnionB::d(_) => UnionBTag_d,
+            UnionB::_Unknown(_) => UnionBTag__UNKNOWN,
+        }
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        match self {
+            UnionB::a(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionB::b(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionB::c(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionB::d(val) => MojomEncodable::encode(val, encoder, context.clone()),
+            UnionB::_Unknown(val) => MojomEncodable::encode(val, encoder, context.clone()),
+        }
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let tag = {
+            let mut state = decoder.get_mut(&context);
+            let bytes = state.decode::<u32>();
+            if (bytes as usize) != UNION_SIZE {
+                return Err(ValidationError::UnexpectedNullUnion);
+            }
+            state.decode::<u32>()
+        };
+        Ok(match tag {
+            UnionBTag_a => UnionB::a({
+                match <u16>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionBTag_b => UnionB::b({
+                match <u32>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionBTag_c => UnionB::c({
+                match <u64>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            UnionBTag_d => UnionB::d({
+                match <u32>::decode(decoder, context.clone()) {
+                    Ok(value) => value,
+                    Err(err) => return Err(err),
+                }
+            }),
+            _ => UnionB::_Unknown(u64::decode(decoder, context.clone()).unwrap()),
+        })
+    }
+}
+
+impl MojomEncodable for UnionB {
+    impl_encodable_for_union!();
+    fn compute_size(&self, context: Context) -> usize {
+        UNION_SIZE
+            + match *self {
+                UnionB::a(ref val) => val.compute_size(context.clone()),
+                UnionB::b(ref val) => val.compute_size(context.clone()),
+                UnionB::c(ref val) => val.compute_size(context.clone()),
+                UnionB::d(ref val) => val.compute_size(context.clone()),
+                UnionB::_Unknown(ref val) => 0,
+            }
+    }
+}
+
+// Mojom Enums:
+type BasicEnum = i32;
+const BasicEnum_A: BasicEnum = 0;
+const BasicEnum_B: BasicEnum = 1;
+const BasicEnum_C: BasicEnum = 0;
+const BasicEnum_D: BasicEnum = -3;
+const BasicEnum_E: BasicEnum = 10;
+
+const BasicEnum__UNKNOWN: BasicEnum = 0x7FFFFFFF;
+
+// Interfaces:
+// --- InterfaceA ---
+
+pub mod InterfaceA {
+    pub const SERVICE_NAME: &'static str = "";
+    pub const VERSION: u32 = 0;
+}
+
+pub struct InterfaceAClient {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl InterfaceAClient {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> InterfaceAClient {
+        InterfaceAClient { pipe: pipe, version: InterfaceA::VERSION }
+    }
+    pub fn with_version(pipe: message_pipe::MessageEndpoint, version: u32) -> InterfaceAClient {
+        InterfaceAClient { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for InterfaceAClient {
+    fn service_name() -> &'static str {
+        InterfaceA::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for InterfaceAClient {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> InterfaceAClient {
+        InterfaceAClient {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for InterfaceAClient {
+    impl_encodable_for_interface!();
+}
+
+impl<R: InterfaceARequest> MojomInterfaceSend<R> for InterfaceAClient {}
+impl MojomInterfaceRecv for InterfaceAClient {
+    type Container = InterfaceAResponseOption;
+}
+
+pub struct InterfaceAServer {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl InterfaceAServer {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> InterfaceAServer {
+        InterfaceAServer { pipe: pipe, version: InterfaceA::VERSION }
+    }
+    pub fn with_version(pipe: message_pipe::MessageEndpoint, version: u32) -> InterfaceAServer {
+        InterfaceAServer { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for InterfaceAServer {
+    fn service_name() -> &'static str {
+        InterfaceA::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for InterfaceAServer {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> InterfaceAServer {
+        InterfaceAServer {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for InterfaceAServer {
+    impl_encodable_for_interface!();
+}
+
+impl<R: InterfaceAResponse> MojomInterfaceSend<R> for InterfaceAServer {}
+impl MojomInterfaceRecv for InterfaceAServer {
+    type Container = InterfaceARequestOption;
+}
+
+// Enums
+
+// Constants
+
+pub trait InterfaceARequest: MojomMessage {}
+pub trait InterfaceAResponse: MojomMessage {}
+
+pub enum InterfaceARequestOption {}
+
+impl MojomMessageOption for InterfaceARequestOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        match header.name {
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+pub enum InterfaceAResponseOption {}
+
+impl MojomMessageOption for InterfaceAResponseOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        if header.flags != message::MESSAGE_HEADER_IS_RESPONSE {
+            return Err(ValidationError::MessageHeaderInvalidFlags);
+        }
+        match header.name {
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+// --- BoundsCheckTestInterface ---
+
+pub mod BoundsCheckTestInterface {
+    pub const SERVICE_NAME: &'static str = "this.is.the.service.name.for.BoundsCheckTestInterface";
+    pub const VERSION: u32 = 0;
+}
+
+pub struct BoundsCheckTestInterfaceClient {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl BoundsCheckTestInterfaceClient {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> BoundsCheckTestInterfaceClient {
+        BoundsCheckTestInterfaceClient { pipe: pipe, version: BoundsCheckTestInterface::VERSION }
+    }
+    pub fn with_version(
+        pipe: message_pipe::MessageEndpoint,
+        version: u32,
+    ) -> BoundsCheckTestInterfaceClient {
+        BoundsCheckTestInterfaceClient { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for BoundsCheckTestInterfaceClient {
+    fn service_name() -> &'static str {
+        BoundsCheckTestInterface::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for BoundsCheckTestInterfaceClient {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> BoundsCheckTestInterfaceClient {
+        BoundsCheckTestInterfaceClient {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for BoundsCheckTestInterfaceClient {
+    impl_encodable_for_interface!();
+}
+
+impl<R: BoundsCheckTestInterfaceRequest> MojomInterfaceSend<R> for BoundsCheckTestInterfaceClient {}
+impl MojomInterfaceRecv for BoundsCheckTestInterfaceClient {
+    type Container = BoundsCheckTestInterfaceResponseOption;
+}
+
+pub struct BoundsCheckTestInterfaceServer {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl BoundsCheckTestInterfaceServer {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> BoundsCheckTestInterfaceServer {
+        BoundsCheckTestInterfaceServer { pipe: pipe, version: BoundsCheckTestInterface::VERSION }
+    }
+    pub fn with_version(
+        pipe: message_pipe::MessageEndpoint,
+        version: u32,
+    ) -> BoundsCheckTestInterfaceServer {
+        BoundsCheckTestInterfaceServer { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for BoundsCheckTestInterfaceServer {
+    fn service_name() -> &'static str {
+        BoundsCheckTestInterface::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for BoundsCheckTestInterfaceServer {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> BoundsCheckTestInterfaceServer {
+        BoundsCheckTestInterfaceServer {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for BoundsCheckTestInterfaceServer {
+    impl_encodable_for_interface!();
+}
+
+impl<R: BoundsCheckTestInterfaceResponse> MojomInterfaceSend<R> for BoundsCheckTestInterfaceServer {}
+impl MojomInterfaceRecv for BoundsCheckTestInterfaceServer {
+    type Container = BoundsCheckTestInterfaceRequestOption;
+}
+
+// Enums
+
+// Constants
+
+pub trait BoundsCheckTestInterfaceRequest: MojomMessage {}
+pub trait BoundsCheckTestInterfaceResponse: MojomMessage {}
+
+pub enum BoundsCheckTestInterfaceRequestOption {
+    BoundsCheckTestInterfaceMethod0(BoundsCheckTestInterfaceMethod0Request),
+    BoundsCheckTestInterfaceMethod1(BoundsCheckTestInterfaceMethod1Request),
+}
+
+impl MojomMessageOption for BoundsCheckTestInterfaceRequestOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        match header.name {
+            BoundsCheckTestInterfaceMethod0::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_EXPECT_RESPONSE {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match BoundsCheckTestInterfaceMethod0Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(BoundsCheckTestInterfaceRequestOption::BoundsCheckTestInterfaceMethod0(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            BoundsCheckTestInterfaceMethod1::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match BoundsCheckTestInterfaceMethod1Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(BoundsCheckTestInterfaceRequestOption::BoundsCheckTestInterfaceMethod1(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+pub enum BoundsCheckTestInterfaceResponseOption {
+    BoundsCheckTestInterfaceMethod0(BoundsCheckTestInterfaceMethod0Response),
+}
+
+impl MojomMessageOption for BoundsCheckTestInterfaceResponseOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        if header.flags != message::MESSAGE_HEADER_IS_RESPONSE {
+            return Err(ValidationError::MessageHeaderInvalidFlags);
+        }
+        match header.name {
+            BoundsCheckTestInterfaceMethod0::ORDINAL => {
+                match BoundsCheckTestInterfaceMethod0Response::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(BoundsCheckTestInterfaceResponseOption::BoundsCheckTestInterfaceMethod0(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+/// Message: BoundsCheckTestInterfaceMethod0
+pub mod BoundsCheckTestInterfaceMethod0 {
+    pub const ORDINAL: u32 = 0;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- BoundsCheckTestInterfaceMethod0Request --
+
+// Constants
+// Enums
+// Struct version information
+const BoundsCheckTestInterfaceMethod0RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct BoundsCheckTestInterfaceMethod0Request {
+    pub param0: u8,
+}
+
+impl MojomPointer for BoundsCheckTestInterfaceMethod0Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&BoundsCheckTestInterfaceMethod0RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <u8>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(BoundsCheckTestInterfaceMethod0Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for BoundsCheckTestInterfaceMethod0Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for BoundsCheckTestInterfaceMethod0Request {}
+impl MojomMessage for BoundsCheckTestInterfaceMethod0Request {
+    fn min_version() -> u32 {
+        BoundsCheckTestInterfaceMethod0::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            1,
+            BoundsCheckTestInterfaceMethod0::ORDINAL,
+            message::MESSAGE_HEADER_EXPECT_RESPONSE,
+        )
+    }
+}
+impl BoundsCheckTestInterfaceRequest for BoundsCheckTestInterfaceMethod0Request {}
+
+// -- BoundsCheckTestInterfaceMethod0Response --
+
+// Constants
+// Enums
+// Struct version information
+const BoundsCheckTestInterfaceMethod0ResponseVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct BoundsCheckTestInterfaceMethod0Response {
+    pub param0: u8,
+}
+
+impl MojomPointer for BoundsCheckTestInterfaceMethod0Response {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&BoundsCheckTestInterfaceMethod0ResponseVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <u8>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(BoundsCheckTestInterfaceMethod0Response { param0: param0 })
+    }
+}
+
+impl MojomEncodable for BoundsCheckTestInterfaceMethod0Response {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for BoundsCheckTestInterfaceMethod0Response {}
+
+impl MojomMessage for BoundsCheckTestInterfaceMethod0Response {
+    fn min_version() -> u32 {
+        BoundsCheckTestInterfaceMethod0::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            1,
+            BoundsCheckTestInterfaceMethod0::ORDINAL,
+            message::MESSAGE_HEADER_IS_RESPONSE,
+        )
+    }
+}
+impl BoundsCheckTestInterfaceResponse for BoundsCheckTestInterfaceMethod0Response {}
+/// Message: BoundsCheckTestInterfaceMethod1
+pub mod BoundsCheckTestInterfaceMethod1 {
+    pub const ORDINAL: u32 = 1;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- BoundsCheckTestInterfaceMethod1Request --
+
+// Constants
+// Enums
+// Struct version information
+const BoundsCheckTestInterfaceMethod1RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct BoundsCheckTestInterfaceMethod1Request {
+    pub param0: u8,
+}
+
+impl MojomPointer for BoundsCheckTestInterfaceMethod1Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&BoundsCheckTestInterfaceMethod1RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <u8>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(BoundsCheckTestInterfaceMethod1Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for BoundsCheckTestInterfaceMethod1Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for BoundsCheckTestInterfaceMethod1Request {}
+impl MojomMessage for BoundsCheckTestInterfaceMethod1Request {
+    fn min_version() -> u32 {
+        BoundsCheckTestInterfaceMethod1::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            BoundsCheckTestInterfaceMethod1::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl BoundsCheckTestInterfaceRequest for BoundsCheckTestInterfaceMethod1Request {}
+
+// --- ConformanceTestInterface ---
+
+pub mod ConformanceTestInterface {
+    pub const SERVICE_NAME: &'static str = "";
+    pub const VERSION: u32 = 0;
+}
+
+pub struct ConformanceTestInterfaceClient {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl ConformanceTestInterfaceClient {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> ConformanceTestInterfaceClient {
+        ConformanceTestInterfaceClient { pipe: pipe, version: ConformanceTestInterface::VERSION }
+    }
+    pub fn with_version(
+        pipe: message_pipe::MessageEndpoint,
+        version: u32,
+    ) -> ConformanceTestInterfaceClient {
+        ConformanceTestInterfaceClient { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for ConformanceTestInterfaceClient {
+    fn service_name() -> &'static str {
+        ConformanceTestInterface::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for ConformanceTestInterfaceClient {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> ConformanceTestInterfaceClient {
+        ConformanceTestInterfaceClient {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceClient {
+    impl_encodable_for_interface!();
+}
+
+impl<R: ConformanceTestInterfaceRequest> MojomInterfaceSend<R> for ConformanceTestInterfaceClient {}
+impl MojomInterfaceRecv for ConformanceTestInterfaceClient {
+    type Container = ConformanceTestInterfaceResponseOption;
+}
+
+pub struct ConformanceTestInterfaceServer {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl ConformanceTestInterfaceServer {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> ConformanceTestInterfaceServer {
+        ConformanceTestInterfaceServer { pipe: pipe, version: ConformanceTestInterface::VERSION }
+    }
+    pub fn with_version(
+        pipe: message_pipe::MessageEndpoint,
+        version: u32,
+    ) -> ConformanceTestInterfaceServer {
+        ConformanceTestInterfaceServer { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for ConformanceTestInterfaceServer {
+    fn service_name() -> &'static str {
+        ConformanceTestInterface::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for ConformanceTestInterfaceServer {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> ConformanceTestInterfaceServer {
+        ConformanceTestInterfaceServer {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceServer {
+    impl_encodable_for_interface!();
+}
+
+impl<R: ConformanceTestInterfaceResponse> MojomInterfaceSend<R> for ConformanceTestInterfaceServer {}
+impl MojomInterfaceRecv for ConformanceTestInterfaceServer {
+    type Container = ConformanceTestInterfaceRequestOption;
+}
+
+// Enums
+
+// Constants
+
+pub trait ConformanceTestInterfaceRequest: MojomMessage {}
+pub trait ConformanceTestInterfaceResponse: MojomMessage {}
+
+pub enum ConformanceTestInterfaceRequestOption {
+    ConformanceTestInterfaceMethod3(ConformanceTestInterfaceMethod3Request),
+    ConformanceTestInterfaceMethod4(ConformanceTestInterfaceMethod4Request),
+    ConformanceTestInterfaceMethod5(ConformanceTestInterfaceMethod5Request),
+    ConformanceTestInterfaceMethod7(ConformanceTestInterfaceMethod7Request),
+    ConformanceTestInterfaceMethod12(ConformanceTestInterfaceMethod12Request),
+    ConformanceTestInterfaceMethod14(ConformanceTestInterfaceMethod14Request),
+    ConformanceTestInterfaceMethod15(ConformanceTestInterfaceMethod15Request),
+    ConformanceTestInterfaceMethod1(ConformanceTestInterfaceMethod1Request),
+    ConformanceTestInterfaceMethod2(ConformanceTestInterfaceMethod2Request),
+    ConformanceTestInterfaceMethod6(ConformanceTestInterfaceMethod6Request),
+    ConformanceTestInterfaceMethod8(ConformanceTestInterfaceMethod8Request),
+    ConformanceTestInterfaceMethod10(ConformanceTestInterfaceMethod10Request),
+    ConformanceTestInterfaceMethod11(ConformanceTestInterfaceMethod11Request),
+    ConformanceTestInterfaceMethod0(ConformanceTestInterfaceMethod0Request),
+    ConformanceTestInterfaceMethod9(ConformanceTestInterfaceMethod9Request),
+    ConformanceTestInterfaceMethod13(ConformanceTestInterfaceMethod13Request),
+}
+
+impl MojomMessageOption for ConformanceTestInterfaceRequestOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        match header.name {
+            ConformanceTestInterfaceMethod3::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod3Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod3(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod4::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod4Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod4(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod5::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod5Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod5(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod7::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod7Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod7(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod12::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_EXPECT_RESPONSE {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod12Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod12(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod14::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod14Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod14(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod15::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod15Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod15(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod1::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod1Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod1(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod2::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod2Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod2(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod6::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod6Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod6(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod8::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod8Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod8(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod10::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod10Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod10(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod11::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod11Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod11(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod0::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod0Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod0(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod9::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod9Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod9(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            ConformanceTestInterfaceMethod13::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_NO_FLAG {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match ConformanceTestInterfaceMethod13Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(ConformanceTestInterfaceRequestOption::ConformanceTestInterfaceMethod13(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+pub enum ConformanceTestInterfaceResponseOption {
+    ConformanceTestInterfaceMethod12(ConformanceTestInterfaceMethod12Response),
+}
+
+impl MojomMessageOption for ConformanceTestInterfaceResponseOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        if header.flags != message::MESSAGE_HEADER_IS_RESPONSE {
+            return Err(ValidationError::MessageHeaderInvalidFlags);
+        }
+        match header.name {
+            ConformanceTestInterfaceMethod12::ORDINAL => {
+                match ConformanceTestInterfaceMethod12Response::deserialize(buffer, handles) {
+                    Ok(value) => Ok(
+                        ConformanceTestInterfaceResponseOption::ConformanceTestInterfaceMethod12(
+                            value,
+                        ),
+                    ),
+                    Err(err) => return Err(err),
+                }
+            }
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+/// Message: ConformanceTestInterfaceMethod3
+pub mod ConformanceTestInterfaceMethod3 {
+    pub const ORDINAL: u32 = 3;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod3Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod3RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod3Request {
+    pub param0: Vec<bool>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod3Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod3RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <Vec<bool>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod3Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod3Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod3Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod3Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod3::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod3::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod3Request {}
+
+/// Message: ConformanceTestInterfaceMethod4
+pub mod ConformanceTestInterfaceMethod4 {
+    pub const ORDINAL: u32 = 4;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod4Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod4RequestVersions: [(u32, u32); 1] = [(0, 24)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod4Request {
+    pub param0: StructC,
+    pub param1: Vec<u8>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod4Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        24
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+        MojomEncodable::encode(self.param1, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod4RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructC>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let param1 = match <Vec<u8>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod4Request { param0: param0, param1: param1 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod4Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+            + self.param1.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod4Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod4Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod4::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod4::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod4Request {}
+
+/// Message: ConformanceTestInterfaceMethod5
+pub mod ConformanceTestInterfaceMethod5 {
+    pub const ORDINAL: u32 = 5;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod5Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod5RequestVersions: [(u32, u32); 1] = [(0, 24)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod5Request {
+    pub param0: StructE,
+    pub param1: system::data_pipe::Producer<u8>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod5Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        24
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+        MojomEncodable::encode(self.param1, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod5RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructE>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let param1 = match <system::data_pipe::Producer<u8>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod5Request { param0: param0, param1: param1 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod5Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+            + self.param1.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod5Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod5Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod5::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod5::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod5Request {}
+
+/// Message: ConformanceTestInterfaceMethod7
+pub mod ConformanceTestInterfaceMethod7 {
+    pub const ORDINAL: u32 = 7;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod7Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod7RequestVersions: [(u32, u32); 1] = [(0, 24)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod7Request {
+    pub param0: StructF,
+    pub param1: [Option<[u8; 3]>; 2],
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod7Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        24
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+        MojomEncodable::encode(self.param1, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod7RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructF>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let param1 = match <[Option<[u8; 3]>; 2]>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod7Request { param0: param0, param1: param1 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod7Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+            + self.param1.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod7Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod7Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod7::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod7::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod7Request {}
+
+/// Message: ConformanceTestInterfaceMethod12
+pub mod ConformanceTestInterfaceMethod12 {
+    pub const ORDINAL: u32 = 12;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod12Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod12RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod12Request {
+    pub param0: f32,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod12Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod12RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <f32>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod12Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod12Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod12Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod12Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod12::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            1,
+            ConformanceTestInterfaceMethod12::ORDINAL,
+            message::MESSAGE_HEADER_EXPECT_RESPONSE,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod12Request {}
+
+// -- ConformanceTestInterfaceMethod12Response --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod12ResponseVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod12Response {
+    pub param0: f32,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod12Response {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod12ResponseVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <f32>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod12Response { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod12Response {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod12Response {}
+
+impl MojomMessage for ConformanceTestInterfaceMethod12Response {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod12::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            1,
+            ConformanceTestInterfaceMethod12::ORDINAL,
+            message::MESSAGE_HEADER_IS_RESPONSE,
+        )
+    }
+}
+impl ConformanceTestInterfaceResponse for ConformanceTestInterfaceMethod12Response {}
+/// Message: ConformanceTestInterfaceMethod14
+pub mod ConformanceTestInterfaceMethod14 {
+    pub const ORDINAL: u32 = 14;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod14Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod14RequestVersions: [(u32, u32); 1] = [(0, 24)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod14Request {
+    pub param0: UnionA,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod14Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        24
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod14RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <UnionA>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod14Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod14Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod14Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod14Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod14::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod14::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod14Request {}
+
+/// Message: ConformanceTestInterfaceMethod15
+pub mod ConformanceTestInterfaceMethod15 {
+    pub const ORDINAL: u32 = 15;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod15Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod15RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod15Request {
+    pub param0: StructH,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod15Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod15RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructH>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod15Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod15Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod15Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod15Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod15::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod15::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod15Request {}
+
+/// Message: ConformanceTestInterfaceMethod1
+pub mod ConformanceTestInterfaceMethod1 {
+    pub const ORDINAL: u32 = 1;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod1Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod1RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod1Request {
+    pub param0: StructA,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod1Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod1RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructA>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod1Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod1Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod1Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod1Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod1::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod1::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod1Request {}
+
+/// Message: ConformanceTestInterfaceMethod2
+pub mod ConformanceTestInterfaceMethod2 {
+    pub const ORDINAL: u32 = 2;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod2Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod2RequestVersions: [(u32, u32); 1] = [(0, 24)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod2Request {
+    pub param0: StructB,
+    pub param1: StructA,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod2Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        24
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+        MojomEncodable::encode(self.param1, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod2RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructB>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let param1 = match <StructA>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod2Request { param0: param0, param1: param1 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod2Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+            + self.param1.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod2Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod2Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod2::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod2::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod2Request {}
+
+/// Message: ConformanceTestInterfaceMethod6
+pub mod ConformanceTestInterfaceMethod6 {
+    pub const ORDINAL: u32 = 6;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod6Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod6RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod6Request {
+    pub param0: Vec<Vec<u8>>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod6Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod6RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <Vec<Vec<u8>>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod6Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod6Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod6Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod6Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod6::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod6::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod6Request {}
+
+/// Message: ConformanceTestInterfaceMethod8
+pub mod ConformanceTestInterfaceMethod8 {
+    pub const ORDINAL: u32 = 8;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod8Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod8RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod8Request {
+    pub param0: Vec<Option<Vec<String>>>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod8Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod8RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <Vec<Option<Vec<String>>>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod8Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod8Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod8Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod8Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod8::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod8::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod8Request {}
+
+/// Message: ConformanceTestInterfaceMethod10
+pub mod ConformanceTestInterfaceMethod10 {
+    pub const ORDINAL: u32 = 10;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod10Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod10RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod10Request {
+    pub param0: HashMap<String, u8>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod10Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod10RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <HashMap<String, u8>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod10Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod10Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod10Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod10Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod10::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod10::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod10Request {}
+
+/// Message: ConformanceTestInterfaceMethod11
+pub mod ConformanceTestInterfaceMethod11 {
+    pub const ORDINAL: u32 = 11;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod11Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod11RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod11Request {
+    pub param0: StructG,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod11Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod11RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <StructG>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod11Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod11Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod11Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod11Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod11::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod11::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod11Request {}
+
+/// Message: ConformanceTestInterfaceMethod0
+pub mod ConformanceTestInterfaceMethod0 {
+    pub const ORDINAL: u32 = 0;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod0Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod0RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod0Request {
+    pub param0: f32,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod0Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod0RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <f32>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod0Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod0Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod0Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod0Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod0::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod0::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod0Request {}
+
+/// Message: ConformanceTestInterfaceMethod9
+pub mod ConformanceTestInterfaceMethod9 {
+    pub const ORDINAL: u32 = 9;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod9Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod9RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod9Request {
+    pub param0: Option<Vec<Vec<Option<system::UntypedHandle>>>>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod9Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod9RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <Option<Vec<Vec<Option<system::UntypedHandle>>>>>::decode(
+            decoder,
+            context.clone(),
+        ) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod9Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod9Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod9Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod9Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod9::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod9::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod9Request {}
+
+/// Message: ConformanceTestInterfaceMethod13
+pub mod ConformanceTestInterfaceMethod13 {
+    pub const ORDINAL: u32 = 13;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- ConformanceTestInterfaceMethod13Request --
+
+// Constants
+// Enums
+// Struct version information
+const ConformanceTestInterfaceMethod13RequestVersions: [(u32, u32); 1] = [(0, 32)];
+
+// Struct definition
+pub struct ConformanceTestInterfaceMethod13Request {
+    pub param0: Option<InterfaceAClient>,
+    pub param1: u32,
+    pub param2: Option<InterfaceAClient>,
+}
+
+impl MojomPointer for ConformanceTestInterfaceMethod13Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        32
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+        MojomEncodable::encode(self.param1, encoder, context.clone());
+        MojomEncodable::encode(self.param2, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&ConformanceTestInterfaceMethod13RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <Option<InterfaceAClient>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let param1 = match <u32>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        let param2 = match <Option<InterfaceAClient>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(ConformanceTestInterfaceMethod13Request {
+            param0: param0,
+            param1: param1,
+            param2: param2,
+        })
+    }
+}
+
+impl MojomEncodable for ConformanceTestInterfaceMethod13Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+            + self.param1.compute_size(context.clone())
+            + self.param2.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for ConformanceTestInterfaceMethod13Request {}
+impl MojomMessage for ConformanceTestInterfaceMethod13Request {
+    fn min_version() -> u32 {
+        ConformanceTestInterfaceMethod13::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            0,
+            ConformanceTestInterfaceMethod13::ORDINAL,
+            message::MESSAGE_HEADER_NO_FLAG,
+        )
+    }
+}
+impl ConformanceTestInterfaceRequest for ConformanceTestInterfaceMethod13Request {}
+
+// --- IntegrationTestInterface ---
+
+pub mod IntegrationTestInterface {
+    pub const SERVICE_NAME: &'static str = "";
+    pub const VERSION: u32 = 0;
+}
+
+pub struct IntegrationTestInterfaceClient {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl IntegrationTestInterfaceClient {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> IntegrationTestInterfaceClient {
+        IntegrationTestInterfaceClient { pipe: pipe, version: IntegrationTestInterface::VERSION }
+    }
+    pub fn with_version(
+        pipe: message_pipe::MessageEndpoint,
+        version: u32,
+    ) -> IntegrationTestInterfaceClient {
+        IntegrationTestInterfaceClient { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for IntegrationTestInterfaceClient {
+    fn service_name() -> &'static str {
+        IntegrationTestInterface::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for IntegrationTestInterfaceClient {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> IntegrationTestInterfaceClient {
+        IntegrationTestInterfaceClient {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for IntegrationTestInterfaceClient {
+    impl_encodable_for_interface!();
+}
+
+impl<R: IntegrationTestInterfaceRequest> MojomInterfaceSend<R> for IntegrationTestInterfaceClient {}
+impl MojomInterfaceRecv for IntegrationTestInterfaceClient {
+    type Container = IntegrationTestInterfaceResponseOption;
+}
+
+pub struct IntegrationTestInterfaceServer {
+    pipe: message_pipe::MessageEndpoint,
+    version: u32,
+}
+
+impl IntegrationTestInterfaceServer {
+    pub fn new(pipe: message_pipe::MessageEndpoint) -> IntegrationTestInterfaceServer {
+        IntegrationTestInterfaceServer { pipe: pipe, version: IntegrationTestInterface::VERSION }
+    }
+    pub fn with_version(
+        pipe: message_pipe::MessageEndpoint,
+        version: u32,
+    ) -> IntegrationTestInterfaceServer {
+        IntegrationTestInterfaceServer { pipe: pipe, version: version }
+    }
+}
+
+impl MojomInterface for IntegrationTestInterfaceServer {
+    fn service_name() -> &'static str {
+        IntegrationTestInterface::SERVICE_NAME
+    }
+    fn version(&self) -> u32 {
+        self.version
+    }
+    fn pipe(&self) -> &message_pipe::MessageEndpoint {
+        &self.pipe
+    }
+    fn unwrap(self) -> message_pipe::MessageEndpoint {
+        self.pipe
+    }
+}
+
+impl CastHandle for IntegrationTestInterfaceServer {
+    unsafe fn from_untyped(handle: system::UntypedHandle) -> IntegrationTestInterfaceServer {
+        IntegrationTestInterfaceServer {
+            pipe: message_pipe::MessageEndpoint::from_untyped(handle),
+            version: 0, // Since we have no other information, assume its the base
+        }
+    }
+    fn as_untyped(self) -> system::UntypedHandle {
+        self.pipe.as_untyped()
+    }
+}
+
+impl MojomEncodable for IntegrationTestInterfaceServer {
+    impl_encodable_for_interface!();
+}
+
+impl<R: IntegrationTestInterfaceResponse> MojomInterfaceSend<R> for IntegrationTestInterfaceServer {}
+impl MojomInterfaceRecv for IntegrationTestInterfaceServer {
+    type Container = IntegrationTestInterfaceRequestOption;
+}
+
+// Enums
+
+// Constants
+
+pub trait IntegrationTestInterfaceRequest: MojomMessage {}
+pub trait IntegrationTestInterfaceResponse: MojomMessage {}
+
+pub enum IntegrationTestInterfaceRequestOption {
+    IntegrationTestInterfaceMethod0(IntegrationTestInterfaceMethod0Request),
+}
+
+impl MojomMessageOption for IntegrationTestInterfaceRequestOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        match header.name {
+            IntegrationTestInterfaceMethod0::ORDINAL => {
+                if header.flags != message::MESSAGE_HEADER_EXPECT_RESPONSE {
+                    return Err(ValidationError::MessageHeaderInvalidFlags);
+                }
+                match IntegrationTestInterfaceMethod0Request::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(IntegrationTestInterfaceRequestOption::IntegrationTestInterfaceMethod0(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+pub enum IntegrationTestInterfaceResponseOption {
+    IntegrationTestInterfaceMethod0(IntegrationTestInterfaceMethod0Response),
+}
+
+impl MojomMessageOption for IntegrationTestInterfaceResponseOption {
+    fn decode_payload(
+        header: MessageHeader,
+        buffer: &[u8],
+        handles: Vec<UntypedHandle>,
+    ) -> Result<Self, ValidationError> {
+        if header.flags != message::MESSAGE_HEADER_IS_RESPONSE {
+            return Err(ValidationError::MessageHeaderInvalidFlags);
+        }
+        match header.name {
+            IntegrationTestInterfaceMethod0::ORDINAL => {
+                match IntegrationTestInterfaceMethod0Response::deserialize(buffer, handles) {
+                    Ok(value) => {
+                        Ok(IntegrationTestInterfaceResponseOption::IntegrationTestInterfaceMethod0(
+                            value,
+                        ))
+                    }
+                    Err(err) => return Err(err),
+                }
+            }
+            _ => Err(ValidationError::MessageHeaderUnknownMethod),
+        }
+    }
+}
+
+/// Message: IntegrationTestInterfaceMethod0
+pub mod IntegrationTestInterfaceMethod0 {
+    pub const ORDINAL: u32 = 0;
+    pub const MIN_VERSION: u32 = 0;
+}
+// -- IntegrationTestInterfaceMethod0Request --
+
+// Constants
+// Enums
+// Struct version information
+const IntegrationTestInterfaceMethod0RequestVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct IntegrationTestInterfaceMethod0Request {
+    pub param0: BasicStruct,
+}
+
+impl MojomPointer for IntegrationTestInterfaceMethod0Request {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&IntegrationTestInterfaceMethod0RequestVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <BasicStruct>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(IntegrationTestInterfaceMethod0Request { param0: param0 })
+    }
+}
+
+impl MojomEncodable for IntegrationTestInterfaceMethod0Request {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for IntegrationTestInterfaceMethod0Request {}
+impl MojomMessage for IntegrationTestInterfaceMethod0Request {
+    fn min_version() -> u32 {
+        IntegrationTestInterfaceMethod0::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            1,
+            IntegrationTestInterfaceMethod0::ORDINAL,
+            message::MESSAGE_HEADER_EXPECT_RESPONSE,
+        )
+    }
+}
+impl IntegrationTestInterfaceRequest for IntegrationTestInterfaceMethod0Request {}
+
+// -- IntegrationTestInterfaceMethod0Response --
+
+// Constants
+// Enums
+// Struct version information
+const IntegrationTestInterfaceMethod0ResponseVersions: [(u32, u32); 1] = [(0, 16)];
+
+// Struct definition
+pub struct IntegrationTestInterfaceMethod0Response {
+    pub param0: Vec<u8>,
+}
+
+impl MojomPointer for IntegrationTestInterfaceMethod0Response {
+    fn header_data(&self) -> DataHeaderValue {
+        DataHeaderValue::Version(0)
+    }
+    fn serialized_size(&self, _context: &Context) -> usize {
+        16
+    }
+    fn encode_value(self, encoder: &mut Encoder, context: Context) {
+        MojomEncodable::encode(self.param0, encoder, context.clone());
+    }
+    fn decode_value(decoder: &mut Decoder, context: Context) -> Result<Self, ValidationError> {
+        let version = {
+            let mut state = decoder.get_mut(&context);
+            match state.decode_struct_header(&IntegrationTestInterfaceMethod0ResponseVersions) {
+                Ok(header) => header.data(),
+                Err(err) => return Err(err),
+            }
+        };
+        let param0 = match <Vec<u8>>::decode(decoder, context.clone()) {
+            Ok(value) => value,
+            Err(err) => return Err(err),
+        };
+        Ok(IntegrationTestInterfaceMethod0Response { param0: param0 })
+    }
+}
+
+impl MojomEncodable for IntegrationTestInterfaceMethod0Response {
+    impl_encodable_for_pointer!();
+    fn compute_size(&self, context: Context) -> usize {
+        encoding::align_default(self.serialized_size(&context))
+            + self.param0.compute_size(context.clone())
+    }
+}
+
+impl MojomStruct for IntegrationTestInterfaceMethod0Response {}
+
+impl MojomMessage for IntegrationTestInterfaceMethod0Response {
+    fn min_version() -> u32 {
+        IntegrationTestInterfaceMethod0::MIN_VERSION
+    }
+    fn create_header() -> MessageHeader {
+        MessageHeader::new(
+            1,
+            IntegrationTestInterfaceMethod0::ORDINAL,
+            message::MESSAGE_HEADER_IS_RESPONSE,
+        )
+    }
+}
+impl IntegrationTestInterfaceResponse for IntegrationTestInterfaceMethod0Response {}
diff --git a/mojo/public/rust/tests/validation.rs b/mojo/public/rust/tests/validation.rs
new file mode 100644
index 0000000..5b85582
--- /dev/null
+++ b/mojo/public/rust/tests/validation.rs
@@ -0,0 +1,131 @@
+// Copyright 2016 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+//! Tests encoding and decoding functionality in the bindings package
+//!
+//! Test failure is defined as the function returning via panicking
+//! and the result being caught in the test! macro. If a test function
+//! returns without panicking, it is assumed to pass.
+
+#[macro_use]
+extern crate mojo;
+
+use mojo::bindings::mojom::MojomMessageOption;
+use mojo::system;
+
+#[macro_use]
+mod util;
+
+use util::mojom_validation::*;
+
+/// This macro is a wrapper for the tests! macro as it takes advantage of the
+/// shared code between tests.
+///
+/// Given a test name, it will generate a test function. In this test function
+/// we perform the following steps:
+///   1. Decode the header of the validation input.
+///   2. Decode the payload of the validation input, expecting a validation
+///      error.
+///
+macro_rules! validation_tests {
+    ($($name:ident => $req_type:ident;)*) => {
+        tests! {
+            $(
+            fn $name() {
+                let data = include_str!(concat!("../../interfaces/bindings/tests/data/validation/",
+                                                stringify!($name),
+                                                ".data"));
+                let expected = include_str!(concat!("../../interfaces/bindings/tests/data/validation/",
+                                                    stringify!($name),
+                                                    ".expected")).trim();
+                match util::parse_validation_test(data) {
+                    Ok((data, num_handles)) => {
+                        let mut mock_handles = Vec::with_capacity(num_handles);
+                        for _ in 0..num_handles {
+                            mock_handles.push(unsafe { system::acquire(0) });
+                        }
+                        match $req_type::decode_message(data, mock_handles) {
+                            Ok(_) => panic!("Should not be valid!"),
+                            Err(err) => assert_eq!(err.as_str(), expected),
+                        }
+                    },
+                    Err(msg) => panic!("Error: {}", msg),
+                }
+            }
+            )*
+        }
+    }
+}
+
+validation_tests! {
+    conformance_empty => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_incomplete_struct => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_incomplete_struct_header => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_invalid_request_flags => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_invalid_request_flags2 => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_struct_num_bytes_huge => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_struct_num_bytes_less_than_min_requirement => ConformanceTestInterfaceRequestOption;
+    conformance_mthd0_struct_num_bytes_less_than_struct_header => ConformanceTestInterfaceRequestOption;
+    conformance_mthd10_null_keys => ConformanceTestInterfaceRequestOption;
+    conformance_mthd10_null_values => ConformanceTestInterfaceRequestOption;
+    conformance_mthd10_one_null_key => ConformanceTestInterfaceRequestOption;
+    conformance_mthd10_unequal_array_size => ConformanceTestInterfaceRequestOption;
+    conformance_mthd11_num_bytes_version_mismatch_1 => ConformanceTestInterfaceRequestOption;
+    conformance_mthd11_num_bytes_version_mismatch_2 => ConformanceTestInterfaceRequestOption;
+    conformance_mthd12_invalid_request_flags => ConformanceTestInterfaceRequestOption;
+    conformance_mthd14_unexpected_null_array_in_union => ConformanceTestInterfaceRequestOption;
+    conformance_mthd14_unexpected_null_map_in_union => ConformanceTestInterfaceRequestOption;
+    conformance_mthd14_unexpected_null_struct_in_union => ConformanceTestInterfaceRequestOption;
+    conformance_mthd14_unexpected_null_union_in_union => ConformanceTestInterfaceRequestOption;
+    conformance_mthd15_unexpected_null_union_in_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd1_misaligned_struct => ConformanceTestInterfaceRequestOption;
+    conformance_mthd1_struct_pointer_overflow => ConformanceTestInterfaceRequestOption;
+    conformance_mthd1_unexpected_null_struct => ConformanceTestInterfaceRequestOption;
+    conformance_mthd2_multiple_pointers_to_same_struct => ConformanceTestInterfaceRequestOption;
+    conformance_mthd2_overlapped_objects => ConformanceTestInterfaceRequestOption;
+    conformance_mthd2_wrong_layout_order => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_array_num_bytes_huge => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_array_num_bytes_less_than_array_header => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_array_num_bytes_less_than_necessary_size => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_array_pointer_overflow => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_incomplete_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_incomplete_array_header => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_misaligned_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd3_unexpected_null_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd4_multiple_pointers_to_same_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd4_overlapped_objects => ConformanceTestInterfaceRequestOption;
+    conformance_mthd4_wrong_layout_order => ConformanceTestInterfaceRequestOption;
+    conformance_mthd5_handle_out_of_range => ConformanceTestInterfaceRequestOption;
+    conformance_mthd5_multiple_handles_with_same_value_1 => ConformanceTestInterfaceRequestOption;
+    conformance_mthd5_multiple_handles_with_same_value_2 => ConformanceTestInterfaceRequestOption;
+    conformance_mthd5_unexpected_invalid_handle => ConformanceTestInterfaceRequestOption;
+    conformance_mthd5_wrong_handle_order => ConformanceTestInterfaceRequestOption;
+    conformance_mthd6_nested_array_num_bytes_less_than_necessary_size => ConformanceTestInterfaceRequestOption;
+    conformance_mthd7_unexpected_null_fixed_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd7_unmatched_array_elements => ConformanceTestInterfaceRequestOption;
+    conformance_mthd7_unmatched_array_elements_nested => ConformanceTestInterfaceRequestOption;
+    conformance_mthd8_array_num_bytes_overflow => ConformanceTestInterfaceRequestOption;
+    conformance_mthd8_unexpected_null_array => ConformanceTestInterfaceRequestOption;
+    conformance_mthd8_unexpected_null_string => ConformanceTestInterfaceRequestOption;
+    conformance_mthd9_unexpected_null_array => ConformanceTestInterfaceRequestOption;
+    boundscheck_msghdr_no_such_method => BoundsCheckTestInterfaceRequestOption;
+    conformance_msghdr_incomplete_struct => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_incomplete_struct_header => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_invalid_flag_combo => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_missing_request_id => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_no_such_method => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_num_bytes_huge => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_num_bytes_less_than_min_requirement => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_num_bytes_less_than_struct_header => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_num_bytes_version_mismatch_1 => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_num_bytes_version_mismatch_2 => ConformanceTestInterfaceRequestOption;
+    conformance_msghdr_num_bytes_version_mismatch_3 => ConformanceTestInterfaceRequestOption;
+    resp_boundscheck_msghdr_no_such_method => BoundsCheckTestInterfaceResponseOption;
+    resp_conformance_msghdr_invalid_response_flags1 => ConformanceTestInterfaceResponseOption;
+    resp_conformance_msghdr_invalid_response_flags2 => ConformanceTestInterfaceResponseOption;
+    resp_conformance_msghdr_no_such_method => ConformanceTestInterfaceResponseOption;
+    integration_intf_resp_mthd0_unexpected_array_header => IntegrationTestInterfaceResponseOption;
+    integration_intf_rqst_mthd0_unexpected_struct_header => IntegrationTestInterfaceRequestOption;
+    integration_msghdr_invalid_flags => IntegrationTestInterfaceRequestOption;
+}
diff --git a/net/cert/crl_set.cc b/net/cert/crl_set.cc
index 5216565..24ceee3 100644
--- a/net/cert/crl_set.cc
+++ b/net/cert/crl_set.cc
@@ -223,10 +223,8 @@
   if (!header_dict.get())
     return false;
 
-  std::string contents;
-  if (!header_dict->GetString("ContentType", &contents))
-    return false;
-  if (contents != "CRLSet")
+  std::string* contents = header_dict->FindStringKey("ContentType");
+  if (!contents || (*contents != "CRLSet"))
     return false;
 
   if (header_dict->FindIntKey("Version") != kCurrentFileVersion)
diff --git a/net/log/net_log_event_type_list.h b/net/log/net_log_event_type_list.h
index e66ebe9..509d788 100644
--- a/net/log/net_log_event_type_list.h
+++ b/net/log/net_log_event_type_list.h
@@ -1489,6 +1489,14 @@
 // On sending an HTTP/2 SETTINGS frame with ACK flag.
 EVENT_TYPE(HTTP2_SESSION_SEND_SETTINGS_ACK)
 
+// Receipt of an HTTP/2 ACCEPT_CH frame.
+// The following parameters are attached:
+//   {
+//     "origin": <The origin associated with the settings>,
+//     "accept_ch":  <the raw ACCEPT_CH setting for that origin>,
+//   }
+EVENT_TYPE(HTTP2_SESSION_RECV_ACCEPT_CH)
+
 // Receipt of an HTTP/2 SETTINGS frame without ACK flag.
 EVENT_TYPE(HTTP2_SESSION_RECV_SETTINGS)
 
@@ -2305,6 +2313,13 @@
 // Session received a HANDSHAKE_DONE frame.
 EVENT_TYPE(QUIC_SESSION_HANDSHAKE_DONE_FRAME_RECEIVED)
 
+// Session received an ACCEPT_CH frame
+// {
+//   "origin": <the origin the accept_ch settings apply to>
+//   "accept_ch": <the raw ACCEPT_CH data>
+// }
+EVENT_TYPE(QUIC_ACCEPT_CH_FRAME_RECEIVED)
+
 // Session sent a coalesced QUIC packet.
 // {
 //   "info": <coalesced packet info>
diff --git a/net/quic/quic_chromium_client_session.cc b/net/quic/quic_chromium_client_session.cc
index f39c94c..03ca363 100644
--- a/net/quic/quic_chromium_client_session.cc
+++ b/net/quic/quic_chromium_client_session.cc
@@ -215,6 +215,14 @@
   return dict;
 }
 
+base::Value NetLogAcceptChFrameReceivedParams(
+    spdy::AcceptChOriginValuePair entry) {
+  base::Value dict(base::Value::Type::DICTIONARY);
+  dict.SetStringKey("origin", entry.origin);
+  dict.SetStringKey("accept_ch", entry.value);
+  return dict;
+}
+
 // Histogram for recording the different reasons that a QUIC session is unable
 // to complete the handshake.
 enum HandshakeFailureReason {
@@ -1241,6 +1249,9 @@
     has_valid_entry = true;
     accept_ch_entries_received_via_alps_.insert(
         std::make_pair(std::move(scheme_host_port), entry.value));
+
+    net_log_.AddEvent(NetLogEventType::QUIC_ACCEPT_CH_FRAME_RECEIVED,
+                      [&] { return NetLogAcceptChFrameReceivedParams(entry); });
   }
   LogAcceptChFrameReceivedHistogram(has_valid_entry, has_invalid_entry);
 }
diff --git a/net/spdy/spdy_session.cc b/net/spdy/spdy_session.cc
index f2b859f..4e88846 100644
--- a/net/spdy/spdy_session.cc
+++ b/net/spdy/spdy_session.cc
@@ -316,6 +316,13 @@
   return dict;
 }
 
+base::Value NetLogSpdyRecvAcceptChParams(spdy::AcceptChOriginValuePair entry) {
+  base::Value dict(base::Value::Type::DICTIONARY);
+  dict.SetStringKey("origin", entry.origin);
+  dict.SetStringKey("accept_ch", entry.value);
+  return dict;
+}
+
 base::Value NetLogSpdyRecvSettingParams(spdy::SpdySettingsId id,
                                         uint32_t value) {
   base::Value dict(base::Value::Type::DICTIONARY);
@@ -1157,6 +1164,9 @@
     has_valid_entry = true;
     accept_ch_entries_received_via_alps_.insert(
         std::make_pair(std::move(scheme_host_port), entry.value));
+
+    net_log_.AddEvent(NetLogEventType::HTTP2_SESSION_RECV_ACCEPT_CH,
+                      [&] { return NetLogSpdyRecvAcceptChParams(entry); });
   }
 
   SpdyAcceptChEntries value;
diff --git a/pdf/pdf_view_plugin_base.cc b/pdf/pdf_view_plugin_base.cc
index fa2aa0c..aef2402 100644
--- a/pdf/pdf_view_plugin_base.cc
+++ b/pdf/pdf_view_plugin_base.cc
@@ -567,8 +567,6 @@
   NotifyLinkUnderCursor();
 }
 
-// TODO(crbug.com/1191817): Add tests for input events. Unit testing should be
-// feasible now that the Pepper dependency is removed for input events.
 bool PdfViewPluginBase::HandleInputEvent(const blink::WebInputEvent& event) {
   // Ignore user input in read-only mode.
   if (engine()->IsReadOnly())
diff --git a/pdf/pdf_view_plugin_base_unittest.cc b/pdf/pdf_view_plugin_base_unittest.cc
index 111a6a9..1788865 100644
--- a/pdf/pdf_view_plugin_base_unittest.cc
+++ b/pdf/pdf_view_plugin_base_unittest.cc
@@ -31,7 +31,10 @@
 #include "testing/gmock/include/gmock/gmock.h"
 #include "testing/gtest/include/gtest/gtest.h"
 #include "third_party/abseil-cpp/absl/types/optional.h"
+#include "third_party/blink/public/common/input/web_input_event.h"
+#include "third_party/blink/public/common/input/web_mouse_event.h"
 #include "third_party/skia/include/core/SkColor.h"
+#include "ui/gfx/geometry/point_f.h"
 #include "ui/gfx/geometry/size.h"
 
 namespace chrome_pdf {
@@ -160,6 +163,7 @@
   using PdfViewPluginBase::accessibility_state;
   using PdfViewPluginBase::engine;
   using PdfViewPluginBase::full_frame;
+  using PdfViewPluginBase::HandleInputEvent;
   using PdfViewPluginBase::HandleMessage;
   using PdfViewPluginBase::LoadUrl;
   using PdfViewPluginBase::SetZoom;
@@ -780,6 +784,25 @@
       fake_plugin_.GetNotifiedBrowserAboutUnsupportedFeatureForTesting());
 }
 
+TEST_F(PdfViewPluginBaseWithEngineTest, HandleInputEvent) {
+  auto* engine = static_cast<TestPDFiumEngine*>(fake_plugin_.engine());
+  EXPECT_CALL(*engine, HandleInputEvent)
+      .WillRepeatedly([](const blink::WebInputEvent& event) {
+        const auto& mouse_event =
+            static_cast<const blink::WebMouseEvent&>(event);
+        EXPECT_EQ(blink::WebInputEvent::Type::kMouseDown,
+                  mouse_event.GetType());
+        EXPECT_EQ(gfx::PointF(10.0f, 20.0f), mouse_event.PositionInWidget());
+        return true;
+      });
+
+  blink::WebMouseEvent mouse_event;
+  mouse_event.SetType(blink::WebInputEvent::Type::kMouseDown);
+  mouse_event.SetPositionInWidget(10.0f, 20.0f);
+
+  EXPECT_TRUE(fake_plugin_.HandleInputEvent(mouse_event));
+}
+
 TEST_F(PdfViewPluginBaseTest, EnteredEditMode) {
   EXPECT_CALL(fake_plugin_, SetPluginCanSave(true));
   fake_plugin_.EnteredEditMode();
diff --git a/pdf/pdf_view_web_plugin_unittest.cc b/pdf/pdf_view_web_plugin_unittest.cc
index d2aa1e9..2d728d2 100644
--- a/pdf/pdf_view_web_plugin_unittest.cc
+++ b/pdf/pdf_view_web_plugin_unittest.cc
@@ -721,28 +721,8 @@
 
 class PdfViewWebPluginImeTest : public PdfViewWebPluginTest {
  public:
-  class TestPDFiumEngineForIme : public TestPDFiumEngine {
-   public:
-    explicit TestPDFiumEngineForIme(PDFEngine::Client* client)
-        : TestPDFiumEngine(client) {}
-
-    // TestPDFiumEngine:
-    MOCK_METHOD(bool,
-                HandleInputEvent,
-                (const blink::WebInputEvent&),
-                (override));
-  };
-
-  std::unique_ptr<TestPDFiumEngine> CreateEngine() override {
-    return std::make_unique<NiceMock<TestPDFiumEngineForIme>>(plugin_.get());
-  }
-
-  TestPDFiumEngineForIme* engine() {
-    return static_cast<TestPDFiumEngineForIme*>(engine_ptr_);
-  }
-
   void TestImeSetCompositionForPlugin(const blink::WebString& text) {
-    EXPECT_CALL(*engine(), HandleInputEvent).Times(0);
+    EXPECT_CALL(*engine_ptr_, HandleInputEvent).Times(0);
     plugin_->ImeSetCompositionForPlugin(text, std::vector<ui::ImeTextSpan>(),
                                         gfx::Range(),
                                         /*selection_start=*/0,
@@ -756,12 +736,12 @@
     if (expected_text16.size()) {
       for (const auto& c : expected_text16) {
         base::StringPiece16 expected_key(&c, 1);
-        EXPECT_CALL(*engine(),
+        EXPECT_CALL(*engine_ptr_,
                     HandleInputEvent(IsExpectedImeKeyEvent(expected_key)))
             .WillOnce(Return(true));
       }
     } else {
-      EXPECT_CALL(*engine(), HandleInputEvent).Times(0);
+      EXPECT_CALL(*engine_ptr_, HandleInputEvent).Times(0);
     }
     plugin_->ImeFinishComposingTextForPlugin(false);
   }
@@ -772,11 +752,12 @@
     if (expected_text16.size()) {
       for (const auto& c : expected_text16) {
         base::StringPiece16 event(&c, 1);
-        EXPECT_CALL(*engine(), HandleInputEvent(IsExpectedImeKeyEvent(event)))
+        EXPECT_CALL(*engine_ptr_,
+                    HandleInputEvent(IsExpectedImeKeyEvent(event)))
             .WillOnce(Return(true));
       }
     } else {
-      EXPECT_CALL(*engine(), HandleInputEvent).Times(0);
+      EXPECT_CALL(*engine_ptr_, HandleInputEvent).Times(0);
     }
     plugin_->ImeCommitTextForPlugin(text, std::vector<ui::ImeTextSpan>(),
                                     gfx::Range(),
diff --git a/pdf/test/test_pdfium_engine.h b/pdf/test/test_pdfium_engine.h
index c1518ed..89afd9ea 100644
--- a/pdf/test/test_pdfium_engine.h
+++ b/pdf/test/test_pdfium_engine.h
@@ -42,6 +42,11 @@
   MOCK_METHOD(void, ScrolledToXPosition, (int), (override));
   MOCK_METHOD(void, ScrolledToYPosition, (int), (override));
 
+  MOCK_METHOD(bool,
+              HandleInputEvent,
+              (const blink::WebInputEvent&),
+              (override));
+
   MOCK_METHOD(void, ZoomUpdated, (double), (override));
 
   MOCK_METHOD(gfx::Size,
diff --git a/remoting/host/mojom/webauthn_proxy.mojom b/remoting/host/mojom/webauthn_proxy.mojom
index 8edb3f1..8ed55423a 100644
--- a/remoting/host/mojom/webauthn_proxy.mojom
+++ b/remoting/host/mojom/webauthn_proxy.mojom
@@ -4,13 +4,37 @@
 
 module remoting.mojom;
 
+// The response object for WebAuthnProxy.Create().
+union WebAuthnCreateResponse {
+  // The `name` property of the `DOMException`, if any, yielded by the remote
+  // request.
+  string error_name;
+
+  // A string-serialized representation of the `PublicKeyCredential`
+  // (https://w3c.github.io/webauthn/#publickeycredential), if any, yielded
+  // by the remote request.
+  // Note that it is opaque to chromoting host processes and will be passed
+  // verbatim to the Chrome webAuthenticationProxy extension API.
+  string response_data;
+};
+
 // An interface for the host-side chromoting extension to pass intercepted Web
 // Authentication API requests to the client side chromoting security extension
 // through a chromoting host process.
-// The remote of this interface is always owned by a low-trust native messaging
-// host process; on Windows, the receiver is bound in a low-trust chromoting
-// network process, while on Linux, the receiver is bound in a high-trust
-// chromoting host process.
+//
+// The interface defined here generally matches the IDL of the Chrome
+// webAuthenticationProxy extension API:
+//   chrome/common/extensions/api/web_authentication_proxy.idl
+//
+// The remote of this interface is always owned by a native messaging host
+// process; on Windows, the receiver is bound in a chromoting network process,
+// while on Linux, the receiver is bound in a chromoting host process. Both the
+// remote and the receiver are generally trusted.
+//
+// There is an intrinsic risk of remote WebAuthn forwarding, but it's an
+// accepted risk and the impact is limited given the limited scope of the
+// feature. Please see the note here: go/crd-webauthn#heading=h.s445jjbbs1m2
+//
 // Note that both processes are chromoting-only and they don't make IPCs with
 // Chrome processes.
 interface WebAuthnProxy {
@@ -18,4 +42,12 @@
   // PublicKeyCredential.isUserVerifyingPlatformAuthenticatorAvailable() call
   // remotely.
   IsUserVerifyingPlatformAuthenticatorAvailable() => (bool is_available);
+
+  // Handles a navigator.credentials.create() call remotely.
+  // |request_data| is the string-serialized representation of the parameters
+  // passed to the create() call. It is opaque to chromoting host processes and
+  // will be passed verbatim to the client.
+  // If |response| is null, it means that the remote create() call has yielded
+  // `null`, which is still a valid response according to the spec.
+  Create(string request_data) => (WebAuthnCreateResponse? response);
 };
diff --git a/remoting/host/webauthn/remote_webauthn_constants.cc b/remoting/host/webauthn/remote_webauthn_constants.cc
index 134c56f..0fd4073 100644
--- a/remoting/host/webauthn/remote_webauthn_constants.cc
+++ b/remoting/host/webauthn/remote_webauthn_constants.cc
@@ -10,8 +10,12 @@
 
 const char kIsUvpaaMessageType[] = "isUvpaa";
 const char kGetRemoteStateMessageType[] = "getRemoteState";
+const char kCreateMessageType[] = "create";
 
 const char kIsUvpaaResponseIsAvailableKey[] = "isAvailable";
 const char kGetRemoteStateResponseIsRemotedKey[] = "isRemoted";
+const char kCreateRequestDataKey[] = "requestData";
+const char kCreateResponseErrorNameKey[] = "errorName";
+const char kCreateResponseDataKey[] = "responseData";
 
 }  // namespace remoting
diff --git a/remoting/host/webauthn/remote_webauthn_constants.h b/remoting/host/webauthn/remote_webauthn_constants.h
index 65ac883..2194881 100644
--- a/remoting/host/webauthn/remote_webauthn_constants.h
+++ b/remoting/host/webauthn/remote_webauthn_constants.h
@@ -12,10 +12,14 @@
 // NMH message types.
 extern const char kIsUvpaaMessageType[];
 extern const char kGetRemoteStateMessageType[];
+extern const char kCreateMessageType[];
 
 // NMH message keys.
 extern const char kIsUvpaaResponseIsAvailableKey[];
 extern const char kGetRemoteStateResponseIsRemotedKey[];
+extern const char kCreateRequestDataKey[];
+extern const char kCreateResponseErrorNameKey[];
+extern const char kCreateResponseDataKey[];
 
 }  // namespace remoting
 
diff --git a/remoting/host/webauthn/remote_webauthn_message_handler.cc b/remoting/host/webauthn/remote_webauthn_message_handler.cc
index 1baeaad..a22567f 100644
--- a/remoting/host/webauthn/remote_webauthn_message_handler.cc
+++ b/remoting/host/webauthn/remote_webauthn_message_handler.cc
@@ -11,6 +11,23 @@
 #include "remoting/proto/remote_webauthn.pb.h"
 #include "remoting/protocol/message_serialization.h"
 
+namespace {
+
+template <typename CallbackType, typename ResponseType>
+void FindAndRunCallback(base::flat_map<uint64_t, CallbackType>& callback_map,
+                        uint64_t id,
+                        ResponseType response) {
+  auto it = callback_map.find(id);
+  if (it == callback_map.end()) {
+    LOG(WARNING) << "No callback found associated with ID: " << id;
+    return;
+  }
+  std::move(it->second).Run(std::move(response));
+  callback_map.erase(it);
+}
+
+}  // namespace
+
 namespace remoting {
 
 RemoteWebAuthnMessageHandler::RemoteWebAuthnMessageHandler(
@@ -48,6 +65,10 @@
       OnIsUvpaaResponse(remote_webauthn->id(),
                         remote_webauthn->is_uvpaa_response());
       break;
+    case protocol::RemoteWebAuthn::kCreateResponse:
+      OnCreateResponse(remote_webauthn->id(),
+                       remote_webauthn->create_response());
+      break;
     default:
       LOG(ERROR) << "Unknown message case: " << remote_webauthn->message_case();
   }
@@ -83,6 +104,20 @@
   Send(remote_webauthn, base::DoNothing());
 }
 
+void RemoteWebAuthnMessageHandler::Create(const std::string& request_data,
+                                          CreateCallback callback) {
+  DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
+
+  uint64_t id = AssignNextMessageId();
+  create_callbacks_[id] = std::move(callback);
+
+  protocol::RemoteWebAuthn remote_webauthn;
+  remote_webauthn.set_id(id);
+  remote_webauthn.mutable_create_request()->set_request_details_json(
+      request_data);
+  Send(remote_webauthn, base::DoNothing());
+}
+
 void RemoteWebAuthnMessageHandler::AddReceiver(
     mojo::PendingReceiver<mojom::WebAuthnProxy> receiver) {
   if (!connected()) {
@@ -121,13 +156,34 @@
     const protocol::RemoteWebAuthn_IsUvpaaResponse& response) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
 
-  auto it = is_uvpaa_callbacks_.find(id);
-  if (it == is_uvpaa_callbacks_.end()) {
-    LOG(WARNING) << "No IsUvpaa IPC callback associated with ID: " << id;
-    return;
+  FindAndRunCallback(is_uvpaa_callbacks_, id, response.is_available());
+}
+
+void RemoteWebAuthnMessageHandler::OnCreateResponse(
+    uint64_t id,
+    const protocol::RemoteWebAuthn_CreateResponse& response) {
+  DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
+
+  mojom::WebAuthnCreateResponsePtr mojo_response;
+  switch (response.result_case()) {
+    case protocol::RemoteWebAuthn::CreateResponse::ResultCase::kErrorName:
+      mojo_response =
+          mojom::WebAuthnCreateResponse::NewErrorName(response.error_name());
+      break;
+    case protocol::RemoteWebAuthn::CreateResponse::ResultCase::kResponseJson:
+      mojo_response = mojom::WebAuthnCreateResponse::NewResponseData(
+          response.response_json());
+      break;
+    case protocol::RemoteWebAuthn::CreateResponse::ResultCase::RESULT_NOT_SET:
+      // Do nothing and send a nullptr to the mojo client. This means the remote
+      // create() call has yielded `null`, which is still a valid response
+      // according to the spec.
+      break;
+    default:
+      NOTREACHED() << "Unknown create result case: " << response.result_case();
   }
-  std::move(it->second).Run(response.is_available());
-  is_uvpaa_callbacks_.erase(it);
+
+  FindAndRunCallback(create_callbacks_, id, std::move(mojo_response));
 }
 
 uint64_t RemoteWebAuthnMessageHandler::AssignNextMessageId() {
diff --git a/remoting/host/webauthn/remote_webauthn_message_handler.h b/remoting/host/webauthn/remote_webauthn_message_handler.h
index 3116a0f..ff405bfdc4 100644
--- a/remoting/host/webauthn/remote_webauthn_message_handler.h
+++ b/remoting/host/webauthn/remote_webauthn_message_handler.h
@@ -22,6 +22,7 @@
 namespace remoting {
 
 namespace protocol {
+class RemoteWebAuthn_CreateResponse;
 class RemoteWebAuthn_IsUvpaaResponse;
 }  // namespace protocol
 
@@ -44,6 +45,8 @@
   // mojom::WebAuthnProxy implementation.
   void IsUserVerifyingPlatformAuthenticatorAvailable(
       IsUserVerifyingPlatformAuthenticatorAvailableCallback callback) override;
+  void Create(const std::string& request_data,
+              CreateCallback callback) override;
 
   void AddReceiver(mojo::PendingReceiver<mojom::WebAuthnProxy> receiver);
   void ClearReceivers();
@@ -55,10 +58,16 @@
   base::WeakPtr<RemoteWebAuthnMessageHandler> GetWeakPtr();
 
  private:
+  template <typename CallbackType>
+  using CallbackMap = base::flat_map<uint64_t, CallbackType>;
+
   void OnReceiverDisconnected();
   void OnIsUvpaaResponse(
       uint64_t id,
       const protocol::RemoteWebAuthn_IsUvpaaResponse& response);
+  void OnCreateResponse(
+      uint64_t id,
+      const protocol::RemoteWebAuthn_CreateResponse& response);
 
   uint64_t AssignNextMessageId();
 
@@ -68,9 +77,10 @@
   mojo::ReceiverSet<mojom::WebAuthnProxy> receiver_set_;
 
   // message ID => mojo callback mappings.
-  base::flat_map<uint64_t,
-                 IsUserVerifyingPlatformAuthenticatorAvailableCallback>
+  CallbackMap<IsUserVerifyingPlatformAuthenticatorAvailableCallback>
       is_uvpaa_callbacks_ GUARDED_BY_CONTEXT(sequence_checker_);
+  CallbackMap<CreateCallback> create_callbacks_
+      GUARDED_BY_CONTEXT(sequence_checker_);
 
   uint64_t current_message_id_ GUARDED_BY_CONTEXT(sequence_checker_) = 0u;
 
diff --git a/remoting/host/webauthn/remote_webauthn_native_messaging_host.cc b/remoting/host/webauthn/remote_webauthn_native_messaging_host.cc
index 7faf2eb..483d6fe 100644
--- a/remoting/host/webauthn/remote_webauthn_native_messaging_host.cc
+++ b/remoting/host/webauthn/remote_webauthn_native_messaging_host.cc
@@ -48,6 +48,8 @@
     ProcessIsUvpaa(request, std::move(response));
   } else if (type == kGetRemoteStateMessageType) {
     ProcessGetRemoteState(std::move(response));
+  } else if (type == kCreateMessageType) {
+    ProcessCreate(request, std::move(response));
   } else {
     LOG(ERROR) << "Unsupported request type: " << type;
   }
@@ -94,6 +96,40 @@
                      base::Unretained(this), std::move(response)));
 }
 
+void RemoteWebAuthnNativeMessagingHost::ProcessCreate(
+    const base::Value& request,
+    base::Value response) {
+  // Create request: {id: string, type: 'create', requestData: string}
+  // Create response: {
+  //   id: string, type: 'createResponse', responseData?: string,
+  //   errorName?: string}
+
+  DCHECK(task_runner_->BelongsToCurrentThread());
+
+  if (!EnsureIpcConnection()) {
+    // TODO(yuweih): See if this is the right error to use here.
+    response.SetStringKey(kCreateResponseErrorNameKey, "InvalidStateError");
+    SendMessageToClient(std::move(response));
+    return;
+  }
+
+  const std::string* request_data =
+      request.FindStringKey(kCreateRequestDataKey);
+  if (!request_data) {
+    LOG(ERROR) << "Request data not found in create request.";
+    // navigator.credentials.create() throws NotSupportedError if the parameter
+    // is unexpected.
+    response.SetStringKey(kCreateResponseErrorNameKey, "NotSupportedError");
+    SendMessageToClient(std::move(response));
+    return;
+  }
+
+  remote_->Create(
+      *request_data,
+      base::BindOnce(&RemoteWebAuthnNativeMessagingHost::OnCreateResponse,
+                     base::Unretained(this), std::move(response)));
+}
+
 void RemoteWebAuthnNativeMessagingHost::ProcessGetRemoteState(
     base::Value response) {
   // GetRemoteState request: {id: string, type: 'getRemoteState'}
@@ -136,6 +172,33 @@
   SendMessageToClient(std::move(response));
 }
 
+void RemoteWebAuthnNativeMessagingHost::OnCreateResponse(
+    base::Value response,
+    mojom::WebAuthnCreateResponsePtr remote_response) {
+  DCHECK(task_runner_->BelongsToCurrentThread());
+
+  // If |remote_response| is null, it means that the remote create() call has
+  // yielded `null`, which is still a valid response according to the spec. In
+  // this case we just send back an empty create response.
+  if (!remote_response.is_null()) {
+    switch (remote_response->which()) {
+      case mojom::WebAuthnCreateResponse::Tag::kErrorName:
+        response.SetStringKey(kCreateResponseErrorNameKey,
+                              remote_response->get_error_name());
+        break;
+      case mojom::WebAuthnCreateResponse::Tag::kResponseData:
+        response.SetStringKey(kCreateResponseDataKey,
+                              remote_response->get_response_data());
+        break;
+      default:
+        NOTREACHED() << "Unexpected create response tag: "
+                     << static_cast<uint32_t>(remote_response->which());
+    }
+  }
+
+  SendMessageToClient(std::move(response));
+}
+
 void RemoteWebAuthnNativeMessagingHost::QueryNextRemoteState() {
   DCHECK(task_runner_->BelongsToCurrentThread());
 
diff --git a/remoting/host/webauthn/remote_webauthn_native_messaging_host.h b/remoting/host/webauthn/remote_webauthn_native_messaging_host.h
index 97daf70..1ddd0ff 100644
--- a/remoting/host/webauthn/remote_webauthn_native_messaging_host.h
+++ b/remoting/host/webauthn/remote_webauthn_native_messaging_host.h
@@ -13,6 +13,7 @@
 #include "extensions/browser/api/messaging/native_message_host.h"
 #include "mojo/public/cpp/bindings/remote.h"
 #include "remoting/host/chromoting_host_services_client.h"
+#include "remoting/host/mojom/webauthn_proxy.mojom-forward.h"
 #include "remoting/host/mojom/webauthn_proxy.mojom.h"
 
 namespace remoting {
@@ -38,10 +39,13 @@
   void ProcessHello(base::Value response);
   void ProcessGetRemoteState(base::Value response);
   void ProcessIsUvpaa(const base::Value& request, base::Value response);
+  void ProcessCreate(const base::Value& request, base::Value response);
 
   void OnQueryVersionResult(uint32_t version);
   void OnIpcDisconnected();
   void OnIsUvpaaResponse(base::Value response, bool is_available);
+  void OnCreateResponse(base::Value response,
+                        mojom::WebAuthnCreateResponsePtr remote_response);
 
   void QueryNextRemoteState();
   void SendNextRemoteState(bool is_remoted);
diff --git a/remoting/proto/remote_webauthn.proto b/remoting/proto/remote_webauthn.proto
index ca5884d..0d56f74 100644
--- a/remoting/proto/remote_webauthn.proto
+++ b/remoting/proto/remote_webauthn.proto
@@ -10,7 +10,7 @@
 
 // Composite message type for messages sent over the remote-webauthn data
 // channel.
-// Next ID: 4
+// Next ID: 6
 message RemoteWebAuthn {
   // Requests the client to handle a call to
   // PublicKeyCredential.isUserVerifyingPlatformAuthenticatorAvailable().
@@ -20,12 +20,38 @@
   // Next ID: 2
   message IsUvpaaResponse { optional bool is_available = 1; }
 
-  // Unique ID to pair a response with the request.
-  // Required for all message types.
+  // Requests the client to handle a navigator.credentials.create() call.
+  // Next ID: 2
+  message CreateRequest {
+    // A JSON serialized representation of PublicKeyCredentialCreationOptions
+    // passed to navigator.credentials.create().
+    optional string request_details_json = 1;
+  }
+
+  // Response for CreateRequest.
+  // Next ID: 3
+  message CreateResponse {
+    // If neither of the fields is set, it means that the remote create() call
+    // has yielded `null`, which is still a valid response according to the
+    // spec.
+    oneof result {
+      // The `name` property of the `DOMException`, if any.
+      string error_name = 1;
+
+      // A JSON serialized representation of the `PublicKeyCredential`
+      // (https://w3c.github.io/webauthn/#publickeycredential), if any.
+      string response_json = 2;
+    }
+  }
+
+  // Unique ID used to multiplex requests.
   optional uint64 id = 1;
 
   oneof message {
     IsUvpaaRequest is_uvpaa_request = 2;
     IsUvpaaResponse is_uvpaa_response = 3;
+
+    CreateRequest create_request = 4;
+    CreateResponse create_response = 5;
   }
 }
diff --git a/services/network/BUILD.gn b/services/network/BUILD.gn
index bf42c74..45070bd 100644
--- a/services/network/BUILD.gn
+++ b/services/network/BUILD.gn
@@ -456,6 +456,7 @@
       "ct_log_list_distributor_unittest.cc",
       "expect_ct_reporter_unittest.cc",
       "sct_auditing/sct_auditing_cache_unittest.cc",
+      "sct_auditing/sct_auditing_handler_unittest.cc",
     ]
     deps += [ "//components/certificate_transparency" ]
   }
diff --git a/services/network/first_party_sets/first_party_sets.cc b/services/network/first_party_sets/first_party_sets.cc
index e4112e8..ed94752a 100644
--- a/services/network/first_party_sets/first_party_sets.cc
+++ b/services/network/first_party_sets/first_party_sets.cc
@@ -9,6 +9,7 @@
 #include <utility>
 #include <vector>
 
+#include "base/check.h"
 #include "base/containers/contains.h"
 #include "base/files/file_util.h"
 #include "base/logging.h"
@@ -100,8 +101,17 @@
 
 void FirstPartySets::ParseAndSet(base::File sets_file) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
-  if (!enabled_)
+  if (!enabled_ || component_sets_parse_progress_ != Progress::kNotStarted) {
     return;
+  }
+
+  component_sets_parse_progress_ = Progress::kStarted;
+
+  if (!sets_file.IsValid()) {
+    OnReadSetsFile("");
+    return;
+  }
+
   base::ThreadPool::PostTaskAndReplyWithResult(
       FROM_HERE, {base::MayBlock(), base::TaskPriority::BEST_EFFORT},
       base::BindOnce(&ReadSetsFile, std::move(sets_file)),
@@ -111,8 +121,8 @@
 
 void FirstPartySets::OnReadSetsFile(const std::string& raw_sets) {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
-  if (!enabled_)
-    return;
+  DCHECK_EQ(component_sets_parse_progress_, Progress::kStarted);
+  DCHECK(enabled_);
 
   bool is_v1_format = raw_sets.find('[') < raw_sets.find('{');
   if (is_v1_format) {
@@ -128,7 +138,7 @@
                             is_v1_format);
 
   ApplyManuallySpecifiedSet();
-  component_sets_ready_ = true;
+  component_sets_parse_progress_ = Progress::kFinished;
   ClearSiteDataOnChangedSetsIfReady();
 }
 
@@ -345,8 +355,9 @@
 
 void FirstPartySets::ClearSiteDataOnChangedSetsIfReady() {
   DCHECK_CALLED_ON_VALID_SEQUENCE(sequence_checker_);
-  if (!persisted_sets_ready_ || !component_sets_ready_ || !manual_sets_ready_ ||
-      on_site_data_cleared_.is_null())
+  if (!persisted_sets_ready_ ||
+      component_sets_parse_progress_ != Progress::kFinished ||
+      !manual_sets_ready_ || on_site_data_cleared_.is_null())
     return;
 
   base::flat_set<net::SchemefulSite> diff = ComputeSetsDiff(
diff --git a/services/network/first_party_sets/first_party_sets.h b/services/network/first_party_sets/first_party_sets.h
index 5afda58..af9ce173 100644
--- a/services/network/first_party_sets/first_party_sets.h
+++ b/services/network/first_party_sets/first_party_sets.h
@@ -51,8 +51,15 @@
   // record is a set declaration in the format specified here:
   // https://github.com/privacycg/first-party-sets.
   //
-  // In case of invalid input, the members-to-owners map is cleared, but keeps
-  // any manually-specified set (i.e. a set provided on the command line).
+  // Only the first call to ParseAndSet can have any effect; subsequent
+  // invocations are ignored.
+  //
+  // If `sets_file.IsValid()` is false, then the set of sets is considered
+  // empty.
+  //
+  // In case of invalid input, the set of sets provided by the file is
+  // considered empty. Note that the FirstPartySets instance may still have some
+  // sets, from the command line or enterprise policies.
   //
   // Has no effect if `kFirstPartySets` is disabled.
   void ParseAndSet(base::File sets_file);
@@ -159,8 +166,15 @@
 
   std::string raw_persisted_sets_ GUARDED_BY_CONTEXT(sequence_checker_);
 
+  enum Progress {
+    kNotStarted,
+    kStarted,
+    kFinished,
+  };
+
   bool persisted_sets_ready_ GUARDED_BY_CONTEXT(sequence_checker_) = false;
-  bool component_sets_ready_ GUARDED_BY_CONTEXT(sequence_checker_) = false;
+  Progress component_sets_parse_progress_
+      GUARDED_BY_CONTEXT(sequence_checker_) = kNotStarted;
   bool manual_sets_ready_ GUARDED_BY_CONTEXT(sequence_checker_) = false;
   bool enabled_ GUARDED_BY_CONTEXT(sequence_checker_) = false;
   // The callback runs after the site state clearing is completed.
diff --git a/services/network/first_party_sets/first_party_sets_unittest.cc b/services/network/first_party_sets/first_party_sets_unittest.cc
index 5448b9e..11c7a92 100644
--- a/services/network/first_party_sets/first_party_sets_unittest.cc
+++ b/services/network/first_party_sets/first_party_sets_unittest.cc
@@ -4,6 +4,8 @@
 
 #include "services/network/first_party_sets/first_party_sets.h"
 
+#include <string>
+
 #include "base/files/file_util.h"
 #include "base/files/scoped_temp_dir.h"
 #include "base/json/json_reader.h"
@@ -62,6 +64,8 @@
 
   FirstPartySets& sets() { return sets_; }
 
+  base::test::TaskEnvironment& env() { return env_; }
+
  private:
   base::test::ScopedFeatureList feature_list_;
   base::test::TaskEnvironment env_;
@@ -155,6 +159,21 @@
   EXPECT_THAT(sets().Sets(), IsEmpty());
 }
 
+TEST_F(FirstPartySetsEnabledTest, IgnoresInvalidFile) {
+  sets().ParseAndSet(base::File());
+  env().RunUntilIdle();
+  EXPECT_THAT(sets().Sets(), IsEmpty());
+
+  const std::string input =
+      "{\"owner\": \"https://example.test\",\"members\": "
+      "[\"https://aaaa.test\",],}";
+
+  // Subsequent ParseAndSet calls should be ignored, because the instance has
+  // already received sets from component updater.
+  SetComponentSetsAndWait(input);
+  EXPECT_THAT(sets().Sets(), IsEmpty());
+}
+
 TEST_F(FirstPartySetsEnabledTest, ParsesJSON) {
   SetComponentSetsAndWait("[]");
   EXPECT_THAT(sets().Sets(), IsEmpty());
@@ -236,8 +255,8 @@
                                     SerializesTo("https://member2.test")))));
 }
 
-TEST_F(FirstPartySetsEnabledTest, ClearsPreloadedOnError) {
-  const std::string input = R"(
+TEST_F(FirstPartySetsEnabledTest, ParseAndSet_Idempotent) {
+  std::string input = R"(
   [
     {
       "owner": "https://example.test",
@@ -262,9 +281,31 @@
                UnorderedElementsAre(SerializesTo("https://foo.test"),
                                     SerializesTo("https://member2.test")))));
 
-  SetComponentSetsAndWait("{}");
+  input = R"(
+  [
+    {
+      "owner": "https://example2.test",
+      "members": ["https://member1.test"]
+    },
+    {
+      "owner": "https://foo2.test",
+      "members": ["https://member2.test"]
+    }
+  ]
+  )";
+  ASSERT_TRUE(base::JSONReader::Read(input));
+  SetComponentSetsAndWait(input);
 
-  EXPECT_THAT(sets().Sets(), IsEmpty());
+  // The second call to ParseAndSet should have had no effect.
+  EXPECT_THAT(
+      sets().Sets(),
+      UnorderedElementsAre(
+          Pair(SerializesTo("https://example.test"),
+               UnorderedElementsAre(SerializesTo("https://example.test"),
+                                    SerializesTo("https://member1.test"))),
+          Pair(SerializesTo("https://foo.test"),
+               UnorderedElementsAre(SerializesTo("https://foo.test"),
+                                    SerializesTo("https://member2.test")))));
 }
 
 TEST_F(FirstPartySetsEnabledTest, OwnerIsOnlyMember) {
@@ -568,42 +609,6 @@
 }
 
 TEST_F(FirstPartySetsEnabledTest,
-       SetsManuallySpecified_ClearsPreloadedOnError) {
-  const std::string input = R"(
-  [
-    {
-      "owner": "https://bar.test",
-      "members": ["https://member3.test"]
-    }
-  ]
-  )";
-  ASSERT_TRUE(base::JSONReader::Read(input));
-  SetComponentSetsAndWait(input);
-
-  sets().SetManuallySpecifiedSet(
-      "https://example.test,https://member1.test,https://member2.test");
-  EXPECT_THAT(
-      sets().Sets(),
-      UnorderedElementsAre(
-          Pair(SerializesTo("https://example.test"),
-               UnorderedElementsAre(SerializesTo("https://example.test"),
-                                    SerializesTo("https://member1.test"),
-                                    SerializesTo("https://member2.test"))),
-          Pair(SerializesTo("https://bar.test"),
-               UnorderedElementsAre(SerializesTo("https://bar.test"),
-                                    SerializesTo("https://member3.test")))));
-
-  SetComponentSetsAndWait("{}");
-
-  EXPECT_THAT(sets().Sets(),
-              UnorderedElementsAre(Pair(
-                  SerializesTo("https://example.test"),
-                  UnorderedElementsAre(SerializesTo("https://example.test"),
-                                       SerializesTo("https://member1.test"),
-                                       SerializesTo("https://member2.test")))));
-}
-
-TEST_F(FirstPartySetsEnabledTest,
        SetsManuallySpecified_PrunesInducedSingletons) {
   const std::string input = R"(
   [
diff --git a/services/network/network_context.cc b/services/network/network_context.cc
index b4cc320..b5b0180 100644
--- a/services/network/network_context.cc
+++ b/services/network/network_context.cc
@@ -516,6 +516,16 @@
   if (params_->ct_policy)
     SetCTPolicy(std::move(params_->ct_policy));
 
+  base::FilePath sct_auditing_path;
+  if (base::FeatureList::IsEnabled(
+          features::kSCTAuditingRetryAndPersistReports)) {
+    GetFullDataFilePath(params_->file_paths,
+                        &network::mojom::NetworkContextFilePaths::
+                            sct_auditing_pending_reports_file_name,
+                        sct_auditing_path);
+  }
+  sct_auditing_handler_ =
+      std::make_unique<SCTAuditingHandler>(this, sct_auditing_path);
   sct_auditing_handler()->SetEnabled(params_->enable_sct_auditing);
 #endif
 
diff --git a/services/network/network_context.h b/services/network/network_context.h
index 40cd0e3d..08d7391 100644
--- a/services/network/network_context.h
+++ b/services/network/network_context.h
@@ -72,10 +72,6 @@
 #include "net/reporting/reporting_report.h"
 #endif  // BUILDFLAG(ENABLE_REPORTING)
 
-#if BUILDFLAG(IS_CT_SUPPORTED)
-#include "services/network/sct_auditing/sct_auditing_handler.h"
-#endif  // BUILDFLAG(IS_CT_SUPPORTED)
-
 namespace base {
 class UnguessableToken;
 }  // namespace base
@@ -115,6 +111,7 @@
 class ProxyLookupRequest;
 class ResourceScheduler;
 class ResourceSchedulerClient;
+class SCTAuditingHandler;
 class SessionCleanupCookieStore;
 class SQLiteTrustTokenPersister;
 class WebSocketFactory;
@@ -303,7 +300,9 @@
   void OnCTLogListUpdated(
       const std::vector<network::mojom::CTLogInfoPtr>& log_list,
       base::Time update_time);
-  SCTAuditingHandler* sct_auditing_handler() { return &sct_auditing_handler_; }
+  SCTAuditingHandler* sct_auditing_handler() {
+    return sct_auditing_handler_.get();
+  }
 #endif  // BUILDFLAG(IS_CT_SUPPORTED)
   void CreateUDPSocket(
       mojo::PendingReceiver<mojom::UDPSocket> receiver,
@@ -751,7 +750,7 @@
   raw_ptr<certificate_transparency::ChromeCTPolicyEnforcer>
       ct_policy_enforcer_ = nullptr;
 
-  SCTAuditingHandler sct_auditing_handler_{this};
+  std::unique_ptr<SCTAuditingHandler> sct_auditing_handler_;
 #endif  // BUILDFLAG(IS_CT_SUPPORTED)
 
 #if BUILDFLAG(IS_CHROMEOS_ASH)
diff --git a/services/network/public/cpp/cookie_manager_mojom_traits.cc b/services/network/public/cpp/cookie_manager_mojom_traits.cc
index 9c7778ae..12c5c13 100644
--- a/services/network/public/cpp/cookie_manager_mojom_traits.cc
+++ b/services/network/public/cpp/cookie_manager_mojom_traits.cc
@@ -8,6 +8,7 @@
 #include "net/cookies/cookie_constants.h"
 #include "net/cookies/cookie_options.h"
 #include "net/cookies/same_party_context.h"
+#include "services/network/public/mojom/cookie_manager.mojom.h"
 
 namespace mojo {
 
diff --git a/services/network/public/cpp/cookie_manager_mojom_traits.h b/services/network/public/cpp/cookie_manager_mojom_traits.h
index c2dc387..8bcd88c 100644
--- a/services/network/public/cpp/cookie_manager_mojom_traits.h
+++ b/services/network/public/cpp/cookie_manager_mojom_traits.h
@@ -17,7 +17,8 @@
 #include "net/cookies/cookie_options.h"
 #include "net/cookies/cookie_partition_key_collection.h"
 #include "net/cookies/same_party_context.h"
-#include "services/network/public/mojom/cookie_manager.mojom.h"
+#include "services/network/public/mojom/cookie_manager.mojom-forward.h"
+#include "services/network/public/mojom/cookie_partition_key.mojom.h"
 #include "third_party/abseil-cpp/absl/types/optional.h"
 
 namespace mojo {
diff --git a/services/network/public/mojom/network_context.mojom b/services/network/public/mojom/network_context.mojom
index 8cdb76c..2fe9068 100644
--- a/services/network/public/mojom/network_context.mojom
+++ b/services/network/public/mojom/network_context.mojom
@@ -253,6 +253,11 @@
   // flag is false.
   mojo_base.mojom.FilePath? reporting_and_nel_store_database_name;
 
+  // The name of the file to store pending SCT auditing reports inside
+  // `data_path`. If empty, or `data_path` is empty, or the file can't be
+  // opened, pending reports will instead be stored in-memory only.
+  mojo_base.mojom.FilePath? sct_auditing_pending_reports_file_name;
+
   // Specifies whether or not a migration of existing data should occur from
   // `unsandboxed_data_path` to `data_path`. It is not valid to set this to true
   // if an `unsandboxed_data_path` is not specified.
diff --git a/services/network/public/mojom/network_service.mojom b/services/network/public/mojom/network_service.mojom
index 245313f..713f0d7 100644
--- a/services/network/public/mojom/network_service.mojom
+++ b/services/network/public/mojom/network_service.mojom
@@ -340,11 +340,15 @@
   // collection of set declarations according to the format specified in this
   // document: https://github.com/privacycg/first-party-sets. The collection may
   // either be a single JSON array of such records, or a sequence of
-  // newline-delimited JSON objects (one per line). Note that by setting the
-  // First-Party Sets, any previous notion of First-Party Sets is cleared. On
-  // any kind of error, all First-Party Sets are cleared (except for the
-  // manually-specified set, if one exists).
-  SetFirstPartySets(mojo_base.mojom.ReadOnlyFile sets_file);
+  // newline-delimited JSON objects (one per line). Note that only the first
+  // invocation will have any effect. On any kind of error, this method has no
+  // effect.
+  //
+  // |sets_file| may be invalid ("nullopt"), if no such file exists on the
+  // client's device (i.e. if the First-Party Sets component has not been
+  // installed yet).  Such a case is considered the same as if the file's
+  // contents were empty.
+  SetFirstPartySets(mojo_base.mojom.ReadOnlyFile? sets_file);
 
   // Sets the First-Party Sets data that was persisted to compare it with the
   // current First-Party Sets data set by `SetFirstPartySets()`, which is
diff --git a/services/network/sct_auditing/sct_auditing_cache.h b/services/network/sct_auditing/sct_auditing_cache.h
index aad251b..c5c3bc6 100644
--- a/services/network/sct_auditing/sct_auditing_cache.h
+++ b/services/network/sct_auditing/sct_auditing_cache.h
@@ -43,6 +43,13 @@
 //
 // The SCTAuditingCache allows the embedder to configure SCT auditing via the
 // network service's ConfigureSCTAuditing() API.
+//
+// Note: The SCTAuditingCache's deduplication cache is not persisted to disk.
+// Pending reports that are persisted to disk by SCTAuditingHandler do not
+// repopulate the deduplication cache when loaded. Not persisting the dedupe
+// cache slightly increases the probability weight of sampling and sending SCTs
+// from sites a user commonly visits (i.e., those they are likely to visit in
+// every session).
 class COMPONENT_EXPORT(NETWORK_SERVICE) SCTAuditingCache {
  public:
   explicit SCTAuditingCache(size_t cache_size = 1024);
diff --git a/services/network/sct_auditing/sct_auditing_handler.cc b/services/network/sct_auditing/sct_auditing_handler.cc
index aecb59e..846e7f5 100644
--- a/services/network/sct_auditing/sct_auditing_handler.cc
+++ b/services/network/sct_auditing/sct_auditing_handler.cc
@@ -4,12 +4,27 @@
 
 #include "services/network/sct_auditing/sct_auditing_handler.h"
 
+#include "base/base64.h"
+#include "base/feature_list.h"
+#include "base/files/file_path.h"
+#include "base/files/file_util.h"
+#include "base/json/json_reader.h"
+#include "base/json/json_writer.h"
 #include "base/metrics/histogram_functions.h"
+#include "base/task/bind_post_task.h"
+#include "base/task/post_task.h"
+#include "base/task/sequenced_task_runner.h"
+#include "base/task/task_runner_util.h"
+#include "base/task/thread_pool.h"
 #include "base/time/time.h"
+#include "base/values.h"
+#include "net/base/backoff_entry.h"
+#include "net/base/backoff_entry_serializer.h"
 #include "net/base/hash_value.h"
 #include "net/traffic_annotation/network_traffic_annotation.h"
 #include "services/network/network_context.h"
 #include "services/network/network_service.h"
+#include "services/network/public/cpp/features.h"
 #include "services/network/public/mojom/network_context.mojom.h"
 #include "services/network/public/mojom/url_loader_factory.mojom.h"
 #include "services/network/public/proto/sct_audit_report.pb.h"
@@ -18,15 +33,169 @@
 
 namespace network {
 
-SCTAuditingHandler::SCTAuditingHandler(NetworkContext* context,
-                                       size_t cache_size)
-    : owner_network_context_(context), pending_reporters_(cache_size) {}
+namespace {
 
-SCTAuditingHandler::~SCTAuditingHandler() = default;
+std::string LoadReports(const base::FilePath& path) {
+  std::string result;
+  if (!base::ReadFileToString(path, &result)) {
+    return "";
+  }
+  return result;
+}
+
+// Keys in dictionary for each serialized pending reporter entry in the
+// top-level list of serialized entries.
+const char kReporterKeyKey[] = "reporter_key";
+const char kBackoffEntryKey[] = "backoff_entry";
+const char kReportKey[] = "report";
+
+}  // namespace
+
+SCTAuditingHandler::SCTAuditingHandler(NetworkContext* context,
+                                       const base::FilePath& persistence_path,
+                                       size_t cache_size)
+    : owner_network_context_(context),
+      pending_reporters_(cache_size),
+      persistence_path_(persistence_path),
+      foreground_runner_(base::SequencedTaskRunnerHandle::Get()) {
+  if (base::FeatureList::IsEnabled(
+          features::kSCTAuditingRetryAndPersistReports)) {
+    // If no persistence path is set, only store pending reporters in memory.
+    if (persistence_path_.empty()) {
+      return;
+    }
+
+    // Persisting reports uses a low priority task runner as it should not block
+    // anything user-visible, but it should block shutdown to ensure updates are
+    // persisted to disk (particularly clearing entries or the entire
+    // persisted state).
+    background_runner_ = base::ThreadPool::CreateSequencedTaskRunner(
+        {base::MayBlock(), base::TaskPriority::BEST_EFFORT,
+         base::TaskShutdownBehavior::BLOCK_SHUTDOWN});
+    writer_ = std::make_unique<base::ImportantFileWriter>(persistence_path_,
+                                                          background_runner_);
+
+    // Post a task to load persisted state after startup has finished.
+    foreground_runner_->PostTask(
+        FROM_HERE, base::BindOnce(&SCTAuditingHandler::OnStartupFinished,
+                                  weak_factory_.GetWeakPtr()));
+  }
+}
+
+SCTAuditingHandler::~SCTAuditingHandler() {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+  if (writer_ && writer_->HasPendingWrite()) {
+    writer_->DoScheduledWrite();
+  }
+}
+
+bool SCTAuditingHandler::SerializeData(std::string* output) {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+
+  base::Value reports(base::Value::Type::LIST);
+  for (const auto& kv : pending_reporters_) {
+    auto reporter_key = kv.first;
+    auto* reporter = kv.second.get();
+
+    base::Value report_entry(base::Value::Type::DICTIONARY);
+
+    report_entry.SetStringKey(kReporterKeyKey, reporter_key.ToString());
+
+    base::Value backoff_entry_value =
+        net::BackoffEntrySerializer::SerializeToValue(
+            *reporter->backoff_entry(), base::Time::Now());
+    report_entry.SetKey(kBackoffEntryKey, std::move(backoff_entry_value));
+
+    std::string serialized_report;
+    reporter->report()->SerializeToString(&serialized_report);
+    base::Base64Encode(serialized_report, &serialized_report);
+    report_entry.SetStringKey(kReportKey, serialized_report);
+
+    reports.Append(std::move(report_entry));
+  }
+  return base::JSONWriter::Write(reports, output);
+}
+
+void SCTAuditingHandler::DeserializeData(const std::string& serialized) {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+
+  // Parse the serialized reports.
+  absl::optional<base::Value> value = base::JSONReader::Read(serialized);
+  if (!value || !value->is_list()) {
+    return;
+  }
+
+  size_t num_reporters_deserialized = 0u;
+  for (const base::Value& sct_entry : value->GetList()) {
+    if (!sct_entry.is_dict()) {
+      continue;
+    }
+
+    const std::string* reporter_key_string =
+        sct_entry.FindStringKey(kReporterKeyKey);
+    const std::string* report_string = sct_entry.FindStringKey(kReportKey);
+    const base::Value* backoff_entry_value =
+        sct_entry.FindKey(kBackoffEntryKey);
+
+    if (!reporter_key_string || !report_string || !backoff_entry_value) {
+      continue;
+    }
+
+    // Try to read the reporter_key from the entry and convert back to a
+    // HashValue. If it fails, continue to the next entry.
+    net::HashValue cache_key(net::HASH_VALUE_SHA256);
+    if (!cache_key.FromString(*reporter_key_string)) {
+      continue;
+    }
+
+    // Check if cache_key already exists. If it's already in the pending set,
+    // skip re-adding it.
+    auto it = pending_reporters_.Get(cache_key);
+    if (it != pending_reporters_.end()) {
+      continue;
+    }
+
+    // Try to recreate the BackoffEntry from the serialized value.
+    std::unique_ptr<net::BackoffEntry> backoff_entry =
+        net::BackoffEntrySerializer::DeserializeFromValue(
+            *backoff_entry_value, &SCTAuditingReporter::kDefaultBackoffPolicy,
+            nullptr, base::Time::Now());
+    if (!backoff_entry) {
+      continue;
+    }
+
+    // Try parsing the serialized protobuf. If it fails, continue to next entry.
+    std::string decoded_report_string;
+    if (!base::Base64Decode(*report_string, &decoded_report_string)) {
+      continue;
+    }
+    auto audit_report = std::make_unique<sct_auditing::SCTClientReport>();
+    if (!audit_report->ParseFromString(decoded_report_string)) {
+      continue;
+    }
+
+    AddReporter(cache_key, std::move(audit_report), std::move(backoff_entry));
+    ++num_reporters_deserialized;
+  }
+  // TODO(crbug.com/1144205): Add metrics for number of reporters deserialized.
+}
+
+void SCTAuditingHandler::OnStartupFinished() {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+  is_after_startup_ = true;
+  // Load the persisted pending reports from disk on a background sequence, and
+  // then process them.
+  background_runner_->PostTaskAndReplyWithResult(
+      FROM_HERE, base::BindOnce(&LoadReports, persistence_path_),
+      base::BindOnce(&SCTAuditingHandler::OnReportsLoadedFromDisk,
+                     weak_factory_.GetWeakPtr()));
+}
 
 void SCTAuditingHandler::AddReporter(
     net::HashValue reporter_key,
-    std::unique_ptr<sct_auditing::SCTClientReport> report) {
+    std::unique_ptr<sct_auditing::SCTClientReport> report,
+    std::unique_ptr<net::BackoffEntry> backoff_entry) {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
   if (!enabled_) {
     return;
   }
@@ -43,14 +212,37 @@
   auto reporter = std::make_unique<SCTAuditingReporter>(
       reporter_key, std::move(report), GetURLLoaderFactory(), report_uri,
       traffic_annotation,
-      base::BindOnce(&SCTAuditingHandler::OnReporterFinished, GetWeakPtr()));
+      base::BindRepeating(&SCTAuditingHandler::OnReporterStateUpdated,
+                          GetWeakPtr()),
+      base::BindOnce(&SCTAuditingHandler::OnReporterFinished, GetWeakPtr()),
+      std::move(backoff_entry));
   reporter->Start();
   pending_reporters_.Put(reporter->key(), std::move(reporter));
 
   if (pending_reporters_.size() > pending_reporters_size_hwm_)
     pending_reporters_size_hwm_ = pending_reporters_.size();
+
+  // Trigger updating the persisted state.
+  if (writer_) {
+    writer_->ScheduleWrite(this);
+  }
 }
 
+void SCTAuditingHandler::OnReportsLoadedFromDisk(
+    const std::string& serialized) {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+  DCHECK(is_after_startup_);
+  DCHECK(!persisted_reports_read_);
+
+  persisted_reports_read_ = true;
+
+  DeserializeData(serialized);
+}
+
+// TODOO(crbug.com/1144205): This method should take a completion callback (for
+// callers like NetworkContext::ClearNetworkingHistoryBetween() that want to be
+// able to wait for the write completing), and pass it through to the `writer_`,
+// like TransportSecurityState does.
 void SCTAuditingHandler::ClearPendingReports() {
   // Delete any outstanding Reporters. This will delete any extant URLLoader
   // instances owned by the Reporters, which will cancel any outstanding
@@ -58,7 +250,9 @@
   // they trigger as they use a WeakPtr to the Reporter instance that posted the
   // task.
   pending_reporters_.Clear();
-  // TODO(crbug.com/1144205): Clear any persisted state.
+  if (writer_) {
+    writer_->ScheduleWrite(this);
+  }
 }
 
 void SCTAuditingHandler::SetEnabled(bool enabled) {
@@ -81,11 +275,27 @@
   return weak_factory_.GetWeakPtr();
 }
 
+void SCTAuditingHandler::OnReporterStateUpdated() {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+
+  // Trigger updating the persisted state.
+  if (writer_) {
+    writer_->ScheduleWrite(this);
+  }
+}
+
 void SCTAuditingHandler::OnReporterFinished(net::HashValue reporter_key) {
+  DCHECK(foreground_runner_->RunsTasksInCurrentSequence());
+
   auto it = pending_reporters_.Get(reporter_key);
   if (it != pending_reporters_.end()) {
     pending_reporters_.Erase(it);
   }
+
+  // Trigger updating the persisted state.
+  if (writer_) {
+    writer_->ScheduleWrite(this);
+  }
 }
 
 void SCTAuditingHandler::ReportHWMMetrics() {
diff --git a/services/network/sct_auditing/sct_auditing_handler.h b/services/network/sct_auditing/sct_auditing_handler.h
index 47c6bd6..188eab1 100644
--- a/services/network/sct_auditing/sct_auditing_handler.h
+++ b/services/network/sct_auditing/sct_auditing_handler.h
@@ -8,9 +8,12 @@
 #include <memory>
 
 #include "base/containers/lru_cache.h"
+#include "base/files/important_file_writer.h"
 #include "base/memory/weak_ptr.h"
+#include "base/task/sequenced_task_runner.h"
 #include "base/timer/timer.h"
 #include "mojo/public/cpp/bindings/remote.h"
+#include "net/base/backoff_entry.h"
 #include "net/base/hash_value.h"
 #include "services/network/public/mojom/url_loader_factory.mojom.h"
 #include "url/gurl.h"
@@ -25,21 +28,64 @@
 class SCTAuditingReporter;
 
 // SCTAuditingHandler owns SCT auditing reports for a specific NetworkContext.
-// Each SCTAuditingHandler is owned by its matching NetworkContext.
-class SCTAuditingHandler {
+// Each SCTAuditingHandler is owned by its matching NetworkContext. The
+// SCTAuditingHandler is also responsible for persisting pending auditing
+// reports to disk and loading them back on browser startup.
+//
+// Note: Persisted reports only repopulate the SCTAuditingHandler's
+// `pending_reports_` cache, and *do not* repopulate the SCTAuditingCache's
+// deduplication cache.
+class COMPONENT_EXPORT(NETWORK_SERVICE) SCTAuditingHandler
+    : public base::ImportantFileWriter::DataSerializer {
  public:
-  explicit SCTAuditingHandler(NetworkContext* context,
-                              size_t cache_size = 1024);
-  ~SCTAuditingHandler();
+  SCTAuditingHandler(NetworkContext* context,
+                     const base::FilePath& persistence_path,
+                     size_t cache_size = 1024);
+  ~SCTAuditingHandler() override;
 
   SCTAuditingHandler(const SCTAuditingHandler&) = delete;
   SCTAuditingHandler& operator=(const SCTAuditingHandler&) = delete;
 
+  // base::ImportantFileWriter::DataSerializer:
+  //
+  // Serializes `pending_reporters_` into `*output`. Returns true if all
+  // reporters were serialized correctly.
+  //
+  // The serialization format is a JSON list-of-dicts of the form:
+  //   [
+  //       {
+  //          "reporter_key": <serialized HashValue>,
+  //          "report": <serialized SCTClientReport>,
+  //          "backoff_entry": <serialized BackoffEntry>
+  //       }
+  //   ]
+  //
+  // Each entry in the dictionary includes sufficient information to deserialize
+  // and recreate the entries in the SCTAuditingHandler's pending reporters set.
+  bool SerializeData(std::string* output) override;
+
+  void DeserializeData(const std::string& serialized);
+
+  void OnStartupFinished();
+
   // Creates a new SCTAuditingReporter for the report and adds it to this
   // SCTAuditingHandler's pending reporters set. After creating the reporter,
   // this will call SCTAuditingReporter::Start() to initiate sending the report.
+  // Optionally takes in a BackoffEntry for recreating reporter state from
+  // persisted storage.
   void AddReporter(net::HashValue reporter_key,
-                   std::unique_ptr<sct_auditing::SCTClientReport> report);
+                   std::unique_ptr<sct_auditing::SCTClientReport> report,
+                   std::unique_ptr<net::BackoffEntry> backoff_entry = nullptr);
+
+  // Loads serialized reports from `serialized` and creates a new
+  // SCTAuditingReporter for each (if a reporter for that report does not yet
+  // exist). This results in the set of loaded reports being merged with any
+  // existing pending reports in the SCTAuditingCache.
+  // Returns true if all entries were parsed and deserialized correctly.
+  // If data does not deserialize correctly, this drops the entries rather than
+  // trying to recover. This means that reports currently (and intentionally,
+  // for simplicity) do no persist over format/version changes.
+  void OnReportsLoadedFromDisk(const std::string& serialized);
 
   // Clears the set of pending reporters for this SCTAuditingHandler.
   void ClearPendingReports();
@@ -58,9 +104,12 @@
     url_loader_factory_.Bind(std::move(factory));
   }
 
+  base::ImportantFileWriter* GetFileWriterForTesting() { return writer_.get(); }
+
   base::WeakPtr<SCTAuditingHandler> GetWeakPtr();
 
  private:
+  void OnReporterStateUpdated();
   void OnReporterFinished(net::HashValue reporter_key);
   void ReportHWMMetrics();
   network::mojom::URLLoaderFactory* GetURLLoaderFactory();
@@ -81,9 +130,18 @@
   bool enabled_ = false;
   base::RepeatingTimer histogram_timer_;
 
+  // Helper for safely writing data to disk.
+  std::unique_ptr<base::ImportantFileWriter> writer_;
+
   // Used to send reports.
   mojo::Remote<mojom::URLLoaderFactory> url_loader_factory_;
 
+  base::FilePath persistence_path_;
+  scoped_refptr<base::SequencedTaskRunner> foreground_runner_;
+  scoped_refptr<base::SequencedTaskRunner> background_runner_;
+  bool is_after_startup_ = false;
+  bool persisted_reports_read_ = false;
+
   base::WeakPtrFactory<SCTAuditingHandler> weak_factory_{this};
 };
 
diff --git a/services/network/sct_auditing/sct_auditing_handler_unittest.cc b/services/network/sct_auditing/sct_auditing_handler_unittest.cc
new file mode 100644
index 0000000..43b4e65
--- /dev/null
+++ b/services/network/sct_auditing/sct_auditing_handler_unittest.cc
@@ -0,0 +1,507 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "services/network/sct_auditing/sct_auditing_handler.h"
+
+#include <memory>
+
+#include "base/base64.h"
+#include "base/feature_list.h"
+#include "base/files/file_util.h"
+#include "base/files/scoped_temp_dir.h"
+#include "base/test/bind.h"
+#include "base/test/scoped_feature_list.h"
+#include "base/test/task_environment.h"
+#include "mojo/public/cpp/bindings/remote.h"
+#include "net/base/hash_value.h"
+#include "net/traffic_annotation/network_traffic_annotation.h"
+#include "net/traffic_annotation/network_traffic_annotation_test_helper.h"
+#include "services/network/network_context.h"
+#include "services/network/network_service.h"
+#include "services/network/public/cpp/features.h"
+#include "services/network/public/cpp/resource_request.h"
+#include "services/network/public/proto/sct_audit_report.pb.h"
+#include "services/network/sct_auditing/sct_auditing_cache.h"
+#include "services/network/sct_auditing/sct_auditing_reporter.h"
+#include "services/network/test/fake_test_cert_verifier_params_factory.h"
+#include "services/network/test/test_url_loader_factory.h"
+#include "services/network/test/test_utils.h"
+#include "services/network/url_loader_factory.h"
+#include "testing/gtest/include/gtest/gtest.h"
+
+namespace network {
+
+namespace {
+
+class SCTAuditingHandlerTest : public testing::Test {
+ public:
+  SCTAuditingHandlerTest()
+      : network_service_(NetworkService::CreateForTesting()) {}
+  ~SCTAuditingHandlerTest() override = default;
+
+  SCTAuditingHandlerTest(const SCTAuditingHandlerTest&) = delete;
+  SCTAuditingHandlerTest& operator=(const SCTAuditingHandlerTest&) = delete;
+
+  void SetUp() override {
+    ASSERT_TRUE(persistence_dir_.CreateUniqueTempDir());
+    persistence_path_ = persistence_dir_.GetPath().AppendASCII("SCT Auditing");
+
+    // Set up a NetworkContext.
+    mojom::NetworkContextParamsPtr context_params =
+        CreateNetworkContextParamsForTesting();
+    context_params->cert_verifier_params =
+        FakeTestCertVerifierParamsFactory::GetCertVerifierParams();
+    context_params->enable_sct_auditing = true;
+    network_context_ = std::make_unique<NetworkContext>(
+        network_service_.get(),
+        network_context_remote_.BindNewPipeAndPassReceiver(),
+        std::move(context_params));
+
+    // Set up SCT auditing configuration.
+    auto* cache = network_service_->sct_auditing_cache();
+    cache->set_enabled(true);
+    cache->set_sampling_rate(1.0);
+    cache->set_report_uri(GURL("https://example.test"));
+    cache->set_traffic_annotation(
+        net::MutableNetworkTrafficAnnotationTag(TRAFFIC_ANNOTATION_FOR_TESTS));
+  }
+
+  // Get the contents of `persistence_path_`. Pumps the message loop before
+  // returning the result.
+  std::string GetTestFileContents() {
+    task_environment_.RunUntilIdle();
+    std::string file_contents;
+    base::ReadFileToString(persistence_path_, &file_contents);
+    return file_contents;
+  }
+
+  // Check whether `substring` appears in the file contents at
+  // `persistence_path_`.
+  bool FileContentsHasString(const std::string& substring) {
+    auto contents = GetTestFileContents();
+    auto position = contents.find(substring);
+    return position != std::string::npos;
+  }
+
+  // Waits for `expected_requests` to be seen by the TestURLLoaderFactory. Note
+  // that this only counts HTTP requests, so network errors (e.g., cert errors)
+  // won't count.
+  void WaitForRequests(size_t expected_requests) {
+    // Initialize a new RunLoop, so that tests can call WaitForRequests()
+    // multiple times, if needed.
+    run_loop_ = std::make_unique<base::RunLoop>();
+
+    if (num_requests_seen_ >= expected_requests) {
+      return;
+    }
+
+    // Add a TestURLLoaderFactory interceptor to count requests seen.
+    url_loader_factory_.SetInterceptor(base::BindLambdaForTesting(
+        [&](const network::ResourceRequest& request) {
+          ++num_requests_seen_;
+          if (run_loop_->running() && num_requests_seen_ >= expected_requests) {
+            run_loop_->QuitWhenIdle();
+          }
+        }));
+
+    run_loop_->Run();
+  }
+
+ protected:
+  base::test::TaskEnvironment task_environment_{
+      base::test::TaskEnvironment::MainThreadType::IO,
+      base::test::TaskEnvironment::TimeSource::MOCK_TIME};
+  base::ScopedTempDir persistence_dir_;
+  base::FilePath persistence_path_;
+  std::unique_ptr<NetworkService> network_service_;
+  std::unique_ptr<NetworkContext> network_context_;
+
+  TestURLLoaderFactory url_loader_factory_;
+
+  std::unique_ptr<base::RunLoop> run_loop_;
+  size_t num_requests_seen_ = 0;
+
+  // Stores the mojo::Remote<mojom::NetworkContext> of the most recently created
+  // NetworkContext.
+  mojo::Remote<mojom::NetworkContext> network_context_remote_;
+};
+
+// Test that when the retry+persistence feature is disabled no reports will be
+// persisted on disk.
+TEST_F(SCTAuditingHandlerTest, PersistenceFeatureDisabled) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndDisableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+  handler.SetEnabled(true);
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  // `file_writer` should not be created for this handler.
+  auto* file_writer = handler.GetFileWriterForTesting();
+  EXPECT_EQ(file_writer, nullptr);
+}
+
+// Test that when the SCTAuditingHandler is created without a persistence path
+// (e.g., as happens for ephemeral profiles), no file writer is created.
+TEST_F(SCTAuditingHandlerTest, HandlerWithoutPersistencePath) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  // Set up a Handler with an empty `persistence_path`.
+  SCTAuditingHandler handler(network_context_.get(), base::FilePath());
+  handler.SetEnabled(true);
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  // `file_writer` should not be created for this handler.
+  auto* file_writer = handler.GetFileWriterForTesting();
+  ASSERT_EQ(file_writer, nullptr);
+}
+
+// Test that when the SCTAuditingHandler is created with a valid persistence
+// path, then pending reports get stored to disk.
+TEST_F(SCTAuditingHandlerTest, HandlerWithPersistencePath) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+  handler.SetEnabled(true);
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  auto* file_writer = handler.GetFileWriterForTesting();
+  ASSERT_TRUE(file_writer);
+
+  // Add a Reporter to the Handler and check that it gets scheduled to be
+  // persisted to disk.
+  auto report = std::make_unique<sct_auditing::SCTClientReport>();
+  auto* tls_report = report->add_certificate_report();
+  auto* connection_context = tls_report->mutable_context();
+  auto* origin = connection_context->mutable_origin();
+  origin->set_hostname("example.test");
+  origin->set_port(443);
+
+  // Fake a HashValue to use as the key.
+  net::HashValue reporter_key(net::HASH_VALUE_SHA256);
+
+  handler.AddReporter(reporter_key, std::move(report));
+  ASSERT_EQ(handler.GetPendingReportersForTesting()->size(), 1u);
+  ASSERT_TRUE(file_writer->HasPendingWrite());
+
+  // Check that file got written with the expected content.
+  file_writer->DoScheduledWrite();
+  ASSERT_FALSE(file_writer->HasPendingWrite());
+  EXPECT_TRUE(FileContentsHasString(reporter_key.ToString()));
+
+  WaitForRequests(1u);
+
+  EXPECT_EQ(1, url_loader_factory_.NumPending());
+
+  // Simulate the server returning 200 OK to the report request.
+  url_loader_factory_.SimulateResponseForPendingRequest(
+      "https://example.test",
+      /*content=*/"",
+      /*status=*/net::HTTP_OK);
+
+  // Check that there are no pending requests anymore.
+  EXPECT_EQ(0, url_loader_factory_.NumPending());
+
+  // Check that the pending reporter was deleted on successful completion.
+  EXPECT_TRUE(handler.GetPendingReportersForTesting()->empty());
+
+  // Check that the Reporter is no longer in the file.
+  file_writer->DoScheduledWrite();
+  ASSERT_FALSE(file_writer->HasPendingWrite());
+  EXPECT_FALSE(FileContentsHasString(reporter_key.ToString()));
+}
+
+// Tests that serializing reports and then deserializing them results in the
+// same data.
+TEST_F(SCTAuditingHandlerTest, DataRoundTrip) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  // Create a Handler, add a reporter, and wait for it to get persisted.
+  {
+    SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+    handler.SetEnabled(true);
+    mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+    url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+    handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+    auto* file_writer = handler.GetFileWriterForTesting();
+    ASSERT_TRUE(file_writer);
+
+    ASSERT_TRUE(handler.is_enabled());
+    ASSERT_FALSE(file_writer->HasPendingWrite());
+
+    // Add a Reporter to the Handler and check that it gets scheduled to be
+    // persisted to disk.
+    auto report = std::make_unique<sct_auditing::SCTClientReport>();
+    auto* tls_report = report->add_certificate_report();
+    auto* connection_context = tls_report->mutable_context();
+    auto* origin = connection_context->mutable_origin();
+    origin->set_hostname("example.test");
+    origin->set_port(443);
+
+    // Fake a HashValue to use as the key.
+    net::HashValue reporter_key(net::HASH_VALUE_SHA256);
+
+    handler.AddReporter(reporter_key, std::move(report));
+    ASSERT_EQ(handler.GetPendingReportersForTesting()->size(), 1u);
+    ASSERT_TRUE(file_writer->HasPendingWrite());
+
+    // Check that file got written with the expected content.
+    file_writer->DoScheduledWrite();
+    ASSERT_FALSE(file_writer->HasPendingWrite());
+    EXPECT_TRUE(FileContentsHasString(reporter_key.ToString()));
+  }
+
+  // Create a second Handler using the same persistence path. It should load
+  // the same data.
+  {
+    SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+    handler.SetEnabled(true);
+    mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+    url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+    handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+    auto* file_writer = handler.GetFileWriterForTesting();
+    ASSERT_TRUE(file_writer);
+
+    WaitForRequests(1u);
+
+    auto* pending_reporters = handler.GetPendingReportersForTesting();
+    ASSERT_EQ(1u, pending_reporters->size());
+
+    // Reporter should be for "example.test:443" as added in the first Handler.
+    for (const auto& reporter : *pending_reporters) {
+      auto origin =
+          reporter.second->report()->certificate_report(0).context().origin();
+      EXPECT_EQ(origin.hostname(), "example.test");
+      EXPECT_EQ(origin.port(), 443);
+    }
+  }
+}
+
+// Test that deserializing bad data shouldn't result in any reporters being
+// created.
+TEST_F(SCTAuditingHandlerTest, DeserializeBadData) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  // Set an empty persistence path so no file IO is performed.
+  SCTAuditingHandler handler(network_context_.get(), base::FilePath());
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  // Non-JSON data.
+  handler.DeserializeData("Blorp");
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 0u);
+
+  // JSON data but non-sensical.
+  handler.DeserializeData("[15]");
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 0u);
+
+  // JSON data in the right format, but with invalid keys.
+  handler.DeserializeData(R"([{"blorp": "a", "bloop": "b", "bleep": "c"}])");
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 0u);
+
+  // JSON data with the right format and keys, but data is invalid.
+  handler.DeserializeData(
+      R"([{"reporter_key": "a", "report": "b", "backoff_entry": ["c"]}])");
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 0u);
+
+  // Check that no file got written to the persistence path.
+  EXPECT_EQ(GetTestFileContents(), std::string());
+}
+
+// Test that a handler loads valid persisted data from disk and creates pending
+// reporters for each entry.
+TEST_F(SCTAuditingHandlerTest, HandlerWithExistingPersistedData) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  // Set up previously persisted data on disk:
+  // - Default-initialized net::HashValue(net::HASH_VALUE_SHA256)
+  // - Empty SCTClientReport for origin "example.test:443".
+  // - A simple BackoffEntry.
+  std::string persisted_report =
+      R"(
+        [{
+          "reporter_key":
+            "sha256/qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqo=",
+          "report": "EhUKExIRCgxleGFtcGxlLnRlc3QQuwM=",
+          "backoff_entry": [2,0,"30000000","11644578625551798"]
+        }]
+      )";
+  ASSERT_TRUE(base::WriteFile(persistence_path_, persisted_report));
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+  handler.SetEnabled(true);
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  auto* file_writer = handler.GetFileWriterForTesting();
+  ASSERT_TRUE(file_writer);
+
+  WaitForRequests(1u);
+
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 1u);
+  EXPECT_EQ(1, url_loader_factory_.NumPending());
+
+  // Simulate the server returning 200 OK to the report request.
+  url_loader_factory_.SimulateResponseForPendingRequest(
+      "https://example.test",
+      /*content=*/"",
+      /*status=*/net::HTTP_OK);
+
+  // Check that there is no pending requests anymore.
+  EXPECT_EQ(0, url_loader_factory_.NumPending());
+
+  // Check that the pending reporter was deleted on successful completion.
+  EXPECT_TRUE(handler.GetPendingReportersForTesting()->empty());
+
+  // Check that the Reporter is no longer in the file.
+  file_writer->DoScheduledWrite();
+  ASSERT_FALSE(file_writer->HasPendingWrite());
+  EXPECT_FALSE(FileContentsHasString(
+      "sha256/qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqo="));
+}
+
+// Test that scheduling a retry causes the failure count to increment in
+// persisted storage.
+TEST_F(SCTAuditingHandlerTest, RetryUpdatesPersistedBackoffEntry) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  // Set up previously persisted data on disk:
+  // - Default-initialized net::HashValue(net::HASH_VALUE_SHA256)
+  // - Empty SCTClientReport for origin "example.test:443".
+  // - A simple BackoffEntry with a failure count of "1".
+  std::string persisted_report =
+      R"(
+        [{
+          "reporter_key":
+            "sha256/qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqo=",
+          "report": "EhUKExIRCgxleGFtcGxlLnRlc3QQuwM=",
+          "backoff_entry": [2,1,"30000000","11644578625551798"]
+        }]
+      )";
+  ASSERT_TRUE(base::WriteFile(persistence_path_, persisted_report));
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+  handler.SetEnabled(true);
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  auto* file_writer = handler.GetFileWriterForTesting();
+  ASSERT_TRUE(file_writer);
+
+  WaitForRequests(1u);
+
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 1u);
+  EXPECT_EQ(url_loader_factory_.NumPending(), 1);
+
+  // Simulate the server returning error to the report request. The Reporter
+  // should schedule a retry and trigger updating the persisted storage.
+  url_loader_factory_.SimulateResponseForPendingRequest(
+      "https://example.test",
+      /*content=*/"",
+      /*status=*/net::HTTP_TOO_MANY_REQUESTS);
+  EXPECT_EQ(url_loader_factory_.NumPending(), 0);
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 1u);
+  ASSERT_TRUE(file_writer->HasPendingWrite());
+
+  // Check that the Reporter is updated in the persisted storage file.
+  file_writer->DoScheduledWrite();
+  ASSERT_FALSE(file_writer->HasPendingWrite());
+  EXPECT_TRUE(FileContentsHasString(
+      "sha256/qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqo="));
+  // Persisted backoff entry should have the failure count incrememted to 2.
+  // (The first value of a serialized BackoffEntry is the version, the second is
+  // the failure count.)
+  EXPECT_TRUE(FileContentsHasString(R"("backoff_entry":[2,2,)"));
+}
+
+// Test that retries carry over correctly. Specifically, a persisted entry with
+// 14 retries already (one less than kMaxRetries), if after being loaded from
+// persisted storage tries and fails once more, should get deleted.
+TEST_F(SCTAuditingHandlerTest, RestoringMaxRetries) {
+  base::test::ScopedFeatureList scoped_feature_list;
+  scoped_feature_list.InitAndEnableFeature(
+      features::kSCTAuditingRetryAndPersistReports);
+
+  // Set up previously persisted data on disk:
+  // - Default-initialized net::HashValue(net::HASH_VALUE_SHA256)
+  // - Empty SCTClientReport for origin "example.test:443".
+  // - A simple BackoffEntry with a failure count of "15" (so it is scheduled to
+  //   retry for the 15th and final time).
+  std::string persisted_report =
+      R"(
+        [{
+          "reporter_key":
+            "sha256/qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqo=",
+          "report": "EhUKExIRCgxleGFtcGxlLnRlc3QQuwM=",
+          "backoff_entry": [2,15,"30000000","11644578625551798"]
+        }]
+      )";
+  ASSERT_TRUE(base::WriteFile(persistence_path_, persisted_report));
+
+  mojo::PendingRemote<network::mojom::URLLoaderFactory> factory_remote;
+  url_loader_factory_.Clone(factory_remote.InitWithNewPipeAndPassReceiver());
+
+  SCTAuditingHandler handler(network_context_.get(), persistence_path_);
+  handler.SetEnabled(true);
+  handler.SetURLLoaderFactoryForTesting(std::move(factory_remote));
+
+  auto* file_writer = handler.GetFileWriterForTesting();
+  ASSERT_TRUE(file_writer);
+
+  WaitForRequests(1u);
+
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 1u);
+  EXPECT_EQ(url_loader_factory_.NumPending(), 1);
+
+  // Simulate the server returning error to the report request. The Reporter
+  // should schedule a retry and trigger updating the persisted storage.
+  url_loader_factory_.SimulateResponseForPendingRequest(
+      "https://example.test",
+      /*content=*/"",
+      /*status=*/net::HTTP_TOO_MANY_REQUESTS);
+  EXPECT_EQ(url_loader_factory_.NumPending(), 0);
+
+  // Pending reporter should get deleted as it has reached max retries.
+  EXPECT_EQ(handler.GetPendingReportersForTesting()->size(), 0u);
+
+  // Reporter state on disk should get deleted as well.
+  file_writer->DoScheduledWrite();
+  ASSERT_FALSE(file_writer->HasPendingWrite());
+  EXPECT_FALSE(FileContentsHasString(
+      "sha256/qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqo="));
+}
+
+}  // namespace
+
+}  // namespace network
diff --git a/services/network/sct_auditing/sct_auditing_reporter.cc b/services/network/sct_auditing/sct_auditing_reporter.cc
index 0cca80d..d664401d 100644
--- a/services/network/sct_auditing/sct_auditing_reporter.cc
+++ b/services/network/sct_auditing/sct_auditing_reporter.cc
@@ -73,7 +73,7 @@
 // roughly the next five days.
 // See more discussion in the SCT Auditing Retry and Persistence design doc:
 // https://docs.google.com/document/d/1YTUzoG6BDF1QIxosaQDp2H5IzYY7_fwH8qNJXSVX8OQ/edit
-constexpr size_t kMaxRetries = 15;
+constexpr int kMaxRetries = 15;
 
 SCTAuditingReporter::SCTAuditingReporter(
     net::HashValue reporter_key,
@@ -81,13 +81,15 @@
     mojom::URLLoaderFactory* url_loader_factory,
     const GURL& report_uri,
     const net::MutableNetworkTrafficAnnotationTag& traffic_annotation,
-    ReporterDoneCallback done_callback)
+    ReporterUpdatedCallback update_callback,
+    ReporterDoneCallback done_callback,
+    std::unique_ptr<net::BackoffEntry> persisted_backoff_entry)
     : reporter_key_(reporter_key),
       report_(std::move(report)),
       traffic_annotation_(traffic_annotation),
       report_uri_(report_uri),
+      update_callback_(std::move(update_callback)),
       done_callback_(std::move(done_callback)),
-      num_retries_(0),
       max_retries_(kMaxRetries) {
   // Clone the URLLoaderFactory to avoid any dependencies on its lifetime. The
   // Reporter instance can maintain its own copy.
@@ -104,34 +106,31 @@
     backoff_policy_.initial_delay_ms =
         g_retry_delay_for_testing->InMilliseconds();
   }
-  backoff_entry_ = std::make_unique<net::BackoffEntry>(&backoff_policy_);
+
+  // `persisted_backoff_entry` is only non-null when persistence is enabled and
+  // this SCTAuditingReporter is being created from a reporter that had been
+  // persisted to disk.
+  if (persisted_backoff_entry) {
+    backoff_entry_ = std::move(persisted_backoff_entry);
+  } else {
+    backoff_entry_ = std::make_unique<net::BackoffEntry>(&backoff_policy_);
+    // Informing the backoff entry of a success will force it to use the initial
+    // delay (and jitter) for the first attempt. Otherwise,
+    // ShouldRejectRequest() will return `true` despite the policy specifying
+    // `always_use_initial_delay = true`.
+    backoff_entry_->InformOfRequest(true);
+  }
 }
 
 SCTAuditingReporter::~SCTAuditingReporter() = default;
 
 void SCTAuditingReporter::Start() {
-  // Informing the backoff entry of a success will force it to use the initial
-  // delay (and jitter) for the first attempt. Otherwise, ShouldRejectRequest()
-  // will return `true` despite the policy specifying
-  // `always_use_initial_delay = true`.
-  backoff_entry_->InformOfRequest(true);
-
-  // Start sending the report.
-  ScheduleReport();
-}
-
-void SCTAuditingReporter::SetRetryDelayForTesting(
-    absl::optional<base::TimeDelta> delay) {
-  g_retry_delay_for_testing = delay;
-}
-
-void SCTAuditingReporter::ScheduleReport() {
   if (base::FeatureList::IsEnabled(
           features::kSCTAuditingRetryAndPersistReports) &&
       backoff_entry_->ShouldRejectRequest()) {
     // TODO(crbug.com/1199827): Investigate if explicit task traits should be
     // used for these tasks (e.g., BEST_EFFORT and SKIP_ON_SHUTDOWN).
-    base::ThreadTaskRunnerHandle::Get()->PostDelayedTask(
+    base::SequencedTaskRunnerHandle::Get()->PostDelayedTask(
         FROM_HERE,
         base::BindOnce(&SCTAuditingReporter::SendReport,
                        weak_factory_.GetWeakPtr()),
@@ -141,6 +140,11 @@
   }
 }
 
+void SCTAuditingReporter::SetRetryDelayForTesting(
+    absl::optional<base::TimeDelta> delay) {
+  g_retry_delay_for_testing = delay;
+}
+
 void SCTAuditingReporter::SendReport() {
   DCHECK(url_loader_factory_remote_);
 
@@ -191,7 +195,7 @@
           features::kSCTAuditingRetryAndPersistReports)) {
     if (success) {
       // Report succeeded.
-      if (num_retries_ == 0) {
+      if (backoff_entry_->failure_count() == 0) {
         ReportSCTAuditingCompletionStatusMetrics(
             CompletionStatus::kSuccessFirstTry);
       } else {
@@ -205,7 +209,7 @@
       return;
     }
     // Sending the report failed.
-    if (num_retries_ >= max_retries_) {
+    if (backoff_entry_->failure_count() >= max_retries_) {
       // Retry limit reached.
       ReportSCTAuditingCompletionStatusMetrics(
           CompletionStatus::kRetriesExhausted);
@@ -215,10 +219,11 @@
       std::move(done_callback_).Run(reporter_key_);
       return;
     } else {
-      // Schedule a retry.
-      ++num_retries_;
+      // Schedule a retry and alert the SCTAuditingHandler to trigger a write so
+      // it can persist the updated backoff entry.
       backoff_entry_->InformOfRequest(false);
-      ScheduleReport();
+      update_callback_.Run();
+      Start();
     }
   } else {
     // Retry is not enabled, so just notify the Cache that this Reporter is
diff --git a/services/network/sct_auditing/sct_auditing_reporter.h b/services/network/sct_auditing/sct_auditing_reporter.h
index 9bcdd2120..7e89aee3 100644
--- a/services/network/sct_auditing/sct_auditing_reporter.h
+++ b/services/network/sct_auditing/sct_auditing_reporter.h
@@ -45,6 +45,9 @@
   // The SHA256HashValue `reporter_key` is passed to uniquely identify this
   // reporter instance.
   using ReporterDoneCallback = base::OnceCallback<void(net::HashValue)>;
+  // Callback to notify the SCTAuditingHandler that the reporter has updated
+  // (e.g., the retry counter has been incremented).
+  using ReporterUpdatedCallback = base::RepeatingCallback<void()>;
 
   SCTAuditingReporter(
       net::HashValue reporter_key,
@@ -52,7 +55,9 @@
       mojom::URLLoaderFactory* url_loader_factory,
       const GURL& report_uri,
       const net::MutableNetworkTrafficAnnotationTag& traffic_annotation,
-      ReporterDoneCallback done_callback);
+      ReporterUpdatedCallback update_callback,
+      ReporterDoneCallback done_callback,
+      std::unique_ptr<net::BackoffEntry> backoff_entry = nullptr);
   ~SCTAuditingReporter();
 
   SCTAuditingReporter(const SCTAuditingReporter&) = delete;
@@ -64,6 +69,7 @@
 
   net::HashValue key() { return reporter_key_; }
   sct_auditing::SCTClientReport* report() { return report_.get(); }
+  net::BackoffEntry* backoff_entry() { return backoff_entry_.get(); }
 
   // These values are persisted to logs. Entries should not be renumbered and
   // numeric values should never be reused.
@@ -77,7 +83,6 @@
   static void SetRetryDelayForTesting(absl::optional<base::TimeDelta> delay);
 
  private:
-  void ScheduleReport();
   void SendReport();
   void OnSendReportComplete(scoped_refptr<net::HttpResponseHeaders> headers);
 
@@ -87,13 +92,13 @@
   std::unique_ptr<SimpleURLLoader> url_loader_;
   net::NetworkTrafficAnnotationTag traffic_annotation_;
   GURL report_uri_;
+  ReporterUpdatedCallback update_callback_;
   ReporterDoneCallback done_callback_;
 
   net::BackoffEntry::Policy backoff_policy_;
   std::unique_ptr<net::BackoffEntry> backoff_entry_;
 
-  size_t num_retries_;
-  size_t max_retries_;
+  int max_retries_;
 
   base::WeakPtrFactory<SCTAuditingReporter> weak_factory_{this};
 };
diff --git a/testing/buildbot/chromium.fyi.json b/testing/buildbot/chromium.fyi.json
index bddb60c..484b328 100644
--- a/testing/buildbot/chromium.fyi.json
+++ b/testing/buildbot/chromium.fyi.json
@@ -5006,6 +5006,2343 @@
       }
     ]
   },
+  "Win11 Tests x64": {
+    "gtest_tests": [
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "absl_hardening_tests",
+        "test_id_prefix": "ninja://third_party/abseil-cpp:absl_hardening_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "accessibility_unittests",
+        "test_id_prefix": "ninja://ui/accessibility:accessibility_unittests/"
+      },
+      {
+        "args": [
+          "angle_unittests"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "angle_unittests",
+        "test_id_prefix": "ninja://third_party/angle/src/tests:angle_unittests/",
+        "use_isolated_scripts_api": true
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "app_shell_unittests",
+        "test_id_prefix": "ninja://extensions/shell:app_shell_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "aura_unittests",
+        "test_id_prefix": "ninja://ui/aura:aura_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "base_unittests",
+        "test_id_prefix": "ninja://base:base_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "blink_common_unittests",
+        "test_id_prefix": "ninja://third_party/blink/common:blink_common_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "blink_fuzzer_unittests",
+        "test_id_prefix": "ninja://third_party/blink/renderer/platform:blink_fuzzer_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "blink_heap_unittests",
+        "test_id_prefix": "ninja://third_party/blink/renderer/platform/heap:blink_heap_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "blink_platform_unittests",
+        "test_id_prefix": "ninja://third_party/blink/renderer/platform:blink_platform_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "name": "webkit_unit_tests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "blink_unittests",
+        "test_id_prefix": "ninja://third_party/blink/renderer/controller:blink_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "boringssl_crypto_tests",
+        "test_id_prefix": "ninja://third_party/boringssl:boringssl_crypto_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "boringssl_ssl_tests",
+        "test_id_prefix": "ninja://third_party/boringssl:boringssl_ssl_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "browser_switcher_bho_unittests",
+        "test_id_prefix": "ninja://chrome/browser/browser_switcher/bho:browser_switcher_bho_unittests/"
+      },
+      {
+        "args": [
+          "--disable-features=WebRTC-H264WithOpenH264FFmpeg"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "quickrun_shards": 30,
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com",
+          "shards": 15
+        },
+        "test": "browser_tests",
+        "test_id_prefix": "ninja://chrome/test:browser_tests/"
+      },
+      {
+        "args": [
+          "--browser-ui-tests-verify-pixels",
+          "--enable-pixel-output-in-tests",
+          "--test-launcher-filter-file=../../testing/buildbot/filters/pixel_browser_tests.filter",
+          "--git-revision=${got_revision}"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "name": "pixel_browser_tests",
+        "precommit_args": [
+          "--gerrit-issue=${patch_issue}",
+          "--gerrit-patchset=${patch_set}",
+          "--buildbucket-id=${buildbucket_build_id}"
+        ],
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chrome-gold@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "browser_tests",
+        "test_id_prefix": "ninja://chrome/test:browser_tests/"
+      },
+      {
+        "args": [
+          "--gtest_filter=-*UsingRealWebcam*"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "capture_unittests",
+        "test_id_prefix": "ninja://media/capture:capture_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "cast_unittests",
+        "test_id_prefix": "ninja://media/cast:cast_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "cc_unittests",
+        "test_id_prefix": "ninja://cc:cc_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "chrome_app_unittests",
+        "test_id_prefix": "ninja://chrome/test:chrome_app_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "chrome_cleaner_unittests",
+        "test_id_prefix": "ninja://chrome/chrome_cleaner:chrome_cleaner_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "chrome_elf_unittests",
+        "test_id_prefix": "ninja://chrome/chrome_elf:chrome_elf_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "chromedriver_unittests",
+        "test_id_prefix": "ninja://chrome/test/chromedriver:chromedriver_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "color_unittests",
+        "test_id_prefix": "ninja://ui/color:color_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "components_browsertests",
+        "test_id_prefix": "ninja://components:components_browsertests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "components_unittests",
+        "test_id_prefix": "ninja://components:components_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "compositor_unittests",
+        "test_id_prefix": "ninja://ui/compositor:compositor_unittests/"
+      },
+      {
+        "args": [
+          "--disable-features=WebRTC-H264WithOpenH264FFmpeg"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com",
+          "shards": 6
+        },
+        "test": "content_browsertests",
+        "test_id_prefix": "ninja://content/test:content_browsertests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "content_unittests",
+        "test_id_prefix": "ninja://content/test:content_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "courgette_unittests",
+        "test_id_prefix": "ninja://courgette:courgette_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "crashpad_tests",
+        "test_id_prefix": "ninja://third_party/crashpad/crashpad:crashpad_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "cronet_tests",
+        "test_id_prefix": "ninja://components/cronet:cronet_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "cronet_unittests",
+        "test_id_prefix": "ninja://components/cronet:cronet_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "crypto_unittests",
+        "test_id_prefix": "ninja://crypto:crypto_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
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+        "test_id_prefix": "ninja://third_party/perfetto:perfetto_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "ppapi_unittests",
+        "test_id_prefix": "ninja://ppapi:ppapi_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
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+        "test_id_prefix": "ninja://printing:printing_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "remoting_unittests",
+        "test_id_prefix": "ninja://remoting:remoting_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "integrity": "high",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "sbox_integration_tests",
+        "test_id_prefix": "ninja://sandbox/win:sbox_integration_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
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+        "test_id_prefix": "ninja://sandbox/win:sbox_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "sbox_validation_tests",
+        "test_id_prefix": "ninja://sandbox/win:sbox_validation_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "service_manager_unittests",
+        "test_id_prefix": "ninja://services/service_manager/tests:service_manager_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "services_unittests",
+        "test_id_prefix": "ninja://services:services_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "integrity": "high",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "setup_unittests",
+        "test_id_prefix": "ninja://chrome/installer/setup:setup_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
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+        },
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+          "dimension_sets": [
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+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "shell_dialogs_unittests",
+        "test_id_prefix": "ninja://ui/shell_dialogs:shell_dialogs_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "skia_unittests",
+        "test_id_prefix": "ninja://skia:skia_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "dimension_sets": [
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+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
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+        "test_id_prefix": "ninja://ui/snapshot:snapshot_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
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+          "dimension_sets": [
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+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "sql_unittests",
+        "test_id_prefix": "ninja://sql:sql_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "storage_unittests",
+        "test_id_prefix": "ninja://storage:storage_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
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+          "dimension_sets": [
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+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "sync_integration_tests",
+        "test_id_prefix": "ninja://chrome/test:sync_integration_tests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "ui_base_unittests",
+        "test_id_prefix": "ninja://ui/base:ui_base_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "ui_touch_selection_unittests",
+        "test_id_prefix": "ninja://ui/touch_selection:ui_touch_selection_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
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+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "unit_tests",
+        "test_id_prefix": "ninja://chrome/test:unit_tests/"
+      },
+      {
+        "args": [
+          "--test-launcher-timeout=90000",
+          "--ui-test-action-max-timeout=45000",
+          "--ui-test-action-timeout=40000"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "updater_tests",
+        "test_id_prefix": "ninja://chrome/updater:updater_tests/"
+      },
+      {
+        "args": [
+          "--test-launcher-print-test-stdio=always",
+          "--test-launcher-timeout=90000",
+          "--ui-test-action-max-timeout=45000",
+          "--ui-test-action-timeout=40000",
+          "--ui-test-action-timeout=40000"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "updater_tests_system",
+        "test_id_prefix": "ninja://chrome/updater:updater_tests_system/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "url_unittests",
+        "test_id_prefix": "ninja://url:url_unittests/"
+      },
+      {
+        "args": [
+          "--git-revision=${got_revision}"
+        ],
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
+        "precommit_args": [
+          "--gerrit-issue=${patch_issue}",
+          "--gerrit-patchset=${patch_set}",
+          "--buildbucket-id=${buildbucket_build_id}"
+        ],
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chrome-gold@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "views_examples_unittests",
+        "test_id_prefix": "ninja://ui/views/examples:views_examples_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
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+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "views_unittests",
+        "test_id_prefix": "ninja://ui/views:views_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "viz_unittests",
+        "test_id_prefix": "ninja://components/viz:viz_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "vr_common_unittests",
+        "test_id_prefix": "ninja://chrome/browser/vr:vr_common_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "vr_pixeltests",
+        "test_id_prefix": "ninja://chrome/browser/vr:vr_pixeltests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "weblayer_browsertests",
+        "test_id_prefix": "ninja://weblayer/test:weblayer_browsertests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "weblayer_unittests",
+        "test_id_prefix": "ninja://weblayer/test:weblayer_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "wm_unittests",
+        "test_id_prefix": "ninja://ui/wm:wm_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "wtf_unittests",
+        "test_id_prefix": "ninja://third_party/blink/renderer/platform/wtf:wtf_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+          "script": "//testing/merge_scripts/standard_gtest_merge.py"
+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "zlib_unittests",
+        "test_id_prefix": "ninja://third_party/zlib:zlib_unittests/"
+      },
+      {
+        "isolate_profile_data": true,
+        "merge": {
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+        },
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+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test": "zucchini_unittests",
+        "test_id_prefix": "ninja://components/zucchini:zucchini_unittests/"
+      }
+    ],
+    "isolated_scripts": [
+      {
+        "isolate_name": "blink_python_tests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "blink_python_tests",
+        "resultdb": {
+          "enable": true
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://:blink_python_tests/"
+      },
+      {
+        "args": [
+          "--num-retries=3",
+          "--target",
+          "Release_x64"
+        ],
+        "isolate_name": "blink_web_tests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [
+            "--verbose"
+          ],
+          "script": "//third_party/blink/tools/merge_web_test_results.py"
+        },
+        "name": "blink_web_tests",
+        "resultdb": {
+          "enable": true
+        },
+        "results_handler": "layout tests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com",
+          "shards": 28
+        },
+        "test_id_prefix": "ninja://:blink_web_tests/"
+      },
+      {
+        "args": [
+          "--test-type=integration"
+        ],
+        "isolate_name": "chromedriver_py_tests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "chromedriver_py_tests",
+        "resultdb": {
+          "enable": true
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://chrome/test/chromedriver:chromedriver_py_tests/"
+      },
+      {
+        "isolate_name": "chromedriver_replay_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "chromedriver_replay_unittests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://chrome/test/chromedriver:chromedriver_replay_unittests/"
+      },
+      {
+        "args": [
+          "--gtest-benchmark-name=components_perftests"
+        ],
+        "isolate_name": "components_perftests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [
+            "--smoke-test-mode"
+          ],
+          "script": "//tools/perf/process_perf_results.py"
+        },
+        "name": "components_perftests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://components:components_perftests/"
+      },
+      {
+        "isolate_name": "content_shell_crash_test",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "content_shell_crash_test",
+        "resultdb": {
+          "enable": true,
+          "result_format": "single"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://content/shell:content_shell_crash_test/"
+      },
+      {
+        "isolate_name": "flatbuffers_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "flatbuffers_unittests",
+        "resultdb": {
+          "enable": true,
+          "result_format": "single"
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://third_party/flatbuffers:flatbuffers_unittests/"
+      },
+      {
+        "isolate_name": "grit_python_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "grit_python_unittests",
+        "resultdb": {
+          "enable": true
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://tools/grit:grit_python_unittests/"
+      },
+      {
+        "isolate_name": "mini_installer_tests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "mini_installer_tests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "integrity": "high",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://chrome/test/mini_installer:mini_installer_tests/"
+      },
+      {
+        "isolate_name": "mojo_python_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "mojo_python_unittests",
+        "resultdb": {
+          "enable": true
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://mojo/public/tools:mojo_python_unittests/"
+      },
+      {
+        "experiment_percentage": 100,
+        "isolate_name": "polymer_tools_python_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "polymer_tools_python_unittests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://tools/polymer:polymer_tools_python_unittests/"
+      },
+      {
+        "args": [
+          "BrowserMinidumpTest",
+          "-v",
+          "--passthrough",
+          "--retry-limit=2"
+        ],
+        "isolate_name": "telemetry_perf_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "telemetry_desktop_minidump_unittests",
+        "resultdb": {
+          "enable": true
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://chrome/test:telemetry_perf_unittests/"
+      },
+      {
+        "isolate_name": "telemetry_gpu_unittests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [],
+          "script": "//testing/merge_scripts/standard_isolated_script_merge.py"
+        },
+        "name": "telemetry_gpu_unittests",
+        "resultdb": {
+          "enable": true
+        },
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "idempotent": false,
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://chrome/test:telemetry_gpu_unittests/"
+      },
+      {
+        "args": [
+          "--gtest-benchmark-name=views_perftests"
+        ],
+        "isolate_name": "views_perftests",
+        "isolate_profile_data": true,
+        "merge": {
+          "args": [
+            "--smoke-test-mode"
+          ],
+          "script": "//tools/perf/process_perf_results.py"
+        },
+        "name": "views_perftests",
+        "swarming": {
+          "can_use_on_swarming_builders": true,
+          "dimension_sets": [
+            {
+              "cpu": "x86-64",
+              "os": "Windows-11-22000"
+            }
+          ],
+          "service_account": "chromium-tester@chops-service-accounts.iam.gserviceaccount.com"
+        },
+        "test_id_prefix": "ninja://ui/views:views_perftests/"
+      }
+    ]
+  },
   "android-backuprefptr-arm-fyi-rel": {
     "gtest_tests": [
       {
diff --git a/testing/buildbot/filters/fuchsia.components_unittests.filter b/testing/buildbot/filters/fuchsia.components_unittests.filter
index a29c809..91efe36 100644
--- a/testing/buildbot/filters/fuchsia.components_unittests.filter
+++ b/testing/buildbot/filters/fuchsia.components_unittests.filter
@@ -9,7 +9,6 @@
 -DownloadFile/DownloadFileTestWithRename.RenameError*
 -DownloadFile/DownloadFileTestWithRename.RenameWith*
 -DownloadPathReservationTrackerTest.UnwriteableDirectory
--EncryptedReportingJobConfigurationTest.Validate*
 -FilesystemProxyTest.DeleteFile*
 -FilesystemProxyTest.OpenFileAppend*
 -FilesystemProxyTest.OpenFileWrite*
@@ -19,6 +18,5 @@
 -PaintPreviewSerialUtils.TestSerialTypeface
 -PaintPreviewSubsetFontTest.TestBasicSubset
 -ProfilingJsonExporterTest.MemoryMaps
--RealtimeReportingJobConfigurationTest.ValidatePayload
 -SslCastSocketTest.TestConnectEndToEndWithRealSSL
 -UIDevToolsServerTest.ConnectionToViewsServer
diff --git a/testing/buildbot/filters/linux-lacros.interactive_ui_tests.filter b/testing/buildbot/filters/linux-lacros.interactive_ui_tests.filter
index d52a20a8..eb7b804 100644
--- a/testing/buildbot/filters/linux-lacros.interactive_ui_tests.filter
+++ b/testing/buildbot/filters/linux-lacros.interactive_ui_tests.filter
@@ -15,6 +15,7 @@
 -ExtensionApiTest.WindowOpenFocus
 -MenuViewDragAndDropTestNestedDrag.MenuViewDragAndDropNestedDrag
 -MenuViewDragAndDropTestTestInMenuDrag.TestInMenuDrag
+-OmniboxViewViewsTest.DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade
 -OmniboxViewViewsTest.SelectionClipboard
 -SameSiteSubframe*
 -SitePerProcessInteractiveBrowserTest.TabAndMouseFocusNavigation
diff --git a/testing/buildbot/filters/ozone-linux.interactive_ui_tests_wayland.filter b/testing/buildbot/filters/ozone-linux.interactive_ui_tests_wayland.filter
index 73af361..58a7b0c 100644
--- a/testing/buildbot/filters/ozone-linux.interactive_ui_tests_wayland.filter
+++ b/testing/buildbot/filters/ozone-linux.interactive_ui_tests_wayland.filter
@@ -28,6 +28,7 @@
 -KeyboardLockInteractiveBrowserTest.ActiveWithSomeKeysLocked
 -MediaDialogViewBrowserTest.PictureInPicture
 -NotificationsTestWithFakeMediaStream.ShouldQueueDuringScreenPresent
+-OmniboxViewViewsTest.DefaultTypedNavigationsToHttps_ZeroSuggest_NoUpgrade
 -OmniboxViewViewsTest.SelectionClipboard
 -PasswordBubbleInteractiveUiTest.AutoSigninNoFocus
 -PopupBlockerBrowserTest.ModalPopUnder
diff --git a/testing/buildbot/mixins.pyl b/testing/buildbot/mixins.pyl
index 40a714f..ad452e5 100644
--- a/testing/buildbot/mixins.pyl
+++ b/testing/buildbot/mixins.pyl
@@ -1106,6 +1106,13 @@
       ],
     },
   },
+  'win11': {
+    'swarming': {
+      'dimensions': {
+        'os': 'Windows-11-22000',
+      },
+    },
+  },
   'win7': {
     'swarming': {
       'dimensions': {
diff --git a/testing/buildbot/test_suite_exceptions.pyl b/testing/buildbot/test_suite_exceptions.pyl
index 631efff..ca15da0 100644
--- a/testing/buildbot/test_suite_exceptions.pyl
+++ b/testing/buildbot/test_suite_exceptions.pyl
@@ -376,6 +376,15 @@
           'Debug_x64',
         ],
       },
+      'Win11 Tests x64': {
+        'args': [
+          '--target',
+          'Release_x64',
+        ],
+        'swarming': {
+          "shards": 28
+        },
+      },
       'Win7 Tests (dbg)(1)': {
         'args': [
           '--debug',
@@ -673,6 +682,18 @@
           'quickrun_shards': 30,
         }
       },
+      'Win11 Tests x64': {
+        # crbug.com/868082
+        'args': [
+          '--disable-features=WebRTC-H264WithOpenH264FFmpeg',
+        ],
+        'swarming': {
+          # This is for slow test execution that often becomes a critical path of
+          # swarming jobs. crbug.com/868114
+          'shards': 15,
+          'quickrun_shards': 30,
+        }
+      },
       'Win7 Tests (1)': {
         # This is for slow test execution that often becomes a critical path of
         # swarming jobs. crbug.com/868114
@@ -1237,6 +1258,12 @@
           '--disable-features=WebRTC-H264WithOpenH264FFmpeg',
         ],
       },
+      'Win11 Tests x64': {
+        # crbug.com/868082
+        'args': [
+          '--disable-features=WebRTC-H264WithOpenH264FFmpeg',
+        ],
+      },
       'android-11-x86-rel': {
         # TODO(crbug.com/1137474): Remove after the test suite is green.
         'experiment_percentage': 100,
@@ -2963,6 +2990,7 @@
       'Linux - Future (dbg)',  # client.v8.chromium
       'Win10 Tests x64',
       'Win10 Tests x64 (dbg)',
+      'Win11 Tests x64',
     ],
   },
   'telemetry_unittests': {
@@ -2980,6 +3008,7 @@
       'Mac10.11 Tests',
 
       'Win10 Tests x64',
+      'Win11 Tests x64',
 
       # TODO(https://crbug.com/1267161): Re-enable when platform is supported.
       'mac11-arm64-rel-tests',
diff --git a/testing/buildbot/waterfalls.pyl b/testing/buildbot/waterfalls.pyl
index d7a91ae..cc4d1a2 100644
--- a/testing/buildbot/waterfalls.pyl
+++ b/testing/buildbot/waterfalls.pyl
@@ -2678,6 +2678,17 @@
           'scripts': 'chromium_win_scripts',
         },
       },
+      'Win11 Tests x64': {
+        'mixins': [
+          'x86-64',
+          'win11',
+          'isolate_profile_data',
+        ],
+        'test_suites': {
+          'gtest_tests': 'chromium_win10_gtests',
+          'isolated_scripts': 'chromium_win_rel_isolated_scripts',
+        },
+      },
       'android-backuprefptr-arm-fyi-rel': {
         'test_suites': {
           'gtest_tests': 'backuprefptr_gtests',
diff --git a/testing/variations/fieldtrial_testing_config.json b/testing/variations/fieldtrial_testing_config.json
index 16f5e83..b063a85 100644
--- a/testing/variations/fieldtrial_testing_config.json
+++ b/testing/variations/fieldtrial_testing_config.json
@@ -526,21 +526,6 @@
             ]
         }
     ],
-    "AndroidMessagesNearOomReduction": [
-        {
-            "platforms": [
-                "android"
-            ],
-            "experiments": [
-                {
-                    "name": "Enabled_2021-10-06",
-                    "enable_features": [
-                        "MessagesForAndroidNearOomReduction"
-                    ]
-                }
-            ]
-        }
-    ],
     "AndroidMessagesPWAInstall": [
         {
             "platforms": [
@@ -2837,6 +2822,21 @@
             ]
         }
     ],
+    "DWriteFontProxyOnIO": [
+        {
+            "platforms": [
+                "windows"
+            ],
+            "experiments": [
+                {
+                    "name": "Enabled",
+                    "enable_features": [
+                        "DWriteFontProxyOnIO"
+                    ]
+                }
+            ]
+        }
+    ],
     "DataReductionProxyFREPromo": [
         {
             "platforms": [
diff --git a/third_party/android_platform/development/scripts/stack.py b/third_party/android_platform/development/scripts/stack.py
index bcd1685..6420406 100755
--- a/third_party/android_platform/development/scripts/stack.py
+++ b/third_party/android_platform/development/scripts/stack.py
@@ -50,12 +50,11 @@
   print("  usage: " + sys.argv[0] + " [options] [FILE]")
   print()
   print("  --symbols-dir=path")
-  print("       the path to a symbols dir, such as")
+  print("       path to the Android OS symbols dir, such as")
   print("       =/tmp/out/target/product/dream/symbols")
   print()
   print("  --chrome-symbols-dir=path")
-  print("       the path to a Chrome symbols dir (can be absolute or relative")
-  print("       to src), such as =out/Debug/lib.unstripped")
+  print("       path to a Chrome symbols dir. E.g.: out/Debug/lib.unstripped")
   print()
   print("  --output-directory=path")
   print("       the path to the build output directory, such as out/Debug.")
@@ -169,8 +168,7 @@
       symbol.ARCH = value
       arch_defined = True
     elif option == "--chrome-symbols-dir":
-      symbol.CHROME_SYMBOLS_DIR = os.path.join(constants.DIR_SOURCE_ROOT,
-                                               value)
+      symbol.CHROME_SYMBOLS_DIR = value
     elif option == "--output-directory":
       constants.SetOutputDirectory(os.path.abspath(value))
     elif option == "--apks-directory":
diff --git a/third_party/blink/public/mojom/input/input_handler.mojom b/third_party/blink/public/mojom/input/input_handler.mojom
index 0216057b..773ac2bf 100644
--- a/third_party/blink/public/mojom/input/input_handler.mojom
+++ b/third_party/blink/public/mojom/input/input_handler.mojom
@@ -199,6 +199,11 @@
   // selection (which is a caret).
   int32 extended_start_adjust;
   int32 extended_end_adjust;
+  // The offset differences between the word selection (regardless of the
+  // extended selection granularity) and the initial selection (which is a
+  // caret).
+  int32 word_start_adjust;
+  int32 word_end_adjust;
 };
 
 // GENERATED_JAVA_ENUM_PACKAGE: org.chromium.blink_public.input
diff --git a/third_party/blink/public/mojom/payments/payment_request.mojom b/third_party/blink/public/mojom/payments/payment_request.mojom
index bcc1ab1..af662edd4 100644
--- a/third_party/blink/public/mojom/payments/payment_request.mojom
+++ b/third_party/blink/public/mojom/payments/payment_request.mojom
@@ -36,8 +36,7 @@
 struct SecurePaymentConfirmationResponse {
   blink.mojom.CommonCredentialInfo credential_info;
   array<uint8> signature;
-  bool has_transport;
-  blink.mojom.AuthenticatorTransport transport;
+  blink.mojom.AuthenticatorAttachment authenticator_attachment;
   array<uint8>? user_handle;
 };
 
diff --git a/third_party/blink/public/mojom/web_feature/web_feature.mojom b/third_party/blink/public/mojom/web_feature/web_feature.mojom
index 2899546..f89b116 100644
--- a/third_party/blink/public/mojom/web_feature/web_feature.mojom
+++ b/third_party/blink/public/mojom/web_feature/web_feature.mojom
@@ -3197,7 +3197,7 @@
   kWebAppManifestProtocolHandlers = 3884,
   kRTCPeerConnectionOfferAllowExtmapMixedFalse = 3885,
   kNewCanvas2DAPI = 3886,
-  kServiceWorkerSubresourceFilterBypassedRequest = 3887,
+  kOBSOLETE_ServiceWorkerSubresourceFilterBypassedRequest = 3887,
   kWebGPU = 3888,
   kCSSFilterColorMatrix = 3889,
   kHTMLFencedFrameElement = 3890,
diff --git a/third_party/blink/public/mojom/webauthn/authenticator.mojom b/third_party/blink/public/mojom/webauthn/authenticator.mojom
index ed9f764de..4156827 100644
--- a/third_party/blink/public/mojom/webauthn/authenticator.mojom
+++ b/third_party/blink/public/mojom/webauthn/authenticator.mojom
@@ -88,11 +88,8 @@
 struct MakeCredentialAuthenticatorResponse {
   CommonCredentialInfo info;
 
-  // True if transport exists. False if transport does not exist, e.g. on old
-  // Windows.
-  bool has_transport;
-  // The transport method used to authenticate.
-  AuthenticatorTransport transport;
+  // The attachment of the authenticator that created the credential.
+  AuthenticatorAttachment authenticator_attachment;
 
   // A blob of data returned by the authenticator after creating a credential.
   array<uint8> attestation_object;
@@ -156,11 +153,8 @@
 struct GetAssertionAuthenticatorResponse {
   CommonCredentialInfo info;
 
-  // True if transport exists. False if transport does not exist, e.g. on old
-  // Windows.
-  bool has_transport;
-  // The transport method used to authenticate.
-  AuthenticatorTransport transport;
+  // The attachment of the authenticator that created the credential.
+  AuthenticatorAttachment authenticator_attachment;
 
   // Cryptographic signature proving possession of the credential private key.
   array<uint8> signature;
diff --git a/third_party/blink/public/web/web_local_frame.h b/third_party/blink/public/web/web_local_frame.h
index a0e3492..562af77 100644
--- a/third_party/blink/public/web/web_local_frame.h
+++ b/third_party/blink/public/web/web_local_frame.h
@@ -875,8 +875,6 @@
   // Reset TextFinder state for the web test runner in between two tests.
   virtual void ClearActiveFindMatchForTesting() = 0;
 
-  virtual bool ServiceWorkerSubresourceFilterEnabled() = 0;
-
   // Sets a local storage area which can be used for this frame. This storage
   // area is ignored if a cached storage area already exists for the storage
   // key.
diff --git a/third_party/blink/renderer/bindings/scripts/bind_gen/callback_function.py b/third_party/blink/renderer/bindings/scripts/bind_gen/callback_function.py
index cae8eb9..b36fced5 100644
--- a/third_party/blink/renderer/bindings/scripts/bind_gen/callback_function.py
+++ b/third_party/blink/renderer/bindings/scripts/bind_gen/callback_function.py
@@ -412,7 +412,7 @@
         T("v8::TryCatch try_catch(${isolate});"),
         T("try_catch.SetVerbose(true);"),
         EmptyNode(),
-        F("ignore_result({api_func_name}({arg_names}));",
+        F("std::ignore = {api_func_name}({arg_names});",
           api_func_name=api_func_name,
           arg_names=", ".join(arg_names)),
     ])
@@ -594,8 +594,10 @@
         "third_party/blink/renderer/platform/bindings/callback_function_base.h",
         "third_party/blink/renderer/platform/bindings/v8_value_or_script_wrappable_adapter.h",
     ])
+    source_node.accumulator.add_stdcpp_include_headers([
+        "tuple",
+    ])
     source_node.accumulator.add_include_headers([
-        "base/ignore_result.h",
         "third_party/blink/renderer/bindings/core/v8/callback_invoke_helper.h",
         "third_party/blink/renderer/bindings/core/v8/generated_code_helper.h",
         "third_party/blink/renderer/bindings/core/v8/to_v8_traits.h",
diff --git a/third_party/blink/renderer/bindings/scripts/bind_gen/callback_interface.py b/third_party/blink/renderer/bindings/scripts/bind_gen/callback_interface.py
index 4bb0545..024ca13 100644
--- a/third_party/blink/renderer/bindings/scripts/bind_gen/callback_interface.py
+++ b/third_party/blink/renderer/bindings/scripts/bind_gen/callback_interface.py
@@ -283,8 +283,10 @@
         "third_party/blink/renderer/platform/bindings/callback_interface_base.h",
         "third_party/blink/renderer/platform/bindings/v8_value_or_script_wrappable_adapter.h",
     ])
+    source_node.accumulator.add_stdcpp_include_headers([
+        "tuple",
+    ])
     source_node.accumulator.add_include_headers([
-        "base/ignore_result.h",
         "third_party/blink/renderer/bindings/core/v8/callback_invoke_helper.h",
         "third_party/blink/renderer/bindings/core/v8/generated_code_helper.h",
         "third_party/blink/renderer/bindings/core/v8/to_v8_traits.h",
diff --git a/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_accumulator.py b/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_accumulator.py
index 2c822edf..c661802 100644
--- a/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_accumulator.py
+++ b/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_accumulator.py
@@ -10,16 +10,18 @@
     """
 
     def __init__(self):
-        # Headers to be included
+        # Headers of non-standard library to be included
         self._include_headers = set()
+        # Headers of C++ standard library to be included
+        self._stdcpp_include_headers = set()
         # Forward declarations of C++ class
         self._class_decls = set()
         # Forward declarations of C++ struct
         self._struct_decls = set()
 
     def total_size(self):
-        return (len(self.include_headers) + len(self.class_decls) + len(
-            self.struct_decls))
+        return (len(self.include_headers) + len(self.class_decls) +
+                len(self.struct_decls) + len(self.stdcpp_include_headers))
 
     @property
     def include_headers(self):
@@ -33,6 +35,18 @@
         return lambda accumulator: accumulator.add_include_headers(headers)
 
     @property
+    def stdcpp_include_headers(self):
+        return self._stdcpp_include_headers
+
+    def add_stdcpp_include_headers(self, headers):
+        self._stdcpp_include_headers.update(filter(None, headers))
+
+    @staticmethod
+    def require_stdcpp_include_headers(headers):
+        return lambda accumulator: accumulator.add_stdcpp_include_headers(
+            headers)
+
+    @property
     def class_decls(self):
         return self._class_decls
 
diff --git a/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_utils.py b/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_utils.py
index b21e325..0d5dfab 100644
--- a/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_utils.py
+++ b/third_party/blink/renderer/bindings/scripts/bind_gen/codegen_utils.py
@@ -55,11 +55,22 @@
             self._accumulator = accumulator
 
         def __str__(self):
-            return "\n".join([
+            lines = []
+
+            if self._accumulator.stdcpp_include_headers:
+                lines.extend([
+                    "#include <{}>".format(header) for header in sorted(
+                        self._accumulator.stdcpp_include_headers)
+                ])
+                lines.append("")
+
+            lines.extend([
                 "#include \"{}\"".format(header)
                 for header in sorted(self._accumulator.include_headers)
             ])
 
+            return "\n".join(lines)
+
     return LiteralNode(HeaderIncludeDirectives(accumulator))
 
 
diff --git a/third_party/blink/renderer/core/BUILD.gn b/third_party/blink/renderer/core/BUILD.gn
index b2a43ce..62eee2d8 100644
--- a/third_party/blink/renderer/core/BUILD.gn
+++ b/third_party/blink/renderer/core/BUILD.gn
@@ -304,7 +304,6 @@
   deps = [
     ":generated_settings_macros",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//components/paint_preview/common",
     "//components/performance_manager/public/mojom:mojom_blink",
     "//components/power_scheduler",
diff --git a/third_party/blink/renderer/core/display_lock/display_lock_utilities.h b/third_party/blink/renderer/core/display_lock/display_lock_utilities.h
index e620b94..a0992f2 100644
--- a/third_party/blink/renderer/core/display_lock/display_lock_utilities.h
+++ b/third_party/blink/renderer/core/display_lock/display_lock_utilities.h
@@ -9,6 +9,7 @@
 #include "third_party/blink/renderer/core/core_export.h"
 #include "third_party/blink/renderer/core/display_lock/display_lock_context.h"
 #include "third_party/blink/renderer/core/dom/range.h"
+#include "third_party/blink/renderer/core/editing/commands/apply_style_command.h"
 #include "third_party/blink/renderer/core/editing/ephemeral_range.h"
 #include "third_party/blink/renderer/core/editing/frame_selection.h"
 #include "third_party/blink/renderer/core/paint/paint_layer.h"
@@ -48,6 +49,9 @@
     friend void Document::UpdateStyleAndLayoutForNode(
         const Node* node,
         DocumentUpdateReason reason);
+    friend void Document::UpdateStyleAndLayoutForRange(
+        const Range* range,
+        DocumentUpdateReason reason);
     friend void Document::UpdateStyleAndLayoutTreeForNode(const Node*);
     friend void Document::UpdateStyleAndLayoutTreeForSubtree(const Node* node);
     friend void Document::EnsurePaintLocationDataValidForNode(
diff --git a/third_party/blink/renderer/core/dom/document.cc b/third_party/blink/renderer/core/dom/document.cc
index 10227b4..297b0b9 100644
--- a/third_party/blink/renderer/core/dom/document.cc
+++ b/third_party/blink/renderer/core/dom/document.cc
@@ -2322,6 +2322,13 @@
   }
 }
 
+void Document::UpdateStyleAndLayoutForRange(const Range* range,
+                                            DocumentUpdateReason reason) {
+  DisplayLockUtilities::ScopedForcedUpdate scoped_update_forced(
+      range, DisplayLockContext::ForcedPhase::kLayout);
+  UpdateStyleAndLayout(reason);
+}
+
 void Document::UpdateStyleAndLayoutForNode(const Node* node,
                                            DocumentUpdateReason reason) {
   DCHECK(node);
diff --git a/third_party/blink/renderer/core/dom/document.h b/third_party/blink/renderer/core/dom/document.h
index 796f548..26f606f6 100644
--- a/third_party/blink/renderer/core/dom/document.h
+++ b/third_party/blink/renderer/core/dom/document.h
@@ -639,6 +639,7 @@
     kRunPostLayoutTasksSynchronously,
   };
   void UpdateStyleAndLayoutForNode(const Node*, DocumentUpdateReason);
+  void UpdateStyleAndLayoutForRange(const Range*, DocumentUpdateReason);
   void IncLayoutCallsCounter() { ++layout_calls_counter_; }
   void IncLayoutCallsCounterNG() { ++layout_calls_counter_ng_; }
   void IncLayoutBlockCounter() { ++layout_blocks_counter_; }
diff --git a/third_party/blink/renderer/core/editing/commands/apply_style_command.cc b/third_party/blink/renderer/core/editing/commands/apply_style_command.cc
index 433b090..97cc32b 100644
--- a/third_party/blink/renderer/core/editing/commands/apply_style_command.cc
+++ b/third_party/blink/renderer/core/editing/commands/apply_style_command.cc
@@ -32,6 +32,7 @@
 #include "third_party/blink/renderer/core/css/css_property_names.h"
 #include "third_party/blink/renderer/core/css/css_property_value_set.h"
 #include "third_party/blink/renderer/core/css_value_keywords.h"
+#include "third_party/blink/renderer/core/display_lock/display_lock_utilities.h"
 #include "third_party/blink/renderer/core/dom/document.h"
 #include "third_party/blink/renderer/core/dom/node_list.h"
 #include "third_party/blink/renderer/core/dom/node_traversal.h"
@@ -965,7 +966,10 @@
   if (remove_only_)
     return;
 
-  GetDocument().UpdateStyleAndLayout(DocumentUpdateReason::kEditing);
+  Range* range = MakeGarbageCollected<Range>(GetDocument(), StartPosition(),
+                                             EndPosition());
+  GetDocument().UpdateStyleAndLayoutForRange(range,
+                                             DocumentUpdateReason::kEditing);
 
   HeapVector<InlineRunToApplyStyle> runs;
   Node* node = start_node;
@@ -1041,7 +1045,8 @@
     }
   }
 
-  GetDocument().UpdateStyleAndLayout(DocumentUpdateReason::kEditing);
+  GetDocument().UpdateStyleAndLayoutForRange(range,
+                                             DocumentUpdateReason::kEditing);
 
   for (auto& run : runs) {
     if (run.position_for_style_computation.IsNotNull())
diff --git a/third_party/blink/renderer/core/editing/frame_selection.cc b/third_party/blink/renderer/core/editing/frame_selection.cc
index 99a2f5b..9386c18 100644
--- a/third_party/blink/renderer/core/editing/frame_selection.cc
+++ b/third_party/blink/renderer/core/editing/frame_selection.cc
@@ -1148,69 +1148,44 @@
     TextGranularity text_granularity,
     HandleVisibility handle_visibility,
     ContextMenuVisibility context_menu_visibility) {
-  // Only supports word and sentence granularities for now.
-  DCHECK(text_granularity == TextGranularity::kWord ||
-         text_granularity == TextGranularity::kSentence);
+  CHECK(text_granularity == TextGranularity::kWord ||
+        text_granularity == TextGranularity::kSentence)
+      << "Only word and sentence granularities are supported for now";
 
-  const VisibleSelection& selection = ComputeVisibleSelectionInDOMTree();
-  // TODO(editing-dev): The use of VisibleSelection needs to be audited. See
-  // http://crbug.com/657237 for more details.
-  if (!selection.IsCaret())
+  EphemeralRange selection_range =
+      GetSelectionRangeAroundCaret(text_granularity);
+  if (selection_range.IsNull()) {
     return false;
-  const Position position = selection.Start();
-  static const WordSide kWordSideList[2] = {kNextWordIfOnBoundary,
-                                            kPreviousWordIfOnBoundary};
-  for (WordSide word_side : kWordSideList) {
-    Position start;
-    Position end;
-    // Use word granularity by default unless sentence granularity is explicitly
-    // requested.
-    if (text_granularity == TextGranularity::kSentence) {
-      start = StartOfSentencePosition(position);
-      end = EndOfSentence(position, SentenceTrailingSpaceBehavior::kOmitSpace)
-                .GetPosition();
-    } else {
-      start = StartOfWordPosition(position, word_side);
-      end = EndOfWordPosition(position, word_side);
-    }
-
-    // TODO(editing-dev): |StartOfWord()| and |EndOfWord()| should not make null
-    // for non-null parameter.
-    // See http://crbug.com/872443
-    if (start.IsNull() || end.IsNull())
-      continue;
-
-    if (start > end) {
-      // Since word boundaries are computed on flat tree, they can be reversed
-      // when mapped back to DOM.
-      std::swap(start, end);
-    }
-
-    String text = PlainText(EphemeralRange(start, end));
-    if (!text.IsEmpty() && !IsSeparator(text.CharacterStartingAt(0))) {
-      SetSelection(
-          SelectionInDOMTree::Builder().Collapse(start).Extend(end).Build(),
-          SetSelectionOptions::Builder()
-              .SetShouldCloseTyping(true)
-              .SetShouldClearTypingStyle(true)
-              .SetGranularity(text_granularity == TextGranularity::kSentence
-                                  ? TextGranularity::kSentence
-                                  : TextGranularity::kWord)
-              .SetShouldShowHandle(handle_visibility ==
-                                   HandleVisibility::kVisible)
-              .Build());
-
-      if (context_menu_visibility == ContextMenuVisibility::kVisible) {
-        ContextMenuAllowedScope scope;
-        frame_->GetEventHandler().ShowNonLocatedContextMenu(
-            /*override_target_element=*/nullptr, kMenuSourceTouch);
-      }
-
-      return true;
-    }
   }
 
-  return false;
+  SetSelection(
+      SelectionInDOMTree::Builder()
+          .Collapse(selection_range.StartPosition())
+          .Extend(selection_range.EndPosition())
+          .Build(),
+      SetSelectionOptions::Builder()
+          .SetShouldCloseTyping(true)
+          .SetShouldClearTypingStyle(true)
+          .SetGranularity(text_granularity)
+          .SetShouldShowHandle(handle_visibility == HandleVisibility::kVisible)
+          .Build());
+
+  if (context_menu_visibility == ContextMenuVisibility::kVisible) {
+    ContextMenuAllowedScope scope;
+    frame_->GetEventHandler().ShowNonLocatedContextMenu(
+        /*override_target_element=*/nullptr, kMenuSourceTouch);
+  }
+
+  return true;
+}
+
+EphemeralRange FrameSelection::GetWordSelectionRangeAroundCaret() const {
+  return GetSelectionRangeAroundCaret(TextGranularity::kWord);
+}
+
+EphemeralRange FrameSelection::GetSelectionRangeAroundCaretForTesting(
+    TextGranularity text_granularity) const {
+  return GetSelectionRangeAroundCaret(text_granularity);
 }
 
 GranularityStrategy* FrameSelection::GetGranularityStrategy() {
@@ -1345,6 +1320,59 @@
   selection_editor_->MarkCacheDirty();
 }
 
+EphemeralRange FrameSelection::GetSelectionRangeAroundCaret(
+    TextGranularity text_granularity) const {
+  DCHECK(text_granularity == TextGranularity::kWord ||
+         text_granularity == TextGranularity::kSentence)
+      << "Only word and sentence granularities are supported for now";
+
+  const VisibleSelection& selection = ComputeVisibleSelectionInDOMTree();
+  // TODO(editing-dev): The use of VisibleSelection needs to be audited. See
+  // http://crbug.com/657237 for more details.
+  if (!selection.IsCaret()) {
+    return EphemeralRange();
+  }
+  const Position position = selection.Start();
+  static const WordSide kWordSideList[2] = {kNextWordIfOnBoundary,
+                                            kPreviousWordIfOnBoundary};
+  for (WordSide word_side : kWordSideList) {
+    Position start;
+    Position end;
+    // Use word granularity by default unless sentence granularity is explicitly
+    // requested.
+    if (text_granularity == TextGranularity::kSentence) {
+      start = StartOfSentencePosition(position);
+      end = EndOfSentence(position, SentenceTrailingSpaceBehavior::kOmitSpace)
+                .GetPosition();
+    } else {
+      start = StartOfWordPosition(position, word_side);
+      end = EndOfWordPosition(position, word_side);
+    }
+
+    // TODO(editing-dev): |StartOfWord()| and |EndOfWord()| should not make null
+    // for non-null parameter.
+    // See http://crbug.com/872443
+    if (start.IsNull() || end.IsNull()) {
+      continue;
+    }
+
+    if (start > end) {
+      // Since word boundaries are computed on flat tree, they can be reversed
+      // when mapped back to DOM.
+      std::swap(start, end);
+    }
+
+    String text = PlainText(EphemeralRange(start, end));
+    if (text.IsEmpty() || IsSeparator(text.CharacterStartingAt(0))) {
+      continue;
+    }
+
+    return EphemeralRange(start, end);
+  }
+
+  return EphemeralRange();
+}
+
 }  // namespace blink
 
 #if DCHECK_IS_ON()
diff --git a/third_party/blink/renderer/core/editing/frame_selection.h b/third_party/blink/renderer/core/editing/frame_selection.h
index d97ed56..f614f06 100644
--- a/third_party/blink/renderer/core/editing/frame_selection.h
+++ b/third_party/blink/renderer/core/editing/frame_selection.h
@@ -32,6 +32,7 @@
 #include "base/dcheck_is_on.h"
 #include "third_party/blink/renderer/core/core_export.h"
 #include "third_party/blink/renderer/core/dom/synchronous_mutation_observer.h"
+#include "third_party/blink/renderer/core/editing/ephemeral_range.h"
 #include "third_party/blink/renderer/core/editing/forward.h"
 #include "third_party/blink/renderer/core/editing/set_selection_options.h"
 #include "third_party/blink/renderer/core/scroll/scroll_alignment.h"
@@ -258,6 +259,18 @@
                          HandleVisibility handle_visibility,
                          ContextMenuVisibility context_menu_visibility);
 
+  // Returns the range corresponding to a word selection around the caret.
+  // Returns a null range if the selection failed, either because the current
+  // selection was not a caret or if a word selection could not be made.
+  EphemeralRange GetWordSelectionRangeAroundCaret() const;
+
+  // Returns the range corresponding to a |text_granularity| selection around
+  // the caret. Returns a null range if the selection failed, either because
+  // the current selection was not a caret or if a |text_granularity| selection
+  // could not be made.
+  EphemeralRange GetSelectionRangeAroundCaretForTesting(
+      TextGranularity text_granularity) const;
+
 #if DCHECK_IS_ON()
   void ShowTreeForThis() const;
 #endif
@@ -327,6 +340,13 @@
   void NodeChildrenWillBeRemoved(ContainerNode&) final;
   void NodeWillBeRemoved(Node&) final;
 
+  // Returns the range corresponding to a |text_granularity| selection around
+  // the caret. Returns a null range if the selection failed, either because
+  // the current selection was not a caret or if a |text_granularity| selection
+  // could not be made.
+  EphemeralRange GetSelectionRangeAroundCaret(
+      TextGranularity text_granularity) const;
+
   Member<LocalFrame> frame_;
   const Member<LayoutSelection> layout_selection_;
   const Member<SelectionEditor> selection_editor_;
diff --git a/third_party/blink/renderer/core/editing/frame_selection_test.cc b/third_party/blink/renderer/core/editing/frame_selection_test.cc
index 8e60a15..9da8b02 100644
--- a/third_party/blink/renderer/core/editing/frame_selection_test.cc
+++ b/third_party/blink/renderer/core/editing/frame_selection_test.cc
@@ -7,11 +7,13 @@
 #include <memory>
 #include "base/memory/scoped_refptr.h"
 #include "testing/gtest/include/gtest/gtest.h"
+#include "third_party/blink/public/web/web_range.h"
 #include "third_party/blink/renderer/core/dom/document.h"
 #include "third_party/blink/renderer/core/dom/element.h"
 #include "third_party/blink/renderer/core/dom/text.h"
 #include "third_party/blink/renderer/core/editing/ephemeral_range.h"
 #include "third_party/blink/renderer/core/editing/frame_caret.h"
+#include "third_party/blink/renderer/core/editing/iterators/text_iterator.h"
 #include "third_party/blink/renderer/core/editing/selection_controller.h"
 #include "third_party/blink/renderer/core/editing/selection_modifier.h"
 #include "third_party/blink/renderer/core/editing/selection_template.h"
@@ -67,11 +69,19 @@
   // Returns if a word is is selected.
   bool SelectWordAroundPosition(const Position&);
 
+  // Returns whether the selection was accomplished.
+  bool SelectWordAroundCaret();
+
+  // Returns whether the selection was accomplished.
+  bool SelectSentenceAroundCaret();
+
   // Places the caret on the |text| at |selection_index|.
-  void ResetAndPlaceCaret(Text* text, int selection_index) {
+  void ResetAndPlaceCaret(Text* text, size_t selection_index) {
+    ASSERT_LE(selection_index,
+              static_cast<size_t>(std::numeric_limits<int>::max()));
     Selection().SetSelectionAndEndTyping(
         SelectionInDOMTree::Builder()
-            .Collapse(Position(text, selection_index))
+            .Collapse(Position(text, static_cast<int>(selection_index)))
             .Build());
   }
 
@@ -107,6 +117,18 @@
   return Selection().SelectWordAroundCaret();
 }
 
+bool FrameSelectionTest::SelectWordAroundCaret() {
+  return Selection().SelectAroundCaret(TextGranularity::kWord,
+                                       HandleVisibility::kNotVisible,
+                                       ContextMenuVisibility::kNotVisible);
+}
+
+bool FrameSelectionTest::SelectSentenceAroundCaret() {
+  return Selection().SelectAroundCaret(TextGranularity::kSentence,
+                                       HandleVisibility::kNotVisible,
+                                       ContextMenuVisibility::kNotVisible);
+}
+
 TEST_F(FrameSelectionTest, FirstEphemeralRangeOf) {
   SetBodyContent("<div id=sample>0123456789</div>abc");
   Element* const sample = GetDocument().getElementById("sample");
@@ -206,6 +228,41 @@
   EXPECT_EQ_SELECTED_TEXT("baz");
 }
 
+TEST_F(FrameSelectionTest, SelectAroundCaret_Word) {
+  Text* text = AppendTextNode("This is a sentence.");
+  UpdateAllLifecyclePhasesForTest();
+
+  // Beginning of text: |This is a sentence.
+  ResetAndPlaceCaret(text, strlen(""));
+  EXPECT_TRUE(SelectWordAroundCaret());
+  EXPECT_EQ_SELECTED_TEXT("This");
+
+  // Beginning of a word: This |is a sentence.
+  ResetAndPlaceCaret(text, strlen("This "));
+  EXPECT_TRUE(SelectWordAroundCaret());
+  EXPECT_EQ_SELECTED_TEXT("is");
+
+  // Somewhere in a word: This is a s|entence.
+  ResetAndPlaceCaret(text, strlen("This is a s"));
+  EXPECT_TRUE(SelectWordAroundCaret());
+  EXPECT_EQ_SELECTED_TEXT("sentence");
+
+  // End a word: This| is a sentence.
+  ResetAndPlaceCaret(text, strlen("This"));
+  EXPECT_TRUE(SelectWordAroundCaret());
+  EXPECT_EQ_SELECTED_TEXT("This");
+
+  // End a word with punctuation: This is a sentence|.
+  ResetAndPlaceCaret(text, strlen("This is a sentence"));
+  EXPECT_TRUE(SelectWordAroundCaret());
+  EXPECT_EQ_SELECTED_TEXT("sentence");
+
+  // End a word after punctuation: This is a sentence.|
+  ResetAndPlaceCaret(text, strlen("This is a sentence."));
+  EXPECT_FALSE(SelectWordAroundCaret());
+  EXPECT_EQ_SELECTED_TEXT("");
+}
+
 TEST_F(FrameSelectionTest, SelectAroundCaret_Sentence) {
   Text* text = AppendTextNode(
       "This is the first sentence. This is the second sentence. This is the "
@@ -214,44 +271,34 @@
 
   // This is the first sentence. Th|is is the second sentence. This is the last
   // sentence.
-  ResetAndPlaceCaret(text, 30);
-  EXPECT_TRUE(Selection().SelectAroundCaret(
-      TextGranularity::kSentence, HandleVisibility::kNotVisible,
-      ContextMenuVisibility::kNotVisible));
+  ResetAndPlaceCaret(text, strlen("This is the first sentence. Th"));
+  EXPECT_TRUE(SelectSentenceAroundCaret());
   EXPECT_EQ_SELECTED_TEXT("This is the second sentence.");
 
   // This is the first sentence|. This is the second sentence. This is the last
   // sentence.
-  ResetAndPlaceCaret(text, 26);
-  EXPECT_TRUE(Selection().SelectAroundCaret(
-      TextGranularity::kSentence, HandleVisibility::kNotVisible,
-      ContextMenuVisibility::kNotVisible));
+  ResetAndPlaceCaret(text, strlen("This is the first sentence"));
+  EXPECT_TRUE(SelectSentenceAroundCaret());
   EXPECT_EQ_SELECTED_TEXT("This is the first sentence.");
 
   // This is the first sentence.| This is the second sentence. This is the last
   // sentence.
-  ResetAndPlaceCaret(text, 27);
-  EXPECT_TRUE(Selection().SelectAroundCaret(
-      TextGranularity::kSentence, HandleVisibility::kNotVisible,
-      ContextMenuVisibility::kNotVisible));
+  ResetAndPlaceCaret(text, strlen("This is the first sentence."));
+  EXPECT_TRUE(SelectSentenceAroundCaret());
   EXPECT_EQ_SELECTED_TEXT(
       "This is the first sentence. This is the second sentence.");
 
   // This is the first sentence. |This is the second sentence. This is the last
   // sentence.
-  ResetAndPlaceCaret(text, 28);
-  EXPECT_TRUE(Selection().SelectAroundCaret(
-      TextGranularity::kSentence, HandleVisibility::kNotVisible,
-      ContextMenuVisibility::kNotVisible));
+  ResetAndPlaceCaret(text, strlen("This is the first sentence. "));
+  EXPECT_TRUE(SelectSentenceAroundCaret());
   EXPECT_EQ_SELECTED_TEXT(
       "This is the first sentence. This is the second sentence.");
 
   // This is the first sentence. T|his is the second sentence. This is the last
   // sentence.
-  ResetAndPlaceCaret(text, 29);
-  EXPECT_TRUE(Selection().SelectAroundCaret(
-      TextGranularity::kSentence, HandleVisibility::kNotVisible,
-      ContextMenuVisibility::kNotVisible));
+  ResetAndPlaceCaret(text, strlen("This is the first sentence. T"));
+  EXPECT_TRUE(SelectSentenceAroundCaret());
   EXPECT_EQ_SELECTED_TEXT("This is the second sentence.");
 }
 
@@ -360,6 +407,117 @@
   EXPECT_TRUE(HasContextMenu());
 }
 
+TEST_F(FrameSelectionTest, GetSelectionRangeAroundCaret_Word) {
+  Text* text = AppendTextNode("This is a sentence.");
+  UpdateAllLifecyclePhasesForTest();
+
+  // Beginning of a text: |This is a sentence.
+  ResetAndPlaceCaret(text, strlen(""));
+  EphemeralRange range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("This", PlainText(range));
+
+  // Beginning of a word: This |is a sentence.
+  ResetAndPlaceCaret(text, strlen("This "));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("is", PlainText(range));
+
+  // Somewhere in a word: This is a s|entence.
+  ResetAndPlaceCaret(text, strlen("This is a s"));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("sentence", PlainText(range));
+
+  // End a word: This| is a sentence.
+  ResetAndPlaceCaret(text, strlen("This"));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("This", PlainText(range));
+
+  // End a word before punctuation: This is a sentence|.
+  ResetAndPlaceCaret(text, strlen("This is a sentence"));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("sentence", PlainText(range));
+
+  // End of text after punctuation (no selection): This is a sentence.|
+  ResetAndPlaceCaret(text, strlen("This is a sentence."));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("", PlainText(range));
+
+  // End of text without punctuation: This is a sentence|
+  ResetAndPlaceCaret(text, strlen("This is a sentence"));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("sentence", PlainText(range));
+
+  // After punctuation before whitespace (no selection): A word.| Another.
+  text = AppendTextNode("A word. Another.");
+  UpdateAllLifecyclePhasesForTest();
+  ResetAndPlaceCaret(text, strlen("A word."));
+  range = Selection().GetWordSelectionRangeAroundCaret();
+  EXPECT_EQ("", PlainText(range));
+}
+
+TEST_F(FrameSelectionTest, GetSelectionRangeAroundCaret_Sentence) {
+  Text* text = AppendTextNode(
+      "This is the first sentence. This is the second sentence. This is the "
+      "last sentence.");
+  UpdateAllLifecyclePhasesForTest();
+
+  // |This is the first sentence. This is the second sentence. This is the last
+  // sentence.
+  ResetAndPlaceCaret(text, strlen(""));
+  EphemeralRange range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the first sentence.", PlainText(range));
+
+  // This is the first sentence|. This is the second sentence. This is the last
+  // sentence.
+  ResetAndPlaceCaret(text, strlen("This is the first sentence"));
+  range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the first sentence.", PlainText(range));
+
+  // TODO(crbug.com/1273856): This should only select one sentence.
+  // This is the first sentence.| This is the second sentence. This is the last
+  // sentence.
+  ResetAndPlaceCaret(text, strlen("This is the first sentence."));
+  range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the first sentence. This is the second sentence.",
+            PlainText(range));
+
+  // TODO(crbug.com/1273856): This should only select one sentence.
+  // This is the first sentence. |This is the second sentence. This is the last
+  // sentence.
+  ResetAndPlaceCaret(text, strlen("This is the first sentence. "));
+  range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the first sentence. This is the second sentence.",
+            PlainText(range));
+
+  // This is the first sentence. Th|is is the second sentence. This is the last
+  // sentence.
+  ResetAndPlaceCaret(text, strlen("This is the first sentence. Th"));
+  range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the second sentence.", PlainText(range));
+
+  // This is the first sentence. This is the second sentence. This is the last
+  // sentence|.
+  ResetAndPlaceCaret(text,
+                     strlen("This is the first sentence. This is the second "
+                            "sentence. This is the last sentence"));
+  range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the last sentence.", PlainText(range));
+
+  // This is the first sentence. This is the second sentence. This is the last
+  // sentence.|
+  ResetAndPlaceCaret(text,
+                     strlen("This is the first sentence. This is the second "
+                            "sentence. This is the last sentence."));
+  range = Selection().GetSelectionRangeAroundCaretForTesting(
+      TextGranularity::kSentence);
+  EXPECT_EQ("This is the last sentence.", PlainText(range));
+}
+
 TEST_F(FrameSelectionTest, ModifyExtendWithFlatTree) {
   SetBodyContent("<span id=host></span>one");
   SetShadowContent("two<slot></slot>", "host");
diff --git a/third_party/blink/renderer/core/frame/find_in_page.cc b/third_party/blink/renderer/core/frame/find_in_page.cc
index 11bc63d..22c97f56 100644
--- a/third_party/blink/renderer/core/frame/find_in_page.cc
+++ b/third_party/blink/renderer/core/frame/find_in_page.cc
@@ -40,7 +40,6 @@
 #include "third_party/blink/renderer/core/editing/finder/text_finder.h"
 #include "third_party/blink/renderer/core/frame/web_local_frame_impl.h"
 #include "third_party/blink/renderer/core/layout/layout_view.h"
-#include "third_party/blink/renderer/core/page/chrome_client.h"
 #include "third_party/blink/renderer/core/page/focus_controller.h"
 #include "third_party/blink/renderer/core/page/page.h"
 
@@ -343,23 +342,13 @@
                    : mojom::blink::FindMatchUpdateType::kMoreUpdatesComing);
 }
 
-void FindInPage::ReportFindInPageSelection(
-    int request_id,
-    int active_match_ordinal,
-    const gfx::Rect& local_selection_rect,
-    bool final_update) {
+void FindInPage::ReportFindInPageSelection(int request_id,
+                                           int active_match_ordinal,
+                                           const gfx::Rect& selection_rect,
+                                           bool final_update) {
   // In tests, |client_| might not be set.
   if (!client_)
     return;
-
-  float device_scale_factor = 1.f;
-  if (LocalFrame* local_frame = frame_->GetFrame()) {
-    device_scale_factor =
-        local_frame->GetPage()->GetChromeClient().WindowToViewportScalar(
-            local_frame, 1.0f);
-  }
-  auto selection_rect = gfx::ScaleToEnclosingRect(local_selection_rect,
-                                                  1.f / device_scale_factor);
   client_->SetActiveMatch(
       request_id, selection_rect, active_match_ordinal,
       final_update ? mojom::blink::FindMatchUpdateType::kFinalUpdate
diff --git a/third_party/blink/renderer/core/frame/web_frame_widget_impl.cc b/third_party/blink/renderer/core/frame/web_frame_widget_impl.cc
index d55d1e3..25e256a 100644
--- a/third_party/blink/renderer/core/frame/web_frame_widget_impl.cc
+++ b/third_party/blink/renderer/core/frame/web_frame_widget_impl.cc
@@ -3691,32 +3691,57 @@
     return;
   }
 
-  // TODO(crbug.com/1278134): Calculate extended adjustments.
-  bool did_select = false;
   int extended_start_adjust = 0;
   int extended_end_adjust = 0;
+  int word_start_adjust = 0;
+  int word_end_adjust = 0;
   blink::WebRange initial_range = focused_frame->SelectionRange();
   SetHandlingInputEvent(true);
-  if (!initial_range.IsNull()) {
-    did_select = focused_frame->SelectAroundCaret(
-        granularity, should_show_handle, should_show_context_menu);
-  }
 
-  if (!did_select) {
+  if (initial_range.IsNull()) {
     std::move(callback).Run(std::move(nullptr));
     return;
   }
 
-  blink::WebRange adjusted_range = focused_frame->SelectionRange();
-  DCHECK(!adjusted_range.IsNull());
+  // If the requested granularity is not word, still calculate the hypothetical
+  // word selection offsets. This is needed for contextual search to support
+  // legacy semantics for the word that was tapped.
+  blink::WebRange word_range;
+  if (granularity != mojom::blink::SelectionGranularity::kWord) {
+    word_range = focused_frame->GetWordSelectionRangeAroundCaret();
+  }
+
+  // Select around the caret at the specified |granularity|.
+  if (!focused_frame->SelectAroundCaret(granularity, should_show_handle,
+                                        should_show_context_menu)) {
+    std::move(callback).Run(std::move(nullptr));
+    return;
+  }
+
+  blink::WebRange extended_range = focused_frame->SelectionRange();
+  DCHECK(!extended_range.IsNull());
   extended_start_adjust =
-      adjusted_range.StartOffset() - initial_range.StartOffset();
-  extended_end_adjust = adjusted_range.EndOffset() - initial_range.EndOffset();
+      extended_range.StartOffset() - initial_range.StartOffset();
+  extended_end_adjust = extended_range.EndOffset() - initial_range.EndOffset();
+
+  if (granularity == mojom::blink::SelectionGranularity::kWord) {
+    // Since the requested granularity was word, simply set the word offset
+    // to be the same as the extended offset values.
+    word_start_adjust = extended_start_adjust;
+    word_end_adjust = extended_end_adjust;
+  } else {
+    // Calculate the word offset compared to the initial selection (caret).
+    DCHECK(!word_range.IsNull());
+    word_start_adjust = word_range.StartOffset() - initial_range.StartOffset();
+    word_end_adjust = word_range.EndOffset() - initial_range.EndOffset();
+  }
 
   SetHandlingInputEvent(false);
   auto result = mojom::blink::SelectAroundCaretResult::New();
   result->extended_start_adjust = extended_start_adjust;
   result->extended_end_adjust = extended_end_adjust;
+  result->word_start_adjust = word_start_adjust;
+  result->word_end_adjust = word_end_adjust;
   std::move(callback).Run(std::move(result));
 }
 #endif
diff --git a/third_party/blink/renderer/core/frame/web_local_frame_impl.cc b/third_party/blink/renderer/core/frame/web_local_frame_impl.cc
index 79ec0d0d..a63f132 100644
--- a/third_party/blink/renderer/core/frame/web_local_frame_impl.cc
+++ b/third_party/blink/renderer/core/frame/web_local_frame_impl.cc
@@ -1429,6 +1429,11 @@
                                : ContextMenuVisibility ::kNotVisible);
 }
 
+EphemeralRange WebLocalFrameImpl::GetWordSelectionRangeAroundCaret() const {
+  TRACE_EVENT0("blink", "WebLocalFrameImpl::getWordSelectionRangeAroundCaret");
+  return GetFrame()->Selection().GetWordSelectionRangeAroundCaret();
+}
+
 void WebLocalFrameImpl::SelectRange(const gfx::Point& base_in_viewport,
                                     const gfx::Point& extent_in_viewport) {
   MoveRangeSelection(base_in_viewport, extent_in_viewport);
@@ -2894,12 +2899,4 @@
   has_scrolled_focused_editable_node_into_rect_ = false;
 }
 
-bool WebLocalFrameImpl::ServiceWorkerSubresourceFilterEnabled() {
-  if (GetFrame() && GetFrame()->GetDocument()) {
-    return RuntimeEnabledFeatures::ServiceWorkerSubresourceFilterEnabled(
-        GetFrame()->GetDocument()->GetExecutionContext());
-  }
-  return false;
-}
-
 }  // namespace blink
diff --git a/third_party/blink/renderer/core/frame/web_local_frame_impl.h b/third_party/blink/renderer/core/frame/web_local_frame_impl.h
index 45c6211..f22f5a2 100644
--- a/third_party/blink/renderer/core/frame/web_local_frame_impl.h
+++ b/third_party/blink/renderer/core/frame/web_local_frame_impl.h
@@ -218,6 +218,7 @@
   bool SelectAroundCaret(mojom::blink::SelectionGranularity granularity,
                          bool should_show_handle,
                          bool should_show_context_menu);
+  EphemeralRange GetWordSelectionRangeAroundCaret() const;
   void SelectRange(const gfx::Point& base, const gfx::Point& extent) override;
   void SelectRange(const WebRange&,
                    HandleVisibilityBehavior,
@@ -335,7 +336,6 @@
   void UpdateCurrentHistoryItem() override;
   PageState CurrentHistoryItemToPageState() override;
   const WebHistoryItem& GetCurrentHistoryItem() const override;
-  bool ServiceWorkerSubresourceFilterEnabled() override;
   void SetLocalStorageArea(
       CrossVariantMojoRemote<mojom::StorageAreaInterfaceBase>
           local_storage_area) override;
diff --git a/third_party/blink/renderer/core/html/canvas/canvas_rendering_context.h b/third_party/blink/renderer/core/html/canvas/canvas_rendering_context.h
index d8bbec9..e212237 100644
--- a/third_party/blink/renderer/core/html/canvas/canvas_rendering_context.h
+++ b/third_party/blink/renderer/core/html/canvas/canvas_rendering_context.h
@@ -287,9 +287,9 @@
     return CanvasColorParams();
   }
 
- private:
-  void Dispose();
+  virtual void Dispose();
 
+ private:
   Member<CanvasRenderingContextHost> host_;
   CanvasColorParams color_params_;
   CanvasContextCreationAttributesCore creation_attributes_;
diff --git a/third_party/blink/renderer/core/html/canvas/html_canvas_element.cc b/third_party/blink/renderer/core/html/canvas/html_canvas_element.cc
index 2e45c9dc..b12205b 100644
--- a/third_party/blink/renderer/core/html/canvas/html_canvas_element.cc
+++ b/third_party/blink/renderer/core/html/canvas/html_canvas_element.cc
@@ -40,7 +40,6 @@
 #include "base/numerics/checked_math.h"
 #include "base/numerics/safe_conversions.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "services/metrics/public/cpp/ukm_recorder.h"
 #include "services/metrics/public/cpp/ukm_source_id.h"
 #include "third_party/blink/public/common/features.h"
diff --git a/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_multi_line.cc b/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_multi_line.cc
index 4469ef6..19fb387 100644
--- a/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_multi_line.cc
+++ b/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_multi_line.cc
@@ -34,20 +34,19 @@
     const HitTestLocation& hit_test_location,
     const PhysicalOffset& accumulated_offset,
     HitTestAction hit_test_action) {
-  if (!LayoutNGBlockFlow::NodeAtPoint(result, hit_test_location,
-                                      accumulated_offset, hit_test_action))
-    return false;
+  bool stop_hit_testing = LayoutNGBlockFlow::NodeAtPoint(
+      result, hit_test_location, accumulated_offset, hit_test_action);
 
   const LayoutObject* stop_node = result.GetHitTestRequest().GetStopNode();
   if (stop_node && stop_node->NodeForHitTest() == result.InnerNode())
-    return true;
+    return stop_hit_testing;
 
   HTMLElement* inner_editor = InnerEditorElement();
   if (result.InnerNode() == GetNode() || result.InnerNode() == inner_editor) {
     LayoutTextControl::HitInnerEditorElement(
         *this, *inner_editor, result, hit_test_location, accumulated_offset);
   }
-  return true;
+  return stop_hit_testing;
 }
 
 }  // namespace blink
diff --git a/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_single_line.cc b/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_single_line.cc
index b425de0..f3157e6 100644
--- a/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_single_line.cc
+++ b/third_party/blink/renderer/core/layout/ng/layout_ng_text_control_single_line.cc
@@ -49,13 +49,14 @@
     const PhysicalOffset& accumulated_offset,
     HitTestAction hit_test_action) {
   NOT_DESTROYED();
-  if (!LayoutNGBlockFlow::NodeAtPoint(result, hit_test_location,
-                                      accumulated_offset, hit_test_action))
-    return false;
+  bool stop_hit_testing = LayoutNGBlockFlow::NodeAtPoint(
+      result, hit_test_location, accumulated_offset, hit_test_action);
 
   const LayoutObject* stop_node = result.GetHitTestRequest().GetStopNode();
-  if (stop_node && stop_node->NodeForHitTest() == result.InnerNode())
-    return true;
+  if (!result.InnerNode() ||
+      (stop_node && stop_node->NodeForHitTest() == result.InnerNode())) {
+    return stop_hit_testing;
+  }
 
   // Say that we hit the inner text element if
   //  - we hit a node inside the inner editor element,
@@ -77,7 +78,7 @@
     LayoutTextControl::HitInnerEditorElement(
         *this, *inner_editor, result, hit_test_location, accumulated_offset);
   }
-  return true;
+  return stop_hit_testing;
 }
 
 bool LayoutNGTextControlSingleLine::AllowsNonVisibleOverflow() const {
diff --git a/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.cc b/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.cc
index 9deba9e3..ebe6556 100644
--- a/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.cc
+++ b/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.cc
@@ -40,6 +40,11 @@
   image_layer_bridge_->Dispose();
 }
 
+void ImageBitmapRenderingContextBase::Dispose() {
+  Stop();
+  CanvasRenderingContext::Dispose();
+}
+
 void ImageBitmapRenderingContextBase::ResetInternalBitmapToBlackTransparent(
     int width,
     int height) {
diff --git a/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.h b/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.h
index efbb8b58..7e38191 100644
--- a/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.h
+++ b/third_party/blink/renderer/modules/canvas/imagebitmap/image_bitmap_rendering_context_base.h
@@ -64,6 +64,8 @@
   bool IsPaintable() const final;
 
  protected:
+  void Dispose() override;
+
   Member<ImageLayerBridge> image_layer_bridge_;
 
   // This function resets the internal image resource to a image of the same
diff --git a/third_party/blink/renderer/modules/credentialmanager/credentials_container.cc b/third_party/blink/renderer/modules/credentialmanager/credentials_container.cc
index 93abfc8d..0be83f1 100644
--- a/third_party/blink/renderer/modules/credentialmanager/credentials_container.cc
+++ b/third_party/blink/renderer/modules/credentialmanager/credentials_container.cc
@@ -609,7 +609,7 @@
   }
   resolver->Resolve(MakeGarbageCollected<PublicKeyCredential>(
       credential->info->id, raw_id, authenticator_response,
-      credential->has_transport, credential->transport, extension_outputs));
+      credential->authenticator_attachment, extension_outputs));
 }
 bool IsForPayment(const CredentialCreationOptions* options,
                   ExecutionContext* context) {
@@ -725,8 +725,8 @@
     resolver->Resolve(MakeGarbageCollected<PublicKeyCredential>(
         credential->info->id,
         VectorToDOMArrayBuffer(std::move(credential->info->raw_id)),
-        authenticator_response, credential->has_transport,
-        credential->transport, extension_outputs));
+        authenticator_response, credential->authenticator_attachment,
+        extension_outputs));
     return;
   }
   DCHECK(!credential);
diff --git a/third_party/blink/renderer/modules/credentialmanager/public_key_credential.cc b/third_party/blink/renderer/modules/credentialmanager/public_key_credential.cc
index 44378a4..e99f340 100644
--- a/third_party/blink/renderer/modules/credentialmanager/public_key_credential.cc
+++ b/third_party/blink/renderer/modules/credentialmanager/public_key_credential.cc
@@ -6,6 +6,7 @@
 
 #include <utility>
 
+#include "third_party/blink/public/mojom/webauthn/authenticator.mojom-shared.h"
 #include "third_party/blink/renderer/bindings/core/v8/script_promise.h"
 #include "third_party/blink/renderer/bindings/core/v8/script_promise_resolver.h"
 #include "third_party/blink/renderer/core/dom/dom_exception.h"
@@ -27,24 +28,32 @@
     bool available) {
   scoped_resolver->Release()->Resolve(available);
 }
+
+absl::optional<std::string> AuthenticatorAttachmentToString(
+    mojom::blink::AuthenticatorAttachment authenticator_attachment) {
+  switch (authenticator_attachment) {
+    case mojom::blink::AuthenticatorAttachment::PLATFORM:
+      return "platform";
+    case mojom::blink::AuthenticatorAttachment::CROSS_PLATFORM:
+      return "cross-platform";
+    case mojom::blink::AuthenticatorAttachment::NO_PREFERENCE:
+      return absl::nullopt;
+  }
+}
 }  // namespace
 
 PublicKeyCredential::PublicKeyCredential(
     const String& id,
     DOMArrayBuffer* raw_id,
     AuthenticatorResponse* response,
-    bool has_transport,
-    mojom::AuthenticatorTransport transport,
+    mojom::blink::AuthenticatorAttachment authenticator_attachment,
     const AuthenticationExtensionsClientOutputs* extension_outputs,
     const String& type)
     : Credential(id, type.IsEmpty() ? kPublicKeyCredentialType : type),
       raw_id_(raw_id),
       response_(response),
       authenticator_attachment_(
-          has_transport ? (transport == mojom::AuthenticatorTransport::INTERNAL
-                               ? absl::make_optional("platform")
-                               : absl::make_optional("cross-platform"))
-                        : absl::nullopt),
+          AuthenticatorAttachmentToString(authenticator_attachment)),
       extension_outputs_(extension_outputs) {}
 
 ScriptPromise
diff --git a/third_party/blink/renderer/modules/credentialmanager/public_key_credential.h b/third_party/blink/renderer/modules/credentialmanager/public_key_credential.h
index 55b44cd..fb49a8f 100644
--- a/third_party/blink/renderer/modules/credentialmanager/public_key_credential.h
+++ b/third_party/blink/renderer/modules/credentialmanager/public_key_credential.h
@@ -6,7 +6,6 @@
 #define THIRD_PARTY_BLINK_RENDERER_MODULES_CREDENTIALMANAGER_PUBLIC_KEY_CREDENTIAL_H_
 
 #include "third_party/abseil-cpp/absl/types/optional.h"
-#include "third_party/blink/public/mojom/webauthn/authenticator.mojom-shared.h"
 #include "third_party/blink/renderer/bindings/modules/v8/v8_authentication_extensions_client_outputs.h"
 #include "third_party/blink/renderer/core/typed_arrays/dom_array_buffer.h"
 #include "third_party/blink/renderer/modules/credentialmanager/authenticator_response.h"
@@ -17,8 +16,11 @@
 
 namespace blink {
 
+namespace mojom {
+enum class AuthenticatorAttachment;
+}
+
 class AuthenticatorResponse;
-class AuthenticatorTransport;
 class ScriptPromise;
 class ScriptState;
 
@@ -30,8 +32,7 @@
       const String& id,
       DOMArrayBuffer* raw_id,
       AuthenticatorResponse*,
-      bool has_transport,
-      mojom::AuthenticatorTransport transport,
+      mojom::AuthenticatorAttachment authenticator_attachment,
       const AuthenticationExtensionsClientOutputs* extension_outputs,
       const String& type = "");
 
diff --git a/third_party/blink/renderer/modules/mediastream/BUILD.gn b/third_party/blink/renderer/modules/mediastream/BUILD.gn
index 736cecf..5b24736 100644
--- a/third_party/blink/renderer/modules/mediastream/BUILD.gn
+++ b/third_party/blink/renderer/modules/mediastream/BUILD.gn
@@ -107,7 +107,6 @@
   deps = [
     "//build:chromecast_buildflags",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//media/capture/mojom:image_capture_blink",
     "//media/webrtc",
     "//services/viz/public/cpp/gpu:gpu",
diff --git a/third_party/blink/renderer/modules/mediastream/media_constraints_impl.cc b/third_party/blink/renderer/modules/mediastream/media_constraints_impl.cc
index d56667d..31c1e51 100644
--- a/third_party/blink/renderer/modules/mediastream/media_constraints_impl.cc
+++ b/third_party/blink/renderer/modules/mediastream/media_constraints_impl.cc
@@ -30,7 +30,7 @@
 
 #include "third_party/blink/renderer/modules/mediastream/media_constraints_impl.h"
 
-#include "build/os_buildflags.h"
+#include "build/build_config.h"
 #include "third_party/blink/public/platform/web_string.h"
 #include "third_party/blink/renderer/bindings/core/v8/array_value.h"
 #include "third_party/blink/renderer/bindings/core/v8/dictionary.h"
diff --git a/third_party/blink/renderer/modules/payments/payment_response.cc b/third_party/blink/renderer/modules/payments/payment_response.cc
index 5a7a284d..1389620 100644
--- a/third_party/blink/renderer/modules/payments/payment_response.cc
+++ b/third_party/blink/renderer/modules/payments/payment_response.cc
@@ -42,8 +42,8 @@
         secure_payment_confirmation->credential_info->id,
         DOMArrayBuffer::Create(static_cast<const void*>(info->raw_id.data()),
                                info->raw_id.size()),
-        authenticator_response, secure_payment_confirmation->has_transport,
-        secure_payment_confirmation->transport,
+        authenticator_response,
+        secure_payment_confirmation->authenticator_attachment,
         AuthenticationExtensionsClientOutputs::Create());
     return result->Wrap(script_state).ToLocalChecked();
   }
diff --git a/third_party/blink/renderer/modules/webcodecs/BUILD.gn b/third_party/blink/renderer/modules/webcodecs/BUILD.gn
index 4053a4a..85d2cf0 100644
--- a/third_party/blink/renderer/modules/webcodecs/BUILD.gn
+++ b/third_party/blink/renderer/modules/webcodecs/BUILD.gn
@@ -81,7 +81,6 @@
     "webcodecs_logger.h",
   ]
   deps = [
-    "//build:os_buildflags",
     "//media",
     "//media/mojo:buildflags",
     "//media/mojo/clients",
diff --git a/third_party/blink/renderer/modules/webcodecs/video_encoder.cc b/third_party/blink/renderer/modules/webcodecs/video_encoder.cc
index ff1a8bd..fd4d78a4 100644
--- a/third_party/blink/renderer/modules/webcodecs/video_encoder.cc
+++ b/third_party/blink/renderer/modules/webcodecs/video_encoder.cc
@@ -17,7 +17,6 @@
 #include "base/trace_event/common/trace_event_common.h"
 #include "base/trace_event/trace_event.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "components/viz/common/gpu/raster_context_provider.h"
 #include "gpu/GLES2/gl2extchromium.h"
 #include "gpu/command_buffer/client/raster_interface.h"
diff --git a/third_party/blink/renderer/platform/BUILD.gn b/third_party/blink/renderer/platform/BUILD.gn
index 72bd14c..2896e16 100644
--- a/third_party/blink/renderer/platform/BUILD.gn
+++ b/third_party/blink/renderer/platform/BUILD.gn
@@ -1662,7 +1662,6 @@
     "//base/allocator:buildflags",
     "//build:chromecast_buildflags",
     "//build:chromeos_buildflags",
-    "//build:os_buildflags",
     "//cc/ipc",
     "//cc/mojo_embedder",
     "//components/paint_preview/common",
diff --git a/third_party/blink/renderer/platform/network/encoded_form_data.cc b/third_party/blink/renderer/platform/network/encoded_form_data.cc
index 665d291..d17dfda 100644
--- a/third_party/blink/renderer/platform/network/encoded_form_data.cc
+++ b/third_party/blink/renderer/platform/network/encoded_form_data.cc
@@ -121,13 +121,6 @@
   return result;
 }
 
-scoped_refptr<EncodedFormData> EncodedFormData::Create(
-    const Vector<char>& vector) {
-  scoped_refptr<EncodedFormData> result = Create();
-  result->AppendData(vector.data(), vector.size());
-  return result;
-}
-
 scoped_refptr<EncodedFormData> EncodedFormData::Copy() const {
   return base::AdoptRef(new EncodedFormData(*this));
 }
diff --git a/third_party/blink/renderer/platform/network/encoded_form_data.h b/third_party/blink/renderer/platform/network/encoded_form_data.h
index 79653a1..9b8e00f 100644
--- a/third_party/blink/renderer/platform/network/encoded_form_data.h
+++ b/third_party/blink/renderer/platform/network/encoded_form_data.h
@@ -103,7 +103,6 @@
   static scoped_refptr<EncodedFormData> Create();
   static scoped_refptr<EncodedFormData> Create(const void*, wtf_size_t);
   static scoped_refptr<EncodedFormData> Create(base::span<const char>);
-  static scoped_refptr<EncodedFormData> Create(const Vector<char>&);
   scoped_refptr<EncodedFormData> Copy() const;
   scoped_refptr<EncodedFormData> DeepCopy() const;
   ~EncodedFormData();
diff --git a/third_party/blink/renderer/platform/runtime_enabled_features.json5 b/third_party/blink/renderer/platform/runtime_enabled_features.json5
index fd09b455..c0cad641 100644
--- a/third_party/blink/renderer/platform/runtime_enabled_features.json5
+++ b/third_party/blink/renderer/platform/runtime_enabled_features.json5
@@ -2098,11 +2098,6 @@
       status: "experimental",
     },
     {
-      name: "ServiceWorkerSubresourceFilter",
-      origin_trial_feature_name: "ServiceWorkerSubresourceFilter",
-      status: "experimental",
-    },
-    {
       name: "SharedArrayBuffer",
     },
     {
diff --git a/third_party/blink/renderer/platform/storage/blink_storage_key_hash.h b/third_party/blink/renderer/platform/storage/blink_storage_key_hash.h
index 1fcf115..5c187b8 100644
--- a/third_party/blink/renderer/platform/storage/blink_storage_key_hash.h
+++ b/third_party/blink/renderer/platform/storage/blink_storage_key_hash.h
@@ -13,8 +13,8 @@
 namespace blink {
 
 // TODO(https://crbug.com/1199077): This needs to be re-implemented for the
-// actual StorageKey content once it's stable. Right now it's just a shim for
-// `SecurityOriginHash`.
+// actual StorageKey content once it's stable. Right now it's just (almost) a
+// shim for `SecurityOriginHash`.
 struct BlinkStorageKeyHash {
   STATIC_ONLY(BlinkStorageKeyHash);
 
@@ -28,8 +28,7 @@
   }
 
   static bool Equal(const BlinkStorageKey* a, const BlinkStorageKey* b) {
-    return SecurityOriginHash::Equal(a->GetSecurityOrigin(),
-                                     b->GetSecurityOrigin());
+    return *a == *b;
   }
 
   static bool Equal(const std::unique_ptr<const BlinkStorageKey>& a,
diff --git a/third_party/blink/renderer/platform/webrtc/webrtc_video_frame_adapter.cc b/third_party/blink/renderer/platform/webrtc/webrtc_video_frame_adapter.cc
index 80771ee..b019cb4a 100644
--- a/third_party/blink/renderer/platform/webrtc/webrtc_video_frame_adapter.cc
+++ b/third_party/blink/renderer/platform/webrtc/webrtc_video_frame_adapter.cc
@@ -13,7 +13,6 @@
 #include "base/synchronization/waitable_event.h"
 #include "base/threading/thread_restrictions.h"
 #include "build/build_config.h"
-#include "build/os_buildflags.h"
 #include "gpu/command_buffer/client/gpu_memory_buffer_manager.h"
 #include "gpu/command_buffer/client/raster_interface.h"
 #include "gpu/command_buffer/client/shared_image_interface.h"
diff --git a/third_party/blink/tools/blinkpy/web_tests/port/base.py b/third_party/blink/tools/blinkpy/web_tests/port/base.py
index 5095962..d6bd435 100644
--- a/third_party/blink/tools/blinkpy/web_tests/port/base.py
+++ b/third_party/blink/tools/blinkpy/web_tests/port/base.py
@@ -1459,7 +1459,6 @@
             ]
             clean_env['DISPLAY'] = self.host.environ.get('DISPLAY', ':1')
         if self.host.platform.is_mac():
-            clean_env['DYLD_LIBRARY_PATH'] = self._build_path()
             variables_to_copy += [
                 'HOME',
             ]
diff --git a/third_party/blink/web_tests/TestExpectations b/third_party/blink/web_tests/TestExpectations
index 4005bf61..a8febfb 100644
--- a/third_party/blink/web_tests/TestExpectations
+++ b/third_party/blink/web_tests/TestExpectations
@@ -3015,6 +3015,16 @@
 crbug.com/626703 [ Mac11 ] external/wpt/css/css-flexbox/abspos/flex-abspos-staticpos-align-self-006.html [ Failure ]
 
 # ====== New tests from wpt-importer added here ======
+crbug.com/626703 [ Linux ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 [ Mac10.12 ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 [ Mac10.13 ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 [ Mac10.14 ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 [ Mac10.15 ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 [ Mac11 ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 [ Win ] external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 external/wpt/css/css-color/tagged-images-004.html [ Failure ]
+crbug.com/626703 virtual/system-color-compute/external/wpt/css/css-color/tagged-images-003.html [ Failure ]
+crbug.com/626703 virtual/system-color-compute/external/wpt/css/css-color/tagged-images-004.html [ Failure ]
 crbug.com/626703 [ Mac10.13 ] virtual/plz-dedicated-worker/external/wpt/resource-timing/object-not-found-adds-entry.html [ Timeout ]
 crbug.com/626703 [ Mac11 ] external/wpt/css/css-color-adjust/inheritance.html [ Crash Failure ]
 crbug.com/626703 [ Mac11-arm64 ] external/wpt/fetch/private-network-access/fetch.window.html [ Timeout ]
@@ -6519,9 +6529,6 @@
 
 # DevTools roll
 crbug.com/1050549 http/tests/devtools/console/console-correct-suggestions.js [ Failure Pass ]
-crbug.com/1016266 http/tests/devtools/security/interstitial-sidebar.js [ Failure Pass ]
-crbug.com/1016266 http/tests/devtools/security/mixed-content-sidebar.js [ Failure Pass ]
-crbug.com/1016266 http/tests/devtools/console/console-format-classes.js [ Failure Pass ]
 
 # Flaky test
 crbug.com/1173439 http/tests/devtools/service-workers/service-worker-manager.js [ Pass Skip Timeout ]
@@ -7090,7 +7097,7 @@
 crbug.com/1201406 [ Mac11 ] fast/events/touch/gesture/touch-gesture-scroll-listbox.html [ Failure ]
 crbug.com/1201406 [ Mac11 ] http/tests/credentialmanager/credentialscontainer-create-from-nested-frame.html [ Crash Timeout ]
 crbug.com/1201406 [ Mac11 ] http/tests/credentialmanager/credentialscontainer-create-origins.html [ Crash Timeout ]
-crbug.com/1201406 [ Mac11 ] http/tests/credentialmanager/publickeycredential-same-origin-with-ancestors.html [ Crash Timeout ]
+crbug.com/1201406 http/tests/credentialmanager/publickeycredential-same-origin-with-ancestors.html [ Crash Pass Timeout ]
 crbug.com/1201406 [ Mac11 ] http/tests/credentialmanager/register-then-sign.html [ Crash Skip Timeout ]
 crbug.com/1201406 [ Mac11 ] http/tests/inspector-protocol/webauthn/webauthn-add-virtual-authenticator.js [ Crash Timeout ]
 crbug.com/1201406 [ Mac11 ] http/tests/inspector-protocol/webauthn/webauthn-clear-credentials.js [ Crash ]
@@ -7883,3 +7890,13 @@
 
 # Sheriff 2022-01-05
 crbug.com/1284572 [ Linux ] virtual/threaded/http/tests/devtools/isolated-code-cache/same-origin-module-test.js [ Failure Pass ]
+
+# Sheriff 2022-01-07
+crbug.com/1285348 [ Mac ] virtual/off-main-thread-css-paint/external/wpt/css/css-paint-api/hidpi/canvas-transform.https.html [ Failure Pass ]
+crbug.com/1285350 virtual/off-main-thread-css-paint/external/wpt/css/css-paint-api/parse-input-arguments-011.https.html [ Failure Pass ]
+crbug.com/1285373 [ Linux ] fast/multicol/dynamic/insert-block-before-spanner-before-content.html [ Crash Failure Pass ]
+crbug.com/1285426 [ Mac ] virtual/controls-refresh-hc/fast/forms/color-scheme/week-picker/week-picker-appearance-highlight-es.html [ Crash Pass ]
+crbug.com/1285438 fast/layers/clip-rects-transformed.html [ Failure Pass ]
+crbug.com/1285431 [ Mac ] virtual/backface-visibility-interop/compositing/overflow/transform-should-update-absolute-clip-rects.html [ Crash Failure Pass ]
+crbug.com/1285437 virtual/scroll-unification-prefer_compositing_to_lcd_text/fast/scroll-behavior/smooth-scroll/ongoing-smooth-scroll-vertical-rl-anchors.html [ Pass Timeout ]
+crbug.com/1285436 virtual/partitioned-cookies/http/tests/inspector-protocol/network/blocked-setcookie-same-site-lax.js [ Crash Failure Pass Timeout ]
diff --git a/third_party/blink/web_tests/external/WPT_BASE_MANIFEST_8.json b/third_party/blink/web_tests/external/WPT_BASE_MANIFEST_8.json
index f44264c..2bff58a9 100644
--- a/third_party/blink/web_tests/external/WPT_BASE_MANIFEST_8.json
+++ b/third_party/blink/web_tests/external/WPT_BASE_MANIFEST_8.json
@@ -601,6 +601,13 @@
         {}
        ]
       ],
+      "hidden-execcommand-crash.html": [
+       "67e297e6520b49325dd6091ca474c0151af5e0ea",
+       [
+        null,
+        {}
+       ]
+      ],
       "hidden-pseudo-element-removed-crash.html": [
        "62e38f214be715299f59bfc5f85697d28dfe4e92",
        [
@@ -85208,6 +85215,71 @@
        {}
       ]
      ],
+     "tagged-images-001.html": [
+      "0af9c0ce51e109588772a291e7b0250549c7fbe8",
+      [
+       null,
+       [
+        [
+         "/css/css-color/009900-image-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
+     "tagged-images-002.html": [
+      "b7c76b35502e13e65c4e8204ea1f05d15940f0ea",
+      [
+       null,
+       [
+        [
+         "/css/css-color/009900-image-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
+     "tagged-images-003.html": [
+      "09ce9e9418f4e3edfb0977b52b24906f45e5a715",
+      [
+       null,
+       [
+        [
+         "/css/css-color/greensquare-090-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
+     "tagged-images-004.html": [
+      "9e67776f680901d05c6c89df044f8b201f33d600",
+      [
+       null,
+       [
+        [
+         "/css/css-color/greensquare-090-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
+     "untagged-images-001.html": [
+      "a1aafb759c0d5994cc45ddd9422a1f7e39fa66e8",
+      [
+       null,
+       [
+        [
+         "/css/css-color/009900-tagged-image-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
      "xyz-001.html": [
       "6fdf98e2dfc9f6d5341d12e5367b3159127e5df3",
       [
@@ -136080,6 +136152,45 @@
        {}
       ]
      ],
+     "overflow-auto-scrollbar-gutter-intrinsic-001.html": [
+      "061339b49cd29b0f68d53c5ecce6d2eb03fdaa6c",
+      [
+       null,
+       [
+        [
+         "/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
+     "overflow-auto-scrollbar-gutter-intrinsic-002.html": [
+      "535f2c4d5298df70e2eb417531093bb7fa753cbd",
+      [
+       null,
+       [
+        [
+         "/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
+     "overflow-auto-scrollbar-gutter-intrinsic-003.html": [
+      "ab247d9ca5a7cac660200cb475feb6b69093e520",
+      [
+       null,
+       [
+        [
+         "/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
      "overflow-body-propagation-001.html": [
       "0998fe68e007d5a46ff11d5ff87fdbad12d1dfe2",
       [
@@ -136496,6 +136607,19 @@
        {}
       ]
      ],
+     "overflow-scroll-intrinsic-001.html": [
+      "093fd283c77b71e7f73914761cc086e10c12a0d6",
+      [
+       null,
+       [
+        [
+         "/css/css-overflow/overflow-scroll-intrinsic-001-ref.html",
+         "=="
+        ]
+       ],
+       {}
+      ]
+     ],
      "overflow-scroll-resize-visibility-hidden.html": [
       "e8d0bc91440c7ed810079cc577d1e02689d3b220",
       [
@@ -242009,6 +242133,14 @@
      }
     },
     "css-color": {
+     "009900-image-ref.html": [
+      "cf1ba5c48f70bba18ac44e3acf35378aa4f62fd5",
+      []
+     ],
+     "009900-tagged-image-ref.html": [
+      "21086fc62185a65da89513daf0c8bc1b66688064",
+      []
+     ],
      "LICENSE": [
       "d47f50cca8a2d9dc40dee384ae256f8aecf44e0a",
       []
@@ -242275,6 +242407,20 @@
       "a1574caa30328d9b053283515f9d2b54d6326a54",
       []
      ],
+     "support": {
+      "009900-sRGB.png": [
+       "d6b0c96642f2552a75fb2be54b3bb3a3d49730dd",
+       []
+      ],
+      "009900.png": [
+       "7ddaa10b44e83d5a64a66370da1b1dcaa1ea7ec4",
+       []
+      ],
+      "swap-990000-iCCP.png": [
+       "766d0f76797a31c3d1c041680b8d04dfcb72ab1a",
+       []
+      ]
+     },
      "t31-color-currentColor-b-ref.html": [
       "3013c7050c3c6f057e295923d43c87da6c09751f",
       []
@@ -259441,6 +259587,18 @@
       "59864d0f4d185ece259879a299f597b80f9babdc",
       []
      ],
+     "overflow-auto-scrollbar-gutter-intrinsic-001-ref.html": [
+      "8c092bd0c876bc328919f4b39358110dd902c726",
+      []
+     ],
+     "overflow-auto-scrollbar-gutter-intrinsic-002-ref.html": [
+      "bb0742bfd0f130021ed4234920365aa83a2efed5",
+      []
+     ],
+     "overflow-auto-scrollbar-gutter-intrinsic-003-ref.html": [
+      "2fb2eb4479a876fb2c990b5a16d1cbbd44aade37",
+      []
+     ],
      "overflow-body-propagation-007-ref.html": [
       "66f9b1c3b0098c0cc448775cde0d94b4325a94a8",
       []
@@ -259517,6 +259675,10 @@
       "c7ea1807443ef1b2d454edd547e65c89a59cea16",
       []
      ],
+     "overflow-scroll-intrinsic-001-ref.html": [
+      "8870d339196d8ccc14db575437190c728fa7e49c",
+      []
+     ],
      "overflow-scroll-resize-visibility-hidden-ref.html": [
       "571ba348df4b2dfdd05b31d074496c95c340635d",
       []
@@ -261011,7 +261173,7 @@
      ],
      "parsing": {
       "marker-supported-properties-expected.txt": [
-       "b599ad933fc63e2535c7740ac8cca8e933e17883",
+       "3b1189ccdf31f07452875606ebf38a736363409b",
        []
       ],
       "marker-supported-properties-in-animation-expected.txt": [
@@ -278108,7 +278270,7 @@
       []
      ],
      "inserthtml.js": [
-      "376d988bec125d1272a8137b34220facf69b006d",
+      "1f0a8f588dd630e3bcdcccc37d6ba3d021cab084",
       []
      ],
      "insertimage.js": [
@@ -278494,7 +278656,7 @@
       []
      ],
      "inserthtml-expected.txt": [
-      "2cae0dffb68410e3daf9c4e94b92bbe9dcee1605",
+      "06c23700443abaff3eb0e9e872ee308d5befa517",
       []
      ],
      "insertimage-expected.txt": [
@@ -282137,11 +282299,15 @@
        []
       ],
       "preflight.py": [
-       "8accc689f3bffe38dca735361ea8f7f582ccf682",
+       "bc2250456e04dbb35edb0496685d0af698fded6b",
        []
       ],
-      "service-worker-fetcher.html": [
-       "d9c0df30fd4bfcc2eb780a839037d0c2ab88af4b",
+      "service-worker-bridge.html": [
+       "9bee90d210580b371dfadbff3061b666b0b83dbe",
+       []
+      ],
+      "service-worker.js": [
+       "bca71ad910cb189c2de6298b4ea59b5594aba637",
        []
       ],
       "shared-worker-fetcher.html": [
@@ -282165,8 +282331,16 @@
        []
       ]
      },
+     "service-worker-fetch.https.window-expected.txt": [
+      "716cc67bdef69bfb4a99cafcc8e0af6c16e94787",
+      []
+     ],
+     "service-worker-update.https.window-expected.txt": [
+      "2884c271eecfd46ee3fee89707cbd5c81c624939",
+      []
+     ],
      "service-worker.https.window-expected.txt": [
-      "862f41ae97d255c84fe160a70cb5d2eb14e72f39",
+      "6c834a89c8d481231d211249ff5451aaa9164f5b",
       []
      ],
      "shared-worker.https.window-expected.txt": [
@@ -284059,6 +284233,12 @@
         "5f10361d5cffd939d1cc12c73cf49218098d7351",
         []
        ],
+       "eligibility": {
+        "broadcast-channel-expected.txt": [
+         "307bd14234d626c558b4070b1f9225ae6b722981",
+         []
+        ]
+       },
        "events-expected.txt": [
         "6dad05534728dc6a05db46b5c112a2fd9546e8ce",
         []
@@ -287948,10 +288128,6 @@
        "377c7296a781adb8ce5792cda50a4ded28472339",
        []
       ],
-      "local-storage.tentative.https.window-expected.txt": [
-       "0f6267c7c83b6d4183dc8d273e43e12b80fe07fc",
-       []
-      ],
       "require-corp-embed-anonymous-iframe.tentative.https.window.js.headers": [
        "6604450991a122e3e241e40b1b9e0516c525389d",
        []
@@ -309168,10 +309344,6 @@
      "3f8456354bd08a3cb87e767ca0eb508603f45f1b",
      []
     ],
-    "basic-dedicated-worker-expected.txt": [
-     "12e06f3594177c46c8e01fcd3873c83d8d03cc0b",
-     []
-    ],
     "basic-popup-and-iframe-tests.https-expected.txt": [
      "712c701f4f7230566278fd0df2cf7d350dab8707",
      []
@@ -315781,7 +315953,7 @@
        []
       ],
       "accumulation-per-property-002-expected.txt": [
-       "b477cd5cfb940ffef79b82973abbec1c049b66e8",
+       "357a3c326e931046ef5cf8a67898fc67f44c2804",
        []
       ],
       "addition-per-property-001-expected.txt": [
@@ -315789,7 +315961,7 @@
        []
       ],
       "addition-per-property-002-expected.txt": [
-       "9a5c6364dc42aa14461a5be0b67cc8eb49593b09",
+       "0e7f2b0b8eee56f51b02421646784b1ce4ea540c",
        []
       ],
       "interpolation-per-property-001-expected.txt": [
@@ -315797,11 +315969,11 @@
        []
       ],
       "interpolation-per-property-002-expected.txt": [
-       "c4a07ae6b232dd902c94032bc86803073cfc67ad",
+       "74ac012b78c356fe0337d24f7d54e680834e2d7a",
        []
       ],
       "property-list.js": [
-       "60b0b595150cd92486d3ed41abba6188fd4d4011",
+       "e9b7c524a749f2a8372868a1245224cf0f7d01d5",
        []
       ],
       "property-types.js": [
@@ -369216,14 +369388,14 @@
        ]
       ],
       "marker-supported-properties-in-animation.html": [
-       "259a5b84eb5122c309294973b5ad745da11216e5",
+       "e581a786367ac13a90f95cb043b95c629babd9ab",
        [
         null,
         {}
        ]
       ],
       "marker-supported-properties.html": [
-       "ddcf98bfcf283fbb72d08396a6676a686bf02da5",
+       "ab03b9825deee02142bd0a03a21e9ff95feaa82f",
        [
         null,
         {}
@@ -375228,7 +375400,7 @@
     },
     "css-text-decor": {
      "inheritance.html": [
-      "b106343742e03aa305a3017610272c8692b2a428",
+      "9ee65b4e5926f043b4841bc1f5a7cf84e214ce49",
       [
        null,
        {}
@@ -375348,7 +375520,7 @@
        ]
       ],
       "text-emphasis-computed.html": [
-       "460035a55179ada38a78be2dd7a280c8a0bd3518",
+       "7765f87d5b1eef59e9ae05f00de11daebeda038c",
        [
         null,
         {}
@@ -375362,7 +375534,7 @@
        ]
       ],
       "text-emphasis-style-computed.html": [
-       "5aa84ab08b615568b96812670674caade7b663ab",
+       "9153e82c30a43b88596ef239c30bf6b1fe095edf",
        [
         null,
         {}
@@ -415327,8 +415499,44 @@
        }
       ]
      ],
+     "service-worker-fetch.https.window.js": [
+      "edb20c04940e3fa76a2dd99e71785f97285c31c6",
+      [
+       "fetch/private-network-access/service-worker-fetch.https.window.html",
+       {
+        "script_metadata": [
+         [
+          "script",
+          "/common/utils.js"
+         ],
+         [
+          "script",
+          "resources/support.sub.js"
+         ]
+        ]
+       }
+      ]
+     ],
+     "service-worker-update.https.window.js": [
+      "703c7650b0dbeeb4559a74e3557a91bf6b484e19",
+      [
+       "fetch/private-network-access/service-worker-update.https.window.html",
+       {
+        "script_metadata": [
+         [
+          "script",
+          "/common/utils.js"
+         ],
+         [
+          "script",
+          "resources/support.sub.js"
+         ]
+        ]
+       }
+      ]
+     ],
      "service-worker.https.window.js": [
-      "969f359700e4c1c145743eb4c826973e7400a3af",
+      "3d3845b4d7cb832dcc4ad7238c54d655c84656fc",
       [
        "fetch/private-network-access/service-worker.https.window.html",
        {
@@ -418160,6 +418368,15 @@
     "browsers": {
      "browsing-the-web": {
       "back-forward-cache": {
+       "eligibility": {
+        "broadcast-channel.html": [
+         "bc04a5ed7f1c1feea66a6db74d6537ea3f48b577",
+         [
+          null,
+          {}
+         ]
+        ]
+       },
        "events.html": [
         "4b1d3e408ebc25a4bf5f18087fc9bac67b2a1889",
         [
@@ -495833,7 +496050,7 @@
    },
    "secure-contexts": {
     "basic-dedicated-worker.html": [
-     "581d761f5e795a2734f306c239d4a96220d4219a",
+     "ecd6138ac25d575a76a8625323513b9ec42646d6",
      [
       null,
       {}
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/009900-image-ref.html b/third_party/blink/web_tests/external/wpt/css/css-color/009900-image-ref.html
new file mode 100644
index 0000000..cf1ba5c
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/009900-image-ref.html
@@ -0,0 +1,11 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Space of Tagged Images. HTML img</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+
+
+<body>
+    <p>Test passes if you see a green square, and no red.</p>
+    <!-- solid color #009900 PNG image, untagged -->
+    <p><img src="./support/009900.png" alt="should be green"/></p>
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/009900-tagged-image-ref.html b/third_party/blink/web_tests/external/wpt/css/css-color/009900-tagged-image-ref.html
new file mode 100644
index 0000000..21086fc
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/009900-tagged-image-ref.html
@@ -0,0 +1,14 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Space of Tagged Images. HTML img</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+
+
+<body>
+    <p>Test passes if you see a green square, and no red.</p>
+    <!--
+        solid color #990000 PNG image, iCCP with v2 profile
+        red-green swapped to be sure the profile is actually applied
+     -->
+    <p><img src="./support/swap-990000-iCCP.png" alt="should be green"/></p>
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/support/009900-sRGB.png b/third_party/blink/web_tests/external/wpt/css/css-color/support/009900-sRGB.png
new file mode 100644
index 0000000..d6b0c96
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/support/009900-sRGB.png
Binary files differ
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/support/009900.png b/third_party/blink/web_tests/external/wpt/css/css-color/support/009900.png
new file mode 100644
index 0000000..7ddaa10
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/support/009900.png
Binary files differ
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/support/swap-990000-iCCP.png b/third_party/blink/web_tests/external/wpt/css/css-color/support/swap-990000-iCCP.png
new file mode 100644
index 0000000..766d0f767
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/support/swap-990000-iCCP.png
Binary files differ
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-001.html b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-001.html
new file mode 100644
index 0000000..0af9c0c
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-001.html
@@ -0,0 +1,14 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Space of Tagged Images. HTML img</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+<link rel="help" href="https://drafts.csswg.org/css-color-4/#tagged-images">
+<link rel="help" href="https://w3c.github.io/PNG-spec/#11iCCP">
+<meta name="assert" content="Tagged RGB images... if the color profile or other identifying information is valid, must be treated as being in the specified color space.">
+<link rel="match" href="009900-image-ref.html">
+
+<body>
+    <p>Test passes if you see a green square, and no red.</p>
+    <!-- solid color #990000 PNG image, iCCP with v2 ICC swapped red-green sRGB profile -->
+    <p><img src="./support/swap-990000-iCCP.png" alt="should be green"/></p>
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-002.html b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-002.html
new file mode 100644
index 0000000..b7c76b3
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-002.html
@@ -0,0 +1,14 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Space of Tagged Images. HTML img</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+<link rel="help" href="https://drafts.csswg.org/css-color-4/#tagged-images">
+<link rel="help" href="https://w3c.github.io/PNG-spec/#11sRGB">
+<meta name="assert" content="Tagged RGB images... if the color profile or other identifying information is valid, must be treated as being in the specified color space.">
+<link rel="match" href="009900-image-ref.html">
+
+<body>
+    <p>Test passes if you see a green square, and no red.</p>
+    <!-- solid color #009900 PNG image, sRGB chunk, relative colorimetric -->
+    <p><img src="./support/009900-sRGB.png" alt="should be green"/></p>
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-003.html b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-003.html
new file mode 100644
index 0000000..09ce9e9
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-003.html
@@ -0,0 +1,22 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Space of Tagged Images. CSS background property</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+<link rel="help" href="https://drafts.csswg.org/css-color-4/#tagged-images">
+<link rel="help" href="https://w3c.github.io/PNG-spec/#11iCCP">
+<meta name="assert" content="Tagged RGB images... if the color profile or other identifying information is valid, must be treated as being in the specified color space.">
+<link rel="match" href="./greensquare-090-ref.html">
+<style>
+    .test { background-color: red; width: 12em; height: 6em; margin-top: 0; }
+    .ref { background-color: #090; width: 12em; height: 6em; margin-bottom: 0; } /* red-green swap of #900 sRGB */
+    /* solid color #990000 PNG image, iCCP with v2 ICC swapped red-green sRGB profile */
+    .test { background: url(./support/swap-990000-iCCP.png); }
+</style>
+<body>
+    <p>Test passes if you see a single green square,
+        not two rectangles of different colors,
+        and no red.</p>
+    <div class="ref"></div>
+    <div class="test"></div>
+
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-004.html b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-004.html
new file mode 100644
index 0000000..9e67776
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/tagged-images-004.html
@@ -0,0 +1,28 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Space of Tagged Images. CSS background property</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+<link rel="help" href="https://drafts.csswg.org/css-color-4/#tagged-images">
+<link rel="help" href="https://w3c.github.io/PNG-spec/#11iCCP">
+<link rel="help" href="https://w3c.github.io/PNG-spec/#11sRGB">
+<meta name="assert" content="Image formats may also use other, equivalent methods, often for brevity.
+For example, PNG specifies a means (the sRGB chunk) ">
+<link rel="match" href="./greensquare-090-ref.html">
+<style>
+    div { width: 12em; height: 6em; margin-top: 0; margin-bottom: 0}
+    .test { background-color: red; }
+
+    /* solid color #990000 PNG image, iCCP with v2 ICC swapped red-green sRGB profile */
+    .ref { background: url(./support/swap-990000-iCCP.png); }
+
+    /* solid color #009900 PNG image, sRGB chunk */
+    .test { background: url(./support/009900-sRGB.png); }
+</style>
+<body>
+    <p>Test passes if you see a single green square,
+        not two rectangles of different colors,
+        and no red.</p>
+    <div class="ref"></div>
+    <div class="test"></div>
+
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-color/untagged-images-001.html b/third_party/blink/web_tests/external/wpt/css/css-color/untagged-images-001.html
new file mode 100644
index 0000000..a1aafb7
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-color/untagged-images-001.html
@@ -0,0 +1,13 @@
+<!DOCTYPE html>
+<meta charset="utf-8">
+<title>CSS Color 4: Color Spaces of Untagged Colors</title>
+<link rel="author" title="Chris Lilley" href="mailto:chris@w3.org">
+<link rel="help" href="https://drafts.csswg.org/css-color-4/#untagged">
+<meta name="assert" content=" untagged images must be treated as being in the sRGB color space">
+<link rel="match" href="009900-tagged-image-ref.html">
+
+<body>
+    <p>Test passes if you see a green square, and no red.</p>
+    <!-- solid color #009900 PNG image, no color information -->
+    <p><img src="./support/009900.png" alt="should be green"/></p>
+</body>
\ No newline at end of file
diff --git a/third_party/blink/web_tests/external/wpt/css/css-contain/content-visibility/hidden-execcommand-crash.html b/third_party/blink/web_tests/external/wpt/css/css-contain/content-visibility/hidden-execcommand-crash.html
new file mode 100644
index 0000000..67e297e6
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-contain/content-visibility/hidden-execcommand-crash.html
@@ -0,0 +1,10 @@
+<!DOCTYPE html>
+<link rel=author href="mailto:jarhar@chromium.org">
+<link rel=help href="https://bugs.chromium.org/p/chromium/issues/detail?id=1280134">
+
+<html contenteditable=true>
+  X<div style="content-visibility:hidden">Y</div>Z
+<script>
+document.execCommand("selectall");
+document.execCommand("fontSize", false, 6);
+</script>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001-ref.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001-ref.html
new file mode 100644
index 0000000..8c092bd
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001-ref.html
@@ -0,0 +1,60 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Reference: scrollbar-gutter size contributes to the scroll container's intrinsic size with "overflow:auto"</title>
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-4/#scrollbar-gutter-property">
+
+  <style>
+  .line {
+    display: flex;
+  }
+  .container {
+    block-size: 50px;
+    border: 5px solid black;
+    scrollbar-gutter: stable;
+    margin: 10px;
+  }
+  .hidden {
+    overflow: hidden;
+  }
+  .scroll-x {
+    overflow-x: scroll;
+  }
+  .scroll-y {
+    overflow-y: scroll;
+  }
+  .tall {
+    /* trigger overflow */
+    block-size: 5000px;
+  }
+  </style>
+
+  <div class="line">
+    <div class="container hidden">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container scroll-y">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+
+  <div class="line">
+    <div class="container hidden" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container scroll-x" style="writing-mode: vertical-rl">
+      <div class="tall">I should not wrap</div>
+    </div>
+
+    <div class="container hidden" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container scroll-x" style="writing-mode: vertical-lr">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001.html
new file mode 100644
index 0000000..061339b
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-001.html
@@ -0,0 +1,53 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Test: scrollbar-gutter size contributes to the scroll container's intrinsic size with "overflow:auto"</title>
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-4/#scrollbar-gutter-property">
+  <link rel="match" href="overflow-auto-scrollbar-gutter-intrinsic-001-ref.html">
+
+  <style>
+  .line {
+    display: flex;
+  }
+  .container {
+    block-size: 50px;
+    border: 5px solid black;
+    overflow: auto;
+    scrollbar-gutter: stable;
+    margin: 10px;
+  }
+  .tall {
+    /* trigger overflow */
+    block-size: 5000px;
+  }
+  </style>
+
+  <div class="line">
+    <div class="container">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+
+  <div class="line">
+    <div class="container" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-rl">
+      <div class="tall">I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002-ref.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002-ref.html
new file mode 100644
index 0000000..bb0742bf
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002-ref.html
@@ -0,0 +1,60 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Reference: scrollbar-gutter size contributes to the scroll container's intrinsic size with "overflow:auto"</title>
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-4/#scrollbar-gutter-property">
+
+  <style>
+  .line {
+    display: flex;
+  }
+  .container {
+    block-size: 50px;
+    border: 5px solid black;
+    scrollbar-gutter: stable both-edges;
+    margin: 10px;
+  }
+  .hidden {
+    overflow: hidden;
+  }
+  .scroll-x {
+    overflow-x: scroll;
+  }
+  .scroll-y {
+    overflow-y: scroll;
+  }
+  .tall {
+    /* trigger overflow */
+    block-size: 5000px;
+  }
+  </style>
+
+  <div class="line">
+    <div class="container hidden">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container scroll-y">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+
+  <div class="line">
+    <div class="container hidden" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container scroll-x" style="writing-mode: vertical-rl">
+      <div class="tall">I should not wrap</div>
+    </div>
+
+    <div class="container hidden" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container scroll-x" style="writing-mode: vertical-lr">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002.html
new file mode 100644
index 0000000..535f2c4
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-002.html
@@ -0,0 +1,53 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Test: scrollbar-gutter size contributes to the scroll container's intrinsic size with "overflow:auto"</title>
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-4/#scrollbar-gutter-property">
+  <link rel="match" href="overflow-auto-scrollbar-gutter-intrinsic-002-ref.html">
+
+  <style>
+  .line {
+    display: flex;
+  }
+  .container {
+    block-size: 50px;
+    border: 5px solid black;
+    overflow: auto;
+    scrollbar-gutter: stable both-edges;
+    margin: 10px;
+  }
+  .tall {
+    /* trigger overflow */
+    block-size: 5000px;
+  }
+  </style>
+
+  <div class="line">
+    <div class="container">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+
+  <div class="line">
+    <div class="container" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-rl">
+      <div class="tall">I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003-ref.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003-ref.html
new file mode 100644
index 0000000..2fb2eb4
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003-ref.html
@@ -0,0 +1,47 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Test: scrollbar-gutter size doesn't contribute to the scroll container's intrinsic size with "overflow:auto" and "scrollbar-width: none"</title>
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-4/#scrollbar-gutter-property">
+  <link rel="help" href="https://drafts.csswg.org/css-scrollbars/#scrollbar-width">
+
+  <style>
+  .line {
+    display: flex;
+  }
+  .container {
+    block-size: 50px;
+    border: 5px solid black;
+    margin: 10px;
+  }
+  </style>
+
+  <div class="line">
+    <div class="container">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container">
+      <div>I should not wrap</div>
+    </div>
+  </div>
+
+  <div class="line">
+    <div class="container" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+  </div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003.html
new file mode 100644
index 0000000..ab247d9c
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-auto-scrollbar-gutter-intrinsic-003.html
@@ -0,0 +1,55 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Test: scrollbar-gutter size doesn't contribute to the scroll container's intrinsic size with "overflow:auto" and "scrollbar-width: none"</title>
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-4/#scrollbar-gutter-property">
+  <link rel="help" href="https://drafts.csswg.org/css-scrollbars/#scrollbar-width">
+  <link rel="match" href="overflow-auto-scrollbar-gutter-intrinsic-003-ref.html">
+
+  <style>
+  .line {
+    display: flex;
+  }
+  .container {
+    block-size: 50px;
+    border: 5px solid black;
+    overflow: auto;
+    scrollbar-gutter: stable;
+    scrollbar-width: none;
+    margin: 10px;
+  }
+  .tall {
+    /* trigger overflow */
+    block-size: 5000px;
+  }
+  </style>
+
+  <div class="line">
+    <div class="container">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+
+  <div class="line">
+    <div class="container" style="writing-mode: vertical-rl">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-rl">
+      <div class="tall">I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div>I should not wrap</div>
+    </div>
+
+    <div class="container" style="writing-mode: vertical-lr">
+      <div class="tall">I should not wrap</div>
+    </div>
+  </div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-scroll-intrinsic-001-ref.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-scroll-intrinsic-001-ref.html
new file mode 100644
index 0000000..8870d33
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-scroll-intrinsic-001-ref.html
@@ -0,0 +1,20 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Reference: Intrinsic size of a "overflow:auto" vertical scroll container</title>
+  <link rel="author" title="Daniel Holbert" href="mailto:dholbert@mozilla.com">
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+
+  <style>
+  .container {
+    border: 1px solid black;
+    width: 100px;
+    display: inline-block;
+  }
+  </style>
+
+  <div class="container" style="overflow-x: scroll;"></div>
+  <div class="container" style="overflow-y: scroll;"></div>
+  <div class="container" style="overflow-x: scroll;"></div>
+  <div class="container" style="overflow-y: scroll;"></div>
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-scroll-intrinsic-001.html b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-scroll-intrinsic-001.html
new file mode 100644
index 0000000..093fd283
--- /dev/null
+++ b/third_party/blink/web_tests/external/wpt/css/css-overflow/overflow-scroll-intrinsic-001.html
@@ -0,0 +1,23 @@
+<!DOCTYPE html>
+<html>
+  <meta charset="utf-8">
+  <title>CSS Overflow Test: Intrinsic size of a "overflow:auto" vertical scroll container</title>
+  <link rel="author" title="Daniel Holbert" href="mailto:dholbert@mozilla.com">
+  <link rel="author" title="Ting-Yu Lin" href="mailto:tlin@mozilla.com">
+  <link rel="help" href="https://drafts.csswg.org/css-overflow-3/#overflow-properties">
+  <link rel="match" href="overflow-scroll-intrinsic-001-ref.html">
+
+  <style>
+  .container {
+    border: 1px solid black;
+    width: 100px;
+    display: inline-block;
+  }
+  </style>
+
+  <div class="container" style="writing-mode: vertical-rl; overflow-x: scroll;"></div>
+  <div class="container" style="writing-mode: vertical-rl; overflow-y: scroll;"></div>
+  <div class="container" style="writing-mode: vertical-lr; overflow-x: scroll;"></div>
+  <div class="container" style="writing-mode: vertical-lr; overflow-y: scroll;"></div>
+
+</html>
diff --git a/third_party/blink/web_tests/external/wpt/editing/data/inserthtml.js b/third_party/blink/web_tests/external/wpt/editing/data/inserthtml.js
index 376d988b..1f0a8f5 100644
--- a/third_party/blink/web_tests/external/wpt/editing/data/inserthtml.js
+++ b/third_party/blink/web_tests/external/wpt/editing/data/inserthtml.js
@@ -571,4 +571,18 @@
      "<pre contenteditable=\"false\"><span contenteditable=\"\">abc<br></span></pre>"],
     [true],
     {"inserthtml":[false,false,"",false,false,""]}],
+
+// Empty inline elements shouldn't be deleted if they are inserted intentionally
+["<div>a[]b</div>",
+    [["inserthtml","<span></span>"]],
+    ["<div>a<span></span>b</div>",
+     "<div>a<span></span>b<br></div>"],
+    [true],
+    {"inserthtml":[false,false,"",false,false,""]}],
+["<div>a[]c</div>",
+    [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]],
+    ["<div>a<span class=\"s1\"></span>b<span class=\"s2\"></span>c</div>",
+     "<div>a<span class=\"s1\"></span>b<span class=\"s2\"></span>c<br></div>"],
+    [true],
+    {"inserthtml":[false,false,"",false,false,""]}],
 ]
diff --git a/third_party/blink/web_tests/external/wpt/editing/run/inserthtml-expected.txt b/third_party/blink/web_tests/external/wpt/editing/run/inserthtml-expected.txt
index 2cae0df..06c23700 100644
--- a/third_party/blink/web_tests/external/wpt/editing/run/inserthtml-expected.txt
+++ b/third_party/blink/web_tests/external/wpt/editing/run/inserthtml-expected.txt
@@ -1,5 +1,5 @@
 This is a testharness.js-based test.
-Found 1498 tests; 1444 PASS, 54 FAIL, 0 TIMEOUT, 0 NOTRUN.
+Found 1516 tests; 1460 PASS, 56 FAIL, 0 TIMEOUT, 0 NOTRUN.
 PASS [["stylewithcss","true"],["inserthtml","ab<b>c</b>d"]] "foo[]bar": execCommand("stylewithcss", false, "true") return value
 PASS [["stylewithcss","true"],["inserthtml","ab<b>c</b>d"]] "foo[]bar": execCommand("inserthtml", false, "ab<b>c</b>d") return value
 PASS [["stylewithcss","true"],["inserthtml","ab<b>c</b>d"]] "foo[]bar" checks for modifications to non-editable content
@@ -1498,5 +1498,23 @@
 PASS [["inserthtml","<pre>abc</pre>"]] "<pre contenteditable=\"false\"><span contenteditable>[1234]</span></pre>" queryCommandIndeterm("inserthtml") after
 PASS [["inserthtml","<pre>abc</pre>"]] "<pre contenteditable=\"false\"><span contenteditable>[1234]</span></pre>" queryCommandState("inserthtml") after
 PASS [["inserthtml","<pre>abc</pre>"]] "<pre contenteditable=\"false\"><span contenteditable>[1234]</span></pre>" queryCommandValue("inserthtml") after
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>": execCommand("inserthtml", false, "<span></span>") return value
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" checks for modifications to non-editable content
+FAIL [["inserthtml","<span></span>"]] "<div>a[]b</div>" compare innerHTML assert_in_array: Unexpected innerHTML (after normalizing inline style) value "<div>ab</div>" not in array ["<div>a<span></span>b</div>", "<div>a<span></span>b<br></div>"]
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" queryCommandIndeterm("inserthtml") before
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" queryCommandState("inserthtml") before
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" queryCommandValue("inserthtml") before
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" queryCommandIndeterm("inserthtml") after
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" queryCommandState("inserthtml") after
+PASS [["inserthtml","<span></span>"]] "<div>a[]b</div>" queryCommandValue("inserthtml") after
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>": execCommand("inserthtml", false, "<span class=\"s1\"></span>b<span class=\"s2\"></span>") return value
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" checks for modifications to non-editable content
+FAIL [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" compare innerHTML assert_in_array: Unexpected innerHTML (after normalizing inline style) value "<div>ab</div><span class=\"s1\"></span><span class=\"s2\"></span><div>c<br></div>" not in array ["<div>a<span class=\"s1\"></span>b<span class=\"s2\"></span>c</div>", "<div>a<span class=\"s1\"></span>b<span class=\"s2\"></span>c<br></div>"]
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" queryCommandIndeterm("inserthtml") before
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" queryCommandState("inserthtml") before
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" queryCommandValue("inserthtml") before
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" queryCommandIndeterm("inserthtml") after
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" queryCommandState("inserthtml") after
+PASS [["inserthtml","<span class=\"s1\"></span>b<span class=\"s2\"></span>"]] "<div>a[]c</div>" queryCommandValue("inserthtml") after
 Harness: the test ran to completion.
 
diff --git a/third_party/blink/web_tests/external/wpt/html/cross-origin-embedder-policy/anonymous-iframe/local-storage.tentative.https.window-expected.txt b/third_party/blink/web_tests/external/wpt/html/cross-origin-embedder-policy/anonymous-iframe/local-storage.tentative.https.window-expected.txt
deleted file mode 100644
index 0f6267c..0000000
--- a/third_party/blink/web_tests/external/wpt/html/cross-origin-embedder-policy/anonymous-iframe/local-storage.tentative.https.window-expected.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-This is a testharness.js-based test.
-PASS Setup
-FAIL same_origin anonymous iframe can't access the localStorage assert_equals: expected "" but got "same_origin"
-FAIL cross_origin anonymous iframe can't access the localStorage assert_equals: expected "" but got "cross_origin"
-Harness: the test ran to completion.
-
diff --git a/third_party/blink/web_tests/platform/mac-mac10.13/virtual/plz-dedicated-worker/external/wpt/referrer-policy/gen/srcdoc.meta/strict-origin/iframe-tag.http-expected.txt b/third_party/blink/web_tests/platform/mac-mac10.13/virtual/plz-dedicated-worker/external/wpt/referrer-policy/gen/srcdoc.meta/strict-origin/iframe-tag.http-expected.txt
new file mode 100644
index 0000000..04a9370
--- /dev/null
+++ b/third_party/blink/web_tests/platform/mac-mac10.13/virtual/plz-dedicated-worker/external/wpt/referrer-policy/gen/srcdoc.meta/strict-origin/iframe-tag.http-expected.txt
@@ -0,0 +1,15 @@
+This is a testharness.js-based test.
+PASS Referrer Policy: Expects origin for iframe-tag to cross-http origin and keep-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to cross-http origin and no-redirect redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to cross-http origin and swap-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to cross-https origin and keep-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to cross-https origin and no-redirect redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to cross-https origin and swap-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to same-http origin and keep-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to same-http origin and no-redirect redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to same-http origin and swap-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to same-https origin and keep-origin redirection from http context.
+PASS Referrer Policy: Expects origin for iframe-tag to same-https origin and no-redirect redirection from http context.
+FAIL Referrer Policy: Expects origin for iframe-tag to same-https origin and swap-origin redirection from http context. assert_in_array: document.referrer value "http://web-platform.test:8001/referrer-policy/gen/srcdoc.meta/strict-origin/iframe-tag.http.html" not in array ["http://web-platform.test:8001/", undefined]
+Harness: the test ran to completion.
+
diff --git a/third_party/blink/web_tests/virtual/third-party-storage-partitioning/external/wpt/webstorage/localstorage-basic-partitioned.tentative.sub-expected.txt b/third_party/blink/web_tests/virtual/third-party-storage-partitioning/external/wpt/webstorage/localstorage-basic-partitioned.tentative.sub-expected.txt
index 6cdbef6..9d229db 100644
--- a/third_party/blink/web_tests/virtual/third-party-storage-partitioning/external/wpt/webstorage/localstorage-basic-partitioned.tentative.sub-expected.txt
+++ b/third_party/blink/web_tests/virtual/third-party-storage-partitioning/external/wpt/webstorage/localstorage-basic-partitioned.tentative.sub-expected.txt
@@ -1,4 +1,4 @@
 This is a testharness.js-based test.
-FAIL Simple test for partitioned localStorage assert_true: IDs pulled from two partitioned iframes are different. expected true got false
+PASS Simple test for partitioned localStorage
 Harness: the test ran to completion.
 
diff --git a/third_party/boringssl/BUILD.generated.gni b/third_party/boringssl/BUILD.generated.gni
index fed3f02..5e57473 100644
--- a/third_party/boringssl/BUILD.generated.gni
+++ b/third_party/boringssl/BUILD.generated.gni
@@ -78,14 +78,15 @@
   "src/crypto/conf/conf.c",
   "src/crypto/conf/conf_def.h",
   "src/crypto/conf/internal.h",
-  "src/crypto/cpu-aarch64-fuchsia.c",
-  "src/crypto/cpu-aarch64-linux.c",
-  "src/crypto/cpu-aarch64-win.c",
-  "src/crypto/cpu-arm-linux.c",
-  "src/crypto/cpu-arm-linux.h",
-  "src/crypto/cpu-arm.c",
-  "src/crypto/cpu-intel.c",
-  "src/crypto/cpu-ppc64le.c",
+  "src/crypto/cpu_aarch64_apple.c",
+  "src/crypto/cpu_aarch64_fuchsia.c",
+  "src/crypto/cpu_aarch64_linux.c",
+  "src/crypto/cpu_aarch64_win.c",
+  "src/crypto/cpu_arm.c",
+  "src/crypto/cpu_arm_linux.c",
+  "src/crypto/cpu_arm_linux.h",
+  "src/crypto/cpu_intel.c",
+  "src/crypto/cpu_ppc64le.c",
   "src/crypto/crypto.c",
   "src/crypto/curve25519/curve25519.c",
   "src/crypto/curve25519/curve25519_tables.h",
diff --git a/third_party/boringssl/BUILD.generated_tests.gni b/third_party/boringssl/BUILD.generated_tests.gni
index 20a4212d..9e612df8 100644
--- a/third_party/boringssl/BUILD.generated_tests.gni
+++ b/third_party/boringssl/BUILD.generated_tests.gni
@@ -40,7 +40,7 @@
   "src/crypto/compiler_test.cc",
   "src/crypto/conf/conf_test.cc",
   "src/crypto/constant_time_test.cc",
-  "src/crypto/cpu-arm-linux_test.cc",
+  "src/crypto/cpu_arm_linux_test.cc",
   "src/crypto/crypto_test.cc",
   "src/crypto/curve25519/ed25519_test.cc",
   "src/crypto/curve25519/spake25519_test.cc",
@@ -91,7 +91,6 @@
   "src/crypto/x509/x509_test.cc",
   "src/crypto/x509/x509_time_test.cc",
   "src/crypto/x509v3/tab_test.cc",
-  "src/crypto/x509v3/v3name_test.cc",
 ]
 
 crypto_test_data = [
diff --git a/third_party/boringssl/BUILD.gn b/third_party/boringssl/BUILD.gn
index 91ce539..e31d0921 100644
--- a/third_party/boringssl/BUILD.gn
+++ b/third_party/boringssl/BUILD.gn
@@ -35,9 +35,6 @@
     "BORINGSSL_NO_STATIC_INITIALIZER",
     "OPENSSL_SMALL",
   ]
-  if (is_posix || is_fuchsia) {
-    defines += [ "_XOPEN_SOURCE=700" ]
-  }
 }
 
 config("no_asm_config") {
diff --git a/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha256-armv8.S b/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha256-armv8.S
index c9b7991..b40b260 100644
--- a/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha256-armv8.S
+++ b/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha256-armv8.S
@@ -12,7 +12,7 @@
 #if defined(BORINGSSL_PREFIX)
 #include <boringssl_prefix_symbols_asm.h>
 #endif
-// Copyright 2014-2016 The OpenSSL Project Authors. All Rights Reserved.
+// Copyright 2014-2020 The OpenSSL Project Authors. All Rights Reserved.
 //
 // Licensed under the OpenSSL license (the "License").  You may not use
 // this file except in compliance with the License.  You can obtain a copy
@@ -40,6 +40,7 @@
 // Denver	2.01		10.5 (+26%)	6.70 (+8%)
 // X-Gene			20.0 (+100%)	12.8 (+300%(***))
 // Mongoose	2.36		13.0 (+50%)	8.36 (+33%)
+// Kryo		1.92		17.4 (+30%)	11.2 (+8%)
 //
 // (*)	Software SHA256 results are of lesser relevance, presented
 //	mostly for informational purposes.
@@ -48,7 +49,7 @@
 //	on Cortex-A53 (or by 4 cycles per round).
 // (***)	Super-impressive coefficients over gcc-generated code are
 //	indication of some compiler "pathology", most notably code
-//	generated with -mgeneral-regs-only is significanty faster
+//	generated with -mgeneral-regs-only is significantly faster
 //	and the gap is only 40-90%.
 
 #ifndef	__KERNEL__
@@ -100,7 +101,7 @@
 	ldr	w19,[x30],#4			// *K++
 	eor	w28,w21,w22				// magic seed
 	str	x1,[x29,#112]
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w3,w3			// 0
 #endif
 	ror	w16,w24,#6
@@ -123,7 +124,7 @@
 	add	w27,w27,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w27,w27,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w4,w4			// 1
 #endif
 	ldp	w5,w6,[x1],#2*4
@@ -148,7 +149,7 @@
 	add	w26,w26,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w26,w26,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w5,w5			// 2
 #endif
 	add	w26,w26,w17			// h+=Sigma0(a)
@@ -172,7 +173,7 @@
 	add	w25,w25,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w25,w25,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w6,w6			// 3
 #endif
 	ldp	w7,w8,[x1],#2*4
@@ -197,7 +198,7 @@
 	add	w24,w24,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w24,w24,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w7,w7			// 4
 #endif
 	add	w24,w24,w17			// h+=Sigma0(a)
@@ -221,7 +222,7 @@
 	add	w23,w23,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w23,w23,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w8,w8			// 5
 #endif
 	ldp	w9,w10,[x1],#2*4
@@ -246,7 +247,7 @@
 	add	w22,w22,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w22,w22,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w9,w9			// 6
 #endif
 	add	w22,w22,w17			// h+=Sigma0(a)
@@ -270,7 +271,7 @@
 	add	w21,w21,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w21,w21,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w10,w10			// 7
 #endif
 	ldp	w11,w12,[x1],#2*4
@@ -295,7 +296,7 @@
 	add	w20,w20,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w20,w20,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w11,w11			// 8
 #endif
 	add	w20,w20,w17			// h+=Sigma0(a)
@@ -319,7 +320,7 @@
 	add	w27,w27,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w27,w27,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w12,w12			// 9
 #endif
 	ldp	w13,w14,[x1],#2*4
@@ -344,7 +345,7 @@
 	add	w26,w26,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w26,w26,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w13,w13			// 10
 #endif
 	add	w26,w26,w17			// h+=Sigma0(a)
@@ -368,7 +369,7 @@
 	add	w25,w25,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w25,w25,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w14,w14			// 11
 #endif
 	ldp	w15,w0,[x1],#2*4
@@ -394,7 +395,7 @@
 	add	w24,w24,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w24,w24,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w15,w15			// 12
 #endif
 	add	w24,w24,w17			// h+=Sigma0(a)
@@ -419,7 +420,7 @@
 	add	w23,w23,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w23,w23,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w0,w0			// 13
 #endif
 	ldp	w1,w2,[x1]
@@ -445,7 +446,7 @@
 	add	w22,w22,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w22,w22,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w1,w1			// 14
 #endif
 	ldr	w6,[sp,#12]
@@ -471,7 +472,7 @@
 	add	w21,w21,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w21,w21,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w2,w2			// 15
 #endif
 	ldr	w7,[sp,#0]
diff --git a/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha512-armv8.S b/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha512-armv8.S
index 97b3230..b2d366d 100644
--- a/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha512-armv8.S
+++ b/third_party/boringssl/ios-aarch64/crypto/fipsmodule/sha512-armv8.S
@@ -12,7 +12,7 @@
 #if defined(BORINGSSL_PREFIX)
 #include <boringssl_prefix_symbols_asm.h>
 #endif
-// Copyright 2014-2016 The OpenSSL Project Authors. All Rights Reserved.
+// Copyright 2014-2020 The OpenSSL Project Authors. All Rights Reserved.
 //
 // Licensed under the OpenSSL license (the "License").  You may not use
 // this file except in compliance with the License.  You can obtain a copy
@@ -40,6 +40,7 @@
 // Denver	2.01		10.5 (+26%)	6.70 (+8%)
 // X-Gene			20.0 (+100%)	12.8 (+300%(***))
 // Mongoose	2.36		13.0 (+50%)	8.36 (+33%)
+// Kryo		1.92		17.4 (+30%)	11.2 (+8%)
 //
 // (*)	Software SHA256 results are of lesser relevance, presented
 //	mostly for informational purposes.
@@ -48,7 +49,7 @@
 //	on Cortex-A53 (or by 4 cycles per round).
 // (***)	Super-impressive coefficients over gcc-generated code are
 //	indication of some compiler "pathology", most notably code
-//	generated with -mgeneral-regs-only is significanty faster
+//	generated with -mgeneral-regs-only is significantly faster
 //	and the gap is only 40-90%.
 
 #ifndef	__KERNEL__
@@ -64,6 +65,17 @@
 
 .align	6
 _sha512_block_data_order:
+	AARCH64_VALID_CALL_TARGET
+#ifndef	__KERNEL__
+#if __has_feature(hwaddress_sanitizer) && __clang_major__ >= 10
+	adrp	x16,:pg_hi21_nc:_OPENSSL_armcap_P
+#else
+	adrp	x16,_OPENSSL_armcap_P@PAGE
+#endif
+	ldr	w16,[x16,_OPENSSL_armcap_P@PAGEOFF]
+	tst	w16,#ARMV8_SHA512
+	b.ne	Lv8_entry
+#endif
 	AARCH64_SIGN_LINK_REGISTER
 	stp	x29,x30,[sp,#-128]!
 	add	x29,sp,#0
@@ -89,7 +101,7 @@
 	ldr	x19,[x30],#8			// *K++
 	eor	x28,x21,x22				// magic seed
 	str	x1,[x29,#112]
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x3,x3			// 0
 #endif
 	ror	x16,x24,#14
@@ -112,7 +124,7 @@
 	add	x27,x27,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x27,x27,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x4,x4			// 1
 #endif
 	ldp	x5,x6,[x1],#2*8
@@ -137,7 +149,7 @@
 	add	x26,x26,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x26,x26,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x5,x5			// 2
 #endif
 	add	x26,x26,x17			// h+=Sigma0(a)
@@ -161,7 +173,7 @@
 	add	x25,x25,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x25,x25,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x6,x6			// 3
 #endif
 	ldp	x7,x8,[x1],#2*8
@@ -186,7 +198,7 @@
 	add	x24,x24,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x24,x24,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x7,x7			// 4
 #endif
 	add	x24,x24,x17			// h+=Sigma0(a)
@@ -210,7 +222,7 @@
 	add	x23,x23,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x23,x23,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x8,x8			// 5
 #endif
 	ldp	x9,x10,[x1],#2*8
@@ -235,7 +247,7 @@
 	add	x22,x22,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x22,x22,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x9,x9			// 6
 #endif
 	add	x22,x22,x17			// h+=Sigma0(a)
@@ -259,7 +271,7 @@
 	add	x21,x21,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x21,x21,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x10,x10			// 7
 #endif
 	ldp	x11,x12,[x1],#2*8
@@ -284,7 +296,7 @@
 	add	x20,x20,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x20,x20,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x11,x11			// 8
 #endif
 	add	x20,x20,x17			// h+=Sigma0(a)
@@ -308,7 +320,7 @@
 	add	x27,x27,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x27,x27,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x12,x12			// 9
 #endif
 	ldp	x13,x14,[x1],#2*8
@@ -333,7 +345,7 @@
 	add	x26,x26,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x26,x26,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x13,x13			// 10
 #endif
 	add	x26,x26,x17			// h+=Sigma0(a)
@@ -357,7 +369,7 @@
 	add	x25,x25,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x25,x25,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x14,x14			// 11
 #endif
 	ldp	x15,x0,[x1],#2*8
@@ -383,7 +395,7 @@
 	add	x24,x24,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x24,x24,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x15,x15			// 12
 #endif
 	add	x24,x24,x17			// h+=Sigma0(a)
@@ -408,7 +420,7 @@
 	add	x23,x23,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x23,x23,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x0,x0			// 13
 #endif
 	ldp	x1,x2,[x1]
@@ -434,7 +446,7 @@
 	add	x22,x22,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x22,x22,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x1,x1			// 14
 #endif
 	ldr	x6,[sp,#24]
@@ -460,7 +472,7 @@
 	add	x21,x21,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x21,x21,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x2,x2			// 15
 #endif
 	ldr	x7,[sp,#0]
@@ -1078,4 +1090,525 @@
 .byte	83,72,65,53,49,50,32,98,108,111,99,107,32,116,114,97,110,115,102,111,114,109,32,102,111,114,32,65,82,77,118,56,44,32,67,82,89,80,84,79,71,65,77,83,32,98,121,32,60,97,112,112,114,111,64,111,112,101,110,115,115,108,46,111,114,103,62,0
 .align	2
 .align	2
+.text
+#ifndef	__KERNEL__
+
+.align	6
+sha512_block_armv8:
+Lv8_entry:
+	stp	x29,x30,[sp,#-16]!
+	add	x29,sp,#0
+
+	ld1	{v16.16b,v17.16b,v18.16b,v19.16b},[x1],#64	// load input
+	ld1	{v20.16b,v21.16b,v22.16b,v23.16b},[x1],#64
+
+	ld1	{v0.2d,v1.2d,v2.2d,v3.2d},[x0]		// load context
+	adrp	x3,LK512@PAGE
+	add	x3,x3,LK512@PAGEOFF
+
+	rev64	v16.16b,v16.16b
+	rev64	v17.16b,v17.16b
+	rev64	v18.16b,v18.16b
+	rev64	v19.16b,v19.16b
+	rev64	v20.16b,v20.16b
+	rev64	v21.16b,v21.16b
+	rev64	v22.16b,v22.16b
+	rev64	v23.16b,v23.16b
+	b	Loop_hw
+
+.align	4
+Loop_hw:
+	ld1	{v24.2d},[x3],#16
+	subs	x2,x2,#1
+	sub	x4,x1,#128
+	orr	v26.16b,v0.16b,v0.16b			// offload
+	orr	v27.16b,v1.16b,v1.16b
+	orr	v28.16b,v2.16b,v2.16b
+	orr	v29.16b,v3.16b,v3.16b
+	csel	x1,x1,x4,ne			// conditional rewind
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v16.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+	rev64	v16.16b,v16.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v17.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+	rev64	v17.16b,v17.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v18.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+	rev64	v18.16b,v18.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v19.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+	rev64	v19.16b,v19.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v20.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+	rev64	v20.16b,v20.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v21.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+	rev64	v21.16b,v21.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v22.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+	rev64	v22.16b,v22.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	sub	x3,x3,#80*8	// rewind
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v23.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+	rev64	v23.16b,v23.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v0.2d,v0.2d,v26.2d			// accumulate
+	add	v1.2d,v1.2d,v27.2d
+	add	v2.2d,v2.2d,v28.2d
+	add	v3.2d,v3.2d,v29.2d
+
+	cbnz	x2,Loop_hw
+
+	st1	{v0.2d,v1.2d,v2.2d,v3.2d},[x0]		// store context
+
+	ldr	x29,[sp],#16
+	ret
+
+#endif
 #endif  // !OPENSSL_NO_ASM
diff --git a/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha256-armv8.S b/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha256-armv8.S
index a4f170e..c777ec8 100644
--- a/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha256-armv8.S
+++ b/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha256-armv8.S
@@ -13,7 +13,7 @@
 #if defined(BORINGSSL_PREFIX)
 #include <boringssl_prefix_symbols_asm.h>
 #endif
-// Copyright 2014-2016 The OpenSSL Project Authors. All Rights Reserved.
+// Copyright 2014-2020 The OpenSSL Project Authors. All Rights Reserved.
 //
 // Licensed under the OpenSSL license (the "License").  You may not use
 // this file except in compliance with the License.  You can obtain a copy
@@ -41,6 +41,7 @@
 // Denver	2.01		10.5 (+26%)	6.70 (+8%)
 // X-Gene			20.0 (+100%)	12.8 (+300%(***))
 // Mongoose	2.36		13.0 (+50%)	8.36 (+33%)
+// Kryo		1.92		17.4 (+30%)	11.2 (+8%)
 //
 // (*)	Software SHA256 results are of lesser relevance, presented
 //	mostly for informational purposes.
@@ -49,7 +50,7 @@
 //	on Cortex-A53 (or by 4 cycles per round).
 // (***)	Super-impressive coefficients over gcc-generated code are
 //	indication of some compiler "pathology", most notably code
-//	generated with -mgeneral-regs-only is significanty faster
+//	generated with -mgeneral-regs-only is significantly faster
 //	and the gap is only 40-90%.
 
 #ifndef	__KERNEL__
@@ -101,7 +102,7 @@
 	ldr	w19,[x30],#4			// *K++
 	eor	w28,w21,w22				// magic seed
 	str	x1,[x29,#112]
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w3,w3			// 0
 #endif
 	ror	w16,w24,#6
@@ -124,7 +125,7 @@
 	add	w27,w27,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w27,w27,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w4,w4			// 1
 #endif
 	ldp	w5,w6,[x1],#2*4
@@ -149,7 +150,7 @@
 	add	w26,w26,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w26,w26,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w5,w5			// 2
 #endif
 	add	w26,w26,w17			// h+=Sigma0(a)
@@ -173,7 +174,7 @@
 	add	w25,w25,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w25,w25,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w6,w6			// 3
 #endif
 	ldp	w7,w8,[x1],#2*4
@@ -198,7 +199,7 @@
 	add	w24,w24,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w24,w24,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w7,w7			// 4
 #endif
 	add	w24,w24,w17			// h+=Sigma0(a)
@@ -222,7 +223,7 @@
 	add	w23,w23,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w23,w23,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w8,w8			// 5
 #endif
 	ldp	w9,w10,[x1],#2*4
@@ -247,7 +248,7 @@
 	add	w22,w22,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w22,w22,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w9,w9			// 6
 #endif
 	add	w22,w22,w17			// h+=Sigma0(a)
@@ -271,7 +272,7 @@
 	add	w21,w21,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w21,w21,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w10,w10			// 7
 #endif
 	ldp	w11,w12,[x1],#2*4
@@ -296,7 +297,7 @@
 	add	w20,w20,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w20,w20,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w11,w11			// 8
 #endif
 	add	w20,w20,w17			// h+=Sigma0(a)
@@ -320,7 +321,7 @@
 	add	w27,w27,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w27,w27,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w12,w12			// 9
 #endif
 	ldp	w13,w14,[x1],#2*4
@@ -345,7 +346,7 @@
 	add	w26,w26,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w26,w26,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w13,w13			// 10
 #endif
 	add	w26,w26,w17			// h+=Sigma0(a)
@@ -369,7 +370,7 @@
 	add	w25,w25,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w25,w25,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w14,w14			// 11
 #endif
 	ldp	w15,w0,[x1],#2*4
@@ -395,7 +396,7 @@
 	add	w24,w24,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w24,w24,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w15,w15			// 12
 #endif
 	add	w24,w24,w17			// h+=Sigma0(a)
@@ -420,7 +421,7 @@
 	add	w23,w23,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w23,w23,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w0,w0			// 13
 #endif
 	ldp	w1,w2,[x1]
@@ -446,7 +447,7 @@
 	add	w22,w22,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w22,w22,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w1,w1			// 14
 #endif
 	ldr	w6,[sp,#12]
@@ -472,7 +473,7 @@
 	add	w21,w21,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w21,w21,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w2,w2			// 15
 #endif
 	ldr	w7,[sp,#0]
diff --git a/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha512-armv8.S b/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha512-armv8.S
index 98b7a7e2..a3b458a 100644
--- a/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha512-armv8.S
+++ b/third_party/boringssl/linux-aarch64/crypto/fipsmodule/sha512-armv8.S
@@ -13,7 +13,7 @@
 #if defined(BORINGSSL_PREFIX)
 #include <boringssl_prefix_symbols_asm.h>
 #endif
-// Copyright 2014-2016 The OpenSSL Project Authors. All Rights Reserved.
+// Copyright 2014-2020 The OpenSSL Project Authors. All Rights Reserved.
 //
 // Licensed under the OpenSSL license (the "License").  You may not use
 // this file except in compliance with the License.  You can obtain a copy
@@ -41,6 +41,7 @@
 // Denver	2.01		10.5 (+26%)	6.70 (+8%)
 // X-Gene			20.0 (+100%)	12.8 (+300%(***))
 // Mongoose	2.36		13.0 (+50%)	8.36 (+33%)
+// Kryo		1.92		17.4 (+30%)	11.2 (+8%)
 //
 // (*)	Software SHA256 results are of lesser relevance, presented
 //	mostly for informational purposes.
@@ -49,7 +50,7 @@
 //	on Cortex-A53 (or by 4 cycles per round).
 // (***)	Super-impressive coefficients over gcc-generated code are
 //	indication of some compiler "pathology", most notably code
-//	generated with -mgeneral-regs-only is significanty faster
+//	generated with -mgeneral-regs-only is significantly faster
 //	and the gap is only 40-90%.
 
 #ifndef	__KERNEL__
@@ -65,6 +66,17 @@
 .type	sha512_block_data_order,%function
 .align	6
 sha512_block_data_order:
+	AARCH64_VALID_CALL_TARGET
+#ifndef	__KERNEL__
+#if __has_feature(hwaddress_sanitizer) && __clang_major__ >= 10
+	adrp	x16,:pg_hi21_nc:OPENSSL_armcap_P
+#else
+	adrp	x16,OPENSSL_armcap_P
+#endif
+	ldr	w16,[x16,:lo12:OPENSSL_armcap_P]
+	tst	w16,#ARMV8_SHA512
+	b.ne	.Lv8_entry
+#endif
 	AARCH64_SIGN_LINK_REGISTER
 	stp	x29,x30,[sp,#-128]!
 	add	x29,sp,#0
@@ -90,7 +102,7 @@
 	ldr	x19,[x30],#8			// *K++
 	eor	x28,x21,x22				// magic seed
 	str	x1,[x29,#112]
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x3,x3			// 0
 #endif
 	ror	x16,x24,#14
@@ -113,7 +125,7 @@
 	add	x27,x27,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x27,x27,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x4,x4			// 1
 #endif
 	ldp	x5,x6,[x1],#2*8
@@ -138,7 +150,7 @@
 	add	x26,x26,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x26,x26,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x5,x5			// 2
 #endif
 	add	x26,x26,x17			// h+=Sigma0(a)
@@ -162,7 +174,7 @@
 	add	x25,x25,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x25,x25,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x6,x6			// 3
 #endif
 	ldp	x7,x8,[x1],#2*8
@@ -187,7 +199,7 @@
 	add	x24,x24,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x24,x24,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x7,x7			// 4
 #endif
 	add	x24,x24,x17			// h+=Sigma0(a)
@@ -211,7 +223,7 @@
 	add	x23,x23,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x23,x23,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x8,x8			// 5
 #endif
 	ldp	x9,x10,[x1],#2*8
@@ -236,7 +248,7 @@
 	add	x22,x22,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x22,x22,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x9,x9			// 6
 #endif
 	add	x22,x22,x17			// h+=Sigma0(a)
@@ -260,7 +272,7 @@
 	add	x21,x21,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x21,x21,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x10,x10			// 7
 #endif
 	ldp	x11,x12,[x1],#2*8
@@ -285,7 +297,7 @@
 	add	x20,x20,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x20,x20,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x11,x11			// 8
 #endif
 	add	x20,x20,x17			// h+=Sigma0(a)
@@ -309,7 +321,7 @@
 	add	x27,x27,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x27,x27,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x12,x12			// 9
 #endif
 	ldp	x13,x14,[x1],#2*8
@@ -334,7 +346,7 @@
 	add	x26,x26,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x26,x26,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x13,x13			// 10
 #endif
 	add	x26,x26,x17			// h+=Sigma0(a)
@@ -358,7 +370,7 @@
 	add	x25,x25,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x25,x25,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x14,x14			// 11
 #endif
 	ldp	x15,x0,[x1],#2*8
@@ -384,7 +396,7 @@
 	add	x24,x24,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x24,x24,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x15,x15			// 12
 #endif
 	add	x24,x24,x17			// h+=Sigma0(a)
@@ -409,7 +421,7 @@
 	add	x23,x23,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x23,x23,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x0,x0			// 13
 #endif
 	ldp	x1,x2,[x1]
@@ -435,7 +447,7 @@
 	add	x22,x22,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x22,x22,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x1,x1			// 14
 #endif
 	ldr	x6,[sp,#24]
@@ -461,7 +473,7 @@
 	add	x21,x21,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x21,x21,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x2,x2			// 15
 #endif
 	ldr	x7,[sp,#0]
@@ -1079,6 +1091,527 @@
 .byte	83,72,65,53,49,50,32,98,108,111,99,107,32,116,114,97,110,115,102,111,114,109,32,102,111,114,32,65,82,77,118,56,44,32,67,82,89,80,84,79,71,65,77,83,32,98,121,32,60,97,112,112,114,111,64,111,112,101,110,115,115,108,46,111,114,103,62,0
 .align	2
 .align	2
+.text
+#ifndef	__KERNEL__
+.type	sha512_block_armv8,%function
+.align	6
+sha512_block_armv8:
+.Lv8_entry:
+	stp	x29,x30,[sp,#-16]!
+	add	x29,sp,#0
+
+	ld1	{v16.16b,v17.16b,v18.16b,v19.16b},[x1],#64	// load input
+	ld1	{v20.16b,v21.16b,v22.16b,v23.16b},[x1],#64
+
+	ld1	{v0.2d,v1.2d,v2.2d,v3.2d},[x0]		// load context
+	adrp	x3,.LK512
+	add	x3,x3,:lo12:.LK512
+
+	rev64	v16.16b,v16.16b
+	rev64	v17.16b,v17.16b
+	rev64	v18.16b,v18.16b
+	rev64	v19.16b,v19.16b
+	rev64	v20.16b,v20.16b
+	rev64	v21.16b,v21.16b
+	rev64	v22.16b,v22.16b
+	rev64	v23.16b,v23.16b
+	b	.Loop_hw
+
+.align	4
+.Loop_hw:
+	ld1	{v24.2d},[x3],#16
+	subs	x2,x2,#1
+	sub	x4,x1,#128
+	orr	v26.16b,v0.16b,v0.16b			// offload
+	orr	v27.16b,v1.16b,v1.16b
+	orr	v28.16b,v2.16b,v2.16b
+	orr	v29.16b,v3.16b,v3.16b
+	csel	x1,x1,x4,ne			// conditional rewind
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.inst	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.inst	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.inst	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.inst	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.inst	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.inst	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.inst	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.inst	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.inst	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.inst	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.inst	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.inst	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.inst	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.inst	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.inst	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.inst	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.inst	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.inst	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.inst	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.inst	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v16.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+	rev64	v16.16b,v16.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v17.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+	rev64	v17.16b,v17.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v18.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+	rev64	v18.16b,v18.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v19.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+	rev64	v19.16b,v19.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.inst	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v20.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+	rev64	v20.16b,v20.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.inst	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v21.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+	rev64	v21.16b,v21.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.inst	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v22.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+	rev64	v22.16b,v22.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.inst	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	sub	x3,x3,#80*8	// rewind
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v23.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.inst	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+	rev64	v23.16b,v23.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.inst	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v0.2d,v0.2d,v26.2d			// accumulate
+	add	v1.2d,v1.2d,v27.2d
+	add	v2.2d,v2.2d,v28.2d
+	add	v3.2d,v3.2d,v29.2d
+
+	cbnz	x2,.Loop_hw
+
+	st1	{v0.2d,v1.2d,v2.2d,v3.2d},[x0]		// store context
+
+	ldr	x29,[sp],#16
+	ret
+.size	sha512_block_armv8,.-sha512_block_armv8
+#endif
 #endif
 #endif  // !OPENSSL_NO_ASM
 .section	.note.GNU-stack,"",%progbits
diff --git a/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha256-armv8.S b/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha256-armv8.S
index 5f233f9c5..15970af 100644
--- a/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha256-armv8.S
+++ b/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha256-armv8.S
@@ -13,7 +13,7 @@
 #if defined(BORINGSSL_PREFIX)
 #include <boringssl_prefix_symbols_asm.h>
 #endif
-// Copyright 2014-2016 The OpenSSL Project Authors. All Rights Reserved.
+// Copyright 2014-2020 The OpenSSL Project Authors. All Rights Reserved.
 //
 // Licensed under the OpenSSL license (the "License").  You may not use
 // this file except in compliance with the License.  You can obtain a copy
@@ -41,6 +41,7 @@
 // Denver	2.01		10.5 (+26%)	6.70 (+8%)
 // X-Gene			20.0 (+100%)	12.8 (+300%(***))
 // Mongoose	2.36		13.0 (+50%)	8.36 (+33%)
+// Kryo		1.92		17.4 (+30%)	11.2 (+8%)
 //
 // (*)	Software SHA256 results are of lesser relevance, presented
 //	mostly for informational purposes.
@@ -49,7 +50,7 @@
 //	on Cortex-A53 (or by 4 cycles per round).
 // (***)	Super-impressive coefficients over gcc-generated code are
 //	indication of some compiler "pathology", most notably code
-//	generated with -mgeneral-regs-only is significanty faster
+//	generated with -mgeneral-regs-only is significantly faster
 //	and the gap is only 40-90%.
 
 #ifndef	__KERNEL__
@@ -103,7 +104,7 @@
 	ldr	w19,[x30],#4			// *K++
 	eor	w28,w21,w22				// magic seed
 	str	x1,[x29,#112]
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w3,w3			// 0
 #endif
 	ror	w16,w24,#6
@@ -126,7 +127,7 @@
 	add	w27,w27,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w27,w27,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w4,w4			// 1
 #endif
 	ldp	w5,w6,[x1],#2*4
@@ -151,7 +152,7 @@
 	add	w26,w26,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w26,w26,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w5,w5			// 2
 #endif
 	add	w26,w26,w17			// h+=Sigma0(a)
@@ -175,7 +176,7 @@
 	add	w25,w25,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w25,w25,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w6,w6			// 3
 #endif
 	ldp	w7,w8,[x1],#2*4
@@ -200,7 +201,7 @@
 	add	w24,w24,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w24,w24,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w7,w7			// 4
 #endif
 	add	w24,w24,w17			// h+=Sigma0(a)
@@ -224,7 +225,7 @@
 	add	w23,w23,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w23,w23,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w8,w8			// 5
 #endif
 	ldp	w9,w10,[x1],#2*4
@@ -249,7 +250,7 @@
 	add	w22,w22,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w22,w22,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w9,w9			// 6
 #endif
 	add	w22,w22,w17			// h+=Sigma0(a)
@@ -273,7 +274,7 @@
 	add	w21,w21,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w21,w21,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w10,w10			// 7
 #endif
 	ldp	w11,w12,[x1],#2*4
@@ -298,7 +299,7 @@
 	add	w20,w20,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w20,w20,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w11,w11			// 8
 #endif
 	add	w20,w20,w17			// h+=Sigma0(a)
@@ -322,7 +323,7 @@
 	add	w27,w27,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w27,w27,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w12,w12			// 9
 #endif
 	ldp	w13,w14,[x1],#2*4
@@ -347,7 +348,7 @@
 	add	w26,w26,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w26,w26,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w13,w13			// 10
 #endif
 	add	w26,w26,w17			// h+=Sigma0(a)
@@ -371,7 +372,7 @@
 	add	w25,w25,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w25,w25,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w14,w14			// 11
 #endif
 	ldp	w15,w0,[x1],#2*4
@@ -397,7 +398,7 @@
 	add	w24,w24,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w24,w24,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w15,w15			// 12
 #endif
 	add	w24,w24,w17			// h+=Sigma0(a)
@@ -422,7 +423,7 @@
 	add	w23,w23,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w23,w23,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w0,w0			// 13
 #endif
 	ldp	w1,w2,[x1]
@@ -448,7 +449,7 @@
 	add	w22,w22,w19			// h+=Maj(a,b,c)
 	ldr	w19,[x30],#4		// *K++, w28 in next round
 	//add	w22,w22,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w1,w1			// 14
 #endif
 	ldr	w6,[sp,#12]
@@ -474,7 +475,7 @@
 	add	w21,w21,w28			// h+=Maj(a,b,c)
 	ldr	w28,[x30],#4		// *K++, w19 in next round
 	//add	w21,w21,w17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	w2,w2			// 15
 #endif
 	ldr	w7,[sp,#0]
diff --git a/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha512-armv8.S b/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha512-armv8.S
index d01304f..b2b5a7e 100644
--- a/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha512-armv8.S
+++ b/third_party/boringssl/win-aarch64/crypto/fipsmodule/sha512-armv8.S
@@ -13,7 +13,7 @@
 #if defined(BORINGSSL_PREFIX)
 #include <boringssl_prefix_symbols_asm.h>
 #endif
-// Copyright 2014-2016 The OpenSSL Project Authors. All Rights Reserved.
+// Copyright 2014-2020 The OpenSSL Project Authors. All Rights Reserved.
 //
 // Licensed under the OpenSSL license (the "License").  You may not use
 // this file except in compliance with the License.  You can obtain a copy
@@ -41,6 +41,7 @@
 // Denver	2.01		10.5 (+26%)	6.70 (+8%)
 // X-Gene			20.0 (+100%)	12.8 (+300%(***))
 // Mongoose	2.36		13.0 (+50%)	8.36 (+33%)
+// Kryo		1.92		17.4 (+30%)	11.2 (+8%)
 //
 // (*)	Software SHA256 results are of lesser relevance, presented
 //	mostly for informational purposes.
@@ -49,7 +50,7 @@
 //	on Cortex-A53 (or by 4 cycles per round).
 // (***)	Super-impressive coefficients over gcc-generated code are
 //	indication of some compiler "pathology", most notably code
-//	generated with -mgeneral-regs-only is significanty faster
+//	generated with -mgeneral-regs-only is significantly faster
 //	and the gap is only 40-90%.
 
 #ifndef	__KERNEL__
@@ -67,6 +68,17 @@
 .endef
 .align	6
 sha512_block_data_order:
+	AARCH64_VALID_CALL_TARGET
+#ifndef	__KERNEL__
+#if __has_feature(hwaddress_sanitizer) && __clang_major__ >= 10
+	adrp	x16,:pg_hi21_nc:OPENSSL_armcap_P
+#else
+	adrp	x16,OPENSSL_armcap_P
+#endif
+	ldr	w16,[x16,:lo12:OPENSSL_armcap_P]
+	tst	w16,#ARMV8_SHA512
+	b.ne	Lv8_entry
+#endif
 	AARCH64_SIGN_LINK_REGISTER
 	stp	x29,x30,[sp,#-128]!
 	add	x29,sp,#0
@@ -92,7 +104,7 @@
 	ldr	x19,[x30],#8			// *K++
 	eor	x28,x21,x22				// magic seed
 	str	x1,[x29,#112]
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x3,x3			// 0
 #endif
 	ror	x16,x24,#14
@@ -115,7 +127,7 @@
 	add	x27,x27,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x27,x27,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x4,x4			// 1
 #endif
 	ldp	x5,x6,[x1],#2*8
@@ -140,7 +152,7 @@
 	add	x26,x26,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x26,x26,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x5,x5			// 2
 #endif
 	add	x26,x26,x17			// h+=Sigma0(a)
@@ -164,7 +176,7 @@
 	add	x25,x25,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x25,x25,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x6,x6			// 3
 #endif
 	ldp	x7,x8,[x1],#2*8
@@ -189,7 +201,7 @@
 	add	x24,x24,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x24,x24,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x7,x7			// 4
 #endif
 	add	x24,x24,x17			// h+=Sigma0(a)
@@ -213,7 +225,7 @@
 	add	x23,x23,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x23,x23,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x8,x8			// 5
 #endif
 	ldp	x9,x10,[x1],#2*8
@@ -238,7 +250,7 @@
 	add	x22,x22,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x22,x22,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x9,x9			// 6
 #endif
 	add	x22,x22,x17			// h+=Sigma0(a)
@@ -262,7 +274,7 @@
 	add	x21,x21,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x21,x21,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x10,x10			// 7
 #endif
 	ldp	x11,x12,[x1],#2*8
@@ -287,7 +299,7 @@
 	add	x20,x20,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x20,x20,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x11,x11			// 8
 #endif
 	add	x20,x20,x17			// h+=Sigma0(a)
@@ -311,7 +323,7 @@
 	add	x27,x27,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x27,x27,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x12,x12			// 9
 #endif
 	ldp	x13,x14,[x1],#2*8
@@ -336,7 +348,7 @@
 	add	x26,x26,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x26,x26,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x13,x13			// 10
 #endif
 	add	x26,x26,x17			// h+=Sigma0(a)
@@ -360,7 +372,7 @@
 	add	x25,x25,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x25,x25,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x14,x14			// 11
 #endif
 	ldp	x15,x0,[x1],#2*8
@@ -386,7 +398,7 @@
 	add	x24,x24,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x24,x24,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x15,x15			// 12
 #endif
 	add	x24,x24,x17			// h+=Sigma0(a)
@@ -411,7 +423,7 @@
 	add	x23,x23,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x23,x23,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x0,x0			// 13
 #endif
 	ldp	x1,x2,[x1]
@@ -437,7 +449,7 @@
 	add	x22,x22,x19			// h+=Maj(a,b,c)
 	ldr	x19,[x30],#8		// *K++, x28 in next round
 	//add	x22,x22,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x1,x1			// 14
 #endif
 	ldr	x6,[sp,#24]
@@ -463,7 +475,7 @@
 	add	x21,x21,x28			// h+=Maj(a,b,c)
 	ldr	x28,[x30],#8		// *K++, x19 in next round
 	//add	x21,x21,x17			// h+=Sigma0(a)
-#ifndef	__ARMEB__
+#ifndef	__AARCH64EB__
 	rev	x2,x2			// 15
 #endif
 	ldr	x7,[sp,#0]
@@ -1081,5 +1093,528 @@
 .byte	83,72,65,53,49,50,32,98,108,111,99,107,32,116,114,97,110,115,102,111,114,109,32,102,111,114,32,65,82,77,118,56,44,32,67,82,89,80,84,79,71,65,77,83,32,98,121,32,60,97,112,112,114,111,64,111,112,101,110,115,115,108,46,111,114,103,62,0
 .align	2
 .align	2
+.text
+#ifndef	__KERNEL__
+.def sha512_block_armv8
+   .type 32
+.endef
+.align	6
+sha512_block_armv8:
+Lv8_entry:
+	stp	x29,x30,[sp,#-16]!
+	add	x29,sp,#0
+
+	ld1	{v16.16b,v17.16b,v18.16b,v19.16b},[x1],#64	// load input
+	ld1	{v20.16b,v21.16b,v22.16b,v23.16b},[x1],#64
+
+	ld1	{v0.2d,v1.2d,v2.2d,v3.2d},[x0]		// load context
+	adrp	x3,LK512
+	add	x3,x3,:lo12:LK512
+
+	rev64	v16.16b,v16.16b
+	rev64	v17.16b,v17.16b
+	rev64	v18.16b,v18.16b
+	rev64	v19.16b,v19.16b
+	rev64	v20.16b,v20.16b
+	rev64	v21.16b,v21.16b
+	rev64	v22.16b,v22.16b
+	rev64	v23.16b,v23.16b
+	b	Loop_hw
+
+.align	4
+Loop_hw:
+	ld1	{v24.2d},[x3],#16
+	subs	x2,x2,#1
+	sub	x4,x1,#128
+	orr	v26.16b,v0.16b,v0.16b			// offload
+	orr	v27.16b,v1.16b,v1.16b
+	orr	v28.16b,v2.16b,v2.16b
+	orr	v29.16b,v3.16b,v3.16b
+	csel	x1,x1,x4,ne			// conditional rewind
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08230	//sha512su0 v16.16b,v17.16b
+	ext	v7.16b,v20.16b,v21.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678af0	//sha512su1 v16.16b,v23.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08251	//sha512su0 v17.16b,v18.16b
+	ext	v7.16b,v21.16b,v22.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678a11	//sha512su1 v17.16b,v16.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec08272	//sha512su0 v18.16b,v19.16b
+	ext	v7.16b,v22.16b,v23.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678a32	//sha512su1 v18.16b,v17.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08293	//sha512su0 v19.16b,v20.16b
+	ext	v7.16b,v23.16b,v16.16b,#8
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+.long	0xce678a53	//sha512su1 v19.16b,v18.16b,v7.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082b4	//sha512su0 v20.16b,v21.16b
+	ext	v7.16b,v16.16b,v17.16b,#8
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+.long	0xce678a74	//sha512su1 v20.16b,v19.16b,v7.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec082d5	//sha512su0 v21.16b,v22.16b
+	ext	v7.16b,v17.16b,v18.16b,#8
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+.long	0xce678a95	//sha512su1 v21.16b,v20.16b,v7.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v25.2d},[x3],#16
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xcec082f6	//sha512su0 v22.16b,v23.16b
+	ext	v7.16b,v18.16b,v19.16b,#8
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+.long	0xce678ab6	//sha512su1 v22.16b,v21.16b,v7.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v24.2d},[x3],#16
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xcec08217	//sha512su0 v23.16b,v16.16b
+	ext	v7.16b,v19.16b,v20.16b,#8
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+.long	0xce678ad7	//sha512su1 v23.16b,v22.16b,v7.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v16.2d
+	ld1	{v16.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+	rev64	v16.16b,v16.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v17.2d
+	ld1	{v17.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+	rev64	v17.16b,v17.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v18.2d
+	ld1	{v18.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+	rev64	v18.16b,v18.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v19.2d
+	ld1	{v19.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v2.16b,v3.16b,#8
+	ext	v6.16b,v1.16b,v2.16b,#8
+	add	v3.2d,v3.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a3	//sha512h v3.16b,v5.16b,v6.16b
+	rev64	v19.16b,v19.16b
+	add	v4.2d,v1.2d,v3.2d		// "D + T1"
+.long	0xce608423	//sha512h2 v3.16b,v1.16b,v0.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v20.2d
+	ld1	{v20.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v4.16b,v2.16b,#8
+	ext	v6.16b,v0.16b,v4.16b,#8
+	add	v2.2d,v2.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a2	//sha512h v2.16b,v5.16b,v6.16b
+	rev64	v20.16b,v20.16b
+	add	v1.2d,v0.2d,v2.2d		// "D + T1"
+.long	0xce638402	//sha512h2 v2.16b,v0.16b,v3.16b
+	ld1	{v24.2d},[x3],#16
+	add	v25.2d,v25.2d,v21.2d
+	ld1	{v21.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v1.16b,v4.16b,#8
+	ext	v6.16b,v3.16b,v1.16b,#8
+	add	v4.2d,v4.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a4	//sha512h v4.16b,v5.16b,v6.16b
+	rev64	v21.16b,v21.16b
+	add	v0.2d,v3.2d,v4.2d		// "D + T1"
+.long	0xce628464	//sha512h2 v4.16b,v3.16b,v2.16b
+	ld1	{v25.2d},[x3],#16
+	add	v24.2d,v24.2d,v22.2d
+	ld1	{v22.16b},[x1],#16		// load next input
+	ext	v24.16b,v24.16b,v24.16b,#8
+	ext	v5.16b,v0.16b,v1.16b,#8
+	ext	v6.16b,v2.16b,v0.16b,#8
+	add	v1.2d,v1.2d,v24.2d			// "T1 + H + K512[i]"
+.long	0xce6680a1	//sha512h v1.16b,v5.16b,v6.16b
+	rev64	v22.16b,v22.16b
+	add	v3.2d,v2.2d,v1.2d		// "D + T1"
+.long	0xce648441	//sha512h2 v1.16b,v2.16b,v4.16b
+	sub	x3,x3,#80*8	// rewind
+	add	v25.2d,v25.2d,v23.2d
+	ld1	{v23.16b},[x1],#16		// load next input
+	ext	v25.16b,v25.16b,v25.16b,#8
+	ext	v5.16b,v3.16b,v0.16b,#8
+	ext	v6.16b,v4.16b,v3.16b,#8
+	add	v0.2d,v0.2d,v25.2d			// "T1 + H + K512[i]"
+.long	0xce6680a0	//sha512h v0.16b,v5.16b,v6.16b
+	rev64	v23.16b,v23.16b
+	add	v2.2d,v4.2d,v0.2d		// "D + T1"
+.long	0xce618480	//sha512h2 v0.16b,v4.16b,v1.16b
+	add	v0.2d,v0.2d,v26.2d			// accumulate
+	add	v1.2d,v1.2d,v27.2d
+	add	v2.2d,v2.2d,v28.2d
+	add	v3.2d,v3.2d,v29.2d
+
+	cbnz	x2,Loop_hw
+
+	st1	{v0.2d,v1.2d,v2.2d,v3.2d},[x0]		// store context
+
+	ldr	x29,[sp],#16
+	ret
+
+#endif
 #endif
 #endif  // !OPENSSL_NO_ASM
diff --git a/third_party/crashpad/README.chromium b/third_party/crashpad/README.chromium
index ff83c0db..226d2dc 100644
--- a/third_party/crashpad/README.chromium
+++ b/third_party/crashpad/README.chromium
@@ -2,7 +2,7 @@
 Short Name: crashpad
 URL: https://crashpad.chromium.org/
 Version: unknown
-Revision: 0ea32e0c7bc2569e597e412a20151ad8a7e64623
+Revision: 23375ab37c3dee6f442bddbf13b84a15116bcd6e
 License: Apache 2.0
 License File: crashpad/LICENSE
 Security Critical: yes
diff --git a/third_party/crashpad/crashpad/DEPS b/third_party/crashpad/crashpad/DEPS
index e13bea8..73adbd44 100644
--- a/third_party/crashpad/crashpad/DEPS
+++ b/third_party/crashpad/crashpad/DEPS
@@ -36,10 +36,10 @@
       '5bcd8e3bb929714e031a542d303f818e5a5af45d',
   'crashpad/third_party/lss/lss':
       Var('chromium_git') + '/linux-syscall-support.git@' +
-      '7bde79cc274d06451bf65ae82c012a5d3e476b5a',
+      'e1e7b0ad8ee99a875b272c8e33e308472e897660',
   'crashpad/third_party/mini_chromium/mini_chromium':
       Var('chromium_git') + '/chromium/mini_chromium@' +
-      '502930381b23c5fa3911c8b82ec3e4ba6ceb3658',
+      'bbb68fcec19ff7c268fadeebd2ef79f7203fa2f2',
   'crashpad/third_party/libfuzzer/src':
       Var('chromium_git') + '/chromium/llvm-project/compiler-rt/lib/fuzzer.git@' +
       'fda403cf93ecb8792cb1d061564d89a6553ca020',
diff --git a/third_party/crashpad/crashpad/client/crash_report_database_generic.cc b/third_party/crashpad/crashpad/client/crash_report_database_generic.cc
index f5dfa89..754f578 100644
--- a/third_party/crashpad/crashpad/client/crash_report_database_generic.cc
+++ b/third_party/crashpad/crashpad/client/crash_report_database_generic.cc
@@ -18,9 +18,9 @@
 #include <sys/stat.h>
 #include <sys/types.h>
 
+#include <tuple>
 #include <utility>
 
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "build/build_config.h"
 #include "client/settings.h"
@@ -356,14 +356,14 @@
     return kFileSystemError;
   }
   // We've moved the report to pending, so it no longer needs to be removed.
-  ignore_result(report->file_remover_.release());
+  std::ignore = report->file_remover_.release();
 
   // Close all the attachments and disarm their removers too.
   for (auto& writer : report->attachment_writers_) {
     writer->Close();
   }
   for (auto& remover : report->attachment_removers_) {
-    ignore_result(remover.release());
+    std::ignore = remover.release();
   }
 
   *uuid = report->ReportID();
diff --git a/third_party/crashpad/crashpad/client/crash_report_database_mac.mm b/third_party/crashpad/crashpad/client/crash_report_database_mac.mm
index d1c0a3ed..52319be 100644
--- a/third_party/crashpad/crashpad/client/crash_report_database_mac.mm
+++ b/third_party/crashpad/crashpad/client/crash_report_database_mac.mm
@@ -25,8 +25,9 @@
 #include <unistd.h>
 #include <uuid/uuid.h>
 
+#include <tuple>
+
 #include "base/cxx17_backports.h"
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/mac/scoped_nsautorelease_pool.h"
 #include "base/posix/eintr_wrapper.h"
@@ -385,14 +386,14 @@
     PLOG(ERROR) << "rename " << path.value() << " to " << new_path.value();
     return kFileSystemError;
   }
-  ignore_result(report->file_remover_.release());
+  std::ignore = report->file_remover_.release();
 
   // Close all the attachments and disarm their removers too.
   for (auto& writer : report->attachment_writers_) {
     writer->Close();
   }
   for (auto& remover : report->attachment_removers_) {
-    ignore_result(remover.release());
+    std::ignore = remover.release();
   }
 
   Metrics::CrashReportPending(Metrics::PendingReportReason::kNewlyCreated);
diff --git a/third_party/crashpad/crashpad/client/crash_report_database_win.cc b/third_party/crashpad/crashpad/client/crash_report_database_win.cc
index 65feaa4..6331f650 100644
--- a/third_party/crashpad/crashpad/client/crash_report_database_win.cc
+++ b/third_party/crashpad/crashpad/client/crash_report_database_win.cc
@@ -21,9 +21,9 @@
 #include <time.h>
 #include <wchar.h>
 
+#include <tuple>
 #include <utility>
 
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/numerics/safe_math.h"
 #include "base/strings/utf_string_conversions.h"
@@ -735,14 +735,14 @@
                                     time(nullptr),
                                     ReportState::kPending));
 
-  ignore_result(report->file_remover_.release());
+  std::ignore = report->file_remover_.release();
 
   // Close all the attachments and disarm their removers too.
   for (auto& writer : report->attachment_writers_) {
     writer->Close();
   }
   for (auto& remover : report->attachment_removers_) {
-    ignore_result(remover.release());
+    std::ignore = remover.release();
   }
 
   *uuid = report->ReportID();
diff --git a/third_party/crashpad/crashpad/client/crashpad_client_mac.cc b/third_party/crashpad/crashpad/client/crashpad_client_mac.cc
index b4a365d..d25bfb7 100644
--- a/third_party/crashpad/crashpad/client/crashpad_client_mac.cc
+++ b/third_party/crashpad/crashpad/client/crashpad_client_mac.cc
@@ -21,9 +21,9 @@
 #include <stdint.h>
 
 #include <memory>
+#include <tuple>
 #include <utility>
 
-#include "base/ignore_result.h"
 #include "base/logging.h"
 #include "base/mac/mach_logging.h"
 #include "base/strings/stringprintf.h"
@@ -178,7 +178,7 @@
         handler_restarter->StartRestartThread(
             handler, database, metrics_dir, url, annotations, arguments)) {
       // The thread owns the object now.
-      ignore_result(handler_restarter.release());
+      std::ignore = handler_restarter.release();
     }
 
     // If StartRestartThread() failed, proceed without the ability to restart.
@@ -362,7 +362,7 @@
       return false;
     }
 
-    ignore_result(receive_right.release());
+    std::ignore = receive_right.release();
     return true;
   }
 
diff --git a/third_party/crashpad/crashpad/test/mac/mach_multiprocess.cc b/third_party/crashpad/crashpad/test/mac/mach_multiprocess.cc
index 91a06e3..5f1b3ac 100644
--- a/third_party/crashpad/crashpad/test/mac/mach_multiprocess.cc
+++ b/third_party/crashpad/crashpad/test/mac/mach_multiprocess.cc
@@ -19,9 +19,9 @@
 
 #include <memory>
 #include <string>
+#include <tuple>
 
 #include "base/auto_reset.h"
-#include "base/ignore_result.h"
 #include "base/mac/scoped_mach_port.h"
 #include "gtest/gtest.h"
 #include "test/errors.h"
@@ -212,7 +212,7 @@
   ScopedForbidReturn forbid_return;
 
   // local_port is not valid in the forked child process.
-  ignore_result(info_->local_port.release());
+  std::ignore = info_->local_port.release();
 
   info_->local_port.reset(NewMachPort(MACH_PORT_RIGHT_RECEIVE));
   ASSERT_NE(info_->local_port, kMachPortNull);
diff --git a/third_party/crashpad/crashpad/third_party/lss/lss.h b/third_party/crashpad/crashpad/third_party/lss/lss.h
index 2646b6c..0bdd381 100644
--- a/third_party/crashpad/crashpad/third_party/lss/lss.h
+++ b/third_party/crashpad/crashpad/third_party/lss/lss.h
@@ -20,7 +20,7 @@
 #elif defined(CRASHPAD_LSS_SOURCE_EMBEDDED)
 #include "third_party/lss/lss/linux_syscall_support.h"
 #elif defined(CRASHPAD_LSS_SOURCE_FUCHSIA)
-#include "../../../../third_party/lss/linux_syscall_support.h"
+#include "../../../../third_party/linux-syscall-support/linux_syscall_support.h"
 #else
 #error Unknown lss source
 #endif
diff --git a/third_party/crashpad/crashpad/util/BUILD.gn b/third_party/crashpad/crashpad/util/BUILD.gn
index 9f178d1..8251312 100644
--- a/third_party/crashpad/crashpad/util/BUILD.gn
+++ b/third_party/crashpad/crashpad/util/BUILD.gn
@@ -663,7 +663,7 @@
   if (crashpad_http_transport_impl == "socket") {
     sources += [ "net/http_transport_socket.cc" ]
     if (crashpad_use_boringssl_for_http_transport_socket) {
-      defines += [ "CRASHPAD_USE_BORINGSSL" ]
+      defines = [ "CRASHPAD_USE_BORINGSSL" ]
 
       if (crashpad_is_in_chromium || crashpad_is_in_fuchsia) {
         deps += [ "//third_party/boringssl" ]
diff --git a/third_party/crashpad/crashpad/util/mach/child_port_handshake.h b/third_party/crashpad/crashpad/util/mach/child_port_handshake.h
index c61f734..54168691 100644
--- a/third_party/crashpad/crashpad/util/mach/child_port_handshake.h
+++ b/third_party/crashpad/crashpad/util/mach/child_port_handshake.h
@@ -18,9 +18,9 @@
 #include <mach/mach.h>
 
 #include <string>
+#include <tuple>
 
 #include "base/files/scoped_file.h"
-#include "base/ignore_result.h"
 #include "util/mach/child_port_types.h"
 
 namespace crashpad {
@@ -124,7 +124,7 @@
 //!   // for use in the parent process.
 //!   if (child_port_handshake.RunClient(receive_right.get(),
 //!                                      MACH_MSG_TYPE_MOVE_RECEIVE)) {
-//!     ignore_result(receive_right.release());
+//!     std::ignore = receive_right.release();
 //!   }
 //! \endcode
 //!
diff --git a/third_party/crashpad/crashpad/util/mach/mach_message_test.cc b/third_party/crashpad/crashpad/util/mach/mach_message_test.cc
index 0bee04b..0c578b9 100644
--- a/third_party/crashpad/crashpad/util/mach/mach_message_test.cc
+++ b/third_party/crashpad/crashpad/util/mach/mach_message_test.cc
@@ -16,7 +16,8 @@
 
 #include <unistd.h>
 
-#include "base/ignore_result.h"
+#include <tuple>
+
 #include "base/mac/scoped_mach_port.h"
 #include "gtest/gtest.h"
 #include "test/mac/mach_errors.h"
@@ -154,7 +155,7 @@
   ASSERT_EQ(right_type,
             implicit_cast<mach_msg_type_name_t>(MACH_MSG_TYPE_PORT_SEND));
   EXPECT_TRUE(MachMessageDestroyReceivedPort(port, MACH_MSG_TYPE_PORT_RECEIVE));
-  ignore_result(receive.release());
+  std::ignore = receive.release();
   EXPECT_TRUE(MachMessageDestroyReceivedPort(port, MACH_MSG_TYPE_PORT_SEND));
 }
 
diff --git a/third_party/crashpad/crashpad/util/posix/close_stdio.cc b/third_party/crashpad/crashpad/util/posix/close_stdio.cc
index a8efc81..37c40a4 100644
--- a/third_party/crashpad/crashpad/util/posix/close_stdio.cc
+++ b/third_party/crashpad/crashpad/util/posix/close_stdio.cc
@@ -18,9 +18,10 @@
 #include <paths.h>
 #include <unistd.h>
 
+#include <tuple>
+
 #include "base/check.h"
 #include "base/files/scoped_file.h"
-#include "base/ignore_result.h"
 #include "base/posix/eintr_wrapper.h"
 
 namespace crashpad {
@@ -32,7 +33,7 @@
       HANDLE_EINTR(open(_PATH_DEVNULL, oflag | O_NOCTTY | O_CLOEXEC)));
   if (fd == desired_fd) {
     // Weird, but play along.
-    ignore_result(fd.release());
+    std::ignore = fd.release();
   } else {
     PCHECK(fd.get() >= 0) << "open";
     PCHECK(HANDLE_EINTR(dup2(fd.get(), desired_fd)) != -1) << "dup2";
diff --git a/third_party/crashpad/crashpad/util/stream/file_encoder.cc b/third_party/crashpad/crashpad/util/stream/file_encoder.cc
index 5cebbfcc..d39b5b09 100644
--- a/third_party/crashpad/crashpad/util/stream/file_encoder.cc
+++ b/third_party/crashpad/crashpad/util/stream/file_encoder.cc
@@ -15,8 +15,8 @@
 #include "util/stream/file_encoder.h"
 
 #include <memory>
+#include <tuple>
 
-#include "base/ignore_result.h"
 #include "util/file/file_io.h"
 #include "util/file/file_reader.h"
 #include "util/file/scoped_remove_file.h"
@@ -77,7 +77,7 @@
   if (!output->Flush())
     return false;
 
-  ignore_result(file_remover.release());
+  std::ignore = file_remover.release();
   return true;
 }
 
diff --git a/third_party/tflite/BUILD.gn b/third_party/tflite/BUILD.gn
index dd01620..8880e6b 100644
--- a/third_party/tflite/BUILD.gn
+++ b/third_party/tflite/BUILD.gn
@@ -414,8 +414,18 @@
     "src/tensorflow/lite/core/api/tensor_utils.cc",
     "src/tensorflow/lite/core/api/tensor_utils.h",
     "src/tensorflow/lite/core/subgraph.cc",
+    "src/tensorflow/lite/delegates/interpreter_utils.cc",
+    "src/tensorflow/lite/delegates/interpreter_utils.h",
     "src/tensorflow/lite/delegates/nnapi/nnapi_delegate.h",
     "src/tensorflow/lite/delegates/nnapi/nnapi_delegate_disabled.cc",
+    "src/tensorflow/lite/experimental/acceleration/configuration/delegate_registry.cc",
+    "src/tensorflow/lite/experimental/acceleration/configuration/delegate_registry.h",
+    "src/tensorflow/lite/experimental/acceleration/configuration/flatbuffer_to_proto.cc",
+    "src/tensorflow/lite/experimental/acceleration/configuration/flatbuffer_to_proto.h",
+    "src/tensorflow/lite/experimental/acceleration/configuration/proto_to_flatbuffer.cc",
+    "src/tensorflow/lite/experimental/acceleration/configuration/proto_to_flatbuffer.h",
+    "src/tensorflow/lite/experimental/acceleration/mini_benchmark/mini_benchmark.cc",
+    "src/tensorflow/lite/experimental/acceleration/mini_benchmark/mini_benchmark.h",
     "src/tensorflow/lite/experimental/resource/initialization_status.cc",
     "src/tensorflow/lite/experimental/resource/initialization_status.h",
     "src/tensorflow/lite/experimental/resource/lookup_interfaces.h",
@@ -474,7 +484,11 @@
   }
 
   if (is_ios) {
-    sources += [ "src/tensorflow/lite/minimal_logging_ios.cc" ]
+    sources += [
+      "src/tensorflow/lite/minimal_logging_ios.cc",
+      "src/tensorflow/lite/profiling/signpost_profiler.h",
+      "src/tensorflow/lite/profiling/signpost_profiler.mm",
+    ]
   } else if (is_android) {
     sources += [
       "src/tensorflow/lite/minimal_logging_android.cc",
diff --git a/third_party/tflite_support/BUILD.gn b/third_party/tflite_support/BUILD.gn
index cc651378..30f80c0b 100644
--- a/third_party/tflite_support/BUILD.gn
+++ b/third_party/tflite_support/BUILD.gn
@@ -16,13 +16,19 @@
 proto_library("tflite_support_proto") {
   proto_in_dir = "src"
   sources = [
+    "src/tensorflow_lite_support/cc/task/core/proto/base_options.proto",
     "src/tensorflow_lite_support/cc/task/core/proto/external_file.proto",
+    "src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options.proto",
+    "src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options.proto",
     "src/tensorflow_lite_support/cc/task/vision/proto/bounding_box.proto",
     "src/tensorflow_lite_support/cc/task/vision/proto/class.proto",
     "src/tensorflow_lite_support/cc/task/vision/proto/classifications.proto",
     "src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.proto",
   ]
   cc_generator_options = "lite=true:"
+
+  import_dirs = [ "//third_party/tflite/src" ]
+  proto_deps = [ "//third_party/tflite:tflite-config-proto" ]
 }
 
 config("tflite_support_flags") {
@@ -31,6 +37,9 @@
     "-Wno-extern-c-compat",
     "-Wno-implicit-function-declaration",
     "-Wno-sign-compare",
+    "-Wno-ignored-attributes",
+    "-Wno-deprecated-declarations",
+    "-Wno-unused-variable",
   ]
   if (!is_win) {
     cflags_cc = [ "-frtti" ]
@@ -51,15 +60,14 @@
   sources = [
     "src/tensorflow_lite_support/cc/common.cc",
     "src/tensorflow_lite_support/cc/common.h",
-    "src/tensorflow_lite_support/cc/port/default/statusor.cc",
-    "src/tensorflow_lite_support/cc/port/default/statusor.h",
-    "src/tensorflow_lite_support/cc/port/default/statusor_internals.h",
     "src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc",
     "src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h",
     "src/tensorflow_lite_support/cc/port/status_macros.h",
     "src/tensorflow_lite_support/cc/port/statusor.h",
     "src/tensorflow_lite_support/cc/task/core/base_task_api.h",
     "src/tensorflow_lite_support/cc/task/core/category.h",
+    "src/tensorflow_lite_support/cc/task/core/error_reporter.cc",
+    "src/tensorflow_lite_support/cc/task/core/error_reporter.h",
     "src/tensorflow_lite_support/cc/task/core/external_file_handler.cc",
     "src/tensorflow_lite_support/cc/task/core/external_file_handler.h",
     "src/tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h",
@@ -68,10 +76,15 @@
     "src/tensorflow_lite_support/cc/task/core/task_utils.h",
     "src/tensorflow_lite_support/cc/task/core/tflite_engine.cc",
     "src/tensorflow_lite_support/cc/task/core/tflite_engine.h",
-    "src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.cc",
-    "src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h",
+    "src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc",
+    "src/tensorflow_lite_support/cc/task/processor/image_preprocessor.h",
+    "src/tensorflow_lite_support/cc/task/processor/processor.cc",
+    "src/tensorflow_lite_support/cc/task/processor/processor.h",
+    "src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc",
+    "src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h",
     "src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc",
     "src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h",
+    "src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options_proto_inc.h",
     "src/tensorflow_lite_support/cc/task/vision/core/classification_head.cc",
     "src/tensorflow_lite_support/cc/task/vision/core/classification_head.h",
     "src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.cc",
@@ -126,8 +139,10 @@
   configs -= [ "//build/config/compiler:chromium_code" ]
 
   configs += [
-    ":tflite_support_flags",
     "//build/config/compiler:no_chromium_code",
+
+    # Must be after no_chromium_code for warning flags to be ordered correctly.
+    ":tflite_support_flags",
   ]
 
   public_configs = [ ":tflite_support_config" ]
diff --git a/third_party/tflite_support/README.chromium b/third_party/tflite_support/README.chromium
index d60ea916..4995893e 100644
--- a/third_party/tflite_support/README.chromium
+++ b/third_party/tflite_support/README.chromium
@@ -1,8 +1,8 @@
 Name: TensorFlow Lite Support
 Short Name: tflite-support
 URL: https://github.com/tensorflow/tflite-support
-Version: 3faaca9c6a3b22dec4d636b6b092431c9ac409e8
-Date: 2021/01/05
+Version: v0.3.1
+Date: 2021/12/16
 License: Apache 2.0
 License File: LICENSE
 Security Critical: Yes
@@ -13,27 +13,32 @@
 models onto mobile devices.  It works cross-Platform and is supported on
 Java, C++ (WIP), and Swift (WIP).
 
-Modifications:
-- Use chromium's logging utility in place of glog (patches/0001-use-base-logging.patch)
-- Use size_t rather than int for loops according to chromium style (0001-use-size_t.patch)
-- Rely on re::StringPiece instead of absl::string_view (0001-use_StringPiece-for_string_view.patch)
-- Remove unsafe use of conversions between NSString and string by using SysNSStringToUTF8. Note, this
-  is unused code but required for presubmit checks. (0001-use-SysNSStringToUTF8.patch)
-- Remove usage of absl::Cord in tflite::support::CreateStatusWithPayload (0001-no-absl-cord.patch)
-- Use _Exit instead of _exit to work on all platforms (0001-use-exit.patch)
-- Remove external file handlers support for memory mapping files to support Windows
-  (0001-remove-unsupported-memory-map-from-file-handler.patch)
-- Fixes sign compare issues in tflite-support (0001-task-utils-sign-compare.patch)
-- Remove support for sentencepiece tokenizers (0001-no-sentencepiece-tokenizer.patch)
-- Allows for the max sequence used by BERT models to be 512 instead of 128 (0001-bert-max-seq-len.patch)
-- Ensure name field in metadata exists before checking for tflite metadata (0001-add-metadata-name-check.patch)
-
 Third party dependencies:
 - tflite
 - libzip
 - utf
 - tensorflow-text
 
+Modifications:
+01) Use re2::StringPiece instead of absl::string_view in regex_tokenizer.cc
+02) Remove support for sentencepiece tokenization because the required overhead
+isn't worth adding this functionality, esp since no feature team needs it.
+03) [To Be Upstreamed] Remove unused functions.
+04) Remove the ABSL_DEPRECATED annotation from a deprecated struct since this
+is a no-op in chromium builds and upsets clang.
+05) [To Be Upstreamed] Use size_t in for loop in nl_classifier.h
+06) [To Be Upstreamed] Remove unused variable in task_utils.h
+07) Do not use absl::any since it is not supported in chromium
+08) [To Be Upstreamed] Remove unused stl include in tokenizer_jni_lib.h
+09) Remove unbuilt files that triggered checkdeps warnings, and fix file perms.
+10) Remove memory mapped file support in external_file_handler.cc since it is
+only available on POSIX systems.
+11) Run clang-format.
+12) Remove an unneeded static initializer.
+
 Update Process:
 1) Clone the tflite-support github repo at the desired commit into src/
 2) Apply each patch listed above residing in patches/ using `git apply patches/$PATCHFILE`
+3) Get the build working.
+4) Record the patches made with `git format-patches HEAD -<number of changes>`
+
diff --git a/third_party/tflite_support/patches/0001-Fix-signed-comparison-in-base_vision_task_api.h.patch b/third_party/tflite_support/patches/0001-Fix-signed-comparison-in-base_vision_task_api.h.patch
deleted file mode 100644
index 6a56310a..0000000
--- a/third_party/tflite_support/patches/0001-Fix-signed-comparison-in-base_vision_task_api.h.patch
+++ /dev/null
@@ -1,34 +0,0 @@
-From c8bdfe3f6b3ce087c36b551d668b97101f620bdc Mon Sep 17 00:00:00 2001
-From: Daniel Rubery <drubery@chromium.org>
-Date: Thu, 6 May 2021 11:45:48 -0700
-Subject: [PATCH] Fix signed comparison in base_vision_task_api.h
-
----
- .../cc/task/vision/core/base_vision_task_api.h                | 4 ++--
- 1 file changed, 2 insertions(+), 2 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
-index 3d1359685f3f..c787876bec33 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
-@@ -204,7 +204,7 @@ class BaseVisionTaskApi
-         if (normalization_options.num_values == 1) {
-           float mean_value = normalization_options.mean_values[0];
-           float inv_std_value = (1.0f / normalization_options.std_values[0]);
--          for (int i = 0; i < input_data_byte_size / sizeof(uint8);
-+          for (size_t i = 0; i < input_data_byte_size / sizeof(uint8);
-                i++, input_data++, normalized_input_data++) {
-             *normalized_input_data =
-                 inv_std_value * (static_cast<float>(*input_data) - mean_value);
-@@ -214,7 +214,7 @@ class BaseVisionTaskApi
-               1.0f / normalization_options.std_values[0],
-               1.0f / normalization_options.std_values[1],
-               1.0f / normalization_options.std_values[2]};
--          for (int i = 0; i < input_data_byte_size / sizeof(uint8);
-+          for (size_t i = 0; i < input_data_byte_size / sizeof(uint8);
-                i++, input_data++, normalized_input_data++) {
-             *normalized_input_data = inv_std_values[i % 3] *
-                                      (static_cast<float>(*input_data) -
--- 
-2.31.1.607.g51e8a6a459-goog
-
diff --git a/third_party/tflite_support/patches/0001-Remove-signed-comparison-in-frame_buffer.h.patch b/third_party/tflite_support/patches/0001-Remove-signed-comparison-in-frame_buffer.h.patch
deleted file mode 100644
index 757ec2e6..0000000
--- a/third_party/tflite_support/patches/0001-Remove-signed-comparison-in-frame_buffer.h.patch
+++ /dev/null
@@ -1,25 +0,0 @@
-From 368b317061ba7deb1f42c52c5443c261bb6c03ea Mon Sep 17 00:00:00 2001
-From: Daniel Rubery <drubery@chromium.org>
-Date: Thu, 6 May 2021 11:40:37 -0700
-Subject: [PATCH] Remove signed comparison in frame_buffer.h
-
----
- .../tensorflow_lite_support/cc/task/vision/core/frame_buffer.h  | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-index 22f63fc34d36..42ac080c4749 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-@@ -246,7 +246,7 @@ class FrameBuffer {
- 
-   // Returns plane indexed by the input `index`.
-   const Plane plane(int index) const {
--    if (index > -1 && index < planes_.size()) {
-+    if (index > -1 && static_cast<size_t>(index) < planes_.size()) {
-       return planes_[index];
-     }
-     return {};
--- 
-2.31.1.607.g51e8a6a459-goog
-
diff --git a/third_party/tflite_support/patches/0001-Remove-unused-qualifiers-in-frame_buffer.h.patch b/third_party/tflite_support/patches/0001-Remove-unused-qualifiers-in-frame_buffer.h.patch
deleted file mode 100644
index d80bdd1..0000000
--- a/third_party/tflite_support/patches/0001-Remove-unused-qualifiers-in-frame_buffer.h.patch
+++ /dev/null
@@ -1,38 +0,0 @@
-From b23fcde4753dbf5e4adc325e9ded16800f1d1bc5 Mon Sep 17 00:00:00 2001
-From: Daniel Rubery <drubery@chromium.org>
-Date: Thu, 6 May 2021 11:38:06 -0700
-Subject: [PATCH] Remove unused qualifiers in frame_buffer.h
-
----
- .../cc/task/vision/core/frame_buffer.h                      | 6 +++---
- 1 file changed, 3 insertions(+), 3 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-index 1556b7dfabef..22f63fc34d36 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-@@ -242,7 +242,7 @@ class FrameBuffer {
-         timestamp_(timestamp) {}
- 
-   // Returns number of planes.
--  const int plane_count() const { return planes_.size(); }
-+  int plane_count() const { return planes_.size(); }
- 
-   // Returns plane indexed by the input `index`.
-   const Plane plane(int index) const {
-@@ -256,10 +256,10 @@ class FrameBuffer {
-   const Dimension dimension() const { return dimension_; }
- 
-   // Returns FrameBuffer format.
--  const Format format() const { return format_; }
-+  Format format() const { return format_; }
- 
-   // Returns FrameBuffer orientation.
--  const Orientation orientation() const { return orientation_; }
-+  Orientation orientation() const { return orientation_; }
- 
-   // Returns FrameBuffer timestamp.
-   const absl::Time timestamp() const { return timestamp_; }
--- 
-2.31.1.607.g51e8a6a459-goog
-
diff --git a/third_party/tflite_support/patches/0001-Remove-use-of-banned-absl-any.patch b/third_party/tflite_support/patches/0001-Remove-use-of-banned-absl-any.patch
deleted file mode 100644
index fdd6997b..0000000
--- a/third_party/tflite_support/patches/0001-Remove-use-of-banned-absl-any.patch
+++ /dev/null
@@ -1,64 +0,0 @@
-From 670dfffa386fd0ff28e66cfe1238af43b4e587ce Mon Sep 17 00:00:00 2001
-From: Daniel Rubery <drubery@chromium.org>
-Date: Thu, 6 May 2021 11:22:13 -0700
-Subject: [PATCH] Remove use of banned absl::any
-
----
- .../cc/task/vision/core/frame_buffer.h        | 27 -------------------
- 1 file changed, 27 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-index 2bea92883c4d..1556b7dfabef 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
-@@ -27,7 +27,6 @@ limitations under the License.
- #include "absl/strings/str_cat.h"
- #include "absl/time/clock.h"
- #include "absl/time/time.h"
--#include "absl/types/any.h"
- #include "absl/types/optional.h"
- #include "tensorflow_lite_support/cc/port/integral_types.h"
- #include "tensorflow_lite_support/cc/port/statusor.h"
-@@ -253,31 +252,6 @@ class FrameBuffer {
-     return {};
-   }
- 
--  // Returns the tag associated to the tag_key.
--  absl::any GetTag(const std::string& tag_key) const {
--    auto iter = tags_.find(tag_key);
--    if (iter != tags_.end()) {
--      return iter->second;
--    }
--    return absl::any();
--  }
--
--  // Inserts or updates the tags map with key value pair (tag_key, tag_value).
--  void InsertOrUpdateTag(const std::string& tag_key, absl::any tag_value) {
--    tags_[tag_key] = std::move(tag_value);
--  }
--
--  // Inserts the key value pair (tag_key, tag_value) into tags map. If the
--  // tag_key already exists, an internal error will return.
--  absl::Status InsertTag(const std::string& tag_key, absl::any tag_value) {
--    auto iter = tags_.emplace(tag_key, tag_value);
--    if (iter.second) {
--      return absl::OkStatus();
--    }
--    return absl::InternalError(absl::StrCat(
--        "tag_key already exists in tags.tag_key was not inserted: ", tag_key));
--  }
--
-   // Returns FrameBuffer dimension.
-   const Dimension dimension() const { return dimension_; }
- 
-@@ -292,7 +266,6 @@ class FrameBuffer {
- 
-  private:
-   std::vector<Plane> planes_;
--  std::map<std::string, absl::any> tags_;
-   Dimension dimension_;
-   Format format_;
-   Orientation orientation_;
--- 
-2.31.1.607.g51e8a6a459-goog
-
diff --git a/third_party/tflite_support/patches/0001-Use-third_party-libyuv.patch b/third_party/tflite_support/patches/0001-Use-third_party-libyuv.patch
deleted file mode 100644
index 1210ba8..0000000
--- a/third_party/tflite_support/patches/0001-Use-third_party-libyuv.patch
+++ /dev/null
@@ -1,30 +0,0 @@
-From 226d36a5d12ca3080b1d0d9b450be949e418e318 Mon Sep 17 00:00:00 2001
-From: Daniel Rubery <drubery@chromium.org>
-Date: Thu, 6 May 2021 11:26:23 -0700
-Subject: [PATCH] Use third_party/libyuv
-
----
- .../cc/task/vision/utils/libyuv_frame_buffer_utils.cc           | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
-index f3cd0c70fe1b..b50b500bb5a4 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
-@@ -23,12 +23,12 @@ limitations under the License.
- #include "absl/status/status.h"
- #include "absl/strings/str_cat.h"
- #include "absl/strings/str_format.h"
--#include "include/libyuv.h"
- #include "tensorflow_lite_support/cc/common.h"
- #include "tensorflow_lite_support/cc/port/integral_types.h"
- #include "tensorflow_lite_support/cc/port/status_macros.h"
- #include "tensorflow_lite_support/cc/port/statusor.h"
- #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
-+#include "third_party/libyuv/include/libyuv.h"
- 
- namespace tflite {
- namespace task {
--- 
-2.31.1.607.g51e8a6a459-goog
-
diff --git a/third_party/tflite_support/patches/0001-add-metadata-name-check.patch b/third_party/tflite_support/patches/0001-add-metadata-name-check.patch
deleted file mode 100644
index fd2b258..0000000
--- a/third_party/tflite_support/patches/0001-add-metadata-name-check.patch
+++ /dev/null
@@ -1,28 +0,0 @@
-From 5e3e4b63a6bfd871afa16f8d27f2daa8b99d84e9 Mon Sep 17 00:00:00 2001
-From: mcrouse <mcrouse@google.com>
-Date: Thu, 19 Aug 2021 11:31:28 -0700
-Subject: [PATCH] add metadata name check
-
----
- .../metadata/cc/metadata_extractor.cc                        | 5 ++++-
- 1 file changed, 4 insertions(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc b/third_party/tflite-support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
-index ad5df76f1c27b..42f2a7c13a516 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
-@@ -159,7 +159,10 @@ absl::Status ModelMetadataExtractor::InitFromModelBuffer(
-   // Look for the "TFLITE_METADATA" field, if any.
-   for (int i = 0; i < model_->metadata()->size(); ++i) {
-     const auto metadata = model_->metadata()->Get(i);
--    if (metadata->name() && metadata->name()->str() != kMetadataBufferName) {
-+    if (!metadata->name()) {
-+      continue;
-+    }
-+    if (metadata->name()->str() != kMetadataBufferName) {
-       continue;
-     }
-     const auto buffer_index = metadata->buffer();
--- 
-2.33.0.rc2.250.ged5fa647cd-goog
-
diff --git a/third_party/tflite_support/patches/0001-bert-max-seq-len.patch b/third_party/tflite_support/patches/0001-bert-max-seq-len.patch
deleted file mode 100644
index d984907b..0000000
--- a/third_party/tflite_support/patches/0001-bert-max-seq-len.patch
+++ /dev/null
@@ -1,25 +0,0 @@
-From 49cd597b3c1fbfef2e3772682aa98575654131ba Mon Sep 17 00:00:00 2001
-From: Sophie Chang <sophiechang@chromium.org>
-Date: Mon, 1 Mar 2021 19:33:21 +0000
-Subject: [PATCH] allow for more tokens
-
----
- .../cc/task/text/nlclassifier/bert_nl_classifier.h              | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h
-index cd5c5a3ade03..e78085d98761 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h
-@@ -52,7 +52,7 @@ class BertNLClassifier : public NLClassifier {
-  public:
-   using NLClassifier::NLClassifier;
-   // Max number of tokens to pass to the model.
--  static constexpr int kMaxSeqLen = 128;
-+  static constexpr int kMaxSeqLen = 512;
- 
-   // Factory function to create a BertNLClassifier from TFLite model with
-   // metadata.
--- 
-2.30.1.766.gb4fecdf3b7-goog
-
diff --git a/third_party/tflite_support/patches/0001-no-absl-cord.patch b/third_party/tflite_support/patches/0001-no-absl-cord.patch
deleted file mode 100644
index 5f18f38..0000000
--- a/third_party/tflite_support/patches/0001-no-absl-cord.patch
+++ /dev/null
@@ -1,33 +0,0 @@
-From 61fb20a08d2325d03759a5b9394c033901fc0a7f Mon Sep 17 00:00:00 2001
-From: Sophie Chang <sophiechang@chromium.org>
-Date: Wed, 3 Feb 2021 04:21:19 +0000
-Subject: [PATCH] do not use cord in tflite status payload
-
----
- .../tflite-support/src/tensorflow_lite_support/cc/common.cc    | 3 ---
- 1 file changed, 3 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/common.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/common.cc
-index 47dd3bcc6581..ed373e96d555 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/common.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/common.cc
-@@ -15,7 +15,6 @@ limitations under the License.
- 
- #include "tensorflow_lite_support/cc/common.h"
- 
--#include "absl/strings/cord.h"
- #include "absl/strings/str_cat.h"
- 
- namespace tflite {
-@@ -26,8 +25,6 @@ absl::Status CreateStatusWithPayload(absl::StatusCode canonical_code,
-                                      TfLiteSupportStatus tfls_code) {
-   // NOTE: Ignores `message` if the canonical code is ok.
-   absl::Status status = absl::Status(canonical_code, message);
--  // NOTE: Does nothing if the canonical code is ok.
--  status.SetPayload(kTfLiteSupportPayload, absl::Cord(absl::StrCat(tfls_code)));
-   return status;
- }
- 
--- 
-2.30.0.365.g02bc693789-goog
-
diff --git a/third_party/tflite_support/patches/0001-no-sentencepiece-tokenizer.patch b/third_party/tflite_support/patches/0001-no-sentencepiece-tokenizer.patch
deleted file mode 100644
index df91f5c..0000000
--- a/third_party/tflite_support/patches/0001-no-sentencepiece-tokenizer.patch
+++ /dev/null
@@ -1,40 +0,0 @@
-From 7faac3ddcbc05275d797dda64a9b9d7f2279ae1c Mon Sep 17 00:00:00 2001
-From: Sophie Chang <sophiechang@chromium.org>
-Date: Thu, 11 Feb 2021 00:53:47 +0000
-Subject: [PATCH] no sentencepiece tokenizer
-
----
- .../cc/text/tokenizers/tokenizer_utils.cc             | 11 -----------
- 1 file changed, 11 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
-index 352c4a8c5e4f..46786fd7faf8 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
-@@ -20,7 +20,6 @@ limitations under the License.
- #include "tensorflow_lite_support/cc/port/status_macros.h"
- #include "tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h"
- #include "tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h"
--#include "tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h"
- #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
- 
- namespace tflite {
-@@ -73,16 +72,6 @@ StatusOr<std::unique_ptr<Tokenizer>> CreateTokenizerFromProcessUnit(
-       return absl::make_unique<BertTokenizer>(vocab_buffer.data(),
-                                               vocab_buffer.size());
-     }
--    case ProcessUnitOptions_SentencePieceTokenizerOptions: {
--      const tflite::SentencePieceTokenizerOptions* options =
--          tokenizer_process_unit->options_as<SentencePieceTokenizerOptions>();
--      ASSIGN_OR_RETURN(absl::string_view model_buffer,
--                       CheckAndLoadFirstAssociatedFile(
--                           options->sentencePiece_model(), metadata_extractor));
--      // TODO(b/160647204): Extract sentence piece model vocabulary
--      return absl::make_unique<SentencePieceTokenizer>(model_buffer.data(),
--                                                       model_buffer.size());
--    }
-     case ProcessUnitOptions_RegexTokenizerOptions: {
-       const tflite::RegexTokenizerOptions* options =
-           tokenizer_process_unit->options_as<RegexTokenizerOptions>();
--- 
-2.30.0.478.g8a0d178c01-goog
diff --git a/third_party/tflite_support/patches/0001-remove-unsupported-memory-map-from-file-handler.patch b/third_party/tflite_support/patches/0001-remove-unsupported-memory-map-from-file-handler.patch
deleted file mode 100644
index 55c2e7b..0000000
--- a/third_party/tflite_support/patches/0001-remove-unsupported-memory-map-from-file-handler.patch
+++ /dev/null
@@ -1,224 +0,0 @@
-From 8c5a37f7324b4a03f123c6faecedb4abc8eb0066 Mon Sep 17 00:00:00 2001
-From: mcrouse <mcrouse@google.com>
-Date: Fri, 5 Feb 2021 15:30:25 +0000
-Subject: [PATCH] remove unsupported memory map from file handler
-
----
- .../cc/task/core/external_file_handler.cc     | 126 +-----------------
- .../cc/task/core/external_file_handler.h      |   7 -
- .../cc/task/core/tflite_engine.cc             |   2 -
- .../cc/task/core/tflite_engine.h              |   2 -
- 4 files changed, 6 insertions(+), 131 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
-index ee689e41c6e5..55b662f0926f 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
-@@ -18,9 +18,6 @@ limitations under the License.
- #include <errno.h>
- #include <fcntl.h>
- #include <stddef.h>
--#include <sys/mman.h>
--#include <unistd.h>
--
- #include <memory>
- #include <string>
- 
-@@ -40,18 +37,6 @@ using ::tflite::support::CreateStatusWithPayload;
- using ::tflite::support::StatusOr;
- using ::tflite::support::TfLiteSupportStatus;
- 
--// Gets the offset aligned to page size for mapping given files into memory by
--// file descriptor correctly, as according to mmap(2), the offset used in mmap
--// must be a multiple of sysconf(_SC_PAGE_SIZE).
--int64 GetPageSizeAlignedOffset(int64 offset) {
--  int64 aligned_offset = offset;
--  int64 page_size = sysconf(_SC_PAGE_SIZE);
--  if (offset % page_size != 0) {
--    aligned_offset = offset / page_size * page_size;
--  }
--  return aligned_offset;
--}
--
- }  // namespace
- 
- /* static */
-@@ -71,103 +56,11 @@ absl::Status ExternalFileHandler::MapExternalFile() {
-   if (!external_file_.file_content().empty()) {
-     return absl::OkStatus();
-   }
--  if (external_file_.file_name().empty() &&
--      !external_file_.has_file_descriptor_meta()) {
--    return CreateStatusWithPayload(
--        StatusCode::kInvalidArgument,
--        "ExternalFile must specify at least one of 'file_content', file_name' "
--        "or 'file_descriptor_meta'.",
--        TfLiteSupportStatus::kInvalidArgumentError);
--  }
--  // Obtain file descriptor, offset and size.
--  int fd = -1;
--  if (!external_file_.file_name().empty()) {
--    owned_fd_ = open(external_file_.file_name().c_str(), O_RDONLY);
--    if (owned_fd_ < 0) {
--      const std::string error_message = absl::StrFormat(
--          "Unable to open file at %s", external_file_.file_name());
--      switch (errno) {
--        case ENOENT:
--          return CreateStatusWithPayload(
--              StatusCode::kNotFound, error_message,
--              TfLiteSupportStatus::kFileNotFoundError);
--        case EACCES:
--        case EPERM:
--          return CreateStatusWithPayload(
--              StatusCode::kPermissionDenied, error_message,
--              TfLiteSupportStatus::kFilePermissionDeniedError);
--        case EINTR:
--          return CreateStatusWithPayload(StatusCode::kUnavailable,
--                                         error_message,
--                                         TfLiteSupportStatus::kFileReadError);
--        case EBADF:
--          return CreateStatusWithPayload(StatusCode::kFailedPrecondition,
--                                         error_message,
--                                         TfLiteSupportStatus::kFileReadError);
--        default:
--          return CreateStatusWithPayload(
--              StatusCode::kUnknown,
--              absl::StrFormat("%s, errno=%d", error_message, errno),
--              TfLiteSupportStatus::kFileReadError);
--      }
--    }
--    fd = owned_fd_;
--  } else {
--    fd = external_file_.file_descriptor_meta().fd();
--    if (fd < 0) {
--      return CreateStatusWithPayload(
--          StatusCode::kInvalidArgument,
--          absl::StrFormat("Provided file descriptor is invalid: %d < 0", fd),
--          TfLiteSupportStatus::kInvalidArgumentError);
--    }
--    buffer_offset_ = external_file_.file_descriptor_meta().offset();
--    buffer_size_ = external_file_.file_descriptor_meta().length();
--  }
--  // Get actual file size. Always use 0 as offset to lseek(2) to get the actual
--  // file size, as SEEK_END returns the size of the file *plus* offset.
--  size_t file_size = lseek(fd, /*offset=*/0, SEEK_END);
--  if (file_size <= 0) {
--    return CreateStatusWithPayload(
--        StatusCode::kUnknown,
--        absl::StrFormat("Unable to get file size, errno=%d", errno),
--        TfLiteSupportStatus::kFileReadError);
--  }
--  // Deduce buffer size if not explicitly provided through file descriptor.
--  if (buffer_size_ <= 0) {
--    buffer_size_ = file_size - buffer_offset_;
--  }
--  // Check for out of range issues.
--  if (file_size <= buffer_offset_) {
--    return CreateStatusWithPayload(
--        StatusCode::kInvalidArgument,
--        absl::StrFormat("Provided file offset (%d) exceeds or matches actual "
--                        "file length (%d)",
--                        buffer_offset_, file_size),
--        TfLiteSupportStatus::kInvalidArgumentError);
--  }
--  if (file_size < buffer_size_ + buffer_offset_) {
--    return CreateStatusWithPayload(
--        StatusCode::kInvalidArgument,
--        absl::StrFormat("Provided file length + offset (%d) exceeds actual "
--                        "file length (%d)",
--                        buffer_size_ + buffer_offset_, file_size),
--        TfLiteSupportStatus::kInvalidArgumentError);
--  }
--  // If buffer_offset_ is not multiple of sysconf(_SC_PAGE_SIZE), align with
--  // extra leading bytes and adjust buffer_size_ to account for the extra
--  // leading bytes.
--  buffer_aligned_offset_ = GetPageSizeAlignedOffset(buffer_offset_);
--  buffer_aligned_size_ = buffer_size_ + buffer_offset_ - buffer_aligned_offset_;
--  // Map into memory.
--  buffer_ = mmap(/*addr=*/nullptr, buffer_aligned_size_, PROT_READ, MAP_SHARED,
--                 fd, buffer_aligned_offset_);
--  if (buffer_ == MAP_FAILED) {
--    return CreateStatusWithPayload(
--        StatusCode::kUnknown,
--        absl::StrFormat("Unable to map file to memory buffer, errno=%d", errno),
--        TfLiteSupportStatus::kFileMmapError);
--  }
--  return absl::OkStatus();
-+  return CreateStatusWithPayload(
-+      StatusCode::kInvalidArgument,
-+      "ExternalFile must have 'file_content' set, loading from"
-+      "'file_name' is not supported.",
-+      TfLiteSupportStatus::kInvalidArgumentError);
- }
- 
- absl::string_view ExternalFileHandler::GetFileContent() {
-@@ -180,14 +73,7 @@ absl::string_view ExternalFileHandler::GetFileContent() {
-   }
- }
- 
--ExternalFileHandler::~ExternalFileHandler() {
--  if (buffer_ != MAP_FAILED) {
--    munmap(buffer_, buffer_aligned_size_);
--  }
--  if (owned_fd_ >= 0) {
--    close(owned_fd_);
--  }
--}
-+ExternalFileHandler::~ExternalFileHandler() = default;
- 
- }  // namespace core
- }  // namespace task
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
-index 236d90347698..ad292dcc3702 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
-@@ -65,10 +65,6 @@ class ExternalFileHandler {
-   // Reference to the input ExternalFile.
-   const ExternalFile& external_file_;
- 
--  // The file descriptor of the ExternalFile if provided by path, as it is
--  // opened and owned by this class. Set to -1 otherwise.
--  int owned_fd_{-1};
--
-   // Points to the memory buffer mapped from the file descriptor of the
-   // ExternalFile, if provided by path or file descriptor.
-   void* buffer_{};
-@@ -82,9 +78,6 @@ class ExternalFileHandler {
- 
-   // The aligned mapped memory buffer offset, if any.
-   int64 buffer_aligned_offset_{};
--  // The aligned mapped memory buffer size in bytes taking into account the
--  // offset shift introduced by buffer_aligned_memory_offset_, if any.
--  int64 buffer_aligned_size_{};
- };
- 
- }  // namespace core
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
-index 0317d5f8ea34..6230e5c645c0 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
-@@ -15,8 +15,6 @@ limitations under the License.
- 
- #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
- 
--#include <unistd.h>
--
- #include "absl/strings/match.h"
- #include "absl/strings/str_cat.h"
- #include "tensorflow/lite/builtin_ops.h"
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
-index 6a7e97dd264e..bc55f6b0fe72 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
-@@ -16,8 +16,6 @@ limitations under the License.
- #ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_TFLITE_ENGINE_H_
- #define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_TFLITE_ENGINE_H_
- 
--#include <sys/mman.h>
--
- #include <memory>
- 
- #include "absl/memory/memory.h"
--- 
-2.30.0.365.g02bc693789-goog
-
diff --git a/third_party/tflite_support/patches/0001-task-utils-sign-compare.patch b/third_party/tflite_support/patches/0001-task-utils-sign-compare.patch
deleted file mode 100644
index 85172c99..0000000
--- a/third_party/tflite_support/patches/0001-task-utils-sign-compare.patch
+++ /dev/null
@@ -1,34 +0,0 @@
-From f84b50f175efff54ee6a6ef795703907245260cd Mon Sep 17 00:00:00 2001
-From: Sophie Chang <sophiechang@chromium.org>
-Date: Wed, 10 Feb 2021 17:55:30 +0000
-Subject: [PATCH] fix sign issues
-
----
- .../src/tensorflow_lite_support/cc/task/core/task_utils.h     | 4 ++--
- 1 file changed, 2 insertions(+), 2 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/task_utils.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/task_utils.h
-index 744dbbfb0f80..ced3dbcae9e4 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/task_utils.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/core/task_utils.h
-@@ -119,7 +119,7 @@ inline void PopulateVector(const TfLiteTensor* tensor, std::vector<T>* data) {
-   const T* results = GetTensorData<T>(tensor);
-   size_t num = tensor->bytes / sizeof(tensor->type);
-   data->reserve(num);
--  for (int i = 0; i < num; i++) {
-+  for (size_t i = 0; i < num; i++) {
-     data->emplace_back(results[i]);
-   }
- }
-@@ -169,7 +169,7 @@ static TensorType* FindTensorByName(
-       tensor_metadatas->size() != tensors.size()) {
-     return nullptr;
-   }
--  for (int i = 0; i < tensor_metadatas->size(); i++) {
-+  for (flatbuffers::uoffset_t i = 0; i < tensor_metadatas->size(); i++) {
-     if (strcmp(name.data(), tensor_metadatas->Get(i)->name()->c_str()) == 0) {
-       return tensors[i];
-     }
--- 
-2.30.0.478.g8a0d178c01-goog
-
diff --git a/third_party/tflite_support/patches/0001-use-StringPiece-for-string_view.patch b/third_party/tflite_support/patches/0001-use-StringPiece-for-string_view.patch
deleted file mode 100644
index 28f4740..0000000
--- a/third_party/tflite_support/patches/0001-use-StringPiece-for-string_view.patch
+++ /dev/null
@@ -1,38 +0,0 @@
-From 81287a62d65139f29c512fed88ed734bef2c33f5 Mon Sep 17 00:00:00 2001
-From: Michael Crouse <mcrouse@chromium.org>
-Date: Tue, 22 Dec 2020 14:25:39 -0800
-Subject: [PATCH] use StringPiece for string_view
-
----
- .../cc/text/tokenizers/regex_tokenizer.cc              | 10 +++++-----
- 1 file changed, 5 insertions(+), 5 deletions(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
-index 38aff8805b30..44c43b2d5086 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
-@@ -61,16 +61,16 @@ RegexTokenizer::RegexTokenizer(const std::string& regex_pattern,
- }
- 
- TokenizerResult RegexTokenizer::Tokenize(const std::string& input) {
--  absl::string_view leftover(input.data());
--  absl::string_view last_end = leftover;
-+  re2::StringPiece leftover(input.data());
-+  re2::StringPiece last_end = leftover;
- 
-   TokenizerResult result;
- 
-   // Keep looking for split points until we have reached the end of the input.
--  absl::string_view extracted_delim_token;
-+  re2::StringPiece extracted_delim_token;
-   while (RE2::FindAndConsume(&leftover, delim_re_, &extracted_delim_token)) {
--    absl::string_view token(last_end.data(),
--                            extracted_delim_token.data() - last_end.data());
-+    re2::StringPiece token(last_end.data(),
-+                           extracted_delim_token.data() - last_end.data());
-     bool has_non_empty_token = token.length() > 0;
- 
-     last_end = leftover;
--- 
-2.29.2.729.g45daf8777d-goog
-
diff --git a/third_party/tflite_support/patches/0001-use-SysNSStringToUTF8.patch b/third_party/tflite_support/patches/0001-use-SysNSStringToUTF8.patch
deleted file mode 100644
index 4ca0e41..0000000
--- a/third_party/tflite_support/patches/0001-use-SysNSStringToUTF8.patch
+++ /dev/null
@@ -1,29 +0,0 @@
-From e4b8790a56487279b084fb59a2186a8bfd24b838 Mon Sep 17 00:00:00 2001
-From: Michael Crouse <mcrouse@chromium.org>
-Date: Thu, 7 Jan 2021 08:20:06 -0800
-Subject: [PATCH] use SysNSStringToUTF8
-
----
- .../tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm | 3 ++-
- 1 file changed, 2 insertions(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm b/third_party/tflite-support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
-index 2a11bb673047..b82be34a9ab9 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
-@@ -12,10 +12,11 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
- ==============================================================================*/
-+#inmport "base/strings/sys_string_conversions.h"
- #import "third_party/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.h"
- 
- std::string MakeString(NSString* str) {
--  return std::string([str UTF8String]);
-+  return SysNSStringToUTF8(str); 
- }
- 
- NSString* MakeNSString(const std::string& str) {
--- 
-2.29.2.729.g45daf8777d-goog
-
diff --git a/third_party/tflite_support/patches/0001-use-base-logging.patch b/third_party/tflite_support/patches/0001-use-base-logging.patch
deleted file mode 100644
index 0cdb9d6..0000000
--- a/third_party/tflite_support/patches/0001-use-base-logging.patch
+++ /dev/null
@@ -1,26 +0,0 @@
-From 5307d81798215dae084b5079e797fd4408040340 Mon Sep 17 00:00:00 2001
-From: Michael Crouse <mcrouse@chromium.org>
-Date: Tue, 22 Dec 2020 14:18:09 -0800
-Subject: [PATCH] use base logging
-
----
- .../src/tensorflow_lite_support/cc/port/default/statusor.cc     | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc
-index 547a79192324..182c37e4aaf6 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc
-@@ -18,8 +18,8 @@ limitations under the License.
- 
- #include <utility>
- 
--#include <glog/logging.h>
- #include "absl/strings/str_cat.h"
-+#include "base/logging.h"
- 
- namespace tflite {
- namespace support {
--- 
-2.29.2.729.g45daf8777d-goog
-
diff --git a/third_party/tflite_support/patches/0001-use-exit.patch b/third_party/tflite_support/patches/0001-use-exit.patch
deleted file mode 100644
index 986543f..0000000
--- a/third_party/tflite_support/patches/0001-use-exit.patch
+++ /dev/null
@@ -1,25 +0,0 @@
-From 49de34d7489ba5218a822461a42786844a1e344b Mon Sep 17 00:00:00 2001
-From: Sophie Chang <sophiechang@chromium.org>
-Date: Wed, 3 Feb 2021 04:30:56 +0000
-Subject: [PATCH] use _Exit
-
----
- .../src/tensorflow_lite_support/cc/port/default/statusor.cc     | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc b/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc
-index 182c37e4aaf6..058c0070f0da 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/port/default/statusor.cc
-@@ -50,7 +50,7 @@ void Helper::HandleInvalidStatusCtorArg(absl::Status* status) {
- void Helper::Crash(const absl::Status& status) {
-   LOG(FATAL) << "Attempting to fetch value instead of handling error "
-              << status;
--  _exit(1);
-+  _Exit(1);
- }
- 
- void ThrowBadStatusOrAccess(absl::Status status) {
--- 
-2.30.0.365.g02bc693789-goog
-
diff --git a/third_party/tflite_support/patches/0001-use-re2-StringPiece-for-RegexTokenizer-Tokenize.patch b/third_party/tflite_support/patches/0001-use-re2-StringPiece-for-RegexTokenizer-Tokenize.patch
new file mode 100644
index 0000000..950a6db
--- /dev/null
+++ b/third_party/tflite_support/patches/0001-use-re2-StringPiece-for-RegexTokenizer-Tokenize.patch
@@ -0,0 +1,36 @@
+From b16b7af6f58ede0718fabf9c0da7495c79400c90 Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Wed, 15 Dec 2021 14:39:48 -0800
+Subject: [PATCH 01/11] use re2 StringPiece for RegexTokenizer::Tokenize
+
+---
+ .../cc/text/tokenizers/regex_tokenizer.cc                 | 8 ++++----
+ 1 file changed, 4 insertions(+), 4 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
+index 564f5f63a0584..832f9df42f824 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
+@@ -61,15 +61,15 @@ RegexTokenizer::RegexTokenizer(const std::string& regex_pattern,
+ }
+ 
+ TokenizerResult RegexTokenizer::Tokenize(const std::string& input) {
+-  absl::string_view leftover(input.data());
+-  absl::string_view last_end = leftover;
++  re2::StringPiece leftover(input.data());
++  re2::StringPiece last_end = leftover;
+ 
+   TokenizerResult result;
+ 
+   // Keep looking for split points until we have reached the end of the input.
+-  absl::string_view extracted_delim_token;
++  re2::StringPiece extracted_delim_token;
+   while (RE2::FindAndConsume(&leftover, delim_re_, &extracted_delim_token)) {
+-    absl::string_view token(last_end.data(),
++    re2::StringPiece token(last_end.data(),
+                             extracted_delim_token.data() - last_end.data());
+     bool has_non_empty_token = token.length() > 0;
+ 
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0001-use-size_t.patch b/third_party/tflite_support/patches/0001-use-size_t.patch
deleted file mode 100644
index 447bdb81..0000000
--- a/third_party/tflite_support/patches/0001-use-size_t.patch
+++ /dev/null
@@ -1,25 +0,0 @@
-From ecb535154168358a72de6b51099a9549b970bce5 Mon Sep 17 00:00:00 2001
-From: Michael Crouse <mcrouse@chromium.org>
-Date: Tue, 22 Dec 2020 14:34:12 -0800
-Subject: [PATCH] use size_t
-
----
- .../cc/task/text/nlclassifier/nl_classifier.h                   | 2 +-
- 1 file changed, 1 insertion(+), 1 deletion(-)
-
-diff --git a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
-index d3c3bed2083d..4055a93467d4 100644
---- a/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
-+++ b/third_party/tflite-support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
-@@ -151,7 +151,7 @@ class NLClassifier : public core::BaseTaskApi<std::vector<core::Category>,
-       const std::string& name,
-       int index) {
-     if (metadata_array != nullptr && metadata_array->size() == tensors.size()) {
--      for (int i = 0; i < metadata_array->size(); i++) {
-+      for (size_t i = 0; i < metadata_array->size(); i++) {
-         if (strcmp(name.data(), metadata_array->Get(i)->name()->c_str()) == 0) {
-           return tensors[i];
-         }
--- 
-2.29.2.729.g45daf8777d-goog
-
diff --git a/third_party/tflite_support/patches/0002-sentencepiece-tokenization-not-supported.patch b/third_party/tflite_support/patches/0002-sentencepiece-tokenization-not-supported.patch
new file mode 100644
index 0000000..95774a5
--- /dev/null
+++ b/third_party/tflite_support/patches/0002-sentencepiece-tokenization-not-supported.patch
@@ -0,0 +1,51 @@
+From 9aa45ea43f8d84db1e20674c294f9ab958b12d7e Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Wed, 15 Dec 2021 14:57:16 -0800
+Subject: [PATCH 02/11] sentencepiece tokenization not supported
+
+---
+ .../cc/text/tokenizers/tokenizer_utils.cc          | 14 ++++----------
+ 1 file changed, 4 insertions(+), 10 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
+index 9abca9691f058..28f0137f54278 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
+@@ -20,7 +20,6 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ #include "tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h"
+ #include "tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h"
+-#include "tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+ 
+ namespace tflite {
+@@ -29,7 +28,6 @@ namespace text {
+ namespace tokenizer {
+ 
+ using ::tflite::ProcessUnit;
+-using ::tflite::SentencePieceTokenizerOptions;
+ using ::tflite::support::CreateStatusWithPayload;
+ using ::tflite::support::StatusOr;
+ using ::tflite::support::TfLiteSupportStatus;
+@@ -74,14 +72,10 @@ StatusOr<std::unique_ptr<Tokenizer>> CreateTokenizerFromProcessUnit(
+                                               vocab_buffer.size());
+     }
+     case ProcessUnitOptions_SentencePieceTokenizerOptions: {
+-      const tflite::SentencePieceTokenizerOptions* options =
+-          tokenizer_process_unit->options_as<SentencePieceTokenizerOptions>();
+-      ASSIGN_OR_RETURN(absl::string_view model_buffer,
+-                       CheckAndLoadFirstAssociatedFile(
+-                           options->sentencePiece_model(), metadata_extractor));
+-      // TODO(b/160647204): Extract sentence piece model vocabulary
+-      return absl::make_unique<SentencePieceTokenizer>(model_buffer.data(),
+-                                                       model_buffer.size());
++      return CreateStatusWithPayload(
++        absl::StatusCode::kInvalidArgument,
++        "Chromium does not support sentencepiece tokenization",
++        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+     }
+     case ProcessUnitOptions_RegexTokenizerOptions: {
+       const tflite::RegexTokenizerOptions* options =
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0003-rm-unused-func.patch b/third_party/tflite_support/patches/0003-rm-unused-func.patch
new file mode 100644
index 0000000..5441faf
--- /dev/null
+++ b/third_party/tflite_support/patches/0003-rm-unused-func.patch
@@ -0,0 +1,224 @@
+From 7bd2e5f0e2bb560e55efc3dd86249ff42a10d08c Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Wed, 15 Dec 2021 15:08:59 -0800
+Subject: [PATCH 03/11] rm unused func
+
+---
+ .../vision/utils/libyuv_frame_buffer_utils.cc | 201 +-----------------
+ 1 file changed, 1 insertion(+), 200 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
+index 0ece48636504e..6fd3ca81c984c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
+@@ -1326,206 +1326,7 @@ absl::Status CropResize(const FrameBuffer& buffer, int x0, int y0, int x1,
+   }
+ }
+ 
+-// Returns the scaled dimension of the input_size best fit within the
+-// output_size bound while respecting the aspect ratio.
+-FrameBuffer::Dimension GetScaledDimension(FrameBuffer::Dimension input_size,
+-                                          FrameBuffer::Dimension output_size) {
+-  int original_width = input_size.width;
+-  int original_height = input_size.height;
+-  int bound_width = output_size.width;
+-  int bound_height = output_size.height;
+-  int new_width = original_width;
+-  int new_height = original_height;
+-
+-  // Try to fit the width first.
+-  new_width = bound_width;
+-  new_height = (new_width * original_height) / original_width;
+-
+-  // Try to fit the height if needed.
+-  if (new_height > bound_height) {
+-    new_height = bound_height;
+-    new_width = (new_height * original_width) / original_height;
+-  }
+-  return FrameBuffer::Dimension{.width = new_width, .height = new_height};
+-}
+-
+-// This method only supports kGRAY, kRGBA, and kRGB formats.
+-absl::Status UniformCropResizePlane(const FrameBuffer& buffer,
+-                                    std::vector<int> crop_coordinates,
+-                                    FrameBuffer* output_buffer) {
+-  int x0 = 0, y0 = 0;
+-  FrameBuffer::Dimension input_dimension = buffer.dimension();
+-  if (!crop_coordinates.empty()) {
+-    x0 = crop_coordinates[0];
+-    y0 = crop_coordinates[1];
+-    input_dimension =
+-        GetCropDimension(x0, crop_coordinates[2], y0, crop_coordinates[3]);
+-  }
+-  if (input_dimension == output_buffer->dimension()) {
+-    // Cropping only case.
+-    return CropPlane(buffer, x0, y0, crop_coordinates[2], crop_coordinates[3],
+-                     output_buffer);
+-  }
+-
+-  // Cropping is achieved by adjusting origin to (x0, y0).
+-  ASSIGN_OR_RETURN(int pixel_stride, GetPixelStrides(buffer.format()));
+-  int adjusted_offset =
+-      buffer.plane(0).stride.row_stride_bytes * y0 + x0 * pixel_stride;
+-  FrameBuffer::Plane plane = {
+-      /*buffer=*/buffer.plane(0).buffer + adjusted_offset,
+-      /*stride=*/{buffer.plane(0).stride.row_stride_bytes, pixel_stride}};
+-  auto adjusted_buffer =
+-      FrameBuffer::Create({plane}, input_dimension, buffer.format(),
+-                          buffer.orientation(), buffer.timestamp());
+-
+-  // Uniform resize is achieved by adjusting the resize dimension to fit the
+-  // output_buffer and respect the input aspect ratio at the same time. We
+-  // create an intermediate output buffer with adjusted dimension and point its
+-  // backing buffer to the output_buffer. Note the stride information on the
+-  // adjusted_output_buffer is not used in the Resize* methods.
+-  FrameBuffer::Dimension adjusted_dimension =
+-      GetScaledDimension(input_dimension, output_buffer->dimension());
+-  FrameBuffer::Plane output_plane = {/*buffer=*/output_buffer->plane(0).buffer,
+-                                     /*stride=*/output_buffer->plane(0).stride};
+-  auto adjusted_output_buffer = FrameBuffer::Create(
+-      {output_plane}, adjusted_dimension, output_buffer->format(),
+-      output_buffer->orientation(), output_buffer->timestamp());
+-
+-  switch (buffer.format()) {
+-    case FrameBuffer::Format::kRGB:
+-      return ResizeRgb(*adjusted_buffer, adjusted_output_buffer.get());
+-    case FrameBuffer::Format::kRGBA:
+-      return ResizeRgba(*adjusted_buffer, adjusted_output_buffer.get());
+-    case FrameBuffer::Format::kGRAY:
+-      return ResizeGray(*adjusted_buffer, adjusted_output_buffer.get());
+-    default:
+-      return CreateStatusWithPayload(
+-          StatusCode::kInternal,
+-          absl::StrFormat("Format %i is not supported.", buffer.format()),
+-          TfLiteSupportStatus::kImageProcessingError);
+-  }
+-}
+-
+-absl::Status UniformCropResizeYuv(const FrameBuffer& buffer,
+-                                  std::vector<int> crop_coordinates,
+-                                  FrameBuffer* output_buffer) {
+-  int x0 = 0, y0 = 0;
+-  FrameBuffer::Dimension input_dimension = buffer.dimension();
+-  if (!crop_coordinates.empty()) {
+-    x0 = crop_coordinates[0];
+-    y0 = crop_coordinates[1];
+-    input_dimension =
+-        GetCropDimension(x0, crop_coordinates[2], y0, crop_coordinates[3]);
+-  }
+-  if (input_dimension == output_buffer->dimension()) {
+-    // Cropping only case.
+-    int x1 = crop_coordinates[2];
+-    int y1 = crop_coordinates[3];
+-    switch (buffer.format()) {
+-      case FrameBuffer::Format::kNV12:
+-      case FrameBuffer::Format::kNV21:
+-        return CropNv(buffer, x0, y0, x1, y1, output_buffer);
+-      case FrameBuffer::Format::kYV12:
+-      case FrameBuffer::Format::kYV21:
+-        return CropYv(buffer, x0, y0, x1, y1, output_buffer);
+-      default:
+-        return CreateStatusWithPayload(
+-            StatusCode::kInternal,
+-            absl::StrFormat("Format %i is not supported.", buffer.format()),
+-            TfLiteSupportStatus::kImageProcessingError);
+-    }
+-  }
+-
+-  // Cropping is achieved by adjusting origin to (x0, y0).
+-  ASSIGN_OR_RETURN(FrameBuffer::YuvData input_data,
+-                   FrameBuffer::GetYuvDataFromFrameBuffer(buffer));
+-  // Cropping YUV planes by offsetting the origins of each plane.
+-  // TODO(b/152629712): Investigate the impact of color shifting caused by the
+-  // bounding box with odd X or Y starting positions.
+-  const int plane_y_offset = input_data.y_row_stride * y0 + x0;
+-  const int plane_uv_offset = input_data.uv_row_stride * (y0 / 2) +
+-                              input_data.uv_pixel_stride * (x0 / 2);
+-  FrameBuffer::Plane adjusted_plane_y = {
+-      /*buffer=*/input_data.y_buffer + plane_y_offset,
+-      /*stride=*/{input_data.y_row_stride, /*pixel_stride_bytes=*/1}};
+-  FrameBuffer::Plane adjusted_plane_u = {
+-      /*buffer=*/input_data.u_buffer + plane_uv_offset,
+-      /*stride=*/{input_data.uv_row_stride, input_data.uv_pixel_stride}};
+-  FrameBuffer::Plane adjusted_plane_v = {
+-      /*buffer=*/input_data.v_buffer + plane_uv_offset,
+-      /*stride=*/{input_data.uv_row_stride, input_data.uv_pixel_stride}};
+-
+-  // Uniform resize is achieved by adjusting the resize dimension to fit the
+-  // output_buffer and respect the input aspect ratio at the same time. For
+-  // YUV formats, we need access to the actual output dimension to get the
+-  // correct address of each plane. For this, we are not calling ResizeNv or
+-  // ResizeYv but the libyuv scale methods directly.
+-  FrameBuffer::Dimension adjusted_dimension =
+-      GetScaledDimension(input_dimension, output_buffer->dimension());
+-  ASSIGN_OR_RETURN(FrameBuffer::YuvData output_data,
+-                   FrameBuffer::GetYuvDataFromFrameBuffer(*output_buffer));
+-
+-  switch (buffer.format()) {
+-    case FrameBuffer::Format::kNV12: {
+-      int ret = libyuv::NV12Scale(
+-          adjusted_plane_y.buffer, adjusted_plane_y.stride.row_stride_bytes,
+-          adjusted_plane_u.buffer, adjusted_plane_u.stride.row_stride_bytes,
+-          input_dimension.width, input_dimension.height,
+-          const_cast<uint8_t*>(output_data.y_buffer), output_data.y_row_stride,
+-          const_cast<uint8_t*>(output_data.u_buffer), output_data.uv_row_stride,
+-          adjusted_dimension.width, adjusted_dimension.height,
+-          libyuv::FilterMode::kFilterBilinear);
+-      if (ret != 0) {
+-        return CreateStatusWithPayload(
+-            StatusCode::kUnknown, "Libyuv NV12Scale operation failed.",
+-            TfLiteSupportStatus::kImageProcessingBackendError);
+-      }
+-      return absl::OkStatus();
+-    }
+-    case FrameBuffer::Format::kNV21: {
+-      int ret = libyuv::NV12Scale(
+-          adjusted_plane_y.buffer, adjusted_plane_y.stride.row_stride_bytes,
+-          adjusted_plane_v.buffer, adjusted_plane_v.stride.row_stride_bytes,
+-          input_dimension.width, input_dimension.height,
+-          const_cast<uint8_t*>(output_data.y_buffer), output_data.y_row_stride,
+-          const_cast<uint8_t*>(output_data.v_buffer), output_data.uv_row_stride,
+-          adjusted_dimension.width, adjusted_dimension.height,
+-          libyuv::FilterMode::kFilterBilinear);
+-      if (ret != 0) {
+-        return CreateStatusWithPayload(
+-            StatusCode::kUnknown, "Libyuv NV12Scale operation failed.",
+-            TfLiteSupportStatus::kImageProcessingBackendError);
+-      }
+-      return absl::OkStatus();
+-    }
+-    case FrameBuffer::Format::kYV12:
+-    case FrameBuffer::Format::kYV21: {
+-      int ret = libyuv::I420Scale(
+-          adjusted_plane_y.buffer, adjusted_plane_y.stride.row_stride_bytes,
+-          adjusted_plane_u.buffer, adjusted_plane_u.stride.row_stride_bytes,
+-          adjusted_plane_v.buffer, adjusted_plane_v.stride.row_stride_bytes,
+-          input_dimension.width, input_dimension.height,
+-          const_cast<uint8_t*>(output_data.y_buffer), output_data.y_row_stride,
+-          const_cast<uint8_t*>(output_data.u_buffer), output_data.uv_row_stride,
+-          const_cast<uint8_t*>(output_data.v_buffer), output_data.uv_row_stride,
+-          adjusted_dimension.width, adjusted_dimension.height,
+-          libyuv::FilterMode::kFilterBilinear);
+-      if (ret != 0) {
+-        return CreateStatusWithPayload(
+-            StatusCode::kUnknown, "Libyuv I420Scale operation failed.",
+-            TfLiteSupportStatus::kImageProcessingBackendError);
+-      }
+-      return absl::OkStatus();
+-    }
+-    default:
+-      return CreateStatusWithPayload(
+-          StatusCode::kInternal,
+-          absl::StrFormat("Format %i is not supported.", buffer.format()),
+-          TfLiteSupportStatus::kImageProcessingError);
+-  }
+-  return absl::OkStatus();
+-}
+-}  // namespace
++} // namespace
+ 
+ absl::Status LibyuvFrameBufferUtils::Crop(const FrameBuffer& buffer, int x0,
+                                           int y0, int x1, int y1,
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0004-rm-noop-deprecated-attribute.patch b/third_party/tflite_support/patches/0004-rm-noop-deprecated-attribute.patch
new file mode 100644
index 0000000..d59a5ad
--- /dev/null
+++ b/third_party/tflite_support/patches/0004-rm-noop-deprecated-attribute.patch
@@ -0,0 +1,26 @@
+From 243aadd7dcea9be980aa89d183bf2dea7cba202b Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Wed, 15 Dec 2021 15:49:40 -0800
+Subject: [PATCH 04/11] rm noop deprecated attribute
+
+---
+ .../cc/task/text/nlclassifier/nl_classifier.h                  | 3 ---
+ 1 file changed, 3 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+index d5b49dfd75277..ac12536355db4 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+@@ -43,9 +43,6 @@ namespace text {
+ namespace nlclassifier {
+ 
+ // Options to identify input and output tensors of the model
+-ABSL_DEPRECATED(
+-    "Prefer using `tflite::task::text::NLClassifierOptions` and "
+-    "`CreateFromOptions`")
+ struct NLClassifierOptions {
+   int input_tensor_index = 0;
+   int output_score_tensor_index = 0;
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0005-use-size_t-in-for-loop.patch b/third_party/tflite_support/patches/0005-use-size_t-in-for-loop.patch
new file mode 100644
index 0000000..015edf6f
--- /dev/null
+++ b/third_party/tflite_support/patches/0005-use-size_t-in-for-loop.patch
@@ -0,0 +1,25 @@
+From 5d67933d8d4440816a02f7a319d7323041c3f7bf Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Wed, 15 Dec 2021 15:51:22 -0800
+Subject: [PATCH 05/11] use size_t in for loop
+
+---
+ .../cc/task/text/nlclassifier/nl_classifier.h                   | 2 +-
+ 1 file changed, 1 insertion(+), 1 deletion(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+index ac12536355db4..2adafba8f2fa9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+@@ -179,7 +179,7 @@ class NLClassifier : public core::BaseTaskApi<std::vector<core::Category>,
+           metadata_array,
+       const std::string& name, int index) {
+     if (metadata_array != nullptr && metadata_array->size() == tensors.size()) {
+-      for (int i = 0; i < metadata_array->size(); i++) {
++      for (size_t i = 0; i < metadata_array->size(); i++) {
+         if (strcmp(name.data(), metadata_array->Get(i)->name()->c_str()) == 0) {
+           return tensors[i];
+         }
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0006-unused-variable.patch b/third_party/tflite_support/patches/0006-unused-variable.patch
new file mode 100644
index 0000000..fa433fa
--- /dev/null
+++ b/third_party/tflite_support/patches/0006-unused-variable.patch
@@ -0,0 +1,29 @@
+From b2d06daf8ab5cff8748489407b6ad10ea600948d Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Thu, 16 Dec 2021 08:35:07 -0800
+Subject: [PATCH 06/11] unused variable
+
+---
+ .../src/tensorflow_lite_support/cc/task/core/task_utils.h   | 6 ++++--
+ 1 file changed, 4 insertions(+), 2 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
+index 03ef9ade9af41..e95ea73a4a812 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
+@@ -144,8 +144,10 @@ inline absl::Status PopulateVector(const TfLiteTensor* tensor,
+ template <>
+ inline absl::Status PopulateVector<std::string>(
+     const TfLiteTensor* tensor, std::vector<std::string>* data) {
+-  std::string* v;
+-  ASSIGN_OR_RETURN(v, AssertAndReturnTypedTensor<std::string>(tensor));
++  if (tensor->type != typeToTfLiteType<std::string>()) {
++    return absl::InvalidArgumentError("not of type string");
++  }
++
+   int num = GetStringCount(tensor);
+   data->reserve(num);
+   for (int i = 0; i < num; i++) {
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0007-do-not-use-absl-any.patch b/third_party/tflite_support/patches/0007-do-not-use-absl-any.patch
new file mode 100644
index 0000000..0fbe740
--- /dev/null
+++ b/third_party/tflite_support/patches/0007-do-not-use-absl-any.patch
@@ -0,0 +1,64 @@
+From d3d4385132632282fc91c735875ebfc90697b067 Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Thu, 16 Dec 2021 13:28:16 -0800
+Subject: [PATCH 07/11] do not use absl any
+
+---
+ .../cc/task/vision/core/frame_buffer.h        | 27 -------------------
+ 1 file changed, 27 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
+index c1289673cb82b..1668447393e9e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
+@@ -27,7 +27,6 @@ limitations under the License.
+ #include "absl/strings/str_cat.h"  // from @com_google_absl
+ #include "absl/time/clock.h"  // from @com_google_absl
+ #include "absl/time/time.h"  // from @com_google_absl
+-#include "absl/types/any.h"  // from @com_google_absl
+ #include "absl/types/optional.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -250,31 +249,6 @@ class FrameBuffer {
+     return {};
+   }
+ 
+-  // Returns the tag associated to the tag_key.
+-  absl::any GetTag(const std::string& tag_key) const {
+-    auto iter = tags_.find(tag_key);
+-    if (iter != tags_.end()) {
+-      return iter->second;
+-    }
+-    return absl::any();
+-  }
+-
+-  // Inserts or updates the tags map with key value pair (tag_key, tag_value).
+-  void InsertOrUpdateTag(const std::string& tag_key, absl::any tag_value) {
+-    tags_[tag_key] = std::move(tag_value);
+-  }
+-
+-  // Inserts the key value pair (tag_key, tag_value) into tags map. If the
+-  // tag_key already exists, an internal error will return.
+-  absl::Status InsertTag(const std::string& tag_key, absl::any tag_value) {
+-    auto iter = tags_.emplace(tag_key, tag_value);
+-    if (iter.second) {
+-      return absl::OkStatus();
+-    }
+-    return absl::InternalError(absl::StrCat(
+-        "tag_key already exists in tags.tag_key was not inserted: ", tag_key));
+-  }
+-
+   // Returns FrameBuffer dimension.
+   const Dimension dimension() const { return dimension_; }
+ 
+@@ -289,7 +263,6 @@ class FrameBuffer {
+ 
+  private:
+   std::vector<Plane> planes_;
+-  std::map<std::string, absl::any> tags_;
+   Dimension dimension_;
+   Format format_;
+   Orientation orientation_;
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0008-unused-string-include.patch b/third_party/tflite_support/patches/0008-unused-string-include.patch
new file mode 100644
index 0000000..2f5c20aeb
--- /dev/null
+++ b/third_party/tflite_support/patches/0008-unused-string-include.patch
@@ -0,0 +1,25 @@
+From 5feffc2cdd8c970490fadd812401be4eb57174d5 Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Thu, 16 Dec 2021 13:43:57 -0800
+Subject: [PATCH 08/11] unused string include
+
+---
+ .../cc/text/tokenizers/tokenizer_jni_lib.h                      | 2 --
+ 1 file changed, 2 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
+index fc7285c6807b0..33677d305a853 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
+@@ -17,8 +17,6 @@ limitations under the License.
+ 
+ #include <jni.h>
+ 
+-#include <string>
+-
+ #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
+ #include "tensorflow_lite_support/cc/utils/jni_utils.h"
+ 
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0009-remove-unbuilt-files-and-change-exec-bit-where-neede.patch b/third_party/tflite_support/patches/0009-remove-unbuilt-files-and-change-exec-bit-where-neede.patch
new file mode 100644
index 0000000..4ea8bdce
--- /dev/null
+++ b/third_party/tflite_support/patches/0009-remove-unbuilt-files-and-change-exec-bit-where-neede.patch
@@ -0,0 +1,666 @@
+From 515f1ef8496e5c73318aa41f6295bbfbefb6bbae Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Thu, 16 Dec 2021 13:56:14 -0800
+Subject: [PATCH 09/11] remove unbuilt files and change exec bit where needed
+
+---
+ .../cc/port/benchmark.h                       |  21 ---
+ .../cc/port/default/status_matchers.h         |  55 -------
+ .../tensorflow_lite_support/cc/port/gmock.h   |  21 ---
+ .../tensorflow_lite_support/cc/port/gtest.h   |  21 ---
+ .../tensorflow_lite_support/cc/port/proto2.h  |  32 ----
+ .../examples/task/audio/desktop/python/BUILD  |   0
+ .../task/audio/desktop/python/README.md       |   0
+ .../desktop/python/audio_classifier_demo.py   |   0
+ .../examples/task/vision/desktop/python/BUILD |   0
+ .../desktop/python/image_classifier_demo.py   |   0
+ .../desktop/python/image_segmenter_demo.py    |   0
+ .../desktop/python/object_detector_demo.py    |   0
+ .../ios/utils/Sources/TFLStringUtil.mm        |  23 ---
+ .../metadata/cc/metadata_populator.cc         | 150 ------------------
+ .../metadata/cc/utils/zip_mem_file.cc         | 124 ---------------
+ .../metadata/cc/utils/zip_mem_file.h          |  71 ---------
+ .../odml/ios/image/resources/grace_hopper.jpg | Bin
+ .../tools/ci_build/build_all.sh               |   0
+ .../ci_build/builds/build_ios_framework.sh    |   0
+ .../tools/ci_build/builds/pip_smoke_test.sh   |   0
+ .../tools/ci_build/common.sh                  |   0
+ .../tools/ci_build/common_win.bat             |   0
+ 22 files changed, 518 deletions(-)
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/cc/port/benchmark.h
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_matchers.h
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/cc/port/gmock.h
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/cc/port/gtest.h
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/cc/port/proto2.h
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/BUILD
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/README.md
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/audio_classifier_demo.py
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/BUILD
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_classifier_demo.py
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_segmenter_demo.py
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/object_detector_demo.py
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.cc
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.cc
+ delete mode 100644 third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.h
+ mode change 100755 => 100644 third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/resources/grace_hopper.jpg
+ mode change 100644 => 100755 third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh
+ mode change 100644 => 100755 third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/build_ios_framework.sh
+ mode change 100644 => 100755 third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/pip_smoke_test.sh
+ mode change 100644 => 100755 third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common.sh
+ mode change 100644 => 100755 third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/benchmark.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/benchmark.h
+deleted file mode 100644
+index 74bc1a6857664..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/benchmark.h
++++ /dev/null
+@@ -1,21 +0,0 @@
+-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_BENCHMARK_H_
+-#define TENSORFLOW_LITE_SUPPORT_CC_PORT_BENCHMARK_H_
+-
+-#include "gtest/benchmark.h"
+-
+-#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_BENCHMARK_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_matchers.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_matchers.h
+deleted file mode 100644
+index 6d9668043c183..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_matchers.h
++++ /dev/null
+@@ -1,55 +0,0 @@
+-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUS_MATCHERS_H_
+-#define TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUS_MATCHERS_H_
+-
+-#include "gmock/gmock.h"
+-#include "gtest/gtest.h"
+-
+-#define SUPPORT_STATUS_MACROS_IMPL_CONCAT_INNER_(x, y) x##y
+-#define SUPPORT_STATUS_MACROS_IMPL_CONCAT_(x, y) \
+-  SUPPORT_STATUS_MACROS_IMPL_CONCAT_INNER_(x, y)
+-
+-#undef SUPPORT_ASSERT_OK
+-#define SUPPORT_ASSERT_OK(expr) \
+-  SUPPORT_ASSERT_OK_IMPL_(      \
+-      SUPPORT_STATUS_MACROS_IMPL_CONCAT_(_status, __LINE__), expr)
+-
+-#define SUPPORT_ASSERT_OK_IMPL_(status, expr) \
+-  auto status = (expr);                       \
+-  ASSERT_TRUE(status.ok());
+-
+-#undef SUPPORT_EXPECT_OK
+-#define SUPPORT_EXPECT_OK(expr) \
+-  SUPPORT_EXPECT_OK_IMPL_(      \
+-      SUPPORT_STATUS_MACROS_IMPL_CONCAT_(_status, __LINE__), expr)
+-
+-#define SUPPORT_EXPECT_OK_IMPL_(status, expr) \
+-  auto status = (expr);                       \
+-  EXPECT_TRUE(status.ok());
+-
+-#undef SUPPORT_ASSERT_OK_AND_ASSIGN
+-#define SUPPORT_ASSERT_OK_AND_ASSIGN(lhs, rexpr)                           \
+-  SUPPORT_ASSERT_OK_AND_ASSIGN_IMPL_(                                      \
+-      SUPPORT_STATUS_MACROS_IMPL_CONCAT_(_status_or_value, __LINE__), lhs, \
+-      rexpr)
+-
+-#define SUPPORT_ASSERT_OK_AND_ASSIGN_IMPL_(statusor, lhs, rexpr) \
+-  auto statusor = (rexpr);                                       \
+-  ASSERT_TRUE(statusor.ok());                                    \
+-  lhs = std::move(statusor.value())
+-
+-#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUS_MATCHERS_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/gmock.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/gmock.h
+deleted file mode 100644
+index 5e4334db323d6..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/gmock.h
++++ /dev/null
+@@ -1,21 +0,0 @@
+-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_GMOCK_H_
+-#define TENSORFLOW_LITE_SUPPORT_CC_PORT_GMOCK_H_
+-
+-#include "gmock/gmock.h"
+-
+-#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_GMOCK_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/gtest.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/gtest.h
+deleted file mode 100644
+index dbe2e5e6f9d7c..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/gtest.h
++++ /dev/null
+@@ -1,21 +0,0 @@
+-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_GTEST_H_
+-#define TENSORFLOW_LITE_SUPPORT_CC_PORT_GTEST_H_
+-
+-#include "gtest/gtest.h"
+-
+-#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_GTEST_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/proto2.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/proto2.h
+deleted file mode 100644
+index 3cde2ab81d6ee..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/proto2.h
++++ /dev/null
+@@ -1,32 +0,0 @@
+-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_PROTO_NS_H_
+-#define TENSORFLOW_LITE_SUPPORT_CC_PORT_PROTO_NS_H_
+-
+-#include "google/protobuf/message_lite.h"
+-#include "google/protobuf/text_format.h"
+-
+-namespace tflite {
+-namespace support {
+-namespace proto {
+-
+-using TextFormat = ::google::protobuf::TextFormat;
+-using MessageLite = ::google::protobuf::MessageLite;
+-
+-}  // namespace proto
+-}  // namespace support
+-}  // namespace tflite
+-
+-#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_PROTO_NS_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/BUILD
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/README.md
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/audio_classifier_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/audio_classifier_demo.py
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/BUILD
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_classifier_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_classifier_demo.py
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_segmenter_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_segmenter_demo.py
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/object_detector_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/object_detector_demo.py
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm b/third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
+deleted file mode 100644
+index 6e9cf23802427..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
++++ /dev/null
+@@ -1,23 +0,0 @@
+-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-#import "third_party/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.h"
+-
+-std::string MakeString(NSString* str) { return std::string([str UTF8String]); }
+-
+-NSString* MakeNSString(const std::string& str) {
+-  return [[NSString alloc] initWithBytes:const_cast<void*>(static_cast<const void*>(str.data()))
+-                                  length:str.length()
+-                                encoding:NSUTF8StringEncoding];
+-}
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.cc
+deleted file mode 100644
+index e21d426369e2e..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.cc
++++ /dev/null
+@@ -1,150 +0,0 @@
+-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#include "tensorflow_lite_support/metadata/cc/metadata_populator.h"
+-
+-#include <cstdlib>
+-#include <cstring>
+-#include <functional>
+-
+-#include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+-#include "contrib/minizip/ioapi.h"
+-#include "contrib/minizip/zip.h"
+-#include "tensorflow/lite/schema/schema_generated.h"
+-#include "tensorflow_lite_support/cc/common.h"
+-#include "tensorflow_lite_support/cc/port/status_macros.h"
+-#include "tensorflow_lite_support/cc/port/statusor.h"
+-#include "tensorflow_lite_support/metadata/cc/utils/zip_mem_file.h"
+-#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+-
+-namespace tflite {
+-namespace metadata {
+-
+-namespace {
+-constexpr char kMetadataBufferName[] = "TFLITE_METADATA";
+-
+-using ::absl::StatusCode;
+-using ::tflite::support::CreateStatusWithPayload;
+-using ::tflite::support::TfLiteSupportStatus;
+-
+-}  // namespace
+-
+-ModelMetadataPopulator::ModelMetadataPopulator(const tflite::Model& model) {
+-  model.UnPackTo(&model_t_);
+-}
+-
+-/* static */
+-tflite::support::StatusOr<std::unique_ptr<ModelMetadataPopulator>>
+-ModelMetadataPopulator::CreateFromModelBuffer(const char* buffer_data,
+-                                              size_t buffer_size) {
+-  // Rely on the simplest, base flatbuffers verifier. Here is not the place to
+-  // e.g. use an OpResolver: we just want to make sure the buffer is valid to
+-  // access the metadata.
+-  flatbuffers::Verifier verifier = flatbuffers::Verifier(
+-      reinterpret_cast<const uint8_t*>(buffer_data), buffer_size);
+-  if (!tflite::VerifyModelBuffer(verifier)) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kInvalidArgument,
+-        "The model is not a valid FlatBuffer buffer.",
+-        TfLiteSupportStatus::kInvalidFlatBufferError);
+-  }
+-  // Use absl::WrapUnique() to call private constructor:
+-  // https://abseil.io/tips/126.
+-  return absl::WrapUnique(
+-      new ModelMetadataPopulator(*tflite::GetModel(buffer_data)));
+-}
+-
+-void ModelMetadataPopulator::LoadMetadata(const char* metadata_buffer_data,
+-                                          size_t metadata_buffer_size) {
+-  // Pack the model metadata in a buffer.
+-  auto model_metadata_buffer = std::make_unique<tflite::BufferT>();
+-  model_metadata_buffer->data = {metadata_buffer_data,
+-                                 metadata_buffer_data + metadata_buffer_size};
+-  // Check if the model already has metadata. If so, just override the buffer
+-  // and exit.
+-  for (const auto& metadata_t : model_t_.metadata) {
+-    if (metadata_t->name == kMetadataBufferName) {
+-      model_t_.buffers[metadata_t->buffer] = std::move(model_metadata_buffer);
+-      return;
+-    }
+-  }
+-  // Model doesn't already have metadata: add metadata buffer and pointer to the
+-  // buffer in the model metadata section.
+-  model_t_.buffers.push_back(std::move(model_metadata_buffer));
+-  auto metadata_t = std::make_unique<tflite::MetadataT>();
+-  metadata_t->name = kMetadataBufferName;
+-  metadata_t->buffer = model_t_.buffers.size() - 1;
+-  model_t_.metadata.push_back(std::move(metadata_t));
+-}
+-
+-void ModelMetadataPopulator::LoadAssociatedFiles(
+-    const absl::flat_hash_map<std::string, std::string>& associated_files) {
+-  associated_files_ = associated_files;
+-}
+-
+-tflite::support::StatusOr<std::string>
+-ModelMetadataPopulator::AppendAssociatedFiles(const char* model_buffer_data,
+-                                              size_t model_buffer_size) {
+-  // Create in-memory zip file.
+-  ZipMemFile mem_file = ZipMemFile(model_buffer_data, model_buffer_size);
+-  // Open zip.
+-  zipFile zf = zipOpen2(/*pathname=*/nullptr, APPEND_STATUS_CREATEAFTER,
+-                        /*globalcomment=*/nullptr, &mem_file.GetFileFuncDef());
+-  if (zf == nullptr) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kUnknown, "Unable to open zip archive",
+-        TfLiteSupportStatus::kMetadataAssociatedFileZipError);
+-  }
+-  // Write associated files.
+-  for (const auto& [name, contents] : associated_files_) {
+-    if ((zipOpenNewFileInZip(zf, name.c_str(),
+-                             /*zipfi=*/nullptr,
+-                             /*extrafield_local=*/nullptr,
+-                             /*size_extrafield_local=*/0,
+-                             /*extrafield_global=*/nullptr,
+-                             /*size_extrafield_global=*/0,
+-                             /*comment=*/nullptr,
+-                             /*method=*/0,
+-                             /*level=*/Z_DEFAULT_COMPRESSION) != ZIP_OK) ||
+-        (zipWriteInFileInZip(zf, contents.data(), contents.length()) !=
+-         ZIP_OK) ||
+-        (zipCloseFileInZip(zf) != ZIP_OK)) {
+-      return CreateStatusWithPayload(
+-          StatusCode::kUnknown, "Unable to write file to zip archive",
+-          TfLiteSupportStatus::kMetadataAssociatedFileZipError);
+-    }
+-  }
+-  // Close zip.
+-  if (zipClose(zf, /*global_comment=*/nullptr) != ZIP_OK) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kUnknown, "Unable to close zip archive",
+-        TfLiteSupportStatus::kMetadataAssociatedFileZipError);
+-  }
+-  // Return as a string.
+-  return std::string(mem_file.GetFileContent());
+-}
+-
+-tflite::support::StatusOr<std::string> ModelMetadataPopulator::Populate() {
+-  // Build model.
+-  flatbuffers::FlatBufferBuilder model_fbb;
+-  model_fbb.Finish(tflite::Model::Pack(model_fbb, &model_t_),
+-                   tflite::ModelIdentifier());
+-  return AppendAssociatedFiles(
+-      reinterpret_cast<char*>(model_fbb.GetBufferPointer()),
+-      model_fbb.GetSize());
+-}
+-
+-}  // namespace metadata
+-}  // namespace tflite
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.cc
+deleted file mode 100644
+index 2e4d9107c8c31..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.cc
++++ /dev/null
+@@ -1,124 +0,0 @@
+-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#include "tensorflow_lite_support/metadata/cc/utils/zip_mem_file.h"
+-
+-#include <algorithm>
+-#include <cstdio>
+-
+-#include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "contrib/minizip/ioapi.h"
+-
+-namespace tflite {
+-namespace metadata {
+-
+-ZipMemFile::ZipMemFile(const char* buffer, size_t size)
+-    : data_(buffer, size), offset_(0) {
+-  zlib_filefunc_def_.zopen_file = OpenFile;
+-  zlib_filefunc_def_.zread_file = ReadFile;
+-  zlib_filefunc_def_.zwrite_file = WriteFile;
+-  zlib_filefunc_def_.ztell_file = TellFile;
+-  zlib_filefunc_def_.zseek_file = SeekFile;
+-  zlib_filefunc_def_.zclose_file = CloseFile;
+-  zlib_filefunc_def_.zerror_file = ErrorFile;
+-  zlib_filefunc_def_.opaque = this;
+-}
+-
+-zlib_filefunc_def& ZipMemFile::GetFileFuncDef() { return zlib_filefunc_def_; }
+-
+-absl::string_view ZipMemFile::GetFileContent() const { return data_; }
+-
+-/* static */
+-voidpf ZipMemFile::OpenFile(voidpf opaque, const char* filename, int mode) {
+-  // Result is never used, but needs to be non-null for `zipOpen2` not to fail.
+-  return opaque;
+-}
+-
+-/* static */
+-size_t ZipMemFile::ReadFile(voidpf opaque, voidpf stream, void* buf,
+-                            size_t size) {
+-  auto* mem_file = static_cast<ZipMemFile*>(opaque);
+-  if (mem_file->offset_ < 0 || mem_file->Size() < mem_file->offset_) {
+-    return 0;
+-  }
+-  if (mem_file->offset_ + size > mem_file->Size()) {
+-    size = mem_file->Size() - mem_file->offset_;
+-  }
+-  memcpy(buf,
+-         static_cast<const char*>(mem_file->data_.c_str()) + mem_file->offset_,
+-         size);
+-  mem_file->offset_ += size;
+-  return size;
+-}
+-
+-/* static */
+-size_t ZipMemFile::WriteFile(voidpf opaque, voidpf stream, const void* buf,
+-                             size_t size) {
+-  auto* mem_file = static_cast<ZipMemFile*>(opaque);
+-  if (mem_file->offset_ + size > mem_file->Size()) {
+-    mem_file->data_.resize(mem_file->offset_ + size);
+-  }
+-  mem_file->data_.replace(mem_file->offset_, size,
+-                          static_cast<const char*>(buf), size);
+-  mem_file->offset_ += size;
+-  return size;
+-}
+-
+-/* static */
+-ptrdiff_t ZipMemFile::TellFile(voidpf opaque, voidpf stream) {
+-  return static_cast<ZipMemFile*>(opaque)->offset_;
+-}
+-
+-/* static */
+-ptrdiff_t ZipMemFile::SeekFile(voidpf opaque, voidpf stream, size_t offset,
+-                               int origin) {
+-  auto* mem_file = static_cast<ZipMemFile*>(opaque);
+-  switch (origin) {
+-    case SEEK_SET:
+-      mem_file->offset_ = offset;
+-      return 0;
+-    case SEEK_CUR:
+-      if (mem_file->offset_ + offset < 0 ||
+-          mem_file->offset_ + offset > mem_file->Size()) {
+-        return -1;
+-      }
+-      mem_file->offset_ += offset;
+-      return 0;
+-    case SEEK_END:
+-      if (mem_file->Size() - offset < 0 ||
+-          mem_file->Size() - offset > mem_file->Size()) {
+-        return -1;
+-      }
+-      mem_file->offset_ = offset + mem_file->Size();
+-      return 0;
+-    default:
+-      return -1;
+-  }
+-}
+-
+-/* static */
+-int ZipMemFile::CloseFile(voidpf opaque, voidpf stream) {
+-  // Nothing to do.
+-  return 0;
+-}
+-
+-/* static */
+-int ZipMemFile::ErrorFile(voidpf opaque, voidpf stream) {
+-  // Unused.
+-  return 0;
+-}
+-
+-}  // namespace metadata
+-}  // namespace tflite
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.h b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.h
+deleted file mode 100644
+index ef7843d70cff6..0000000000000
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/zip_mem_file.h
++++ /dev/null
+@@ -1,71 +0,0 @@
+-/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+-
+-Licensed under the Apache License, Version 2.0 (the "License");
+-you may not use this file except in compliance with the License.
+-You may obtain a copy of the License at
+-
+-    http://www.apache.org/licenses/LICENSE-2.0
+-
+-Unless required by applicable law or agreed to in writing, software
+-distributed under the License is distributed on an "AS IS" BASIS,
+-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+-See the License for the specific language governing permissions and
+-limitations under the License.
+-==============================================================================*/
+-
+-#ifndef TENSORFLOW_LITE_SUPPORT_METADATA_CC_UTILS_ZIP_MEM_FILE_H_
+-#define TENSORFLOW_LITE_SUPPORT_METADATA_CC_UTILS_ZIP_MEM_FILE_H_
+-
+-#include <cstdlib>
+-
+-#include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "contrib/minizip/ioapi.h"
+-
+-namespace tflite {
+-namespace metadata {
+-
+-// In-memory zip file implementation.
+-//
+-// Adapted from [1], with a few key differences:
+-// * backed by an `std::string` instead of malloc-ed C buffers,
+-// * supports opening the file for writing through `zipOpen2`.
+-//
+-// [1]:
+-// https://github.com/google/libkml/blob/master/third_party/zlib-1.2.3/contrib/minizip/iomem_simple.c
+-class ZipMemFile {
+- public:
+-  // Constructs an in-memory zip file from a buffer.
+-  ZipMemFile(const char* buffer, size_t size);
+-  // Provides access to the `zlib_filefunc_def` implementation for the in-memory
+-  // zip file.
+-  zlib_filefunc_def& GetFileFuncDef();
+-  // Provides access to the file contents.
+-  absl::string_view GetFileContent() const;
+-
+- private:
+-  // The string backing the in-memory file.
+-  std::string data_;
+-  // The current offset in the file.
+-  size_t offset_;
+-  // The `zlib_filefunc_def` implementation for this in-memory zip file.
+-  zlib_filefunc_def zlib_filefunc_def_;
+-
+-  // Convenience function to access the current data size.
+-  size_t Size() const { return data_.size(); }
+-
+-  // The file function implementations used in the `zlib_filefunc_def`.
+-  static voidpf OpenFile(voidpf opaque, const char* filename, int mode);
+-  static size_t ReadFile(voidpf opaque, voidpf stream, void* buf, size_t size);
+-  static size_t WriteFile(voidpf opaque, voidpf stream, const void* buf,
+-                          size_t size);
+-  static ptrdiff_t TellFile(voidpf opaque, voidpf stream);
+-  static ptrdiff_t SeekFile(voidpf opaque, voidpf stream, size_t offset,
+-                            int origin);
+-  static int CloseFile(voidpf opaque, voidpf stream);
+-  static int ErrorFile(voidpf opaque, voidpf stream);
+-};
+-
+-}  // namespace metadata
+-}  // namespace tflite
+-
+-#endif  // TENSORFLOW_LITE_SUPPORT_METADATA_CC_UTILS_ZIP_MEM_FILE_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/resources/grace_hopper.jpg b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/resources/grace_hopper.jpg
+old mode 100755
+new mode 100644
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh
+old mode 100644
+new mode 100755
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/build_ios_framework.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/build_ios_framework.sh
+old mode 100644
+new mode 100755
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/pip_smoke_test.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/pip_smoke_test.sh
+old mode 100644
+new mode 100755
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common.sh
+old mode 100644
+new mode 100755
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat
+old mode 100644
+new mode 100755
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0010-only-support-model-file-passed-in-from-mem.patch b/third_party/tflite_support/patches/0010-only-support-model-file-passed-in-from-mem.patch
new file mode 100644
index 0000000..d97f8ed
--- /dev/null
+++ b/third_party/tflite_support/patches/0010-only-support-model-file-passed-in-from-mem.patch
@@ -0,0 +1,265 @@
+From 4b7e971e2f2f6ef3fd394858d975b64479047872 Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Mon, 20 Dec 2021 08:50:35 -0800
+Subject: [PATCH 10/11] only support model file passed in from mem
+
+---
+ .../cc/task/core/external_file_handler.cc     | 143 ++----------------
+ .../cc/task/core/external_file_handler.h      |  23 +--
+ .../cc/task/core/tflite_engine.cc             |   2 -
+ .../cc/task/core/tflite_engine.h              |   2 -
+ 4 files changed, 10 insertions(+), 160 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
+index dcde0c926c653..e91a54fb7d11a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
+@@ -15,45 +15,25 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+ 
+-#include <errno.h>
+-#include <fcntl.h>
+ #include <stddef.h>
+-#include <sys/mman.h>
+-#include <unistd.h>
+-
+ #include <memory>
+ #include <string>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
++#include "absl/memory/memory.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+-#include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
++#include "tensorflow_lite_support/cc/port/statusor.h"
+ 
+ namespace tflite {
+ namespace task {
+ namespace core {
+-namespace {
+ 
+ using ::absl::StatusCode;
+ using ::tflite::support::CreateStatusWithPayload;
+ using ::tflite::support::StatusOr;
+ using ::tflite::support::TfLiteSupportStatus;
+ 
+-// Gets the offset aligned to page size for mapping given files into memory by
+-// file descriptor correctly, as according to mmap(2), the offset used in mmap
+-// must be a multiple of sysconf(_SC_PAGE_SIZE).
+-int64 GetPageSizeAlignedOffset(int64 offset) {
+-  int64 aligned_offset = offset;
+-  int64 page_size = sysconf(_SC_PAGE_SIZE);
+-  if (offset % page_size != 0) {
+-    aligned_offset = offset / page_size * page_size;
+-  }
+-  return aligned_offset;
+-}
+-
+-}  // namespace
+-
+ /* static */
+ StatusOr<std::unique_ptr<ExternalFileHandler>>
+ ExternalFileHandler::CreateFromExternalFile(const ExternalFile* external_file) {
+@@ -71,123 +51,18 @@ absl::Status ExternalFileHandler::MapExternalFile() {
+   if (!external_file_.file_content().empty()) {
+     return absl::OkStatus();
+   }
+-  if (external_file_.file_name().empty() &&
+-      !external_file_.has_file_descriptor_meta()) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kInvalidArgument,
+-        "ExternalFile must specify at least one of 'file_content', file_name' "
+-        "or 'file_descriptor_meta'.",
+-        TfLiteSupportStatus::kInvalidArgumentError);
+-  }
+-  // Obtain file descriptor, offset and size.
+-  int fd = -1;
+-  if (!external_file_.file_name().empty()) {
+-    owned_fd_ = open(external_file_.file_name().c_str(), O_RDONLY);
+-    if (owned_fd_ < 0) {
+-      const std::string error_message = absl::StrFormat(
+-          "Unable to open file at %s", external_file_.file_name());
+-      switch (errno) {
+-        case ENOENT:
+-          return CreateStatusWithPayload(
+-              StatusCode::kNotFound, error_message,
+-              TfLiteSupportStatus::kFileNotFoundError);
+-        case EACCES:
+-        case EPERM:
+-          return CreateStatusWithPayload(
+-              StatusCode::kPermissionDenied, error_message,
+-              TfLiteSupportStatus::kFilePermissionDeniedError);
+-        case EINTR:
+-          return CreateStatusWithPayload(StatusCode::kUnavailable,
+-                                         error_message,
+-                                         TfLiteSupportStatus::kFileReadError);
+-        case EBADF:
+-          return CreateStatusWithPayload(StatusCode::kFailedPrecondition,
+-                                         error_message,
+-                                         TfLiteSupportStatus::kFileReadError);
+-        default:
+-          return CreateStatusWithPayload(
+-              StatusCode::kUnknown,
+-              absl::StrFormat("%s, errno=%d", error_message, errno),
+-              TfLiteSupportStatus::kFileReadError);
+-      }
+-    }
+-    fd = owned_fd_;
+-  } else {
+-    fd = external_file_.file_descriptor_meta().fd();
+-    if (fd < 0) {
+-      return CreateStatusWithPayload(
+-          StatusCode::kInvalidArgument,
+-          absl::StrFormat("Provided file descriptor is invalid: %d < 0", fd),
+-          TfLiteSupportStatus::kInvalidArgumentError);
+-    }
+-    buffer_offset_ = external_file_.file_descriptor_meta().offset();
+-    buffer_size_ = external_file_.file_descriptor_meta().length();
+-  }
+-  // Get actual file size. Always use 0 as offset to lseek(2) to get the actual
+-  // file size, as SEEK_END returns the size of the file *plus* offset.
+-  size_t file_size = lseek(fd, /*offset=*/0, SEEK_END);
+-  if (file_size <= 0) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kUnknown,
+-        absl::StrFormat("Unable to get file size, errno=%d", errno),
+-        TfLiteSupportStatus::kFileReadError);
+-  }
+-  // Deduce buffer size if not explicitly provided through file descriptor.
+-  if (buffer_size_ <= 0) {
+-    buffer_size_ = file_size - buffer_offset_;
+-  }
+-  // Check for out of range issues.
+-  if (file_size <= buffer_offset_) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kInvalidArgument,
+-        absl::StrFormat("Provided file offset (%d) exceeds or matches actual "
+-                        "file length (%d)",
+-                        buffer_offset_, file_size),
+-        TfLiteSupportStatus::kInvalidArgumentError);
+-  }
+-  if (file_size < buffer_size_ + buffer_offset_) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kInvalidArgument,
+-        absl::StrFormat("Provided file length + offset (%d) exceeds actual "
+-                        "file length (%d)",
+-                        buffer_size_ + buffer_offset_, file_size),
+-        TfLiteSupportStatus::kInvalidArgumentError);
+-  }
+-  // If buffer_offset_ is not multiple of sysconf(_SC_PAGE_SIZE), align with
+-  // extra leading bytes and adjust buffer_size_ to account for the extra
+-  // leading bytes.
+-  buffer_aligned_offset_ = GetPageSizeAlignedOffset(buffer_offset_);
+-  buffer_aligned_size_ = buffer_size_ + buffer_offset_ - buffer_aligned_offset_;
+-  // Map into memory.
+-  buffer_ = mmap(/*addr=*/nullptr, buffer_aligned_size_, PROT_READ, MAP_SHARED,
+-                 fd, buffer_aligned_offset_);
+-  if (buffer_ == MAP_FAILED) {
+-    return CreateStatusWithPayload(
+-        StatusCode::kUnknown,
+-        absl::StrFormat("Unable to map file to memory buffer, errno=%d", errno),
+-        TfLiteSupportStatus::kFileMmapError);
+-  }
+-  return absl::OkStatus();
++
++  return CreateStatusWithPayload(StatusCode::kInvalidArgument,
++                                 "ExternalFile must specify 'file_content' "
++                                 "to be compatible with Chromium.",
++                                 TfLiteSupportStatus::kInvalidArgumentError);
+ }
+ 
+ absl::string_view ExternalFileHandler::GetFileContent() {
+-  if (!external_file_.file_content().empty()) {
+-    return external_file_.file_content();
+-  } else {
+-    return absl::string_view(static_cast<const char*>(buffer_) +
+-                                 buffer_offset_ - buffer_aligned_offset_,
+-                             buffer_size_);
+-  }
++  return external_file_.file_content();
+ }
+ 
+-ExternalFileHandler::~ExternalFileHandler() {
+-  if (buffer_ != MAP_FAILED) {
+-    munmap(buffer_, buffer_aligned_size_);
+-  }
+-  if (owned_fd_ >= 0) {
+-    close(owned_fd_);
+-  }
+-}
++ExternalFileHandler::~ExternalFileHandler() = default;
+ 
+ }  // namespace core
+ }  // namespace task
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
+index cf0bdf0b48037..48c62813e212e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -64,27 +64,6 @@ class ExternalFileHandler {
+ 
+   // Reference to the input ExternalFile.
+   const ExternalFile& external_file_;
+-
+-  // The file descriptor of the ExternalFile if provided by path, as it is
+-  // opened and owned by this class. Set to -1 otherwise.
+-  int owned_fd_{-1};
+-
+-  // Points to the memory buffer mapped from the file descriptor of the
+-  // ExternalFile, if provided by path or file descriptor.
+-  void* buffer_{};
+-
+-  // The mapped memory buffer offset, if any.
+-  int64 buffer_offset_{};
+-  // The size in bytes of the mapped memory buffer, if any.
+-  int64 buffer_size_{};
+-
+-  // As mmap(2) requires the offset to be a multiple of sysconf(_SC_PAGE_SIZE):
+-
+-  // The aligned mapped memory buffer offset, if any.
+-  int64 buffer_aligned_offset_{};
+-  // The aligned mapped memory buffer size in bytes taking into account the
+-  // offset shift introduced by buffer_aligned_memory_offset_, if any.
+-  int64 buffer_aligned_size_{};
+ };
+ 
+ }  // namespace core
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+index 8cd4585161df7..484b9a099ecdc 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+@@ -15,8 +15,6 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+ 
+-#include <unistd.h>
+-
+ #include <memory>
+ 
+ #include "absl/strings/match.h"  // from @com_google_absl
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
+index 9b44c6e5c022a..53dabdc4841d7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
+@@ -16,8 +16,6 @@ limitations under the License.
+ #ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_TFLITE_ENGINE_H_
+ #define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_TFLITE_ENGINE_H_
+ 
+-#include <sys/mman.h>
+-
+ #include <memory>
+ 
+ #include "absl/memory/memory.h"  // from @com_google_absl
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0011-run-clang-format.patch b/third_party/tflite_support/patches/0011-run-clang-format.patch
new file mode 100644
index 0000000..6f390e38
--- /dev/null
+++ b/third_party/tflite_support/patches/0011-run-clang-format.patch
@@ -0,0 +1,43843 @@
+From 66d958947df0a4366b2a808e2a74e5ba412a2c38 Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Mon, 20 Dec 2021 11:40:47 -0800
+Subject: [PATCH 11/11] run clang format
+
+---
+ .../configuration/edgetpu_coral_plugin.cc     |   20 +-
+ .../edgetpu_coral_plugin_test.cc              |    3 +-
+ .../src/tensorflow_lite_support/c/common.cc   |    2 +-
+ .../src/tensorflow_lite_support/c/common.h    |    4 +-
+ .../tensorflow_lite_support/c/common_utils.cc |   11 +-
+ .../tensorflow_lite_support/c/common_utils.h  |    3 +-
+ .../c/task/text/bert_nl_classifier.cc         |    6 +-
+ .../c/task/text/bert_nl_classifier.h          |    6 +-
+ .../c/task/text/bert_question_answerer.cc     |    3 +-
+ .../c/task/text/bert_question_answerer.h      |    3 +-
+ .../c/task/text/nl_classifier.cc              |    3 +-
+ .../c/task/text/nl_classifier.h               |    3 +-
+ .../c/task/vision/image_classifier.cc         |    9 +-
+ .../c/task/vision/image_classifier.h          |    9 +-
+ .../c/task/vision/object_detector.h           |    6 +-
+ .../test/task/vision/image_classifier_test.cc |   84 +-
+ .../src/tensorflow_lite_support/cc/common.cc  |    2 +-
+ .../src/tensorflow_lite_support/cc/common.h   |    5 +-
+ .../cc/port/default/status_macros.h           |    2 +-
+ .../cc/port/default/statusor_internals.h      |   38 +-
+ .../cc/port/default/tflite_wrapper.cc         |   12 +-
+ .../cc/port/default/tflite_wrapper.h          |    2 +-
+ .../cc/port/integral_types.h                  |    2 +-
+ .../cc/task/audio/audio_classifier.cc         |    2 +-
+ .../cc/task/audio/audio_embedder.h            |    6 +-
+ .../cc/task/audio/core/audio_buffer.h         |   10 +-
+ .../cc/task/audio/utils/wav_io.cc             |   19 +-
+ .../cc/task/audio/utils/wav_io.h              |    6 +-
+ .../cc/task/core/base_task_api.h              |    2 +-
+ .../cc/task/core/classification_head.h        |    2 +-
+ .../cc/task/core/error_reporter.cc            |    8 +-
+ .../cc/task/core/label_map_item.cc            |    5 +-
+ .../cc/task/core/label_map_item.h             |    7 +-
+ .../cc/task/core/proto/external_file.proto    |    2 -
+ .../cc/task/core/score_calibration.cc         |    8 +-
+ .../cc/task/core/score_calibration.h          |   11 +-
+ .../cc/task/core/task_api_factory.h           |    8 +-
+ .../cc/task/core/task_utils.h                 |   23 +-
+ .../cc/task/core/tflite_engine.cc             |   14 +-
+ .../cc/task/core/tflite_engine.h              |   13 +-
+ .../cc/task/processor/audio_preprocessor.cc   |    5 +-
+ .../processor/classification_postprocessor.cc |    5 +-
+ .../task/processor/embedding_postprocessor.h  |   10 +-
+ .../cc/task/processor/image_preprocessor.cc   |    6 +-
+ .../cc/task/processor/processor.h             |    5 +-
+ .../cc/task/processor/regex_preprocessor.cc   |    3 +-
+ .../cc/task/processor/regex_preprocessor.h    |    3 +-
+ .../cc/task/text/bert_nl_classifier.cc        |    7 +-
+ .../cc/task/text/bert_nl_classifier.h         |    2 +-
+ .../cc/task/text/bert_question_answerer.cc    |   34 +-
+ .../cc/task/text/bert_question_answerer.h     |    7 +-
+ .../task/text/nlclassifier/nl_classifier.cc   |   16 +-
+ .../cc/task/text/nlclassifier/nl_classifier.h |   16 +-
+ .../cc/task/text/question_answerer.h          |    6 +-
+ .../text/universal_sentence_encoder_qa.cc     |   14 +-
+ .../task/text/universal_sentence_encoder_qa.h |    9 +-
+ .../task/vision/core/base_vision_task_api.h   |    9 +-
+ .../cc/task/vision/core/classification_head.h |    2 +-
+ .../cc/task/vision/core/frame_buffer.h        |   47 +-
+ .../cc/task/vision/core/label_map_item.cc     |    5 +-
+ .../cc/task/vision/core/label_map_item.h      |    7 +-
+ .../cc/task/vision/image_classifier.cc        |   14 +-
+ .../cc/task/vision/image_classifier.h         |    8 +-
+ .../cc/task/vision/image_embedder.cc          |   17 +-
+ .../cc/task/vision/image_embedder.h           |    9 +-
+ .../cc/task/vision/image_segmenter.cc         |   15 +-
+ .../cc/task/vision/image_segmenter.h          |    8 +-
+ .../cc/task/vision/object_detector.cc         |   16 +-
+ .../cc/task/vision/object_detector.h          |    5 +-
+ .../cc/task/vision/proto/segmentations.proto  |    8 +-
+ .../vision/utils/frame_buffer_common_utils.cc |   59 +-
+ .../vision/utils/frame_buffer_common_utils.h  |   37 +-
+ .../task/vision/utils/frame_buffer_utils.cc   |   50 +-
+ .../cc/task/vision/utils/frame_buffer_utils.h |   40 +-
+ .../utils/frame_buffer_utils_interface.h      |   11 +-
+ .../vision/utils/libyuv_frame_buffer_utils.cc |   81 +-
+ .../vision/utils/libyuv_frame_buffer_utils.h  |    9 +-
+ .../cc/task/vision/utils/score_calibration.cc |    8 +-
+ .../cc/task/vision/utils/score_calibration.h  |   11 +-
+ .../cc/test/common_test.cc                    |    2 +-
+ .../task/processor/image_preprocessor_test.cc |   13 +-
+ .../test/task/text/bert_nl_classifier_test.cc |   36 +-
+ .../task/text/bert_question_answerer_test.cc  |    7 +-
+ .../text/nlclassifier/nl_classifier_test.cc   |   83 +-
+ .../test/task/vision/image_classifier_test.cc |  149 +-
+ .../test/task/vision/image_embedder_test.cc   |   95 +-
+ .../test/task/vision/image_segmenter_test.cc  |  117 +-
+ .../test/task/vision/object_detector_test.cc  |  157 +-
+ .../cc/test/test_utils.cc                     |   18 +-
+ .../cc/test/test_utils.h                      |    6 +-
+ .../cc/text/tokenizers/bert_tokenizer.cc      |    3 +-
+ .../cc/text/tokenizers/bert_tokenizer.h       |    3 +-
+ .../cc/text/tokenizers/bert_tokenizer_jni.cc  |   25 +-
+ .../cc/text/tokenizers/regex_tokenizer.cc     |    4 +-
+ .../cc/text/tokenizers/sentencepiece_jni.cc   |   20 +-
+ .../cc/text/tokenizers/tokenizer_jni_lib.cc   |    3 +-
+ .../cc/text/tokenizers/tokenizer_jni_lib.h    |    3 +-
+ .../cc/text/tokenizers/tokenizer_utils.cc     |    6 +-
+ .../cc/text/tokenizers/tokenizer_utils.h      |    1 -
+ .../cc/utils/common_utils.cc                  |    3 +-
+ .../cc/utils/common_utils.h                   |    3 +-
+ .../cc/utils/jni_utils.cc                     |    7 +-
+ .../cc/utils/jni_utils.h                      |    8 +-
+ .../codegen/android_java_generator.cc         |   37 +-
+ .../codegen/android_java_generator.h          |    5 +-
+ .../codegen/code_generator.cc                 |    3 +-
+ .../codegen/code_generator.h                  |    3 +-
+ .../codegen/code_generator_test.cc            |    3 +-
+ .../codegen/metadata_helper.h                 |    2 +-
+ .../codegen/python/codegen_lib.cc             |    9 +-
+ .../tensorflow_lite_support/codegen/utils.cc  |   36 +-
+ .../custom_ops/kernel/ngrams.cc               |    7 +-
+ .../custom_ops/kernel/ngrams_op_resolver.cc   |    2 +-
+ .../custom_ops/kernel/ngrams_test.cc          |    9 +-
+ .../kernel/ragged/py_tflite_registerer.h      |    2 +-
+ .../kernel/ragged/ragged_range_tflite.cc      |    9 +-
+ .../kernel/ragged/ragged_range_tflite_test.cc |    3 +-
+ .../ragged/ragged_tensor_to_tensor_tflite.cc  |   47 +-
+ .../ragged_tensor_to_tensor_tflite_test.cc    |    6 +-
+ .../kernel/sentencepiece/model_converter.cc   |   10 +-
+ .../kernel/sentencepiece/model_converter.h    |    6 +-
+ .../sentencepiece/optimized_decoder_test.cc   |    6 +-
+ .../kernel/sentencepiece/optimized_encoder.cc |   23 +-
+ .../kernel/sentencepiece/optimized_encoder.h  |   10 +-
+ .../sentencepiece/optimized_encoder_test.cc   |    8 +-
+ .../sentencepiece/py_tflite_registerer.h      |    2 +-
+ .../sentencepiece_detokenizer_tflite.cc       |    3 +-
+ .../sentencepiece_tokenizer_op.cc             |    6 +-
+ .../sentencepiece_tokenizer_tflite.cc         |    7 +-
+ .../custom_ops/kernel/whitespace_tokenizer.cc |   13 +-
+ .../whitespace_tokenizer_op_resolver.cc       |    2 +-
+ .../audio/desktop/audio_classifier_demo.cc    |   18 +-
+ .../audio/desktop/audio_classifier_lib.cc     |   11 +-
+ .../task/audio/desktop/audio_classifier_lib.h |    3 +-
+ .../text/desktop/bert_nl_classifier_demo.cc   |   14 +-
+ .../desktop/bert_question_answerer_demo.cc    |   18 +-
+ .../task/text/desktop/nl_classifier_demo.cc   |   14 +-
+ .../universal_sentence_encoder_qa_demo.cc     |   32 +-
+ .../vision/desktop/image_classifier_demo.cc   |   34 +-
+ .../vision/desktop/image_embedder_demo.cc     |   30 +-
+ .../vision/desktop/image_segmenter_demo.cc    |   24 +-
+ .../vision/desktop/object_detector_demo.cc    |   40 +-
+ .../task/vision/desktop/utils/image_utils.cc  |   12 +-
+ .../task/vision/desktop/utils/image_utils.h   |    2 +-
+ .../ios/sources/TFLCommon.h                   |   11 +-
+ .../ios/sources/TFLCommonUtils.h              |   41 +-
+ .../ios/sources/TFLCommonUtils.m              |   42 +-
+ .../core/sources/TFLBaseOptions+Helpers.h     |    2 +-
+ .../core/sources/TFLBaseOptions+Helpers.m     |    2 +-
+ .../ios/task/core/sources/TFLBaseOptions.h    |   32 +-
+ .../ios/task/core/sources/TFLBaseOptions.m    |   16 +-
+ .../TFLClassificationOptions+Helpers.h        |    6 +-
+ .../TFLClassificationOptions+Helpers.m        |   66 +-
+ .../sources/TFLClassificationOptions.h        |    9 +-
+ .../sources/TFLClassificationOptions.m        |    5 +-
+ .../sources/TFLClassificationResult.h         |   23 +-
+ .../utils/sources/TFLClassificationUtils.h    |   21 +-
+ .../utils/sources/TFLClassificationUtils.m    |   31 +-
+ .../Sources/TFLBertNLClassifier.h             |   21 +-
+ .../Sources/TFLBertNLClassifier.m             |   28 +-
+ .../nlclassifier/Sources/TFLNLClassifier.h    |   47 +-
+ .../nlclassifier/Sources/TFLNLClassifier.m    |   18 +-
+ .../Tests/TFLBertNLClassifierTest.m           |   29 +-
+ .../nlclassifier/Tests/TFLNLClassifierTest.m  |   28 +-
+ .../text/qa/Sources/TFLBertQuestionAnswerer.h |    4 +-
+ .../text/qa/Sources/TFLBertQuestionAnswerer.m |   23 +-
+ .../qa/Tests/TFLBertQuestionAnswererTest.m    |   33 +-
+ .../task/vision/sources/TFLImageClassifier.h  |   37 +-
+ .../task/vision/sources/TFLImageClassifier.m  |   52 +-
+ .../task/vision/utils/sources/GMLImageUtils.h |    5 +-
+ .../task/vision/utils/sources/GMLImageUtils.m |  146 +-
+ .../TFLImageClassifierTests.m                 |  109 +-
+ .../tokenizers/Sources/TFLBertTokenizer.h     |    6 +-
+ .../tokenizers/Sources/TFLBertTokenizer.mm    |   10 +-
+ .../Sources/TFLSentencepieceTokenizer.h       |    2 +-
+ .../Sources/TFLSentencepieceTokenizer.mm      |   12 +-
+ .../text/tokenizers/Sources/TFLTokenizer.h    |    4 +-
+ .../tokenizers/Sources/TFLTokenizerUtil.h     |   11 +-
+ .../tokenizers/Sources/TFLTokenizerUtil.mm    |   15 +-
+ .../lite/support/audio/TensorAudio.java       |  524 ++---
+ .../lite/support/common/FileUtil.java         |  301 +--
+ .../lite/support/common/Operator.java         |   15 +-
+ .../lite/support/common/Processor.java        |    2 +-
+ .../support/common/SequentialProcessor.java   |   83 +-
+ .../lite/support/common/TensorOperator.java   |    6 +-
+ .../lite/support/common/TensorProcessor.java  |   57 +-
+ .../common/internal/SupportPreconditions.java |  302 +--
+ .../lite/support/common/ops/CastOp.java       |   55 +-
+ .../lite/support/common/ops/DequantizeOp.java |    9 +-
+ .../lite/support/common/ops/NormalizeOp.java  |  245 ++-
+ .../lite/support/common/ops/QuantizeOp.java   |    9 +-
+ .../lite/support/image/BitmapContainer.java   |  116 +-
+ .../lite/support/image/BoundingBoxUtil.java   |  369 ++--
+ .../lite/support/image/ColorSpaceType.java    |  623 +++---
+ .../lite/support/image/ImageContainer.java    |   36 +-
+ .../lite/support/image/ImageConversions.java  |  217 +-
+ .../lite/support/image/ImageOperator.java     |   41 +-
+ .../lite/support/image/ImageProcessor.java    |  285 +--
+ .../lite/support/image/ImageProperties.java   |   91 +-
+ .../support/image/MediaImageContainer.java    |  112 +-
+ .../lite/support/image/MlImageAdapter.java    |  160 +-
+ .../support/image/TensorBufferContainer.java  |  202 +-
+ .../lite/support/image/TensorImage.java       |  677 +++---
+ .../lite/support/image/ops/ResizeOp.java      |  105 +-
+ .../image/ops/ResizeWithCropOrPadOp.java      |  170 +-
+ .../lite/support/image/ops/Rot90Op.java       |  141 +-
+ .../image/ops/TensorOperatorWrapper.java      |   78 +-
+ .../image/ops/TransformToGrayscaleOp.java     |  127 +-
+ .../lite/support/label/Category.java          |  192 +-
+ .../lite/support/label/LabelUtil.java         |   77 +-
+ .../lite/support/label/TensorLabel.java       |  331 +--
+ .../lite/support/label/ops/LabelAxisOp.java   |   70 +-
+ .../lite/support/model/GpuDelegateProxy.java  |   71 +-
+ .../tensorflow/lite/support/model/Model.java  |  449 ++--
+ .../support/tensorbuffer/TensorBuffer.java    |  899 ++++----
+ .../tensorbuffer/TensorBufferFloat.java       |  181 +-
+ .../tensorbuffer/TensorBufferUint8.java       |  188 +-
+ .../audio/classifier/AudioClassifier.java     |  857 ++++----
+ .../audio/classifier/Classifications.java     |   28 +-
+ .../lite/task/core/BaseOptions.java           |  105 +-
+ .../lite/task/core/BaseTaskApi.java           |  122 +-
+ .../lite/task/core/ComputeSettings.java       |   48 +-
+ .../lite/task/core/TaskJniUtils.java          |  275 ++-
+ .../core/vision/ImageProcessingOptions.java   |  125 +-
+ .../text/nlclassifier/BertNLClassifier.java   |  391 ++--
+ .../task/text/nlclassifier/NLClassifier.java  |  568 ++---
+ .../task/text/qa/BertQuestionAnswerer.java    |  394 ++--
+ .../lite/task/text/qa/QaAnswer.java           |   60 +-
+ .../lite/task/text/qa/QuestionAnswerer.java   |   19 +-
+ .../vision/classifier/Classifications.java    |   25 +-
+ .../vision/classifier/ImageClassifier.java    |  882 ++++----
+ .../task/vision/core/BaseVisionTaskApi.java   |  349 ++--
+ .../lite/task/vision/detector/Detection.java  |   26 +-
+ .../task/vision/detector/ObjectDetector.java  |  873 ++++----
+ .../task/vision/segmenter/ColoredLabel.java   |  112 +-
+ .../task/vision/segmenter/ImageSegmenter.java |  752 ++++---
+ .../task/vision/segmenter/OutputType.java     |  202 +-
+ .../task/vision/segmenter/Segmentation.java   |  106 +-
+ .../lite/support/audio/TensorAudioTest.java   |  486 ++---
+ .../lite/support/common/FileUtilTest.java     |  129 +-
+ .../support/common/TensorProcessorTest.java   |   91 +-
+ .../lite/support/common/ops/CastOpTest.java   |   91 +-
+ .../support/common/ops/DequantizeOpTest.java  |   23 +-
+ .../support/common/ops/NormalizeOpTest.java   |  217 +-
+ .../support/common/ops/QuantizeOpTest.java    |   21 +-
+ .../support/image/BoundingBoxUtilTest.java    |  343 ++--
+ .../image/ColorSpaceTypeInstrumentedTest.java |   37 +-
+ .../support/image/ColorSpaceTypeTest.java     |  703 +++----
+ .../ImageConversionsInstrumentedTest.java     |  338 +--
+ .../support/image/ImageConversionsTest.java   |  164 +-
+ .../image/ImageProcessorInstrumentedTest.java |  221 +-
+ .../support/image/ImageProcessorTest.java     |  209 +-
+ .../support/image/MlImageAdapterTest.java     |  259 +--
+ .../image/TensorImageInstrumentedTest.java    |  208 +-
+ .../lite/support/image/TensorImageTest.java   | 1391 ++++++-------
+ .../lite/support/image/TestImageCreator.java  |  183 +-
+ .../image/ops/ResizeOpInstrumentedTest.java   |  103 +-
+ ...ResizeWithCropOrPadOpInstrumentedTest.java |  239 ++-
+ .../image/ops/Rot90OpInstrumentedTest.java    |  122 +-
+ ...ransformToGrayScaleOpInstrumentedTest.java |  104 +-
+ .../lite/support/label/CategoryTest.java      |  204 +-
+ .../lite/support/label/LabelUtilTest.java     |   47 +-
+ .../lite/support/label/TensorLabelTest.java   |  327 +--
+ .../support/label/ops/LabelAxisOpTest.java    |  160 +-
+ .../GpuDelegateProxyInstrumentedTest.java     |   18 +-
+ .../support/model/GpuDelegateProxyTest.java   |   11 +-
+ .../lite/support/model/ModelTest.java         |  244 +--
+ .../tensorbuffer/TensorBufferFloatTest.java   |   82 +-
+ .../tensorbuffer/TensorBufferTest.java        | 1707 +++++++--------
+ .../tensorbuffer/TensorBufferUint8Test.java   |   82 +-
+ .../audio/classifier/audio_classifier_jni.cc  |   42 +-
+ .../src/native/task/core/task_jni_utils.cc    |    5 +-
+ .../bert/bert_nl_classifier_jni.cc            |   23 +-
+ .../text/nlclassifier/nl_classifier_jni.cc    |   21 +-
+ .../text/qa/bert_question_answerer_jni.cc     |   24 +-
+ .../vision/classifier/image_classifier_jni.cc |   27 +-
+ .../vision/core/base_vision_task_api_jni.cc   |   40 +-
+ .../vision/detector/object_detector_jni.cc    |   27 +-
+ .../java/src/native/task/vision/jni_utils.cc  |   30 +-
+ .../java/src/native/task/vision/jni_utils.h   |   28 +-
+ .../vision/segmenter/image_segmenter_jni.cc   |   32 +-
+ .../metadata/cc/metadata_extractor.cc         |   21 +-
+ .../metadata/cc/metadata_extractor.h          |    4 +-
+ .../metadata/cc/metadata_populator.h          |    7 +-
+ .../metadata/cc/metadata_version.cc           |   35 +-
+ .../flatbuffers_lib/flatbuffers_lib.cc        |    2 +-
+ .../support/metadata/BoundedInputStream.java  |  138 +-
+ .../support/metadata/ByteBufferChannel.java   |  188 +-
+ .../support/metadata/MetadataExtractor.java   |  622 +++---
+ .../lite/support/metadata/MetadataParser.java |   12 +-
+ .../lite/support/metadata/ModelInfo.java      |  448 ++--
+ .../support/metadata/ModelMetadataInfo.java   |  243 ++-
+ .../lite/support/metadata/Preconditions.java  |  306 +--
+ .../metadata/SeekableByteChannelCompat.java   |  140 +-
+ .../lite/support/metadata/ZipFile.java        |  686 +++----
+ .../metadata/BoundedInputStreamTest.java      |  429 ++--
+ .../metadata/ByteBufferChannelTest.java       |  480 +++--
+ .../metadata/MetadataExtractorTest.java       | 1828 ++++++++---------
+ .../support/metadata/MetadataParserTest.java  |   18 +-
+ .../lite/support/metadata/ZipFileTest.java    |  206 +-
+ .../odml/ios/image/apis/GMLImage.h            |   47 +-
+ .../odml/ios/image/sources/GMLImage.m         |    2 +-
+ .../odml/ios/image/tests/GMLImageTests.m      |   73 +-
+ .../android/odml/image/BitmapExtractor.java   |   43 +-
+ .../odml/image/BitmapImageContainer.java      |   70 +-
+ .../odml/image/BitmapMlImageBuilder.java      |  137 +-
+ .../odml/image/ByteBufferExtractor.java       |  421 ++--
+ .../odml/image/ByteBufferImageContainer.java  |   68 +-
+ .../odml/image/ByteBufferMlImageBuilder.java  |  135 +-
+ .../android/odml/image/ImageContainer.java    |   12 +-
+ .../android/odml/image/ImageProperties.java   |   92 +-
+ .../odml/image/MediaImageContainer.java       |   81 +-
+ .../odml/image/MediaImageExtractor.java       |   42 +-
+ .../odml/image/MediaMlImageBuilder.java       |  105 +-
+ .../google/android/odml/image/MlImage.java    |  423 ++--
+ .../odml/image/BitmapExtractorTest.java       |   46 +-
+ .../odml/image/BitmapMlImageBuilderTest.java  |  116 +-
+ .../odml/image/ByteBufferExtractorTest.java   |  264 ++-
+ .../image/ByteBufferMlImageBuilderTest.java   |   93 +-
+ .../odml/image/MediaImageExtractorTest.java   |   48 +-
+ .../odml/image/MediaMlImageBuilderTest.java   |  109 +-
+ .../android/odml/image/TestImageCreator.java  |  211 +-
+ .../src/third_party/fft2d/fft.h               |   12 +-
+ .../src/third_party/fft2d/fft2d.h             |   12 +-
+ 324 files changed, 17479 insertions(+), 17052 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc
+index 9f27f3baae82f..6a16d12856258 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc
+@@ -17,12 +17,12 @@ limitations under the License.
+ 
+ #include <glog/logging.h>
+ #include "absl/container/node_hash_map.h"  // from @com_google_absl
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/strings/match.h"  // from @com_google_absl
+-#include "absl/strings/numbers.h"  // from @com_google_absl
+-#include "tflite/public/edgetpu_c.h"
++#include "absl/memory/memory.h"            // from @com_google_absl
++#include "absl/strings/match.h"            // from @com_google_absl
++#include "absl/strings/numbers.h"          // from @com_google_absl
+ #include "tensorflow/lite/experimental/acceleration/configuration/configuration_generated.h"
+ #include "tensorflow/lite/experimental/acceleration/configuration/delegate_registry.h"
++#include "tflite/public/edgetpu_c.h"
+ 
+ namespace tflite {
+ namespace delegates {
+@@ -50,12 +50,16 @@ inline std::string ConvertBool(bool from_bool) {
+   return from_bool ? "True" : "False";
+ }
+ 
+-bool MatchDevice(const std::string& device, const std::string& type,
++bool MatchDevice(const std::string& device,
++                 const std::string& type,
+                  int* index) {
+   const auto prefix(type + ":");
+-  if (!absl::StartsWith(device, prefix)) return false;
+-  if (!absl::SimpleAtoi(device.substr(prefix.size()), index)) return false;
+-  if (*index < 0) return false;
++  if (!absl::StartsWith(device, prefix))
++    return false;
++  if (!absl::SimpleAtoi(device.substr(prefix.size()), index))
++    return false;
++  if (*index < 0)
++    return false;
+   return true;
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc
+index 83cb6f24b1277..cc183a65a9e5f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc
+@@ -43,7 +43,8 @@ using ::tflite::task::vision::ImageDataFree;
+ 
+ using EdgeTpuCoralPluginTest = testing::TestWithParam<std::string>;
+ 
+-INSTANTIATE_TEST_SUITE_P(CoralPluginTests, EdgeTpuCoralPluginTest,
++INSTANTIATE_TEST_SUITE_P(CoralPluginTests,
++                         EdgeTpuCoralPluginTest,
+                          testing::Values(kRegularModelFilePath,
+                                          kEdgeTpuModelFilePath));
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc
+index 2a182bbd6535a..f0974ed26b826 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc
+@@ -17,7 +17,7 @@ limitations under the License.
+ 
+ #include <cstdlib>
+ 
+-void TfLiteSupportErrorDelete(TfLiteSupportError *error) {
++void TfLiteSupportErrorDelete(TfLiteSupportError* error) {
+   // `strdup` obtains memory using `malloc` and the memory needs to be
+   // released using `free`.
+   free(error->message);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common.h b/third_party/tflite_support/src/tensorflow_lite_support/c/common.h
+index 1e21f1dcb31dc..3ced64226987f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/common.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common.h
+@@ -190,10 +190,10 @@ typedef struct TfLiteSupportError {
+   // Holds the error code.
+   enum TfLiteSupportErrorCode code;
+   // Detailed description of the error.
+-  char *message;
++  char* message;
+ } TfLiteSupportError;
+ 
+-void TfLiteSupportErrorDelete(TfLiteSupportError *error);
++void TfLiteSupportErrorDelete(TfLiteSupportError* error);
+ 
+ #ifdef __cplusplus
+ }  // extern "C"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc
+index 39287377c4b36..39afb9c8cbdf3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc
+@@ -18,15 +18,17 @@ limitations under the License.
+ #include <string>
+ 
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/cord.h"  // from @com_google_absl
++#include "absl/strings/cord.h"   // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ 
+ namespace tflite {
+ namespace support {
+ 
+ void CreateTfLiteSupportError(enum TfLiteSupportErrorCode code,
+-                              const char* message, TfLiteSupportError** error) {
+-  if (error == nullptr) return;
++                              const char* message,
++                              TfLiteSupportError** error) {
++  if (error == nullptr)
++    return;
+ 
+   *error = new TfLiteSupportError;
+   (*error)->code = code;
+@@ -35,7 +37,8 @@ void CreateTfLiteSupportError(enum TfLiteSupportErrorCode code,
+ 
+ void CreateTfLiteSupportErrorWithStatus(const absl::Status& status,
+                                         TfLiteSupportError** error) {
+-  if (status.ok() || error == nullptr) return;
++  if (status.ok() || error == nullptr)
++    return;
+ 
+   // Payload of absl::Status created by the tflite task library stores an
+   // appropriate value of the enum TfLiteSupportStatus. The integer value
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h
+index 6959029575663..551f64a598970 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h
+@@ -27,7 +27,8 @@ namespace support {
+ 
+ // Creates a TfLiteSupportError with a TfLiteSupportErrorCode and message.
+ void CreateTfLiteSupportError(enum TfLiteSupportErrorCode code,
+-                              const char* message, TfLiteSupportError** error);
++                              const char* message,
++                              TfLiteSupportError** error);
+ 
+ // Creates a TfLiteSupportError from absl::Status and passes it back as a
+ // parameter which is a pointer to the error pointer.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc
+index 26888a832fc34..52907f4fe7d35 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc
+@@ -40,7 +40,8 @@ struct TfLiteBertNLClassifier {
+ };
+ 
+ TfLiteBertNLClassifier* TfLiteBertNLClassifierCreateFromOptions(
+-    const char* model_path, const TfLiteBertNLClassifierOptions* options) {
++    const char* model_path,
++    const TfLiteBertNLClassifierOptions* options) {
+   BertNLClassifierOptionsCpp cc_options;
+ 
+   cc_options.mutable_base_options()->mutable_model_file()->set_file_name(
+@@ -64,7 +65,8 @@ TfLiteBertNLClassifier* TfLiteBertNLClassifierCreate(const char* model_path) {
+ }
+ 
+ Categories* TfLiteBertNLClassifierClassify(
+-    const TfLiteBertNLClassifier* classifier, const char* text) {
++    const TfLiteBertNLClassifier* classifier,
++    const char* text) {
+   std::vector<CategoryCpp> results =
+ 
+       classifier->impl->Classify(absl::string_view(text).data());
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h
+index 430f5735c6bd2..94138a291233b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h
+@@ -48,7 +48,8 @@ typedef struct TfLiteBertNLClassifierOptions {
+ // Creates TfLiteBertNLClassifier from model path and options, returns nullptr
+ // if the file doesn't exist or is not a well formatted TFLite model path.
+ TfLiteBertNLClassifier* TfLiteBertNLClassifierCreateFromOptions(
+-    const char* model_path, const TfLiteBertNLClassifierOptions* options);
++    const char* model_path,
++    const TfLiteBertNLClassifierOptions* options);
+ 
+ // Creates TfLiteBertNLClassifier from model path and default options, returns
+ // nullptr if the file doesn't exist or is not a well formatted TFLite model
+@@ -57,7 +58,8 @@ TfLiteBertNLClassifier* TfLiteBertNLClassifierCreate(const char* model_path);
+ 
+ // Invokes the encapsulated TFLite model and classifies the input text.
+ Categories* TfLiteBertNLClassifierClassify(
+-    const TfLiteBertNLClassifier* classifier, const char* text);
++    const TfLiteBertNLClassifier* classifier,
++    const char* text);
+ 
+ void TfLiteBertNLClassifierDelete(TfLiteBertNLClassifier* classifier);
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc
+index d0d1639357348..1887d5234d180 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc
+@@ -48,7 +48,8 @@ TfLiteBertQuestionAnswerer* TfLiteBertQuestionAnswererCreate(
+ }
+ 
+ TfLiteQaAnswers* TfLiteBertQuestionAnswererAnswer(
+-    const TfLiteBertQuestionAnswerer* question_answerer, const char* context,
++    const TfLiteBertQuestionAnswerer* question_answerer,
++    const char* context,
+     const char* question) {
+   std::vector<QaAnswerCpp> answers = question_answerer->impl->Answer(
+       absl::string_view(context).data(), absl::string_view(question).data());
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h
+index 7bc6e6ed385db..e9a1190356914 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h
+@@ -58,7 +58,8 @@ TfLiteBertQuestionAnswerer* TfLiteBertQuestionAnswererCreate(
+ // Invokes the encapsulated TFLite model and answers a question based on
+ // context.
+ TfLiteQaAnswers* TfLiteBertQuestionAnswererAnswer(
+-    const TfLiteBertQuestionAnswerer* question_answerer, const char* context,
++    const TfLiteBertQuestionAnswerer* question_answerer,
++    const char* context,
+     const char* question);
+ 
+ void TfLiteBertQuestionAnswererDelete(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc
+index d6d86f67a620a..1e6805c1d1cd6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc
+@@ -37,7 +37,8 @@ struct TfLiteNLClassifier {
+ };
+ 
+ TfLiteNLClassifier* TfLiteNLClassifierCreateFromOptions(
+-    const char* model_path, const TfLiteNLClassifierOptions* options) {
++    const char* model_path,
++    const TfLiteNLClassifierOptions* options) {
+   auto classifier_status = NLClassifierCpp::CreateFromFileAndOptions(
+       std::string(model_path),
+       {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h
+index c47dd59b13eb4..389ca5d686df0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h
+@@ -48,7 +48,8 @@ typedef struct TfLiteNLClassifierOptions {
+ // Creates TfLiteNLClassifier from model path and options, returns nullptr if
+ // the file doesn't exist or is not a well formatted TFLite model path.
+ TfLiteNLClassifier* TfLiteNLClassifierCreateFromOptions(
+-    const char* model_path, const TfLiteNLClassifierOptions* options);
++    const char* model_path,
++    const TfLiteNLClassifierOptions* options);
+ 
+ // Invokes the encapsulated TFLite model and classifies the input text.
+ Categories* TfLiteNLClassifierClassify(const TfLiteNLClassifier* classifier,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc
+index edf3889059b27..8981e66b41d0c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc
+@@ -108,7 +108,8 @@ TfLiteImageClassifierOptions TfLiteImageClassifierOptionsCreate() {
+ }
+ 
+ TfLiteImageClassifier* TfLiteImageClassifierFromOptions(
+-    const TfLiteImageClassifierOptions* options, TfLiteSupportError** error) {
++    const TfLiteImageClassifierOptions* options,
++    TfLiteSupportError** error) {
+   StatusOr<ImageClassifierOptionsCpp> cpp_option_status =
+       CreateImageClassifierCppOptionsFromCOptions(options);
+ 
+@@ -175,7 +176,8 @@ TfLiteClassificationResult* GetClassificationResultCStruct(
+ 
+ TfLiteClassificationResult* TfLiteImageClassifierClassifyWithRoi(
+     const TfLiteImageClassifier* classifier,
+-    const TfLiteFrameBuffer* frame_buffer, const TfLiteBoundingBox* roi,
++    const TfLiteFrameBuffer* frame_buffer,
++    const TfLiteBoundingBox* roi,
+     TfLiteSupportError** error) {
+   if (classifier == nullptr) {
+     tflite::support::CreateTfLiteSupportError(
+@@ -219,7 +221,8 @@ TfLiteClassificationResult* TfLiteImageClassifierClassifyWithRoi(
+ 
+ TfLiteClassificationResult* TfLiteImageClassifierClassify(
+     const TfLiteImageClassifier* classifier,
+-    const TfLiteFrameBuffer* frame_buffer, TfLiteSupportError** error) {
++    const TfLiteFrameBuffer* frame_buffer,
++    TfLiteSupportError** error) {
+   return TfLiteImageClassifierClassifyWithRoi(classifier, frame_buffer, nullptr,
+                                               error);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h
+index 290e57d56f5a1..8a53e5e2a079e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h
+@@ -158,7 +158,8 @@ TfLiteImageClassifierOptions TfLiteImageClassifierOptionsCreate();
+ // TfLiteSupportErrorDelete(error)
+ //
+ TfLiteImageClassifier* TfLiteImageClassifierFromOptions(
+-    const TfLiteImageClassifierOptions* options, TfLiteSupportError** error);
++    const TfLiteImageClassifierOptions* options,
++    TfLiteSupportError** error);
+ 
+ // Invokes the encapsulated TFLite model and classifies the frame_buffer.
+ // Returns a pointer to the created classification result in case of success or
+@@ -186,7 +187,8 @@ TfLiteImageClassifier* TfLiteImageClassifierFromOptions(
+ //
+ TfLiteClassificationResult* TfLiteImageClassifierClassify(
+     const TfLiteImageClassifier* classifier,
+-    const TfLiteFrameBuffer* frame_buffer, TfLiteSupportError** error);
++    const TfLiteFrameBuffer* frame_buffer,
++    TfLiteSupportError** error);
+ 
+ // Invokes the encapsulated TFLite model and classifies the region of the
+ // frame_buffer specified by the bounding box. Same as TfLiteImageClassifier*
+@@ -198,7 +200,8 @@ TfLiteClassificationResult* TfLiteImageClassifierClassify(
+ // operations.
+ TfLiteClassificationResult* TfLiteImageClassifierClassifyWithRoi(
+     const TfLiteImageClassifier* classifier,
+-    const TfLiteFrameBuffer* frame_buffer, const TfLiteBoundingBox* roi,
++    const TfLiteFrameBuffer* frame_buffer,
++    const TfLiteBoundingBox* roi,
+     TfLiteSupportError** error);
+ 
+ // Disposes off the image classifier.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h
+index a46cf043aeb24..5a2d3e1d1e4d2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h
+@@ -157,7 +157,8 @@ TfLiteObjectDetectorOptions TfLiteObjectDetectorOptionsCreate();
+ // TfLiteSupportErrorDelete(error)
+ //
+ TfLiteObjectDetector* TfLiteObjectDetectorFromOptions(
+-    const TfLiteObjectDetectorOptions* options, TfLiteSupportError** error);
++    const TfLiteObjectDetectorOptions* options,
++    TfLiteSupportError** error);
+ 
+ // Invokes the encapsulated TFLite model and performs object detection on the
+ // frame_buffer. Returns a pointer to the created object detection result result
+@@ -185,7 +186,8 @@ TfLiteObjectDetector* TfLiteObjectDetectorFromOptions(
+ // TfLiteSupportErrorDelete(error)
+ //
+ TfLiteDetectionResult* TfLiteObjectDetectorDetect(
+-    const TfLiteObjectDetector* detector, const TfLiteFrameBuffer* frame_buffer,
++    const TfLiteObjectDetector* detector,
++    const TfLiteFrameBuffer* frame_buffer,
+     TfLiteSupportError** error);
+ 
+ // Disposes off the object detector.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc
+index 688af14580ab3..b398b7adafe5c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc
+@@ -44,8 +44,8 @@ constexpr char kMobileNetQuantizedWithMetadata[] =
+     "mobilenet_v1_0.25_224_quant.tflite";
+ 
+ StatusOr<ImageData> LoadImage(const char* image_name) {
+-  return DecodeImageFromFile(JoinPath("./" /*test src dir*/,
+-                                      kTestDataDirectory, image_name));
++  return DecodeImageFromFile(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+ }
+ 
+ class ImageClassifierFromOptionsTest : public tflite_shims::testing::Test {};
+@@ -56,7 +56,8 @@ TEST_F(ImageClassifierFromOptionsTest, FailsWithNullOptionsAndError) {
+       TfLiteImageClassifierFromOptions(nullptr, &error);
+ 
+   EXPECT_EQ(image_classifier, nullptr);
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
+ 
+   ASSERT_NE(error, nullptr);
+   EXPECT_EQ(error->code, kInvalidArgumentError);
+@@ -71,7 +72,8 @@ TEST_F(ImageClassifierFromOptionsTest, FailsWithMissingModelPath) {
+   TfLiteImageClassifier* image_classifier =
+       TfLiteImageClassifierFromOptions(&options, nullptr);
+   EXPECT_EQ(image_classifier, nullptr);
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
+ }
+ 
+ TEST_F(ImageClassifierFromOptionsTest, FailsWithMissingModelPathAndError) {
+@@ -82,7 +84,8 @@ TEST_F(ImageClassifierFromOptionsTest, FailsWithMissingModelPathAndError) {
+       TfLiteImageClassifierFromOptions(&options, &error);
+ 
+   EXPECT_EQ(image_classifier, nullptr);
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
+ 
+   ASSERT_NE(error, nullptr);
+   EXPECT_EQ(error->code, kInvalidArgumentError);
+@@ -93,9 +96,8 @@ TEST_F(ImageClassifierFromOptionsTest, FailsWithMissingModelPathAndError) {
+ }
+ 
+ TEST_F(ImageClassifierFromOptionsTest, SucceedsWithModelPath) {
+-  std::string model_path =
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetQuantizedWithMetadata);
++  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
++                                    kMobileNetQuantizedWithMetadata);
+   TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+   options.base_options.model_file.file_path = model_path.data();
+   TfLiteImageClassifier* image_classifier =
+@@ -106,9 +108,8 @@ TEST_F(ImageClassifierFromOptionsTest, SucceedsWithModelPath) {
+ }
+ 
+ TEST_F(ImageClassifierFromOptionsTest, SucceedsWithNumberOfThreadsAndError) {
+-  std::string model_path =
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetQuantizedWithMetadata);
++  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
++                                    kMobileNetQuantizedWithMetadata);
+   TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+   options.base_options.model_file.file_path = model_path.data();
+   options.base_options.compute_settings.cpu_settings.num_threads = 3;
+@@ -120,15 +121,16 @@ TEST_F(ImageClassifierFromOptionsTest, SucceedsWithNumberOfThreadsAndError) {
+   EXPECT_NE(image_classifier, nullptr);
+   EXPECT_EQ(error, nullptr);
+ 
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
+-  if (error) TfLiteSupportErrorDelete(error);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
++  if (error)
++    TfLiteSupportErrorDelete(error);
+ }
+ 
+ TEST_F(ImageClassifierFromOptionsTest,
+        FailsWithClassNameDenyListAndClassNameAllowListAndError) {
+-  std::string model_path =
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetQuantizedWithMetadata);
++  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
++                                    kMobileNetQuantizedWithMetadata);
+ 
+   TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+   options.base_options.model_file.file_path = model_path.data();
+@@ -146,7 +148,8 @@ TEST_F(ImageClassifierFromOptionsTest,
+       TfLiteImageClassifierFromOptions(&options, &error);
+ 
+   EXPECT_EQ(image_classifier, nullptr);
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
+ 
+   ASSERT_NE(error, nullptr);
+   EXPECT_EQ(error->code, kInvalidArgumentError);
+@@ -158,7 +161,8 @@ TEST_F(ImageClassifierFromOptionsTest,
+ 
+ TEST(ImageClassifierNullClassifierClassifyTest,
+      FailsWithNullImageClassifierAndError) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteSupportError* error = nullptr;
+   TfLiteClassificationResult* classification_result =
+@@ -181,9 +185,8 @@ TEST(ImageClassifierNullClassifierClassifyTest,
+ class ImageClassifierClassifyTest : public tflite_shims::testing::Test {
+  protected:
+   void SetUp() override {
+-    std::string model_path =
+-        JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-                 kMobileNetQuantizedWithMetadata);
++    std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
++                                      kMobileNetQuantizedWithMetadata);
+ 
+     TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+     options.base_options.model_file.file_path = model_path.data();
+@@ -196,7 +199,8 @@ class ImageClassifierClassifyTest : public tflite_shims::testing::Test {
+ };
+ 
+ TEST_F(ImageClassifierClassifyTest, SucceedsWithImageData) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteFrameBuffer frame_buffer = {
+       .format = kRGB,
+@@ -223,7 +227,8 @@ TEST_F(ImageClassifierClassifyTest, SucceedsWithImageData) {
+ }
+ 
+ TEST_F(ImageClassifierClassifyTest, FailsWithNullFrameBufferAndError) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteSupportError* error = nullptr;
+   TfLiteClassificationResult* classification_result =
+@@ -244,7 +249,8 @@ TEST_F(ImageClassifierClassifyTest, FailsWithNullFrameBufferAndError) {
+ }
+ 
+ TEST_F(ImageClassifierClassifyTest, FailsWithNullImageDataAndError) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteFrameBuffer frame_buffer = {.format = kRGB, .orientation = kTopLeft};
+ 
+@@ -267,7 +273,8 @@ TEST_F(ImageClassifierClassifyTest, FailsWithNullImageDataAndError) {
+ }
+ 
+ TEST_F(ImageClassifierClassifyTest, SucceedsWithRoiWithinImageBounds) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteFrameBuffer frame_buffer = {
+       .format = kRGB,
+@@ -298,7 +305,8 @@ TEST_F(ImageClassifierClassifyTest, SucceedsWithRoiWithinImageBounds) {
+ }
+ 
+ TEST_F(ImageClassifierClassifyTest, FailsWithRoiOutsideImageBoundsAndError) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteFrameBuffer frame_buffer = {
+       .format = kRGB,
+@@ -330,9 +338,8 @@ TEST_F(ImageClassifierClassifyTest, FailsWithRoiOutsideImageBoundsAndError) {
+ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+      SucceedsWithClassNameDenyList) {
+   char* denylisted_label_name = (char*)"cheeseburger";
+-  std::string model_path =
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetQuantizedWithMetadata);
++  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
++                                    kMobileNetQuantizedWithMetadata);
+ 
+   TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+   options.base_options.model_file.file_path = model_path.data();
+@@ -345,7 +352,8 @@ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+       TfLiteImageClassifierFromOptions(&options, nullptr);
+   ASSERT_NE(image_classifier, nullptr);
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteFrameBuffer frame_buffer = {
+       .format = kRGB,
+@@ -357,7 +365,8 @@ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+       TfLiteImageClassifierClassify(image_classifier, &frame_buffer, nullptr);
+ 
+   ImageDataFree(&image_data);
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
+ 
+   ASSERT_NE(classification_result, nullptr);
+   EXPECT_GE(classification_result->size, 1);
+@@ -374,10 +383,9 @@ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+      SucceedsWithClassNameAllowList) {
+   char* allowlisted_label_name = (char*)"cheeseburger";
+-  std::string model_path =
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetQuantizedWithMetadata)
+-          .data();
++  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
++                                    kMobileNetQuantizedWithMetadata)
++                               .data();
+ 
+   TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+   options.base_options.model_file.file_path = model_path.data();
+@@ -390,7 +398,8 @@ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+       TfLiteImageClassifierFromOptions(&options, nullptr);
+   ASSERT_NE(image_classifier, nullptr);
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data, LoadImage("burger-224.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
++                               LoadImage("burger-224.png"));
+ 
+   TfLiteFrameBuffer frame_buffer = {
+       .format = kRGB,
+@@ -402,7 +411,8 @@ TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+       TfLiteImageClassifierClassify(image_classifier, &frame_buffer, nullptr);
+ 
+   ImageDataFree(&image_data);
+-  if (image_classifier) TfLiteImageClassifierDelete(image_classifier);
++  if (image_classifier)
++    TfLiteImageClassifierDelete(image_classifier);
+ 
+   ASSERT_NE(classification_result, nullptr);
+   EXPECT_GE(classification_result->size, 1);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc
+index abfef722d6659..09e9a83e07bef 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc
+@@ -15,7 +15,7 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/cc/common.h"
+ 
+-#include "absl/strings/cord.h"  // from @com_google_absl
++#include "absl/strings/cord.h"     // from @com_google_absl
+ #include "absl/strings/str_cat.h"  // from @com_google_absl
+ 
+ namespace tflite {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h
+index b06e9f58459af..71dd920b86bed 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h
+@@ -16,7 +16,7 @@ limitations under the License.
+ #ifndef TENSORFLOW_LITE_SUPPORT_CC_COMMON_H_
+ #define TENSORFLOW_LITE_SUPPORT_CC_COMMON_H_
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ 
+ namespace tflite {
+@@ -164,7 +164,8 @@ enum class TfLiteSupportStatus {
+ // more than returning an object identical to an OK status. See `absl::Status`
+ // for more details.
+ absl::Status CreateStatusWithPayload(
+-    absl::StatusCode canonical_code, absl::string_view message,
++    absl::StatusCode canonical_code,
++    absl::string_view message,
+     tflite::support::TfLiteSupportStatus tfls_code =
+         tflite::support::TfLiteSupportStatus::kError);
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h
+index 14999ca37b7ac..cb145dbd232c8 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ #define TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUS_MACROS_H_
+ 
+ #include "absl/base/optimization.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"      // from @com_google_absl
+ 
+ // Evaluates an expression that produces a `absl::Status`. If the status is not
+ // ok, returns it from the current function.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h
+index dc04c293c6ffd..81ec3c1ab5f86 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h
+@@ -21,8 +21,8 @@ limitations under the License.
+ #include <utility>
+ 
+ #include "absl/meta/type_traits.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/utility/utility.h"  // from @com_google_absl
++#include "absl/status/status.h"     // from @com_google_absl
++#include "absl/utility/utility.h"   // from @com_google_absl
+ 
+ namespace tflite {
+ namespace support {
+@@ -63,7 +63,8 @@ struct IsDirectInitializationAmbiguous
+                        U>::value,
+           std::false_type,
+           IsDirectInitializationAmbiguous<
+-              T, absl::remove_cv_t<absl::remove_reference_t<U>>>> {};
++              T,
++              absl::remove_cv_t<absl::remove_reference_t<U>>>> {};
+ 
+ template <typename T, typename V>
+ struct IsDirectInitializationAmbiguous<T, tflite::support::StatusOr<V>>
+@@ -101,7 +102,8 @@ struct IsForwardingAssignmentAmbiguous
+                        U>::value,
+           std::false_type,
+           IsForwardingAssignmentAmbiguous<
+-              T, absl::remove_cv_t<absl::remove_reference_t<U>>>> {};
++              T,
++              absl::remove_cv_t<absl::remove_reference_t<U>>>> {};
+ 
+ template <typename T, typename U>
+ struct IsForwardingAssignmentAmbiguous<T, tflite::support::StatusOr<U>>
+@@ -136,7 +138,8 @@ template <typename T, typename... Args>
+ void PlacementNew(void* p, Args&&... args) {
+ #if defined(__GNUC__) && !defined(__clang__)
+   // Teach gcc that 'p' cannot be null, fixing code size issues.
+-  if (p == nullptr) __builtin_unreachable();
++  if (p == nullptr)
++    __builtin_unreachable();
+ #endif
+   new (p) T(std::forward<Args>(args)...);
+ }
+@@ -207,7 +210,8 @@ class StatusOrData {
+   }
+ 
+   StatusOrData& operator=(const StatusOrData& other) {
+-    if (this == &other) return *this;
++    if (this == &other)
++      return *this;
+     if (other.ok())
+       Assign(other.data_);
+     else
+@@ -216,7 +220,8 @@ class StatusOrData {
+   }
+ 
+   StatusOrData& operator=(StatusOrData&& other) {
+-    if (this == &other) return *this;
++    if (this == &other)
++      return *this;
+     if (other.ok())
+       Assign(std::move(other.data_));
+     else
+@@ -295,15 +300,18 @@ class StatusOrData {
+   };
+ 
+   void Clear() {
+-    if (ok()) data_.~T();
++    if (ok())
++      data_.~T();
+   }
+ 
+   void EnsureOk() const {
+-    if (ABSL_PREDICT_FALSE(!ok())) Helper::Crash(status_);
++    if (ABSL_PREDICT_FALSE(!ok()))
++      Helper::Crash(status_);
+   }
+ 
+   void EnsureNotOk() {
+-    if (ABSL_PREDICT_FALSE(ok())) Helper::HandleInvalidStatusCtorArg(&status_);
++    if (ABSL_PREDICT_FALSE(ok()))
++      Helper::HandleInvalidStatusCtorArg(&status_);
+   }
+ 
+   // Construct the value (ie. data_) through placement new with the passed
+@@ -362,8 +370,9 @@ struct MoveCtorBase<T, false> {
+   MoveCtorBase& operator=(MoveCtorBase&&) = default;
+ };
+ 
+-template <typename T, bool = std::is_copy_constructible<T>::value&&
+-                          std::is_copy_assignable<T>::value>
++template <typename T,
++          bool = std::is_copy_constructible<T>::value&&
++              std::is_copy_assignable<T>::value>
+ struct CopyAssignBase {
+   CopyAssignBase() = default;
+   CopyAssignBase(const CopyAssignBase&) = default;
+@@ -381,8 +390,9 @@ struct CopyAssignBase<T, false> {
+   CopyAssignBase& operator=(CopyAssignBase&&) = default;
+ };
+ 
+-template <typename T, bool = std::is_move_constructible<T>::value&&
+-                          std::is_move_assignable<T>::value>
++template <typename T,
++          bool = std::is_move_constructible<T>::value&&
++              std::is_move_assignable<T>::value>
+ struct MoveAssignBase {
+   MoveAssignBase() = default;
+   MoveAssignBase(const MoveAssignBase&) = default;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc
+index 6334c02d738a6..0b3e5d6a2269a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc
+@@ -15,7 +15,7 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/cc/port/default/tflite_wrapper.h"
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/delegates/interpreter_utils.h"
+@@ -53,7 +53,8 @@ TfLiteInterpreterWrapper::TfLiteInterpreterWrapper(
+     : delegate_(nullptr, nullptr),
+       got_error_do_not_delegate_anymore_(false),
+       default_model_namespace_(default_model_namespace),
+-      default_model_id_(default_model_id), mini_benchmark_(nullptr) {}
++      default_model_id_(default_model_id),
++      mini_benchmark_(nullptr) {}
+ 
+ std::string TfLiteInterpreterWrapper::ModelNamespace() {
+   const auto& ns_from_acceleration =
+@@ -299,7 +300,9 @@ absl::Status TfLiteInterpreterWrapper::InvokeWithoutFallback() {
+   return absl::OkStatus();
+ }
+ 
+-void TfLiteInterpreterWrapper::Cancel() { cancel_flag_.Set(true); }
++void TfLiteInterpreterWrapper::Cancel() {
++  cancel_flag_.Set(true);
++}
+ 
+ void TfLiteInterpreterWrapper::SetTfLiteCancellation() {
+   // Create a cancellation check function and set to the TFLite interpreter.
+@@ -312,7 +315,8 @@ void TfLiteInterpreterWrapper::SetTfLiteCancellation() {
+ }
+ 
+ absl::Status TfLiteInterpreterWrapper::LoadDelegatePlugin(
+-    const std::string& name, const tflite::TFLiteSettings& tflite_settings) {
++    const std::string& name,
++    const tflite::TFLiteSettings& tflite_settings) {
+   delegate_plugin_ = DelegatePluginRegistry::CreateByName(
+       absl::StrFormat("%sPlugin", name), tflite_settings);
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h
+index 278ae7643264e..9f32fa8735ccf 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h
+@@ -19,7 +19,7 @@ limitations under the License.
+ #include <string>
+ #include <utility>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/experimental/acceleration/configuration/configuration.pb.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h
+index 0d808ab24d6cc..dc6183bee693c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h
+@@ -37,7 +37,7 @@ typedef unsigned long uword_t;
+ #define GG_LL_FORMAT "ll"  // As in "%lld". Note that "q" is poor form also.
+ #define GG_LL_FORMAT_W L"ll"
+ 
+-const uint8   kuint8max{0xFF};
++const uint8 kuint8max{0xFF};
+ const uint16 kuint16max{0xFFFF};
+ const uint32 kuint32max{0xFFFFFFFF};
+ const uint64 kuint64max{GG_ULONGLONG(0xFFFFFFFFFFFFFFFF)};
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc
+index 4b1439dcc0719..4be3e53c11972 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc
+@@ -17,7 +17,7 @@ limitations under the License.
+ 
+ #include <initializer_list>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/c_api_types.h"
+ #include "tensorflow_lite_support/cc/common.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h
+index 28b379996cb42..a3d4c5717f239 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h
+@@ -27,9 +27,9 @@ limitations under the License.
+ namespace tflite {
+ namespace task {
+ namespace audio {
+-class AudioEmbedder
+-    : public tflite::task::core::BaseTaskApi<
+-          tflite::task::processor::EmbeddingResult, const AudioBuffer&> {
++class AudioEmbedder : public tflite::task::core::BaseTaskApi<
++                          tflite::task::processor::EmbeddingResult,
++                          const AudioBuffer&> {
+  public:
+   // Use base class constructor.
+   using BaseTaskApi::BaseTaskApi;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h
+index 39110ed8d0b15..d922e48af25bc 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h
+@@ -17,8 +17,8 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/memory/memory.h"       // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -41,7 +41,8 @@ class AudioBuffer {
+   // Factory method for creating an AudioBuffer object. The internal buffer does
+   // not take the ownership of the input backing buffer.
+   static tflite::support::StatusOr<std::unique_ptr<AudioBuffer>> Create(
+-      const float* audio_buffer, int buffer_size,
++      const float* audio_buffer,
++      int buffer_size,
+       const AudioFormat& audio_format) {
+     return absl::make_unique<AudioBuffer>(audio_buffer, buffer_size,
+                                           audio_format);
+@@ -50,7 +51,8 @@ class AudioBuffer {
+   // AudioBuffer for internal use only. Uses the factory method to construct
+   // AudioBuffer instance. The internal buffer does not take the ownership of
+   // the input backing buffer.
+-  AudioBuffer(const float* audio_buffer, int buffer_size,
++  AudioBuffer(const float* audio_buffer,
++              int buffer_size,
+               const AudioFormat& audio_format)
+       : audio_buffer_(audio_buffer),
+         buffer_size_(buffer_size),
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc
+index 3c0ad996a9919..9ae3fbec70543 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc
+@@ -27,9 +27,9 @@ limitations under the License.
+ #include <fstream>
+ #include <limits>
+ 
+-#include "absl/base/casts.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_cat.h"  // from @com_google_absl
++#include "absl/base/casts.h"          // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/str_cat.h"     // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ 
+@@ -62,7 +62,9 @@ std::string ReadFile(const std::string filepath) {
+ 
+ // Handles moving the data index forward, validating the arguments, and avoiding
+ // overflow or underflow.
+-absl::Status IncrementOffset(int old_offset, size_t increment, size_t max_size,
++absl::Status IncrementOffset(int old_offset,
++                             size_t increment,
++                             size_t max_size,
+                              int* new_offset) {
+   if (old_offset < 0) {
+     return absl::InvalidArgumentError(
+@@ -87,7 +89,8 @@ absl::Status IncrementOffset(int old_offset, size_t increment, size_t max_size,
+ }
+ 
+ absl::Status ExpectText(const std::string& data,
+-                        const std::string& expected_text, int* offset) {
++                        const std::string& expected_text,
++                        int* offset) {
+   int new_offset;
+   RETURN_IF_ERROR(
+       IncrementOffset(*offset, expected_text.size(), data.size(), &new_offset));
+@@ -101,8 +104,10 @@ absl::Status ExpectText(const std::string& data,
+   return absl::OkStatus();
+ }
+ 
+-absl::Status ReadString(const std::string& data, int expected_length,
+-                        std::string* value, int* offset) {
++absl::Status ReadString(const std::string& data,
++                        int expected_length,
++                        std::string* value,
++                        int* offset) {
+   int new_offset;
+   RETURN_IF_ERROR(
+       IncrementOffset(*offset, expected_length, data.size(), &new_offset));
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h
+index 51271fc065c83..9aca5d06f7985 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h
+@@ -20,9 +20,9 @@ limitations under the License.
+ 
+ #define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_UTILS_WAV_IO_H_
+ 
++#include <cstdint>
+ #include <string>
+ #include <vector>
+-#include <cstdint>
+ 
+ #include "absl/status/status.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -64,7 +64,9 @@ absl::Status DecodeLin16WaveAsFloatVector(const std::string& wav_string,
+ 
+ // Handles moving the data index forward, validating the arguments, and avoiding
+ // overflow or underflow.
+-absl::Status IncrementOffset(int old_offset, size_t increment, size_t max_size,
++absl::Status IncrementOffset(int old_offset,
++                             size_t increment,
++                             size_t max_size,
+                              int* new_offset);
+ 
+ // This function is only exposed in the header for testing purposes, as a
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h
+index d743383734b42..effd42f0f0336 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ 
+ #include <utility>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow_lite_support/cc/common.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h
+index c868060f9894a..c91552f7ec82e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
++#include "absl/memory/memory.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc
+index 80dea95cce24b..a626ce6030b96 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc
+@@ -35,9 +35,13 @@ int ErrorReporter::Report(const char* format, va_list args) {
+   return num_characters;
+ }
+ 
+-std::string ErrorReporter::message() { return last_message_; }
++std::string ErrorReporter::message() {
++  return last_message_;
++}
+ 
+-std::string ErrorReporter::previous_message() { return second_last_message_; }
++std::string ErrorReporter::previous_message() {
++  return second_last_message_;
++}
+ 
+ }  // namespace core
+ }  // namespace task
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc
+index 694c55ab34e78..72e4b670cb172 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc
+@@ -15,7 +15,7 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+ 
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "absl/strings/str_split.h"  // from @com_google_absl
++#include "absl/strings/str_split.h"   // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ 
+ namespace tflite {
+@@ -28,7 +28,8 @@ using ::tflite::support::StatusOr;
+ using ::tflite::support::TfLiteSupportStatus;
+ 
+ StatusOr<std::vector<LabelMapItem>> BuildLabelMapFromFiles(
+-    absl::string_view labels_file, absl::string_view display_names_file) {
++    absl::string_view labels_file,
++    absl::string_view display_names_file) {
+   if (labels_file.empty()) {
+     return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                    "Expected non-empty labels file.",
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h
+index 4d8422a2a572d..d8e1f70d8fab1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h
+@@ -20,8 +20,8 @@ limitations under the License.
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+ #include "absl/container/flat_hash_set.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/string_view.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/string_view.h"      // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ 
+ namespace tflite {
+@@ -49,7 +49,8 @@ struct LabelMapItem {
+ // Returns an error e.g. if there's a mismatch between the number of labels and
+ // display names.
+ tflite::support::StatusOr<std::vector<LabelMapItem>> BuildLabelMapFromFiles(
+-    absl::string_view labels_file, absl::string_view display_names_file);
++    absl::string_view labels_file,
++    absl::string_view display_names_file);
+ 
+ // A class that represents a hierarchy of labels as specified in a label map.
+ //
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/external_file.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/external_file.proto
+index c0a42124e1b50..91b6a214b1253 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/external_file.proto
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/external_file.proto
+@@ -17,7 +17,6 @@ syntax = "proto2";
+ 
+ package tflite.task.core;
+ 
+-
+ // Represents external files used by the Task APIs (e.g. TF Lite FlatBuffer or
+ // plain-text labels file). The files can be specified by one of the following
+ // three ways:
+@@ -64,4 +63,3 @@ message FileDescriptorMeta {
+   // offset of a given asset obtained from AssetFileDescriptor#getStartOffset().
+   optional int64 offset = 3;
+ }
+-
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc
+index 818839a77e43d..e7faebad487b9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc
+@@ -19,11 +19,11 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "absl/strings/str_split.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
++#include "absl/strings/str_format.h"   // from @com_google_absl
++#include "absl/strings/str_split.h"    // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "absl/types/optional.h"  // from @com_google_absl
++#include "absl/types/optional.h"       // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h
+index c1b945f76ab48..6e2b308bef101 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h
+@@ -23,9 +23,9 @@ limitations under the License.
+ #include <vector>
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "absl/types/optional.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/string_view.h"      // from @com_google_absl
++#include "absl/types/optional.h"           // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+@@ -37,7 +37,10 @@ namespace core {
+ // Sigmoid structure.
+ struct Sigmoid {
+   Sigmoid() : scale(1.0) {}
+-  Sigmoid(std::string label, float slope, float offset, float scale = 1.0,
++  Sigmoid(std::string label,
++          float slope,
++          float offset,
++          float scale = 1.0,
+           absl::optional<float> min_uncalibrated_score = absl::nullopt)
+       : label(label),
+         slope(slope),
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h
+index 4e4b42cceaff7..f42d703fd1ae8 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/base/macros.h"  // from @com_google_absl
++#include "absl/base/macros.h"    // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+ #include "tensorflow/lite/core/api/op_resolver.h"
+ #include "tensorflow/lite/kernels/op_macros.h"
+@@ -48,7 +48,8 @@ class TaskAPIFactory {
+       "Use CreateFromBaseOptions and configure model input from "
+       "tensorflow_lite_support/cc/task/core/proto/base_options.proto")
+   static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromBuffer(
+-      const char* buffer_data, size_t buffer_size,
++      const char* buffer_data,
++      size_t buffer_size,
+       std::unique_ptr<tflite::OpResolver> resolver =
+           absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+       int num_threads = 1,
+@@ -151,7 +152,8 @@ class TaskAPIFactory {
+  private:
+   template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
+   static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromTfLiteEngine(
+-      std::unique_ptr<TfLiteEngine> engine, int num_threads,
++      std::unique_ptr<TfLiteEngine> engine,
++      int num_threads,
+       const tflite::proto::ComputeSettings& compute_settings =
+           tflite::proto::ComputeSettings()) {
+     tflite::proto::ComputeSettings settings_copy =
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
+index e95ea73a4a812..7cde474dcd8f6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
+@@ -21,9 +21,9 @@ limitations under the License.
+ #include <numeric>
+ #include <vector>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_cat.h"  // from @com_google_absl
++#include "absl/memory/memory.h"       // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/str_cat.h"     // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+@@ -65,9 +65,11 @@ tflite::support::StatusOr<T*> AssertAndReturnTypedTensor(
+ // type or has not the same number of elements.
+ // Note: std::negation is not used because it is from C++17, where the code will
+ // be compiled using C++14 in OSS.
+-template <typename T, typename = std::enable_if_t<
+-                          std::is_same<T, std::string>::value == false>>
+-inline absl::Status PopulateTensor(const T* data, int num_elements,
++template <
++    typename T,
++    typename = std::enable_if_t<std::is_same<T, std::string>::value == false>>
++inline absl::Status PopulateTensor(const T* data,
++                                   int num_elements,
+                                    TfLiteTensor* tensor) {
+   T* v;
+   ASSIGN_OR_RETURN(v, AssertAndReturnTypedTensor<T>(tensor));
+@@ -92,7 +94,8 @@ inline absl::Status PopulateTensor(const std::vector<T>& data,
+ 
+ template <>
+ inline absl::Status PopulateTensor<std::string>(
+-    const std::vector<std::string>& data, TfLiteTensor* tensor) {
++    const std::vector<std::string>& data,
++    TfLiteTensor* tensor) {
+   if (tensor->type != kTfLiteString) {
+     return tflite::support::CreateStatusWithPayload(
+         absl::StatusCode::kInternal,
+@@ -143,7 +146,8 @@ inline absl::Status PopulateVector(const TfLiteTensor* tensor,
+ 
+ template <>
+ inline absl::Status PopulateVector<std::string>(
+-    const TfLiteTensor* tensor, std::vector<std::string>* data) {
++    const TfLiteTensor* tensor,
++    std::vector<std::string>* data) {
+   if (tensor->type != typeToTfLiteType<std::string>()) {
+     return absl::InvalidArgumentError("not of type string");
+   }
+@@ -161,7 +165,8 @@ inline absl::Status PopulateVector<std::string>(
+ // Note: std::negation is not used because it is from C++17, where the code will
+ // be compiled using C++14 in OSS.
+ template <
+-    class TRepeatedField, class T = float,
++    class TRepeatedField,
++    class T = float,
+     typename = std::enable_if_t<std::is_same<T, std::string>::value == false>>
+ inline absl::Status PopulateVectorToRepeated(const TfLiteTensor* tensor,
+                                              TRepeatedField* data) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+index 484b9a099ecdc..0b34bad4f18f7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+@@ -17,7 +17,7 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/strings/match.h"  // from @com_google_absl
++#include "absl/strings/match.h"    // from @com_google_absl
+ #include "absl/strings/str_cat.h"  // from @com_google_absl
+ #include "tensorflow/lite/builtin_ops.h"
+ #include "tensorflow/lite/core/shims/cc/kernels/register.h"
+@@ -53,7 +53,8 @@ using ::tflite::support::CreateStatusWithPayload;
+ using ::tflite::support::InterpreterCreationResources;
+ using ::tflite::support::TfLiteSupportStatus;
+ 
+-bool TfLiteEngine::Verifier::Verify(const char* data, int length,
++bool TfLiteEngine::Verifier::Verify(const char* data,
++                                    int length,
+                                     tflite::ErrorReporter* reporter) {
+   return tflite_shims::Verify(data, length, reporter);
+ }
+@@ -84,7 +85,8 @@ std::vector<const TfLiteTensor*> TfLiteEngine::GetOutputs() {
+ }
+ 
+ void TfLiteEngine::VerifyAndBuildModelFromBuffer(
+-    const char* buffer_data, size_t buffer_size,
++    const char* buffer_data,
++    size_t buffer_size,
+     TfLiteVerifier* extra_verifier) {
+   model_ = tflite_shims::FlatBufferModel::VerifyAndBuildFromBuffer(
+       buffer_data, buffer_size, extra_verifier, &error_reporter_);
+@@ -131,7 +133,8 @@ absl::Status TfLiteEngine::InitializeFromModelFileHandler(
+ }
+ 
+ absl::Status TfLiteEngine::BuildModelFromFlatBuffer(
+-    const char* buffer_data, size_t buffer_size,
++    const char* buffer_data,
++    size_t buffer_size,
+     const tflite::proto::ComputeSettings& compute_settings) {
+   if (model_) {
+     return CreateStatusWithPayload(StatusCode::kInternal,
+@@ -220,7 +223,8 @@ absl::Status TfLiteEngine::InitInterpreter(int num_threads) {
+ // absl::Status TfLiteEngine::InitInterpreter(
+ //    const tflite::proto::ComputeSettings& compute_settings)
+ absl::Status TfLiteEngine::InitInterpreter(
+-    const tflite::proto::ComputeSettings& compute_settings, int num_threads) {
++    const tflite::proto::ComputeSettings& compute_settings,
++    int num_threads) {
+   ComputeSettings settings_copy = ComputeSettings(compute_settings);
+   settings_copy.mutable_tflite_settings()
+       ->mutable_cpu_settings()
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
+index 53dabdc4841d7..0cbaa738e6db6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
+@@ -18,8 +18,8 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/memory/memory.h"        // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow/lite/core/api/op_resolver.h"
+ #include "tensorflow/lite/core/shims/c/common.h"
+@@ -96,7 +96,8 @@ class TfLiteEngine {
+   // object. This performs extra verification on the input data using
+   // tflite::Verify.
+   absl::Status BuildModelFromFlatBuffer(
+-      const char* buffer_data, size_t buffer_size,
++      const char* buffer_data,
++      size_t buffer_size,
+       const tflite::proto::ComputeSettings& compute_settings =
+           tflite::proto::ComputeSettings());
+ 
+@@ -138,7 +139,8 @@ class TfLiteEngine {
+   // absl::Status TfLiteEngine::InitInterpreter(
+   //    const tflite::proto::ComputeSettings& compute_settings)
+   absl::Status InitInterpreter(
+-      const tflite::proto::ComputeSettings& compute_settings, int num_threads);
++      const tflite::proto::ComputeSettings& compute_settings,
++      int num_threads);
+ 
+   // Cancels the on-going `Invoke()` call if any and if possible. This method
+   // can be called from a different thread than the one where `Invoke()` is
+@@ -155,7 +157,8 @@ class TfLiteEngine {
+   // the FlatBuffer data provided as input.
+   class Verifier : public tflite::TfLiteVerifier {
+    public:
+-    bool Verify(const char* data, int length,
++    bool Verify(const char* data,
++                int length,
+                 tflite::ErrorReporter* reporter) override;
+   };
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc
+index e3ea2b134e3f4..254d0689e5ecc 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc
+@@ -14,7 +14,7 @@ limitations under the License.
+ ==============================================================================*/
+ #include "tensorflow_lite_support/cc/task/processor/audio_preprocessor.h"
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -29,7 +29,8 @@ namespace {
+ // Looks up AudioProperty from metadata. If no error occurs, the returned value
+ // is guaranteed to be valid (not null).
+ tflite::support::StatusOr<const AudioProperties*> GetAudioPropertiesSafe(
+-    const TensorMetadata* tensor_metadata, int input_index) {
++    const TensorMetadata* tensor_metadata,
++    int input_index) {
+   if (tensor_metadata->content() == nullptr ||
+       tensor_metadata->content()->content_properties() == nullptr) {
+     return CreateStatusWithPayload(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc
+index 9c11083c4f839..63962003f5e77 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc
+@@ -17,7 +17,7 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/c_api_types.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -42,7 +42,8 @@ using ::tflite::task::core::ScoreCalibration;
+ /* static */
+ tflite::support::StatusOr<std::unique_ptr<ClassificationPostprocessor>>
+ ClassificationPostprocessor::Create(
+-    core::TfLiteEngine* engine, const std::initializer_list<int> output_indices,
++    core::TfLiteEngine* engine,
++    const std::initializer_list<int> output_indices,
+     std::unique_ptr<ClassificationOptions> options) {
+   ASSIGN_OR_RETURN(auto processor,
+                    Processor::Create<ClassificationPostprocessor>(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h
+index fdc872a23d3d4..78cef8ab57e3d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h
+@@ -66,8 +66,8 @@ class EmbeddingPostprocessor : public Postprocessor {
+ 
+   // Performs actual cosine similarity computation.
+   template <typename T>
+-  static tflite::support::StatusOr<double> ComputeCosineSimilarity(
+-      const T* u, const T* v, int num_elements);
++  static tflite::support::StatusOr<double>
++  ComputeCosineSimilarity(const T* u, const T* v, int num_elements);
+ 
+   template <typename T>
+   void NormalizeFeatureVector(T* feature_vector) const;
+@@ -143,7 +143,8 @@ void EmbeddingPostprocessor::QuantizeFeatureVector(T* feature_vector) const {
+ /* static */
+ template <typename T>
+ tflite::support::StatusOr<double>
+-EmbeddingPostprocessor::ComputeCosineSimilarity(const T* u, const T* v,
++EmbeddingPostprocessor::ComputeCosineSimilarity(const T* u,
++                                                const T* v,
+                                                 int num_elements) {
+   if (num_elements <= 0) {
+     return CreateStatusWithPayload(
+@@ -171,7 +172,8 @@ EmbeddingPostprocessor::ComputeCosineSimilarity(const T* u, const T* v,
+ /* static */
+ template <typename T>
+ tflite::support::StatusOr<double> EmbeddingPostprocessor::CosineSimilarity(
+-    const T& u, const T& v) {
++    const T& u,
++    const T& v) {
+   if (u.has_value_string() && v.has_value_string()) {
+     if (u.value_string().size() != v.value_string().size()) {
+       return CreateStatusWithPayload(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc
+index 7ad4ad4703789..310a1f5eba724 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc
+@@ -36,7 +36,8 @@ using ::tflite::task::vision::FrameBuffer;
+ /* static */
+ tflite::support::StatusOr<std::unique_ptr<ImagePreprocessor>>
+ ImagePreprocessor::Create(
+-    core::TfLiteEngine* engine, const std::initializer_list<int> input_indices,
++    core::TfLiteEngine* engine,
++    const std::initializer_list<int> input_indices,
+     const vision::FrameBufferUtils::ProcessEngine& process_engine) {
+   ASSIGN_OR_RETURN(auto processor,
+                    Processor::Create<ImagePreprocessor>(
+@@ -49,7 +50,8 @@ ImagePreprocessor::Create(
+ 
+ // Returns false if image preprocessing could be skipped, true otherwise.
+ bool ImagePreprocessor::IsImagePreprocessingNeeded(
+-    const FrameBuffer& frame_buffer, const BoundingBox& roi) {
++    const FrameBuffer& frame_buffer,
++    const BoundingBox& roi) {
+   // Is crop required?
+   if (roi.origin_x() != 0 || roi.origin_y() != 0 ||
+       roi.width() != frame_buffer.dimension().width ||
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h
+index 4aad40b2afd97..b3c43605ac82e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ #include <initializer_list>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/core/shims/c/common.h"
+ #include "tensorflow_lite_support/cc/common.h"
+@@ -52,7 +52,8 @@ class Processor {
+   //   num_expected_tensors, engine, tensor_indices);
+   template <typename T, EnableIfProcessorSubclass<T> = nullptr>
+   static tflite::support::StatusOr<std::unique_ptr<T>> Create(
+-      int num_expected_tensors, tflite::task::core::TfLiteEngine* engine,
++      int num_expected_tensors,
++      tflite::task::core::TfLiteEngine* engine,
+       const std::initializer_list<int> tensor_indices,
+       bool requires_metadata = true) {
+     auto processor = absl::make_unique<T>(engine, tensor_indices);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc
+index af923b4d6f2c1..58b77b6952de1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc
+@@ -55,7 +55,8 @@ StatusOr<absl::string_view> CheckAndLoadFirstAssociatedFile(
+ 
+ /* static */
+ StatusOr<std::unique_ptr<RegexPreprocessor>> RegexPreprocessor::Create(
+-    tflite::task::core::TfLiteEngine* engine, int input_tensor_index) {
++    tflite::task::core::TfLiteEngine* engine,
++    int input_tensor_index) {
+   ASSIGN_OR_RETURN(auto processor, Processor::Create<RegexPreprocessor>(
+                                        /* num_expected_tensors = */ 1, engine,
+                                        {input_tensor_index},
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h
+index 1f92bcc18e524..bdd4e5e207a12 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h
+@@ -34,7 +34,8 @@ namespace processor {
+ class RegexPreprocessor : public TextPreprocessor {
+  public:
+   static tflite::support::StatusOr<std::unique_ptr<RegexPreprocessor>> Create(
+-      tflite::task::core::TfLiteEngine* engine, int input_tensor_index);
++      tflite::task::core::TfLiteEngine* engine,
++      int input_tensor_index);
+ 
+   absl::Status Preprocess(const std::string& text);
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc
+index c52f73be8b7a8..ac8fa548c669d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc
+@@ -23,8 +23,8 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/ascii.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/ascii.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/api/op_resolver.h"
+@@ -76,7 +76,8 @@ int GetLastDimSize(const TfLiteTensor* tensor) {
+ }  // namespace
+ 
+ absl::Status BertNLClassifier::Preprocess(
+-    const std::vector<TfLiteTensor*>& input_tensors, const std::string& input) {
++    const std::vector<TfLiteTensor*>& input_tensors,
++    const std::string& input) {
+   auto* input_tensor_metadatas =
+       GetMetadataExtractor()->GetInputTensorMetadata();
+   auto* ids_tensor =
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h
+index 541b5561d5c6d..91bcfe50712d0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h
+@@ -22,7 +22,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/base/macros.h"  // from @com_google_absl
++#include "absl/base/macros.h"    // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/api/op_resolver.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc
+index 6b37649d4fbfd..591b70e84eb22 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc
+@@ -15,8 +15,8 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_join.h"  // from @com_google_absl
++#include "absl/status/status.h"      // from @com_google_absl
++#include "absl/strings/str_join.h"   // from @com_google_absl
+ #include "absl/strings/str_split.h"  // from @com_google_absl
+ #include "tensorflow/lite/core/shims/cc/kernels/register.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -111,7 +111,8 @@ StatusOr<std::unique_ptr<QuestionAnswerer>> BertQuestionAnswerer::CreateFromFd(
+ 
+ StatusOr<std::unique_ptr<QuestionAnswerer>>
+ BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
+-    const std::string& path_to_model, const std::string& path_to_vocab) {
++    const std::string& path_to_model,
++    const std::string& path_to_vocab) {
+   std::unique_ptr<BertQuestionAnswerer> api_to_init;
+   ASSIGN_OR_RETURN(
+       api_to_init,
+@@ -125,8 +126,10 @@ BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
+ 
+ StatusOr<std::unique_ptr<QuestionAnswerer>>
+ BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
+-    const char* model_buffer_data, size_t model_buffer_size,
+-    const char* vocab_buffer_data, size_t vocab_buffer_size) {
++    const char* model_buffer_data,
++    size_t model_buffer_size,
++    const char* vocab_buffer_data,
++    size_t vocab_buffer_size) {
+   std::unique_ptr<BertQuestionAnswerer> api_to_init;
+   ASSIGN_OR_RETURN(
+       api_to_init,
+@@ -141,7 +144,8 @@ BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
+ 
+ StatusOr<std::unique_ptr<QuestionAnswerer>>
+ BertQuestionAnswerer::CreateAlbertQuestionAnswererFromFile(
+-    const std::string& path_to_model, const std::string& path_to_spmodel) {
++    const std::string& path_to_model,
++    const std::string& path_to_spmodel) {
+   std::unique_ptr<BertQuestionAnswerer> api_to_init;
+   ASSIGN_OR_RETURN(
+       api_to_init,
+@@ -155,8 +159,10 @@ BertQuestionAnswerer::CreateAlbertQuestionAnswererFromFile(
+ 
+ StatusOr<std::unique_ptr<QuestionAnswerer>>
+ BertQuestionAnswerer::CreateAlbertQuestionAnswererFromBuffer(
+-    const char* model_buffer_data, size_t model_buffer_size,
+-    const char* spmodel_buffer_data, size_t spmodel_buffer_size) {
++    const char* model_buffer_data,
++    size_t model_buffer_size,
++    const char* spmodel_buffer_data,
++    size_t spmodel_buffer_size) {
+   std::unique_ptr<BertQuestionAnswerer> api_to_init;
+   ASSIGN_OR_RETURN(
+       api_to_init,
+@@ -170,14 +176,16 @@ BertQuestionAnswerer::CreateAlbertQuestionAnswererFromBuffer(
+ }
+ 
+ std::vector<QaAnswer> BertQuestionAnswerer::Answer(
+-    const std::string& context, const std::string& question) {
++    const std::string& context,
++    const std::string& question) {
+   // The BertQuestionAnswererer implementation for Preprocess() and
+   // Postprocess() never returns errors: just call value().
+   return Infer(context, question).value();
+ }
+ 
+ absl::Status BertQuestionAnswerer::Preprocess(
+-    const std::vector<TfLiteTensor*>& input_tensors, const std::string& context,
++    const std::vector<TfLiteTensor*>& input_tensors,
++    const std::string& context,
+     const std::string& query) {
+   auto* input_tensor_metadatas =
+       GetMetadataExtractor()->GetInputTensorMetadata();
+@@ -392,7 +400,8 @@ void BertQuestionAnswerer::InitializeBertTokenizer(
+ }
+ 
+ void BertQuestionAnswerer::InitializeBertTokenizerFromBinary(
+-    const char* vocab_buffer_data, size_t vocab_buffer_size) {
++    const char* vocab_buffer_data,
++    size_t vocab_buffer_size) {
+   tokenizer_ =
+       absl::make_unique<BertTokenizer>(vocab_buffer_data, vocab_buffer_size);
+ }
+@@ -403,7 +412,8 @@ void BertQuestionAnswerer::InitializeSentencepieceTokenizer(
+ }
+ 
+ void BertQuestionAnswerer::InitializeSentencepieceTokenizerFromBinary(
+-    const char* spmodel_buffer_data, size_t spmodel_buffer_size) {
++    const char* spmodel_buffer_data,
++    size_t spmodel_buffer_size) {
+   tokenizer_ = absl::make_unique<SentencePieceTokenizer>(spmodel_buffer_data,
+                                                          spmodel_buffer_size);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h
+index f041cc8e51637..52ec835371386 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h
+@@ -16,9 +16,9 @@ limitations under the License.
+ #ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_BERT_QUESTION_ANSWERER_H_
+ #define TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_BERT_QUESTION_ANSWERER_H_
+ 
+-#include "absl/base/macros.h"  // from @com_google_absl
++#include "absl/base/macros.h"              // from @com_google_absl
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+ #include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+@@ -136,7 +136,8 @@ class BertQuestionAnswerer : public QuestionAnswerer {
+   void InitializeSentencepieceTokenizer(const std::string& path_to_spmodel);
+   // Initialize API with a SentencepieceTokenizer from the model buffer.
+   void InitializeSentencepieceTokenizerFromBinary(
+-      const char* spmodel_buffer_data, size_t spmodel_buffer_size);
++      const char* spmodel_buffer_data,
++      size_t spmodel_buffer_size);
+ 
+   // Initialize the API with the tokenizer set in the metadata.
+   absl::Status InitializeFromMetadata(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc
+index d3697f326db1b..6986bcc665733 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc
+@@ -22,8 +22,8 @@ limitations under the License.
+ #include <vector>
+ 
+ #include "absl/algorithm/container.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_cat.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
++#include "absl/strings/str_cat.h"      // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/c/common.h"
+@@ -200,7 +200,8 @@ std::vector<Category> NLClassifier::Classify(const std::string& text) {
+ }
+ 
+ absl::Status NLClassifier::Preprocess(
+-    const std::vector<TfLiteTensor*>& input_tensors, const std::string& input) {
++    const std::vector<TfLiteTensor*>& input_tensors,
++    const std::string& input) {
+   TfLiteTensor* input_tensor = FindTensorWithNameOrIndex(
+       input_tensors, GetMetadataExtractor()->GetInputTensorMetadata(),
+       struct_options_.input_tensor_name, struct_options_.input_tensor_index);
+@@ -446,7 +447,8 @@ StatusOr<std::unique_ptr<NLClassifier>> NLClassifier::CreateFromOptions(
+ 
+ StatusOr<std::unique_ptr<NLClassifier>>
+ NLClassifier::CreateFromBufferAndOptions(
+-    const char* model_buffer_data, size_t model_buffer_size,
++    const char* model_buffer_data,
++    size_t model_buffer_size,
+     const NLClassifierOptions& options,
+     std::unique_ptr<tflite::OpResolver> resolver) {
+   std::unique_ptr<NLClassifier> nl_classifier;
+@@ -459,7 +461,8 @@ NLClassifier::CreateFromBufferAndOptions(
+ }
+ 
+ StatusOr<std::unique_ptr<NLClassifier>> NLClassifier::CreateFromFileAndOptions(
+-    const std::string& path_to_model, const NLClassifierOptions& options,
++    const std::string& path_to_model,
++    const NLClassifierOptions& options,
+     std::unique_ptr<tflite::OpResolver> resolver) {
+   std::unique_ptr<NLClassifier> nl_classifier;
+   ASSIGN_OR_RETURN(nl_classifier,
+@@ -470,7 +473,8 @@ StatusOr<std::unique_ptr<NLClassifier>> NLClassifier::CreateFromFileAndOptions(
+ }
+ 
+ StatusOr<std::unique_ptr<NLClassifier>> NLClassifier::CreateFromFdAndOptions(
+-    int fd, const NLClassifierOptions& options,
++    int fd,
++    const NLClassifierOptions& options,
+     std::unique_ptr<tflite::OpResolver> resolver) {
+   std::unique_ptr<NLClassifier> nl_classifier;
+   ASSIGN_OR_RETURN(nl_classifier,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+index 2adafba8f2fa9..331a6e4274342 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+@@ -23,8 +23,8 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/base/macros.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/base/macros.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/api/op_resolver.h"
+@@ -109,7 +109,8 @@ class NLClassifier : public core::BaseTaskApi<std::vector<core::Category>,
+   ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+   static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
+   CreateFromBufferAndOptions(
+-      const char* model_buffer_data, size_t model_buffer_size,
++      const char* model_buffer_data,
++      size_t model_buffer_size,
+       const NLClassifierOptions& options = {},
+       std::unique_ptr<tflite::OpResolver> resolver =
+           absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+@@ -118,7 +119,8 @@ class NLClassifier : public core::BaseTaskApi<std::vector<core::Category>,
+   ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+   static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
+   CreateFromFileAndOptions(
+-      const std::string& path_to_model, const NLClassifierOptions& options = {},
++      const std::string& path_to_model,
++      const NLClassifierOptions& options = {},
+       std::unique_ptr<tflite::OpResolver> resolver =
+           absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+ 
+@@ -126,7 +128,8 @@ class NLClassifier : public core::BaseTaskApi<std::vector<core::Category>,
+   ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+   static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
+   CreateFromFdAndOptions(
+-      int fd, const NLClassifierOptions& options = {},
++      int fd,
++      const NLClassifierOptions& options = {},
+       std::unique_ptr<tflite::OpResolver> resolver =
+           absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+ 
+@@ -177,7 +180,8 @@ class NLClassifier : public core::BaseTaskApi<std::vector<core::Category>,
+       const std::vector<TensorType*>& tensors,
+       const flatbuffers::Vector<flatbuffers::Offset<TensorMetadata>>*
+           metadata_array,
+-      const std::string& name, int index) {
++      const std::string& name,
++      int index) {
+     if (metadata_array != nullptr && metadata_array->size() == tensors.size()) {
+       for (size_t i = 0; i < metadata_array->size(); i++) {
+         if (strcmp(name.data(), metadata_array->Get(i)->name()->c_str()) == 0) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h
+index 4cde4329a716b..df21662a40e3a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h
+@@ -45,9 +45,9 @@ struct QaAnswer {
+ };
+ 
+ // Interface for an Question-Answer API.
+-class QuestionAnswerer
+-    : public core::BaseTaskApi<std::vector<QaAnswer>, const std::string&,
+-                               const std::string&> {
++class QuestionAnswerer : public core::BaseTaskApi<std::vector<QaAnswer>,
++                                                  const std::string&,
++                                                  const std::string&> {
+  public:
+   explicit QuestionAnswerer(std::unique_ptr<core::TfLiteEngine> engine)
+       : BaseTaskApi(std::move(engine)) {}
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc
+index 069491f6e47c9..2937a175c5e3c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc
+@@ -21,7 +21,7 @@ limitations under the License.
+ #include <vector>
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+ #include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+@@ -197,7 +197,8 @@ StatusOr<FeatureVector> UniversalSentenceEncoderQA::EncodeQuery(
+ }
+ 
+ StatusOr<FeatureVector> UniversalSentenceEncoderQA::EncodeResponse(
+-    absl::string_view response_text, absl::string_view response_context) {
++    absl::string_view response_text,
++    absl::string_view response_context) {
+   if (response_text.empty() && response_context.empty()) {
+     return Status(
+         StatusCode::kInvalidArgument,
+@@ -218,7 +219,8 @@ StatusOr<float> UniversalSentenceEncoderQA::Similarity(const FeatureVector& a,
+ }
+ 
+ std::vector<size_t> UniversalSentenceEncoderQA::Top(
+-    const RetrievalOutput& output, size_t k) {
++    const RetrievalOutput& output,
++    size_t k) {
+   // Ensure k in [0, total_size).
+   // If k == 0, it means that all outputs are ranked.
+   if (k == 0) {
+@@ -242,7 +244,8 @@ std::vector<size_t> UniversalSentenceEncoderQA::Top(
+ }
+ 
+ Status UniversalSentenceEncoderQA::Preprocess(
+-    const std::vector<TfLiteTensor*>& input_tensors, const QAInput& input) {
++    const std::vector<TfLiteTensor*>& input_tensors,
++    const QAInput& input) {
+   auto* input_tensor_metadatas =
+       GetMetadataExtractor()->GetInputTensorMetadata();
+   TfLiteTensor* query_text_tensor =
+@@ -293,7 +296,8 @@ StatusOr<QAOutput> UniversalSentenceEncoderQA::Postprocess(
+ }
+ 
+ internal::QAOutput UniversalSentenceEncoderQA::Run(
+-    absl::string_view query_text, absl::string_view response_text,
++    absl::string_view query_text,
++    absl::string_view response_text,
+     absl::string_view response_context) {
+   QAInput input;
+   input.query_text = query_text;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h
+index fae2f29721722..0269033918cc9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h
+@@ -20,14 +20,14 @@ limitations under the License.
+ #include <vector>
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/str_format.h"       // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+ #include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+ #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+-#include "tensorflow_lite_support/cc/task/text/proto/retrieval.pb.h"
+ #include "tensorflow_lite_support/cc/task/processor/proto/embedding.pb.h"
++#include "tensorflow_lite_support/cc/task/text/proto/retrieval.pb.h"
+ 
+ namespace tflite {
+ namespace task {
+@@ -73,7 +73,8 @@ class UniversalSentenceEncoderQA
+   // Encodes response from the text and/or context.
+   // Returns an error, if both text and context are empty.
+   tflite::support::StatusOr<FeatureVector> EncodeResponse(
+-      absl::string_view response_text, absl::string_view response_context);
++      absl::string_view response_text,
++      absl::string_view response_context);
+ 
+   // Calculates similarity between two encoded vectors (require same size).
+   static tflite::support::StatusOr<float> Similarity(const FeatureVector& a,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
+index 76a03671b54af..d3557fc508c61 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
+@@ -23,7 +23,7 @@ limitations under the License.
+ 
+ #include "absl/memory/memory.h"  // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/time/clock.h"  // from @com_google_absl
++#include "absl/time/clock.h"     // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+@@ -45,11 +45,12 @@ namespace vision {
+ // Base class providing common logic for vision models.
+ template <class OutputType>
+ class BaseVisionTaskApi
+-    : public tflite::task::core::BaseTaskApi<OutputType, const FrameBuffer&,
+-                                             const BoundingBox&> {
++    : public tflite::task::core::
++          BaseTaskApi<OutputType, const FrameBuffer&, const BoundingBox&> {
+  public:
+   explicit BaseVisionTaskApi(std::unique_ptr<core::TfLiteEngine> engine)
+-      : tflite::task::core::BaseTaskApi<OutputType, const FrameBuffer&,
++      : tflite::task::core::BaseTaskApi<OutputType,
++                                        const FrameBuffer&,
+                                         const BoundingBox&>(std::move(engine)) {
+   }
+   // BaseVisionTaskApi is neither copyable nor movable.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h
+index 47db0d121d43b..2e1aa6d652967 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h
+@@ -18,7 +18,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
++#include "absl/memory/memory.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
+index 1668447393e9e..2936f5acbb921 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
+@@ -22,12 +22,12 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/memory/memory.h"    // from @com_google_absl
++#include "absl/status/status.h"    // from @com_google_absl
+ #include "absl/strings/str_cat.h"  // from @com_google_absl
+-#include "absl/time/clock.h"  // from @com_google_absl
+-#include "absl/time/time.h"  // from @com_google_absl
+-#include "absl/types/optional.h"  // from @com_google_absl
++#include "absl/time/clock.h"       // from @com_google_absl
++#include "absl/time/time.h"        // from @com_google_absl
++#include "absl/types/optional.h"   // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ 
+@@ -74,7 +74,16 @@ namespace vision {
+ class FrameBuffer {
+  public:
+   // Colorspace formats.
+-  enum class Format { kRGBA, kRGB, kNV12, kNV21, kYV12, kYV21, kGRAY, kUNKNOWN};
++  enum class Format {
++    kRGBA,
++    kRGB,
++    kNV12,
++    kNV21,
++    kYV12,
++    kYV21,
++    kGRAY,
++    kUNKNOWN
++  };
+ 
+   // Stride information.
+   struct Stride {
+@@ -166,7 +175,8 @@ class FrameBuffer {
+   // buffers. In a streaming use case (e.g continuous camera stream), the
+   // timestamp can be used as an ID to identify a frame.
+   static std::unique_ptr<FrameBuffer> Create(const std::vector<Plane>& planes,
+-                                             Dimension dimension, Format format,
++                                             Dimension dimension,
++                                             Format format,
+                                              Orientation orientation,
+                                              absl::Time timestamp) {
+     return absl::make_unique<FrameBuffer>(planes, dimension, format,
+@@ -177,7 +187,8 @@ class FrameBuffer {
+   // backing buffers. In a streaming use case (e.g continuous camera stream),
+   // the timestamp can be used as an ID to identify a frame.
+   static std::unique_ptr<FrameBuffer> Create(std::vector<Plane>&& planes,
+-                                             Dimension dimension, Format format,
++                                             Dimension dimension,
++                                             Format format,
+                                              Orientation orientation,
+                                              absl::Time timestamp) {
+     return absl::make_unique<FrameBuffer>(std::move(planes), dimension, format,
+@@ -189,7 +200,8 @@ class FrameBuffer {
+   // more suitable for processing use case that does not need to re-identify
+   // this buffer.
+   static std::unique_ptr<FrameBuffer> Create(const std::vector<Plane>& planes,
+-                                             Dimension dimension, Format format,
++                                             Dimension dimension,
++                                             Format format,
+                                              Orientation orientation) {
+     return absl::make_unique<FrameBuffer>(planes, dimension, format,
+                                           orientation, absl::Now());
+@@ -200,7 +212,8 @@ class FrameBuffer {
+   // method is more suitable for processing use case that does not need to
+   // re-identify this buffer.
+   static std::unique_ptr<FrameBuffer> Create(std::vector<Plane>&& planes,
+-                                             Dimension dimension, Format format,
++                                             Dimension dimension,
++                                             Format format,
+                                              Orientation orientation) {
+     return absl::make_unique<FrameBuffer>(std::move(planes), dimension, format,
+                                           orientation, absl::Now());
+@@ -217,8 +230,11 @@ class FrameBuffer {
+   // The FrameBuffer does not take ownership of the backing buffer. The backing
+   // buffer is read-only and the caller is responsible for maintaining the
+   // backing buffer lifecycle for the lifetime of FrameBuffer.
+-  FrameBuffer(const std::vector<Plane>& planes, Dimension dimension,
+-              Format format, Orientation orientation, absl::Time timestamp)
++  FrameBuffer(const std::vector<Plane>& planes,
++              Dimension dimension,
++              Format format,
++              Orientation orientation,
++              absl::Time timestamp)
+       : planes_(planes),
+         dimension_(dimension),
+         format_(format),
+@@ -230,8 +246,11 @@ class FrameBuffer {
+   // The FrameBuffer does not take ownership of the backing buffer. The backing
+   // buffer is read-only and the caller is responsible for maintaining the
+   // backing buffer lifecycle for the lifetime of FrameBuffer.
+-  FrameBuffer(std::vector<Plane>&& planes, Dimension dimension, Format format,
+-              Orientation orientation, absl::Time timestamp)
++  FrameBuffer(std::vector<Plane>&& planes,
++              Dimension dimension,
++              Format format,
++              Orientation orientation,
++              absl::Time timestamp)
+       : planes_(std::move(planes)),
+         dimension_(dimension),
+         format_(format),
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc
+index 9c82b63a10359..67fe07534b52a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc
+@@ -16,7 +16,7 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
+ 
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "absl/strings/str_split.h"  // from @com_google_absl
++#include "absl/strings/str_split.h"   // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ 
+ namespace tflite {
+@@ -29,7 +29,8 @@ using ::tflite::support::StatusOr;
+ using ::tflite::support::TfLiteSupportStatus;
+ 
+ StatusOr<std::vector<LabelMapItem>> BuildLabelMapFromFiles(
+-    absl::string_view labels_file, absl::string_view display_names_file) {
++    absl::string_view labels_file,
++    absl::string_view display_names_file) {
+   if (labels_file.empty()) {
+     return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                    "Expected non-empty labels file.",
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h
+index 0fb66f2639806..20c316ba4a992 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h
+@@ -20,8 +20,8 @@ limitations under the License.
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+ #include "absl/container/flat_hash_set.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/string_view.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/string_view.h"      // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ 
+ namespace tflite {
+@@ -49,7 +49,8 @@ struct LabelMapItem {
+ // Returns an error e.g. if there's a mismatch between the number of labels and
+ // display names.
+ tflite::support::StatusOr<std::vector<LabelMapItem>> BuildLabelMapFromFiles(
+-    absl::string_view labels_file, absl::string_view display_names_file);
++    absl::string_view labels_file,
++    absl::string_view display_names_file);
+ 
+ // A class that represents a hierarchy of labels as specified in a label map.
+ //
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc
+index aa1e7707dd99b..36ab3c3ca1903 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc
+@@ -16,9 +16,9 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/vision/image_classifier.h"
+ 
+ #include "absl/algorithm/container.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
++#include "absl/strings/str_format.h"   // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "flatbuffers/flatbuffers.h"  // from @flatbuffers
++#include "flatbuffers/flatbuffers.h"   // from @flatbuffers
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -146,7 +146,9 @@ absl::Status ImageClassifier::PreInit() {
+   return absl::OkStatus();
+ }
+ 
+-absl::Status ImageClassifier::PostInit() { return InitScoreCalibrations(); }
++absl::Status ImageClassifier::PostInit() {
++  return InitScoreCalibrations();
++}
+ 
+ absl::Status ImageClassifier::CheckAndSetOutputs() {
+   num_outputs_ = TfLiteEngine::OutputCount(GetTfLiteEngine()->interpreter());
+@@ -380,13 +382,15 @@ StatusOr<ClassificationResult> ImageClassifier::Classify(
+ }
+ 
+ StatusOr<ClassificationResult> ImageClassifier::Classify(
+-    const FrameBuffer& frame_buffer, const BoundingBox& roi) {
++    const FrameBuffer& frame_buffer,
++    const BoundingBox& roi) {
+   return InferWithFallback(frame_buffer, roi);
+ }
+ 
+ StatusOr<ClassificationResult> ImageClassifier::Postprocess(
+     const std::vector<const TfLiteTensor*>& output_tensors,
+-    const FrameBuffer& /*frame_buffer*/, const BoundingBox& /*roi*/) {
++    const FrameBuffer& /*frame_buffer*/,
++    const BoundingBox& /*roi*/) {
+   if (output_tensors.size() != num_outputs_) {
+     return CreateStatusWithPayload(
+         StatusCode::kInternal,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h
+index b2f595715e9da..eb0c13ec55c5b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h
+@@ -20,7 +20,7 @@ limitations under the License.
+ #include <vector>
+ 
+ #include "absl/container/flat_hash_set.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/api/op_resolver.h"
+ #include "tensorflow/lite/core/shims/cc/kernels/register.h"
+@@ -109,7 +109,8 @@ class ImageClassifier : public BaseVisionTaskApi<ClassificationResult> {
+   // region of interest is not clamped, so this method will return a non-ok
+   // status if the region is out of these bounds.
+   tflite::support::StatusOr<ClassificationResult> Classify(
+-      const FrameBuffer& frame_buffer, const BoundingBox& roi);
++      const FrameBuffer& frame_buffer,
++      const BoundingBox& roi);
+ 
+  protected:
+   // The options used to build this ImageClassifier.
+@@ -123,7 +124,8 @@ class ImageClassifier : public BaseVisionTaskApi<ClassificationResult> {
+   // results.
+   tflite::support::StatusOr<ClassificationResult> Postprocess(
+       const std::vector<const TfLiteTensor*>& output_tensors,
+-      const FrameBuffer& frame_buffer, const BoundingBox& roi) override;
++      const FrameBuffer& frame_buffer,
++      const BoundingBox& roi) override;
+ 
+   // Performs sanity checks on the provided ImageClassifierOptions.
+   static absl::Status SanityCheckOptions(const ImageClassifierOptions& options);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc
+index 0ce46fb9f9806..943a39b1f762e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc
+@@ -18,10 +18,10 @@ limitations under the License.
+ #include <algorithm>
+ 
+ #include "absl/container/node_hash_set.h"  // from @com_google_absl
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "absl/strings/string_view.h"  // from @com_google_absl
++#include "absl/memory/memory.h"            // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/str_format.h"       // from @com_google_absl
++#include "absl/strings/string_view.h"      // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -51,7 +51,8 @@ CreatePostprocessor(core::TfLiteEngine* engine,
+ 
+ /* static */
+ tflite::support::StatusOr<double> ImageEmbedder::CosineSimilarity(
+-    const FeatureVector& u, const FeatureVector& v) {
++    const FeatureVector& u,
++    const FeatureVector& v) {
+   return processor::EmbeddingPostprocessor::CosineSimilarity(u, v);
+ }
+ 
+@@ -118,13 +119,15 @@ tflite::support::StatusOr<EmbeddingResult> ImageEmbedder::Embed(
+ }
+ 
+ tflite::support::StatusOr<EmbeddingResult> ImageEmbedder::Embed(
+-    const FrameBuffer& frame_buffer, const BoundingBox& roi) {
++    const FrameBuffer& frame_buffer,
++    const BoundingBox& roi) {
+   return InferWithFallback(frame_buffer, roi);
+ }
+ 
+ tflite::support::StatusOr<EmbeddingResult> ImageEmbedder::Postprocess(
+     const std::vector<const TfLiteTensor*>& output_tensors,
+-    const FrameBuffer& /*frame_buffer*/, const BoundingBox& /*roi*/) {
++    const FrameBuffer& /*frame_buffer*/,
++    const BoundingBox& /*roi*/) {
+   EmbeddingResult result;
+   for (int i = 0; i < postprocessors_.size(); ++i) {
+     RETURN_IF_ERROR(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h
+index bc321c83d3774..93e2455eebd19 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h
+@@ -90,7 +90,8 @@ class ImageEmbedder
+   // region of interest. Note that the region of interest is not clamped, so
+   // this method will fail if the region is out of bounds of the input image.
+   tflite::support::StatusOr<EmbeddingResult> Embed(
+-      const FrameBuffer& frame_buffer, const BoundingBox& roi);
++      const FrameBuffer& frame_buffer,
++      const BoundingBox& roi);
+ 
+   // Returns the Embedding output by the output_index'th layer. In (the most
+   // common) case where a single embedding is produced, you can just call
+@@ -113,7 +114,8 @@ class ImageEmbedder
+   //
+   // [1]: https://en.wikipedia.org/wiki/Cosine_similarity
+   static tflite::support::StatusOr<double> CosineSimilarity(
+-      const FeatureVector& u, const FeatureVector& v);
++      const FeatureVector& u,
++      const FeatureVector& v);
+ 
+  protected:
+   // The options used to build this ImageEmbedder.
+@@ -122,7 +124,8 @@ class ImageEmbedder
+   // Post-processing to transform the raw model outputs into embedding results.
+   tflite::support::StatusOr<EmbeddingResult> Postprocess(
+       const std::vector<const TfLiteTensor*>& output_tensors,
+-      const FrameBuffer& frame_buffer, const BoundingBox& roi) override;
++      const FrameBuffer& frame_buffer,
++      const BoundingBox& roi) override;
+ 
+   // Performs pre-initialization actions.
+   virtual absl::Status PreInit();
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc
+index f87c6b078eddc..20a34a956200b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc
+@@ -17,8 +17,8 @@ limitations under the License.
+ 
+ #include <algorithm>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
++#include "absl/memory/memory.h"        // from @com_google_absl
++#include "absl/strings/str_format.h"   // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/c/common.h"
+@@ -110,7 +110,8 @@ constexpr uint8 kColorMap[768] = {
+ 
+ StatusOr<std::vector<LabelMapItem>> GetLabelMapIfAny(
+     const ModelMetadataExtractor& metadata_extractor,
+-    const TensorMetadata& tensor_metadata, absl::string_view locale) {
++    const TensorMetadata& tensor_metadata,
++    absl::string_view locale) {
+   const std::string labels_filename =
+       ModelMetadataExtractor::FindFirstAssociatedFileName(
+           tensor_metadata, tflite::AssociatedFileType_TENSOR_AXIS_LABELS);
+@@ -332,7 +333,8 @@ StatusOr<SegmentationResult> ImageSegmenter::Segment(
+ 
+ StatusOr<SegmentationResult> ImageSegmenter::Postprocess(
+     const std::vector<const TfLiteTensor*>& output_tensors,
+-    const FrameBuffer& frame_buffer, const BoundingBox& /*roi*/) {
++    const FrameBuffer& frame_buffer,
++    const BoundingBox& /*roi*/) {
+   if (output_tensors.size() != 1) {
+     return CreateStatusWithPayload(
+         StatusCode::kInternal,
+@@ -432,7 +434,10 @@ StatusOr<SegmentationResult> ImageSegmenter::Postprocess(
+ }
+ 
+ StatusOr<float> ImageSegmenter::GetOutputConfidence(
+-    const TfLiteTensor& output_tensor, int x, int y, int depth) {
++    const TfLiteTensor& output_tensor,
++    int x,
++    int y,
++    int depth) {
+   int index = output_width_ * output_depth_ * y + output_depth_ * x + depth;
+   if (has_uint8_outputs_) {
+     ASSIGN_OR_RETURN(const uint8* data,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h
+index 3f51f4962738e..e255110d9dc66 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h
+@@ -119,7 +119,8 @@ class ImageSegmenter : public BaseVisionTaskApi<SegmentationResult> {
+   // results.
+   tflite::support::StatusOr<SegmentationResult> Postprocess(
+       const std::vector<const TfLiteTensor*>& output_tensors,
+-      const FrameBuffer& frame_buffer, const BoundingBox& roi) override;
++      const FrameBuffer& frame_buffer,
++      const BoundingBox& roi) override;
+ 
+   // Performs sanity checks on the provided ImageSegmenterOptions.
+   static absl::Status SanityCheckOptions(const ImageSegmenterOptions& options);
+@@ -148,7 +149,10 @@ class ImageSegmenter : public BaseVisionTaskApi<SegmentationResult> {
+   // Returns the output confidence at coordinates {x, y, depth}, dequantizing
+   // on-the-fly if needed (i.e. if `has_uint8_outputs_` is true).
+   tflite::support::StatusOr<float> GetOutputConfidence(
+-      const TfLiteTensor& output_tensor, int x, int y, int depth);
++      const TfLiteTensor& output_tensor,
++      int x,
++      int y,
++      int depth);
+ 
+   // Prebuilt list of ColoredLabel attached to each Segmentation result. The
+   // i-th item in this list corresponds to the i-th label map item.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc
+index 872bd8d5876a4..3eb512699bbda 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc
+@@ -20,9 +20,9 @@ limitations under the License.
+ #include <vector>
+ 
+ #include <glog/logging.h>
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
++#include "absl/memory/memory.h"        // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
++#include "absl/strings/str_format.h"   // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow_lite_support/cc/common.h"
+@@ -141,7 +141,8 @@ StatusOr<const BoundingBoxProperties*> GetBoundingBoxProperties(
+ 
+ StatusOr<std::vector<LabelMapItem>> GetLabelMapIfAny(
+     const ModelMetadataExtractor& metadata_extractor,
+-    const TensorMetadata& tensor_metadata, absl::string_view locale) {
++    const TensorMetadata& tensor_metadata,
++    absl::string_view locale) {
+   const std::string labels_filename =
+       ModelMetadataExtractor::FindFirstAssociatedFileName(
+           tensor_metadata, tflite::AssociatedFileType_TENSOR_VALUE_LABELS);
+@@ -370,7 +371,9 @@ absl::Status ObjectDetector::PreInit() {
+   return absl::OkStatus();
+ }
+ 
+-absl::Status ObjectDetector::PostInit() { return InitScoreCalibrations(); }
++absl::Status ObjectDetector::PostInit() {
++  return InitScoreCalibrations();
++}
+ 
+ StatusOr<SigmoidCalibrationParameters> BuildCalibrationParametersIfAny(
+     const tflite::metadata::ModelMetadataExtractor& metadata_extractor,
+@@ -599,7 +602,8 @@ StatusOr<DetectionResult> ObjectDetector::Detect(
+ 
+ StatusOr<DetectionResult> ObjectDetector::Postprocess(
+     const std::vector<const TfLiteTensor*>& output_tensors,
+-    const FrameBuffer& frame_buffer, const BoundingBox& /*roi*/) {
++    const FrameBuffer& frame_buffer,
++    const BoundingBox& /*roi*/) {
+   // Most of the checks here should never happen, as outputs have been validated
+   // at construction time. Checking nonetheless and returning internal errors if
+   // something bad happens.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h
+index eaa6b5371ba52..c37fa8771081e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h
+@@ -19,7 +19,7 @@ limitations under the License.
+ #include <memory>
+ 
+ #include "absl/container/flat_hash_set.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
+ #include "tensorflow/lite/core/api/op_resolver.h"
+ #include "tensorflow/lite/core/shims/cc/kernels/register.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -123,7 +123,8 @@ class ObjectDetector : public BaseVisionTaskApi<DetectionResult> {
+   // Post-processing to transform the raw model outputs into detection results.
+   tflite::support::StatusOr<DetectionResult> Postprocess(
+       const std::vector<const TfLiteTensor*>& output_tensors,
+-      const FrameBuffer& frame_buffer, const BoundingBox& roi) override;
++      const FrameBuffer& frame_buffer,
++      const BoundingBox& roi) override;
+ 
+   // Performs sanity checks on the provided ObjectDetectorOptions.
+   static absl::Status SanityCheckOptions(const ObjectDetectorOptions& options);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations.proto
+index 259bee8194735..f6df558cc1a1a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations.proto
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations.proto
+@@ -31,17 +31,13 @@ message Segmentation {
+   // pixel, the value indicates the prediction confidence usually in the [0, 1]
+   // range where higher values represent a stronger confidence. Ultimately this
+   // is model specific, and other range of values might be used.
+-  message ConfidenceMask {
+-    repeated float value = 1 [packed = true];
+-  }
++  message ConfidenceMask { repeated float value = 1 [packed = true]; }
+ 
+   // List of confidence masks with respect to the model output depth (this depth
+   // represents how many classes are supported). Note: some models have a single
+   // class (e.g. a sky segmentation model) which turns into a single confidence
+   // mask in this list.
+-  message ConfidenceMasks {
+-    repeated ConfidenceMask confidence_mask = 1;
+-  }
++  message ConfidenceMasks { repeated ConfidenceMask confidence_mask = 1; }
+ 
+   // IMPORTANT: segmentation masks are not direcly suited for display, in
+   // particular:
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc
+index f30af1e7d27d8..cea7ef3fb1f23 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc
+@@ -18,7 +18,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/strings/str_cat.h"  // from @com_google_absl
++#include "absl/strings/str_cat.h"     // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ 
+@@ -36,8 +36,10 @@ constexpr int kGrayChannel = 1;
+ // Creates a FrameBuffer from one plane raw NV21/NV12 buffer and passing
+ // arguments.
+ StatusOr<std::unique_ptr<FrameBuffer>> CreateFromOnePlaneNVRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
+-    FrameBuffer::Format format, FrameBuffer::Orientation orientation,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
++    FrameBuffer::Format format,
++    FrameBuffer::Orientation orientation,
+     const absl::Time timestamp) {
+   FrameBuffer::Plane input_plane = {/*buffer=*/input,
+                                     /*stride=*/{dimension.width, kGrayChannel}};
+@@ -129,7 +131,8 @@ StatusOr<const uint8*> GetUvRawBuffer(const FrameBuffer& buffer) {
+ }
+ 
+ StatusOr<FrameBuffer::Dimension> GetUvPlaneDimension(
+-    FrameBuffer::Dimension dimension, FrameBuffer::Format format) {
++    FrameBuffer::Dimension dimension,
++    FrameBuffer::Format format) {
+   if (dimension.width <= 0 || dimension.height <= 0) {
+     return absl::InvalidArgumentError(
+         absl::StrFormat("Invalid input dimension: {%d, %d}.", dimension.width,
+@@ -176,7 +179,8 @@ absl::Status ValidateBufferFormat(const FrameBuffer& buffer) {
+     case FrameBuffer::Format::kGRAY:
+     case FrameBuffer::Format::kRGB:
+     case FrameBuffer::Format::kRGBA:
+-      if (buffer.plane_count() == 1) return absl::OkStatus();
++      if (buffer.plane_count() == 1)
++        return absl::OkStatus();
+       return absl::InvalidArgumentError(
+           "Plane count must be 1 for grayscale and RGB[a] buffers.");
+     case FrameBuffer::Format::kNV21:
+@@ -252,8 +256,11 @@ absl::Status ValidateRotateBufferInputs(const FrameBuffer& buffer,
+ }
+ 
+ absl::Status ValidateCropBufferInputs(const FrameBuffer& buffer,
+-                                      const FrameBuffer& output_buffer, int x0,
+-                                      int y0, int x1, int y1) {
++                                      const FrameBuffer& output_buffer,
++                                      int x0,
++                                      int y0,
++                                      int x1,
++                                      int y1) {
+   if (!AreBufferFormatsCompatible(buffer, output_buffer)) {
+     return absl::InvalidArgumentError(
+         "Input and output buffer formats must match.");
+@@ -314,8 +321,10 @@ absl::Status ValidateConvertFormats(FrameBuffer::Format from_format,
+ 
+ // Creates a FrameBuffer from raw RGBA buffer and passing arguments.
+ std::unique_ptr<FrameBuffer> CreateFromRgbaRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
+-    FrameBuffer::Orientation orientation, const absl::Time timestamp,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
++    FrameBuffer::Orientation orientation,
++    const absl::Time timestamp,
+     FrameBuffer::Stride stride) {
+   if (stride == kDefaultStride) {
+     stride.row_stride_bytes = dimension.width * kRgbaChannels;
+@@ -330,8 +339,10 @@ std::unique_ptr<FrameBuffer> CreateFromRgbaRawBuffer(
+ 
+ // Creates a FrameBuffer from raw RGB buffer and passing arguments.
+ std::unique_ptr<FrameBuffer> CreateFromRgbRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
+-    FrameBuffer::Orientation orientation, const absl::Time timestamp,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
++    FrameBuffer::Orientation orientation,
++    const absl::Time timestamp,
+     FrameBuffer::Stride stride) {
+   if (stride == kDefaultStride) {
+     stride.row_stride_bytes = dimension.width * kRgbChannels;
+@@ -345,8 +356,10 @@ std::unique_ptr<FrameBuffer> CreateFromRgbRawBuffer(
+ 
+ // Creates a FrameBuffer from raw grayscale buffer and passing arguments.
+ std::unique_ptr<FrameBuffer> CreateFromGrayRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
+-    FrameBuffer::Orientation orientation, const absl::Time timestamp,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
++    FrameBuffer::Orientation orientation,
++    const absl::Time timestamp,
+     FrameBuffer::Stride stride) {
+   if (stride == kDefaultStride) {
+     stride.row_stride_bytes = dimension.width * kGrayChannel;
+@@ -361,10 +374,16 @@ std::unique_ptr<FrameBuffer> CreateFromGrayRawBuffer(
+ 
+ // Creates a FrameBuffer from raw YUV buffer and passing arguments.
+ StatusOr<std::unique_ptr<FrameBuffer>> CreateFromYuvRawBuffer(
+-    const uint8* y_plane, const uint8* u_plane, const uint8* v_plane,
+-    FrameBuffer::Format format, FrameBuffer::Dimension dimension,
+-    int row_stride_y, int row_stride_uv, int pixel_stride_uv,
+-    FrameBuffer::Orientation orientation, const absl::Time timestamp) {
++    const uint8* y_plane,
++    const uint8* u_plane,
++    const uint8* v_plane,
++    FrameBuffer::Format format,
++    FrameBuffer::Dimension dimension,
++    int row_stride_y,
++    int row_stride_uv,
++    int pixel_stride_uv,
++    FrameBuffer::Orientation orientation,
++    const absl::Time timestamp) {
+   const int pixel_stride_y = 1;
+   std::vector<FrameBuffer::Plane> planes;
+   if (format == FrameBuffer::Format::kNV21 ||
+@@ -385,9 +404,11 @@ StatusOr<std::unique_ptr<FrameBuffer>> CreateFromYuvRawBuffer(
+ }
+ 
+ StatusOr<std::unique_ptr<FrameBuffer>> CreateFromRawBuffer(
+-    const uint8* buffer, FrameBuffer::Dimension dimension,
++    const uint8* buffer,
++    FrameBuffer::Dimension dimension,
+     const FrameBuffer::Format target_format,
+-    FrameBuffer::Orientation orientation, absl::Time timestamp) {
++    FrameBuffer::Orientation orientation,
++    absl::Time timestamp) {
+   switch (target_format) {
+     case FrameBuffer::Format::kNV12:
+       return CreateFromOnePlaneNVRawBuffer(buffer, dimension, target_format,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h
+index 470e76b9037a1..7ebf69fadc3de 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h
+@@ -18,8 +18,8 @@ limitations under the License.
+ #include <memory>
+ 
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/time/clock.h"  // from @com_google_absl
+-#include "absl/time/time.h"  // from @com_google_absl
++#include "absl/time/clock.h"     // from @com_google_absl
++#include "absl/time/time.h"      // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+@@ -58,7 +58,8 @@ tflite::support::StatusOr<const uint8*> GetUvRawBuffer(
+ // supported formats. This method assums the UV plane share the same dimension,
+ // especially for the YV12 / YV21 formats.
+ tflite::support::StatusOr<FrameBuffer::Dimension> GetUvPlaneDimension(
+-    FrameBuffer::Dimension dimension, FrameBuffer::Format format);
++    FrameBuffer::Dimension dimension,
++    FrameBuffer::Format format);
+ 
+ // Returns crop dimension based on crop start and end points.
+ FrameBuffer::Dimension GetCropDimension(int x0, int x1, int y0, int y1);
+@@ -92,8 +93,11 @@ absl::Status ValidateRotateBufferInputs(const FrameBuffer& buffer,
+ // (x0, y0) represents the top-left point of the buffer.
+ // (x1, y1) represents the bottom-right point of the buffer.
+ absl::Status ValidateCropBufferInputs(const FrameBuffer& buffer,
+-                                      const FrameBuffer& output_buffer, int x0,
+-                                      int y0, int x1, int y1);
++                                      const FrameBuffer& output_buffer,
++                                      int x0,
++                                      int y0,
++                                      int x1,
++                                      int y1);
+ 
+ // Validates the given inputs for flipping `buffer` horizontally or vertically.
+ absl::Status ValidateFlipBufferInputs(const FrameBuffer& buffer,
+@@ -110,36 +114,45 @@ absl::Status ValidateConvertFormats(FrameBuffer::Format from_format,
+ 
+ // Creates a FrameBuffer from raw RGBA buffer and passing arguments.
+ std::unique_ptr<FrameBuffer> CreateFromRgbaRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
+     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
+     absl::Time timestamp = absl::Now(),
+     FrameBuffer::Stride stride = kDefaultStride);
+ 
+ // Creates a FrameBuffer from raw RGB buffer and passing arguments.
+ std::unique_ptr<FrameBuffer> CreateFromRgbRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
+     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
+     absl::Time timestamp = absl::Now(),
+     FrameBuffer::Stride stride = kDefaultStride);
+ 
+ // Creates a FrameBuffer from raw grayscale buffer and passing arguments.
+ std::unique_ptr<FrameBuffer> CreateFromGrayRawBuffer(
+-    const uint8* input, FrameBuffer::Dimension dimension,
++    const uint8* input,
++    FrameBuffer::Dimension dimension,
+     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
+     absl::Time timestamp = absl::Now(),
+     FrameBuffer::Stride stride = kDefaultStride);
+ 
+ // Creates a FrameBuffer from raw YUV buffer and passing arguments.
+ tflite::support::StatusOr<std::unique_ptr<FrameBuffer>> CreateFromYuvRawBuffer(
+-    const uint8* y_plane, const uint8* u_plane, const uint8* v_plane,
+-    FrameBuffer::Format format, FrameBuffer::Dimension dimension,
+-    int row_stride_y, int row_stride_uv, int pixel_stride_uv,
++    const uint8* y_plane,
++    const uint8* u_plane,
++    const uint8* v_plane,
++    FrameBuffer::Format format,
++    FrameBuffer::Dimension dimension,
++    int row_stride_y,
++    int row_stride_uv,
++    int pixel_stride_uv,
+     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
+     absl::Time timestamp = absl::Now());
+ 
+ // Creates an instance of FrameBuffer from raw buffer and passing arguments.
+ tflite::support::StatusOr<std::unique_ptr<FrameBuffer>> CreateFromRawBuffer(
+-    const uint8* buffer, FrameBuffer::Dimension dimension,
++    const uint8* buffer,
++    FrameBuffer::Dimension dimension,
+     FrameBuffer::Format target_format,
+     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
+     absl::Time timestamp = absl::Now());
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc
+index 4d767fc3e48b2..4728c30cb60dc 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc
+@@ -22,8 +22,8 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/memory/memory.h"       // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/kernels/internal/compatibility.h"
+ #include "tensorflow/lite/kernels/op_macros.h"
+@@ -91,7 +91,8 @@ static int GetOrientationIndex(FrameBuffer::Orientation orientation) {
+ // The new box origin is (x:box.origin_y, y:width - (box.origin_x + box.width).
+ // The new box dimension is (w: box.height, h: box.width).
+ //
+-static BoundingBox RotateBoundingBox(const BoundingBox& box, int angle,
++static BoundingBox RotateBoundingBox(const BoundingBox& box,
++                                     int angle,
+                                      FrameBuffer::Dimension frame_dimension) {
+   int rx = box.origin_x(), ry = box.origin_y(), rw = box.width(),
+       rh = box.height();
+@@ -130,9 +131,12 @@ static BoundingBox RotateBoundingBox(const BoundingBox& box, int angle,
+ // in counterclockwise degree in one of the values [0, 90, 180, 270].
+ //
+ // See `RotateBoundingBox` above for more details.
+-static void RotateCoordinates(int from_x, int from_y, int angle,
++static void RotateCoordinates(int from_x,
++                              int from_y,
++                              int angle,
+                               const FrameBuffer::Dimension& frame_dimension,
+-                              int* to_x, int* to_y) {
++                              int* to_x,
++                              int* to_y) {
+   switch (angle) {
+     case 0:
+       *to_x = from_x;
+@@ -199,7 +203,10 @@ BoundingBox OrientBoundingBox(const BoundingBox& from_box,
+ }
+ 
+ BoundingBox OrientAndDenormalizeBoundingBox(
+-    float from_left, float from_top, float from_right, float from_bottom,
++    float from_left,
++    float from_top,
++    float from_right,
++    float from_bottom,
+     FrameBuffer::Orientation from_orientation,
+     FrameBuffer::Orientation to_orientation,
+     FrameBuffer::Dimension from_dimension) {
+@@ -214,10 +221,12 @@ BoundingBox OrientAndDenormalizeBoundingBox(
+   return to_box;
+ }
+ 
+-void OrientCoordinates(int from_x, int from_y,
++void OrientCoordinates(int from_x,
++                       int from_y,
+                        FrameBuffer::Orientation from_orientation,
+                        FrameBuffer::Orientation to_orientation,
+-                       FrameBuffer::Dimension from_dimension, int* to_x,
++                       FrameBuffer::Dimension from_dimension,
++                       int* to_x,
+                        int* to_y) {
+   *to_x = from_x;
+   *to_y = from_y;
+@@ -298,15 +307,19 @@ bool RequireDimensionSwap(FrameBuffer::Orientation from_orientation,
+   return params.rotation_angle_deg == 90 || params.rotation_angle_deg == 270;
+ }
+ 
+-absl::Status FrameBufferUtils::Crop(const FrameBuffer& buffer, int x0, int y0,
+-                                    int x1, int y1,
++absl::Status FrameBufferUtils::Crop(const FrameBuffer& buffer,
++                                    int x0,
++                                    int y0,
++                                    int x1,
++                                    int y1,
+                                     FrameBuffer* output_buffer) {
+   TFLITE_DCHECK(utils_ != nullptr);
+   return utils_->Crop(buffer, x0, y0, x1, y1, output_buffer);
+ }
+ 
+ FrameBuffer::Dimension FrameBufferUtils::GetSize(
+-    const FrameBuffer& buffer, const FrameBufferOperation& operation) {
++    const FrameBuffer& buffer,
++    const FrameBufferOperation& operation) {
+   FrameBuffer::Dimension dimension = buffer.dimension();
+   if (absl::holds_alternative<OrientOperation>(operation)) {
+     OrientParams params =
+@@ -327,7 +340,8 @@ FrameBuffer::Dimension FrameBufferUtils::GetSize(
+ }
+ 
+ std::vector<FrameBuffer::Plane> FrameBufferUtils::GetPlanes(
+-    const uint8* buffer, FrameBuffer::Dimension dimension,
++    const uint8* buffer,
++    FrameBuffer::Dimension dimension,
+     FrameBuffer::Format format) {
+   std::vector<FrameBuffer::Plane> planes;
+   switch (format) {
+@@ -378,7 +392,8 @@ std::vector<FrameBuffer::Plane> FrameBufferUtils::GetPlanes(
+ }
+ 
+ FrameBuffer::Orientation FrameBufferUtils::GetOrientation(
+-    const FrameBuffer& buffer, const FrameBufferOperation& operation) {
++    const FrameBuffer& buffer,
++    const FrameBufferOperation& operation) {
+   if (absl::holds_alternative<OrientOperation>(operation)) {
+     return absl::get<OrientOperation>(operation).to_orientation;
+   }
+@@ -386,7 +401,8 @@ FrameBuffer::Orientation FrameBufferUtils::GetOrientation(
+ }
+ 
+ FrameBuffer::Format FrameBufferUtils::GetFormat(
+-    const FrameBuffer& buffer, const FrameBufferOperation& operation) {
++    const FrameBuffer& buffer,
++    const FrameBufferOperation& operation) {
+   if (absl::holds_alternative<ConvertOperation>(operation)) {
+     return absl::get<ConvertOperation>(operation).to_format;
+   }
+@@ -578,8 +594,10 @@ absl::Status FrameBufferUtils::Execute(
+ }
+ 
+ absl::Status FrameBufferUtils::Preprocess(
+-    const FrameBuffer& buffer, absl::optional<BoundingBox> bounding_box,
+-    FrameBuffer* output_buffer, bool uniform_resizing) {
++    const FrameBuffer& buffer,
++    absl::optional<BoundingBox> bounding_box,
++    FrameBuffer* output_buffer,
++    bool uniform_resizing) {
+   std::vector<FrameBufferOperation> frame_buffer_operations;
+   // Handle cropping and resizing.
+   bool needs_dimension_swap =
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h
+index 59e80e5765bb0..48549461159cb 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h
+@@ -19,9 +19,9 @@ limitations under the License.
+ #include <memory>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"   // from @com_google_absl
+ #include "absl/types/optional.h"  // from @com_google_absl
+-#include "absl/types/variant.h"  // from @com_google_absl
++#include "absl/types/variant.h"   // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+ #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+@@ -45,7 +45,10 @@ BoundingBox OrientBoundingBox(const BoundingBox& from_box,
+ 
+ // Same as OrientBoundingBox but from normalized coordinates.
+ BoundingBox OrientAndDenormalizeBoundingBox(
+-    float from_left, float from_top, float from_right, float from_bottom,
++    float from_left,
++    float from_top,
++    float from_right,
++    float from_bottom,
+     FrameBuffer::Orientation from_orientation,
+     FrameBuffer::Orientation to_orientation,
+     FrameBuffer::Dimension from_dimension);
+@@ -53,10 +56,12 @@ BoundingBox OrientAndDenormalizeBoundingBox(
+ // Rotates `(from_x, from_y)` coordinates from an image of dimension
+ // `from_dimension` and orientation `from_orientation` into `(to_x, to_y)`
+ // coordinates with orientation `to_orientation`.
+-void OrientCoordinates(int from_x, int from_y,
++void OrientCoordinates(int from_x,
++                       int from_y,
+                        FrameBuffer::Orientation from_orientation,
+                        FrameBuffer::Orientation to_orientation,
+-                       FrameBuffer::Dimension from_dimension, int* to_x,
++                       FrameBuffer::Dimension from_dimension,
++                       int* to_x,
+                        int* to_y);
+ 
+ // Returns whether the conversion from from_orientation to to_orientation
+@@ -92,7 +97,8 @@ OrientParams GetOrientParams(FrameBuffer::Orientation from_orientation,
+ // To perform just cropping, the `crop_width` and `crop_height` should be the
+ // same as `resize_width` `and resize_height`.
+ struct CropResizeOperation {
+-  CropResizeOperation(int crop_origin_x, int crop_origin_y,
++  CropResizeOperation(int crop_origin_x,
++                      int crop_origin_y,
+                       FrameBuffer::Dimension crop_dimension,
+                       FrameBuffer::Dimension resize_dimension)
+       : crop_origin_x(crop_origin_x),
+@@ -124,7 +130,8 @@ struct CropResizeOperation {
+ // The resized region is aligned to the upper left pixel of the output buffer.
+ // The unfilled area of the output buffer remains untouched.
+ struct UniformCropResizeOperation {
+-  UniformCropResizeOperation(int crop_origin_x, int crop_origin_y,
++  UniformCropResizeOperation(int crop_origin_x,
++                             int crop_origin_y,
+                              FrameBuffer::Dimension crop_dimension,
+                              FrameBuffer::Dimension output_dimension)
+       : crop_origin_x(crop_origin_x),
+@@ -154,9 +161,10 @@ struct OrientOperation {
+ 
+ // A variant of the supported operations on FrameBuffers. Alias for user
+ // convenience.
+-using FrameBufferOperation =
+-    absl::variant<CropResizeOperation, ConvertOperation, OrientOperation,
+-                  UniformCropResizeOperation>;
++using FrameBufferOperation = absl::variant<CropResizeOperation,
++                                           ConvertOperation,
++                                           OrientOperation,
++                                           UniformCropResizeOperation>;
+ 
+ // Image processing utility. This utility provides both basic image buffer
+ // manipulations (e.g. rotation, format conversion, resizing, etc) as well as
+@@ -212,7 +220,11 @@ class FrameBufferUtils {
+   // should be big enough to store the operation result. If the `output_buffer`
+   // size dimension does not match with crop dimension, then a resize is
+   // automatically performed.
+-  absl::Status Crop(const FrameBuffer& buffer, int x0, int y0, int x1, int y1,
++  absl::Status Crop(const FrameBuffer& buffer,
++                    int x0,
++                    int y0,
++                    int x1,
++                    int y1,
+                     FrameBuffer* output_buffer);
+ 
+   // Performs resizing operation.
+@@ -229,7 +241,8 @@ class FrameBufferUtils {
+   //
+   // The output_buffer should have metadata populated and its backing buffer
+   // should be big enough to store the operation result.
+-  absl::Status Rotate(const FrameBuffer& buffer, RotationDegree rotation,
++  absl::Status Rotate(const FrameBuffer& buffer,
++                      RotationDegree rotation,
+                       FrameBuffer* output_buffer);
+ 
+   // Performs horizontal flip operation.
+@@ -305,7 +318,8 @@ class FrameBufferUtils {
+ 
+   // Returns the new FrameBuffer orientation after command is processed.
+   FrameBuffer::Orientation GetOrientation(
+-      const FrameBuffer& buffer, const FrameBufferOperation& operation);
++      const FrameBuffer& buffer,
++      const FrameBufferOperation& operation);
+ 
+   // Returns the new FrameBuffer format after command is processed.
+   FrameBuffer::Format GetFormat(const FrameBuffer& buffer,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h
+index ec0c3119ea4e8..59da2206bb06f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h
+@@ -37,8 +37,12 @@ class FrameBufferUtilsInterface {
+   //
+   // The `output_buffer` should have metadata populated and its backing buffer
+   // should be big enough to store the operation result.
+-  virtual absl::Status Crop(const FrameBuffer& buffer, int x0, int y0, int x1,
+-                            int y1, FrameBuffer* output_buffer) = 0;
++  virtual absl::Status Crop(const FrameBuffer& buffer,
++                            int x0,
++                            int y0,
++                            int x1,
++                            int y1,
++                            FrameBuffer* output_buffer) = 0;
+ 
+   // Resizes `buffer` to the size of the given `output_buffer`.
+   //
+@@ -57,7 +61,8 @@ class FrameBufferUtilsInterface {
+   //
+   // The `output_buffer` should have metadata populated and its backing buffer
+   // should be big enough to store the operation result.
+-  virtual absl::Status Rotate(const FrameBuffer& buffer, int angle_deg,
++  virtual absl::Status Rotate(const FrameBuffer& buffer,
++                              int angle_deg,
+                               FrameBuffer* output_buffer) = 0;
+ 
+   // Flips `buffer` horizontally.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
+index 6fd3ca81c984c..a00c8223fac99 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
+@@ -20,10 +20,10 @@ limitations under the License.
+ #include <memory>
+ #include <string>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_cat.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/str_cat.h"     // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "libyuv.h"  // from @libyuv
++#include "libyuv.h"                   // from @libyuv
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -383,7 +383,8 @@ absl::Status ResizeNv(const FrameBuffer& buffer, FrameBuffer* output_buffer) {
+ 
+ // Converts `buffer` to libyuv ARGB format and stores the conversion result
+ // in `dest_argb`.
+-absl::Status ConvertRgbToArgb(const FrameBuffer& buffer, uint8* dest_argb,
++absl::Status ConvertRgbToArgb(const FrameBuffer& buffer,
++                              uint8* dest_argb,
+                               int dest_stride_argb) {
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(buffer));
+   if (buffer.format() != FrameBuffer::Format::kRGB) {
+@@ -420,7 +421,8 @@ absl::Status ConvertRgbToArgb(const FrameBuffer& buffer, uint8* dest_argb,
+ 
+ // Converts `src_argb` in libyuv ARGB format to FrameBuffer::kRGB format and
+ // stores the conversion result in `output_buffer`.
+-absl::Status ConvertArgbToRgb(uint8* src_argb, int src_stride_argb,
++absl::Status ConvertArgbToRgb(uint8* src_argb,
++                              int src_stride_argb,
+                               FrameBuffer* output_buffer) {
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(*output_buffer));
+   if (output_buffer->format() != FrameBuffer::Format::kRGB) {
+@@ -456,7 +458,8 @@ absl::Status ConvertArgbToRgb(uint8* src_argb, int src_stride_argb,
+ 
+ // Converts `buffer` in FrameBuffer::kRGBA format to libyuv ARGB (BGRA in
+ // memory) format and stores the conversion result in `dest_argb`.
+-absl::Status ConvertRgbaToArgb(const FrameBuffer& buffer, uint8* dest_argb,
++absl::Status ConvertRgbaToArgb(const FrameBuffer& buffer,
++                               uint8* dest_argb,
+                                int dest_stride_argb) {
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(buffer));
+   if (buffer.format() != FrameBuffer::Format::kRGBA) {
+@@ -674,7 +677,8 @@ libyuv::RotationMode GetLibyuvRotationMode(int angle_deg) {
+   }
+ }
+ 
+-absl::Status RotateRgba(const FrameBuffer& buffer, int angle_deg,
++absl::Status RotateRgba(const FrameBuffer& buffer,
++                        int angle_deg,
+                         FrameBuffer* output_buffer) {
+   if (buffer.plane_count() > 1) {
+     return CreateStatusWithPayload(
+@@ -698,7 +702,8 @@ absl::Status RotateRgba(const FrameBuffer& buffer, int angle_deg,
+   return absl::OkStatus();
+ }
+ 
+-absl::Status RotateRgb(const FrameBuffer& buffer, int angle_deg,
++absl::Status RotateRgb(const FrameBuffer& buffer,
++                       int angle_deg,
+                        FrameBuffer* output_buffer) {
+   // libyuv does not support rotate kRGB (RGB24) foramat. In this method, the
+   // implementation converts kRGB format to ARGB and use ARGB buffer for
+@@ -731,7 +736,8 @@ absl::Status RotateRgb(const FrameBuffer& buffer, int angle_deg,
+                           output_buffer);
+ }
+ 
+-absl::Status RotateGray(const FrameBuffer& buffer, int angle_deg,
++absl::Status RotateGray(const FrameBuffer& buffer,
++                        int angle_deg,
+                         FrameBuffer* output_buffer) {
+   if (buffer.plane_count() > 1) {
+     return CreateStatusWithPayload(
+@@ -754,7 +760,8 @@ absl::Status RotateGray(const FrameBuffer& buffer, int angle_deg,
+ }
+ 
+ // Rotates YV12/YV21 frame buffer.
+-absl::Status RotateYv(const FrameBuffer& buffer, int angle_deg,
++absl::Status RotateYv(const FrameBuffer& buffer,
++                      int angle_deg,
+                       FrameBuffer* output_buffer) {
+   ASSIGN_OR_RETURN(FrameBuffer::YuvData input_data,
+                    FrameBuffer::GetYuvDataFromFrameBuffer(buffer));
+@@ -779,7 +786,8 @@ absl::Status RotateYv(const FrameBuffer& buffer, int angle_deg,
+ // Rotates NV12/NV21 frame buffer.
+ // TODO(b/152097364): Refactor NV12/NV21 rotation after libyuv explicitly
+ // support that.
+-absl::Status RotateNv(const FrameBuffer& buffer, int angle_deg,
++absl::Status RotateNv(const FrameBuffer& buffer,
++                      int angle_deg,
+                       FrameBuffer* output_buffer) {
+   if (buffer.format() != FrameBuffer::Format::kNV12 &&
+       buffer.format() != FrameBuffer::Format::kNV21) {
+@@ -869,8 +877,12 @@ absl::Status FlipPlaneVertically(const FrameBuffer& buffer,
+ }
+ 
+ // This method only supports kGRAY, kRGBA, and kRGB formats.
+-absl::Status CropPlane(const FrameBuffer& buffer, int x0, int y0, int x1,
+-                       int y1, FrameBuffer* output_buffer) {
++absl::Status CropPlane(const FrameBuffer& buffer,
++                       int x0,
++                       int y0,
++                       int x1,
++                       int y1,
++                       FrameBuffer* output_buffer) {
+   if (buffer.plane_count() > 1) {
+     return CreateStatusWithPayload(
+         StatusCode::kInternal,
+@@ -897,7 +909,11 @@ absl::Status CropPlane(const FrameBuffer& buffer, int x0, int y0, int x1,
+ 
+ // Crops NV12/NV21 FrameBuffer to the subregion defined by the top left pixel
+ // position (x0, y0) and the bottom right pixel position (x1, y1).
+-absl::Status CropNv(const FrameBuffer& buffer, int x0, int y0, int x1, int y1,
++absl::Status CropNv(const FrameBuffer& buffer,
++                    int x0,
++                    int y0,
++                    int x1,
++                    int y1,
+                     FrameBuffer* output_buffer) {
+   ASSIGN_OR_RETURN(FrameBuffer::YuvData input_data,
+                    FrameBuffer::GetYuvDataFromFrameBuffer(buffer));
+@@ -929,7 +945,11 @@ absl::Status CropNv(const FrameBuffer& buffer, int x0, int y0, int x1, int y1,
+ 
+ // Crops YV12/YV21 FrameBuffer to the subregion defined by the top left pixel
+ // position (x0, y0) and the bottom right pixel position (x1, y1).
+-absl::Status CropYv(const FrameBuffer& buffer, int x0, int y0, int x1, int y1,
++absl::Status CropYv(const FrameBuffer& buffer,
++                    int x0,
++                    int y0,
++                    int x1,
++                    int y1,
+                     FrameBuffer* output_buffer) {
+   ASSIGN_OR_RETURN(FrameBuffer::YuvData input_data,
+                    FrameBuffer::GetYuvDataFromFrameBuffer(buffer));
+@@ -964,8 +984,12 @@ absl::Status CropYv(const FrameBuffer& buffer, int x0, int y0, int x1, int y1,
+   return absl::OkStatus();
+ }
+ 
+-absl::Status CropResizeYuv(const FrameBuffer& buffer, int x0, int y0, int x1,
+-                           int y1, FrameBuffer* output_buffer) {
++absl::Status CropResizeYuv(const FrameBuffer& buffer,
++                           int x0,
++                           int y0,
++                           int x1,
++                           int y1,
++                           FrameBuffer* output_buffer) {
+   FrameBuffer::Dimension crop_dimension = GetCropDimension(x0, x1, y0, y1);
+   if (crop_dimension == output_buffer->dimension()) {
+     switch (buffer.format()) {
+@@ -1293,8 +1317,12 @@ absl::Status ResizeGray(const FrameBuffer& buffer, FrameBuffer* output_buffer) {
+ }
+ 
+ // This method only supports kGRAY, kRGBA, and kRGB formats.
+-absl::Status CropResize(const FrameBuffer& buffer, int x0, int y0, int x1,
+-                        int y1, FrameBuffer* output_buffer) {
++absl::Status CropResize(const FrameBuffer& buffer,
++                        int x0,
++                        int y0,
++                        int x1,
++                        int y1,
++                        FrameBuffer* output_buffer) {
+   FrameBuffer::Dimension crop_dimension = GetCropDimension(x0, x1, y0, y1);
+   if (crop_dimension == output_buffer->dimension()) {
+     return CropPlane(buffer, x0, y0, x1, y1, output_buffer);
+@@ -1326,10 +1354,13 @@ absl::Status CropResize(const FrameBuffer& buffer, int x0, int y0, int x1,
+   }
+ }
+ 
+-} // namespace
++}  // namespace
+ 
+-absl::Status LibyuvFrameBufferUtils::Crop(const FrameBuffer& buffer, int x0,
+-                                          int y0, int x1, int y1,
++absl::Status LibyuvFrameBufferUtils::Crop(const FrameBuffer& buffer,
++                                          int x0,
++                                          int y0,
++                                          int x1,
++                                          int y1,
+                                           FrameBuffer* output_buffer) {
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(buffer));
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(*output_buffer));
+@@ -1410,7 +1441,8 @@ absl::Status LibyuvFrameBufferUtils::Rotate(const FrameBuffer& buffer,
+ }
+ 
+ absl::Status LibyuvFrameBufferUtils::FlipHorizontally(
+-    const FrameBuffer& buffer, FrameBuffer* output_buffer) {
++    const FrameBuffer& buffer,
++    FrameBuffer* output_buffer) {
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(buffer));
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(*output_buffer));
+   RETURN_IF_ERROR(ValidateFlipBufferInputs(buffer, *output_buffer));
+@@ -1438,7 +1470,8 @@ absl::Status LibyuvFrameBufferUtils::FlipHorizontally(
+ }
+ 
+ absl::Status LibyuvFrameBufferUtils::FlipVertically(
+-    const FrameBuffer& buffer, FrameBuffer* output_buffer) {
++    const FrameBuffer& buffer,
++    FrameBuffer* output_buffer) {
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(buffer));
+   RETURN_IF_ERROR(ValidateBufferPlaneMetadata(*output_buffer));
+   RETURN_IF_ERROR(ValidateFlipBufferInputs(buffer, *output_buffer));
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h
+index 5da898bc058a4..6f83559139130 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h
+@@ -41,7 +41,11 @@ class LibyuvFrameBufferUtils : public FrameBufferUtilsInterface {
+   //
+   // Crop region dimensions must be equal or smaller than input `buffer`
+   // dimensions.
+-  absl::Status Crop(const FrameBuffer& buffer, int x0, int y0, int x1, int y1,
++  absl::Status Crop(const FrameBuffer& buffer,
++                    int x0,
++                    int y0,
++                    int x1,
++                    int y1,
+                     FrameBuffer* output_buffer) override;
+ 
+   // Resizes `buffer` to the size of the given `output_buffer`.
+@@ -51,7 +55,8 @@ class LibyuvFrameBufferUtils : public FrameBufferUtilsInterface {
+   // Rotates `buffer` counter-clockwise by the given `angle_deg` (in degrees).
+   //
+   // The given angle must be a multiple of 90 degrees.
+-  absl::Status Rotate(const FrameBuffer& buffer, int angle_deg,
++  absl::Status Rotate(const FrameBuffer& buffer,
++                      int angle_deg,
+                       FrameBuffer* output_buffer) override;
+ 
+   // Flips `buffer` horizontally.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc
+index bc57c0b904534..d58969d96827e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc
+@@ -20,11 +20,11 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "absl/strings/str_split.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
++#include "absl/strings/str_format.h"   // from @com_google_absl
++#include "absl/strings/str_split.h"    // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "absl/types/optional.h"  // from @com_google_absl
++#include "absl/types/optional.h"       // from @com_google_absl
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h
+index 95cbecf54bd1d..e2b403d9b35b9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h
+@@ -23,9 +23,9 @@ limitations under the License.
+ #include <vector>
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/string_view.h"  // from @com_google_absl
+-#include "absl/types/optional.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/string_view.h"      // from @com_google_absl
++#include "absl/types/optional.h"           // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+@@ -37,7 +37,10 @@ namespace vision {
+ // Sigmoid structure.
+ struct Sigmoid {
+   Sigmoid() : scale(1.0) {}
+-  Sigmoid(std::string label, float slope, float offset, float scale = 1.0,
++  Sigmoid(std::string label,
++          float slope,
++          float offset,
++          float scale = 1.0,
+           absl::optional<float> min_uncalibrated_score = absl::nullopt)
+       : label(label),
+         slope(slope),
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc
+index 311994c1abbf9..bc2f9dfd53a96 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc
+@@ -16,7 +16,7 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/common.h"
+ 
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/cord.h"  // from @com_google_absl
++#include "absl/strings/cord.h"   // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/gmock.h"
+ #include "tensorflow_lite_support/cc/port/gtest.h"
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc
+index d0a7e33129e7e..9ae943548dc63 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc
+@@ -46,8 +46,8 @@ constexpr char kTestDataDirectory[] =
+ constexpr char kDilatedConvolutionModelWithMetaData[] = "dilated_conv.tflite";
+ 
+ StatusOr<ImageData> LoadImage(std::string image_name) {
+-  return DecodeImageFromFile(JoinPath("./" /*test src dir*/,
+-                                      kTestDataDirectory, image_name));
++  return DecodeImageFromFile(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+ }
+ 
+ class DynamicInputTest : public tflite_shims::testing::Test {
+@@ -60,7 +60,7 @@ class DynamicInputTest : public tflite_shims::testing::Test {
+     SUPPORT_ASSERT_OK(engine_->InitInterpreter());
+ 
+     SUPPORT_ASSERT_OK_AND_ASSIGN(auto preprocessor,
+-                         ImagePreprocessor::Create(engine_.get(), {0}));
++                                 ImagePreprocessor::Create(engine_.get(), {0}));
+ 
+     SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+     std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+@@ -94,9 +94,10 @@ TEST_F(DynamicInputTest, GoldenImageComparison) {
+   PreprocessImage();
+ 
+   // Get the processed input image.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(float* processed_input_data,
+-                       tflite::task::core::AssertAndReturnTypedTensor<float>(
+-                           engine_->GetInputs()[0]));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      float* processed_input_data,
++      tflite::task::core::AssertAndReturnTypedTensor<float>(
++          engine_->GetInputs()[0]));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+   const uint8* image_data = image.pixel_data;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc
+index 629f069e7b8d1..c4a8cea0d53b9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc
+@@ -49,8 +49,7 @@ constexpr char kInvalidModelPath[] = "i/do/not/exist.tflite";
+ constexpr int kMaxSeqLen = 128;
+ 
+ std::string GetFullPath(absl::string_view file_name) {
+-  return JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-                  file_name);
++  return JoinPath("./" /*test src dir*/, kTestDataDirectory, file_name);
+ }
+ 
+ class BertNLClassifierTest : public tflite_shims::testing::Test {};
+@@ -77,14 +76,15 @@ TEST_F(BertNLClassifierTest, CreateFromOptionsFailsWithMissingBaseOptions) {
+ }
+ 
+ TEST_F(BertNLClassifierTest, TestNLClassifierCreationFilePath) {
+-  SUPPORT_ASSERT_OK(BertNLClassifier::CreateFromFile(GetFullPath(kTestModelPath)));
++  SUPPORT_ASSERT_OK(
++      BertNLClassifier::CreateFromFile(GetFullPath(kTestModelPath)));
+ }
+ 
+ TEST_F(BertNLClassifierTest, TestNLClassifierCreationBinary) {
+   std::string model_buffer =
+       LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+   SUPPORT_ASSERT_OK(BertNLClassifier::CreateFromBuffer(model_buffer.data(),
+-                                               model_buffer.size()));
++                                                       model_buffer.size()));
+ }
+ 
+ TEST_F(BertNLClassifierTest, TestNLClassifierCreationFailure) {
+@@ -136,7 +136,7 @@ TEST_F(BertNLClassifierTest, ClassifySucceedsWithBaseOptions) {
+         contents);
+ 
+     SUPPORT_ASSERT_OK_AND_ASSIGN(classifier,
+-                         BertNLClassifier::CreateFromOptions(options));
++                                 BertNLClassifier::CreateFromOptions(options));
+   }
+ 
+   verify_classifier(std::move(classifier), /*verify_positive=*/false);
+@@ -146,8 +146,8 @@ TEST_F(BertNLClassifierTest, TestNLClassifier_ClassifyNegative) {
+   std::string model_buffer =
+       LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+-                       BertNLClassifier::CreateFromBuffer(model_buffer.data(),
+-                                                          model_buffer.size()));
++                               BertNLClassifier::CreateFromBuffer(
++                                   model_buffer.data(), model_buffer.size()));
+ 
+   verify_classifier(std::move(classifier), false);
+ }
+@@ -156,24 +156,26 @@ TEST_F(BertNLClassifierTest, TestNLClassifier_ClassifyPositive) {
+   std::string model_buffer =
+       LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+-                       BertNLClassifier::CreateFromBuffer(model_buffer.data(),
+-                                                          model_buffer.size()));
++                               BertNLClassifier::CreateFromBuffer(
++                                   model_buffer.data(), model_buffer.size()));
+ 
+   verify_classifier(std::move(classifier), true);
+ }
+ 
+ TEST_F(BertNLClassifierTest, TestNLClassifierFd_ClassifyPositive) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+-                       BertNLClassifier::CreateFromFd(open(
+-                           GetFullPath(kTestModelPath).c_str(), O_RDONLY)));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<BertNLClassifier> classifier,
++      BertNLClassifier::CreateFromFd(
++          open(GetFullPath(kTestModelPath).c_str(), O_RDONLY)));
+ 
+   verify_classifier(std::move(classifier), false);
+ }
+ 
+ TEST_F(BertNLClassifierTest, TestNLClassifierFd_ClassifyNegative) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+-                       BertNLClassifier::CreateFromFd(open(
+-                           GetFullPath(kTestModelPath).c_str(), O_RDONLY)));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<BertNLClassifier> classifier,
++      BertNLClassifier::CreateFromFd(
++          open(GetFullPath(kTestModelPath).c_str(), O_RDONLY)));
+ 
+   verify_classifier(std::move(classifier), true);
+ }
+@@ -191,8 +193,8 @@ TEST_F(BertNLClassifierTest, TestNLClassifier_ClassifyLongPositive_notOOB) {
+   }
+   ss_for_positive_review << " movie review";
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+-                       BertNLClassifier::CreateFromBuffer(model_buffer.data(),
+-                                                          model_buffer.size()));
++                               BertNLClassifier::CreateFromBuffer(
++                                   model_buffer.data(), model_buffer.size()));
+ 
+   std::vector<core::Category> results =
+       classifier->Classify(ss_for_positive_review.str());
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc
+index 252441df1cb59..a70dab7782044 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc
+@@ -69,8 +69,7 @@ constexpr int kPredictAnsNum = 5;
+ class BertQuestionAnswererTest : public tflite_shims::testing::Test {};
+ 
+ std::string GetFullPath(absl::string_view file_name) {
+-  return JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-                  file_name);
++  return JoinPath("./" /*test src dir*/, kTestDataDirectory, file_name);
+ }
+ 
+ TEST_F(BertQuestionAnswererTest,
+@@ -108,8 +107,8 @@ TEST_F(BertQuestionAnswererTest, AnswerSucceedsWithModelWithMetadata) {
+     options.mutable_base_options()->mutable_model_file()->set_file_content(
+         contents);
+ 
+-    SUPPORT_ASSERT_OK_AND_ASSIGN(question_answerer,
+-                         BertQuestionAnswerer::CreateFromOptions(options));
++    SUPPORT_ASSERT_OK_AND_ASSIGN(
++        question_answerer, BertQuestionAnswerer::CreateFromOptions(options));
+   }
+ 
+   std::vector<QaAnswer> answer = question_answerer->Answer(kContext, kQuestion);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc
+index 67b03c3a45323..81198cfca30fc 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc
+@@ -121,8 +121,7 @@ struct ProtoOptionsTestParam {
+ };
+ 
+ std::string GetFullPath(absl::string_view file_name) {
+-  return JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-                  file_name);
++  return JoinPath("./" /*test src dir*/, kTestDataDirectory, file_name);
+ }
+ 
+ class ProtoOptionsTest : public TestWithParam<ProtoOptionsTestParam> {
+@@ -163,7 +162,8 @@ TEST_F(ProtoOptionsTest, ClassifySucceedsWithBaseOptions) {
+     options.mutable_base_options()->mutable_model_file()->set_file_content(
+         contents);
+ 
+-    SUPPORT_ASSERT_OK_AND_ASSIGN(classifier, NLClassifier::CreateFromOptions(options));
++    SUPPORT_ASSERT_OK_AND_ASSIGN(classifier,
++                                 NLClassifier::CreateFromOptions(options));
+   }
+ 
+   std::vector<core::Category> positive_results =
+@@ -180,8 +180,8 @@ TEST_F(ProtoOptionsTest, ClassifySucceedsWithBaseOptions) {
+ 
+ TEST_F(ProtoOptionsTest, CreationFromIncorrectInputTensor) {
+   NLClassifierProtoOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kTestModelPath));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath));
+   options.set_input_tensor_name("invalid_tensor_name");
+   options.set_input_tensor_index(-1);
+ 
+@@ -200,8 +200,8 @@ TEST_F(ProtoOptionsTest, CreationFromIncorrectInputTensor) {
+ 
+ TEST_F(ProtoOptionsTest, CreationFromIncorrectOutputScoreTensor) {
+   NLClassifierProtoOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kTestModelPath));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath));
+   options.set_output_score_tensor_name("invalid_tensor_name");
+   options.set_output_score_tensor_index(-1);
+ 
+@@ -224,7 +224,7 @@ TEST_F(ProtoOptionsTest, TestInferenceWithRegexTokenizer) {
+   options.mutable_base_options()->mutable_model_file()->set_file_name(
+       GetFullPath(kTestModelWithRegexTokenizer));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+-                       NLClassifier::CreateFromOptions(options));
++                               NLClassifier::CreateFromOptions(options));
+ 
+   std::vector<core::Category> positive_results =
+       classifier->Classify(kPositiveInput);
+@@ -277,7 +277,7 @@ TEST_F(ProtoOptionsTest, TestInferenceWithAssociatedLabelBuiltinOps) {
+   options.mutable_base_options()->mutable_model_file()->set_file_name(
+       GetFullPath(kTestModelWithLabelBuiltInOpsPath));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+-                       NLClassifier::CreateFromOptions(options));
++                               NLClassifier::CreateFromOptions(options));
+   std::vector<core::Category> results = classifier->Classify(kInputStr);
+   std::vector<core::Category> expected_class = {
+       {"Negative", 0.49332118034362793},
+@@ -296,8 +296,10 @@ struct ProtoOptionsTestParamToString {
+ };
+ 
+ NLClassifierProtoOptions CreateProtoOptionsFromTensorName(
+-    const char* input_tensor_name, const char* output_score_tensor_name,
+-    const char* output_label_tensor_name, const char* model_path) {
++    const char* input_tensor_name,
++    const char* output_score_tensor_name,
++    const char* output_label_tensor_name,
++    const char* model_path) {
+   NLClassifierProtoOptions options;
+   options.set_input_tensor_name(input_tensor_name);
+   options.set_output_score_tensor_name(output_score_tensor_name);
+@@ -310,8 +312,10 @@ NLClassifierProtoOptions CreateProtoOptionsFromTensorName(
+ }
+ 
+ NLClassifierProtoOptions CreateProtoOptionsFromTensorIndex(
+-    const int input_tensor_index, const int output_score_tensor_index,
+-    const int output_label_tensor_index, const char* model_path) {
++    const int input_tensor_index,
++    const int output_score_tensor_index,
++    const int output_label_tensor_index,
++    const char* model_path) {
+   NLClassifierProtoOptions options;
+   options.set_input_tensor_index(input_tensor_index);
+   options.set_output_score_tensor_index(output_score_tensor_index);
+@@ -439,14 +443,16 @@ TEST_P(ProtoOptionsTest, TestClassify) {
+   EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+ }
+ 
+-INSTANTIATE_TEST_SUITE_P(TestClassify, ProtoOptionsTest,
++INSTANTIATE_TEST_SUITE_P(TestClassify,
++                         ProtoOptionsTest,
+                          ValuesIn(ClassifyParams()),
+                          ProtoOptionsTestParamToString());
+ 
+ // Tests for struct sNLClassifierOptions.
+ class StructOptionsTest : public tflite_shims::testing::Test {};
+ 
+-void AssertStatus(absl::Status status, absl::StatusCode status_code,
++void AssertStatus(absl::Status status,
++                  absl::StatusCode status_code,
+                   TfLiteSupportStatus tfls_code) {
+   ASSERT_EQ(status.code(), status_code);
+   EXPECT_THAT(status.GetPayload(kTfLiteSupportPayload),
+@@ -454,30 +460,29 @@ void AssertStatus(absl::Status status, absl::StatusCode status_code,
+ }
+ 
+ TEST_F(StructOptionsTest, TestApiCreationFromBuffer) {
+-  std::string model_buffer =
+-      LoadBinaryContent(JoinPath("./" /*test src dir*/,
+-                                 kTestDataDirectory, kTestModelPath)
+-                            .c_str());
++  std::string model_buffer = LoadBinaryContent(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath)
++          .c_str());
+   SUPPORT_ASSERT_OK(NLClassifier::CreateFromBufferAndOptions(
+       model_buffer.data(), model_buffer.size(), {}, CreateCustomResolver()));
+ }
+ 
+ TEST_F(StructOptionsTest, TestApiCreationFromFile) {
+-  SUPPORT_ASSERT_OK(NLClassifier::CreateFromFileAndOptions(GetFullPath(kTestModelPath),
+-                                                   {}, CreateCustomResolver()));
++  SUPPORT_ASSERT_OK(NLClassifier::CreateFromFileAndOptions(
++      GetFullPath(kTestModelPath), {}, CreateCustomResolver()));
+ }
+ 
+ TEST_F(StructOptionsTest, TestApiCreationFromIncorrectInputTensor) {
+   NLClassifierOptions options;
+   options.input_tensor_index = -1;
+   options.input_tensor_name = "I do not exist";
+-  AssertStatus(NLClassifier::CreateFromFileAndOptions(
+-                   JoinPath("./" /*test src dir*/,
+-                            kTestDataDirectory, kTestModelPath),
+-                   options, CreateCustomResolver())
+-                   .status(),
+-               absl::StatusCode::kInvalidArgument,
+-               TfLiteSupportStatus::kInputTensorNotFoundError);
++  AssertStatus(
++      NLClassifier::CreateFromFileAndOptions(
++          JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath),
++          options, CreateCustomResolver())
++          .status(),
++      absl::StatusCode::kInvalidArgument,
++      TfLiteSupportStatus::kInputTensorNotFoundError);
+ }
+ 
+ TEST_F(StructOptionsTest, TestApiCreationFromIncorrectOutputScoreTensor) {
+@@ -497,9 +502,10 @@ TEST_F(StructOptionsTest, TestInferenceWithRegexTokenizer) {
+   options.output_score_tensor_name = "probability";
+ 
+   // The model with regex tokenizer doesn't need any custom ops.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+-                       NLClassifier::CreateFromFileAndOptions(
+-                           GetFullPath(kTestModelWithRegexTokenizer), options));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<NLClassifier> classifier,
++      NLClassifier::CreateFromFileAndOptions(
++          GetFullPath(kTestModelWithRegexTokenizer), options));
+ 
+   std::vector<core::Category> positive_results =
+       classifier->Classify(kPositiveInput);
+@@ -519,9 +525,9 @@ TEST_F(StructOptionsTest, TestInferenceWithBoolOutput) {
+   options.output_score_tensor_index = 0;
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+-                       NLClassifier::CreateFromFileAndOptions(
+-                           GetFullPath(kTestModelBoolOutputPath), options,
+-                           CreateCustomResolver()));
++                               NLClassifier::CreateFromFileAndOptions(
++                                   GetFullPath(kTestModelBoolOutputPath),
++                                   options, CreateCustomResolver()));
+   std::vector<core::Category> results = classifier->Classify(kInputStr);
+   std::vector<core::Category> expected_class = {
+       {"0", 1},
+@@ -535,10 +541,11 @@ TEST_F(StructOptionsTest, TestInferenceWithBoolOutput) {
+ TEST_F(StructOptionsTest, TestInferenceWithAssociatedLabelCustomOps) {
+   NLClassifierOptions options;
+   options.output_score_tensor_name = kMetadataOutputScoreTensorName;
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+-                       NLClassifier::CreateFromFileAndOptions(
+-                           GetFullPath(kTestModelWithLabelCustomOpsPath),
+-                           options, CreateCustomResolver()));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<NLClassifier> classifier,
++      NLClassifier::CreateFromFileAndOptions(
++          GetFullPath(kTestModelWithLabelCustomOpsPath), options,
++          CreateCustomResolver()));
+   std::vector<core::Category> results = classifier->Classify(kInputStr);
+   std::vector<core::Category> expected_class = {
+       {"label0", 255},
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc
+index 6da6b6f7a2da3..ae4e48cac2410 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc
+@@ -17,9 +17,9 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
++#include "absl/flags/flag.h"     // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/cord.h"  // from @com_google_absl
++#include "absl/strings/cord.h"   // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+ #include "tensorflow/lite/kernels/builtin_op_kernels.h"
+@@ -70,8 +70,8 @@ constexpr char kMobileNetQuantizedWithMetadata[] =
+ constexpr char kAutoMLModelWithMetadata[] = "automl_labeler_model.tflite";
+ 
+ StatusOr<ImageData> LoadImage(std::string image_name) {
+-  return DecodeImageFromFile(JoinPath("./" /*test src dir*/,
+-                                      kTestDataDirectory, image_name));
++  return DecodeImageFromFile(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+ }
+ 
+ // If the proto definition changes, please also change this function.
+@@ -159,9 +159,8 @@ TEST_F(CreateFromOptionsTest, FailsWithTwoModelSources) {
+   options.mutable_model_file_with_metadata()->set_file_name(
+       JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                kMobileNetQuantizedWithMetadata));
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+ 
+   StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+       ImageClassifier::CreateFromOptions(options);
+@@ -234,9 +233,8 @@ TEST_F(CreateFromOptionsTest, FailsWithCombinedWhitelistAndBlacklist) {
+ TEST_F(CreateFromOptionsTest, SucceedsWithNumberOfThreads) {
+   ImageClassifierOptions options;
+   options.set_num_threads(4);
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+ 
+   SUPPORT_ASSERT_OK(ImageClassifier::CreateFromOptions(options));
+ }
+@@ -248,9 +246,8 @@ INSTANTIATE_TEST_SUITE_P(Default, NumThreadsTest, testing::Values(0, -2));
+ TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+   ImageClassifierOptions options;
+   options.set_num_threads(GetParam());
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+ 
+   StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+       ImageClassifier::CreateFromOptions(options);
+@@ -273,12 +270,12 @@ TEST(ClassifyTest, SucceedsWithFloatModel) {
+ 
+   ImageClassifierOptions options;
+   options.set_max_results(3);
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   StatusOr<ClassificationResult> result_or =
+       image_classifier->Classify(*frame_buffer);
+@@ -307,19 +304,20 @@ TEST(ClassifyTest, SucceedsWithFloatModel) {
+ }
+ 
+ TEST(ClassifyTest, SucceedsWithRegionOfInterest) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("multi_objects.jpg"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
++                               LoadImage("multi_objects.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+ 
+   ImageClassifierOptions options;
+   options.set_max_results(1);
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   // Crop around the soccer ball.
+   BoundingBox roi;
+@@ -358,8 +356,9 @@ TEST(ClassifyTest, SucceedsWithQuantizedModel) {
+       JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                kMobileNetQuantizedWithMetadata));
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   StatusOr<ClassificationResult> result_or =
+       image_classifier->Classify(*frame_buffer);
+@@ -391,12 +390,12 @@ TEST(ClassifyTest, SucceedsWithBaseOptions) {
+ 
+   ImageClassifierOptions options;
+   options.set_max_results(3);
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   StatusOr<ClassificationResult> result_or =
+       image_classifier->Classify(*frame_buffer);
+@@ -426,11 +425,11 @@ TEST(ClassifyTest, SucceedsWithBaseOptions) {
+ 
+ TEST(ClassifyTest, GetInputCountSucceeds) {
+   ImageClassifierOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   int32_t input_count = image_classifier->GetInputCount();
+   EXPECT_THAT(input_count, 1);
+@@ -438,11 +437,11 @@ TEST(ClassifyTest, GetInputCountSucceeds) {
+ 
+ TEST(ClassifyTest, GetInputShapeSucceeds) {
+   ImageClassifierOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   // Verify the shape array size.
+   const TfLiteIntArray* input_shape_0 = image_classifier->GetInputShape(0);
+@@ -456,11 +455,11 @@ TEST(ClassifyTest, GetInputShapeSucceeds) {
+ 
+ TEST(ClassifyTest, GetOutputCountSucceeds) {
+   ImageClassifierOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   int32_t output_count = image_classifier->GetOutputCount();
+   EXPECT_THAT(output_count, 1);
+@@ -468,11 +467,11 @@ TEST(ClassifyTest, GetOutputCountSucceeds) {
+ 
+ TEST(ClassifyTest, GetOutputShapeSucceeds) {
+   ImageClassifierOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileNetFloatWithMetadata));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageClassifier> image_classifier,
+-                       ImageClassifier::CreateFromOptions(options));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      std::unique_ptr<ImageClassifier> image_classifier,
++      ImageClassifier::CreateFromOptions(options));
+ 
+   // Verify the shape array size.
+   const TfLiteIntArray* output_shape_0 = image_classifier->GetOutputShape(0);
+@@ -537,9 +536,8 @@ class PostprocessTest : public tflite_shims::testing::Test {
+ 
+ TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+   ImageClassifierOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kAutoMLModelWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+   options.set_max_results(3);
+ 
+   SetUp(options);
+@@ -551,9 +549,10 @@ TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+   std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                  /*sunflowers*/ 32, /*tulips*/ 128};
+   SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ClassificationResult result,
+-                       test_image_classifier_->Postprocess(
+-                           {output_tensor}, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      ClassificationResult result,
++      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
++                                          /*roi=*/{}));
+   ExpectApproximatelyEqual(
+       result,
+       ParseTextProtoOrDie<ClassificationResult>(
+@@ -568,9 +567,8 @@ TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithScoreThresholdOption) {
+   ImageClassifierOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kAutoMLModelWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+   options.set_score_threshold(0.4);
+ 
+   SetUp(options);
+@@ -582,9 +580,10 @@ TEST_F(PostprocessTest, SucceedsWithScoreThresholdOption) {
+   std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                  /*sunflowers*/ 32, /*tulips*/ 128};
+   SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ClassificationResult result,
+-                       test_image_classifier_->Postprocess(
+-                           {output_tensor}, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      ClassificationResult result,
++      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
++                                          /*roi=*/{}));
+ 
+   ExpectApproximatelyEqual(
+       result,
+@@ -599,9 +598,8 @@ TEST_F(PostprocessTest, SucceedsWithScoreThresholdOption) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+   ImageClassifierOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kAutoMLModelWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+   options.add_class_name_whitelist("dandelion");
+   options.add_class_name_whitelist("daisy");
+ 
+@@ -614,9 +612,10 @@ TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+   std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                  /*sunflowers*/ 32, /*tulips*/ 128};
+   SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ClassificationResult result,
+-                       test_image_classifier_->Postprocess(
+-                           {output_tensor}, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      ClassificationResult result,
++      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
++                                          /*roi=*/{}));
+   ExpectApproximatelyEqual(
+       result,
+       ParseTextProtoOrDie<ClassificationResult>(
+@@ -630,9 +629,8 @@ TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithBlacklistOption) {
+   ImageClassifierOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kAutoMLModelWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+   options.add_class_name_blacklist("dandelion");
+   options.add_class_name_blacklist("daisy");
+ 
+@@ -645,9 +643,10 @@ TEST_F(PostprocessTest, SucceedsWithBlacklistOption) {
+   std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                  /*sunflowers*/ 32, /*tulips*/ 128};
+   SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ClassificationResult result,
+-                       test_image_classifier_->Postprocess(
+-                           {output_tensor}, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      ClassificationResult result,
++      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
++                                          /*roi=*/{}));
+ 
+   ExpectApproximatelyEqual(
+       result,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc
+index d5606d12440b0..8877f28b98beb 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc
+@@ -17,7 +17,7 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
++#include "absl/flags/flag.h"     // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+@@ -59,8 +59,8 @@ constexpr char kMobileNetV3[] = "mobilenet_v3_small_100_224_embedder.tflite";
+ constexpr double kSimilarityTolerancy = 1e-6;
+ 
+ StatusOr<ImageData> LoadImage(std::string image_name) {
+-  return DecodeImageFromFile(JoinPath("./" /*test src dir*/,
+-                                      kTestDataDirectory, image_name));
++  return DecodeImageFromFile(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+ }
+ 
+ class MobileNetV3OpResolver : public ::tflite::MutableOpResolver {
+@@ -93,8 +93,8 @@ class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+ 
+ TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+ 
+   SUPPORT_ASSERT_OK(ImageEmbedder::CreateFromOptions(
+       options, absl::make_unique<MobileNetV3OpResolver>()));
+@@ -113,8 +113,8 @@ class MobileNetV3OpResolverMissingOps : public ::tflite::MutableOpResolver {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+ 
+   auto image_embedder_or = ImageEmbedder::CreateFromOptions(
+       options, absl::make_unique<MobileNetV3OpResolverMissingOps>());
+@@ -231,8 +231,9 @@ TEST(CosineSimilarityTest, Succeeds) {
+   // Prevent literal from being interpreted as null-terminated C-style string.
+   *v_quantized.mutable_value_string() = std::string("\x80\x00\x00\x00", 4);
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(double float_similarity,
+-                       ImageEmbedder::CosineSimilarity(u_float, v_float));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      double float_similarity,
++      ImageEmbedder::CosineSimilarity(u_float, v_float));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(
+       double quantized_similarity,
+       ImageEmbedder::CosineSimilarity(u_quantized, v_quantized));
+@@ -246,10 +247,10 @@ TEST(CosineSimilarityTest, Succeeds) {
+ TEST(EmbedTest, SucceedsWithoutL2Normalization) {
+   // Create embedder.
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+-                       ImageEmbedder::CreateFromOptions(options));
++                               ImageEmbedder::CreateFromOptions(options));
+   // Load images: one is a crop of the other.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+   std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+@@ -260,10 +261,10 @@ TEST(EmbedTest, SucceedsWithoutL2Normalization) {
+ 
+   // Extract both embeddings.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+-                       embedder->Embed(*image_frame_buffer));
++                               embedder->Embed(*image_frame_buffer));
+   ImageDataFree(&image);
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+-                       embedder->Embed(*crop_frame_buffer));
++                               embedder->Embed(*crop_frame_buffer));
+   ImageDataFree(&crop);
+ 
+   // Check results sizes
+@@ -276,9 +277,9 @@ TEST(EmbedTest, SucceedsWithoutL2Normalization) {
+       crop_result.embeddings(0).feature_vector();
+   EXPECT_EQ(crop_feature_vector.value_float_size(), 1024);
+   // Check cosine similarity.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(double similarity,
+-                       ImageEmbedder::CosineSimilarity(image_feature_vector,
+-                                                       crop_feature_vector));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
++                                                         crop_feature_vector));
+   double expected_similarity = 0.932738;
+   EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+ }
+@@ -287,11 +288,11 @@ TEST(EmbedTest, SucceedsWithoutL2Normalization) {
+ TEST(EmbedTest, SucceedsWithL2Normalization) {
+   // Create embedder.
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+   options.set_l2_normalize(true);
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+-                       ImageEmbedder::CreateFromOptions(options));
++                               ImageEmbedder::CreateFromOptions(options));
+   // Load images: one is a crop of the other.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+   std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+@@ -302,10 +303,10 @@ TEST(EmbedTest, SucceedsWithL2Normalization) {
+ 
+   // Extract both embeddings.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+-                       embedder->Embed(*image_frame_buffer));
++                               embedder->Embed(*image_frame_buffer));
+   ImageDataFree(&image);
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+-                       embedder->Embed(*crop_frame_buffer));
++                               embedder->Embed(*crop_frame_buffer));
+   ImageDataFree(&crop);
+ 
+   // Check results sizes
+@@ -318,9 +319,9 @@ TEST(EmbedTest, SucceedsWithL2Normalization) {
+       crop_result.embeddings(0).feature_vector();
+   EXPECT_EQ(crop_feature_vector.value_float_size(), 1024);
+   // Check cosine similarity.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(double similarity,
+-                       ImageEmbedder::CosineSimilarity(image_feature_vector,
+-                                                       crop_feature_vector));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
++                                                         crop_feature_vector));
+   double expected_similarity = 0.932738;
+   EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+ }
+@@ -331,12 +332,12 @@ TEST(EmbedTest, SucceedsWithL2Normalization) {
+ TEST(EmbedTest, SucceedsWithQuantization) {
+   // Create embedder.
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+   options.set_l2_normalize(true);
+   options.set_quantize(true);
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+-                       ImageEmbedder::CreateFromOptions(options));
++                               ImageEmbedder::CreateFromOptions(options));
+   // Load images: one is a crop of the other.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+   std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+@@ -347,10 +348,10 @@ TEST(EmbedTest, SucceedsWithQuantization) {
+ 
+   // Extract both embeddings.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+-                       embedder->Embed(*image_frame_buffer));
++                               embedder->Embed(*image_frame_buffer));
+   ImageDataFree(&image);
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+-                       embedder->Embed(*crop_frame_buffer));
++                               embedder->Embed(*crop_frame_buffer));
+   ImageDataFree(&crop);
+ 
+   // Check results sizes
+@@ -363,9 +364,9 @@ TEST(EmbedTest, SucceedsWithQuantization) {
+       crop_result.embeddings(0).feature_vector();
+   EXPECT_EQ(crop_feature_vector.value_string().size(), 1024);
+   // Check cosine similarity.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(double similarity,
+-                       ImageEmbedder::CosineSimilarity(image_feature_vector,
+-                                                       crop_feature_vector));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
++                                                         crop_feature_vector));
+   // Close to but expectedly different from the above tests due to slight loss
+   // of precision during quantization:
+   double expected_similarity = 0.929717;
+@@ -378,10 +379,10 @@ TEST(EmbedTest, SucceedsWithQuantization) {
+ TEST(EmbedTest, SucceedsWithRegionOfInterest) {
+   // Create embedder.
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+-                       ImageEmbedder::CreateFromOptions(options));
++                               ImageEmbedder::CreateFromOptions(options));
+   // Load images: one is a crop of the other.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+   std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+@@ -398,10 +399,10 @@ TEST(EmbedTest, SucceedsWithRegionOfInterest) {
+ 
+   // Extract both embeddings.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+-                       embedder->Embed(*image_frame_buffer, roi));
++                               embedder->Embed(*image_frame_buffer, roi));
+   ImageDataFree(&image);
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+-                       embedder->Embed(*crop_frame_buffer));
++                               embedder->Embed(*crop_frame_buffer));
+   ImageDataFree(&crop);
+ 
+   // Check results sizes
+@@ -414,9 +415,9 @@ TEST(EmbedTest, SucceedsWithRegionOfInterest) {
+       crop_result.embeddings(0).feature_vector();
+   EXPECT_EQ(crop_feature_vector.value_float_size(), 1024);
+   // Check cosine similarity.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(double similarity,
+-                       ImageEmbedder::CosineSimilarity(image_feature_vector,
+-                                                       crop_feature_vector));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
++                                                         crop_feature_vector));
+   double expected_similarity = 0.999914;
+   EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+ }
+@@ -424,10 +425,10 @@ TEST(EmbedTest, SucceedsWithRegionOfInterest) {
+ TEST(GetEmbeddingDimension, Succeeds) {
+   // Create embedder.
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+-                       ImageEmbedder::CreateFromOptions(options));
++                               ImageEmbedder::CreateFromOptions(options));
+ 
+   EXPECT_EQ(embedder->GetEmbeddingDimension(0), 1024);
+   EXPECT_EQ(embedder->GetEmbeddingDimension(1), -1);
+@@ -436,10 +437,10 @@ TEST(GetEmbeddingDimension, Succeeds) {
+ TEST(GetNumberOfOutputLayers, Succeeds) {
+   // Create embedder.
+   ImageEmbedderOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+-                       ImageEmbedder::CreateFromOptions(options));
++                               ImageEmbedder::CreateFromOptions(options));
+ 
+   EXPECT_EQ(embedder->GetNumberOfOutputLayers(), 1);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc
+index 3aab0bbee48ef..dc768a43a8726 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc
+@@ -17,9 +17,9 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
++#include "absl/flags/flag.h"     // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/cord.h"  // from @com_google_absl
++#include "absl/strings/cord.h"   // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+ #include "tensorflow/lite/kernels/builtin_op_kernels.h"
+@@ -99,8 +99,8 @@ constexpr float kGoldenMaskTolerance = 1e-2;
+ constexpr int kGoldenMaskMagnificationFactor = 10;
+ 
+ StatusOr<ImageData> LoadImage(std::string image_name) {
+-  return DecodeImageFromFile(JoinPath("./" /*test src dir*/,
+-                                      kTestDataDirectory, image_name));
++  return DecodeImageFromFile(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+ }
+ 
+ // Checks that the two provided `Segmentation` protos are equal.
+@@ -141,8 +141,8 @@ class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+ 
+ TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+ 
+   SUPPORT_ASSERT_OK(ImageSegmenter::CreateFromOptions(
+       options, absl::make_unique<DeepLabOpResolver>()));
+@@ -160,8 +160,8 @@ class DeepLabOpResolverMissingOps : public ::tflite::MutableOpResolver {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+ 
+   auto image_segmenter_or = ImageSegmenter::CreateFromOptions(
+       options, absl::make_unique<DeepLabOpResolverMissingOps>());
+@@ -177,10 +177,10 @@ TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithTwoModelSources) {
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+ 
+   StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
+       ImageSegmenter::CreateFromOptions(options);
+@@ -212,8 +212,8 @@ TEST_F(CreateFromOptionsTest, FailsWithMissingModel) {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithUnspecifiedOutputType) {
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   options.set_output_type(ImageSegmenterOptions::UNSPECIFIED);
+ 
+   auto image_segmenter_or = ImageSegmenter::CreateFromOptions(options);
+@@ -230,8 +230,8 @@ TEST_F(CreateFromOptionsTest, FailsWithUnspecifiedOutputType) {
+ TEST_F(CreateFromOptionsTest, SucceedsWithNumberOfThreads) {
+   ImageSegmenterOptions options;
+   options.set_num_threads(4);
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+ 
+   SUPPORT_ASSERT_OK(ImageSegmenter::CreateFromOptions(options));
+ }
+@@ -243,8 +243,8 @@ INSTANTIATE_TEST_SUITE_P(Default, NumThreadsTest, testing::Values(0, -2));
+ TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+   ImageSegmenterOptions options;
+   options.set_num_threads(GetParam());
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+ 
+   StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
+       ImageSegmenter::CreateFromOptions(options);
+@@ -263,21 +263,21 @@ TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+ TEST(SegmentTest, SucceedsWithCategoryMask) {
+   // Load input and build frame buffer.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+-                       LoadImage("segmentation_input_rotation0.jpg"));
++                               LoadImage("segmentation_input_rotation0.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+   // Load golden mask output.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData golden_mask,
+-                       LoadImage("segmentation_golden_rotation0.png"));
++                               LoadImage("segmentation_golden_rotation0.png"));
+ 
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> image_segmenter,
+-                       ImageSegmenter::CreateFromOptions(options));
++                               ImageSegmenter::CreateFromOptions(options));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const SegmentationResult result,
+-                       image_segmenter->Segment(*frame_buffer));
++                               image_segmenter->Segment(*frame_buffer));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+@@ -301,23 +301,24 @@ TEST(SegmentTest, SucceedsWithCategoryMask) {
+ 
+ TEST(SegmentTest, SucceedsWithOrientation) {
+   // Load input and build frame buffer with kRightBottom orientation.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+-                       LoadImage("segmentation_input_rotation90_flop.jpg"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      ImageData rgb_image, LoadImage("segmentation_input_rotation90_flop.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height},
+       FrameBuffer::Orientation::kRightBottom);
+   // Load golden mask output.
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData golden_mask,
+-                       LoadImage("segmentation_golden_rotation90_flop.png"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      ImageData golden_mask,
++      LoadImage("segmentation_golden_rotation90_flop.png"));
+ 
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> image_segmenter,
+-                       ImageSegmenter::CreateFromOptions(options));
++                               ImageSegmenter::CreateFromOptions(options));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const SegmentationResult result,
+-                       image_segmenter->Segment(*frame_buffer));
++                               image_segmenter->Segment(*frame_buffer));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+@@ -341,21 +342,21 @@ TEST(SegmentTest, SucceedsWithOrientation) {
+ TEST(SegmentTest, SucceedsWithBaseOptions) {
+   // Load input and build frame buffer.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+-                       LoadImage("segmentation_input_rotation0.jpg"));
++                               LoadImage("segmentation_input_rotation0.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+   // Load golden mask output.
+   SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData golden_mask,
+-                       LoadImage("segmentation_golden_rotation0.png"));
++                               LoadImage("segmentation_golden_rotation0.png"));
+ 
+   ImageSegmenterOptions options;
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> image_segmenter,
+-                       ImageSegmenter::CreateFromOptions(options));
++                               ImageSegmenter::CreateFromOptions(options));
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const SegmentationResult result,
+-                       image_segmenter->Segment(*frame_buffer));
++                               image_segmenter->Segment(*frame_buffer));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+@@ -461,18 +462,18 @@ class PostprocessTest : public tflite_shims::testing::Test {
+ 
+ TEST_F(PostprocessTest, SucceedsWithCategoryMask) {
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   std::unique_ptr<FrameBuffer> frame_buffer =
+       CreateFromRgbaRawBuffer(/*input=*/nullptr, {});
+ 
+   SetUp(options);
+   ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+-                       FillAndGetOutputTensor());
++                               FillAndGetOutputTensor());
+   SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+-                       test_image_segmenter_->Postprocess(
+-                           {output_tensor}, *frame_buffer, /*roi=*/{}));
++                               test_image_segmenter_->Postprocess(
++                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+@@ -487,8 +488,8 @@ TEST_F(PostprocessTest, SucceedsWithCategoryMask) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithCategoryMaskAndOrientation) {
+   ImageSegmenterOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   // Frame buffer with kRightBottom orientation.
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbaRawBuffer(
+       /*input=*/nullptr, {}, FrameBuffer::Orientation::kRightBottom);
+@@ -496,10 +497,10 @@ TEST_F(PostprocessTest, SucceedsWithCategoryMaskAndOrientation) {
+   SetUp(options);
+   ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+-                       FillAndGetOutputTensor());
++                               FillAndGetOutputTensor());
+   SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+-                       test_image_segmenter_->Postprocess(
+-                           {output_tensor}, *frame_buffer, /*roi=*/{}));
++                               test_image_segmenter_->Postprocess(
++                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+@@ -515,18 +516,18 @@ TEST_F(PostprocessTest, SucceedsWithCategoryMaskAndOrientation) {
+ TEST_F(PostprocessTest, SucceedsWithConfidenceMask) {
+   ImageSegmenterOptions options;
+   options.set_output_type(ImageSegmenterOptions::CONFIDENCE_MASK);
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   std::unique_ptr<FrameBuffer> frame_buffer =
+       CreateFromRgbaRawBuffer(/*input=*/nullptr, {});
+ 
+   SetUp(options);
+   ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+-                       FillAndGetOutputTensor());
++                               FillAndGetOutputTensor());
+   SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+-                       test_image_segmenter_->Postprocess(
+-                           {output_tensor}, *frame_buffer, /*roi=*/{}));
++                               test_image_segmenter_->Postprocess(
++                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+@@ -547,8 +548,8 @@ TEST_F(PostprocessTest, SucceedsWithConfidenceMask) {
+ TEST_F(PostprocessTest, SucceedsWithConfidenceMaskAndOrientation) {
+   ImageSegmenterOptions options;
+   options.set_output_type(ImageSegmenterOptions::CONFIDENCE_MASK);
+-  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+-      "./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
++  options.mutable_model_file_with_metadata()->set_file_name(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+   // Frame buffer with kRightBottom orientation.
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbaRawBuffer(
+       /*input=*/nullptr, {}, FrameBuffer::Orientation::kRightBottom);
+@@ -556,10 +557,10 @@ TEST_F(PostprocessTest, SucceedsWithConfidenceMaskAndOrientation) {
+   SetUp(options);
+   ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+-                       FillAndGetOutputTensor());
++                               FillAndGetOutputTensor());
+   SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+-                       test_image_segmenter_->Postprocess(
+-                           {output_tensor}, *frame_buffer, /*roi=*/{}));
++                               test_image_segmenter_->Postprocess(
++                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+ 
+   EXPECT_EQ(result.segmentation_size(), 1);
+   const Segmentation& segmentation = result.segmentation(0);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc
+index ef1f6509080ed..4a33e4b479354 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc
+@@ -17,9 +17,9 @@ limitations under the License.
+ 
+ #include <memory>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
++#include "absl/flags/flag.h"     // from @com_google_absl
+ #include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/cord.h"  // from @com_google_absl
++#include "absl/strings/cord.h"   // from @com_google_absl
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+ #include "tensorflow/lite/kernels/builtin_op_kernels.h"
+@@ -103,8 +103,8 @@ constexpr char kEfficientDetWithMetadata[] =
+     "coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite";
+ 
+ StatusOr<ImageData> LoadImage(std::string image_name) {
+-  return DecodeImageFromFile(JoinPath("./" /*test src dir*/,
+-                                      kTestDataDirectory, image_name));
++  return DecodeImageFromFile(
++      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+ }
+ 
+ // Checks that the two provided `DetectionResult` protos are equal, with a
+@@ -153,9 +153,8 @@ class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+ 
+ TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   SUPPORT_ASSERT_OK(ObjectDetector::CreateFromOptions(
+       options, absl::make_unique<MobileSsdQuantizedOpResolver>()));
+@@ -186,9 +185,8 @@ class MobileSsdQuantizedOpResolverMissingOps
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   auto object_detector_or = ObjectDetector::CreateFromOptions(
+       options, absl::make_unique<MobileSsdQuantizedOpResolverMissingOps>());
+@@ -203,12 +201,10 @@ TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithTwoModelSources) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+       ObjectDetector::CreateFromOptions(options);
+@@ -241,9 +237,8 @@ TEST_F(CreateFromOptionsTest, FailsWithMissingModel) {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithInvalidMaxResults) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.set_max_results(0);
+ 
+   StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+@@ -260,9 +255,8 @@ TEST_F(CreateFromOptionsTest, FailsWithInvalidMaxResults) {
+ 
+ TEST_F(CreateFromOptionsTest, FailsWithCombinedWhitelistAndBlacklist) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.add_class_name_whitelist("foo");
+   options.add_class_name_blacklist("bar");
+ 
+@@ -281,9 +275,8 @@ TEST_F(CreateFromOptionsTest, FailsWithCombinedWhitelistAndBlacklist) {
+ TEST_F(CreateFromOptionsTest, SucceedsWithNumberOfThreads) {
+   ObjectDetectorOptions options;
+   options.set_num_threads(4);
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   SUPPORT_ASSERT_OK(ObjectDetector::CreateFromOptions(options));
+ }
+@@ -295,9 +288,8 @@ INSTANTIATE_TEST_SUITE_P(Default, NumThreadsTest, testing::Values(0, -2));
+ TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+   ObjectDetectorOptions options;
+   options.set_num_threads(GetParam());
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+       ObjectDetector::CreateFromOptions(options);
+@@ -315,51 +307,52 @@ TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+ class DetectTest : public tflite_shims::testing::Test {};
+ 
+ TEST_F(DetectTest, Succeeds) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("cats_and_dogs.jpg"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
++                               LoadImage("cats_and_dogs.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+ 
+   ObjectDetectorOptions options;
+   options.set_max_results(4);
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
+-                       ObjectDetector::CreateFromOptions(options));
++                               ObjectDetector::CreateFromOptions(options));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const DetectionResult result,
+-                       object_detector->Detect(*frame_buffer));
++                               object_detector->Detect(*frame_buffer));
+   ImageDataFree(&rgb_image);
+   ExpectApproximatelyEqual(
+       result, ParseTextProtoOrDie<DetectionResult>(kExpectResults));
+ }
+ 
+ TEST_F(DetectTest, SucceedswithBaseOptions) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("cats_and_dogs.jpg"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
++                               LoadImage("cats_and_dogs.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+ 
+   ObjectDetectorOptions options;
+   options.set_max_results(4);
+-  options.mutable_base_options()->mutable_model_file()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
+-                       ObjectDetector::CreateFromOptions(options));
++                               ObjectDetector::CreateFromOptions(options));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const DetectionResult result,
+-                       object_detector->Detect(*frame_buffer));
++                               object_detector->Detect(*frame_buffer));
+   ImageDataFree(&rgb_image);
+   ExpectApproximatelyEqual(
+       result, ParseTextProtoOrDie<DetectionResult>(kExpectResults));
+ }
+ 
+ TEST_F(DetectTest, SucceedswithScoreCalibrations) {
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("cats_and_dogs.jpg"));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
++                               LoadImage("cats_and_dogs.jpg"));
+   std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+       rgb_image.pixel_data,
+       FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+@@ -371,10 +364,10 @@ TEST_F(DetectTest, SucceedswithScoreCalibrations) {
+                kMobileSsdWithMetadataDummyScoreCalibration));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
+-                       ObjectDetector::CreateFromOptions(options));
++                               ObjectDetector::CreateFromOptions(options));
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(const DetectionResult result,
+-                       object_detector->Detect(*frame_buffer));
++                               object_detector->Detect(*frame_buffer));
+   ImageDataFree(&rgb_image);
+   ExpectApproximatelyEqual(
+       result, ParseTextProtoOrDie<DetectionResult>(kExpectResults));
+@@ -482,20 +475,21 @@ class PostprocessTest : public tflite_shims::testing::Test {
+ 
+ TEST_F(PostprocessTest, SucceedsWithScoreThresholdOption) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.set_score_threshold(0.5);
+ 
+   SetUp(options);
+   ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(const std::vector<const TfLiteTensor*> output_tensors,
+-                       FillAndGetOutputTensors());
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      const std::vector<const TfLiteTensor*> output_tensors,
++      FillAndGetOutputTensors());
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(DetectionResult result,
+-                       test_object_detector_->Postprocess(
+-                           output_tensors, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      DetectionResult result,
++      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
++                                         /*roi=*/{}));
+ 
+   ExpectApproximatelyEqual(
+       result,
+@@ -517,16 +511,16 @@ TEST_F(PostprocessTest, SucceedsWithFrameBufferOrientation) {
+                              FrameBuffer::Orientation::kBottomRight);
+ 
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.set_score_threshold(0.5);
+ 
+   SetUp(options);
+   ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(const std::vector<const TfLiteTensor*> output_tensors,
+-                       FillAndGetOutputTensors());
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      const std::vector<const TfLiteTensor*> output_tensors,
++      FillAndGetOutputTensors());
+ 
+   SUPPORT_ASSERT_OK_AND_ASSIGN(
+       DetectionResult result,
+@@ -549,20 +543,21 @@ TEST_F(PostprocessTest, SucceedsWithFrameBufferOrientation) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.set_max_results(1);
+ 
+   SetUp(options);
+   ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(const std::vector<const TfLiteTensor*> output_tensors,
+-                       FillAndGetOutputTensors());
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      const std::vector<const TfLiteTensor*> output_tensors,
++      FillAndGetOutputTensors());
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(DetectionResult result,
+-                       test_object_detector_->Postprocess(
+-                           output_tensors, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      DetectionResult result,
++      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
++                                         /*roi=*/{}));
+ 
+   ExpectApproximatelyEqual(
+       result,
+@@ -576,21 +571,22 @@ TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.add_class_name_whitelist("car");
+   options.add_class_name_whitelist("motorcycle");
+ 
+   SetUp(options);
+   ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(const std::vector<const TfLiteTensor*> output_tensors,
+-                       FillAndGetOutputTensors());
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      const std::vector<const TfLiteTensor*> output_tensors,
++      FillAndGetOutputTensors());
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(DetectionResult result,
+-                       test_object_detector_->Postprocess(
+-                           output_tensors, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      DetectionResult result,
++      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
++                                         /*roi=*/{}));
+ 
+   ExpectApproximatelyEqual(
+       result,
+@@ -608,9 +604,8 @@ TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+ 
+ TEST_F(PostprocessTest, SucceedsWithBlacklistOption) {
+   ObjectDetectorOptions options;
+-  options.mutable_model_file_with_metadata()->set_file_name(
+-      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+-               kMobileSsdWithMetadata));
++  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
++      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+   options.add_class_name_blacklist("car");
+   // Setting score threshold to discard the 7 padded-with-zeros results.
+   options.set_score_threshold(0.1);
+@@ -618,12 +613,14 @@ TEST_F(PostprocessTest, SucceedsWithBlacklistOption) {
+   SetUp(options);
+   ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(const std::vector<const TfLiteTensor*> output_tensors,
+-                       FillAndGetOutputTensors());
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      const std::vector<const TfLiteTensor*> output_tensors,
++      FillAndGetOutputTensors());
+ 
+-  SUPPORT_ASSERT_OK_AND_ASSIGN(DetectionResult result,
+-                       test_object_detector_->Postprocess(
+-                           output_tensors, *dummy_frame_buffer_, /*roi=*/{}));
++  SUPPORT_ASSERT_OK_AND_ASSIGN(
++      DetectionResult result,
++      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
++                                         /*roi=*/{}));
+ 
+   ExpectApproximatelyEqual(
+       result,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc
+index 7937dbafb090b..c16815cb38061 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc
+@@ -21,13 +21,16 @@ namespace tflite {
+ namespace task {
+ 
+ std::string JoinPath(absl::string_view path1, absl::string_view path2) {
+-  if (path1.empty()) return std::string(path2);
+-  if (path2.empty()) return std::string(path1);
++  if (path1.empty())
++    return std::string(path2);
++  if (path2.empty())
++    return std::string(path1);
+   if (path1.back() == '/') {
+     if (path2.front() == '/')
+       return absl::StrCat(path1, absl::ClippedSubstr(path2, 1));
+   } else {
+-    if (path2.front() != '/') return absl::StrCat(path1, "/", path2);
++    if (path2.front() != '/')
++      return absl::StrCat(path1, "/", path2);
+   }
+   return absl::StrCat(path1, path2);
+ }
+@@ -44,14 +47,16 @@ std::string JoinPathImpl(bool honor_abs,
+     // This size calculation is worst-case: it assumes one extra "/" for every
+     // path other than the first.
+     size_t total_size = paths.size() - 1;
+-    for (const absl::string_view path : paths) total_size += path.size();
++    for (const absl::string_view path : paths)
++      total_size += path.size();
+     result.resize(total_size);
+ 
+     auto begin = result.begin();
+     auto out = begin;
+     bool trailing_slash = false;
+     for (absl::string_view path : paths) {
+-      if (path.empty()) continue;
++      if (path.empty())
++        continue;
+       if (path.front() == '/') {
+         if (honor_abs) {
+           out = begin;  // wipe out whatever we've built up so far.
+@@ -59,7 +64,8 @@ std::string JoinPathImpl(bool honor_abs,
+           path.remove_prefix(1);
+         }
+       } else {
+-        if (!trailing_slash && out != begin) *out++ = '/';
++        if (!trailing_slash && out != begin)
++          *out++ = '/';
+       }
+       const size_t this_size = path.size();
+       memcpy(&*out, path.data(), this_size);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h
+index db72bc5d5ae98..1d730d5a6d981 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h
+@@ -33,8 +33,10 @@ std::string JoinPathImpl(bool honor_abs,
+ std::string JoinPath(absl::string_view path1, absl::string_view path2);
+ 
+ template <typename... T>
+-inline std::string JoinPath(absl::string_view path1, absl::string_view path2,
+-                            absl::string_view path3, const T&... args) {
++inline std::string JoinPath(absl::string_view path1,
++                            absl::string_view path2,
++                            absl::string_view path3,
++                            const T&... args) {
+   return internal::JoinPathImpl(false, {path1, path2, path3, args...});
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc
+index 6a050668edcbe..53c88310dde43 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc
+@@ -31,7 +31,8 @@ FlatHashMapBackedWordpiece::FlatHashMapBackedWordpiece(
+ }
+ 
+ tensorflow::text::LookupStatus FlatHashMapBackedWordpiece::Contains(
+-    absl::string_view key, bool* value) const {
++    absl::string_view key,
++    bool* value) const {
+   *value = index_map_.contains(key);
+   return tensorflow::text::LookupStatus();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h
+index aec178daf3cc5..1de54fa8f651c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h
+@@ -103,7 +103,8 @@ class BertTokenizer : public tflite::support::text::tokenizer::Tokenizer {
+ 
+   // Initialize the tokenizer from buffer and size of vocab and tokenizer
+   // configs.
+-  BertTokenizer(const char* vocab_buffer_data, size_t vocab_buffer_size,
++  BertTokenizer(const char* vocab_buffer_data,
++                size_t vocab_buffer_size,
+                 const BertTokenizerOptions& options = {})
+       : BertTokenizer(
+             utils::LoadVocabFromBuffer(vocab_buffer_data, vocab_buffer_size),
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc
+index 151161777863f..249bc2d1b6bc2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc
+@@ -31,9 +31,14 @@ using ::tflite::support::utils::StringListToVector;
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_BertTokenizer_nativeLoadResource(  // NOLINT
+-    JNIEnv* env, jobject thiz, jobject vocab_list, jint max_bytes_per_token,
+-    jint max_chars_per_sub_token, jstring jsuffix_indicator,
+-    jboolean use_unknown_token, jstring junknown_token,
++    JNIEnv* env,
++    jobject thiz,
++    jobject vocab_list,
++    jint max_bytes_per_token,
++    jint max_chars_per_sub_token,
++    jstring jsuffix_indicator,
++    jboolean use_unknown_token,
++    jstring junknown_token,
+     jboolean split_unknown_chars) {
+   // Convert java.util.List<String> into std::vector<string>
+   std::vector<std::string> vocab = StringListToVector(env, vocab_list);
+@@ -66,20 +71,28 @@ Java_org_tensorflow_lite_support_text_tokenizers_BertTokenizer_nativeLoadResourc
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_BertTokenizer_nativeUnloadResource(  // NOLINT
+-    JNIEnv* env, jobject thiz, jlong handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong handle) {
+   delete reinterpret_cast<BertTokenizer*>(handle);
+   return 0;
+ }
+ 
+ extern "C" JNIEXPORT jobjectArray JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_BertTokenizer_nativeTokenize(
+-    JNIEnv* env, jobject thiz, jlong handle, jstring jtext) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong handle,
++    jstring jtext) {
+   return nativeTokenize(env, handle, jtext);
+ }
+ 
+ extern "C" JNIEXPORT jintArray JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_BertTokenizer_nativeConvertTokensToIds(  // NOLINT
+-    JNIEnv* env, jobject thiz, jlong handle, jobjectArray jtokens) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong handle,
++    jobjectArray jtokens) {
+   return nativeConvertTokensToIds(env, handle, jtokens);
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
+index 832f9df42f824..ded6fbd13ea4a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
+@@ -17,7 +17,7 @@ limitations under the License.
+ 
+ #include <iostream>
+ 
+-#include "absl/strings/str_cat.h"  // from @com_google_absl
++#include "absl/strings/str_cat.h"     // from @com_google_absl
+ #include "absl/strings/substitute.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/utils/common_utils.h"
+ namespace tflite {
+@@ -70,7 +70,7 @@ TokenizerResult RegexTokenizer::Tokenize(const std::string& input) {
+   re2::StringPiece extracted_delim_token;
+   while (RE2::FindAndConsume(&leftover, delim_re_, &extracted_delim_token)) {
+     re2::StringPiece token(last_end.data(),
+-                            extracted_delim_token.data() - last_end.data());
++                           extracted_delim_token.data() - last_end.data());
+     bool has_non_empty_token = token.length() > 0;
+ 
+     last_end = leftover;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc
+index 6ecfff0d2baa1..8ca14c52eb262 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc
+@@ -20,7 +20,7 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
++#include "absl/memory/memory.h"      // from @com_google_absl
+ #include "absl/strings/str_split.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h"
+ #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h"
+@@ -34,7 +34,9 @@ using ::tflite::support::utils::GetMappedFileBuffer;
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_SentencePieceTokenizer_nativeLoadResource(  // NOLINT
+-    JNIEnv* env, jobject obj, jobject model_buffer) {
++    JNIEnv* env,
++    jobject obj,
++    jobject model_buffer) {
+   auto model = GetMappedFileBuffer(env, model_buffer);
+   auto handle =
+       absl::make_unique<SentencePieceTokenizer>(model.data(), model.size());
+@@ -43,20 +45,28 @@ Java_org_tensorflow_lite_support_text_tokenizers_SentencePieceTokenizer_nativeLo
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_SentencePieceTokenizer_nativeUnloadResource(  // NOLINT
+-    JNIEnv* env, jobject obj, jlong handle) {
++    JNIEnv* env,
++    jobject obj,
++    jlong handle) {
+   delete reinterpret_cast<SentencePieceTokenizer*>(handle);
+   return 0;
+ }
+ 
+ extern "C" JNIEXPORT jobjectArray JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_SentencePieceTokenizer_nativeTokenize(  // NOLINT
+-    JNIEnv* env, jobject thiz, jlong handle, jstring jtext) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong handle,
++    jstring jtext) {
+   return nativeTokenize(env, handle, jtext);
+ }
+ 
+ extern "C" JNIEXPORT jintArray JNICALL
+ Java_org_tensorflow_lite_support_text_tokenizers_SentencePieceTokenizer_nativeConvertTokensToIds(  // NOLINT
+-    JNIEnv* env, jobject thiz, jlong handle, jobjectArray jtokens) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong handle,
++    jobjectArray jtokens) {
+   return nativeConvertTokensToIds(env, handle, jtokens);
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.cc
+index a72523be5984e..4e32bc5581a48 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.cc
+@@ -54,7 +54,8 @@ jobjectArray nativeTokenize(JNIEnv* env, jlong handle, jstring jtext) {
+   return result;
+ }
+ 
+-jintArray nativeConvertTokensToIds(JNIEnv* env, jlong handle,
++jintArray nativeConvertTokensToIds(JNIEnv* env,
++                                   jlong handle,
+                                    jobjectArray jtokens) {
+   if (handle == 0) {
+     env->ThrowNew(env->FindClass(kIllegalStateException),
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
+index 33677d305a853..fd76f3aa553e4 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
+@@ -25,7 +25,8 @@ namespace support {
+ 
+ jobjectArray nativeTokenize(JNIEnv* env, jlong handle, jstring jtext);
+ 
+-jintArray nativeConvertTokensToIds(JNIEnv* env, jlong handle,
++jintArray nativeConvertTokensToIds(JNIEnv* env,
++                                   jlong handle,
+                                    jobjectArray jtokens);
+ 
+ }  // namespace support
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
+index 28f0137f54278..32957d155dce6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
+@@ -73,9 +73,9 @@ StatusOr<std::unique_ptr<Tokenizer>> CreateTokenizerFromProcessUnit(
+     }
+     case ProcessUnitOptions_SentencePieceTokenizerOptions: {
+       return CreateStatusWithPayload(
+-        absl::StatusCode::kInvalidArgument,
+-        "Chromium does not support sentencepiece tokenization",
+-        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
++          absl::StatusCode::kInvalidArgument,
++          "Chromium does not support sentencepiece tokenization",
++          TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+     }
+     case ProcessUnitOptions_RegexTokenizerOptions: {
+       const tflite::RegexTokenizerOptions* options =
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h
+index 2e50a79963f82..696c5d4e27db7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h
+@@ -26,7 +26,6 @@ namespace support {
+ namespace text {
+ namespace tokenizer {
+ 
+-
+ // Create a Tokenizer from model metadata by extracting
+ tflite::support::StatusOr<std::unique_ptr<Tokenizer>>
+ CreateTokenizerFromProcessUnit(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc
+index 84cc0ef6ae52e..3ea6b147fcdd6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc
+@@ -83,7 +83,8 @@ absl::node_hash_map<std::string, int> LoadVocabAndIndexFromFile(
+ }
+ 
+ absl::node_hash_map<std::string, int> LoadVocabAndIndexFromBuffer(
+-    const char* vocab_buffer_data, const size_t vocab_buffer_size) {
++    const char* vocab_buffer_data,
++    const size_t vocab_buffer_size) {
+   membuf sbuf(const_cast<char*>(vocab_buffer_data),
+               const_cast<char*>(vocab_buffer_data + vocab_buffer_size));
+   absl::node_hash_map<std::string, int> vocab_index_map;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h
+index 6921d2f5ac01b..275c4932f8ec0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h
+@@ -41,7 +41,8 @@ absl::node_hash_map<std::string, int> LoadVocabAndIndexFromFile(
+ // Read a vocab buffer with one vocabulary and its corresponding index on each
+ // line separated by space, create a map of <vocab, index>.
+ absl::node_hash_map<std::string, int> LoadVocabAndIndexFromBuffer(
+-    const char* vocab_buffer_data, const size_t vocab_buffer_size);
++    const char* vocab_buffer_data,
++    const size_t vocab_buffer_size);
+ }  // namespace utils
+ }  // namespace support
+ }  // namespace tflite
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc
+index bf9e93f9aa24a..35ce822951ad8 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc
+@@ -18,8 +18,8 @@ limitations under the License.
+ #include <dlfcn.h>
+ #include <string.h>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/memory/memory.h"       // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow/lite/core/shims/c/experimental/acceleration/configuration/delegate_plugin.h"
+ #include "tensorflow/lite/core/shims/cc/experimental/acceleration/configuration/delegate_registry.h"
+@@ -168,7 +168,8 @@ void ThrowException(JNIEnv* env, const char* clazz, const char* fmt, ...) {
+   va_end(args);
+ }
+ 
+-void ThrowExceptionWithMessage(JNIEnv* env, const char* clazz,
++void ThrowExceptionWithMessage(JNIEnv* env,
++                               const char* clazz,
+                                const char* message) {
+   jclass e_class = env->FindClass(clazz);
+   if (strcmp(clazz, kAssertionError) == 0) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h
+index 7f0674d3c9187..7caf49e479859 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h
+@@ -22,7 +22,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -57,7 +57,8 @@ T CheckNotNull(JNIEnv* env, T&& t) {
+ // Converts a std::vector<T> into a Java ArrayList using a converter, which
+ // processes a single element in the vector before adding it to the ArrayList.
+ template <typename T>
+-jobject ConvertVectorToArrayList(JNIEnv* env, const std::vector<T>& results,
++jobject ConvertVectorToArrayList(JNIEnv* env,
++                                 const std::vector<T>& results,
+                                  std::function<jobject(T)> converter) {
+   jclass array_list_class = env->FindClass("java/util/ArrayList");
+   jmethodID array_list_ctor =
+@@ -91,7 +92,8 @@ jbyteArray CreateByteArray(JNIEnv* env, const jbyte* data, int num_bytes);
+ 
+ void ThrowException(JNIEnv* env, const char* clazz, const char* fmt, ...);
+ 
+-void ThrowExceptionWithMessage(JNIEnv* env, const char* clazz,
++void ThrowExceptionWithMessage(JNIEnv* env,
++                               const char* clazz,
+                                const char* message);
+ 
+ const char* GetExceptionClassNameForStatusCode(absl::StatusCode status_code);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc b/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc
+index eb94cb7020475..bb8f1f4d40655 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc
+@@ -63,7 +63,8 @@ using details_android_java::TensorInfo;
+ // Using ctor and dtor to simulate an enter/exit schema like `with` in Python.
+ class AsBlock {
+  public:
+-  AsBlock(CodeWriter* code_writer, const std::string& before,
++  AsBlock(CodeWriter* code_writer,
++          const std::string& before,
+           bool trailing_blank_line = false)
+       : code_writer_(code_writer), trailing_blank_line_(trailing_blank_line) {
+     code_writer_->AppendNoNewLine(before);
+@@ -105,7 +106,9 @@ std::string GetModelVersionedName(const ModelMetadata* metadata) {
+ }
+ 
+ TensorInfo CreateTensorInfo(const TensorMetadata* metadata,
+-                            const std::string& name, bool is_input, int index,
++                            const std::string& name,
++                            bool is_input,
++                            int index,
+                             ErrorReporter* err) {
+   TensorInfo tensor_info;
+   std::string tensor_identifier = is_input ? "input" : "output";
+@@ -273,7 +276,8 @@ bool IsImageUsed(const ModelInfo& model) {
+ 
+ // The following functions generates the wrapper Java code for a model.
+ 
+-bool GenerateWrapperFileContent(CodeWriter* code_writer, const ModelInfo& model,
++bool GenerateWrapperFileContent(CodeWriter* code_writer,
++                                const ModelInfo& model,
+                                 ErrorReporter* err) {
+   code_writer->Append("// Generated by TFLite Support.");
+   code_writer->Append("package {{PACKAGE}};");
+@@ -291,7 +295,8 @@ bool GenerateWrapperFileContent(CodeWriter* code_writer, const ModelInfo& model,
+   return true;
+ }
+ 
+-bool GenerateWrapperImports(CodeWriter* code_writer, const ModelInfo& model,
++bool GenerateWrapperImports(CodeWriter* code_writer,
++                            const ModelInfo& model,
+                             ErrorReporter* err) {
+   const std::string support_pkg = "org.tensorflow.lite.support.";
+   std::vector<std::string> imports{
+@@ -336,7 +341,8 @@ bool GenerateWrapperImports(CodeWriter* code_writer, const ModelInfo& model,
+   return true;
+ }
+ 
+-bool GenerateWrapperClass(CodeWriter* code_writer, const ModelInfo& model,
++bool GenerateWrapperClass(CodeWriter* code_writer,
++                          const ModelInfo& model,
+                           ErrorReporter* err) {
+   code_writer->SetTokenValue("MODEL_VERSIONED_NAME",
+                              model.model_versioned_name);
+@@ -373,7 +379,8 @@ private static final String MODEL_NAME = "{{MODEL_PATH}}";)");
+   return true;
+ }
+ 
+-bool GenerateWrapperOutputs(CodeWriter* code_writer, const ModelInfo& model,
++bool GenerateWrapperOutputs(CodeWriter* code_writer,
++                            const ModelInfo& model,
+                             ErrorReporter* err) {
+   code_writer->Append("/** Output wrapper of {@link {{MODEL_CLASS_NAME}}} */");
+   auto class_block = AsBlock(code_writer, "public static class Outputs");
+@@ -459,7 +466,8 @@ bool GenerateWrapperOutputs(CodeWriter* code_writer, const ModelInfo& model,
+   return true;
+ }
+ 
+-bool GenerateWrapperMetadata(CodeWriter* code_writer, const ModelInfo& model,
++bool GenerateWrapperMetadata(CodeWriter* code_writer,
++                             const ModelInfo& model,
+                              ErrorReporter* err) {
+   code_writer->Append(
+       "/** Metadata accessors of {@link {{MODEL_CLASS_NAME}}} */");
+@@ -605,7 +613,8 @@ public List<String> get{{NAME_U}}Labels() {
+   return true;
+ }
+ 
+-bool GenerateWrapperAPI(CodeWriter* code_writer, const ModelInfo& model,
++bool GenerateWrapperAPI(CodeWriter* code_writer,
++                        const ModelInfo& model,
+                         ErrorReporter* err) {
+   code_writer->Append(R"(public Metadata getMetadata() {
+   return metadata;
+@@ -980,8 +989,10 @@ AndroidJavaGenerator::AndroidJavaGenerator(const std::string& module_root)
+     : CodeGenerator(), module_root_(module_root) {}
+ 
+ GenerationResult AndroidJavaGenerator::Generate(
+-    const Model* model, const std::string& package_name,
+-    const std::string& model_class_name, const std::string& model_asset_path) {
++    const Model* model,
++    const std::string& package_name,
++    const std::string& model_class_name,
++    const std::string& model_asset_path) {
+   GenerationResult result;
+   if (model == nullptr) {
+     err_.Error(
+@@ -1006,8 +1017,10 @@ GenerationResult AndroidJavaGenerator::Generate(
+ }
+ 
+ GenerationResult AndroidJavaGenerator::Generate(
+-    const char* model_storage, const std::string& package_name,
+-    const std::string& model_class_name, const std::string& model_asset_path) {
++    const char* model_storage,
++    const std::string& package_name,
++    const std::string& model_class_name,
++    const std::string& model_asset_path) {
+   const Model* model = GetModel(model_storage);
+   return Generate(model, package_name, model_class_name, model_asset_path);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.h b/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.h
+index 634ccf69f6c1a..1ea8bb2182a67 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.h
+@@ -20,10 +20,10 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
++#include "tensorflow/lite/schema/schema_generated.h"
+ #include "tensorflow_lite_support/codegen/code_generator.h"
+ #include "tensorflow_lite_support/codegen/utils.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+-#include "tensorflow/lite/schema/schema_generated.h"
+ 
+ namespace tflite {
+ namespace support {
+@@ -90,7 +90,8 @@ class AndroidJavaGenerator : public CodeGenerator {
+   /// as "ImageClassifier", "MobileNetV2" or "MyModel".
+   /// - model_asset_path: The relevant path to the model file in the asset.
+   // TODO(b/141225157): Automatically generate model_class_name.
+-  GenerationResult Generate(const Model* model, const std::string& package_name,
++  GenerationResult Generate(const Model* model,
++                            const std::string& package_name,
+                             const std::string& model_class_name,
+                             const std::string& model_asset_path);
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.cc b/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.cc
+index 1337708d4ac66..b6ec55cbc5e8b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.cc
+@@ -144,7 +144,8 @@ std::string CodeGenerator::NameTensor(const TensorMetadata& tensor,
+ }
+ 
+ void CodeGenerator::ResolveConflictedInputAndOutputNames(
+-    std::vector<std::string>* inputs, std::vector<std::string>* outputs) {
++    std::vector<std::string>* inputs,
++    std::vector<std::string>* outputs) {
+   std::unordered_set<std::string> io_conflict;
+   auto& input_names = *inputs;
+   auto& output_names = *outputs;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.h b/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.h
+index b557773ddcc7a..fe67327986bd7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator.h
+@@ -70,7 +70,8 @@ class CodeGenerator {
+   static std::string NameTensor(const TensorMetadata& tensor,
+                                 const std::string& default_name);
+   static void ResolveConflictedInputAndOutputNames(
+-      std::vector<std::string>* input, std::vector<std::string>* output);
++      std::vector<std::string>* input,
++      std::vector<std::string>* output);
+ };
+ 
+ }  // namespace codegen
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator_test.cc
+index 5e9d64a0d8f98..ccc87668ed3cb 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/code_generator_test.cc
+@@ -36,7 +36,8 @@ class CodeGeneratorTest : public ::testing::Test {
+       return CodeGenerator::ConvertToValidName(name);
+     }
+     static void ResolveConflictedInputAndOutputNames(
+-        std::vector<std::string>* input, std::vector<std::string>* output) {
++        std::vector<std::string>* input,
++        std::vector<std::string>* output) {
+       CodeGenerator::ResolveConflictedInputAndOutputNames(input, output);
+     }
+   };
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/metadata_helper.h b/third_party/tflite_support/src/tensorflow_lite_support/codegen/metadata_helper.h
+index 8e3dc6abaed66..193dfb2fb23f3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/metadata_helper.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/metadata_helper.h
+@@ -18,9 +18,9 @@ limitations under the License.
+ 
+ #include <string>
+ 
++#include "tensorflow/lite/schema/schema_generated.h"
+ #include "tensorflow_lite_support/codegen/utils.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+-#include "tensorflow/lite/schema/schema_generated.h"
+ 
+ namespace tflite {
+ namespace support {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/python/codegen_lib.cc b/third_party/tflite_support/src/tensorflow_lite_support/codegen/python/codegen_lib.cc
+index 6b2cd5ea9a778..a9da2403afc4f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/python/codegen_lib.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/python/codegen_lib.cc
+@@ -29,11 +29,10 @@ using overload_cast_ = pybind11::detail::overload_cast_impl<Args...>;
+ 
+ PYBIND11_MODULE(_pywrap_codegen, m) {
+   pybind11::class_<AndroidJavaGenerator>(m, "AndroidJavaGenerator")
+-      .def(pybind11::init<const std::string &>())
+-      .def("generate",
+-           overload_cast_<const char *, const std::string &,
+-                          const std::string &, const std::string &>()(
+-               &AndroidJavaGenerator::Generate))
++      .def(pybind11::init<const std::string&>())
++      .def("generate", overload_cast_<const char*, const std::string&,
++                                      const std::string&, const std::string&>()(
++                           &AndroidJavaGenerator::Generate))
+       .def("get_error_message", &AndroidJavaGenerator::GetErrorMessage);
+   pybind11::class_<GenerationResult>(m, "GenerationResult")
+       .def(pybind11::init<>())
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/codegen/utils.cc
+index c75fc5fae631d..e89d09629dda1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/utils.cc
+@@ -32,7 +32,8 @@ int ErrorReporter::Error(const char* format, ...) {
+   return Report("[ERROR] ", format, args);
+ }
+ 
+-int ErrorReporter::Report(const char* prefix, const char* format,
++int ErrorReporter::Report(const char* prefix,
++                          const char* format,
+                           va_list args) {
+   char buf[1024];
+   int formatted = vsnprintf(buf, sizeof(buf), format, args);
+@@ -69,9 +70,13 @@ void CodeWriter::SetIndentString(const std::string& indent_str) {
+   indent_str_ = indent_str;
+ }
+ 
+-void CodeWriter::Indent() { indent_++; }
++void CodeWriter::Indent() {
++  indent_++;
++}
+ 
+-void CodeWriter::Outdent() { indent_--; }
++void CodeWriter::Outdent() {
++  indent_--;
++}
+ 
+ std::string CodeWriter::GenerateIndent() const {
+   std::string res;
+@@ -82,7 +87,9 @@ std::string CodeWriter::GenerateIndent() const {
+   return res;
+ }
+ 
+-void CodeWriter::Append(const std::string& text) { AppendInternal(text, true); }
++void CodeWriter::Append(const std::string& text) {
++  AppendInternal(text, true);
++}
+ 
+ void CodeWriter::AppendNoNewLine(const std::string& text) {
+   AppendInternal(text, false);
+@@ -144,15 +151,21 @@ void CodeWriter::AppendInternal(const std::string& text, bool newline) {
+   }
+ }
+ 
+-void CodeWriter::NewLine() { Append(""); }
++void CodeWriter::NewLine() {
++  Append("");
++}
+ 
+ void CodeWriter::Backspace(int n) {
+   buffer_.resize(buffer_.size() > n ? buffer_.size() - n : 0);
+ }
+ 
+-std::string CodeWriter::ToString() const { return buffer_; }
++std::string CodeWriter::ToString() const {
++  return buffer_;
++}
+ 
+-bool CodeWriter::IsStreamEmpty() const { return buffer_.empty(); }
++bool CodeWriter::IsStreamEmpty() const {
++  return buffer_.empty();
++}
+ 
+ void CodeWriter::Clear() {
+   buffer_.clear();
+@@ -181,11 +194,14 @@ std::string SnakeCaseToCamelCase(const std::string& s) {
+ }
+ 
+ std::string JoinPath(const std::string& a, const std::string& b) {
+-  if (a.empty()) return b;
++  if (a.empty())
++    return b;
+   std::string a_fixed = a;
+-  if (!a_fixed.empty() && a_fixed.back() == '/') a_fixed.pop_back();
++  if (!a_fixed.empty() && a_fixed.back() == '/')
++    a_fixed.pop_back();
+   std::string b_fixed = b;
+-  if (!b_fixed.empty() && b_fixed.front() == '/') b_fixed.erase(0, 1);
++  if (!b_fixed.empty() && b_fixed.front() == '/')
++    b_fixed.erase(0, 1);
+   return a_fixed + "/" + b_fixed;
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams.cc
+index 3831c63ca17cc..f55ffb907f133 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams.cc
+@@ -66,7 +66,9 @@ struct NgramsAttributes {
+         string_separator(m["string_separator"].ToString()) {}
+ };
+ 
+-inline bool OutputIsTensor(TfLiteNode* node) { return NumOutputs(node) == 1; }
++inline bool OutputIsTensor(TfLiteNode* node) {
++  return NumOutputs(node) == 1;
++}
+ inline int NumRowSplits(TfLiteNode* node) {
+   return NumInputs(node) - kRowSplitsStart;
+ }
+@@ -176,7 +178,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+     std::vector<StringRef> tokens;
+     for (int j = input_row_splits[i]; j < input_row_splits[i + 1]; ++j) {
+       tokens.emplace_back(GetString(input_values, j));
+-      if (tokens.size() < attributes.width) continue;
++      if (tokens.size() < attributes.width)
++        continue;
+       tokens.erase(tokens.begin(),
+                    tokens.begin() + tokens.size() - attributes.width);
+       buffer.AddJoinedString(tokens, separator);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_op_resolver.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_op_resolver.cc
+index b87fcac328623..dc21f37beb3bf 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_op_resolver.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_op_resolver.cc
+@@ -15,8 +15,8 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/custom_ops/kernel/ngrams_op_resolver.h"
+ 
+-#include "tensorflow_lite_support/custom_ops/kernel/ngrams.h"
+ #include "tensorflow/lite/mutable_op_resolver.h"
++#include "tensorflow_lite_support/custom_ops/kernel/ngrams.h"
+ 
+ namespace tflite {
+ namespace ops {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.cc
+index 91ef47af6fd0f..4a5e671fa0987 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.cc
+@@ -40,7 +40,8 @@ using ::testing::ElementsAreArray;
+ class NgramsModel : public SingleOpModel {
+  public:
+   // Constructor for testing the op with a tf.Tensor
+-  NgramsModel(int width, const std::string& string_separator,
++  NgramsModel(int width,
++              const std::string& string_separator,
+               const std::vector<std::string>& input_values,
+               const std::vector<int>& input_shape) {
+     input_values_ = AddInput(TensorType_STRING);
+@@ -56,7 +57,8 @@ class NgramsModel : public SingleOpModel {
+   // Constructor for the op with a tf.RaggedTensor
+   // Note: This interface uses row_lengths, as they're closer to the
+   // dimensions in a TensorShape, but internally everything is row_splits.
+-  NgramsModel(int width, const std::string& string_separator,
++  NgramsModel(int width,
++              const std::string& string_separator,
+               const std::vector<std::string>& input_values,
+               const std::vector<std::vector<int64_t>> nested_row_lengths) {
+     std::vector<std::vector<int>> input_shapes;
+@@ -203,8 +205,7 @@ TEST(NgramsTest, TensorMultidimensionalInputWidthTwo) {
+ TEST(NgramsTest, RaggedTensorSingleSequenceWidthTwo) {
+   std::vector<std::vector<int64_t>> nested_row_lengths;
+   nested_row_lengths.push_back({4});
+-  NgramsModel m(2, " ", {"this", "is", "a", "test"},
+-                nested_row_lengths);
++  NgramsModel m(2, " ", {"this", "is", "a", "test"}, nested_row_lengths);
+   EXPECT_THAT(m.GetValuesTensorShape(), ElementsAre(3));
+   EXPECT_THAT(m.ExtractValuesTensorVector(),
+               ElementsAre("this is", "is a", "a test"));
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py_tflite_registerer.h b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py_tflite_registerer.h
+index ade3c5c178920..811be781d27fe 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py_tflite_registerer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py_tflite_registerer.h
+@@ -20,6 +20,6 @@ limitations under the License.
+ // C-function that is called from the Python Wrapper.
+ 
+ extern "C" void TFLite_RaggedTensorToTensorRegisterer(
+-    tflite::MutableOpResolver *resolver);
++    tflite::MutableOpResolver* resolver);
+ 
+ #endif  // TENSORFLOW_LITE_SUPPORT_CUSTOM_OPS_KERNEL_RAGGED_PY_TFLITE_REGISTERER_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite.cc
+index a35a6db9ad48f..9fc73dd0f9778 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite.cc
+@@ -71,9 +71,12 @@ TfLiteStatus EvalT(TfLiteContext* context, TfLiteNode* node) {
+   // nrows (number of output rows) is the size of the non-broadcast inputs,
+   // or 1 if all inputs are scalars.
+   std::vector<int> in_sizes;
+-  if (!broadcast_starts) in_sizes.push_back(input_starts.dims->data[0]);
+-  if (!broadcast_limits) in_sizes.push_back(input_limits.dims->data[0]);
+-  if (!broadcast_deltas) in_sizes.push_back(input_deltas.dims->data[0]);
++  if (!broadcast_starts)
++    in_sizes.push_back(input_starts.dims->data[0]);
++  if (!broadcast_limits)
++    in_sizes.push_back(input_limits.dims->data[0]);
++  if (!broadcast_deltas)
++    in_sizes.push_back(input_deltas.dims->data[0]);
+   if (std::adjacent_find(std::begin(in_sizes), std::end(in_sizes),
+                          std::not_equal_to<>()) != std::end(in_sizes)) {
+     context->ReportError(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite_test.cc
+index 54cf4459a27ed..87a047c512ea7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_range_tflite_test.cc
+@@ -39,7 +39,8 @@ class RaggedRangeOpModel : public SingleOpModel {
+  public:
+   static TensorType GetType();
+ 
+-  RaggedRangeOpModel(const std::vector<T>& start, const std::vector<T>& limits,
++  RaggedRangeOpModel(const std::vector<T>& start,
++                     const std::vector<T>& limits,
+                      const std::vector<T>& deltas) {
+     const TensorType value_type = GetType();
+     std::vector<std::vector<int>> shapes;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite.cc
+index 09ac76c71b26c..ff5c14b8e5e08 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite.cc
+@@ -140,8 +140,10 @@ RuntimeShape TensorShapeFromTensor(const TfLiteTensor& tensor) {
+ }
+ 
+ const TfLiteTensor* GetRowPartitionTensor(
+-    const ConversionAttributes& conversion_attributes, TfLiteContext* context,
+-    TfLiteNode* node, int dimension) {
++    const ConversionAttributes& conversion_attributes,
++    TfLiteContext* context,
++    TfLiteNode* node,
++    int dimension) {
+   if (conversion_attributes.partition_types.front() ==
+       tensorflow::RowPartitionType::FIRST_DIM_SIZE) {
+     return &context->tensors[node->inputs->data[kFirstPartitionInputIndex + 1 +
+@@ -211,7 +213,9 @@ int GetMaxWidthRowSplit(const TfLiteTensor* tensor) {
+ }
+ 
+ int GetMaxWidth(const ConversionAttributes& conversion_attributes,
+-                TfLiteContext* context, TfLiteNode* node, int dimension) {
++                TfLiteContext* context,
++                TfLiteNode* node,
++                int dimension) {
+   const TfLiteTensor* tensor = GetRowPartitionTensor(
+       conversion_attributes, context, node, dimension - 1);
+   switch (conversion_attributes.GetRowPartitionTypeByDimension(dimension - 1)) {
+@@ -226,7 +230,8 @@ int GetMaxWidth(const ConversionAttributes& conversion_attributes,
+ }
+ 
+ RuntimeShape CombineRaggedTensorToTensorShapes(
+-    int ragged_rank, const RuntimeShape& output_shape,
++    int ragged_rank,
++    const RuntimeShape& output_shape,
+     const RuntimeShape& value_shape) {
+   // TODO(mgubin): No checks, see
+   // third_party/tensorflow/core/ops/ragged_to_dense_util.cc
+@@ -247,9 +252,13 @@ RuntimeShape CombineRaggedTensorToTensorShapes(
+ }
+ 
+ RuntimeShape CalculateOutputSize(
+-    const ConversionAttributes& conversion_attributes, TfLiteContext* context,
+-    TfLiteNode* node, int first_dimension, int ragged_rank,
+-    const TfLiteTensor& values, const TfLiteTensor& default_value,
++    const ConversionAttributes& conversion_attributes,
++    TfLiteContext* context,
++    TfLiteNode* node,
++    int first_dimension,
++    int ragged_rank,
++    const TfLiteTensor& values,
++    const TfLiteTensor& default_value,
+     const TfLiteTensor& output_shape) {
+   RuntimeShape values_shape(values.dims->size, values.dims->data);
+   RuntimeShape default_value_shape(default_value.dims->size,
+@@ -331,7 +340,8 @@ void CalculateFirstParentOutputIndex(int first_dimension,
+ void CalculateOutputIndexValueRowID(const TfLiteTensor& value_rowids,
+                                     const std::vector<int>& parent_output_index,
+                                     int output_index_multiplier,
+-                                    int output_size, std::vector<int>* result) {
++                                    int output_size,
++                                    std::vector<int>* result) {
+   const RuntimeShape tensor_shape(value_rowids.dims->size,
+                                   value_rowids.dims->data);
+   const int index_size = tensor_shape.FlatSize();
+@@ -380,7 +390,8 @@ void CalculateOutputIndexValueRowID(const TfLiteTensor& value_rowids,
+ 
+ void CalculateOutputIndexRowSplit(const TfLiteTensor& row_split,
+                                   const std::vector<int>& parent_output_index,
+-                                  int output_index_multiplier, int output_size,
++                                  int output_index_multiplier,
++                                  int output_size,
+                                   std::vector<int>* result) {
+   const RuntimeShape row_split_shape(row_split.dims->size,
+                                      row_split.dims->data);
+@@ -421,10 +432,14 @@ void CalculateOutputIndexRowSplit(const TfLiteTensor& row_split,
+ }
+ 
+ TfLiteStatus CalculateOutputIndex(
+-    const ConversionAttributes& conversion_attributes, TfLiteContext* context,
+-    TfLiteNode* node, int dimension,
+-    const std::vector<int>& parent_output_index, int output_index_multiplier,
+-    int output_size, std::vector<int>* result) {
++    const ConversionAttributes& conversion_attributes,
++    TfLiteContext* context,
++    TfLiteNode* node,
++    int dimension,
++    const std::vector<int>& parent_output_index,
++    int output_index_multiplier,
++    int output_size,
++    std::vector<int>* result) {
+   const TfLiteTensor* row_partition_tensor =
+       GetRowPartitionTensor(conversion_attributes, context, node, dimension);
+   auto partition_type =
+@@ -447,7 +462,8 @@ TfLiteStatus CalculateOutputIndex(
+ }
+ 
+ template <typename VALUE_TYPE>
+-void SetOutputT(TfLiteContext* context, int ragged_rank,
++void SetOutputT(TfLiteContext* context,
++                int ragged_rank,
+                 const std::vector<int>& output_index,
+                 const TfLiteTensor& values_tensor,
+                 const TfLiteTensor& default_value_tensor,
+@@ -522,7 +538,8 @@ void SetOutputT(TfLiteContext* context, int ragged_rank,
+   }
+ }
+ 
+-void SetOutput(TfLiteContext* context, int ragged_rank,
++void SetOutput(TfLiteContext* context,
++               int ragged_rank,
+                const std::vector<int>& output_index,
+                const TfLiteTensor& values_tensor,
+                const TfLiteTensor& default_value_tensor,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite_test.cc
+index b1cde57c47c68..2f7a2a95b8478 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/ragged_tensor_to_tensor_tflite_test.cc
+@@ -82,7 +82,8 @@ class RaggedTensorToTensorOpModel : public SingleOpModel {
+   std::vector<int32> GetOutputInt() { return ExtractVector<int32>(output_); }
+ 
+   void InvokeFloat(const std::vector<int>& shape,
+-                   const std::vector<float>& values, float default_value,
++                   const std::vector<float>& values,
++                   float default_value,
+                    const std::vector<std::vector<int>>& partition_values) {
+     PopulateTensor(input_shape_, shape);
+     PopulateTensor(input_values_, values);
+@@ -93,7 +94,8 @@ class RaggedTensorToTensorOpModel : public SingleOpModel {
+     SingleOpModel::Invoke();
+   }
+   void InvokeInt(const std::vector<int>& shape,
+-                 const std::vector<int32>& values, int32 default_value,
++                 const std::vector<int32>& values,
++                 int32 default_value,
+                  const std::vector<std::vector<int>>& partition_values) {
+     PopulateTensor(input_shape_, shape);
+     PopulateTensor(input_values_, values);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc
+index 4e2b87de37327..47ba9fdfebcae 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc
+@@ -15,8 +15,8 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h"
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_replace.h"  // from @com_google_absl
++#include "absl/status/status.h"          // from @com_google_absl
++#include "absl/strings/str_replace.h"    // from @com_google_absl
+ #include "src/sentencepiece_model.pb.h"  // from @com_google_sentencepiece
+ #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/decoder_config_generated.h"
+ #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.h"
+@@ -48,7 +48,8 @@ DecodePrecompiledCharsmap(
+ }
+ 
+ tflite::support::StatusOr<std::string> ConvertSentencepieceModelToFlatBuffer(
+-    const std::string& model_config_str, int encoding_offset) {
++    const std::string& model_config_str,
++    int encoding_offset) {
+   ::sentencepiece::ModelProto model_config;
+   if (!model_config.ParseFromString(model_config_str)) {
+     return absl::InvalidArgumentError(
+@@ -128,7 +129,8 @@ tflite::support::StatusOr<std::string> ConvertSentencepieceModelToFlatBuffer(
+ 
+ tflite::support::StatusOr<std::string>
+ ConvertSentencepieceModelToFlatBufferForDecoder(
+-    const std::string& model_config_str, int encoding_offset) {
++    const std::string& model_config_str,
++    int encoding_offset) {
+   ::sentencepiece::ModelProto model_config;
+   if (!model_config.ParseFromString(model_config_str)) {
+     return absl::InvalidArgumentError(
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h
+index 5687b6287d140..03b3596820886 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h
+@@ -27,13 +27,15 @@ namespace sentencepiece {
+ // Converts Sentencepiece configuration to flatbuffer format.
+ // encoding_offset is used by some encoders that combine different encodings.
+ tflite::support::StatusOr<std::string> ConvertSentencepieceModelToFlatBuffer(
+-    const std::string& model_config_str, int encoding_offset = 0);
++    const std::string& model_config_str,
++    int encoding_offset = 0);
+ 
+ // Converts Sentencepiece configuration to flatbuffer format for encoder.
+ // encoding_offset is used by some encoders that combine different encodings.
+ tflite::support::StatusOr<std::string>
+ ConvertSentencepieceModelToFlatBufferForDecoder(
+-    const std::string& model_config_str, int encoding_offset = 0);
++    const std::string& model_config_str,
++    int encoding_offset = 0);
+ 
+ // The functions that are provided for the Python wrapper.
+ std::string ConvertSentencepieceModel(const std::string& model_string);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc
+index 8e130ef73b9b6..94161c2ac4c4e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc
+@@ -19,9 +19,9 @@ limitations under the License.
+ 
+ #include <gmock/gmock.h>
+ #include <gtest/gtest.h>
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "src/sentencepiece.pb.h"  // from @com_google_sentencepiece
++#include "absl/flags/flag.h"              // from @com_google_absl
++#include "absl/strings/str_format.h"      // from @com_google_absl
++#include "src/sentencepiece.pb.h"         // from @com_google_sentencepiece
+ #include "src/sentencepiece_processor.h"  // from @com_google_sentencepiece
+ #include "tensorflow/core/platform/env.h"
+ #include "tensorflow_lite_support/cc/test/test_utils.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc
+index 45fde32237c65..4148f8e96627a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc
+@@ -31,7 +31,8 @@ const char kSpaceSymbol[] = "\xe2\x96\x81";
+ 
+ template <typename processing_callback>
+ std::tuple<std::string, std::vector<int>> process_string(
+-    const std::string& input, const std::vector<int>& offsets,
++    const std::string& input,
++    const std::vector<int>& offsets,
+     const processing_callback& pc) {
+   std::string result_string;
+   result_string.reserve(input.size());
+@@ -78,7 +79,9 @@ std::tuple<int, utils::string_view> remove_extra_whitespaces(const char* data,
+ }
+ 
+ std::tuple<int, utils::string_view> find_replacement(
+-    const char* data, int len, const DoubleArrayTrie& dat,
++    const char* data,
++    int len,
++    const DoubleArrayTrie& dat,
+     const flatbuffers::Vector<int8_t>& replacements) {
+   const auto max_match = dat.LongestPrefixMatch(utils::string_view(data, len));
+   if (!max_match.empty()) {
+@@ -94,7 +97,8 @@ std::tuple<int, utils::string_view> find_replacement(
+ }  // namespace
+ 
+ std::tuple<std::string, std::vector<int>> NormalizeString(
+-    const std::string& in_string, const EncoderConfig& config) {
++    const std::string& in_string,
++    const EncoderConfig& config) {
+   std::vector<int> output_offsets;
+   std::string result = in_string;
+   output_offsets.reserve(in_string.length());
+@@ -145,8 +149,10 @@ std::tuple<std::string, std::vector<int>> NormalizeString(
+ 
+ EncoderResult EncodeNormalizedString(const std::string& str,
+                                      const std::vector<int>& offsets,
+-                                     const EncoderConfig& config, bool add_bos,
+-                                     bool add_eos, bool reverse) {
++                                     const EncoderConfig& config,
++                                     bool add_bos,
++                                     bool add_eos,
++                                     bool reverse) {
+   const DoubleArrayTrie piece_matcher(config.pieces()->nodes());
+   const flatbuffers::Vector<float>* piece_scores = config.pieces_scores();
+   const int unknown_code = config.unknown_code();
+@@ -219,8 +225,11 @@ EncoderResult EncodeNormalizedString(const std::string& str,
+   return result;
+ }
+ 
+-EncoderResult EncodeString(const std::string& string, const void* config_buffer,
+-                           bool add_bos, bool add_eos, bool reverse) {
++EncoderResult EncodeString(const std::string& string,
++                           const void* config_buffer,
++                           bool add_bos,
++                           bool add_eos,
++                           bool reverse) {
+   // Get the config from the buffer.
+   const EncoderConfig* config = GetEncoderConfig(config_buffer);
+   if (config->version() != EncoderVersion::EncoderVersion_SENTENCE_PIECE) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h
+index 44d6e88f2531c..b89154cbfa396 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h
+@@ -37,12 +37,16 @@ struct EncoderResult {
+   std::vector<int> offsets;
+ };
+ std::tuple<std::string, std::vector<int>> NormalizeString(
+-    const std::string& in_string, const EncoderConfig& config);
++    const std::string& in_string,
++    const EncoderConfig& config);
+ 
+ // Encodes one string and returns ids and offsets. Takes the configuration as a
+ // type-erased buffer.
+-EncoderResult EncodeString(const std::string& string, const void* config_buffer,
+-                           bool add_bos, bool add_eos, bool reverse);
++EncoderResult EncodeString(const std::string& string,
++                           const void* config_buffer,
++                           bool add_bos,
++                           bool add_eos,
++                           bool reverse);
+ 
+ }  // namespace sentencepiece
+ }  // namespace custom
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc
+index e2787c785e8c4..dd956a22b26c1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc
+@@ -19,10 +19,10 @@ limitations under the License.
+ 
+ #include <gmock/gmock.h>
+ #include <gtest/gtest.h>
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "src/sentencepiece.pb.h"  // from @com_google_sentencepiece
++#include "absl/flags/flag.h"              // from @com_google_absl
++#include "absl/status/status.h"           // from @com_google_absl
++#include "absl/strings/str_format.h"      // from @com_google_absl
++#include "src/sentencepiece.pb.h"         // from @com_google_sentencepiece
+ #include "src/sentencepiece_processor.h"  // from @com_google_sentencepiece
+ #include "tensorflow/core/platform/env.h"
+ #include "tensorflow_lite_support/cc/test/test_utils.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/py_tflite_registerer.h b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/py_tflite_registerer.h
+index deb4e4ee08dc2..3efcfefc6438d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/py_tflite_registerer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/py_tflite_registerer.h
+@@ -20,6 +20,6 @@ limitations under the License.
+ // C-function that is called from the Python Wrapper.
+ 
+ extern "C" void TFLite_SentencepieceTokenizerRegisterer(
+-    tflite::MutableOpResolver *resolver);
++    tflite::MutableOpResolver* resolver);
+ 
+ #endif  // TENSORFLOW_LITE_SUPPORT_CUSTOM_OPS_KERNEL_SENTENCEPIECE_PY_TFLITE_REGISTERER_H_
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_detokenizer_tflite.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_detokenizer_tflite.cc
+index 54b34e4e33196..f5be376b45e12 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_detokenizer_tflite.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_detokenizer_tflite.cc
+@@ -35,7 +35,8 @@ namespace detokenizer {
+ 
+ constexpr int kOutputValuesInd = 0;
+ // Initializes text encoder object from serialized parameters.
+-void* Initialize(TfLiteContext* /*context*/, const char* /*buffer*/,
++void* Initialize(TfLiteContext* /*context*/,
++                 const char* /*buffer*/,
+                  size_t /*length*/) {
+   return nullptr;
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_op.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_op.cc
+index 41fc5aa28bf30..68f8e64492394 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_op.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_op.cc
+@@ -16,16 +16,16 @@ limitations under the License.
+ #include <iterator>
+ #include <vector>
+ 
+-#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h"
+-#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer.h"
+ #include "tensorflow/core/framework/op.h"
+ #include "tensorflow/core/framework/op_kernel.h"
+ #include "tensorflow/core/framework/shape_inference.h"
+ #include "tensorflow/core/framework/tensor.h"
+ #include "tensorflow/core/protobuf/error_codes.pb.h"
++#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h"
++#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer.h"
+ 
+ namespace tensorflow {
+-namespace ops{
++namespace ops {
+ 
+ // copied from third_party/tensorflow_text/core/ops/sentencepiece_ops.cc
+ REGISTER_OP("TFSentencepieceTokenizeOp")
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_tflite.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_tflite.cc
+index 8309a6a2616fd..edb0160b508a3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_tflite.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer_tflite.cc
+@@ -16,8 +16,6 @@ limitations under the License.
+ /**
+  * Sentencepiece tflite tokenizer implementation.
+  */
+-#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h"
+-#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer.h"
+ #include "flatbuffers/flexbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/c/common.h"
+ #include "tensorflow/lite/context.h"
+@@ -25,6 +23,8 @@ limitations under the License.
+ #include "tensorflow/lite/kernels/kernel_util.h"
+ #include "tensorflow/lite/model.h"
+ #include "tensorflow/lite/string_util.h"
++#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.h"
++#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/sentencepiece_tokenizer.h"
+ 
+ namespace tflite {
+ namespace ops {
+@@ -47,7 +47,8 @@ TfLiteIntArray* CreateSizeArray(const std::initializer_list<int>& sizes) {
+ }  // namespace
+ 
+ // Initializes text encoder object from serialized parameters.
+-void* Initialize(TfLiteContext* /*context*/, const char* /*buffer*/,
++void* Initialize(TfLiteContext* /*context*/,
++                 const char* /*buffer*/,
+                  size_t /*length*/) {
+   return nullptr;
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer.cc
+index dad2f0004be06..8096a5008bd12 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer.cc
+@@ -19,10 +19,10 @@ limitations under the License.
+ #include <utility>
+ #include <vector>
+ 
++#include "libutf/utf.h"
+ #include "tensorflow/lite/context.h"
+ #include "tensorflow/lite/kernels/kernel_util.h"
+ #include "tensorflow/lite/string_util.h"
+-#include "libutf/utf.h"
+ 
+ constexpr int kInput = 0;
+ constexpr int kOutputValues = 0;
+@@ -49,7 +49,7 @@ inline bool OutputIsPaddedTensor(TfLiteNode* node) {
+ }
+ 
+ inline int charntorune(Rune* r, const char* s, int n) {
+-  const int bytes_read = chartorune(r, const_cast<char *>(s));
++  const int bytes_read = chartorune(r, const_cast<char*>(s));
+   if (bytes_read > n) {
+     *r = Runeerror;
+     return 0;
+@@ -66,7 +66,8 @@ std::vector<std::pair<const char*, int>> Tokenize(StringRef str) {
+   while (n > 0) {
+     Rune r;
+     int c = charntorune(&r, p, n);
+-    if (r == Runeerror) break;
++    if (r == Runeerror)
++      break;
+ 
+     if (isspacerune(r)) {
+       if (start != nullptr) {
+@@ -91,7 +92,8 @@ std::vector<std::pair<const char*, int>> Tokenize(StringRef str) {
+ 
+ TfLiteStatus WritePaddedOutput(
+     const std::vector<std::vector<std::pair<const char*, int>>>& list_of_tokens,
+-    const TfLiteTensor* input, TfLiteTensor* output_values) {
++    const TfLiteTensor* input,
++    TfLiteTensor* output_values) {
+   TfLiteIntArray* output_shape = TfLiteIntArrayCreate(NumDimensions(input) + 1);
+   for (int i = 0; i < NumDimensions(input); ++i) {
+     output_shape->data[i] = SizeOfDimension(input, i);
+@@ -118,7 +120,8 @@ TfLiteStatus WritePaddedOutput(
+ 
+ TfLiteStatus WriteRaggedOutput(
+     const std::vector<std::vector<std::pair<const char*, int>>>& list_of_tokens,
+-    const TfLiteTensor* input, TfLiteTensor* output_values,
++    const TfLiteTensor* input,
++    TfLiteTensor* output_values,
+     std::vector<TfLiteTensor*> nested_row_splits) {
+   // The outer dimensions of the ragged tensor are all non-ragged.
+   for (int i = 0; i < nested_row_splits.size() - 1; ++i) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer_op_resolver.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer_op_resolver.cc
+index 534fbef4aff2d..6166bc149bc00 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer_op_resolver.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer_op_resolver.cc
+@@ -15,8 +15,8 @@ limitations under the License.
+ 
+ #include "tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer_op_resolver.h"
+ 
+-#include "tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer.h"
+ #include "tensorflow/lite/mutable_op_resolver.h"
++#include "tensorflow_lite_support/custom_ops/kernel/whitespace_tokenizer.h"
+ 
+ namespace tflite {
+ namespace ops {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc
+index 7447870046f48..6339ed705bcb9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc
+@@ -24,22 +24,30 @@ limitations under the License.
+ #include <iostream>
+ #include <limits>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
++#include "absl/flags/flag.h"   // from @com_google_absl
+ #include "absl/flags/parse.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' audio classification model.");
+-ABSL_FLAG(std::string, audio_wav_path, "",
++ABSL_FLAG(std::string,
++          audio_wav_path,
++          "",
+           "Absolute path to the 16-bit PCM WAV file to classify. The WAV "
+           "file must be monochannel and has a sampling rate matches the model "
+           "expected sampling rate (as in the Metadata).  If the WAV file is "
+           "longer than what the model requires, only the beginning section is "
+           "used for inference.");
+-ABSL_FLAG(float, score_threshold, 0.001f,
++ABSL_FLAG(float,
++          score_threshold,
++          0.001f,
+           "Apply a filter on the results. Only display classes with score "
+           "higher than the threshold.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc
+index 36d6633d902e3..a843501ec3d75 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc
+@@ -19,7 +19,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+@@ -34,7 +34,8 @@ namespace task {
+ namespace audio {
+ 
+ tflite::support::StatusOr<AudioBuffer> LoadAudioBufferFromFile(
+-    const std::string& wav_file, int buffer_size,
++    const std::string& wav_file,
++    int buffer_size,
+     std::vector<float>* wav_data) {
+   std::string contents = ReadFile(wav_file);
+ 
+@@ -55,7 +56,8 @@ tflite::support::StatusOr<AudioBuffer> LoadAudioBufferFromFile(
+ }
+ 
+ tflite::support::StatusOr<ClassificationResult> Classify(
+-    const std::string& model_path, const std::string& wav_file,
++    const std::string& model_path,
++    const std::string& wav_file,
+     bool use_coral) {
+   AudioClassifierOptions options;
+   options.mutable_base_options()->mutable_model_file()->set_file_name(
+@@ -97,7 +99,8 @@ void Display(const ClassificationResult& result, float score_threshold) {
+     std::cout << absl::StrFormat("\nHead[%d]: %s\n", i, head.head_name());
+     for (int j = 0; j < head.classes_size(); j++) {
+       const auto& category = head.classes(j);
+-      if (category.score() < score_threshold) continue;
++      if (category.score() < score_threshold)
++        continue;
+       std::cout << absl::StrFormat("\tcategory[%s]: %.5f\t",
+                                    category.class_name(), category.score());
+       if (!category.display_name().empty()) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h
+index 6d23078ba3e19..13b2d7792e025 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h
+@@ -28,7 +28,8 @@ namespace audio {
+ // than what the model requires, only the beginning section is used for
+ // inference.
+ tflite::support::StatusOr<ClassificationResult> Classify(
+-    const std::string& model_path, const std::string& wav_file,
++    const std::string& model_path,
++    const std::string& wav_file,
+     bool use_coral = false);
+ 
+ // Prints the output classification result in the standard output. It only
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc
+index 02eed2332b2e4..5203200808d60 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc
+@@ -15,18 +15,22 @@ limitations under the License.
+ #include <iostream>
+ #include <limits>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/category.h"
+ #include "tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' bert classification model.");
+ ABSL_FLAG(std::string, text, "", "Text to classify.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc
+index 4eaa2bbbdd9f5..f2577cfad54c2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc
+@@ -15,19 +15,25 @@ limitations under the License.
+ #include <iostream>
+ #include <limits>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' bert question answerer model.");
+ ABSL_FLAG(std::string, question, "", "Question to ask.");
+-ABSL_FLAG(std::string, context, "",
++ABSL_FLAG(std::string,
++          context,
++          "",
+           "Context the asked question is based upon.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc
+index 49f233ce1e74c..613744ffdb20b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc
+@@ -15,18 +15,22 @@ limitations under the License.
+ #include <iostream>
+ #include <limits>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/category.h"
+ #include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' classification model.");
+ ABSL_FLAG(std::string, text, "", "Text to classify.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc
+index 8c4a36c31674f..8ba00cb5d50bd 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc
+@@ -14,26 +14,30 @@ limitations under the License.
+ ==============================================================================*/
+ 
+ // Demostration the usage of UniversalSentenceEncoderQA.
+-#include "tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h"
++#include "absl/flags/flag.h"         // from @com_google_absl
++#include "absl/flags/parse.h"        // from @com_google_absl
++#include "absl/status/status.h"      // from @com_google_absl
+ #include "absl/strings/str_split.h"  // from @com_google_absl
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-using tflite::task::text::RetrievalOptions;
++#include "tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h"
+ using tflite::task::text::RetrievalInput;
++using tflite::task::text::RetrievalOptions;
+ using tflite::task::text::RetrievalOutput;
+ using tflite::task::text::retrieval::UniversalSentenceEncoderQA;
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' UniversalSentenceEncoderQA model.");
+-ABSL_FLAG(std::string, question, "How are you feeling today?",
++ABSL_FLAG(std::string,
++          question,
++          "How are you feeling today?",
+           "Question to ask.");
+ ABSL_FLAG(
+-    std::string, answers,
++    std::string,
++    answers,
+     "I'm not feeling very well.:Paris is the capital of France.:He looks good.",
+     "Candidate answers seperated by `:`.");
+ 
+-
+ int main(int argc, char** argv) {
+   // Parse command line arguments and perform sanity checks.
+   absl::ParseCommandLine(argc, argv);
+@@ -55,8 +59,8 @@ int main(int argc, char** argv) {
+       absl::GetFlag(FLAGS_model_path));
+   auto status = UniversalSentenceEncoderQA::CreateFromOption(options);
+   CHECK_OK(status);
+-  std::unique_ptr<UniversalSentenceEncoderQA> client
+-      = std::move(status.value());
++  std::unique_ptr<UniversalSentenceEncoderQA> client =
++      std::move(status.value());
+ 
+   // Create RetrievalInput with a query and responses.
+   RetrievalInput input;
+@@ -80,8 +84,8 @@ int main(int argc, char** argv) {
+   // Consume the results according to the ranking. Here we just print them out.
+   std::cout << input.query_text() << std::endl;
+   for (size_t k : top) {
+-     std::cout << input.responses(k).raw_text().text() << ", "
+-               << input.responses(k).raw_text().context() << ", "
+-               << output.response_results(k).score() << std::endl;
++    std::cout << input.responses(k).raw_text().text() << ", "
++              << input.responses(k).raw_text().context() << ", "
++              << output.response_results(k).score() << std::endl;
+   }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc
+index 8b2ed939686b3..bd2aaaf188726 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc
+@@ -22,9 +22,9 @@ limitations under the License.
+ 
+ #include <iostream>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+@@ -36,29 +36,43 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+ #include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' image classifier model.");
+-ABSL_FLAG(std::string, image_path, "",
++ABSL_FLAG(std::string,
++          image_path,
++          "",
+           "Absolute path to the image to classify. The image must be RGB or "
+           "RGBA (grayscale is not supported). The image EXIF orientation "
+           "flag, if any, is NOT taken into account.");
+-ABSL_FLAG(int32, max_results, 5,
++ABSL_FLAG(int32,
++          max_results,
++          5,
+           "Maximum number of classification results to display.");
+-ABSL_FLAG(float, score_threshold, 0,
++ABSL_FLAG(float,
++          score_threshold,
++          0,
+           "Classification results with a confidence score below this value are "
+           "rejected. If >= 0, overrides the score threshold(s) provided in the "
+           "TFLite Model Metadata. Ignored otherwise.");
+ ABSL_FLAG(
+-    std::vector<std::string>, class_name_whitelist, {},
++    std::vector<std::string>,
++    class_name_whitelist,
++    {},
+     "Comma-separated list of class names that acts as a whitelist. If "
+     "non-empty, classification results whose 'class_name' is not in this list "
+     "are filtered out. Mutually exclusive with 'class_name_blacklist'.");
+ ABSL_FLAG(
+-    std::vector<std::string>, class_name_blacklist, {},
++    std::vector<std::string>,
++    class_name_blacklist,
++    {},
+     "Comma-separated list of class names that acts as a blacklist. If "
+     "non-empty, classification results whose 'class_name' is in this list "
+     "are filtered out. Mutually exclusive with 'class_name_whitelist'.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc
+index 722194f34ee5e..040878aa37841 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc
+@@ -26,9 +26,9 @@ limitations under the License.
+ 
+ #include <iostream>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+@@ -39,28 +39,40 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+ #include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' image embedder model.");
+-ABSL_FLAG(std::string, first_image_path, "",
++ABSL_FLAG(std::string,
++          first_image_path,
++          "",
+           "Absolute path to the first image, whose feature vector will be "
+           "extracted and compared to the second image using cosine similarity. "
+           "The image must be RGB or RGBA (grayscale is not supported). The "
+           "image EXIF orientation flag, if any, is NOT taken into account.");
+-ABSL_FLAG(std::string, second_image_path, "",
++ABSL_FLAG(std::string,
++          second_image_path,
++          "",
+           "Absolute path to the second image, whose feature vector will be "
+           "extracted and compared to the first image using cosine similarity. "
+           "The image must be RGB or RGBA (grayscale is not supported). The "
+           "image EXIF orientation flag, if any, is NOT taken into account.");
+-ABSL_FLAG(bool, l2_normalize, false,
++ABSL_FLAG(bool,
++          l2_normalize,
++          false,
+           "If true, the raw feature vectors returned by the image embedder "
+           "will be normalized with L2-norm. Generally only needed if the model "
+           "doesn't already contain a L2_NORMALIZATION TFLite Op.");
+ ABSL_FLAG(
+-    bool, quantize, false,
++    bool,
++    quantize,
++    false,
+     "If true, the raw feature vectors returned by the image embedder will "
+     "be quantized to 8 bit integers (uniform quantization) via post-processing "
+     "before cosine similarity is computed.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc
+index 2cb606e011aca..6487fe92166cd 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc
+@@ -23,10 +23,10 @@ limitations under the License.
+ 
+ #include <iostream>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/match.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/match.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+@@ -37,16 +37,24 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+ #include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' image segmenter model.");
+-ABSL_FLAG(std::string, image_path, "",
++ABSL_FLAG(std::string,
++          image_path,
++          "",
+           "Absolute path to the image to segment. The image must be RGB or "
+           "RGBA (grayscale is not supported). The image EXIF orientation "
+           "flag, if any, is NOT taken into account.");
+-ABSL_FLAG(std::string, output_mask_png, "",
++ABSL_FLAG(std::string,
++          output_mask_png,
++          "",
+           "Absolute path to the output category mask (confidence masks outputs "
+           "are not supported by this tool). Must have a '.png' extension.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc
+index 0130b4550b9d9..9208439df6263 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc
+@@ -24,10 +24,10 @@ limitations under the License.
+ #include <iostream>
+ #include <limits>
+ 
+-#include "absl/flags/flag.h"  // from @com_google_absl
+-#include "absl/flags/parse.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/match.h"  // from @com_google_absl
++#include "absl/flags/flag.h"          // from @com_google_absl
++#include "absl/flags/parse.h"         // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/match.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+@@ -40,32 +40,48 @@ limitations under the License.
+ #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+ #include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+ 
+-ABSL_FLAG(std::string, model_path, "",
++ABSL_FLAG(std::string,
++          model_path,
++          "",
+           "Absolute path to the '.tflite' object detector model.");
+-ABSL_FLAG(std::string, image_path, "",
++ABSL_FLAG(std::string,
++          image_path,
++          "",
+           "Absolute path to the image to run detection on. The image must be "
+           "RGB or RGBA (grayscale is not supported). The image EXIF "
+           "orientation flag, if any, is NOT taken into account.");
+-ABSL_FLAG(std::string, output_png, "",
++ABSL_FLAG(std::string,
++          output_png,
++          "",
+           "Absolute path to a file where to draw the detection results on top "
+           "of the input image. Must have a '.png' extension.");
+-ABSL_FLAG(int32, max_results, 5,
++ABSL_FLAG(int32,
++          max_results,
++          5,
+           "Maximum number of detection results to display.");
+ ABSL_FLAG(
+-    float, score_threshold, std::numeric_limits<float>::lowest(),
++    float,
++    score_threshold,
++    std::numeric_limits<float>::lowest(),
+     "Detection results with a confidence score below this value are "
+     "rejected. If specified, overrides the score threshold(s) provided in the "
+     "TFLite Model Metadata. Ignored otherwise.");
+ ABSL_FLAG(
+-    std::vector<std::string>, class_name_whitelist, {},
++    std::vector<std::string>,
++    class_name_whitelist,
++    {},
+     "Comma-separated list of class names that acts as a whitelist. If "
+     "non-empty, detections results whose 'class_name' is not in this list "
+     "are filtered out. Mutually exclusive with 'class_name_blacklist'.");
+-ABSL_FLAG(std::vector<std::string>, class_name_blacklist, {},
++ABSL_FLAG(std::vector<std::string>,
++          class_name_blacklist,
++          {},
+           "Comma-separated list of class names that acts as a blacklist. If "
+           "non-empty, detections results whose 'class_name' is in this list "
+           "are filtered out. Mutually exclusive with 'class_name_whitelist'.");
+-ABSL_FLAG(bool, use_coral, false,
++ABSL_FLAG(bool,
++          use_coral,
++          false,
+           "If true, inference will be delegated to a connected Coral Edge TPU "
+           "device.");
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc
+index 6f3aa737bd090..efdcda993f5e8 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc
+@@ -23,11 +23,11 @@ limitations under the License.
+ #define STB_IMAGE_IMPLEMENTATION
+ #define STB_IMAGE_WRITE_IMPLEMENTATION
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/match.h"  // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
++#include "absl/strings/match.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+-#include "stb_image.h"  // from @stblib
+-#include "stb_image_write.h"  // from @stblib
++#include "stb_image.h"                // from @stblib
++#include "stb_image_write.h"          // from @stblib
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ 
+@@ -87,7 +87,9 @@ absl::Status EncodeImageToPngFile(const ImageData& image_data,
+   return absl::OkStatus();
+ }
+ 
+-void ImageDataFree(ImageData* image) { stbi_image_free(image->pixel_data); }
++void ImageDataFree(ImageData* image) {
++  stbi_image_free(image->pixel_data);
++}
+ 
+ }  // namespace vision
+ }  // namespace task
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h
+index a0b0c6bbad191..9e7e3ba500f2d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h
+@@ -15,7 +15,7 @@ limitations under the License.
+ #ifndef TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_VISION_DESKTOP_UTILS_IMAGE_UTILS_H_
+ #define TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_VISION_DESKTOP_UTILS_IMAGE_UTILS_H_
+ 
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/status/status.h"        // from @com_google_absl
+ #include "absl/strings/string_view.h"  // from @com_google_absl
+ #include "tensorflow_lite_support/cc/port/integral_types.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h
+index a4fee55abe158..2ca42fb7f3fbe 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h
+@@ -56,7 +56,8 @@ typedef NS_ENUM(NSUInteger, TFLSupportErrorCode) {
+ 
+   /** TensorFlow Lite metadata error codes. */
+ 
+-  /** Unexpected schema version (aka file_identifier) in the Metadata FlatBuffer. */
++  /** Unexpected schema version (aka file_identifier) in the Metadata
++     FlatBuffer. */
+   TFLSupportErrorCodeMetadataInvalidSchemaVersionError = 200,
+ 
+   /** No such associated file within metadata, or file has not been packed. */
+@@ -198,11 +199,13 @@ typedef NS_ENUM(NSUInteger, TFLSupportErrorCode) {
+    */
+   TFLSupportErrorCodeImageProcessingBackendError,
+ 
+-  /** kNotFound indicates some requested entity (such as a file or directory) was not found. */
++  /** kNotFound indicates some requested entity (such as a file or directory)
++     was not found. */
+   TFLSupportErrorCodeNotFoundError = 900,
+ 
+-  /** kInternal indicates an internal error has occurred and some invariants expected by the
+-   * underlying system have not been satisfied. This error code is reserved for serious errors.
++  /** kInternal indicates an internal error has occurred and some invariants
++   * expected by the underlying system have not been satisfied. This error code
++   * is reserved for serious errors.
+    */
+   TFLSupportErrorCodeInternalError,
+ } NS_SWIFT_NAME(SupportErrorCode);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h
+index 8ef21659a4a1a..a194b2834323a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h
+@@ -21,42 +21,43 @@ NS_ASSUME_NONNULL_BEGIN
+ @interface TFLCommonUtils : NSObject
+ 
+ /**
+- * Creates and saves an error originating from the task library with the given error code and
+- * description.
++ * Creates and saves an error originating from the task library with the given
++ * error code and description.
+  *
+  * @param code Error code.
+  * @param description Error description.
+- * @param error Pointer to the memory location where the created error should be saved. If `nil`, no
+- * error will be saved.
++ * @param error Pointer to the memory location where the created error should be
++ * saved. If `nil`, no error will be saved.
+  */
+ + (void)customErrorWithCode:(NSInteger)code
+-                description:(NSString *)description
+-                      error:(NSError **)error;
++                description:(NSString*)description
++                      error:(NSError**)error;
+ 
+ /**
+- * Creates and saves an error originating from the task library from a C library error,
+- * TfLiteSupportError .
++ * Creates and saves an error originating from the task library from a C library
++ * error, TfLiteSupportError .
+  *
+  * @param supportError C library error.
+- * @param error Pointer to the memory location where the created error should be saved. If `nil`, no
+- * error will be saved.
++ * @param error Pointer to the memory location where the created error should be
++ * saved. If `nil`, no error will be saved.
+  */
+-+ (void)errorFromTfLiteSupportError:(TfLiteSupportError *)supportError error:(NSError **)error;
+++ (void)errorFromTfLiteSupportError:(TfLiteSupportError*)supportError
++                              error:(NSError**)error;
+ 
+ /**
+- * Allocates a block of memory with the specified size and returns a pointer to it. If memory cannot
+- * be allocated because of an invalid memSize, it saves an error. In other cases, it terminates
+- * program execution.
++ * Allocates a block of memory with the specified size and returns a pointer to
++ * it. If memory cannot be allocated because of an invalid memSize, it saves an
++ * error. In other cases, it terminates program execution.
+  *
+  * @param memSize size of memory to be allocated
+- * @param error Pointer to the memory location where errors if any should be saved. If `nil`, no
+- * error will be saved.
++ * @param error Pointer to the memory location where errors if any should be
++ * saved. If `nil`, no error will be saved.
+  *
+- * @return Pointer to the allocated block of memory on successfull allocation. nil in case as error
+- * is encountered because of invalid memSize. If failure is due to any other reason, method
+- * terminates program execution.
++ * @return Pointer to the allocated block of memory on successfull allocation.
++ * nil in case as error is encountered because of invalid memSize. If failure is
++ * due to any other reason, method terminates program execution.
+  */
+-+ (void *)mallocWithSize:(size_t)memSize error:(NSError **)error;
+++ (void*)mallocWithSize:(size_t)memSize error:(NSError**)error;
+ @end
+ 
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m
+index 6fc2eadeeafe9..2f2d85a23593a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m
+@@ -16,39 +16,43 @@
+ #import "tensorflow_lite_support/ios/sources/TFLCommon.h"
+ 
+ /** Error domain of TensorFlow Lite Support related errors. */
+-static NSString *const TFLSupportTaskErrorDomain = @"org.tensorflow.lite.tasks";
++static NSString* const TFLSupportTaskErrorDomain = @"org.tensorflow.lite.tasks";
+ 
+ @implementation TFLCommonUtils
+ 
+ + (void)customErrorWithCode:(NSInteger)code
+-                description:(NSString *)description
+-                      error:(NSError **)error {
++                description:(NSString*)description
++                      error:(NSError**)error {
+   if (error)
+-    *error = [NSError errorWithDomain:TFLSupportTaskErrorDomain
+-                                 code:code
+-                             userInfo:@{NSLocalizedDescriptionKey : description}];
++    *error =
++        [NSError errorWithDomain:TFLSupportTaskErrorDomain
++                            code:code
++                        userInfo:@{NSLocalizedDescriptionKey : description}];
+ }
+ 
+-+ (void)errorFromTfLiteSupportError:(TfLiteSupportError *)supportError error:(NSError **)error {
+++ (void)errorFromTfLiteSupportError:(TfLiteSupportError*)supportError
++                              error:(NSError**)error {
+   if (supportError && error)
+-    *error = [NSError
+-        errorWithDomain:TFLSupportTaskErrorDomain
+-                   code:supportError->code
+-               userInfo:@{
+-                 NSLocalizedDescriptionKey : [NSString stringWithCString:supportError->message
+-                                                                encoding:NSUTF8StringEncoding]
+-               }];
++    *error = [NSError errorWithDomain:TFLSupportTaskErrorDomain
++                                 code:supportError->code
++                             userInfo:@{
++                               NSLocalizedDescriptionKey : [NSString
++                                   stringWithCString:supportError->message
++                                            encoding:NSUTF8StringEncoding]
++                             }];
+ }
+ 
+-+ (void *)mallocWithSize:(size_t)memSize error:(NSError **)error {
+++ (void*)mallocWithSize:(size_t)memSize error:(NSError**)error {
+   if (!memSize) {
+-    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+-                            description:@"Invalid memory size passed for allocation of object."
+-                                  error:error];
++    [TFLCommonUtils
++        customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
++                description:
++                    @"Invalid memory size passed for allocation of object."
++                      error:error];
+     return NULL;
+   }
+ 
+-  void *allocedMemory = malloc(memSize);
++  void* allocedMemory = malloc(memSize);
+   if (!allocedMemory && memSize) {
+     exit(-1);
+   }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h
+index 40ba41b8eb0f9..90864c703c411 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h
+@@ -18,7 +18,7 @@
+ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLBaseOptions (Helpers)
+-- (void)copyBaseOptionsToCBaseOptions:(TfLiteBaseOptions *)cBaseOptions;
++- (void)copyBaseOptionsToCBaseOptions:(TfLiteBaseOptions*)cBaseOptions;
+ @end
+ 
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m
+index 0fed6d7c9966e..ddab0f7ab4207 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m
+@@ -16,7 +16,7 @@
+ 
+ @implementation TFLBaseOptions (Helpers)
+ 
+-- (void)copyBaseOptionsToCBaseOptions:(TfLiteBaseOptions *)cBaseOptions {
++- (void)copyBaseOptionsToCBaseOptions:(TfLiteBaseOptions*)cBaseOptions {
+   if (self.modelFile.filePath) {
+     cBaseOptions->model_file.file_path = self.modelFile.filePath.UTF8String;
+   }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h
+index cdcddabe7323a..0f92dd1005631 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h
+@@ -19,10 +19,10 @@ NS_ASSUME_NONNULL_BEGIN
+ NS_SWIFT_NAME(CpuSettings)
+ @interface TFLCpuSettings : NSObject <NSCopying>
+ 
+-/** Specifies the number of threads to be used for TFLite ops that support multi-threadingwhen
+- * running inference with CPU.
+- * @discussion This property hould be greater than 0 or equal to -1. Setting  it to -1 has the
+- * effect to let TFLite runtime set the value.
++/** Specifies the number of threads to be used for TFLite ops that support
++ * multi-threadingwhen running inference with CPU.
++ * @discussion This property hould be greater than 0 or equal to -1. Setting  it
++ * to -1 has the effect to let TFLite runtime set the value.
+  */
+ @property(nonatomic, assign) int numThreads;
+ 
+@@ -35,7 +35,7 @@ NS_SWIFT_NAME(ComputeSettings)
+ @interface TFLComputeSettings : NSObject <NSCopying>
+ 
+ /** Holds cpu settings. */
+-@property(nonatomic, copy) TFLCpuSettings *cpuSettings;
++@property(nonatomic, copy) TFLCpuSettings* cpuSettings;
+ 
+ @end
+ 
+@@ -46,30 +46,32 @@ NS_SWIFT_NAME(ExternalFile)
+ @interface TFLExternalFile : NSObject <NSCopying>
+ 
+ /** Path to the file in bundle. */
+-@property(nonatomic, copy) NSString *filePath;
++@property(nonatomic, copy) NSString* filePath;
+ /// Add provision for other sources in future.
+ 
+ @end
+ 
+ /**
+- * Holds the base options that is used for creation of any type of task. It has fields with
+- * important information acceleration configuration, tflite model source etc.
++ * Holds the base options that is used for creation of any type of task. It has
++ * fields with important information acceleration configuration, tflite model
++ * source etc.
+  */
+ NS_SWIFT_NAME(BaseOptions)
+ @interface TFLBaseOptions : NSObject <NSCopying>
+ 
+ /**
+- * The external model file, as a single standalone TFLite file. It could be packed with TFLite Model
+- * Metadata[1] and associated files if exist. Fail to provide the necessary metadata and associated
+- * files might result in errors.
++ * The external model file, as a single standalone TFLite file. It could be
++ * packed with TFLite Model Metadata[1] and associated files if exist. Fail to
++ * provide the necessary metadata and associated files might result in errors.
+  */
+-@property(nonatomic, copy) TFLExternalFile *modelFile;
++@property(nonatomic, copy) TFLExternalFile* modelFile;
+ 
+ /**
+- * Holds settings for one possible acceleration configuration including.cpu/gpu settings.
+- * Please see documentation of TfLiteComputeSettings and its members for more details.
++ * Holds settings for one possible acceleration configuration including.cpu/gpu
++ * settings. Please see documentation of TfLiteComputeSettings and its members
++ * for more details.
+  */
+-@property(nonatomic, copy) TFLComputeSettings *computeSettings;
++@property(nonatomic, copy) TFLComputeSettings* computeSettings;
+ 
+ @end
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m
+index 826380f1f62db..1e536cdc08194 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m
+@@ -25,8 +25,8 @@
+   return self;
+ }
+ 
+-- (id)copyWithZone:(NSZone *)zone {
+-  TFLCpuSettings *cpuSettings = [[TFLCpuSettings alloc] init];
++- (id)copyWithZone:(NSZone*)zone {
++  TFLCpuSettings* cpuSettings = [[TFLCpuSettings alloc] init];
+ 
+   [cpuSettings setNumThreads:self.numThreads];
+ 
+@@ -46,8 +46,8 @@
+   return self;
+ }
+ 
+-- (id)copyWithZone:(NSZone *)zone {
+-  TFLComputeSettings *computeSettings = [[TFLComputeSettings alloc] init];
++- (id)copyWithZone:(NSZone*)zone {
++  TFLComputeSettings* computeSettings = [[TFLComputeSettings alloc] init];
+ 
+   [computeSettings setCpuSettings:self.cpuSettings];
+ 
+@@ -59,8 +59,8 @@
+ @implementation TFLExternalFile
+ @synthesize filePath;
+ 
+-- (id)copyWithZone:(NSZone *)zone {
+-  TFLExternalFile *externalFile = [[TFLExternalFile alloc] init];
++- (id)copyWithZone:(NSZone*)zone {
++  TFLExternalFile* externalFile = [[TFLExternalFile alloc] init];
+ 
+   [externalFile setFilePath:self.filePath];
+ 
+@@ -82,8 +82,8 @@
+   return self;
+ }
+ 
+-- (id)copyWithZone:(NSZone *)zone {
+-  TFLBaseOptions *baseOptions = [[TFLBaseOptions alloc] init];
++- (id)copyWithZone:(NSZone*)zone {
++  TFLBaseOptions* baseOptions = [[TFLBaseOptions alloc] init];
+ 
+   [baseOptions setModelFile:self.modelFile];
+   [baseOptions setComputeSettings:self.computeSettings];
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h
+index 623065d416904..78a1f965769aa 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h
+@@ -19,11 +19,11 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLClassificationOptions (Helpers)
+ - (BOOL)copyClassificationOptionsToCClassificationOptions:
+-            (TfLiteClassificationOptions *)cClassificationOptions
+-                                                    error:(NSError **)error;
++            (TfLiteClassificationOptions*)cClassificationOptions
++                                                    error:(NSError**)error;
+ 
+ - (void)deleteCStringArraysOfClassificationOptions:
+-    (TfLiteClassificationOptions *)cClassificationOptions;
++    (TfLiteClassificationOptions*)cClassificationOptions;
+ @end
+ 
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m
+index f7aa5fdf18b36..07254ab675c4b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m
+@@ -18,28 +18,35 @@
+ 
+ @implementation TFLClassificationOptions (Helpers)
+ 
+-+ (char **)cStringArrayFromNSArray:(NSArray<NSString *> *)strings error:(NSError **)error {
+++ (char**)cStringArrayFromNSArray:(NSArray<NSString*>*)strings
++                            error:(NSError**)error {
+   if (strings.count <= 0) {
+-    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+-                            description:@"Invalid length of strings found for list type options."
+-                                  error:error];
++    [TFLCommonUtils
++        customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
++                description:
++                    @"Invalid length of strings found for list type options."
++                      error:error];
+     return NULL;
+   }
+ 
+-  char **cStrings = (char **)calloc(strings.count, sizeof(char *));
++  char** cStrings = (char**)calloc(strings.count, sizeof(char*));
+ 
+   if (!cStrings) {
+-    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInternalError
+-                            description:@"Could not initialize list type options."
+-                                  error:error];
++    [TFLCommonUtils
++        customErrorWithCode:TFLSupportErrorCodeInternalError
++                description:@"Could not initialize list type options."
++                      error:error];
+     return nil;
+   }
+ 
+   for (NSInteger i = 0; i < strings.count; i++) {
+-    char *cString = [TFLCommonUtils
+-        mallocWithSize:[strings[i] lengthOfBytesUsingEncoding:NSUTF8StringEncoding] + 1
++    char* cString = [TFLCommonUtils
++        mallocWithSize:[strings[i]
++                           lengthOfBytesUsingEncoding:NSUTF8StringEncoding] +
++                       1
+                  error:error];
+-    if (!cString) return nil;
++    if (!cString)
++      return nil;
+ 
+     strcpy(cString, strings[i].UTF8String);
+   }
+@@ -47,7 +54,7 @@
+   return cStrings;
+ }
+ 
+-+ (void)deleteCStringsArray:(char **)cStrings count:(int)count {
+++ (void)deleteCStringsArray:(char**)cStrings count:(int)count {
+   for (NSInteger i = 0; i < count; i++) {
+     free(cStrings[i]);
+   }
+@@ -56,49 +63,56 @@
+ }
+ 
+ - (BOOL)copyClassificationOptionsToCClassificationOptions:
+-            (TfLiteClassificationOptions *)cClassificationOptions
+-                                                    error:(NSError **)error {
++            (TfLiteClassificationOptions*)cClassificationOptions
++                                                    error:(NSError**)error {
+   cClassificationOptions->score_threshold = self.scoreThreshold;
+   cClassificationOptions->max_results = (int)self.maxResults;
+ 
+   if (self.labelDenyList) {
+-    char **cClassNameBlackList =
+-        [TFLClassificationOptions cStringArrayFromNSArray:self.labelDenyList error:error];
++    char** cClassNameBlackList =
++        [TFLClassificationOptions cStringArrayFromNSArray:self.labelDenyList
++                                                    error:error];
+     if (!cClassNameBlackList) {
+       return NO;
+     }
+     cClassificationOptions->label_denylist.list = cClassNameBlackList;
+-    cClassificationOptions->label_denylist.length = (int)self.labelDenyList.count;
++    cClassificationOptions->label_denylist.length =
++        (int)self.labelDenyList.count;
+   }
+ 
+   if (self.labelAllowList) {
+-    char **cClassNameWhiteList =
+-        [TFLClassificationOptions cStringArrayFromNSArray:self.labelAllowList error:error];
++    char** cClassNameWhiteList =
++        [TFLClassificationOptions cStringArrayFromNSArray:self.labelAllowList
++                                                    error:error];
+     if (!cClassNameWhiteList) {
+       return NO;
+     }
+ 
+     cClassificationOptions->label_allowlist.list = cClassNameWhiteList;
+-    cClassificationOptions->label_allowlist.length = (int)self.labelAllowList.count;
++    cClassificationOptions->label_allowlist.length =
++        (int)self.labelAllowList.count;
+   }
+ 
+   if (self.displayNamesLocal) {
+-    cClassificationOptions->display_names_local = (char *)self.displayNamesLocal.UTF8String;
++    cClassificationOptions->display_names_local =
++        (char*)self.displayNamesLocal.UTF8String;
+   }
+ 
+   return YES;
+ }
+ 
+ - (void)deleteCStringArraysOfClassificationOptions:
+-    (TfLiteClassificationOptions *)cClassificationOptions {
++    (TfLiteClassificationOptions*)cClassificationOptions {
+   if (self.labelAllowList) {
+-    [TFLClassificationOptions deleteCStringsArray:cClassificationOptions->label_allowlist.list
+-                                            count:cClassificationOptions->label_allowlist.length];
++    [TFLClassificationOptions
++        deleteCStringsArray:cClassificationOptions->label_allowlist.list
++                      count:cClassificationOptions->label_allowlist.length];
+   }
+ 
+   if (self.labelDenyList) {
+-    [TFLClassificationOptions deleteCStringsArray:cClassificationOptions->label_denylist.list
+-                                            count:cClassificationOptions->label_denylist.length];
++    [TFLClassificationOptions
++        deleteCStringsArray:cClassificationOptions->label_denylist.list
++                      count:cClassificationOptions->label_denylist.length];
+   }
+ }
+ @end
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h
+index dbe05c8f98d2f..cc0c8a87da148 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h
+@@ -22,13 +22,14 @@ NS_ASSUME_NONNULL_BEGIN
+ @interface TFLClassificationOptions : NSObject <NSCopying>
+ 
+ /** If set, all classes  in this list will be filtered out from the results . */
+-@property(nonatomic, copy) NSArray *labelDenyList;
++@property(nonatomic, copy) NSArray* labelDenyList;
+ 
+-/** If set, all classes not in this list will be filtered out from the results . */
+-@property(nonatomic, copy) NSArray *labelAllowList;
++/** If set, all classes not in this list will be filtered out from the results .
++ */
++@property(nonatomic, copy) NSArray* labelAllowList;
+ 
+ /** Display names local for display names*/
+-@property(nonatomic, copy) NSString *displayNamesLocal;
++@property(nonatomic, copy) NSString* displayNamesLocal;
+ 
+ /** Results with score threshold greater than this value are returned . */
+ @property(nonatomic, assign) float scoreThreshold;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m
+index 784f782ebc271..dca232d673238 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m
+@@ -30,8 +30,9 @@
+   return self;
+ }
+ 
+-- (id)copyWithZone:(NSZone *)zone {
+-  TFLClassificationOptions *classificationOptions = [[TFLClassificationOptions alloc] init];
++- (id)copyWithZone:(NSZone*)zone {
++  TFLClassificationOptions* classificationOptions =
++      [[TFLClassificationOptions alloc] init];
+ 
+   [classificationOptions setScoreThreshold:self.scoreThreshold];
+   [classificationOptions setMaxResults:self.maxResults];
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h
+index 377e02f32045a..c0d6fb335ebf3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h
+@@ -20,39 +20,40 @@ NS_ASSUME_NONNULL_BEGIN
+ @interface TFLCategory : NSObject
+ 
+ /** Display name of the class. */
+-@property(nonatomic, copy) NSString *displayName;
++@property(nonatomic, copy) NSString* displayName;
+ 
+ /** Class name of the class . */
+-@property(nonatomic, copy) NSString *label;
++@property(nonatomic, copy) NSString* label;
+ 
+ /** Confidence score for this class . */
+ @property(nonatomic, assign) float score;
+ 
+-/** The index of the class in the corresponding label map, usually packed in the TFLite Model
+- * Metadata. */
++/** The index of the class in the corresponding label map, usually packed in the
++ * TFLite Model Metadata. */
+ @property(nonatomic, assign) NSInteger classIndex;
+ 
+ @end
+ 
+-/** Encapsulates list of predicted classes (aka labels) for a given image classifier head. */
++/** Encapsulates list of predicted classes (aka labels) for a given image
++ * classifier head. */
+ @interface TFLClassifications : NSObject
+ 
+ /**
+- * The index of the image classifier head these classes refer to. This is useful for multi-head
+- * models.
++ * The index of the image classifier head these classes refer to. This is useful
++ * for multi-head models.
+  */
+ @property(nonatomic, assign) int headIndex;
+ 
+-/** The array of predicted classes, usually sorted by descending scores (e.g.from high to low
+- * probability). */
+-@property(nonatomic, copy) NSArray<TFLCategory *> *categories;
++/** The array of predicted classes, usually sorted by descending scores
++ * (e.g.from high to low probability). */
++@property(nonatomic, copy) NSArray<TFLCategory*>* categories;
+ 
+ @end
+ 
+ /** Encapsulates results of any classification task. */
+ @interface TFLClassificationResult : NSObject
+ 
+-@property(nonatomic, copy) NSArray<TFLClassifications *> *classifications;
++@property(nonatomic, copy) NSArray<TFLClassifications*>* classifications;
+ 
+ @end
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h
+index 406eb1e4ceb5a..c52876e9a5d7a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h
+@@ -19,22 +19,23 @@
+ 
+ NS_ASSUME_NONNULL_BEGIN
+ 
+-/** Helper utility for conversion between TFLite Task C Library Classification Results and iOS
+- * Classification Results . */
++/** Helper utility for conversion between TFLite Task C Library Classification
++ * Results and iOS Classification Results . */
+ @interface TFLClassificationUtils : NSObject
+ 
+ /**
+- * Creates and retrurns a TFLClassificationResult from a TfLiteClassificationResult returned by
+- * TFLite Task C Library Classification tasks.
++ * Creates and retrurns a TFLClassificationResult from a
++ * TfLiteClassificationResult returned by TFLite Task C Library Classification
++ * tasks.
+  *
+- * @param cClassificationResult Classification results returned by TFLite Task C Library
+- * Classification tasks
++ * @param cClassificationResult Classification results returned by TFLite Task C
++ * Library Classification tasks
+  *
+- * @return Classification Result of type TFLClassificationResult to be returned by inference methods
+- * of the iOS TF Lite Task Classification tasks.
++ * @return Classification Result of type TFLClassificationResult to be returned
++ * by inference methods of the iOS TF Lite Task Classification tasks.
+  */
+-+ (TFLClassificationResult *)classificationResultFromCClassificationResults:
+-    (TfLiteClassificationResult *)cClassificationResult;
+++ (TFLClassificationResult*)classificationResultFromCClassificationResults:
++    (TfLiteClassificationResult*)cClassificationResult;
+ 
+ - (instancetype)init NS_UNAVAILABLE;
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m
+index a24a91e5c9729..b5d884d39f864 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m
+@@ -16,39 +16,44 @@
+ 
+ @implementation TFLClassificationUtils
+ 
+-+ (TFLClassificationResult *)classificationResultFromCClassificationResults:
+-    (TfLiteClassificationResult *)cClassificationResult {
+-  if (cClassificationResult == nil) return nil;
+++ (TFLClassificationResult*)classificationResultFromCClassificationResults:
++    (TfLiteClassificationResult*)cClassificationResult {
++  if (cClassificationResult == nil)
++    return nil;
+ 
+-  NSMutableArray *classificationHeads = [[NSMutableArray alloc] init];
++  NSMutableArray* classificationHeads = [[NSMutableArray alloc] init];
+   for (int i = 0; i < cClassificationResult->size; i++) {
+-    TfLiteClassifications cClassifications = cClassificationResult->classifications[i];
+-    NSMutableArray *classes = [[NSMutableArray alloc] init];
++    TfLiteClassifications cClassifications =
++        cClassificationResult->classifications[i];
++    NSMutableArray* classes = [[NSMutableArray alloc] init];
+     for (int j = 0; j < cClassifications.size; j++) {
+       TfLiteCategory cCategory = cClassifications.categories[j];
+-      TFLCategory *resultCategory = [[TFLCategory alloc] init];
++      TFLCategory* resultCategory = [[TFLCategory alloc] init];
+ 
+       if (cCategory.display_name != nil) {
+-        resultCategory.displayName = [NSString stringWithCString:cCategory.display_name
+-                                                        encoding:NSUTF8StringEncoding];
++        resultCategory.displayName =
++            [NSString stringWithCString:cCategory.display_name
++                               encoding:NSUTF8StringEncoding];
+       }
+ 
+       if (cCategory.label != nil) {
+-        resultCategory.label = [NSString stringWithCString:cCategory.label
+-                                                  encoding:NSUTF8StringEncoding];
++        resultCategory.label =
++            [NSString stringWithCString:cCategory.label
++                               encoding:NSUTF8StringEncoding];
+       }
+ 
+       resultCategory.score = cCategory.score;
+       resultCategory.classIndex = (NSInteger)cCategory.index;
+       [classes addObject:resultCategory];
+     }
+-    TFLClassifications *classificationHead = [[TFLClassifications alloc] init];
++    TFLClassifications* classificationHead = [[TFLClassifications alloc] init];
+     classificationHead.categories = classes;
+     classificationHead.headIndex = i;
+     [classificationHeads addObject:classificationHead];
+   }
+ 
+-  TFLClassificationResult *classificationResult = [[TFLClassificationResult alloc] init];
++  TFLClassificationResult* classificationResult =
++      [[TFLClassificationResult alloc] init];
+   classificationResult.classifications = classificationHeads;
+   return classificationResult;
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h
+index 99de5ad04febf..ac81a15ac11c6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h
+@@ -27,15 +27,17 @@ NS_ASSUME_NONNULL_BEGIN
+ @end
+ 
+ /**
+- * Classifier API for NLClassification tasks with Bert models, categorizes string into different
+- * classes. The API expects a Bert based TFLite model with metadata populated.
++ * Classifier API for NLClassification tasks with Bert models, categorizes
++ * string into different classes. The API expects a Bert based TFLite model with
++ * metadata populated.
+  *
+  * The metadata should contain the following information:
+  *   1 input_process_unit for Wordpiece/Sentencepiece Tokenizer.
+  *   3 input tensors with names "ids", "mask" and "segment_ids".
+- *   1 output tensor of type float32[1, 2], with a optionally attached label file. If a label
+- *     file is attached, the file should be a plain text file with one label per line, the number
+- *     of labels should match the number of categories the model outputs.
++ *   1 output tensor of type float32[1, 2], with a optionally attached label
++ * file. If a label file is attached, the file should be a plain text file with
++ * one label per line, the number of labels should match the number of
++ * categories the model outputs.
+  */
+ @interface TFLBertNLClassifier : NSObject
+ 
+@@ -45,7 +47,7 @@ NS_ASSUME_NONNULL_BEGIN
+  * @param modelPath Path to the classification model.
+  * @return A TFLBertNLClassifier instance.
+  */
+-+ (instancetype)bertNLClassifierWithModelPath:(NSString *)modelPath
+++ (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath
+     NS_SWIFT_NAME(bertNLClassifier(modelPath:));
+ 
+ /**
+@@ -54,8 +56,9 @@ NS_ASSUME_NONNULL_BEGIN
+  * @param modelPath Path to the classification model.
+  * @return A TFLBertNLClassifier instance.
+  */
+-+ (instancetype)bertNLClassifierWithModelPath:(NSString *)modelPath
+-                                      options:(TFLBertNLClassifierOptions *)options
+++ (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath
++                                      options:
++                                          (TFLBertNLClassifierOptions*)options
+     NS_SWIFT_NAME(bertNLClassifier(modelPath:options:));
+ 
+ /**
+@@ -65,7 +68,7 @@ NS_ASSUME_NONNULL_BEGIN
+  * @param text input text to the model.
+  * @return A NSDictionary of categorization results.
+  */
+-- (NSDictionary<NSString *, NSNumber *> *)classifyWithText:(NSString *)text
++- (NSDictionary<NSString*, NSNumber*>*)classifyWithText:(NSString*)text
+     NS_SWIFT_NAME(classify(text:));
+ @end
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m
+index e9d3b3dbbd1e3..8c45ee62cceea 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m
+@@ -25,7 +25,7 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLBertNLClassifier ()
+ /** BertNLClassifier backed by C API */
+-@property(nonatomic) TfLiteBertNLClassifier *bertNLClassifier;
++@property(nonatomic) TfLiteBertNLClassifier* bertNLClassifier;
+ @end
+ 
+ @implementation TFLBertNLClassifier
+@@ -34,24 +34,28 @@ NS_ASSUME_NONNULL_BEGIN
+   TfLiteBertNLClassifierDelete(_bertNLClassifier);
+ }
+ 
+-+ (instancetype)bertNLClassifierWithModelPath:(NSString *)modelPath {
+-  TfLiteBertNLClassifier *classifier = TfLiteBertNLClassifierCreate(modelPath.UTF8String);
+++ (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath {
++  TfLiteBertNLClassifier* classifier =
++      TfLiteBertNLClassifierCreate(modelPath.UTF8String);
+ 
+   _GTMDevAssert(classifier, @"Failed to create BertNLClassifier");
+   return [[TFLBertNLClassifier alloc] initWithBertNLClassifier:classifier];
+ }
+ 
+-+ (instancetype)bertNLClassifierWithModelPath:(NSString *)modelPath
+-                                  options:(TFLBertNLClassifierOptions *)options {
+-  // Note that maxSeqLen has been deprecated. Passing it to the C API is a no-op.
+++ (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath
++                                      options:
++                                          (TFLBertNLClassifierOptions*)options {
++  // Note that maxSeqLen has been deprecated. Passing it to the C API is a
++  // no-op.
+   TfLiteBertNLClassifierOptions cOptions = {.max_seq_len = options.maxSeqLen};
+-  TfLiteBertNLClassifier *classifier =
++  TfLiteBertNLClassifier* classifier =
+       TfLiteBertNLClassifierCreateFromOptions(modelPath.UTF8String, &cOptions);
+   _GTMDevAssert(classifier, @"Failed to create BertNLClassifier");
+   return [[TFLBertNLClassifier alloc] initWithBertNLClassifier:classifier];
+ }
+ 
+-- (instancetype)initWithBertNLClassifier:(TfLiteBertNLClassifier *)bertNLClassifier {
++- (instancetype)initWithBertNLClassifier:
++    (TfLiteBertNLClassifier*)bertNLClassifier {
+   self = [super init];
+   if (self) {
+     _bertNLClassifier = bertNLClassifier;
+@@ -59,9 +63,11 @@ NS_ASSUME_NONNULL_BEGIN
+   return self;
+ }
+ 
+-- (NSDictionary<NSString *, NSNumber *> *)classifyWithText:(NSString *)text {
+-  Categories *cCategories = TfLiteBertNLClassifierClassify(_bertNLClassifier, text.UTF8String);
+-  NSMutableDictionary<NSString *, NSNumber *> *ret = [NSMutableDictionary dictionary];
++- (NSDictionary<NSString*, NSNumber*>*)classifyWithText:(NSString*)text {
++  Categories* cCategories =
++      TfLiteBertNLClassifierClassify(_bertNLClassifier, text.UTF8String);
++  NSMutableDictionary<NSString*, NSNumber*>* ret =
++      [NSMutableDictionary dictionary];
+   for (int i = 0; i < cCategories->size; i++) {
+     Category cCategory = cCategories->categories[i];
+     [ret setValue:[NSNumber numberWithDouble:cCategory.score]
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.h
+index ceb8d2ef9a307..41eb0fb76c9ea 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.h
+@@ -23,14 +23,14 @@ NS_ASSUME_NONNULL_BEGIN
+ @property(nonatomic) int inputTensorIndex;
+ @property(nonatomic) int outputScoreTensorIndex;
+ @property(nonatomic) int outputLabelTensorIndex;
+-@property(nonatomic) NSString *inputTensorName;
+-@property(nonatomic) NSString *outputScoreTensorName;
+-@property(nonatomic) NSString *outputLabelTensorName;
++@property(nonatomic) NSString* inputTensorName;
++@property(nonatomic) NSString* outputScoreTensorName;
++@property(nonatomic) NSString* outputLabelTensorName;
+ @end
+ 
+ /**
+- * Classifier API for natural language classification tasks, categorizes string into different
+- * classes.
++ * Classifier API for natural language classification tasks, categorizes string
++ * into different classes.
+  *
+  * The API expects a TFLite model with the following input/output tensor:
+  *
+@@ -39,25 +39,28 @@ NS_ASSUME_NONNULL_BEGIN
+  *
+  *   Output score tensor
+  *     (kTfLiteUInt8/kTfLiteInt8/kTfLiteInt16/kTfLiteFloat32/kTfLiteFloat64/kTfLiteBool)
+- *     output scores for each class, if type is one of the Int types, dequantize it, if it
+- *       is Bool type, convert the values to 0.0 and 1.0 respectively.
++ *     output scores for each class, if type is one of the Int types, dequantize
++ * it, if it is Bool type, convert the values to 0.0 and 1.0 respectively.
+  *
+- *     can have an optional associated file in metadata for labels, the file should be a
+- *       plain text file with one label per line, the number of labels should match the number
+- *       of categories the model outputs. Output label tensor: optional (kTfLiteString) -
+- *       output classname for each class, should be of the same length with scores. If this
+- *       tensor is not present, the API uses score indices as classnames. - will be ignored if
+- *       output score tensor already has an associated label file.
++ *     can have an optional associated file in metadata for labels, the file
++ * should be a plain text file with one label per line, the number of labels
++ * should match the number of categories the model outputs. Output label tensor:
++ * optional (kTfLiteString) - output classname for each class, should be of the
++ * same length with scores. If this tensor is not present, the API uses score
++ * indices as classnames. - will be ignored if output score tensor already has
++ * an associated label file.
+  *
+  *   Optional Output label tensor (kTfLiteString/kTfLiteInt32)
+- *     output classname for each class, should be of the same length with scores. If this
+- *       tensor is not present, the API uses score indices as classnames.
++ *     output classname for each class, should be of the same length with
++ * scores. If this tensor is not present, the API uses score indices as
++ * classnames.
+  *
+- *     will be ignored if output score tensor already has an associated labe file.
++ *     will be ignored if output score tensor already has an associated labe
++ * file.
+  *
+- * By default the API tries to find the input/output tensors with default configurations in
+- * TFLNLClassifierOptions, with tensor name prioritized over tensor index. The option is
+- * configurable for different TFLite models.
++ * By default the API tries to find the input/output tensors with default
++ * configurations in TFLNLClassifierOptions, with tensor name prioritized over
++ * tensor index. The option is configurable for different TFLite models.
+  */
+ @interface TFLNLClassifier : NSObject
+ 
+@@ -69,8 +72,8 @@ NS_ASSUME_NONNULL_BEGIN
+  *
+  * @return A TFLNLClassifier instance.
+  */
+-+ (instancetype)nlClassifierWithModelPath:(NSString *)modelPath
+-                                  options:(TFLNLClassifierOptions *)options
+++ (instancetype)nlClassifierWithModelPath:(NSString*)modelPath
++                                  options:(TFLNLClassifierOptions*)options
+     NS_SWIFT_NAME(nlClassifier(modelPath:options:));
+ 
+ /**
+@@ -80,7 +83,7 @@ NS_ASSUME_NONNULL_BEGIN
+  * @param text input text to the model.
+  * @return A NSDictionary of categorization results.
+  */
+-- (NSDictionary<NSString *, NSNumber *> *)classifyWithText:(NSString *)text
++- (NSDictionary<NSString*, NSNumber*>*)classifyWithText:(NSString*)text
+     NS_SWIFT_NAME(classify(text:));
+ @end
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m
+index 8d21a111345d2..39eb15c71681c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m
+@@ -30,7 +30,7 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLNLClassifier ()
+ /** NLClassifier backed by C API */
+-@property(nonatomic) TfLiteNLClassifier *nlClassifier;
++@property(nonatomic) TfLiteNLClassifier* nlClassifier;
+ @end
+ 
+ @implementation TFLNLClassifier
+@@ -39,8 +39,8 @@ NS_ASSUME_NONNULL_BEGIN
+   TfLiteNLClassifierDelete(_nlClassifier);
+ }
+ 
+-+ (instancetype)nlClassifierWithModelPath:(NSString *)modelPath
+-                                  options:(TFLNLClassifierOptions *)options {
+++ (instancetype)nlClassifierWithModelPath:(NSString*)modelPath
++                                  options:(TFLNLClassifierOptions*)options {
+   TfLiteNLClassifierOptions cOptions = {
+       .input_tensor_index = options.inputTensorIndex,
+       .output_score_tensor_index = options.outputScoreTensorIndex,
+@@ -48,13 +48,13 @@ NS_ASSUME_NONNULL_BEGIN
+       .input_tensor_name = options.inputTensorName.UTF8String,
+       .output_score_tensor_name = options.outputScoreTensorName.UTF8String,
+       .output_label_tensor_name = options.outputLabelTensorName.UTF8String};
+-  TfLiteNLClassifier *classifier =
++  TfLiteNLClassifier* classifier =
+       TfLiteNLClassifierCreateFromOptions(modelPath.UTF8String, &cOptions);
+   _GTMDevAssert(classifier, @"Failed to create NLClassifier");
+   return [[TFLNLClassifier alloc] initWithNLClassifier:classifier];
+ }
+ 
+-- (instancetype)initWithNLClassifier:(TfLiteNLClassifier *)nlClassifier {
++- (instancetype)initWithNLClassifier:(TfLiteNLClassifier*)nlClassifier {
+   self = [super init];
+   if (self) {
+     _nlClassifier = nlClassifier;
+@@ -62,9 +62,11 @@ NS_ASSUME_NONNULL_BEGIN
+   return self;
+ }
+ 
+-- (NSDictionary<NSString *, NSNumber *> *)classifyWithText:(NSString *)text {
+-  Categories *cCategories = TfLiteNLClassifierClassify(_nlClassifier, text.UTF8String);
+-  NSMutableDictionary<NSString *, NSNumber *> *ret = [NSMutableDictionary dictionary];
++- (NSDictionary<NSString*, NSNumber*>*)classifyWithText:(NSString*)text {
++  Categories* cCategories =
++      TfLiteNLClassifierClassify(_nlClassifier, text.UTF8String);
++  NSMutableDictionary<NSString*, NSNumber*>* ret =
++      [NSMutableDictionary dictionary];
+   for (int i = 0; i < cCategories->size; i++) {
+     Category cCategory = cCategories->categories[i];
+     [ret setValue:[NSNumber numberWithDouble:cCategory.score]
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m
+index 9734fe7987a5e..407be10c1381c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m
+@@ -19,8 +19,8 @@ limitations under the License.
+ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLBertNLClassifierTest : XCTestCase
+-@property(nonatomic, nullable) NSString *bertModelPath;
+-@property(nonatomic, nullable) TFLBertNLClassifierOptions *modelOptions;
++@property(nonatomic, nullable) NSString* bertModelPath;
++@property(nonatomic, nullable) TFLBertNLClassifierOptions* modelOptions;
+ @end
+ 
+ @implementation TFLBertNLClassifierTest
+@@ -28,30 +28,31 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ - (void)setUp {
+   [super setUp];
+-  NSBundle *bundle = [NSBundle bundleForClass:[self class]];
+-  self.bertModelPath = [bundle pathForResource:@"bert_nl_classifier" ofType:@"tflite"];
++  NSBundle* bundle = [NSBundle bundleForClass:[self class]];
++  self.bertModelPath = [bundle pathForResource:@"bert_nl_classifier"
++                                        ofType:@"tflite"];
+ }
+ 
+ - (void)testClassifyPositiveResult {
+-  TFLBertNLClassifier *bertNLClassifier =
++  TFLBertNLClassifier* bertNLClassifier =
+       [TFLBertNLClassifier bertNLClassifierWithModelPath:self.bertModelPath];
+ 
+   XCTAssertNotNil(bertNLClassifier);
+ 
+-  NSDictionary<NSString *, NSNumber *> *categories =
+-      [bertNLClassifier classifyWithText:@"it's a charming and often affecting journey"];
++  NSDictionary<NSString*, NSNumber*>* categories = [bertNLClassifier
++      classifyWithText:@"it's a charming and often affecting journey"];
+ 
+   XCTAssertGreaterThan([categories[@"positive"] doubleValue],
+                        [categories[@"negative"] doubleValue]);
+ }
+ 
+ - (void)testClassifyNegativeResult {
+-  TFLBertNLClassifier *bertNLClassifier =
++  TFLBertNLClassifier* bertNLClassifier =
+       [TFLBertNLClassifier bertNLClassifierWithModelPath:self.bertModelPath];
+ 
+   XCTAssertNotNil(bertNLClassifier);
+ 
+-  NSDictionary<NSString *, NSNumber *> *categories =
++  NSDictionary<NSString*, NSNumber*>* categories =
+       [bertNLClassifier classifyWithText:@"unflinchingly bleak and desperate"];
+ 
+   XCTAssertGreaterThan([categories[@"negative"] doubleValue],
+@@ -62,14 +63,14 @@ NS_ASSUME_NONNULL_BEGIN
+   self.modelOptions = [[TFLBertNLClassifierOptions alloc] init];
+   [self.modelOptions setMaxSeqLen:128];
+ 
+-  TFLBertNLClassifier *bertNLClassifier =
++  TFLBertNLClassifier* bertNLClassifier =
+       [TFLBertNLClassifier bertNLClassifierWithModelPath:self.bertModelPath
+                                                  options:self.modelOptions];
+ 
+   XCTAssertNotNil(bertNLClassifier);
+ 
+-  NSDictionary<NSString *, NSNumber *> *categories =
+-      [bertNLClassifier classifyWithText:@"it's a charming and often affecting journey"];
++  NSDictionary<NSString*, NSNumber*>* categories = [bertNLClassifier
++      classifyWithText:@"it's a charming and often affecting journey"];
+ 
+   XCTAssertGreaterThan([categories[@"positive"] doubleValue],
+                        [categories[@"negative"] doubleValue]);
+@@ -79,13 +80,13 @@ NS_ASSUME_NONNULL_BEGIN
+   self.modelOptions = [[TFLBertNLClassifierOptions alloc] init];
+   [self.modelOptions setMaxSeqLen:128];
+ 
+-  TFLBertNLClassifier *bertNLClassifier =
++  TFLBertNLClassifier* bertNLClassifier =
+       [TFLBertNLClassifier bertNLClassifierWithModelPath:self.bertModelPath
+                                                  options:self.modelOptions];
+ 
+   XCTAssertNotNil(bertNLClassifier);
+ 
+-  NSDictionary<NSString *, NSNumber *> *categories =
++  NSDictionary<NSString*, NSNumber*>* categories =
+       [bertNLClassifier classifyWithText:@"unflinchingly bleak and desperate"];
+ 
+   XCTAssertGreaterThan([categories[@"negative"] doubleValue],
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLNLClassifierTest.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLNLClassifierTest.m
+index 40814ac6409b0..1dcf08acc8c86 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLNLClassifierTest.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLNLClassifierTest.m
+@@ -19,8 +19,8 @@ limitations under the License.
+ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLNLClassifierTest : XCTestCase
+-@property(nonatomic, nullable) NSString *modelPath;
+-@property(nonatomic, nullable) TFLNLClassifierOptions *modelOptions;
++@property(nonatomic, nullable) NSString* modelPath;
++@property(nonatomic, nullable) TFLNLClassifierOptions* modelOptions;
+ @end
+ 
+ @implementation TFLNLClassifierTest
+@@ -28,34 +28,38 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ - (void)setUp {
+   [super setUp];
+-  NSBundle *bundle = [NSBundle bundleForClass:[self class]];
+-  self.modelPath = [bundle pathForResource:@"test_model_nl_classifier_with_regex_tokenizer"
+-                                    ofType:@"tflite"];
++  NSBundle* bundle = [NSBundle bundleForClass:[self class]];
++  self.modelPath =
++      [bundle pathForResource:@"test_model_nl_classifier_with_regex_tokenizer"
++                       ofType:@"tflite"];
+   self.modelOptions = [[TFLNLClassifierOptions alloc] init];
+   [self.modelOptions setInputTensorName:@"input_text"];
+   [self.modelOptions setOutputScoreTensorName:@"probability"];
+ }
+ 
+ - (void)testClassifyPositiveResult {
+-  TFLNLClassifier *nlClassifier = [TFLNLClassifier nlClassifierWithModelPath:self.modelPath
+-                                                                     options:self.modelOptions];
++  TFLNLClassifier* nlClassifier =
++      [TFLNLClassifier nlClassifierWithModelPath:self.modelPath
++                                         options:self.modelOptions];
+ 
+   XCTAssertNotNil(nlClassifier);
+ 
+-  NSDictionary<NSString *, NSNumber *> *categories = [nlClassifier
+-      classifyWithText:@"This is the best movie I’ve seen in recent years. Strongly recommend it!"];
++  NSDictionary<NSString*, NSNumber*>* categories =
++      [nlClassifier classifyWithText:@"This is the best movie I’ve seen in "
++                                     @"recent years. Strongly recommend it!"];
+ 
+   XCTAssertGreaterThan([categories[@"Positive"] doubleValue],
+                        [categories[@"Negative"] doubleValue]);
+ }
+ 
+ - (void)testClassifyNegativeResult {
+-  TFLNLClassifier *nlClassifier = [TFLNLClassifier nlClassifierWithModelPath:self.modelPath
+-                                                                     options:self.modelOptions];
++  TFLNLClassifier* nlClassifier =
++      [TFLNLClassifier nlClassifierWithModelPath:self.modelPath
++                                         options:self.modelOptions];
+ 
+   XCTAssertNotNil(nlClassifier);
+ 
+-  NSDictionary<NSString *, NSNumber *> *categories =
++  NSDictionary<NSString*, NSNumber*>* categories =
+       [nlClassifier classifyWithText:@"What a waste of my time."];
+ 
+   XCTAssertGreaterThan([categories[@"Negative"] doubleValue],
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.h
+index 57b7c69c70f62..446e2cb137dd9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.h
+@@ -54,13 +54,13 @@ struct TFLPos {
+  * @param modelPath The file path to the tflite model.
+  * @return A BertQuestionAnswerer instance.
+  */
+-+ (instancetype)questionAnswererWithModelPath:(NSString *)modelPath
+++ (instancetype)questionAnswererWithModelPath:(NSString*)modelPath
+     NS_SWIFT_NAME(questionAnswerer(modelPath:));
+ 
+ /**
+  * Answers question based on the context. Could be empty if no answer was found
+  * from the given context.
+- * 
++ *
+  * @param context Context the question bases on.
+  * @param question Question to ask.
+  *
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m
+index a07f8753fbae3..b470c4643111e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m
+@@ -25,7 +25,7 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLBertQuestionAnswerer ()
+ /** BertQuestionAnswerer backed by C API */
+-@property(nonatomic) TfLiteBertQuestionAnswerer *bertQuestionAnswerer;
++@property(nonatomic) TfLiteBertQuestionAnswerer* bertQuestionAnswerer;
+ @end
+ 
+ @implementation TFLBertQuestionAnswerer
+@@ -34,14 +34,16 @@ NS_ASSUME_NONNULL_BEGIN
+   TfLiteBertQuestionAnswererDelete(_bertQuestionAnswerer);
+ }
+ 
+-+ (instancetype)questionAnswererWithModelPath:(NSString *)modelPath {
+-  TfLiteBertQuestionAnswerer *bert_qa = TfLiteBertQuestionAnswererCreate(modelPath.UTF8String);
+++ (instancetype)questionAnswererWithModelPath:(NSString*)modelPath {
++  TfLiteBertQuestionAnswerer* bert_qa =
++      TfLiteBertQuestionAnswererCreate(modelPath.UTF8String);
+ 
+   _GTMDevAssert(bert_qa, @"Failed to create BertQuestionAnswerer");
+   return [[TFLBertQuestionAnswerer alloc] initWithBertQuestionAnswerer:bert_qa];
+ }
+ 
+-- (instancetype)initWithBertQuestionAnswerer:(TfLiteBertQuestionAnswerer *)bertQuestionAnswerer {
++- (instancetype)initWithBertQuestionAnswerer:
++    (TfLiteBertQuestionAnswerer*)bertQuestionAnswerer {
+   self = [super init];
+   if (self) {
+     _bertQuestionAnswerer = bertQuestionAnswerer;
+@@ -49,14 +51,17 @@ NS_ASSUME_NONNULL_BEGIN
+   return self;
+ }
+ 
+-- (NSArray<TFLQAAnswer *> *)answerWithContext:(NSString *)context question:(NSString *)question {
+-  TfLiteQaAnswers *cAnswers = TfLiteBertQuestionAnswererAnswer(
++- (NSArray<TFLQAAnswer*>*)answerWithContext:(NSString*)context
++                                   question:(NSString*)question {
++  TfLiteQaAnswers* cAnswers = TfLiteBertQuestionAnswererAnswer(
+       _bertQuestionAnswerer, context.UTF8String, question.UTF8String);
+-  NSMutableArray<TFLQAAnswer *> *ret = [NSMutableArray arrayWithCapacity:cAnswers->size];
++  NSMutableArray<TFLQAAnswer*>* ret =
++      [NSMutableArray arrayWithCapacity:cAnswers->size];
+   for (int i = 0; i < cAnswers->size; i++) {
+     TfLiteQaAnswer cAnswer = cAnswers->answers[i];
+-    TFLQAAnswer *answer = [[TFLQAAnswer alloc] init];
+-    struct TFLPos pos = {.start = cAnswer.start, .end = cAnswer.end, .logit = cAnswer.logit};
++    TFLQAAnswer* answer = [[TFLQAAnswer alloc] init];
++    struct TFLPos pos = {
++        .start = cAnswer.start, .end = cAnswer.end, .logit = cAnswer.logit};
+     [answer setPos:pos];
+     [answer setText:[NSString stringWithUTF8String:cAnswer.text]];
+     [ret addObject:answer];
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Tests/TFLBertQuestionAnswererTest.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Tests/TFLBertQuestionAnswererTest.m
+index 9061063096cb4..ac4a1d3be63ef 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Tests/TFLBertQuestionAnswererTest.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Tests/TFLBertQuestionAnswererTest.m
+@@ -16,7 +16,7 @@ limitations under the License.
+ 
+ #import <XCTest/XCTest.h>
+ 
+-static NSString *const kContext =
++static NSString* const kContext =
+     @"The role of teacher is often formal and ongoing, carried out at a school "
+      "or other place of formal education. In many countries, a person who "
+      "wishes to become a teacher must first obtain specified professional "
+@@ -27,12 +27,12 @@ static NSString *const kContext =
+      "continuing professional development. Teachers may use a lesson plan to "
+      "facilitate student learning, providing a course of study which is called "
+      "the curriculum.";
+-static NSString *const kQuestion = @"What is a course of study called?";
+-static NSString *const kAnswer = @"the curriculum.";
++static NSString* const kQuestion = @"What is a course of study called?";
++static NSString* const kAnswer = @"the curriculum.";
+ 
+ @interface TFLBertQuestionAnswererTest : XCTestCase
+-@property(nonatomic, nullable) NSString *mobileBertModelPath;
+-@property(nonatomic, nullable) NSString *albertModelPath;
++@property(nonatomic, nullable) NSString* mobileBertModelPath;
++@property(nonatomic, nullable) NSString* albertModelPath;
+ @end
+ 
+ @implementation TFLBertQuestionAnswererTest
+@@ -40,32 +40,33 @@ static NSString *const kAnswer = @"the curriculum.";
+ 
+ - (void)setUp {
+   [super setUp];
+-  NSBundle *bundle = [NSBundle bundleForClass:[self class]];
+-  self.mobileBertModelPath = [bundle pathForResource:@"mobilebert_with_metadata" ofType:@"tflite"];
+-  self.albertModelPath = [bundle pathForResource:@"albert_with_metadata" ofType:@"tflite"];
++  NSBundle* bundle = [NSBundle bundleForClass:[self class]];
++  self.mobileBertModelPath = [bundle pathForResource:@"mobilebert_with_metadata"
++                                              ofType:@"tflite"];
++  self.albertModelPath = [bundle pathForResource:@"albert_with_metadata"
++                                          ofType:@"tflite"];
+ }
+ 
+ - (void)testInitMobileBert {
+-  TFLBertQuestionAnswerer* mobileBertAnswerer =
+-    [TFLBertQuestionAnswerer questionAnswererWithModelPath:self.mobileBertModelPath];
++  TFLBertQuestionAnswerer* mobileBertAnswerer = [TFLBertQuestionAnswerer
++      questionAnswererWithModelPath:self.mobileBertModelPath];
+ 
+   XCTAssertNotNil(mobileBertAnswerer);
+ 
+   NSArray<TFLQAAnswer*>* answers =
+-    [mobileBertAnswerer answerWithContext:kContext question:kQuestion];
++      [mobileBertAnswerer answerWithContext:kContext question:kQuestion];
+ 
+   XCTAssertEqualObjects([answers[0] text], kAnswer);
+ }
+ 
+ - (void)testInitAlbert {
+-  TFLBertQuestionAnswerer* albertAnswerer =
+-    [TFLBertQuestionAnswerer questionAnswererWithModelPath:self.albertModelPath];
++  TFLBertQuestionAnswerer* albertAnswerer = [TFLBertQuestionAnswerer
++      questionAnswererWithModelPath:self.albertModelPath];
+ 
+   XCTAssertNotNil(albertAnswerer);
+ 
+-  NSArray<TFLQAAnswer*>* answers =
+-    [albertAnswerer answerWithContext:kContext question:kQuestion];
+-
++  NSArray<TFLQAAnswer*>* answers = [albertAnswerer answerWithContext:kContext
++                                                            question:kQuestion];
+ 
+   XCTAssertEqualObjects([answers[0] text], kAnswer);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h
+index c37f22f3fb9aa..1b988f2be9737 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h
+@@ -30,27 +30,29 @@ NS_ASSUME_NONNULL_BEGIN
+  * Base options that is used for creation of any type of task.
+  * @seealso TFLBaseOptions
+  */
+-@property(nonatomic, copy) TFLBaseOptions *baseOptions;
++@property(nonatomic, copy) TFLBaseOptions* baseOptions;
+ 
+ /**
+  * Options that configure the display and filtering of results.
+  * @seealso TFLClassificationOptions
+  */
+-@property(nonatomic, copy) TFLClassificationOptions *classificationOptions;
++@property(nonatomic, copy) TFLClassificationOptions* classificationOptions;
+ 
+ /**
+- * Initializes TFLImageClassifierOptions with the model path set to the specified path to a model
+- * file.
+- * @description The external model file, must be a single standalone TFLite file. It could be packed
+- * with TFLite Model Metadata[1] and associated files if exist. Fail to provide the necessary
+- * metadata and associated files might result in errors. Check the [documentation]
+- * (https://www.tensorflow.org/lite/convert/metadata) for each task about the specific requirement.
++ * Initializes TFLImageClassifierOptions with the model path set to the
++ * specified path to a model file.
++ * @description The external model file, must be a single standalone TFLite
++ * file. It could be packed with TFLite Model Metadata[1] and associated files
++ * if exist. Fail to provide the necessary metadata and associated files might
++ * result in errors. Check the [documentation]
++ * (https://www.tensorflow.org/lite/convert/metadata) for each task about the
++ * specific requirement.
+  *
+  * @param modelPath Path to a TFLite model file.
+  * @return An instance of TFLImageClassifierOptions set to the specified
+  * modelPath.
+  */
+-- (nullable instancetype)initWithModelPath:(nonnull NSString *)modelPath;
++- (nullable instancetype)initWithModelPath:(nonnull NSString*)modelPath;
+ 
+ @end
+ 
+@@ -67,8 +69,9 @@ NS_ASSUME_NONNULL_BEGIN
+  *
+  * @return A TFLImageClassifier instance.
+  */
+-+ (nullable instancetype)imageClassifierWithOptions:(nonnull TFLImageClassifierOptions *)options
+-                                              error:(NSError **)error
+++ (nullable instancetype)imageClassifierWithOptions:
++                             (nonnull TFLImageClassifierOptions*)options
++                                              error:(NSError**)error
+     NS_SWIFT_NAME(imageClassifier(options:));
+ 
+ /**
+@@ -79,8 +82,9 @@ NS_ASSUME_NONNULL_BEGIN
+  * @param image input to the model.
+  * @return An NSArray<NSArray<TFLClass *>*> * of classification results.
+  */
+-- (nullable TFLClassificationResult *)classifyWithGMLImage:(GMLImage *)image
+-                                                     error:(NSError *_Nullable *)error
++- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
++                                                    error:(NSError* _Nullable*)
++                                                              error
+     NS_SWIFT_NAME(classify(gmlImage:));
+ 
+ /**
+@@ -94,9 +98,10 @@ NS_ASSUME_NONNULL_BEGIN
+  *
+  * @return An NSArray<NSArray<TFLClass *>*> * of classification results.
+  */
+-- (nullable TFLClassificationResult *)classifyWithGMLImage:(GMLImage *)image
+-                                          regionOfInterest:(CGRect)roi
+-                                                     error:(NSError *_Nullable *)error
++- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
++                                         regionOfInterest:(CGRect)roi
++                                                    error:(NSError* _Nullable*)
++                                                              error
+     NS_SWIFT_NAME(classify(gmlImage:regionOfInterest:));
+ 
+ - (instancetype)init NS_UNAVAILABLE;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m
+index b0a6b005b2a2d..06d6793340269 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m
+@@ -24,7 +24,7 @@
+ 
+ @interface TFLImageClassifier ()
+ /** ImageClassifier backed by C API */
+-@property(nonatomic) TfLiteImageClassifier *imageClassifier;
++@property(nonatomic) TfLiteImageClassifier* imageClassifier;
+ @end
+ 
+ @implementation TFLImageClassifierOptions
+@@ -40,7 +40,7 @@
+   return self;
+ }
+ 
+-- (nullable instancetype)initWithModelPath:(nonnull NSString *)modelPath {
++- (nullable instancetype)initWithModelPath:(nonnull NSString*)modelPath {
+   self = [self init];
+   if (self) {
+     self.baseOptions.modelFile.filePath = modelPath;
+@@ -55,7 +55,8 @@
+   TfLiteImageClassifierDelete(_imageClassifier);
+ }
+ 
+-- (instancetype)initWithImageClassifier:(TfLiteImageClassifier *)imageClassifier {
++- (instancetype)initWithImageClassifier:
++    (TfLiteImageClassifier*)imageClassifier {
+   self = [super init];
+   if (self) {
+     _imageClassifier = imageClassifier;
+@@ -63,25 +64,28 @@
+   return self;
+ }
+ 
+-+ (nullable instancetype)imageClassifierWithOptions:(nonnull TFLImageClassifierOptions *)options
+-                                              error:(NSError **)error {
+++ (nullable instancetype)imageClassifierWithOptions:
++                             (nonnull TFLImageClassifierOptions*)options
++                                              error:(NSError**)error {
+   TfLiteImageClassifierOptions cOptions = TfLiteImageClassifierOptionsCreate();
+   if (![options.classificationOptions
+-          copyClassificationOptionsToCClassificationOptions:&(cOptions.classification_options)
++          copyClassificationOptionsToCClassificationOptions:
++              &(cOptions.classification_options)
+                                                       error:error])
+     return nil;
+ 
+   [options.baseOptions copyBaseOptionsToCBaseOptions:&(cOptions.base_options)];
+ 
+-  TfLiteSupportError *createClassifierError = nil;
+-  TfLiteImageClassifier *imageClassifier =
++  TfLiteSupportError* createClassifierError = nil;
++  TfLiteImageClassifier* imageClassifier =
+       TfLiteImageClassifierFromOptions(&cOptions, &createClassifierError);
+ 
+-  [options.classificationOptions
+-      deleteCStringArraysOfClassificationOptions:&(cOptions.classification_options)];
++  [options.classificationOptions deleteCStringArraysOfClassificationOptions:
++                                     &(cOptions.classification_options)];
+ 
+   if (!imageClassifier) {
+-    [TFLCommonUtils errorFromTfLiteSupportError:createClassifierError error:error];
++    [TFLCommonUtils errorFromTfLiteSupportError:createClassifierError
++                                          error:error];
+     TfLiteSupportErrorDelete(createClassifierError);
+     return nil;
+   }
+@@ -89,17 +93,20 @@
+   return [[TFLImageClassifier alloc] initWithImageClassifier:imageClassifier];
+ }
+ 
+-- (nullable TFLClassificationResult *)classifyWithGMLImage:(GMLImage *)image
+-                                                     error:(NSError *_Nullable *)error {
++- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
++                                                    error:(NSError* _Nullable*)
++                                                              error {
+   return [self classifyWithGMLImage:image
+                    regionOfInterest:CGRectMake(0, 0, image.width, image.height)
+                               error:error];
+ }
+ 
+-- (nullable TFLClassificationResult *)classifyWithGMLImage:(GMLImage *)image
+-                                          regionOfInterest:(CGRect)roi
+-                                                     error:(NSError *_Nullable *)error {
+-  TfLiteFrameBuffer *cFrameBuffer = [GMLImageUtils cFrameBufferFromGMLImage:image error:error];
++- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
++                                         regionOfInterest:(CGRect)roi
++                                                    error:(NSError* _Nullable*)
++                                                              error {
++  TfLiteFrameBuffer* cFrameBuffer =
++      [GMLImageUtils cFrameBufferFromGMLImage:image error:error];
+ 
+   if (!cFrameBuffer) {
+     return nil;
+@@ -110,9 +117,10 @@
+                                    .width = roi.size.width,
+                                    .height = roi.size.height};
+ 
+-  TfLiteSupportError *classifyError = nil;
+-  TfLiteClassificationResult *cClassificationResult = TfLiteImageClassifierClassifyWithRoi(
+-      _imageClassifier, cFrameBuffer, &boundingBox, &classifyError);
++  TfLiteSupportError* classifyError = nil;
++  TfLiteClassificationResult* cClassificationResult =
++      TfLiteImageClassifierClassifyWithRoi(_imageClassifier, cFrameBuffer,
++                                           &boundingBox, &classifyError);
+ 
+   free(cFrameBuffer->buffer);
+   cFrameBuffer->buffer = nil;
+@@ -126,8 +134,8 @@
+     return nil;
+   }
+ 
+-  TFLClassificationResult *classificationHeadsResults =
+-      [TFLClassificationUtils classificationResultFromCClassificationResults:cClassificationResult];
++  TFLClassificationResult* classificationHeadsResults = [TFLClassificationUtils
++      classificationResultFromCClassificationResults:cClassificationResult];
+   TfLiteClassificationResultDelete(cClassificationResult);
+ 
+   return classificationHeadsResults;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h
+index 4ae67d11665b4..298485b3ceda2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h
+@@ -37,8 +37,9 @@ NS_ASSUME_NONNULL_BEGIN
+  * @return The TfLiteFrameBuffer created from the gmlImage which can be used
+  * with the TF Lite Task Vision C library.
+  */
+-+ (nullable TfLiteFrameBuffer *)cFrameBufferFromGMLImage:(GMLImage *)gmlImage
+-                                                   error:(NSError *_Nullable *)error;
+++ (nullable TfLiteFrameBuffer*)cFrameBufferFromGMLImage:(GMLImage*)gmlImage
++                                                  error:(NSError* _Nullable*)
++                                                            error;
+ 
+ - (instancetype)init NS_UNAVAILABLE;
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m
+index 7f2a0611ce1f2..72425b39630d1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m
+@@ -24,18 +24,20 @@
+ #import <CoreVideo/CoreVideo.h>
+ 
+ @interface TFLCVPixelBufferUtils : NSObject
+-+ (uint8_t *_Nullable)convertBGRAtoRGBforPixelBufferBaseAddress:(CVPixelBufferRef)pixelBuffer
+-                                                          error:(NSError **)error;
+++ (uint8_t* _Nullable)
++    convertBGRAtoRGBforPixelBufferBaseAddress:(CVPixelBufferRef)pixelBuffer
++                                        error:(NSError**)error;
+ @end
+ 
+ @interface UIImage (RawPixelDataUtils)
+-- (TfLiteFrameBuffer *)frameBufferWithError:(NSError **)error;
++- (TfLiteFrameBuffer*)frameBufferWithError:(NSError**)error;
+ @end
+ 
+ @implementation TFLCVPixelBufferUtils
+ 
+-+ (uint8_t *)convertBGRAtoRGBforPixelBufferBaseAddress:(CVPixelBufferRef)pixelBuffer
+-                                                 error:(NSError **)error {
+++ (uint8_t*)convertBGRAtoRGBforPixelBufferBaseAddress:
++                (CVPixelBufferRef)pixelBuffer
++                                                error:(NSError**)error {
+   size_t width = CVPixelBufferGetWidth(pixelBuffer);
+   size_t height = CVPixelBufferGetHeight(pixelBuffer);
+   size_t stride = CVPixelBufferGetBytesPerRow(pixelBuffer);
+@@ -43,17 +45,21 @@
+   int destinationChannelCount = 3;
+   size_t destinationBytesPerRow = destinationChannelCount * width;
+ 
+-  uint8_t *pixelBufferBaseAddress = (uint8_t *)CVPixelBufferGetBaseAddress(pixelBuffer);
++  uint8_t* pixelBufferBaseAddress =
++      (uint8_t*)CVPixelBufferGetBaseAddress(pixelBuffer);
+ 
+-  uint8_t *destPixelBufferAddress = [TFLCommonUtils mallocWithSize:height * destinationBytesPerRow
+-                                                             error:error];
++  uint8_t* destPixelBufferAddress =
++      [TFLCommonUtils mallocWithSize:height * destinationBytesPerRow
++                               error:error];
+ 
+   if (!destPixelBufferAddress) {
+     return NULL;
+   }
+ 
+-  vImage_Buffer srcBuffer = {
+-      .data = pixelBufferBaseAddress, .height = height, .width = width, .rowBytes = stride};
++  vImage_Buffer srcBuffer = {.data = pixelBufferBaseAddress,
++                             .height = height,
++                             .width = width,
++                             .rowBytes = stride};
+ 
+   vImage_Buffer destBuffer = {.data = destPixelBufferAddress,
+                               .height = height,
+@@ -61,7 +67,8 @@
+                               .rowBytes = destinationBytesPerRow};
+ 
+   vImage_Error convertError = kvImageNoError;
+-  convertError = vImageConvert_BGRA8888toRGB888(&srcBuffer, &destBuffer, kvImageNoFlags);
++  convertError =
++      vImageConvert_BGRA8888toRGB888(&srcBuffer, &destBuffer, kvImageNoFlags);
+ 
+   if (convertError != kvImageNoError) {
+     [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeImageProcessingError
+@@ -78,8 +85,8 @@
+ 
+ @implementation UIImage (RawPixelDataUtils)
+ 
+-- (TfLiteFrameBuffer *)frameBufferWithError:(NSError **)error {
+-  TfLiteFrameBuffer *frameBuffer = NULL;
++- (TfLiteFrameBuffer*)frameBufferWithError:(NSError**)error {
++  TfLiteFrameBuffer* frameBuffer = NULL;
+ 
+   if (self.CGImage) {
+     frameBuffer = [self frameBufferFromCGImage:self.CGImage error:error];
+@@ -95,23 +102,25 @@
+   return frameBuffer;
+ }
+ 
+-+ (UInt8 *_Nullable)pixelDataFromCGImage:(CGImageRef)cgImage error:(NSError **)error {
+++ (UInt8* _Nullable)pixelDataFromCGImage:(CGImageRef)cgImage
++                                   error:(NSError**)error {
+   long width = CGImageGetWidth(cgImage);
+   long height = CGImageGetHeight(cgImage);
+ 
+   int bitsPerComponent = 8;
+-  UInt8 *buffer_to_return = NULL;
++  UInt8* buffer_to_return = NULL;
+ 
+   CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
+-  CGContextRef context = CGBitmapContextCreate(nil, width, height, bitsPerComponent, 0, colorSpace,
+-                                               kCGImageAlphaNoneSkipLast);
++  CGContextRef context =
++      CGBitmapContextCreate(nil, width, height, bitsPerComponent, 0, colorSpace,
++                            kCGImageAlphaNoneSkipLast);
+ 
+   if (context) {
+     CGContextDrawImage(context, CGRectMake(0, 0, width, height), cgImage);
+-    buffer_to_return =
+-        [UIImage populateRGBBufferFromSourceRGBABuffer:CGBitmapContextGetData(context)
+-                                                 width:width
+-                                                height:height];
++    buffer_to_return = [UIImage
++        populateRGBBufferFromSourceRGBABuffer:CGBitmapContextGetData(context)
++                                        width:width
++                                       height:height];
+     CGContextRelease(context);
+   }
+ 
+@@ -126,15 +135,16 @@
+   return buffer_to_return;
+ }
+ 
+-+ (nullable UInt8 *)populateRGBBufferFromSourceRGBABuffer:(UInt8 *)buffer
+-                                                    width:(size_t)width
+-                                                   height:(size_t)height {
+-  if (!buffer) return nil;
+++ (nullable UInt8*)populateRGBBufferFromSourceRGBABuffer:(UInt8*)buffer
++                                                   width:(size_t)width
++                                                  height:(size_t)height {
++  if (!buffer)
++    return nil;
+ 
+   int sourceChannelCount = 4;
+   int destChannelCount = 3;
+ 
+-  UInt8 *buffer_to_return = malloc(height * destChannelCount * width);
++  UInt8* buffer_to_return = malloc(height * destChannelCount * width);
+   if (!buffer_to_return) {
+     return nil;
+   }
+@@ -150,14 +160,15 @@
+   return buffer_to_return;
+ }
+ 
+-- (TfLiteFrameBuffer *)frameBufferFromCGImage:(CGImageRef)cgImage error:(NSError **)error {
+-  UInt8 *buffer = [UIImage pixelDataFromCGImage:cgImage error:error];
++- (TfLiteFrameBuffer*)frameBufferFromCGImage:(CGImageRef)cgImage
++                                       error:(NSError**)error {
++  UInt8* buffer = [UIImage pixelDataFromCGImage:cgImage error:error];
+ 
+   if (buffer == NULL) {
+     return NULL;
+   }
+ 
+-  TfLiteFrameBuffer *cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
++  TfLiteFrameBuffer* cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
+ 
+   cFrameBuffer->dimension.width = (int)CGImageGetWidth(cgImage);
+   cFrameBuffer->dimension.height = (int)CGImageGetHeight(cgImage);
+@@ -169,14 +180,16 @@
+   return cFrameBuffer;
+ }
+ 
+-- (TfLiteFrameBuffer *)frameBufferFromCIImage:(CIImage *)ciImage error:(NSError **)error {
+-  uint8_t *buffer = nil;
++- (TfLiteFrameBuffer*)frameBufferFromCIImage:(CIImage*)ciImage
++                                       error:(NSError**)error {
++  uint8_t* buffer = nil;
+ 
+   int width = 0;
+   int height = 0;
+   if (ciImage.pixelBuffer) {
+-    buffer = [TFLCVPixelBufferUtils convertBGRAtoRGBforPixelBufferBaseAddress:ciImage.pixelBuffer
+-                                                                        error:error];
++    buffer = [TFLCVPixelBufferUtils
++        convertBGRAtoRGBforPixelBufferBaseAddress:ciImage.pixelBuffer
++                                            error:error];
+     width = (int)CVPixelBufferGetWidth(ciImage.pixelBuffer);
+     height = (int)CVPixelBufferGetHeight(ciImage.pixelBuffer);
+ 
+@@ -195,7 +208,7 @@
+     return NULL;
+   }
+ 
+-  TfLiteFrameBuffer *cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
++  TfLiteFrameBuffer* cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
+   cFrameBuffer->buffer = buffer;
+   cFrameBuffer->dimension.width = width;
+   cFrameBuffer->dimension.height = height;
+@@ -210,41 +223,49 @@
+ 
+ @implementation GMLImageUtils
+ 
+-+ (nullable TfLiteFrameBuffer *)cFrameBufferFromGMLImage:(GMLImage *)gmlImage
+-                                                   error:(NSError *_Nullable *)error {
+-  TfLiteFrameBuffer *cFrameBuffer = NULL;
+++ (nullable TfLiteFrameBuffer*)cFrameBufferFromGMLImage:(GMLImage*)gmlImage
++                                                  error:(NSError* _Nullable*)
++                                                            error {
++  TfLiteFrameBuffer* cFrameBuffer = NULL;
+ 
+   switch (gmlImage.imageSourceType) {
+     case GMLImageSourceTypeSampleBuffer: {
+-      CVPixelBufferRef sampleImagePixelBuffer = CMSampleBufferGetImageBuffer(gmlImage.sampleBuffer);
+-      cFrameBuffer = [GMLImageUtils bufferFromCVPixelBuffer:sampleImagePixelBuffer error:error];
++      CVPixelBufferRef sampleImagePixelBuffer =
++          CMSampleBufferGetImageBuffer(gmlImage.sampleBuffer);
++      cFrameBuffer =
++          [GMLImageUtils bufferFromCVPixelBuffer:sampleImagePixelBuffer
++                                           error:error];
+       break;
+     }
+     case GMLImageSourceTypePixelBuffer: {
+-      cFrameBuffer = [GMLImageUtils bufferFromCVPixelBuffer:gmlImage.pixelBuffer error:error];
++      cFrameBuffer = [GMLImageUtils bufferFromCVPixelBuffer:gmlImage.pixelBuffer
++                                                      error:error];
+       break;
+     }
+     case GMLImageSourceTypeImage: {
+-      cFrameBuffer = [GMLImageUtils frameBufferFromUIImage:gmlImage.image error:error];
++      cFrameBuffer = [GMLImageUtils frameBufferFromUIImage:gmlImage.image
++                                                     error:error];
+     }
+ 
+     default:
+-      [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+-                              description:@"Invalid source type for GMLImage."
+-                                    error:error];
++      [TFLCommonUtils
++          customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
++                  description:@"Invalid source type for GMLImage."
++                        error:error];
+       break;
+   }
+ 
+   return cFrameBuffer;
+ }
+ 
+-+ (TfLiteFrameBuffer *)frameBufferFromUIImage:(UIImage *)image error:(NSError **)error {
+++ (TfLiteFrameBuffer*)frameBufferFromUIImage:(UIImage*)image
++                                       error:(NSError**)error {
+   return [image frameBufferWithError:error];
+ }
+ 
+-+ (TfLiteFrameBuffer *)bufferFromCVPixelBuffer:(CVPixelBufferRef)pixelBuffer
+-                                         error:(NSError **)error {
+-  uint8_t *buffer = nil;
+++ (TfLiteFrameBuffer*)bufferFromCVPixelBuffer:(CVPixelBufferRef)pixelBuffer
++                                        error:(NSError**)error {
++  uint8_t* buffer = nil;
+   enum TfLiteFrameBufferFormat cPixelFormat = kRGB;
+ 
+   CVPixelBufferLockBaseAddress(pixelBuffer, 0);
+@@ -253,25 +274,30 @@
+   switch (pixelBufferFormat) {
+     case kCVPixelFormatType_24RGB: {
+       cPixelFormat = kRGB;
+-      buffer = [GMLImageUtils copyPixelufferDataForInference:pixelBuffer error:error];
++      buffer = [GMLImageUtils copyPixelufferDataForInference:pixelBuffer
++                                                       error:error];
+       break;
+     }
+     case kCVPixelFormatType_32RGBA: {
+       cPixelFormat = kRGBA;
+-      buffer = [GMLImageUtils copyPixelufferDataForInference:pixelBuffer error:error];
++      buffer = [GMLImageUtils copyPixelufferDataForInference:pixelBuffer
++                                                       error:error];
+       break;
+     }
+     case kCVPixelFormatType_32BGRA: {
+       cPixelFormat = kRGB;
+-      buffer = [TFLCVPixelBufferUtils convertBGRAtoRGBforPixelBufferBaseAddress:pixelBuffer
+-                                                                          error:error];
++      buffer = [TFLCVPixelBufferUtils
++          convertBGRAtoRGBforPixelBufferBaseAddress:pixelBuffer
++                                              error:error];
+       break;
+     }
+ 
+     default: {
+-      [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+-                              description:@"Unsupported pixel format for TfLiteFrameBufferFormat."
+-                                    error:error];
++      [TFLCommonUtils
++          customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
++                  description:
++                      @"Unsupported pixel format for TfLiteFrameBufferFormat."
++                        error:error];
+       break;
+     }
+   }
+@@ -282,7 +308,7 @@
+     return nil;
+   }
+ 
+-  TfLiteFrameBuffer *cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
++  TfLiteFrameBuffer* cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
+ 
+   cFrameBuffer->dimension.width = (int)CVPixelBufferGetWidth(pixelBuffer);
+   cFrameBuffer->dimension.height = (int)CVPixelBufferGetHeight(pixelBuffer);
+@@ -292,12 +318,14 @@
+   return cFrameBuffer;
+ }
+ 
+-+ (UInt8 *)copyPixelufferDataForInference:(CVPixelBufferRef)pixelBuffer error:(NSError **)error {
+++ (UInt8*)copyPixelufferDataForInference:(CVPixelBufferRef)pixelBuffer
++                                   error:(NSError**)error {
+   size_t height = CVPixelBufferGetHeight(pixelBuffer);
+   size_t stride = CVPixelBufferGetBytesPerRow(pixelBuffer);
+-  UInt8 *buffer = [TFLCommonUtils mallocWithSize:height * stride error:error];
++  UInt8* buffer = [TFLCommonUtils mallocWithSize:height * stride error:error];
+ 
+-  if (buffer) memcpy(buffer, CVPixelBufferGetBaseAddress(pixelBuffer), height * stride);
++  if (buffer)
++    memcpy(buffer, CVPixelBufferGetBaseAddress(pixelBuffer), height * stride);
+ 
+   return buffer;
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m
+index b5f514397e41d..f26959434bbc9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m
+@@ -18,123 +18,140 @@
+ NS_ASSUME_NONNULL_BEGIN
+ 
+ @interface TFLImageClassifierTests : XCTestCase
+-@property(nonatomic, nullable) NSString *modelPath;
++@property(nonatomic, nullable) NSString* modelPath;
+ @end
+ 
+ @implementation TFLImageClassifierTests
+ 
+-- (GMLImage *)imageFromBundleWithName:(NSString *)name ofType:(NSString *)type {
+-  NSString *imagePath = [[NSBundle bundleForClass:[self class]] pathForResource:name ofType:type];
++- (GMLImage*)imageFromBundleWithName:(NSString*)name ofType:(NSString*)type {
++  NSString* imagePath =
++      [[NSBundle bundleForClass:[self class]] pathForResource:name ofType:type];
+   XCTAssertNotNil(imagePath);
+-  UIImage *image = [[UIImage alloc] initWithContentsOfFile:imagePath];
++  UIImage* image = [[UIImage alloc] initWithContentsOfFile:imagePath];
+   XCTAssertNotNil(image);
+ 
+-  GMLImage *gmlImage = [[GMLImage alloc] initWithImage:image];
++  GMLImage* gmlImage = [[GMLImage alloc] initWithImage:image];
+   XCTAssertNotNil(gmlImage);
+ 
+   return gmlImage;
+ }
+ - (void)setUp {
+-  // Put setup code here. This method is called before the invocation of each test method in the
+-  // class. static let bundle = Bundle(for: TFLSentencepieceTokenizerTest.self)
+-  self.modelPath = [[NSBundle bundleForClass:[self class]] pathForResource:@"mobilenet_v2_1.0_224"
+-                                                                    ofType:@"tflite"];
++  // Put setup code here. This method is called before the invocation of each
++  // test method in the class. static let bundle = Bundle(for:
++  // TFLSentencepieceTokenizerTest.self)
++  self.modelPath = [[NSBundle bundleForClass:[self class]]
++      pathForResource:@"mobilenet_v2_1.0_224"
++               ofType:@"tflite"];
+   XCTAssertNotNil(self.modelPath);
+ }
+ 
+ - (void)tearDown {
+-  // Put teardown code here. This method is called after the invocation of each test method in the
+-  // class.
++  // Put teardown code here. This method is called after the invocation of each
++  // test method in the class.
+ }
+ 
+ - (void)testSuccessfullImageInferenceOnMLImageWithUIImage {
+-  TFLImageClassifierOptions *imageClassifierOptions =
++  TFLImageClassifierOptions* imageClassifierOptions =
+       [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+ 
+-  TFLImageClassifier *imageClassifier =
+-      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions error:nil];
++  TFLImageClassifier* imageClassifier =
++      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
++                                               error:nil];
+   XCTAssertNotNil(imageClassifier);
+-  GMLImage *gmlImage = [self imageFromBundleWithName:@"burger" ofType:@"jpg"];
++  GMLImage* gmlImage = [self imageFromBundleWithName:@"burger" ofType:@"jpg"];
+ 
+-  TFLClassificationResult *classificationResults = [imageClassifier classifyWithGMLImage:gmlImage
+-                                                                                   error:nil];
++  TFLClassificationResult* classificationResults =
++      [imageClassifier classifyWithGMLImage:gmlImage error:nil];
+   XCTAssertTrue([classificationResults.classifications count] > 0);
+-  XCTAssertTrue([classificationResults.classifications[0].categories count] > 0);
++  XCTAssertTrue([classificationResults.classifications[0].categories count] >
++                0);
+ 
+-  TFLCategory *category = classificationResults.classifications[0].categories[0];
++  TFLCategory* category =
++      classificationResults.classifications[0].categories[0];
+   XCTAssertTrue([category.label isEqual:@"cheeseburger"]);
+   // TODO: match the score as image_classifier_test.cc
+   XCTAssertEqualWithAccuracy(category.score, 0.748976, 0.001);
+ }
+ 
+ - (void)testModelOptionsWithMaxResults {
+-  TFLImageClassifierOptions *imageClassifierOptions =
++  TFLImageClassifierOptions* imageClassifierOptions =
+       [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+   int maxResults = 3;
+   imageClassifierOptions.classificationOptions.maxResults = maxResults;
+ 
+-  TFLImageClassifier *imageClassifier =
+-      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions error:nil];
++  TFLImageClassifier* imageClassifier =
++      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
++                                               error:nil];
+   XCTAssertNotNil(imageClassifier);
+ 
+-  GMLImage *gmlImage = [self imageFromBundleWithName:@"burger" ofType:@"jpg"];
++  GMLImage* gmlImage = [self imageFromBundleWithName:@"burger" ofType:@"jpg"];
+ 
+-  TFLClassificationResult *classificationResults = [imageClassifier classifyWithGMLImage:gmlImage
+-                                                                                   error:nil];
++  TFLClassificationResult* classificationResults =
++      [imageClassifier classifyWithGMLImage:gmlImage error:nil];
+   XCTAssertTrue([classificationResults.classifications count] > 0);
+-  XCTAssertLessThanOrEqual([classificationResults.classifications[0].categories count], maxResults);
++  XCTAssertLessThanOrEqual(
++      [classificationResults.classifications[0].categories count], maxResults);
+ 
+-  TFLCategory *category = classificationResults.classifications[0].categories[0];
++  TFLCategory* category =
++      classificationResults.classifications[0].categories[0];
+   XCTAssertTrue([category.label isEqual:@"cheeseburger"]);
+   // TODO: match the score as image_classifier_test.cc
+   XCTAssertEqualWithAccuracy(category.score, 0.748976, 0.001);
+ }
+ 
+ - (void)testInferenceWithBoundingBox {
+-  TFLImageClassifierOptions *imageClassifierOptions =
++  TFLImageClassifierOptions* imageClassifierOptions =
+       [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+   int maxResults = 3;
+   imageClassifierOptions.classificationOptions.maxResults = maxResults;
+ 
+-  TFLImageClassifier *imageClassifier =
+-      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions error:nil];
++  TFLImageClassifier* imageClassifier =
++      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
++                                               error:nil];
+   XCTAssertNotNil(imageClassifier);
+ 
+-  GMLImage *gmlImage = [self imageFromBundleWithName:@"multi_objects" ofType:@"jpg"];
++  GMLImage* gmlImage = [self imageFromBundleWithName:@"multi_objects"
++                                              ofType:@"jpg"];
+ 
+   CGRect roi = CGRectMake(406, 110, 148, 153);
+-  TFLClassificationResult *classificationResults = [imageClassifier classifyWithGMLImage:gmlImage
+-                                                                        regionOfInterest:roi
+-                                                                                   error:nil];
++  TFLClassificationResult* classificationResults =
++      [imageClassifier classifyWithGMLImage:gmlImage
++                           regionOfInterest:roi
++                                      error:nil];
+   XCTAssertTrue([classificationResults.classifications count] > 0);
+-  XCTAssertTrue([classificationResults.classifications[0].categories count] > 0);
++  XCTAssertTrue([classificationResults.classifications[0].categories count] >
++                0);
+ 
+-  TFLCategory *category = classificationResults.classifications[0].categories[0];
++  TFLCategory* category =
++      classificationResults.classifications[0].categories[0];
+   // TODO: match the label and score as image_classifier_test.cc
+   // XCTAssertTrue([category.label isEqual:@"soccer ball"]);
+   // XCTAssertEqualWithAccuracy(category.score, 0.256512, 0.001);
+ }
+ 
+ - (void)testInferenceWithRGBAImage {
+-  TFLImageClassifierOptions *imageClassifierOptions =
++  TFLImageClassifierOptions* imageClassifierOptions =
+       [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+ 
+-  TFLImageClassifier *imageClassifier =
+-      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions error:nil];
++  TFLImageClassifier* imageClassifier =
++      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
++                                               error:nil];
+   XCTAssertNotNil(imageClassifier);
+ 
+-  GMLImage *gmlImage = [self imageFromBundleWithName:@"sparrow" ofType:@"png"];
++  GMLImage* gmlImage = [self imageFromBundleWithName:@"sparrow" ofType:@"png"];
+   XCTAssertNotNil(gmlImage);
+ 
+-  TFLClassificationResult *classificationResults = [imageClassifier classifyWithGMLImage:gmlImage
+-                                                                                   error:nil];
++  TFLClassificationResult* classificationResults =
++      [imageClassifier classifyWithGMLImage:gmlImage error:nil];
+   XCTAssertTrue([classificationResults.classifications count] > 0);
+-  XCTAssertTrue([classificationResults.classifications[0].categories count] > 0);
++  XCTAssertTrue([classificationResults.classifications[0].categories count] >
++                0);
+ 
+-  TFLCategory *category = classificationResults.classifications[0].categories[0];
++  TFLCategory* category =
++      classificationResults.classifications[0].categories[0];
+   XCTAssertTrue([category.label isEqual:@"junco"]);
+-  // TODO: inspect if score is correct. Better to test againest "burger", because we know the
+-  // expected result for "burger.jpg".
++  // TODO: inspect if score is correct. Better to test againest "burger",
++  // because we know the expected result for "burger.jpg".
+   XCTAssertEqualWithAccuracy(category.score, 0.253016, 0.001);
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.h
+index aa6924893b301..d08f5177ceee9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.h
+@@ -28,11 +28,13 @@ NS_ASSUME_NONNULL_BEGIN
+ /**
+  * Initializes the tokenizer with the path to wordpiece vocabulary file.
+  */
+-- (instancetype)initWithVocabPath:(NSString *)vocabPath NS_DESIGNATED_INITIALIZER;
++- (instancetype)initWithVocabPath:(NSString*)vocabPath
++    NS_DESIGNATED_INITIALIZER;
+ 
+ /**
+  * Initializes the tokenizer with a list of tokens.
+  */
+-- (instancetype)initWithVocab:(NSArray<NSString *> *)vocab NS_DESIGNATED_INITIALIZER;
++- (instancetype)initWithVocab:(NSArray<NSString*>*)vocab
++    NS_DESIGNATED_INITIALIZER;
+ @end
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.mm b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.mm
+index 949cef2b0b7c2..2a028f6cd7d1a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.mm
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLBertTokenizer.mm
+@@ -24,7 +24,7 @@ using BertTokenizerCPP = ::tflite::support::text::tokenizer::BertTokenizer;
+   std::unique_ptr<BertTokenizerCPP> _bertTokenizer;
+ }
+ 
+-- (instancetype)initWithVocabPath:(NSString *)vocabPath {
++- (instancetype)initWithVocabPath:(NSString*)vocabPath {
+   self = [super init];
+   if (self) {
+     _bertTokenizer = absl::make_unique<BertTokenizerCPP>(MakeString(vocabPath));
+@@ -32,12 +32,12 @@ using BertTokenizerCPP = ::tflite::support::text::tokenizer::BertTokenizer;
+   return self;
+ }
+ 
+-- (instancetype)initWithVocab:(NSArray<NSString *> *)vocab {
++- (instancetype)initWithVocab:(NSArray<NSString*>*)vocab {
+   self = [super init];
+   if (self) {
+     std::vector<std::string> vocabCpp;
+     vocabCpp.reserve([vocab count]);
+-    for (NSString *word in vocab) {
++    for (NSString* word in vocab) {
+       vocabCpp.emplace_back(MakeString(word));
+     }
+     _bertTokenizer = absl::make_unique<BertTokenizerCPP>(vocabCpp);
+@@ -45,11 +45,11 @@ using BertTokenizerCPP = ::tflite::support::text::tokenizer::BertTokenizer;
+   return self;
+ }
+ 
+-- (NSArray<NSString *> *)tokensFromInput:(NSString *)input {
++- (NSArray<NSString*>*)tokensFromInput:(NSString*)input {
+   return Tokenize(_bertTokenizer.get(), input);
+ }
+ 
+-- (NSArray<NSNumber *> *)idsFromTokens:(NSArray<NSString *> *)tokens {
++- (NSArray<NSNumber*>*)idsFromTokens:(NSArray<NSString*>*)tokens {
+   return ConvertTokensToIds(_bertTokenizer.get(), tokens);
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.h
+index eef3bf1e223e6..9813e32ecb5d3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.h
+@@ -28,6 +28,6 @@ NS_ASSUME_NONNULL_BEGIN
+ /**
+  * Initializes the tokenizer with the path to sentencepiece model file.
+  */
+-- (instancetype)initWithModelPath:(NSString *)modelPath;
++- (instancetype)initWithModelPath:(NSString*)modelPath;
+ @end
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.mm b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.mm
+index 1e21cee5c08d2..1ba49923040c1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.mm
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLSentencepieceTokenizer.mm
+@@ -19,25 +19,27 @@ limitations under the License.
+ #import "third_party/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.h"
+ 
+ NS_ASSUME_NONNULL_BEGIN
+-using SentencepieceTokenizerCPP = ::tflite::support::text::tokenizer::SentencePieceTokenizer;
++using SentencepieceTokenizerCPP =
++    ::tflite::support::text::tokenizer::SentencePieceTokenizer;
+ 
+ @implementation TFLSentencepieceTokenizer {
+   std::unique_ptr<SentencepieceTokenizerCPP> _spTokenizer;
+ }
+ 
+-- (instancetype)initWithModelPath:(NSString *)modelPath {
++- (instancetype)initWithModelPath:(NSString*)modelPath {
+   self = [super init];
+   if (self) {
+-    _spTokenizer = absl::make_unique<SentencepieceTokenizerCPP>(MakeString(modelPath));
++    _spTokenizer =
++        absl::make_unique<SentencepieceTokenizerCPP>(MakeString(modelPath));
+   }
+   return self;
+ }
+ 
+-- (NSArray<NSString *> *)tokensFromInput:(NSString *)input {
++- (NSArray<NSString*>*)tokensFromInput:(NSString*)input {
+   return Tokenize(_spTokenizer.get(), input);
+ }
+ 
+-- (NSArray<NSNumber *> *)idsFromTokens:(NSArray<NSString *> *)tokens {
++- (NSArray<NSNumber*>*)idsFromTokens:(NSArray<NSString*>*)tokens {
+   return ConvertTokensToIds(_spTokenizer.get(), tokens);
+ }
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizer.h
+index ee0972f8aba30..bd832060b6e80 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizer.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizer.h
+@@ -26,7 +26,7 @@ NS_ASSUME_NONNULL_BEGIN
+  *
+  * @return A list of tokens.
+  */
+-- (NSArray<NSString *> *)tokensFromInput:(NSString *)input;
++- (NSArray<NSString*>*)tokensFromInput:(NSString*)input;
+ 
+ /*
+  * Convert a list of tokens back to their coressponding IDs.
+@@ -34,6 +34,6 @@ NS_ASSUME_NONNULL_BEGIN
+  *
+  * @return A list of ids.
+  */
+-- (NSArray<NSNumber *> *)idsFromTokens:(NSArray<NSString *> *)tokens;
++- (NSArray<NSNumber*>*)idsFromTokens:(NSArray<NSString*>*)tokens;
+ @end
+ NS_ASSUME_NONNULL_END
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.h
+index 574b555301616..14e2906675b71 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.h
+@@ -18,21 +18,24 @@ limitations under the License.
+ using ::tflite::support::text::tokenizer::Tokenizer;
+ 
+ /**
+- * Invokes the cpp tokenizer's tokenize function and converts input/output to objc.
++ * Invokes the cpp tokenizer's tokenize function and converts input/output to
++ * objc.
+  *
+  * @param tokenizer The cpp tokenizer pointer.
+  * @param input The input string to be tokenized.
+  *
+  * @return A list of tokens.
+  */
+-NSArray<NSString *> *Tokenize(Tokenizer *tokenizer, NSString *input);
++NSArray<NSString*>* Tokenize(Tokenizer* tokenizer, NSString* input);
+ 
+ /**
+- * Invokes the cpp tokenizer's convertTokensToIds function and converts input/output to objc.
++ * Invokes the cpp tokenizer's convertTokensToIds function and converts
++ * input/output to objc.
+  *
+  * @param tokenizer The cpp tokenizer pointer.
+  * @param input The tokens to be converted.
+  *
+  * @return A list of ids.
+  */
+-NSArray<NSNumber *> *ConvertTokensToIds(Tokenizer *tokenizer, NSArray<NSString *> *tokens);
++NSArray<NSNumber*>* ConvertTokensToIds(Tokenizer* tokenizer,
++                                       NSArray<NSString*>* tokens);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.mm b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.mm
+index 52180578170d8..8e92e3712e29e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.mm
++++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Sources/TFLTokenizerUtil.mm
+@@ -18,21 +18,24 @@ limitations under the License.
+ 
+ using ::tflite::support::text::tokenizer::TokenizerResult;
+ 
+-NSArray<NSString *> *Tokenize(Tokenizer *tokenizer, NSString *input) {
++NSArray<NSString*>* Tokenize(Tokenizer* tokenizer, NSString* input) {
+   TokenizerResult tokenize_result = tokenizer->Tokenize(MakeString(input));
+   std::vector<std::string> subwords = tokenize_result.subwords;
+-  NSMutableArray<NSString *> *ret = [NSMutableArray arrayWithCapacity:subwords.size()];
++  NSMutableArray<NSString*>* ret =
++      [NSMutableArray arrayWithCapacity:subwords.size()];
+   for (int i = 0; i < subwords.size(); ++i) {
+     [ret addObject:MakeNSString(subwords[i])];
+   }
+   return ret;
+ }
+ 
+-NSArray<NSNumber *> *ConvertTokensToIds(Tokenizer *tokenizer, NSArray<NSString *> *tokens) {
+-  NSMutableArray<NSNumber *> *ret = [NSMutableArray arrayWithCapacity:[tokens count]];
+-  for (NSString *token in tokens) {
++NSArray<NSNumber*>* ConvertTokensToIds(Tokenizer* tokenizer,
++                                       NSArray<NSString*>* tokens) {
++  NSMutableArray<NSNumber*>* ret =
++      [NSMutableArray arrayWithCapacity:[tokens count]];
++  for (NSString* token in tokens) {
+     std::string cc_token = MakeString(token);
+-    const char *cToken = cc_token.c_str();
++    const char* cToken = cc_token.c_str();
+     int id;
+     tokenizer->LookupId(cToken, &id);
+     [ret addObject:[NSNumber numberWithInt:id]];
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java
+index 1d8a9767f41c7..e066146eb0c7d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java
+@@ -15,19 +15,24 @@ limitations under the License.
+ 
+ package org.tensorflow.lite.support.audio;
+ 
+-import static java.lang.System.arraycopy;
+ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+ 
++import static java.lang.System.arraycopy;
++
+ import android.media.AudioFormat;
+ import android.media.AudioRecord;
+ import android.os.Build;
++
+ import androidx.annotation.RequiresApi;
++
+ import com.google.auto.value.AutoValue;
++
++import org.tensorflow.lite.DataType;
++import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
++
+ import java.nio.ByteBuffer;
+ import java.nio.ByteOrder;
+ import java.nio.FloatBuffer;
+-import org.tensorflow.lite.DataType;
+-import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /**
+  * Defines a ring buffer and some utility functions to prepare the input audio samples.
+@@ -60,285 +65,282 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * </pre>
+  */
+ public class TensorAudio {
++    private static final String TAG = TensorAudio.class.getSimpleName();
++    private final FloatRingBuffer buffer;
++    private final TensorAudioFormat format;
+ 
+-  private static final String TAG = TensorAudio.class.getSimpleName();
+-  private final FloatRingBuffer buffer;
+-  private final TensorAudioFormat format;
+-
+-  /**
+-   * Creates a {@link android.media.AudioRecord} instance with a ring buffer whose size is {@code
+-   * sampleCounts} * {@code format.getChannels()}.
+-   *
+-   * @param format the expected {@link TensorAudioFormat} of audio data loaded into this class.
+-   * @param sampleCounts the number of samples to be fed into the model
+-   */
+-  public static TensorAudio create(TensorAudioFormat format, int sampleCounts) {
+-    return new TensorAudio(format, sampleCounts);
+-  }
+-
+-  /**
+-   * Creates a {@link TensorAudio} instance with a ring buffer whose size is {@code sampleCounts} *
+-   * {@code format.getChannelCount()}.
+-   *
+-   * @param format the {@link android.media.AudioFormat} required by the TFLite model. It defines
+-   *     the number of channels and sample rate.
+-   * @param sampleCounts the number of samples to be fed into the model
+-   */
+-  public static TensorAudio create(AudioFormat format, int sampleCounts) {
+-    return new TensorAudio(TensorAudioFormat.create(format), sampleCounts);
+-  }
+-
+-  /**
+-   * Wraps a few constants describing the format of the incoming audio samples, namely number of
+-   * channels and the sample rate. By default, channels is set to 1.
+-   */
+-  @AutoValue
+-  public abstract static class TensorAudioFormat {
+-    private static final int DEFAULT_CHANNELS = 1;
+-
+-    /** Creates a {@link TensorAudioFormat} instance from Android AudioFormat class. */
+-    @RequiresApi(Build.VERSION_CODES.M)
+-    public static TensorAudioFormat create(AudioFormat format) {
+-      return TensorAudioFormat.builder()
+-          .setChannels(format.getChannelCount())
+-          .setSampleRate(format.getSampleRate())
+-          .build();
++    /**
++     * Creates a {@link android.media.AudioRecord} instance with a ring buffer whose size is {@code
++     * sampleCounts} * {@code format.getChannels()}.
++     *
++     * @param format the expected {@link TensorAudioFormat} of audio data loaded into this class.
++     * @param sampleCounts the number of samples to be fed into the model
++     */
++    public static TensorAudio create(TensorAudioFormat format, int sampleCounts) {
++        return new TensorAudio(format, sampleCounts);
+     }
+ 
+-    public abstract int getChannels();
+-
+-    public abstract int getSampleRate();
+-
+-    public static Builder builder() {
+-      return new AutoValue_TensorAudio_TensorAudioFormat.Builder().setChannels(DEFAULT_CHANNELS);
++    /**
++     * Creates a {@link TensorAudio} instance with a ring buffer whose size is {@code sampleCounts}
++     * *
++     * {@code format.getChannelCount()}.
++     *
++     * @param format the {@link android.media.AudioFormat} required by the TFLite model. It defines
++     *     the number of channels and sample rate.
++     * @param sampleCounts the number of samples to be fed into the model
++     */
++    public static TensorAudio create(AudioFormat format, int sampleCounts) {
++        return new TensorAudio(TensorAudioFormat.create(format), sampleCounts);
+     }
+ 
+-    /** Builder for {@link TensorAudioFormat} */
+-    @AutoValue.Builder
+-    public abstract static class Builder {
+-
+-      /* By default, it's set to have 1 channel. */
+-      public abstract Builder setChannels(int value);
+-
+-      public abstract Builder setSampleRate(int value);
+-
+-      abstract TensorAudioFormat autoBuild();
+-
+-      public TensorAudioFormat build() {
+-        TensorAudioFormat format = autoBuild();
+-        checkArgument(format.getChannels() > 0, "Number of channels should be greater than 0");
+-        checkArgument(format.getSampleRate() > 0, "Sample rate should be greater than 0");
+-        return format;
+-      }
+-    }
+-  }
+-
+-  /**
+-   * Stores the input audio samples {@code src} in the ring buffer.
+-   *
+-   * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_FLOAT}. For
+-   *     multi-channel input, the array is interleaved.
+-   */
+-  public void load(float[] src) {
+-    load(src, 0, src.length);
+-  }
+-
+-  /**
+-   * Stores the input audio samples {@code src} in the ring buffer.
+-   *
+-   * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_FLOAT}. For
+-   *     multi-channel input, the array is interleaved.
+-   * @param offsetInFloat starting position in the {@code src} array
+-   * @param sizeInFloat the number of float values to be copied
+-   * @throws IllegalArgumentException for incompatible audio format or incorrect input size
+-   */
+-  public void load(float[] src, int offsetInFloat, int sizeInFloat) {
+-    checkArgument(
+-        sizeInFloat % format.getChannels() == 0,
+-        String.format(
+-            "Size (%d) needs to be a multiplier of the number of channels (%d)",
+-            sizeInFloat, format.getChannels()));
+-    buffer.load(src, offsetInFloat, sizeInFloat);
+-  }
+-
+-  /**
+-   * Converts the input audio samples {@code src} to ENCODING_PCM_FLOAT, then stores it in the ring
+-   * buffer.
+-   *
+-   * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_16BIT}. For
+-   *     multi-channel input, the array is interleaved.
+-   */
+-  public void load(short[] src) {
+-    load(src, 0, src.length);
+-  }
+-
+-  /**
+-   * Converts the input audio samples {@code src} to ENCODING_PCM_FLOAT, then stores it in the ring
+-   * buffer.
+-   *
+-   * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_16BIT}. For
+-   *     multi-channel input, the array is interleaved.
+-   * @param offsetInShort starting position in the src array
+-   * @param sizeInShort the number of short values to be copied
+-   * @throws IllegalArgumentException if the source array can't be copied
+-   */
+-  public void load(short[] src, int offsetInShort, int sizeInShort) {
+-    checkArgument(
+-        offsetInShort + sizeInShort <= src.length,
+-        String.format(
+-            "Index out of range. offset (%d) + size (%d) should <= newData.length (%d)",
+-            offsetInShort, sizeInShort, src.length));
+-    float[] floatData = new float[sizeInShort];
+-    for (int i = offsetInShort; i < sizeInShort; i++) {
+-      // Convert the data to PCM Float encoding i.e. values between -1 and 1
+-      floatData[i] = src[i] / Short.MAX_VALUE;
+-    }
+-    load(floatData);
+-  }
+-
+-  /**
+-   * Loads latest data from the {@link android.media.AudioRecord} in a non-blocking way. Only
+-   * supporting ENCODING_PCM_16BIT and ENCODING_PCM_FLOAT.
+-   *
+-   * @param record an instance of {@link android.media.AudioRecord}
+-   * @return number of captured audio values whose size is {@code channelCount * sampleCount}. If
+-   *     there was no new data in the AudioRecord or an error occurred, this method will return 0.
+-   * @throws IllegalArgumentException for unsupported audio encoding format
+-   * @throws IllegalStateException if reading from AudioRecord failed
+-   */
+-  @RequiresApi(Build.VERSION_CODES.M)
+-  public int load(AudioRecord record) {
+-    checkArgument(
+-        this.format.equals(TensorAudioFormat.create(record.getFormat())),
+-        "Incompatible audio format.");
+-    int loadedValues = 0;
+-    if (record.getAudioFormat() == AudioFormat.ENCODING_PCM_FLOAT) {
+-      float[] newData = new float[record.getChannelCount() * record.getBufferSizeInFrames()];
+-      loadedValues = record.read(newData, 0, newData.length, AudioRecord.READ_NON_BLOCKING);
+-      if (loadedValues > 0) {
+-        load(newData, 0, loadedValues);
+-        return loadedValues;
+-      }
+-    } else if (record.getAudioFormat() == AudioFormat.ENCODING_PCM_16BIT) {
+-      short[] newData = new short[record.getChannelCount() * record.getBufferSizeInFrames()];
+-      loadedValues = record.read(newData, 0, newData.length, AudioRecord.READ_NON_BLOCKING);
+-      if (loadedValues > 0) {
+-        load(newData, 0, loadedValues);
+-        return loadedValues;
+-      }
+-    } else {
+-      throw new IllegalArgumentException(
+-          "Unsupported encoding. Requires ENCODING_PCM_16BIT or ENCODING_PCM_FLOAT.");
++    /**
++     * Wraps a few constants describing the format of the incoming audio samples, namely number of
++     * channels and the sample rate. By default, channels is set to 1.
++     */
++    @AutoValue
++    public abstract static class TensorAudioFormat {
++        private static final int DEFAULT_CHANNELS = 1;
++
++        /** Creates a {@link TensorAudioFormat} instance from Android AudioFormat class. */
++        @RequiresApi(Build.VERSION_CODES.M)
++        public static TensorAudioFormat create(AudioFormat format) {
++            return TensorAudioFormat.builder()
++                    .setChannels(format.getChannelCount())
++                    .setSampleRate(format.getSampleRate())
++                    .build();
++        }
++
++        public abstract int getChannels();
++
++        public abstract int getSampleRate();
++
++        public static Builder builder() {
++            return new AutoValue_TensorAudio_TensorAudioFormat.Builder().setChannels(
++                    DEFAULT_CHANNELS);
++        }
++
++        /** Builder for {@link TensorAudioFormat} */
++        @AutoValue.Builder
++        public abstract static class Builder {
++            /* By default, it's set to have 1 channel. */
++            public abstract Builder setChannels(int value);
++
++            public abstract Builder setSampleRate(int value);
++
++            abstract TensorAudioFormat autoBuild();
++
++            public TensorAudioFormat build() {
++                TensorAudioFormat format = autoBuild();
++                checkArgument(
++                        format.getChannels() > 0, "Number of channels should be greater than 0");
++                checkArgument(format.getSampleRate() > 0, "Sample rate should be greater than 0");
++                return format;
++            }
++        }
+     }
+ 
+-    switch (loadedValues) {
+-      case AudioRecord.ERROR_INVALID_OPERATION:
+-        throw new IllegalStateException("AudioRecord.ERROR_INVALID_OPERATION");
+-
+-      case AudioRecord.ERROR_BAD_VALUE:
+-        throw new IllegalStateException("AudioRecord.ERROR_BAD_VALUE");
+-
+-      case AudioRecord.ERROR_DEAD_OBJECT:
+-        throw new IllegalStateException("AudioRecord.ERROR_DEAD_OBJECT");
++    /**
++     * Stores the input audio samples {@code src} in the ring buffer.
++     *
++     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_FLOAT}. For
++     *     multi-channel input, the array is interleaved.
++     */
++    public void load(float[] src) {
++        load(src, 0, src.length);
++    }
+ 
+-      case AudioRecord.ERROR:
+-        throw new IllegalStateException("AudioRecord.ERROR");
++    /**
++     * Stores the input audio samples {@code src} in the ring buffer.
++     *
++     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_FLOAT}. For
++     *     multi-channel input, the array is interleaved.
++     * @param offsetInFloat starting position in the {@code src} array
++     * @param sizeInFloat the number of float values to be copied
++     * @throws IllegalArgumentException for incompatible audio format or incorrect input size
++     */
++    public void load(float[] src, int offsetInFloat, int sizeInFloat) {
++        checkArgument(sizeInFloat % format.getChannels() == 0,
++                String.format("Size (%d) needs to be a multiplier of the number of channels (%d)",
++                        sizeInFloat, format.getChannels()));
++        buffer.load(src, offsetInFloat, sizeInFloat);
++    }
+ 
+-      default:
+-        return 0;
++    /**
++     * Converts the input audio samples {@code src} to ENCODING_PCM_FLOAT, then stores it in the
++     * ring buffer.
++     *
++     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_16BIT}. For
++     *     multi-channel input, the array is interleaved.
++     */
++    public void load(short[] src) {
++        load(src, 0, src.length);
+     }
+-  }
+-
+-  /**
+-   * Returns a float {@link TensorBuffer} holding all the available audio samples in {@link
+-   * android.media.AudioFormat#ENCODING_PCM_FLOAT} i.e. values are in the range of [-1, 1].
+-   */
+-  public TensorBuffer getTensorBuffer() {
+-    ByteBuffer byteBuffer = buffer.getBuffer();
+-    TensorBuffer tensorBuffer =
+-        TensorBuffer.createFixedSize(
+-            new int[] {
+-              /* batch= */ 1, /* modelInputLengthInFloat= */ byteBuffer.asFloatBuffer().limit()
+-            },
+-            DataType.FLOAT32);
+-    tensorBuffer.loadBuffer(byteBuffer);
+-    return tensorBuffer;
+-  }
+-
+-  /* Returns the {@link TensorAudioFormat} associated with the tensor. */
+-  public TensorAudioFormat getFormat() {
+-    return format;
+-  }
+-
+-  private TensorAudio(TensorAudioFormat format, int sampleCounts) {
+-    this.format = format;
+-    this.buffer = new FloatRingBuffer(sampleCounts * format.getChannels());
+-  }
+-
+-  /** Actual implementation of the ring buffer. */
+-  private static class FloatRingBuffer {
+-
+-    private final float[] buffer;
+-    private int nextIndex = 0;
+-
+-    public FloatRingBuffer(int flatSize) {
+-      buffer = new float[flatSize];
++
++    /**
++     * Converts the input audio samples {@code src} to ENCODING_PCM_FLOAT, then stores it in the
++     * ring buffer.
++     *
++     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_16BIT}. For
++     *     multi-channel input, the array is interleaved.
++     * @param offsetInShort starting position in the src array
++     * @param sizeInShort the number of short values to be copied
++     * @throws IllegalArgumentException if the source array can't be copied
++     */
++    public void load(short[] src, int offsetInShort, int sizeInShort) {
++        checkArgument(offsetInShort + sizeInShort <= src.length,
++                String.format(
++                        "Index out of range. offset (%d) + size (%d) should <= newData.length (%d)",
++                        offsetInShort, sizeInShort, src.length));
++        float[] floatData = new float[sizeInShort];
++        for (int i = offsetInShort; i < sizeInShort; i++) {
++            // Convert the data to PCM Float encoding i.e. values between -1 and 1
++            floatData[i] = src[i] / Short.MAX_VALUE;
++        }
++        load(floatData);
+     }
+ 
+     /**
+-     * Loads the entire float array to the ring buffer. If the float array is longer than ring
+-     * buffer's capacity, samples with lower indices in the array will be ignored.
++     * Loads latest data from the {@link android.media.AudioRecord} in a non-blocking way. Only
++     * supporting ENCODING_PCM_16BIT and ENCODING_PCM_FLOAT.
++     *
++     * @param record an instance of {@link android.media.AudioRecord}
++     * @return number of captured audio values whose size is {@code channelCount * sampleCount}. If
++     *     there was no new data in the AudioRecord or an error occurred, this method will return 0.
++     * @throws IllegalArgumentException for unsupported audio encoding format
++     * @throws IllegalStateException if reading from AudioRecord failed
+      */
+-    public void load(float[] newData) {
+-      load(newData, 0, newData.length);
++    @RequiresApi(Build.VERSION_CODES.M)
++    public int load(AudioRecord record) {
++        checkArgument(this.format.equals(TensorAudioFormat.create(record.getFormat())),
++                "Incompatible audio format.");
++        int loadedValues = 0;
++        if (record.getAudioFormat() == AudioFormat.ENCODING_PCM_FLOAT) {
++            float[] newData = new float[record.getChannelCount() * record.getBufferSizeInFrames()];
++            loadedValues = record.read(newData, 0, newData.length, AudioRecord.READ_NON_BLOCKING);
++            if (loadedValues > 0) {
++                load(newData, 0, loadedValues);
++                return loadedValues;
++            }
++        } else if (record.getAudioFormat() == AudioFormat.ENCODING_PCM_16BIT) {
++            short[] newData = new short[record.getChannelCount() * record.getBufferSizeInFrames()];
++            loadedValues = record.read(newData, 0, newData.length, AudioRecord.READ_NON_BLOCKING);
++            if (loadedValues > 0) {
++                load(newData, 0, loadedValues);
++                return loadedValues;
++            }
++        } else {
++            throw new IllegalArgumentException(
++                    "Unsupported encoding. Requires ENCODING_PCM_16BIT or ENCODING_PCM_FLOAT.");
++        }
++
++        switch (loadedValues) {
++            case AudioRecord.ERROR_INVALID_OPERATION:
++                throw new IllegalStateException("AudioRecord.ERROR_INVALID_OPERATION");
++
++            case AudioRecord.ERROR_BAD_VALUE:
++                throw new IllegalStateException("AudioRecord.ERROR_BAD_VALUE");
++
++            case AudioRecord.ERROR_DEAD_OBJECT:
++                throw new IllegalStateException("AudioRecord.ERROR_DEAD_OBJECT");
++
++            case AudioRecord.ERROR:
++                throw new IllegalStateException("AudioRecord.ERROR");
++
++            default:
++                return 0;
++        }
+     }
+ 
+     /**
+-     * Loads a slice of the float array to the ring buffer. If the float array is longer than ring
+-     * buffer's capacity, samples with lower indices in the array will be ignored.
++     * Returns a float {@link TensorBuffer} holding all the available audio samples in {@link
++     * android.media.AudioFormat#ENCODING_PCM_FLOAT} i.e. values are in the range of [-1, 1].
+      */
+-    public void load(float[] newData, int offset, int size) {
+-      checkArgument(
+-          offset + size <= newData.length,
+-          String.format(
+-              "Index out of range. offset (%d) + size (%d) should <= newData.length (%d)",
+-              offset, size, newData.length));
+-      // If buffer can't hold all the data, only keep the most recent data of size buffer.length
+-      if (size > buffer.length) {
+-        offset = size - buffer.length;
+-        size = buffer.length;
+-      }
+-      if (nextIndex + size < buffer.length) {
+-        // No need to wrap nextIndex, just copy newData[offset:offset + size]
+-        // to buffer[nextIndex:nextIndex+size]
+-        arraycopy(newData, offset, buffer, nextIndex, size);
+-      } else {
+-        // Need to wrap nextIndex, perform copy in two chunks.
+-        int firstChunkSize = buffer.length - nextIndex;
+-        // First copy newData[offset:offset+firstChunkSize] to buffer[nextIndex:buffer.length]
+-        arraycopy(newData, offset, buffer, nextIndex, firstChunkSize);
+-        // Then copy newData[offset+firstChunkSize:offset+size] to buffer[0:size-firstChunkSize]
+-        arraycopy(newData, offset + firstChunkSize, buffer, 0, size - firstChunkSize);
+-      }
+-
+-      nextIndex = (nextIndex + size) % buffer.length;
++    public TensorBuffer getTensorBuffer() {
++        ByteBuffer byteBuffer = buffer.getBuffer();
++        TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(
++                new int[] {/* batch= */ 1,
++                        /* modelInputLengthInFloat= */ byteBuffer.asFloatBuffer().limit()},
++                DataType.FLOAT32);
++        tensorBuffer.loadBuffer(byteBuffer);
++        return tensorBuffer;
++    }
++
++    /* Returns the {@link TensorAudioFormat} associated with the tensor. */
++    public TensorAudioFormat getFormat() {
++        return format;
+     }
+ 
+-    public ByteBuffer getBuffer() {
+-      // Create non-direct buffers. On Pixel 4, creating direct buffer costs around 0.1 ms, which
+-      // can be 5x ~ 10x longer compared to non-direct buffer backed by arrays (around 0.01ms), so
+-      // generally we don't create direct buffer for every invocation.
+-      ByteBuffer byteBuffer = ByteBuffer.allocate(DataType.FLOAT32.byteSize() * buffer.length);
+-      byteBuffer.order(ByteOrder.nativeOrder());
+-      FloatBuffer result = byteBuffer.asFloatBuffer();
+-      result.put(buffer, nextIndex, buffer.length - nextIndex);
+-      result.put(buffer, 0, nextIndex);
+-      byteBuffer.rewind();
+-      return byteBuffer;
++    private TensorAudio(TensorAudioFormat format, int sampleCounts) {
++        this.format = format;
++        this.buffer = new FloatRingBuffer(sampleCounts * format.getChannels());
+     }
+ 
+-    public int getCapacity() {
+-      return buffer.length;
++    /** Actual implementation of the ring buffer. */
++    private static class FloatRingBuffer {
++        private final float[] buffer;
++        private int nextIndex = 0;
++
++        public FloatRingBuffer(int flatSize) {
++            buffer = new float[flatSize];
++        }
++
++        /**
++         * Loads the entire float array to the ring buffer. If the float array is longer than ring
++         * buffer's capacity, samples with lower indices in the array will be ignored.
++         */
++        public void load(float[] newData) {
++            load(newData, 0, newData.length);
++        }
++
++        /**
++         * Loads a slice of the float array to the ring buffer. If the float array is longer than
++         * ring buffer's capacity, samples with lower indices in the array will be ignored.
++         */
++        public void load(float[] newData, int offset, int size) {
++            checkArgument(offset + size <= newData.length,
++                    String.format(
++                            "Index out of range. offset (%d) + size (%d) should <= newData.length (%d)",
++                            offset, size, newData.length));
++            // If buffer can't hold all the data, only keep the most recent data of size
++            // buffer.length
++            if (size > buffer.length) {
++                offset = size - buffer.length;
++                size = buffer.length;
++            }
++            if (nextIndex + size < buffer.length) {
++                // No need to wrap nextIndex, just copy newData[offset:offset + size]
++                // to buffer[nextIndex:nextIndex+size]
++                arraycopy(newData, offset, buffer, nextIndex, size);
++            } else {
++                // Need to wrap nextIndex, perform copy in two chunks.
++                int firstChunkSize = buffer.length - nextIndex;
++                // First copy newData[offset:offset+firstChunkSize] to
++                // buffer[nextIndex:buffer.length]
++                arraycopy(newData, offset, buffer, nextIndex, firstChunkSize);
++                // Then copy newData[offset+firstChunkSize:offset+size] to
++                // buffer[0:size-firstChunkSize]
++                arraycopy(newData, offset + firstChunkSize, buffer, 0, size - firstChunkSize);
++            }
++
++            nextIndex = (nextIndex + size) % buffer.length;
++        }
++
++        public ByteBuffer getBuffer() {
++            // Create non-direct buffers. On Pixel 4, creating direct buffer costs around 0.1 ms,
++            // which can be 5x ~ 10x longer compared to non-direct buffer backed by arrays (around
++            // 0.01ms), so generally we don't create direct buffer for every invocation.
++            ByteBuffer byteBuffer =
++                    ByteBuffer.allocate(DataType.FLOAT32.byteSize() * buffer.length);
++            byteBuffer.order(ByteOrder.nativeOrder());
++            FloatBuffer result = byteBuffer.asFloatBuffer();
++            result.put(buffer, nextIndex, buffer.length - nextIndex);
++            result.put(buffer, 0, nextIndex);
++            byteBuffer.rewind();
++            return byteBuffer;
++        }
++
++        public int getCapacity() {
++            return buffer.length;
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java
+index 776391b526b47..6090f85d99083 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java
+@@ -17,6 +17,10 @@ package org.tensorflow.lite.support.common;
+ 
+ import android.content.Context;
+ import android.content.res.AssetFileDescriptor;
++
++import org.checkerframework.checker.nullness.qual.NonNull;
++import org.tensorflow.lite.support.common.internal.SupportPreconditions;
++
+ import java.io.BufferedReader;
+ import java.io.FileInputStream;
+ import java.io.IOException;
+@@ -28,160 +32,159 @@ import java.nio.channels.FileChannel;
+ import java.nio.charset.Charset;
+ import java.util.ArrayList;
+ import java.util.List;
+-import org.checkerframework.checker.nullness.qual.NonNull;
+-import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ 
+ /** File I/O utilities. */
+ public class FileUtil {
+-  private FileUtil() {}
+-
+-  /**
+-   * Loads labels from the label file into a list of strings.
+-   *
+-   * <p>A legal label file is the plain text file whose contents are split into lines, and each line
+-   * is an individual value. The file should be in assets of the context.
+-   *
+-   * @param context The context holds assets.
+-   * @param filePath The path of the label file, relative with assets directory.
+-   * @return a list of labels.
+-   * @throws IOException if error occurs to open or read the file.
+-   */
+-  @NonNull
+-  public static List<String> loadLabels(@NonNull Context context, @NonNull String filePath)
+-      throws IOException {
+-    return loadLabels(context, filePath, Charset.defaultCharset());
+-  }
+-
+-  /**
+-   * Loads labels from the label file into a list of strings.
+-   *
+-   * <p>A legal label file is the plain text file whose contents are split into lines, and each line
+-   * is an individual value. The empty lines will be ignored. The file should be in assets of the
+-   * context.
+-   *
+-   * @param context The context holds assets.
+-   * @param filePath The path of the label file, relative with assets directory.
+-   * @param cs {@code Charset} to use when decoding content of label file.
+-   * @return a list of labels.
+-   * @throws IOException if error occurs to open or read the file.
+-   */
+-  @NonNull
+-  public static List<String> loadLabels(
+-      @NonNull Context context, @NonNull String filePath, Charset cs) throws IOException {
+-    SupportPreconditions.checkNotNull(context, "Context cannot be null.");
+-    SupportPreconditions.checkNotNull(filePath, "File path cannot be null.");
+-    try (InputStream inputStream = context.getAssets().open(filePath)) {
+-      return loadLabels(inputStream, cs);
++    private FileUtil() {}
++
++    /**
++     * Loads labels from the label file into a list of strings.
++     *
++     * <p>A legal label file is the plain text file whose contents are split into lines, and each
++     * line is an individual value. The file should be in assets of the context.
++     *
++     * @param context The context holds assets.
++     * @param filePath The path of the label file, relative with assets directory.
++     * @return a list of labels.
++     * @throws IOException if error occurs to open or read the file.
++     */
++    @NonNull
++    public static List<String> loadLabels(@NonNull Context context, @NonNull String filePath)
++            throws IOException {
++        return loadLabels(context, filePath, Charset.defaultCharset());
+     }
+-  }
+-
+-  /**
+-   * Loads labels from an input stream of an opened label file. See details for label files in
+-   * {@link FileUtil#loadLabels(Context, String)}.
+-   *
+-   * @param inputStream the input stream of an opened label file.
+-   * @return a list of labels.
+-   * @throws IOException if error occurs to open or read the file.
+-   */
+-  @NonNull
+-  public static List<String> loadLabels(@NonNull InputStream inputStream) throws IOException {
+-    return loadLabels(inputStream, Charset.defaultCharset());
+-  }
+-
+-  /**
+-   * Loads labels from an input stream of an opened label file. See details for label files in
+-   * {@link FileUtil#loadLabels(Context, String)}.
+-   *
+-   * @param inputStream the input stream of an opened label file.
+-   * @param cs {@code Charset} to use when decoding content of label file.
+-   * @return a list of labels.
+-   * @throws IOException if error occurs to open or read the file.
+-   */
+-  @NonNull
+-  public static List<String> loadLabels(@NonNull InputStream inputStream, Charset cs)
+-      throws IOException {
+-    List<String> labels = new ArrayList<>();
+-    try (BufferedReader reader = new BufferedReader(new InputStreamReader(inputStream, cs))) {
+-      String line;
+-      while ((line = reader.readLine()) != null) {
+-        if (line.trim().length() > 0) {
+-          labels.add(line);
++
++    /**
++     * Loads labels from the label file into a list of strings.
++     *
++     * <p>A legal label file is the plain text file whose contents are split into lines, and each
++     * line is an individual value. The empty lines will be ignored. The file should be in assets of
++     * the context.
++     *
++     * @param context The context holds assets.
++     * @param filePath The path of the label file, relative with assets directory.
++     * @param cs {@code Charset} to use when decoding content of label file.
++     * @return a list of labels.
++     * @throws IOException if error occurs to open or read the file.
++     */
++    @NonNull
++    public static List<String> loadLabels(
++            @NonNull Context context, @NonNull String filePath, Charset cs) throws IOException {
++        SupportPreconditions.checkNotNull(context, "Context cannot be null.");
++        SupportPreconditions.checkNotNull(filePath, "File path cannot be null.");
++        try (InputStream inputStream = context.getAssets().open(filePath)) {
++            return loadLabels(inputStream, cs);
+         }
+-      }
+-      return labels;
+     }
+-  }
+-
+-  /**
+-   * Loads a vocabulary file (a single-column text file) into a list of strings.
+-   *
+-   * <p>A vocabulary file is a single-column plain text file whose contents are split into lines,
+-   * and each line is an individual value. The file should be in assets of the context.
+-   *
+-   * @param context The context holds assets.
+-   * @param filePath The path of the vocabulary file, relative with assets directory.
+-   * @return a list of vocabulary words.
+-   * @throws IOException if error occurs to open or read the file.
+-   */
+-  @NonNull
+-  public static List<String> loadSingleColumnTextFile(
+-      @NonNull Context context, @NonNull String filePath, Charset cs) throws IOException {
+-    return loadLabels(context, filePath, cs);
+-  }
+-
+-  /**
+-   * Loads vocabulary from an input stream of an opened vocabulary file (which is a single-column
+-   * text file).
+-   *
+-   * <p>A vocabulary file is a single-column plain text file whose contents are split into lines,
+-   * and each line is an individual value. The file should be in assets of the context.
+-   *
+-   * @param inputStream the input stream of an opened vocabulary file.
+-   * @return a list of vocabulary words.
+-   * @throws IOException if error occurs to open or read the file.
+-   */
+-  @NonNull
+-  public static List<String> loadSingleColumnTextFile(@NonNull InputStream inputStream, Charset cs)
+-      throws IOException {
+-    return loadLabels(inputStream, cs);
+-  }
+-
+-  /**
+-   * Loads a file from the asset folder through memory mapping.
+-   *
+-   * @param context Application context to access assets.
+-   * @param filePath Asset path of the file.
+-   * @return the loaded memory mapped file.
+-   * @throws IOException if an I/O error occurs when loading the tflite model.
+-   */
+-  @NonNull
+-  public static MappedByteBuffer loadMappedFile(@NonNull Context context, @NonNull String filePath)
+-      throws IOException {
+-    SupportPreconditions.checkNotNull(context, "Context should not be null.");
+-    SupportPreconditions.checkNotNull(filePath, "File path cannot be null.");
+-    try (AssetFileDescriptor fileDescriptor = context.getAssets().openFd(filePath);
+-        FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor())) {
+-      FileChannel fileChannel = inputStream.getChannel();
+-      long startOffset = fileDescriptor.getStartOffset();
+-      long declaredLength = fileDescriptor.getDeclaredLength();
+-      return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
++
++    /**
++     * Loads labels from an input stream of an opened label file. See details for label files in
++     * {@link FileUtil#loadLabels(Context, String)}.
++     *
++     * @param inputStream the input stream of an opened label file.
++     * @return a list of labels.
++     * @throws IOException if error occurs to open or read the file.
++     */
++    @NonNull
++    public static List<String> loadLabels(@NonNull InputStream inputStream) throws IOException {
++        return loadLabels(inputStream, Charset.defaultCharset());
++    }
++
++    /**
++     * Loads labels from an input stream of an opened label file. See details for label files in
++     * {@link FileUtil#loadLabels(Context, String)}.
++     *
++     * @param inputStream the input stream of an opened label file.
++     * @param cs {@code Charset} to use when decoding content of label file.
++     * @return a list of labels.
++     * @throws IOException if error occurs to open or read the file.
++     */
++    @NonNull
++    public static List<String> loadLabels(@NonNull InputStream inputStream, Charset cs)
++            throws IOException {
++        List<String> labels = new ArrayList<>();
++        try (BufferedReader reader = new BufferedReader(new InputStreamReader(inputStream, cs))) {
++            String line;
++            while ((line = reader.readLine()) != null) {
++                if (line.trim().length() > 0) {
++                    labels.add(line);
++                }
++            }
++            return labels;
++        }
++    }
++
++    /**
++     * Loads a vocabulary file (a single-column text file) into a list of strings.
++     *
++     * <p>A vocabulary file is a single-column plain text file whose contents are split into lines,
++     * and each line is an individual value. The file should be in assets of the context.
++     *
++     * @param context The context holds assets.
++     * @param filePath The path of the vocabulary file, relative with assets directory.
++     * @return a list of vocabulary words.
++     * @throws IOException if error occurs to open or read the file.
++     */
++    @NonNull
++    public static List<String> loadSingleColumnTextFile(
++            @NonNull Context context, @NonNull String filePath, Charset cs) throws IOException {
++        return loadLabels(context, filePath, cs);
++    }
++
++    /**
++     * Loads vocabulary from an input stream of an opened vocabulary file (which is a single-column
++     * text file).
++     *
++     * <p>A vocabulary file is a single-column plain text file whose contents are split into lines,
++     * and each line is an individual value. The file should be in assets of the context.
++     *
++     * @param inputStream the input stream of an opened vocabulary file.
++     * @return a list of vocabulary words.
++     * @throws IOException if error occurs to open or read the file.
++     */
++    @NonNull
++    public static List<String> loadSingleColumnTextFile(
++            @NonNull InputStream inputStream, Charset cs) throws IOException {
++        return loadLabels(inputStream, cs);
++    }
++
++    /**
++     * Loads a file from the asset folder through memory mapping.
++     *
++     * @param context Application context to access assets.
++     * @param filePath Asset path of the file.
++     * @return the loaded memory mapped file.
++     * @throws IOException if an I/O error occurs when loading the tflite model.
++     */
++    @NonNull
++    public static MappedByteBuffer loadMappedFile(
++            @NonNull Context context, @NonNull String filePath) throws IOException {
++        SupportPreconditions.checkNotNull(context, "Context should not be null.");
++        SupportPreconditions.checkNotNull(filePath, "File path cannot be null.");
++        try (AssetFileDescriptor fileDescriptor = context.getAssets().openFd(filePath);
++                FileInputStream inputStream =
++                        new FileInputStream(fileDescriptor.getFileDescriptor())) {
++            FileChannel fileChannel = inputStream.getChannel();
++            long startOffset = fileDescriptor.getStartOffset();
++            long declaredLength = fileDescriptor.getDeclaredLength();
++            return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
++        }
++    }
++
++    /**
++     * Loads a binary file from the asset folder.
++     *
++     * @param context Application context to access assets.
++     * @param filePath Asset path of the file.
++     * @return the byte array for the binary file.
++     * @throws IOException if an I/O error occurs when loading file.
++     */
++    @NonNull
++    public static byte[] loadByteFromFile(@NonNull Context context, @NonNull String filePath)
++            throws IOException {
++        ByteBuffer buffer = loadMappedFile(context, filePath);
++        byte[] byteArray = new byte[buffer.remaining()];
++        buffer.get(byteArray);
++        return byteArray;
+     }
+-  }
+-
+-  /**
+-   * Loads a binary file from the asset folder.
+-   *
+-   * @param context Application context to access assets.
+-   * @param filePath Asset path of the file.
+-   * @return the byte array for the binary file.
+-   * @throws IOException if an I/O error occurs when loading file.
+-   */
+-  @NonNull
+-  public static byte[] loadByteFromFile(@NonNull Context context, @NonNull String filePath)
+-      throws IOException {
+-    ByteBuffer buffer = loadMappedFile(context, filePath);
+-    byte[] byteArray = new byte[buffer.remaining()];
+-    buffer.get(byteArray);
+-    return byteArray;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Operator.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Operator.java
+index 38dfe8818cbbc..45dfc4d9d868b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Operator.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Operator.java
+@@ -20,12 +20,11 @@ package org.tensorflow.lite.support.common;
+  * @param <T> The class which Operator handles.
+  */
+ public interface Operator<T> {
+-
+-  /**
+-   * Applies an operation on a T object, returning a T object.
+-   *
+-   * <p>Note: The returned object could probably be the same one with given input, and given input
+-   * could probably be changed.
+-   */
+-  T apply(T x);
++    /**
++     * Applies an operation on a T object, returning a T object.
++     *
++     * <p>Note: The returned object could probably be the same one with given input, and given input
++     * could probably be changed.
++     */
++    T apply(T x);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java
+index 9d0024b2f5887..a94adb89b8666 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java
+@@ -17,5 +17,5 @@ package org.tensorflow.lite.support.common;
+ 
+ /** Processes T object with prepared {@code Operator<T>}. */
+ public interface Processor<T> {
+-  T process(T input);
++    T process(T input);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java
+index af688c863c254..aa900b7c93d87 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java
+@@ -15,13 +15,14 @@ limitations under the License.
+ 
+ package org.tensorflow.lite.support.common;
+ 
++import org.checkerframework.checker.nullness.qual.NonNull;
++import org.tensorflow.lite.support.common.internal.SupportPreconditions;
++
+ import java.util.ArrayList;
+ import java.util.Collections;
+ import java.util.HashMap;
+ import java.util.List;
+ import java.util.Map;
+-import org.checkerframework.checker.nullness.qual.NonNull;
+-import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ 
+ /**
+  * A processor base class that chains a serial of {@code Operator<T>} and executes them.
+@@ -32,52 +33,50 @@ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+  * @param <T> The type that the Operator is handling.
+  */
+ public class SequentialProcessor<T> implements Processor<T> {
++    /** List of operators added to this {@link SequentialProcessor}. */
++    protected final List<Operator<T>> operatorList;
++    /**
++     * The {@link Map} between the operator name and the corresponding op indexes in {@code
++     * operatorList}. An operator may be added multiple times into this {@link SequentialProcessor}.
++     */
++    protected final Map<String, List<Integer>> operatorIndex;
+ 
+-  /** List of operators added to this {@link SequentialProcessor}. */
+-  protected final List<Operator<T>> operatorList;
+-  /**
+-   * The {@link Map} between the operator name and the corresponding op indexes in {@code
+-   * operatorList}. An operator may be added multiple times into this {@link SequentialProcessor}.
+-   */
+-  protected final Map<String, List<Integer>> operatorIndex;
+-
+-  protected SequentialProcessor(Builder<T> builder) {
+-    operatorList = builder.operatorList;
+-    operatorIndex = Collections.unmodifiableMap(builder.operatorIndex);
+-  }
++    protected SequentialProcessor(Builder<T> builder) {
++        operatorList = builder.operatorList;
++        operatorIndex = Collections.unmodifiableMap(builder.operatorIndex);
++    }
+ 
+-  @Override
+-  public T process(T x) {
+-    for (Operator<T> op : operatorList) {
+-      x = op.apply(x);
++    @Override
++    public T process(T x) {
++        for (Operator<T> op : operatorList) {
++            x = op.apply(x);
++        }
++        return x;
+     }
+-    return x;
+-  }
+ 
+-  /** The inner builder class to build a Sequential Processor. */
+-  protected static class Builder<T> {
++    /** The inner builder class to build a Sequential Processor. */
++    protected static class Builder<T> {
++        private final List<Operator<T>> operatorList;
++        private final Map<String, List<Integer>> operatorIndex;
+ 
+-    private final List<Operator<T>> operatorList;
+-    private final Map<String, List<Integer>> operatorIndex;
++        protected Builder() {
++            operatorList = new ArrayList<>();
++            operatorIndex = new HashMap<>();
++        }
+ 
+-    protected Builder() {
+-      operatorList = new ArrayList<>();
+-      operatorIndex = new HashMap<>();
+-    }
+-
+-    public Builder<T> add(@NonNull Operator<T> op) {
+-      SupportPreconditions.checkNotNull(op, "Adding null Op is illegal.");
+-      operatorList.add(op);
+-      String operatorName = op.getClass().getName();
+-      if (!operatorIndex.containsKey(operatorName)) {
+-        operatorIndex.put(operatorName, new ArrayList<Integer>());
+-      }
+-      operatorIndex.get(operatorName).add(operatorList.size() - 1);
+-      return this;
+-    }
++        public Builder<T> add(@NonNull Operator<T> op) {
++            SupportPreconditions.checkNotNull(op, "Adding null Op is illegal.");
++            operatorList.add(op);
++            String operatorName = op.getClass().getName();
++            if (!operatorIndex.containsKey(operatorName)) {
++                operatorIndex.put(operatorName, new ArrayList<Integer>());
++            }
++            operatorIndex.get(operatorName).add(operatorList.size() - 1);
++            return this;
++        }
+ 
+-    public SequentialProcessor<T> build() {
+-      return new SequentialProcessor<T>(this);
++        public SequentialProcessor<T> build() {
++            return new SequentialProcessor<T>(this);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorOperator.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorOperator.java
+index d1b7021df257c..692c2d479dcce 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorOperator.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorOperator.java
+@@ -21,7 +21,7 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * Applies some operation on TensorBuffers.
+  */
+ public interface TensorOperator extends Operator<TensorBuffer> {
+-  /** @see Operator#apply(Object) . */
+-  @Override
+-  TensorBuffer apply(TensorBuffer input);
++    /** @see Operator#apply(Object) . */
++    @Override
++    TensorBuffer apply(TensorBuffer input);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java
+index b9d3d620e9c52..4391c4523527f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java
+@@ -32,37 +32,36 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * @see TensorProcessor#process to apply the processor on a {@link TensorBuffer}.
+  */
+ public class TensorProcessor extends SequentialProcessor<TensorBuffer> {
+-  private TensorProcessor(Builder builder) {
+-    super(builder);
+-  }
+-
+-  /** The Builder to create an {@link TensorProcessor}, which could be executed later. */
+-  public static class Builder extends SequentialProcessor.Builder<TensorBuffer> {
+-
+-    /**
+-     * Creates a Builder to build {@link TensorProcessor}.
+-     *
+-     * @see #add(TensorOperator) to add an Op.
+-     * @see #build() to complete the building process and get a built Processor.
+-     */
+-    public Builder() {
+-      super();
++    private TensorProcessor(Builder builder) {
++        super(builder);
+     }
+ 
+-    /**
+-     * Adds an {@link TensorOperator} into the Operator chain.
+-     *
+-     * @param op the Operator instance to be executed then.
+-     */
+-    public TensorProcessor.Builder add(TensorOperator op) {
+-      super.add(op);
+-      return this;
+-    }
++    /** The Builder to create an {@link TensorProcessor}, which could be executed later. */
++    public static class Builder extends SequentialProcessor.Builder<TensorBuffer> {
++        /**
++         * Creates a Builder to build {@link TensorProcessor}.
++         *
++         * @see #add(TensorOperator) to add an Op.
++         * @see #build() to complete the building process and get a built Processor.
++         */
++        public Builder() {
++            super();
++        }
++
++        /**
++         * Adds an {@link TensorOperator} into the Operator chain.
++         *
++         * @param op the Operator instance to be executed then.
++         */
++        public TensorProcessor.Builder add(TensorOperator op) {
++            super.add(op);
++            return this;
++        }
+ 
+-    /** Completes the building process and gets the {@link TensorProcessor} instance. */
+-    @Override
+-    public TensorProcessor build() {
+-      return new TensorProcessor(this);
++        /** Completes the building process and gets the {@link TensorProcessor} instance. */
++        @Override
++        public TensorProcessor build() {
++            return new TensorProcessor(this);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java
+index e3e962a5f8252..29faa545b71f2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java
+@@ -19,164 +19,168 @@ import org.checkerframework.checker.nullness.qual.Nullable;
+ 
+ /** Static error checking util methods. */
+ public final class SupportPreconditions {
+-  /**
+-   * Ensures that an object reference passed as a parameter to the calling method is not null.
+-   *
+-   * @param reference an object reference
+-   * @return the non-null reference that was validated
+-   * @throws NullPointerException if {@code reference} is null
+-   */
+-  public static <T extends Object> T checkNotNull(T reference) {
+-    if (reference == null) {
+-      throw new NullPointerException("The object reference is null.");
++    /**
++     * Ensures that an object reference passed as a parameter to the calling method is not null.
++     *
++     * @param reference an object reference
++     * @return the non-null reference that was validated
++     * @throws NullPointerException if {@code reference} is null
++     */
++    public static <T extends Object> T checkNotNull(T reference) {
++        if (reference == null) {
++            throw new NullPointerException("The object reference is null.");
++        }
++        return reference;
+     }
+-    return reference;
+-  }
+-
+-  /**
+-   * Ensures that an object reference passed as a parameter to the calling method is not null.
+-   *
+-   * @param reference an object reference
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}
+-   * @return the non-null reference that was validated
+-   * @throws NullPointerException if {@code reference} is null
+-   */
+-  public static <T extends Object> T checkNotNull(T reference, @Nullable Object errorMessage) {
+-    if (reference == null) {
+-      throw new NullPointerException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures that an object reference passed as a parameter to the calling method is not null.
++     *
++     * @param reference an object reference
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}
++     * @return the non-null reference that was validated
++     * @throws NullPointerException if {@code reference} is null
++     */
++    public static <T extends Object> T checkNotNull(T reference, @Nullable Object errorMessage) {
++        if (reference == null) {
++            throw new NullPointerException(String.valueOf(errorMessage));
++        }
++        return reference;
++    }
++
++    /**
++     * Ensures that the given String is not empty and not null.
++     *
++     * @param string the String to test
++     * @return the non-null non-empty String that was validated
++     * @throws IllegalArgumentException if {@code string} is null or empty
++     */
++    public static String checkNotEmpty(String string) {
++        if (string == null || string.length() == 0) {
++            throw new IllegalArgumentException("Given String is empty or null.");
++        }
++        return string;
+     }
+-    return reference;
+-  }
+-
+-  /**
+-   * Ensures that the given String is not empty and not null.
+-   *
+-   * @param string the String to test
+-   * @return the non-null non-empty String that was validated
+-   * @throws IllegalArgumentException if {@code string} is null or empty
+-   */
+-  public static String checkNotEmpty(String string) {
+-    if (string == null || string.length() == 0) {
+-      throw new IllegalArgumentException("Given String is empty or null.");
++
++    /**
++     * Ensures that the given String is not empty and not null.
++     *
++     * @param string the String to test
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}
++     * @return the non-null non-empty String that was validated
++     * @throws IllegalArgumentException if {@code string} is null or empty
++     */
++    public static String checkNotEmpty(String string, Object errorMessage) {
++        if (string == null || string.length() == 0) {
++            throw new IllegalArgumentException(String.valueOf(errorMessage));
++        }
++        return string;
+     }
+-    return string;
+-  }
+-
+-  /**
+-   * Ensures that the given String is not empty and not null.
+-   *
+-   * @param string the String to test
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}
+-   * @return the non-null non-empty String that was validated
+-   * @throws IllegalArgumentException if {@code string} is null or empty
+-   */
+-  public static String checkNotEmpty(String string, Object errorMessage) {
+-    if (string == null || string.length() == 0) {
+-      throw new IllegalArgumentException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures the truth of an expression involving one or more parameters to the calling method.
++     *
++     * @param expression a boolean expression.
++     * @throws IllegalArgumentException if {@code expression} is false.
++     */
++    public static void checkArgument(boolean expression) {
++        if (!expression) {
++            throw new IllegalArgumentException();
++        }
+     }
+-    return string;
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving one or more parameters to the calling method.
+-   *
+-   * @param expression a boolean expression.
+-   * @throws IllegalArgumentException if {@code expression} is false.
+-   */
+-  public static void checkArgument(boolean expression) {
+-    if (!expression) {
+-      throw new IllegalArgumentException();
++
++    /**
++     * Ensures the truth of an expression involving one or more parameters to the calling method.
++     *
++     * @param expression a boolean expression.
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}.
++     * @throws IllegalArgumentException if {@code expression} is false.
++     */
++    public static void checkArgument(boolean expression, @Nullable Object errorMessage) {
++        if (!expression) {
++            throw new IllegalArgumentException(String.valueOf(errorMessage));
++        }
+     }
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving one or more parameters to the calling method.
+-   *
+-   * @param expression a boolean expression.
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}.
+-   * @throws IllegalArgumentException if {@code expression} is false.
+-   */
+-  public static void checkArgument(boolean expression, @Nullable Object errorMessage) {
+-    if (!expression) {
+-      throw new IllegalArgumentException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
++     * size
++     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
++     *
++     * @param index a user-supplied index identifying an element of an array, list or string
++     * @param size the size of that array, list or string
++     * @return the value of {@code index}
++     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
++     *         size}
++     * @throws IllegalArgumentException if {@code size} is negative
++     */
++    public static int checkElementIndex(int index, int size) {
++        return checkElementIndex(index, size, "index");
+     }
+-  }
+-
+-  /**
+-   * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of size
+-   * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
+-   *
+-   * @param index a user-supplied index identifying an element of an array, list or string
+-   * @param size the size of that array, list or string
+-   * @return the value of {@code index}
+-   * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code size}
+-   * @throws IllegalArgumentException if {@code size} is negative
+-   */
+-  public static int checkElementIndex(int index, int size) {
+-    return checkElementIndex(index, size, "index");
+-  }
+-
+-  /**
+-   * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of size
+-   * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
+-   *
+-   * @param index a user-supplied index identifying an element of an array, list or string
+-   * @param size the size of that array, list or string
+-   * @param desc the text to use to describe this index in an error message
+-   * @return the value of {@code index}
+-   * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code size}
+-   * @throws IllegalArgumentException if {@code size} is negative
+-   */
+-  public static int checkElementIndex(int index, int size, @Nullable String desc) {
+-    // Carefully optimized for execution by hotspot (explanatory comment above)
+-    if (index < 0 || index >= size) {
+-      throw new IndexOutOfBoundsException(badElementIndex(index, size, desc));
++
++    /**
++     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
++     * size
++     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
++     *
++     * @param index a user-supplied index identifying an element of an array, list or string
++     * @param size the size of that array, list or string
++     * @param desc the text to use to describe this index in an error message
++     * @return the value of {@code index}
++     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
++     *         size}
++     * @throws IllegalArgumentException if {@code size} is negative
++     */
++    public static int checkElementIndex(int index, int size, @Nullable String desc) {
++        // Carefully optimized for execution by hotspot (explanatory comment above)
++        if (index < 0 || index >= size) {
++            throw new IndexOutOfBoundsException(badElementIndex(index, size, desc));
++        }
++        return index;
+     }
+-    return index;
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving the state of the calling instance, but not
+-   * involving any parameters to the calling method.
+-   *
+-   * @param expression a boolean expression
+-   * @throws IllegalStateException if {@code expression} is false
+-   */
+-  public static void checkState(boolean expression) {
+-    if (!expression) {
+-      throw new IllegalStateException();
++
++    /**
++     * Ensures the truth of an expression involving the state of the calling instance, but not
++     * involving any parameters to the calling method.
++     *
++     * @param expression a boolean expression
++     * @throws IllegalStateException if {@code expression} is false
++     */
++    public static void checkState(boolean expression) {
++        if (!expression) {
++            throw new IllegalStateException();
++        }
+     }
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving the state of the calling instance, but not
+-   * involving any parameters to the calling method.
+-   *
+-   * @param expression a boolean expression
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}
+-   * @throws IllegalStateException if {@code expression} is false
+-   */
+-  public static void checkState(boolean expression, @Nullable Object errorMessage) {
+-    if (!expression) {
+-      throw new IllegalStateException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures the truth of an expression involving the state of the calling instance, but not
++     * involving any parameters to the calling method.
++     *
++     * @param expression a boolean expression
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}
++     * @throws IllegalStateException if {@code expression} is false
++     */
++    public static void checkState(boolean expression, @Nullable Object errorMessage) {
++        if (!expression) {
++            throw new IllegalStateException(String.valueOf(errorMessage));
++        }
+     }
+-  }
+-
+-  private static String badElementIndex(int index, int size, @Nullable String desc) {
+-    if (index < 0) {
+-      return String.format("%s (%s) must not be negative", desc, index);
+-    } else if (size < 0) {
+-      throw new IllegalArgumentException("negative size: " + size);
+-    } else { // index >= size
+-      return String.format("%s (%s) must be less than size (%s)", desc, index, size);
++
++    private static String badElementIndex(int index, int size, @Nullable String desc) {
++        if (index < 0) {
++            return String.format("%s (%s) must not be negative", desc, index);
++        } else if (size < 0) {
++            throw new IllegalArgumentException("negative size: " + size);
++        } else { // index >= size
++            return String.format("%s (%s) must be less than size (%s)", desc, index, size);
++        }
+     }
+-  }
+ 
+-  private SupportPreconditions() {
+-    throw new AssertionError("SupportPreconditions is Uninstantiable.");
+-  }
++    private SupportPreconditions() {
++        throw new AssertionError("SupportPreconditions is Uninstantiable.");
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java
+index 742a1ef90994c..a14cd1f1e503d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java
+@@ -22,34 +22,33 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /** Casts a {@link TensorBuffer} to a specified data type. */
+ public class CastOp implements TensorOperator {
++    private final DataType destinationType;
++
++    /**
++     * Constructs a CastOp.
++     *
++     * <p>Note: For only converting type for a certain {@link TensorBuffer} on-the-fly rather than
++     * in a processor, please directly use {@link TensorBuffer#createFrom(TensorBuffer, DataType)}.
++     *
++     * <p>When this Op is executed, if the original {@link TensorBuffer} is already in {@code
++     * destinationType}, the original buffer will be directly returned.
++     *
++     * @param destinationType The type of the casted {@link TensorBuffer}.
++     * @throws IllegalArgumentException if {@code destinationType} is neither {@link DataType#UINT8}
++     *     nor {@link DataType#FLOAT32}.
++     */
++    public CastOp(DataType destinationType) {
++        SupportPreconditions.checkArgument(
++                destinationType == DataType.UINT8 || destinationType == DataType.FLOAT32,
++                "Destination type " + destinationType + " is not supported.");
++        this.destinationType = destinationType;
++    }
+ 
+-  private final DataType destinationType;
+-
+-  /**
+-   * Constructs a CastOp.
+-   *
+-   * <p>Note: For only converting type for a certain {@link TensorBuffer} on-the-fly rather than in
+-   * a processor, please directly use {@link TensorBuffer#createFrom(TensorBuffer, DataType)}.
+-   *
+-   * <p>When this Op is executed, if the original {@link TensorBuffer} is already in {@code
+-   * destinationType}, the original buffer will be directly returned.
+-   *
+-   * @param destinationType The type of the casted {@link TensorBuffer}.
+-   * @throws IllegalArgumentException if {@code destinationType} is neither {@link DataType#UINT8}
+-   *     nor {@link DataType#FLOAT32}.
+-   */
+-  public CastOp(DataType destinationType) {
+-    SupportPreconditions.checkArgument(
+-        destinationType == DataType.UINT8 || destinationType == DataType.FLOAT32,
+-        "Destination type " + destinationType + " is not supported.");
+-    this.destinationType = destinationType;
+-  }
+-
+-  @Override
+-  public TensorBuffer apply(TensorBuffer input) {
+-    if (input.getDataType() == destinationType) {
+-      return input;
++    @Override
++    public TensorBuffer apply(TensorBuffer input) {
++        if (input.getDataType() == destinationType) {
++            return input;
++        }
++        return TensorBuffer.createFrom(input, destinationType);
+     }
+-    return TensorBuffer.createFrom(input, destinationType);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/DequantizeOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/DequantizeOp.java
+index 1881747870be3..8b6d183189b7f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/DequantizeOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/DequantizeOp.java
+@@ -32,9 +32,8 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * as 0.
+  */
+ public class DequantizeOp extends NormalizeOp implements TensorOperator {
+-
+-  public DequantizeOp(float zeroPoint, float scale) {
+-    // Quantization: f = (q - z) * s
+-    super(zeroPoint, 1 / scale);
+-  }
++    public DequantizeOp(float zeroPoint, float scale) {
++        // Quantization: f = (q - z) * s
++        super(zeroPoint, 1 / scale);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java
+index cff4d0b55d60a..912df13b59cec 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java
+@@ -26,135 +26,134 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBufferFloat;
+  * Normalizes a {@link TensorBuffer} with given mean and stddev: output = (input - mean) / stddev.
+  */
+ public class NormalizeOp implements TensorOperator {
++    // mean.length should always be equal to stddev.length and always >= 1.
++    private final float[] mean;
++    private final float[] stddev;
++    private final int numChannels;
++    private final boolean isIdentityOp;
+ 
+-  // mean.length should always be equal to stddev.length and always >= 1.
+-  private final float[] mean;
+-  private final float[] stddev;
+-  private final int numChannels;
+-  private final boolean isIdentityOp;
++    /**
++     * Initializes a NormalizeOp. When being called, it creates a new {@link TensorBuffer}, which
++     * satisfies:
++     *
++     * <pre>
++     *   output = (input - mean) / stddev
++     * </pre>
++     *
++     * <p>In the following two cases, reset {@code mean} to 0 and {@code stddev} to 1 to bypass the
++     * normalization. <br>
++     * 1. Both {@code mean} and {code stddev} are 0. <br>
++     * 2. {@code mean} is 0 and {stddev} is Infinity.
++     *
++     * <p>Note: If {@code mean} is set to 0 and {@code stddev} is set to 1, no computation will
++     * happen, and original input will be directly returned in execution.
++     *
++     * <p>Note: The returned {@link TensorBuffer} is always a {@link DataType#FLOAT32} tensor at
++     * present, except when the input is a {@link DataType#UINT8} tensor, {@code mean} is set to 0
++     * and
++     * {@code stddev} is set to 1, so that the original {@link DataType#UINT8} tensor is returned.
++     *
++     * @param mean the mean value to be subtracted first.
++     * @param stddev the standard deviation value to divide then.
++     * @throws IllegalArgumentException if {@code stddev} is zero.
++     */
++    public NormalizeOp(float mean, float stddev) {
++        // Make exceptions to the cases that
++        // 1. Both mean and stddev are 0.0f. This may happen when reading the normalization
++        // parameters from a tensor which does not have the values populated in the metadata. The
++        // same situation may also happen to the quantization parameters.
++        // 2. mean is 0.0f and stddev is Infinity. This may happen when reading the quantization
++        // parameters from a tensor which does not have the values populated in the metadata, and
++        // then passing the parameters into the DequantizeOp. Bypass both of the two cases, by
++        // reseting stddev to 1.0f.
++        if (mean == 0.0f && (stddev == 0.0f || Float.isInfinite(stddev))) {
++            stddev = 1.0f;
++        }
+ 
+-  /**
+-   * Initializes a NormalizeOp. When being called, it creates a new {@link TensorBuffer}, which
+-   * satisfies:
+-   *
+-   * <pre>
+-   *   output = (input - mean) / stddev
+-   * </pre>
+-   *
+-   * <p>In the following two cases, reset {@code mean} to 0 and {@code stddev} to 1 to bypass the
+-   * normalization. <br>
+-   * 1. Both {@code mean} and {code stddev} are 0. <br>
+-   * 2. {@code mean} is 0 and {stddev} is Infinity.
+-   *
+-   * <p>Note: If {@code mean} is set to 0 and {@code stddev} is set to 1, no computation will
+-   * happen, and original input will be directly returned in execution.
+-   *
+-   * <p>Note: The returned {@link TensorBuffer} is always a {@link DataType#FLOAT32} tensor at
+-   * present, except when the input is a {@link DataType#UINT8} tensor, {@code mean} is set to 0 and
+-   * {@code stddev} is set to 1, so that the original {@link DataType#UINT8} tensor is returned.
+-   *
+-   * @param mean the mean value to be subtracted first.
+-   * @param stddev the standard deviation value to divide then.
+-   * @throws IllegalArgumentException if {@code stddev} is zero.
+-   */
+-  public NormalizeOp(float mean, float stddev) {
+-    // Make exceptions to the cases that
+-    // 1. Both mean and stddev are 0.0f. This may happen when reading the normalization parameters
+-    // from a tensor which does not have the values populated in the metadata. The same situation
+-    // may also happen to the quantization parameters.
+-    // 2. mean is 0.0f and stddev is Infinity. This may happen when reading the quantization
+-    // parameters from a tensor which does not have the values populated in the metadata, and then
+-    // passing the parameters into the DequantizeOp.
+-    // Bypass both of the two cases, by reseting stddev to 1.0f.
+-    if (mean == 0.0f && (stddev == 0.0f || Float.isInfinite(stddev))) {
+-      stddev = 1.0f;
+-    }
++        SupportPreconditions.checkArgument(stddev != 0.0f, "Stddev cannot be zero.");
++        boolean meansIsZeroAndDevsIs1 = false;
++        if (mean == 0.0f && stddev == 1.0f) {
++            meansIsZeroAndDevsIs1 = true;
++        }
+ 
+-    SupportPreconditions.checkArgument(stddev != 0.0f, "Stddev cannot be zero.");
+-    boolean meansIsZeroAndDevsIs1 = false;
+-    if (mean == 0.0f && stddev == 1.0f) {
+-      meansIsZeroAndDevsIs1 = true;
++        this.isIdentityOp = meansIsZeroAndDevsIs1;
++        this.mean = new float[] {mean};
++        this.stddev = new float[] {stddev};
++        this.numChannels = 1;
+     }
+ 
+-    this.isIdentityOp = meansIsZeroAndDevsIs1;
+-    this.mean = new float[] {mean};
+-    this.stddev = new float[] {stddev};
+-    this.numChannels = 1;
+-  }
+-
+-  /**
+-   * Initializes a NormalizeOp. When being called, it creates a new {@link TensorBuffer}, which
+-   * satisfies:
+-   *
+-   * <pre>
+-   *   // Pseudo code. [...][i] means a certain element whose channel id is i.
+-   *   output[...][i] = (input[...][i] - mean[i]) / stddev[i]
+-   * </pre>
+-   *
+-   * <p>Note: If all values in {@code mean} are set to 0 and all {@code stddev} are set to 1, no
+-   * computation will happen, and original input will be directly returned in execution.
+-   *
+-   * <p>Note: The returned {@link TensorBuffer} is always a {@link DataType#FLOAT32} tensor at
+-   * present, except that the input is a {@link DataType#UINT8} tensor, all {@code mean} are set to
+-   * 0 and all {@code stddev} are set to 1.
+-   *
+-   * @param mean the mean values to be subtracted first for each channel.
+-   * @param stddev the standard deviation values to divide then for each channel.
+-   * @throws IllegalArgumentException if any {@code stddev} is zero, or {@code mean} has different
+-   *     number of elements with {@code stddev}, or any of them is empty.
+-   */
+-  public NormalizeOp(@NonNull float[] mean, @NonNull float[] stddev) {
+-    SupportPreconditions.checkNotNull(mean, "Mean cannot be null");
+-    SupportPreconditions.checkNotNull(stddev, "Stddev cannot be null");
+-    SupportPreconditions.checkArgument(
+-        mean.length == stddev.length,
+-        "Per channel normalization requires same number of means and stddevs");
+-    SupportPreconditions.checkArgument(mean.length > 0, "Means and stddevs are empty.");
+-    this.mean = mean.clone();
+-    this.stddev = stddev.clone();
+-    boolean allMeansAreZeroAndAllDevsAre1 = true;
+-    this.numChannels = mean.length;
+-    for (int i = 0; i < numChannels; i++) {
+-      SupportPreconditions.checkArgument(this.stddev[i] != 0, "Stddev cannot be zero.");
+-      if (this.stddev[i] != 1 || this.mean[i] != 0) {
+-        allMeansAreZeroAndAllDevsAre1 = false;
+-      }
++    /**
++     * Initializes a NormalizeOp. When being called, it creates a new {@link TensorBuffer}, which
++     * satisfies:
++     *
++     * <pre>
++     *   // Pseudo code. [...][i] means a certain element whose channel id is i.
++     *   output[...][i] = (input[...][i] - mean[i]) / stddev[i]
++     * </pre>
++     *
++     * <p>Note: If all values in {@code mean} are set to 0 and all {@code stddev} are set to 1, no
++     * computation will happen, and original input will be directly returned in execution.
++     *
++     * <p>Note: The returned {@link TensorBuffer} is always a {@link DataType#FLOAT32} tensor at
++     * present, except that the input is a {@link DataType#UINT8} tensor, all {@code mean} are set
++     * to 0 and all {@code stddev} are set to 1.
++     *
++     * @param mean the mean values to be subtracted first for each channel.
++     * @param stddev the standard deviation values to divide then for each channel.
++     * @throws IllegalArgumentException if any {@code stddev} is zero, or {@code mean} has different
++     *     number of elements with {@code stddev}, or any of them is empty.
++     */
++    public NormalizeOp(@NonNull float[] mean, @NonNull float[] stddev) {
++        SupportPreconditions.checkNotNull(mean, "Mean cannot be null");
++        SupportPreconditions.checkNotNull(stddev, "Stddev cannot be null");
++        SupportPreconditions.checkArgument(mean.length == stddev.length,
++                "Per channel normalization requires same number of means and stddevs");
++        SupportPreconditions.checkArgument(mean.length > 0, "Means and stddevs are empty.");
++        this.mean = mean.clone();
++        this.stddev = stddev.clone();
++        boolean allMeansAreZeroAndAllDevsAre1 = true;
++        this.numChannels = mean.length;
++        for (int i = 0; i < numChannels; i++) {
++            SupportPreconditions.checkArgument(this.stddev[i] != 0, "Stddev cannot be zero.");
++            if (this.stddev[i] != 1 || this.mean[i] != 0) {
++                allMeansAreZeroAndAllDevsAre1 = false;
++            }
++        }
++        this.isIdentityOp = allMeansAreZeroAndAllDevsAre1;
+     }
+-    this.isIdentityOp = allMeansAreZeroAndAllDevsAre1;
+-  }
+ 
+-  /**
+-   * Applies the defined normalization on given tensor and returns the result.
+-   *
+-   * <p>Note: {@code input} is possibly the same instance with the output.
+-   *
+-   * @param input input tensor. It may be the same instance with the output.
+-   * @return output tensor.
+-   */
+-  @Override
+-  @NonNull
+-  public TensorBuffer apply(@NonNull TensorBuffer input) {
+-    if (isIdentityOp) {
+-      return input;
+-    }
+-    int[] shape = input.getShape();
+-    SupportPreconditions.checkArgument(
+-        numChannels == 1 || (shape.length != 0 && shape[shape.length - 1] == numChannels),
+-        "Number of means (stddevs) is not same with number of channels (size of last axis).");
+-    // TODO(136750944): Eliminate the array copy here.
+-    float[] values = input.getFloatArray();
+-    int j = 0;
+-    for (int i = 0; i < values.length; i++) {
+-      values[i] = (values[i] - mean[j]) / stddev[j];
+-      j = (j + 1) % numChannels;
+-    }
+-    TensorBuffer output;
+-    if (input.isDynamic()) {
+-      output = TensorBufferFloat.createDynamic(DataType.FLOAT32);
+-    } else {
+-      output = TensorBufferFloat.createFixedSize(shape, DataType.FLOAT32);
++    /**
++     * Applies the defined normalization on given tensor and returns the result.
++     *
++     * <p>Note: {@code input} is possibly the same instance with the output.
++     *
++     * @param input input tensor. It may be the same instance with the output.
++     * @return output tensor.
++     */
++    @Override
++    @NonNull
++    public TensorBuffer apply(@NonNull TensorBuffer input) {
++        if (isIdentityOp) {
++            return input;
++        }
++        int[] shape = input.getShape();
++        SupportPreconditions.checkArgument(
++                numChannels == 1 || (shape.length != 0 && shape[shape.length - 1] == numChannels),
++                "Number of means (stddevs) is not same with number of channels (size of last axis).");
++        // TODO(136750944): Eliminate the array copy here.
++        float[] values = input.getFloatArray();
++        int j = 0;
++        for (int i = 0; i < values.length; i++) {
++            values[i] = (values[i] - mean[j]) / stddev[j];
++            j = (j + 1) % numChannels;
++        }
++        TensorBuffer output;
++        if (input.isDynamic()) {
++            output = TensorBufferFloat.createDynamic(DataType.FLOAT32);
++        } else {
++            output = TensorBufferFloat.createFixedSize(shape, DataType.FLOAT32);
++        }
++        output.loadArray(values, shape);
++        return output;
+     }
+-    output.loadArray(values, shape);
+-    return output;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/QuantizeOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/QuantizeOp.java
+index 8b3e82aee13ef..84cb856fd4ed9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/QuantizeOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/QuantizeOp.java
+@@ -33,9 +33,8 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * as 0.
+  */
+ public class QuantizeOp extends NormalizeOp implements TensorOperator {
+-
+-  public QuantizeOp(float zeroPoint, float scale) {
+-    // Quantization: f = (q - z) * s, i.e. q = f / s + z = (f - (-z * s)) / s
+-    super(-zeroPoint * scale, scale);
+-  }
++    public QuantizeOp(float zeroPoint, float scale) {
++        // Quantization: f = (q - z) * s, i.e. q = f / s + z = (f - (-z * s)) / s
++        super(-zeroPoint * scale, scale);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java
+index 9bee78d139efa..f9b6a1f874bff 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java
+@@ -21,67 +21,67 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import android.graphics.Bitmap;
+ import android.graphics.Bitmap.Config;
+ import android.media.Image;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /** Holds a {@link Bitmap} and converts it to other image formats as needed. */
+ final class BitmapContainer implements ImageContainer {
+-
+-  private final Bitmap bitmap;
+-
+-  /**
+-   * Creates a {@link BitmapContainer} object with ARGB_8888 {@link Bitmap}.
+-   *
+-   * @throws IllegalArgumentException if the bitmap configuration is not ARGB_8888
+-   */
+-  static BitmapContainer create(Bitmap bitmap) {
+-    return new BitmapContainer(bitmap);
+-  }
+-
+-  private BitmapContainer(Bitmap bitmap) {
+-    checkNotNull(bitmap, "Cannot load null bitmap.");
+-    checkArgument(
+-        bitmap.getConfig().equals(Config.ARGB_8888), "Only supports loading ARGB_8888 bitmaps.");
+-    this.bitmap = bitmap;
+-  }
+-
+-  @Override
+-  public BitmapContainer clone() {
+-    return create(bitmap.copy(bitmap.getConfig(), bitmap.isMutable()));
+-  }
+-
+-  @Override
+-  public Bitmap getBitmap() {
+-    // Not making a defensive copy for performance considerations. During image processing,
+-    // users may need to set and get the bitmap many times.
+-    return bitmap;
+-  }
+-
+-  @Override
+-  public TensorBuffer getTensorBuffer(DataType dataType) {
+-    TensorBuffer buffer = TensorBuffer.createDynamic(dataType);
+-    ImageConversions.convertBitmapToTensorBuffer(bitmap, buffer);
+-    return buffer;
+-  }
+-
+-  @Override
+-  public Image getMediaImage() {
+-    throw new UnsupportedOperationException(
+-        "Converting from Bitmap to android.media.Image is unsupported.");
+-  }
+-
+-  @Override
+-  public int getWidth() {
+-    return bitmap.getWidth();
+-  }
+-
+-  @Override
+-  public int getHeight() {
+-    return bitmap.getHeight();
+-  }
+-
+-  @Override
+-  public ColorSpaceType getColorSpaceType() {
+-    return ColorSpaceType.fromBitmapConfig(bitmap.getConfig());
+-  }
++    private final Bitmap bitmap;
++
++    /**
++     * Creates a {@link BitmapContainer} object with ARGB_8888 {@link Bitmap}.
++     *
++     * @throws IllegalArgumentException if the bitmap configuration is not ARGB_8888
++     */
++    static BitmapContainer create(Bitmap bitmap) {
++        return new BitmapContainer(bitmap);
++    }
++
++    private BitmapContainer(Bitmap bitmap) {
++        checkNotNull(bitmap, "Cannot load null bitmap.");
++        checkArgument(bitmap.getConfig().equals(Config.ARGB_8888),
++                "Only supports loading ARGB_8888 bitmaps.");
++        this.bitmap = bitmap;
++    }
++
++    @Override
++    public BitmapContainer clone() {
++        return create(bitmap.copy(bitmap.getConfig(), bitmap.isMutable()));
++    }
++
++    @Override
++    public Bitmap getBitmap() {
++        // Not making a defensive copy for performance considerations. During image processing,
++        // users may need to set and get the bitmap many times.
++        return bitmap;
++    }
++
++    @Override
++    public TensorBuffer getTensorBuffer(DataType dataType) {
++        TensorBuffer buffer = TensorBuffer.createDynamic(dataType);
++        ImageConversions.convertBitmapToTensorBuffer(bitmap, buffer);
++        return buffer;
++    }
++
++    @Override
++    public Image getMediaImage() {
++        throw new UnsupportedOperationException(
++                "Converting from Bitmap to android.media.Image is unsupported.");
++    }
++
++    @Override
++    public int getWidth() {
++        return bitmap.getWidth();
++    }
++
++    @Override
++    public int getHeight() {
++        return bitmap.getHeight();
++    }
++
++    @Override
++    public ColorSpaceType getColorSpaceType() {
++        return ColorSpaceType.fromBitmapConfig(bitmap.getConfig());
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java
+index 8571d6227e136..a2e833b68d6d0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java
+@@ -18,13 +18,15 @@ package org.tensorflow.lite.support.image;
+ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+ 
+ import android.graphics.RectF;
++
++import org.tensorflow.lite.DataType;
++import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
++
+ import java.nio.ByteBuffer;
+ import java.nio.FloatBuffer;
+ import java.util.ArrayList;
+ import java.util.Arrays;
+ import java.util.List;
+-import org.tensorflow.lite.DataType;
+-import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /**
+  * Helper class for converting values that represents bounding boxes into rectangles.
+@@ -37,207 +39,186 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * elements in each type is configurable as well.
+  */
+ public final class BoundingBoxUtil {
++    /** Denotes how a bounding box is represented. */
++    public enum Type {
++        /**
++         * Represents the bounding box by using the combination of boundaries, {left, top, right,
++         * bottom}. The default order is {left, top, right, bottom}. Other orders can be indicated
++         * by an index array.
++         */
++        BOUNDARIES,
++        /**
++         * Represents the bounding box by using the upper_left corner, width and height. The default
++         * order is {upper_left_x, upper_left_y, width, height}. Other orders can be indicated by an
++         * index array.
++         */
++        UPPER_LEFT,
++        /**
++         * Represents the bounding box by using the center of the box, width and height. The default
++         * order is {center_x, center_y, width, height}. Other orders can be indicated by an index
++         * array.
++         */
++        CENTER,
++    }
++
++    /** Denotes if the coordinates are actual pixels or relative ratios. */
++    public enum CoordinateType {
++        /** The coordinates are relative ratios in range [0, 1]. */
++        RATIO,
++        /** The coordinates are actual pixel values. */
++        PIXEL
++    }
+ 
+-  /** Denotes how a bounding box is represented. */
+-  public enum Type {
+-    /**
+-     * Represents the bounding box by using the combination of boundaries, {left, top, right,
+-     * bottom}. The default order is {left, top, right, bottom}. Other orders can be indicated by an
+-     * index array.
+-     */
+-    BOUNDARIES,
+-    /**
+-     * Represents the bounding box by using the upper_left corner, width and height. The default
+-     * order is {upper_left_x, upper_left_y, width, height}. Other orders can be indicated by an
+-     * index array.
+-     */
+-    UPPER_LEFT,
+     /**
+-     * Represents the bounding box by using the center of the box, width and height. The default
+-     * order is {center_x, center_y, width, height}. Other orders can be indicated by an index
+-     * array.
++     * Creates a list of bounding boxes from a {@link TensorBuffer} which represents bounding boxes.
++     *
++     * @param tensor holds the data representing some boxes.
++     * @param valueIndex denotes the order of the elements defined in each bounding box type. An
++     *         empty
++     *     index array represent the default order of each bounding box type. For example, to denote
++     *     the default order of BOUNDARIES, {left, top, right, bottom}, the index should be {0, 1,
++     * 2, 3}. To denote the order {left, right, top, bottom}, the order should be {0, 2, 1, 3}.
++     *     <p>The index array can be applied to all bounding box types to adjust the order of their
++     *     corresponding underlying elements.
++     * @param boundingBoxAxis specifies the index of the dimension that represents bounding box. The
++     *     size of that dimension is required to be 4. Index here starts from 0. For example, if the
++     *     tensor has shape 4x10, the axis for bounding boxes is likely to be 0. Negative axis is
++     * also supported: -1 gives the last axis and -2 gives the second, .etc. theFor shape 10x4, the
++     *     axis is likely to be 1 (or -1, equivalently).
++     * @param type defines how values should be converted into boxes. See {@link Type}
++     * @param coordinateType defines how values are interpreted to coordinates. See {@link
++     *     CoordinateType}
++     * @param height the height of the image which the boxes belong to. Only has effects when {@code
++     *     coordinateType} is {@link CoordinateType#RATIO}
++     * @param width the width of the image which the boxes belong to. Only has effects when {@code
++     *     coordinateType} is {@link CoordinateType#RATIO}
++     * @return A list of bounding boxes that the {@code tensor} represents. All dimensions except
++     *     {@code boundingBoxAxis} will be collapsed with order kept. For example, given {@code
++     *     tensor} with shape {1, 4, 10, 2} and {@code boundingBoxAxis = 1}, The result will be a
++     * list of 20 bounding boxes.
++     * @throws IllegalArgumentException if size of bounding box dimension (set by {@code
++     *     boundingBoxAxis}) is not 4.
++     * @throws IllegalArgumentException if {@code boundingBoxAxis} is not in {@code (-(D+1), D)}
++     *         where
++     *     {@code D} is the number of dimensions of the {@code tensor}.
++     * @throws IllegalArgumentException if {@code tensor} has data type other than {@link
++     *     DataType#FLOAT32}.
+      */
+-    CENTER,
+-  }
+-
+-  /** Denotes if the coordinates are actual pixels or relative ratios. */
+-  public enum CoordinateType {
+-    /** The coordinates are relative ratios in range [0, 1]. */
+-    RATIO,
+-    /** The coordinates are actual pixel values. */
+-    PIXEL
+-  }
+-
+-  /**
+-   * Creates a list of bounding boxes from a {@link TensorBuffer} which represents bounding boxes.
+-   *
+-   * @param tensor holds the data representing some boxes.
+-   * @param valueIndex denotes the order of the elements defined in each bounding box type. An empty
+-   *     index array represent the default order of each bounding box type. For example, to denote
+-   *     the default order of BOUNDARIES, {left, top, right, bottom}, the index should be {0, 1, 2,
+-   *     3}. To denote the order {left, right, top, bottom}, the order should be {0, 2, 1, 3}.
+-   *     <p>The index array can be applied to all bounding box types to adjust the order of their
+-   *     corresponding underlying elements.
+-   * @param boundingBoxAxis specifies the index of the dimension that represents bounding box. The
+-   *     size of that dimension is required to be 4. Index here starts from 0. For example, if the
+-   *     tensor has shape 4x10, the axis for bounding boxes is likely to be 0. Negative axis is also
+-   *     supported: -1 gives the last axis and -2 gives the second, .etc. theFor shape 10x4, the
+-   *     axis is likely to be 1 (or -1, equivalently).
+-   * @param type defines how values should be converted into boxes. See {@link Type}
+-   * @param coordinateType defines how values are interpreted to coordinates. See {@link
+-   *     CoordinateType}
+-   * @param height the height of the image which the boxes belong to. Only has effects when {@code
+-   *     coordinateType} is {@link CoordinateType#RATIO}
+-   * @param width the width of the image which the boxes belong to. Only has effects when {@code
+-   *     coordinateType} is {@link CoordinateType#RATIO}
+-   * @return A list of bounding boxes that the {@code tensor} represents. All dimensions except
+-   *     {@code boundingBoxAxis} will be collapsed with order kept. For example, given {@code
+-   *     tensor} with shape {1, 4, 10, 2} and {@code boundingBoxAxis = 1}, The result will be a list
+-   *     of 20 bounding boxes.
+-   * @throws IllegalArgumentException if size of bounding box dimension (set by {@code
+-   *     boundingBoxAxis}) is not 4.
+-   * @throws IllegalArgumentException if {@code boundingBoxAxis} is not in {@code (-(D+1), D)} where
+-   *     {@code D} is the number of dimensions of the {@code tensor}.
+-   * @throws IllegalArgumentException if {@code tensor} has data type other than {@link
+-   *     DataType#FLOAT32}.
+-   */
+-  public static List<RectF> convert(
+-      TensorBuffer tensor,
+-      int[] valueIndex,
+-      int boundingBoxAxis,
+-      Type type,
+-      CoordinateType coordinateType,
+-      int height,
+-      int width) {
+-    int[] shape = tensor.getShape();
+-    checkArgument(
+-        boundingBoxAxis >= -shape.length && boundingBoxAxis < shape.length,
+-        String.format(
+-            "Axis %d is not in range (-(D+1), D), where D is the number of dimensions of input"
+-                + " tensor (shape=%s)",
+-            boundingBoxAxis, Arrays.toString(shape)));
+-    if (boundingBoxAxis < 0) {
+-      boundingBoxAxis = shape.length + boundingBoxAxis;
+-    }
+-    checkArgument(
+-        shape[boundingBoxAxis] == 4,
+-        String.format(
+-            "Size of bounding box dimension %d is not 4. Got %d in shape %s",
+-            boundingBoxAxis, shape[boundingBoxAxis], Arrays.toString(shape)));
+-    checkArgument(
+-        valueIndex.length == 4,
+-        String.format(
+-            "Bounding box index array length %d is not 4. Got index array %s",
+-            valueIndex.length, Arrays.toString(valueIndex)));
+-    checkArgument(
+-        tensor.getDataType() == DataType.FLOAT32,
+-        "Bounding Boxes only create from FLOAT32 buffers. Got: " + tensor.getDataType().name());
+-    List<RectF> boundingBoxList = new ArrayList<>();
+-    // Collapse dimensions to {a, 4, b}. So each bounding box could be represent as (i, j), and its
+-    // four values are (i, k, j), where 0 <= k < 4. We can compute the 4 flattened index by
+-    // i * 4b + k * b + j.
+-    int a = 1;
+-    for (int i = 0; i < boundingBoxAxis; i++) {
+-      a *= shape[i];
++    public static List<RectF> convert(TensorBuffer tensor, int[] valueIndex, int boundingBoxAxis,
++            Type type, CoordinateType coordinateType, int height, int width) {
++        int[] shape = tensor.getShape();
++        checkArgument(boundingBoxAxis >= -shape.length && boundingBoxAxis < shape.length,
++                String.format(
++                        "Axis %d is not in range (-(D+1), D), where D is the number of dimensions of input"
++                                + " tensor (shape=%s)",
++                        boundingBoxAxis, Arrays.toString(shape)));
++        if (boundingBoxAxis < 0) {
++            boundingBoxAxis = shape.length + boundingBoxAxis;
++        }
++        checkArgument(shape[boundingBoxAxis] == 4,
++                String.format("Size of bounding box dimension %d is not 4. Got %d in shape %s",
++                        boundingBoxAxis, shape[boundingBoxAxis], Arrays.toString(shape)));
++        checkArgument(valueIndex.length == 4,
++                String.format("Bounding box index array length %d is not 4. Got index array %s",
++                        valueIndex.length, Arrays.toString(valueIndex)));
++        checkArgument(tensor.getDataType() == DataType.FLOAT32,
++                "Bounding Boxes only create from FLOAT32 buffers. Got: "
++                        + tensor.getDataType().name());
++        List<RectF> boundingBoxList = new ArrayList<>();
++        // Collapse dimensions to {a, 4, b}. So each bounding box could be represent as (i, j), and
++        // its four values are (i, k, j), where 0 <= k < 4. We can compute the 4 flattened index by
++        // i * 4b + k * b + j.
++        int a = 1;
++        for (int i = 0; i < boundingBoxAxis; i++) {
++            a *= shape[i];
++        }
++        int b = 1;
++        for (int i = boundingBoxAxis + 1; i < shape.length; i++) {
++            b *= shape[i];
++        }
++        float[] values = new float[4];
++        ByteBuffer byteBuffer = tensor.getBuffer();
++        byteBuffer.rewind();
++        FloatBuffer floatBuffer = byteBuffer.asFloatBuffer();
++        for (int i = 0; i < a; i++) {
++            for (int j = 0; j < b; j++) {
++                for (int k = 0; k < 4; k++) {
++                    values[k] = floatBuffer.get((i * 4 + k) * b + j);
++                }
++                boundingBoxList.add(convertOneBoundingBox(
++                        values, valueIndex, type, coordinateType, height, width));
++            }
++        }
++        byteBuffer.rewind();
++        return boundingBoxList;
+     }
+-    int b = 1;
+-    for (int i = boundingBoxAxis + 1; i < shape.length; i++) {
+-      b *= shape[i];
++
++    private static RectF convertOneBoundingBox(float[] values, int[] valueIndex, Type type,
++            CoordinateType coordinateType, int height, int width) {
++        float[] orderedValues = new float[4];
++        for (int i = 0; i < 4; i++) {
++            orderedValues[i] = values[valueIndex[i]];
++        }
++        return convertOneBoundingBox(orderedValues, type, coordinateType, height, width);
+     }
+-    float[] values = new float[4];
+-    ByteBuffer byteBuffer = tensor.getBuffer();
+-    byteBuffer.rewind();
+-    FloatBuffer floatBuffer = byteBuffer.asFloatBuffer();
+-    for (int i = 0; i < a; i++) {
+-      for (int j = 0; j < b; j++) {
+-        for (int k = 0; k < 4; k++) {
+-          values[k] = floatBuffer.get((i * 4 + k) * b + j);
++
++    private static RectF convertOneBoundingBox(
++            float[] values, Type type, CoordinateType coordinateType, int height, int width) {
++        switch (type) {
++            case BOUNDARIES:
++                return convertFromBoundaries(values, coordinateType, height, width);
++            case UPPER_LEFT:
++                return convertFromUpperLeft(values, coordinateType, height, width);
++            case CENTER:
++                return convertFromCenter(values, coordinateType, height, width);
+         }
+-        boundingBoxList.add(
+-            convertOneBoundingBox(values, valueIndex, type, coordinateType, height, width));
+-      }
++        throw new IllegalArgumentException("Cannot recognize BoundingBox.Type " + type);
+     }
+-    byteBuffer.rewind();
+-    return boundingBoxList;
+-  }
+-
+-  private static RectF convertOneBoundingBox(
+-      float[] values,
+-      int[] valueIndex,
+-      Type type,
+-      CoordinateType coordinateType,
+-      int height,
+-      int width) {
+-    float[] orderedValues = new float[4];
+-    for (int i = 0; i < 4; i++) {
+-      orderedValues[i] = values[valueIndex[i]];
++
++    private static RectF convertFromBoundaries(
++            float[] values, CoordinateType coordinateType, int imageHeight, int imageWidth) {
++        float left = values[0];
++        float top = values[1];
++        float right = values[2];
++        float bottom = values[3];
++        return getRectF(left, top, right, bottom, imageHeight, imageWidth, coordinateType);
++    }
++
++    private static RectF convertFromUpperLeft(
++            float[] values, CoordinateType coordinateType, int imageHeight, int imageWidth) {
++        float left = values[0];
++        float top = values[1];
++        float right = values[0] + values[2];
++        float bottom = values[1] + values[3];
++        return getRectF(left, top, right, bottom, imageHeight, imageWidth, coordinateType);
+     }
+-    return convertOneBoundingBox(orderedValues, type, coordinateType, height, width);
+-  }
+-
+-  private static RectF convertOneBoundingBox(
+-      float[] values, Type type, CoordinateType coordinateType, int height, int width) {
+-    switch (type) {
+-      case BOUNDARIES:
+-        return convertFromBoundaries(values, coordinateType, height, width);
+-      case UPPER_LEFT:
+-        return convertFromUpperLeft(values, coordinateType, height, width);
+-      case CENTER:
+-        return convertFromCenter(values, coordinateType, height, width);
++
++    private static RectF convertFromCenter(
++            float[] values, CoordinateType coordinateType, int imageHeight, int imageWidth) {
++        float centerX = values[0];
++        float centerY = values[1];
++        float w = values[2];
++        float h = values[3];
++
++        float left = centerX - w / 2;
++        float top = centerY - h / 2;
++        float right = centerX + w / 2;
++        float bottom = centerY + h / 2;
++        return getRectF(left, top, right, bottom, imageHeight, imageWidth, coordinateType);
+     }
+-    throw new IllegalArgumentException("Cannot recognize BoundingBox.Type " + type);
+-  }
+-
+-  private static RectF convertFromBoundaries(
+-      float[] values, CoordinateType coordinateType, int imageHeight, int imageWidth) {
+-    float left = values[0];
+-    float top = values[1];
+-    float right = values[2];
+-    float bottom = values[3];
+-    return getRectF(left, top, right, bottom, imageHeight, imageWidth, coordinateType);
+-  }
+-
+-  private static RectF convertFromUpperLeft(
+-      float[] values, CoordinateType coordinateType, int imageHeight, int imageWidth) {
+-    float left = values[0];
+-    float top = values[1];
+-    float right = values[0] + values[2];
+-    float bottom = values[1] + values[3];
+-    return getRectF(left, top, right, bottom, imageHeight, imageWidth, coordinateType);
+-  }
+-
+-  private static RectF convertFromCenter(
+-      float[] values, CoordinateType coordinateType, int imageHeight, int imageWidth) {
+-    float centerX = values[0];
+-    float centerY = values[1];
+-    float w = values[2];
+-    float h = values[3];
+-
+-    float left = centerX - w / 2;
+-    float top = centerY - h / 2;
+-    float right = centerX + w / 2;
+-    float bottom = centerY + h / 2;
+-    return getRectF(left, top, right, bottom, imageHeight, imageWidth, coordinateType);
+-  }
+-
+-  private static RectF getRectF(
+-      float left,
+-      float top,
+-      float right,
+-      float bottom,
+-      int imageHeight,
+-      int imageWidth,
+-      CoordinateType coordinateType) {
+-    if (coordinateType == CoordinateType.PIXEL) {
+-      return new RectF(left, top, right, bottom);
+-    } else if (coordinateType == CoordinateType.RATIO) {
+-      return new RectF(
+-          left * imageWidth, top * imageHeight, right * imageWidth, bottom * imageHeight);
+-    } else {
+-      throw new IllegalArgumentException("Cannot convert coordinate type " + coordinateType);
++
++    private static RectF getRectF(float left, float top, float right, float bottom, int imageHeight,
++            int imageWidth, CoordinateType coordinateType) {
++        if (coordinateType == CoordinateType.PIXEL) {
++            return new RectF(left, top, right, bottom);
++        } else if (coordinateType == CoordinateType.RATIO) {
++            return new RectF(
++                    left * imageWidth, top * imageHeight, right * imageWidth, bottom * imageHeight);
++        } else {
++            throw new IllegalArgumentException("Cannot convert coordinate type " + coordinateType);
++        }
+     }
+-  }
+ 
+-  // Private constructor to prevent initialization.
+-  private BoundingBoxUtil() {}
++    // Private constructor to prevent initialization.
++    private BoundingBoxUtil() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java
+index 457bcf1da1de3..716cacdf7bf51 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java
+@@ -20,354 +20,351 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import android.graphics.Bitmap;
+ import android.graphics.Bitmap.Config;
+ import android.graphics.ImageFormat;
+-import java.util.Arrays;
++
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.Arrays;
++
+ /** Represents the type of color space of an image. */
+ public enum ColorSpaceType {
+-  /** Each pixel has red, green, and blue color components. */
+-  RGB(0) {
+-
+-    // The channel axis should always be 3 for RGB images.
+-    private static final int CHANNEL_VALUE = 3;
+-
+-    @Override
+-    Bitmap convertTensorBufferToBitmap(TensorBuffer buffer) {
+-      return ImageConversions.convertRgbTensorBufferToBitmap(buffer);
++    /** Each pixel has red, green, and blue color components. */
++    RGB(0) {
++        // The channel axis should always be 3 for RGB images.
++        private static final int CHANNEL_VALUE = 3;
++
++        @Override
++        Bitmap convertTensorBufferToBitmap(TensorBuffer buffer) {
++            return ImageConversions.convertRgbTensorBufferToBitmap(buffer);
++        }
++
++        @Override
++        int getChannelValue() {
++            return CHANNEL_VALUE;
++        }
++
++        @Override
++        int[] getNormalizedShape(int[] shape) {
++            switch (shape.length) {
++                    // The shape is in (h, w, c) format.
++                case 3:
++                    return insertValue(shape, BATCH_DIM, BATCH_VALUE);
++                case 4:
++                    return shape;
++                default:
++                    throw new IllegalArgumentException(getShapeInfoMessage()
++                            + "The provided image shape is " + Arrays.toString(shape));
++            }
++        }
++
++        @Override
++        int getNumElements(int height, int width) {
++            return height * width * CHANNEL_VALUE;
++        }
++
++        @Override
++        String getShapeInfoMessage() {
++            return "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
++                    + " representing R, G, B in order. ";
++        }
++
++        @Override
++        Config toBitmapConfig() {
++            return Config.ARGB_8888;
++        }
++    },
++
++    /** Each pixel is a single element representing only the amount of light. */
++    GRAYSCALE(1) {
++        // The channel axis should always be 1 for grayscale images.
++        private static final int CHANNEL_VALUE = 1;
++
++        @Override
++        Bitmap convertTensorBufferToBitmap(TensorBuffer buffer) {
++            return ImageConversions.convertGrayscaleTensorBufferToBitmap(buffer);
++        }
++
++        @Override
++        int getChannelValue() {
++            return CHANNEL_VALUE;
++        }
++
++        @Override
++        int[] getNormalizedShape(int[] shape) {
++            switch (shape.length) {
++                    // The shape is in (h, w) format.
++                case 2:
++                    int[] shapeWithBatch = insertValue(shape, BATCH_DIM, BATCH_VALUE);
++                    return insertValue(shapeWithBatch, CHANNEL_DIM, CHANNEL_VALUE);
++                case 4:
++                    return shape;
++                default:
++                    // (1, h, w) and (h, w, 1) are potential grayscale image shapes. However, since
++                    // they both have three dimensions, it will require extra info to differentiate
++                    // between them. Since we haven't encountered real use cases of these two
++                    // shapes, they are not supported at this moment to avoid confusion. We may want
++                    // to revisit it in the future.
++                    throw new IllegalArgumentException(getShapeInfoMessage()
++                            + "The provided image shape is " + Arrays.toString(shape));
++            }
++        }
++
++        @Override
++        int getNumElements(int height, int width) {
++            return height * width;
++        }
++
++        @Override
++        String getShapeInfoMessage() {
++            return "The shape of a grayscale image should be (h, w) or (1, h, w, 1). ";
++        }
++
++        @Override
++        Config toBitmapConfig() {
++            return Config.ALPHA_8;
++        }
++    },
++
++    /** YUV420sp format, encoded as "YYYYYYYY UVUV". */
++    NV12(2) {
++        @Override
++        int getNumElements(int height, int width) {
++            return getYuv420NumElements(height, width);
++        }
++    },
++
++    /**
++     * YUV420sp format, encoded as "YYYYYYYY VUVU", the standard picture format on Android Camera1
++     * preview.
++     */
++    NV21(3) {
++        @Override
++        int getNumElements(int height, int width) {
++            return getYuv420NumElements(height, width);
++        }
++    },
++
++    /** YUV420p format, encoded as "YYYYYYYY VV UU". */
++    YV12(4) {
++        @Override
++        int getNumElements(int height, int width) {
++            return getYuv420NumElements(height, width);
++        }
++    },
++
++    /** YUV420p format, encoded as "YYYYYYYY UU VV". */
++    YV21(5) {
++        @Override
++        int getNumElements(int height, int width) {
++            return getYuv420NumElements(height, width);
++        }
++    },
++
++    /**
++     * YUV420 format corresponding to {@link android.graphics.ImageFormat#YUV_420_888}. The actual
++     * encoding format (i.e. NV12 / Nv21 / YV12 / YV21) depends on the implementation of the image.
++     *
++     * <p>Use this format only when you load an {@link android.media.Image}.
++     */
++    YUV_420_888(6) {
++        @Override
++        int getNumElements(int height, int width) {
++            return getYuv420NumElements(height, width);
++        }
++    };
++
++    private static final int BATCH_DIM = 0; // The first element of the normalizaed shape.
++    private static final int BATCH_VALUE = 1; // The batch axis should always be one.
++    private static final int HEIGHT_DIM = 1; // The second element of the normalizaed shape.
++    private static final int WIDTH_DIM = 2; // The third element of the normalizaed shape.
++    private static final int CHANNEL_DIM = 3; // The fourth element of the normalizaed shape.
++    private final int value;
++
++    ColorSpaceType(int value) {
++        this.value = value;
+     }
+ 
+-    @Override
+-    int getChannelValue() {
+-      return CHANNEL_VALUE;
++    /**
++     * Converts a bitmap configuration into the corresponding color space type.
++     *
++     * @throws IllegalArgumentException if the config is unsupported
++     */
++    static ColorSpaceType fromBitmapConfig(Config config) {
++        switch (config) {
++            case ARGB_8888:
++                return ColorSpaceType.RGB;
++            case ALPHA_8:
++                return ColorSpaceType.GRAYSCALE;
++            default:
++                throw new IllegalArgumentException(
++                        "Bitmap configuration: " + config + ", is not supported yet.");
++        }
+     }
+ 
+-    @Override
+-    int[] getNormalizedShape(int[] shape) {
+-      switch (shape.length) {
+-          // The shape is in (h, w, c) format.
+-        case 3:
+-          return insertValue(shape, BATCH_DIM, BATCH_VALUE);
+-        case 4:
+-          return shape;
+-        default:
+-          throw new IllegalArgumentException(
+-              getShapeInfoMessage() + "The provided image shape is " + Arrays.toString(shape));
+-      }
++    /**
++     * Converts an {@link ImageFormat} value into the corresponding color space type.
++     *
++     * @throws IllegalArgumentException if the config is unsupported
++     */
++    static ColorSpaceType fromImageFormat(int imageFormat) {
++        switch (imageFormat) {
++            case ImageFormat.NV21:
++                return ColorSpaceType.NV21;
++            case ImageFormat.YV12:
++                return ColorSpaceType.YV12;
++            case ImageFormat.YUV_420_888:
++                return ColorSpaceType.YUV_420_888;
++            default:
++                throw new IllegalArgumentException(
++                        "ImageFormat: " + imageFormat + ", is not supported yet.");
++        }
+     }
+ 
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return height * width * CHANNEL_VALUE;
++    public int getValue() {
++        return value;
+     }
+ 
+-    @Override
+-    String getShapeInfoMessage() {
+-      return "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+-          + " representing R, G, B in order. ";
++    /**
++     * Verifies if the given shape matches the color space type.
++     *
++     * @throws IllegalArgumentException if {@code shape} does not match the color space type
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
++    void assertShape(int[] shape) {
++        assertRgbOrGrayScale("assertShape()");
++
++        int[] normalizedShape = getNormalizedShape(shape);
++        checkArgument(isValidNormalizedShape(normalizedShape),
++                getShapeInfoMessage() + "The provided image shape is " + Arrays.toString(shape));
+     }
+ 
+-    @Override
+-    Config toBitmapConfig() {
+-      return Config.ARGB_8888;
++    /**
++     * Verifies if the given {@code numElements} in an image buffer matches {@code height} / {@code
++     * width} under this color space type. For example, the {@code numElements} of an RGB image of
++     * 30 x 20 should be {@code 30 * 20 * 3 = 1800}; the {@code numElements} of a NV21 image of 30 x
++     * 20 should be {@code 30 * 20 + ((30 + 1) / 2 * (20 + 1) / 2) * 2 = 952}.
++     *
++     * @throws IllegalArgumentException if {@code shape} does not match the color space type
++     */
++    void assertNumElements(int numElements, int height, int width) {
++        checkArgument(numElements >= getNumElements(height, width),
++                String.format(
++                        "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
++                                + " expected number of elements should be at least %d.",
++                        numElements, this.name(), height, width, getNumElements(height, width)));
+     }
+-  },
+-
+-  /** Each pixel is a single element representing only the amount of light. */
+-  GRAYSCALE(1) {
+-
+-    // The channel axis should always be 1 for grayscale images.
+-    private static final int CHANNEL_VALUE = 1;
+ 
+-    @Override
++    /**
++     * Converts a {@link TensorBuffer} that represents an image to a Bitmap with the color space
++     * type.
++     *
++     * @throws IllegalArgumentException if the shape of buffer does not match the color space type,
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
+     Bitmap convertTensorBufferToBitmap(TensorBuffer buffer) {
+-      return ImageConversions.convertGrayscaleTensorBufferToBitmap(buffer);
++        throw new UnsupportedOperationException(
++                "convertTensorBufferToBitmap() is unsupported for the color space type "
++                + this.name());
+     }
+ 
+-    @Override
+-    int getChannelValue() {
+-      return CHANNEL_VALUE;
++    /**
++     * Returns the width of the given shape corresponding to the color space type.
++     *
++     * @throws IllegalArgumentException if {@code shape} does not match the color space type
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
++    int getWidth(int[] shape) {
++        assertRgbOrGrayScale("getWidth()");
++        assertShape(shape);
++        return getNormalizedShape(shape)[WIDTH_DIM];
+     }
+ 
+-    @Override
+-    int[] getNormalizedShape(int[] shape) {
+-      switch (shape.length) {
+-          // The shape is in (h, w) format.
+-        case 2:
+-          int[] shapeWithBatch = insertValue(shape, BATCH_DIM, BATCH_VALUE);
+-          return insertValue(shapeWithBatch, CHANNEL_DIM, CHANNEL_VALUE);
+-        case 4:
+-          return shape;
+-        default:
+-          // (1, h, w) and (h, w, 1) are potential grayscale image shapes. However, since they
+-          // both have three dimensions, it will require extra info to differentiate between them.
+-          // Since we haven't encountered real use cases of these two shapes, they are not supported
+-          // at this moment to avoid confusion. We may want to revisit it in the future.
+-          throw new IllegalArgumentException(
+-              getShapeInfoMessage() + "The provided image shape is " + Arrays.toString(shape));
+-      }
++    /**
++     * Returns the height of the given shape corresponding to the color space type.
++     *
++     * @throws IllegalArgumentException if {@code shape} does not match the color space type
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
++    int getHeight(int[] shape) {
++        assertRgbOrGrayScale("getHeight()");
++        assertShape(shape);
++        return getNormalizedShape(shape)[HEIGHT_DIM];
+     }
+ 
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return height * width;
++    /**
++     * Returns the channel value corresponding to the color space type.
++     *
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
++    int getChannelValue() {
++        throw new UnsupportedOperationException(
++                "getChannelValue() is unsupported for the color space type " + this.name());
++    }
++    /**
++     * Gets the normalized shape in the form of (1, h, w, c). Sometimes, a given shape may not have
++     * batch or channel axis.
++     *
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
++    int[] getNormalizedShape(int[] shape) {
++        throw new UnsupportedOperationException(
++                "getNormalizedShape() is unsupported for the color space type " + this.name());
+     }
+ 
+-    @Override
++    /**
++     * Returns the shape information corresponding to the color space type.
++     *
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
+     String getShapeInfoMessage() {
+-      return "The shape of a grayscale image should be (h, w) or (1, h, w, 1). ";
++        throw new UnsupportedOperationException(
++                "getShapeInfoMessage() is unsupported for the color space type " + this.name());
+     }
+ 
+-    @Override
++    /**
++     * Converts the color space type to the corresponding bitmap config.
++     *
++     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
++     */
+     Config toBitmapConfig() {
+-      return Config.ALPHA_8;
++        throw new UnsupportedOperationException(
++                "toBitmapConfig() is unsupported for the color space type " + this.name());
+     }
+-  },
+ 
+-  /** YUV420sp format, encoded as "YYYYYYYY UVUV". */
+-  NV12(2) {
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return getYuv420NumElements(height, width);
+-    }
+-  },
+-
+-  /**
+-   * YUV420sp format, encoded as "YYYYYYYY VUVU", the standard picture format on Android Camera1
+-   * preview.
+-   */
+-  NV21(3) {
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return getYuv420NumElements(height, width);
+-    }
+-  },
++    /**
++     * Gets the number of elements given the height and width of an image. For example, the number
++     * of elements of an RGB image of 30 x 20 is {@code 30 * 20 * 3 = 1800}; the number of elements
++     * of a NV21 image of 30 x 20 is {@code 30 * 20 + ((30 + 1) / 2 * (20 + 1) / 2) * 2 = 952}.
++     */
++    abstract int getNumElements(int height, int width);
+ 
+-  /** YUV420p format, encoded as "YYYYYYYY VV UU". */
+-  YV12(4) {
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return getYuv420NumElements(height, width);
++    private static int getYuv420NumElements(int height, int width) {
++        // Height and width of U/V planes are half of the Y plane.
++        return height * width + ((height + 1) / 2) * ((width + 1) / 2) * 2;
+     }
+-  },
+ 
+-  /** YUV420p format, encoded as "YYYYYYYY UU VV". */
+-  YV21(5) {
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return getYuv420NumElements(height, width);
++    /** Inserts a value at the specified position and return the new array. */
++    private static int[] insertValue(int[] array, int pos, int value) {
++        int[] newArray = new int[array.length + 1];
++        for (int i = 0; i < pos; i++) {
++            newArray[i] = array[i];
++        }
++        newArray[pos] = value;
++        for (int i = pos + 1; i < newArray.length; i++) {
++            newArray[i] = array[i - 1];
++        }
++        return newArray;
+     }
+-  },
+-
+-  /**
+-   * YUV420 format corresponding to {@link android.graphics.ImageFormat#YUV_420_888}. The actual
+-   * encoding format (i.e. NV12 / Nv21 / YV12 / YV21) depends on the implementation of the image.
+-   *
+-   * <p>Use this format only when you load an {@link android.media.Image}.
+-   */
+-  YUV_420_888(6) {
+-    @Override
+-    int getNumElements(int height, int width) {
+-      return getYuv420NumElements(height, width);
+-    }
+-  };
+-
+-  private static final int BATCH_DIM = 0; // The first element of the normalizaed shape.
+-  private static final int BATCH_VALUE = 1; // The batch axis should always be one.
+-  private static final int HEIGHT_DIM = 1; // The second element of the normalizaed shape.
+-  private static final int WIDTH_DIM = 2; // The third element of the normalizaed shape.
+-  private static final int CHANNEL_DIM = 3; // The fourth element of the normalizaed shape.
+-  private final int value;
+-
+-  ColorSpaceType(int value) {
+-    this.value = value;
+-  }
+-
+-  /**
+-   * Converts a bitmap configuration into the corresponding color space type.
+-   *
+-   * @throws IllegalArgumentException if the config is unsupported
+-   */
+-  static ColorSpaceType fromBitmapConfig(Config config) {
+-    switch (config) {
+-      case ARGB_8888:
+-        return ColorSpaceType.RGB;
+-      case ALPHA_8:
+-        return ColorSpaceType.GRAYSCALE;
+-      default:
+-        throw new IllegalArgumentException(
+-            "Bitmap configuration: " + config + ", is not supported yet.");
+-    }
+-  }
+-
+-  /**
+-   * Converts an {@link ImageFormat} value into the corresponding color space type.
+-   *
+-   * @throws IllegalArgumentException if the config is unsupported
+-   */
+-  static ColorSpaceType fromImageFormat(int imageFormat) {
+-    switch (imageFormat) {
+-      case ImageFormat.NV21:
+-        return ColorSpaceType.NV21;
+-      case ImageFormat.YV12:
+-        return ColorSpaceType.YV12;
+-      case ImageFormat.YUV_420_888:
+-        return ColorSpaceType.YUV_420_888;
+-      default:
+-        throw new IllegalArgumentException(
+-            "ImageFormat: " + imageFormat + ", is not supported yet.");
+-    }
+-  }
+-
+-  public int getValue() {
+-    return value;
+-  }
+-
+-  /**
+-   * Verifies if the given shape matches the color space type.
+-   *
+-   * @throws IllegalArgumentException if {@code shape} does not match the color space type
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  void assertShape(int[] shape) {
+-    assertRgbOrGrayScale("assertShape()");
+-
+-    int[] normalizedShape = getNormalizedShape(shape);
+-    checkArgument(
+-        isValidNormalizedShape(normalizedShape),
+-        getShapeInfoMessage() + "The provided image shape is " + Arrays.toString(shape));
+-  }
+-
+-  /**
+-   * Verifies if the given {@code numElements} in an image buffer matches {@code height} / {@code
+-   * width} under this color space type. For example, the {@code numElements} of an RGB image of 30
+-   * x 20 should be {@code 30 * 20 * 3 = 1800}; the {@code numElements} of a NV21 image of 30 x 20
+-   * should be {@code 30 * 20 + ((30 + 1) / 2 * (20 + 1) / 2) * 2 = 952}.
+-   *
+-   * @throws IllegalArgumentException if {@code shape} does not match the color space type
+-   */
+-  void assertNumElements(int numElements, int height, int width) {
+-    checkArgument(
+-        numElements >= getNumElements(height, width),
+-        String.format(
+-            "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
+-                + " expected number of elements should be at least %d.",
+-            numElements, this.name(), height, width, getNumElements(height, width)));
+-  }
+-
+-  /**
+-   * Converts a {@link TensorBuffer} that represents an image to a Bitmap with the color space type.
+-   *
+-   * @throws IllegalArgumentException if the shape of buffer does not match the color space type,
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  Bitmap convertTensorBufferToBitmap(TensorBuffer buffer) {
+-    throw new UnsupportedOperationException(
+-        "convertTensorBufferToBitmap() is unsupported for the color space type " + this.name());
+-  }
+-
+-  /**
+-   * Returns the width of the given shape corresponding to the color space type.
+-   *
+-   * @throws IllegalArgumentException if {@code shape} does not match the color space type
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  int getWidth(int[] shape) {
+-    assertRgbOrGrayScale("getWidth()");
+-    assertShape(shape);
+-    return getNormalizedShape(shape)[WIDTH_DIM];
+-  }
+-
+-  /**
+-   * Returns the height of the given shape corresponding to the color space type.
+-   *
+-   * @throws IllegalArgumentException if {@code shape} does not match the color space type
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  int getHeight(int[] shape) {
+-    assertRgbOrGrayScale("getHeight()");
+-    assertShape(shape);
+-    return getNormalizedShape(shape)[HEIGHT_DIM];
+-  }
+-
+-  /**
+-   * Returns the channel value corresponding to the color space type.
+-   *
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  int getChannelValue() {
+-    throw new UnsupportedOperationException(
+-        "getChannelValue() is unsupported for the color space type " + this.name());
+-  }
+-  /**
+-   * Gets the normalized shape in the form of (1, h, w, c). Sometimes, a given shape may not have
+-   * batch or channel axis.
+-   *
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  int[] getNormalizedShape(int[] shape) {
+-    throw new UnsupportedOperationException(
+-        "getNormalizedShape() is unsupported for the color space type " + this.name());
+-  }
+-
+-  /**
+-   * Returns the shape information corresponding to the color space type.
+-   *
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  String getShapeInfoMessage() {
+-    throw new UnsupportedOperationException(
+-        "getShapeInfoMessage() is unsupported for the color space type " + this.name());
+-  }
+-
+-  /**
+-   * Converts the color space type to the corresponding bitmap config.
+-   *
+-   * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+-   */
+-  Config toBitmapConfig() {
+-    throw new UnsupportedOperationException(
+-        "toBitmapConfig() is unsupported for the color space type " + this.name());
+-  }
+-
+-  /**
+-   * Gets the number of elements given the height and width of an image. For example, the number of
+-   * elements of an RGB image of 30 x 20 is {@code 30 * 20 * 3 = 1800}; the number of elements of a
+-   * NV21 image of 30 x 20 is {@code 30 * 20 + ((30 + 1) / 2 * (20 + 1) / 2) * 2 = 952}.
+-   */
+-  abstract int getNumElements(int height, int width);
+-
+-  private static int getYuv420NumElements(int height, int width) {
+-    // Height and width of U/V planes are half of the Y plane.
+-    return height * width + ((height + 1) / 2) * ((width + 1) / 2) * 2;
+-  }
+-
+-  /** Inserts a value at the specified position and return the new array. */
+-  private static int[] insertValue(int[] array, int pos, int value) {
+-    int[] newArray = new int[array.length + 1];
+-    for (int i = 0; i < pos; i++) {
+-      newArray[i] = array[i];
+-    }
+-    newArray[pos] = value;
+-    for (int i = pos + 1; i < newArray.length; i++) {
+-      newArray[i] = array[i - 1];
++
++    protected boolean isValidNormalizedShape(int[] shape) {
++        return shape[BATCH_DIM] == BATCH_VALUE && shape[HEIGHT_DIM] > 0 && shape[WIDTH_DIM] > 0
++                && shape[CHANNEL_DIM] == getChannelValue();
+     }
+-    return newArray;
+-  }
+-
+-  protected boolean isValidNormalizedShape(int[] shape) {
+-    return shape[BATCH_DIM] == BATCH_VALUE
+-        && shape[HEIGHT_DIM] > 0
+-        && shape[WIDTH_DIM] > 0
+-        && shape[CHANNEL_DIM] == getChannelValue();
+-  }
+-
+-  /** Some existing methods are only valid for RGB and GRAYSCALE images. */
+-  private void assertRgbOrGrayScale(String unsupportedMethodName) {
+-    if (this != ColorSpaceType.RGB && this != ColorSpaceType.GRAYSCALE) {
+-      throw new UnsupportedOperationException(
+-          unsupportedMethodName
+-              + " only supports RGB and GRAYSCALE formats, but not "
+-              + this.name());
++
++    /** Some existing methods are only valid for RGB and GRAYSCALE images. */
++    private void assertRgbOrGrayScale(String unsupportedMethodName) {
++        if (this != ColorSpaceType.RGB && this != ColorSpaceType.GRAYSCALE) {
++            throw new UnsupportedOperationException(unsupportedMethodName
++                    + " only supports RGB and GRAYSCALE formats, but not " + this.name());
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java
+index 379d14798d62d..5c097da5ecb6d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java
+@@ -17,6 +17,7 @@ package org.tensorflow.lite.support.image;
+ 
+ import android.graphics.Bitmap;
+ import android.media.Image;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+@@ -32,28 +33,27 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * </ul>
+  */
+ interface ImageContainer {
++    /** Performs deep copy of the {@link ImageContainer}. */
++    ImageContainer clone();
+ 
+-  /** Performs deep copy of the {@link ImageContainer}. */
+-  ImageContainer clone();
+-
+-  /** Returns the width of the image. */
+-  int getWidth();
++    /** Returns the width of the image. */
++    int getWidth();
+ 
+-  /** Returns the height of the image. */
+-  int getHeight();
++    /** Returns the height of the image. */
++    int getHeight();
+ 
+-  /** Gets the {@link Bitmap} representation of the underlying image format. */
+-  Bitmap getBitmap();
++    /** Gets the {@link Bitmap} representation of the underlying image format. */
++    Bitmap getBitmap();
+ 
+-  /**
+-   * Gets the {@link TensorBuffer} representation with the specific {@code dataType} of the
+-   * underlying image format.
+-   */
+-  TensorBuffer getTensorBuffer(DataType dataType);
++    /**
++     * Gets the {@link TensorBuffer} representation with the specific {@code dataType} of the
++     * underlying image format.
++     */
++    TensorBuffer getTensorBuffer(DataType dataType);
+ 
+-  /** Gets the {@link Image} representation of the underlying image format. */
+-  Image getMediaImage();
++    /** Gets the {@link Image} representation of the underlying image format. */
++    Image getMediaImage();
+ 
+-  /** Returns the color space type of the image. */
+-  ColorSpaceType getColorSpaceType();
++    /** Returns the color space type of the image. */
++    ColorSpaceType getColorSpaceType();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java
+index 8ed169c49348e..7ed5306fd9f96 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java
+@@ -17,128 +17,127 @@ package org.tensorflow.lite.support.image;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.Color;
+-import java.nio.ByteBuffer;
+-import java.nio.ByteOrder;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.nio.ByteBuffer;
++import java.nio.ByteOrder;
++
+ /**
+  * Implements some stateless image conversion methods.
+  *
+  * <p>This class is an internal helper for {@link org.tensorflow.lite.support.image}.
+  */
+ class ImageConversions {
++    /**
++     * Converts a {@link TensorBuffer} that represents a RGB image to an ARGB_8888 Bitmap.
++     *
++     * <p>Data in buffer will be converted into integer to match the Bitmap API.
++     *
++     * @param buffer a RGB image. Its shape should be either (h, w, 3) or (1, h, w, 3)
++     * @throws IllegalArgumentException if the shape of buffer is neither (h, w, 3) nor (1, h, w, 3)
++     */
++    static Bitmap convertRgbTensorBufferToBitmap(TensorBuffer buffer) {
++        int[] shape = buffer.getShape();
++        ColorSpaceType rgb = ColorSpaceType.RGB;
++        rgb.assertShape(shape);
+ 
+-  /**
+-   * Converts a {@link TensorBuffer} that represents a RGB image to an ARGB_8888 Bitmap.
+-   *
+-   * <p>Data in buffer will be converted into integer to match the Bitmap API.
+-   *
+-   * @param buffer a RGB image. Its shape should be either (h, w, 3) or (1, h, w, 3)
+-   * @throws IllegalArgumentException if the shape of buffer is neither (h, w, 3) nor (1, h, w, 3)
+-   */
+-  static Bitmap convertRgbTensorBufferToBitmap(TensorBuffer buffer) {
+-    int[] shape = buffer.getShape();
+-    ColorSpaceType rgb = ColorSpaceType.RGB;
+-    rgb.assertShape(shape);
+-
+-    int h = rgb.getHeight(shape);
+-    int w = rgb.getWidth(shape);
+-    Bitmap bitmap = Bitmap.createBitmap(w, h, rgb.toBitmapConfig());
+-
+-    // TODO(b/138904567): Find a way to avoid creating multiple intermediate buffers every time.
+-    int[] intValues = new int[w * h];
+-    int[] rgbValues = buffer.getIntArray();
+-    for (int i = 0, j = 0; i < intValues.length; i++) {
+-      int r = rgbValues[j++];
+-      int g = rgbValues[j++];
+-      int b = rgbValues[j++];
+-      intValues[i] = Color.rgb(r, g, b);
+-    }
+-    bitmap.setPixels(intValues, 0, w, 0, 0, w, h);
+-
+-    return bitmap;
+-  }
+-
+-  /**
+-   * Converts a {@link TensorBuffer} that represents a grayscale image to an ALPHA_8 Bitmap.
+-   *
+-   * <p>Data in buffer will be converted into integer to match the Bitmap API.
+-   *
+-   * @param buffer a grayscale image. Its shape should be either (h, w) or (1, h, w)
+-   * @throws IllegalArgumentException if the shape of buffer is neither (h, w) nor (1, h, w, 1)
+-   */
+-  static Bitmap convertGrayscaleTensorBufferToBitmap(TensorBuffer buffer) {
+-    // Convert buffer into Uint8 as needed.
+-    TensorBuffer uint8Buffer =
+-        buffer.getDataType() == DataType.UINT8
+-            ? buffer
+-            : TensorBuffer.createFrom(buffer, DataType.UINT8);
+-
+-    int[] shape = uint8Buffer.getShape();
+-    ColorSpaceType grayscale = ColorSpaceType.GRAYSCALE;
+-    grayscale.assertShape(shape);
+-
+-    // Even though `Bitmap.createBitmap(int[] colors, int width, int height, Bitmap.Config config)`
+-    // seems to work for internal Android testing framework, but it actually doesn't work for the
+-    // real Android environment.
+-    //
+-    // The only reliable way to create an ALPHA_8 Bitmap is to use `copyPixelsFromBuffer()` to load
+-    // the pixels from a ByteBuffer, and then use `copyPixelsToBuffer` to read out.
+-    // Note: for ALPHA_8 Bitmap, methods such as, `setPixels()` and `getPixels()` do not work.
+-    Bitmap bitmap =
+-        Bitmap.createBitmap(
+-            grayscale.getWidth(shape), grayscale.getHeight(shape), grayscale.toBitmapConfig());
+-    uint8Buffer.getBuffer().rewind();
+-    bitmap.copyPixelsFromBuffer(uint8Buffer.getBuffer());
+-    return bitmap;
+-  }
+-
+-  /**
+-   * Converts an Image in a Bitmap to a TensorBuffer (3D Tensor: Width-Height-Channel) whose memory
+-   * is already allocated, or could be dynamically allocated.
+-   *
+-   * @param bitmap The Bitmap object representing the image. Currently we only support ARGB_8888
+-   *     config.
+-   * @param buffer The destination of the conversion. Needs to be created in advance. If it's
+-   *     fixed-size, its flat size should be w*h*3.
+-   * @throws IllegalArgumentException if the buffer is fixed-size, but the size doesn't match.
+-   */
+-  static void convertBitmapToTensorBuffer(Bitmap bitmap, TensorBuffer buffer) {
+-    int w = bitmap.getWidth();
+-    int h = bitmap.getHeight();
+-    int[] intValues = new int[w * h];
+-    bitmap.getPixels(intValues, 0, w, 0, 0, w, h);
+-    // TODO(b/138904567): Find a way to avoid creating multiple intermediate buffers every time.
+-    int[] shape = new int[] {h, w, 3};
+-    switch (buffer.getDataType()) {
+-      case UINT8:
+-        byte[] byteArr = new byte[w * h * 3];
++        int h = rgb.getHeight(shape);
++        int w = rgb.getWidth(shape);
++        Bitmap bitmap = Bitmap.createBitmap(w, h, rgb.toBitmapConfig());
++
++        // TODO(b/138904567): Find a way to avoid creating multiple intermediate buffers every time.
++        int[] intValues = new int[w * h];
++        int[] rgbValues = buffer.getIntArray();
+         for (int i = 0, j = 0; i < intValues.length; i++) {
+-          byteArr[j++] = (byte) ((intValues[i] >> 16) & 0xff);
+-          byteArr[j++] = (byte) ((intValues[i] >> 8) & 0xff);
+-          byteArr[j++] = (byte) (intValues[i] & 0xff);
++            int r = rgbValues[j++];
++            int g = rgbValues[j++];
++            int b = rgbValues[j++];
++            intValues[i] = Color.rgb(r, g, b);
+         }
+-        ByteBuffer byteBuffer = ByteBuffer.wrap(byteArr);
+-        byteBuffer.order(ByteOrder.nativeOrder());
+-        buffer.loadBuffer(byteBuffer, shape);
+-        break;
+-      case FLOAT32:
+-        float[] floatArr = new float[w * h * 3];
+-        for (int i = 0, j = 0; i < intValues.length; i++) {
+-          floatArr[j++] = (float) ((intValues[i] >> 16) & 0xff);
+-          floatArr[j++] = (float) ((intValues[i] >> 8) & 0xff);
+-          floatArr[j++] = (float) (intValues[i] & 0xff);
++        bitmap.setPixels(intValues, 0, w, 0, 0, w, h);
++
++        return bitmap;
++    }
++
++    /**
++     * Converts a {@link TensorBuffer} that represents a grayscale image to an ALPHA_8 Bitmap.
++     *
++     * <p>Data in buffer will be converted into integer to match the Bitmap API.
++     *
++     * @param buffer a grayscale image. Its shape should be either (h, w) or (1, h, w)
++     * @throws IllegalArgumentException if the shape of buffer is neither (h, w) nor (1, h, w, 1)
++     */
++    static Bitmap convertGrayscaleTensorBufferToBitmap(TensorBuffer buffer) {
++        // Convert buffer into Uint8 as needed.
++        TensorBuffer uint8Buffer = buffer.getDataType() == DataType.UINT8
++                ? buffer
++                : TensorBuffer.createFrom(buffer, DataType.UINT8);
++
++        int[] shape = uint8Buffer.getShape();
++        ColorSpaceType grayscale = ColorSpaceType.GRAYSCALE;
++        grayscale.assertShape(shape);
++
++        // Even though `Bitmap.createBitmap(int[] colors, int width, int height, Bitmap.Config
++        // config)` seems to work for internal Android testing framework, but it actually doesn't
++        // work for the real Android environment.
++        //
++        // The only reliable way to create an ALPHA_8 Bitmap is to use `copyPixelsFromBuffer()` to
++        // load the pixels from a ByteBuffer, and then use `copyPixelsToBuffer` to read out. Note:
++        // for ALPHA_8 Bitmap, methods such as, `setPixels()` and `getPixels()` do not work.
++        Bitmap bitmap = Bitmap.createBitmap(
++                grayscale.getWidth(shape), grayscale.getHeight(shape), grayscale.toBitmapConfig());
++        uint8Buffer.getBuffer().rewind();
++        bitmap.copyPixelsFromBuffer(uint8Buffer.getBuffer());
++        return bitmap;
++    }
++
++    /**
++     * Converts an Image in a Bitmap to a TensorBuffer (3D Tensor: Width-Height-Channel) whose
++     * memory is already allocated, or could be dynamically allocated.
++     *
++     * @param bitmap The Bitmap object representing the image. Currently we only support ARGB_8888
++     *     config.
++     * @param buffer The destination of the conversion. Needs to be created in advance. If it's
++     *     fixed-size, its flat size should be w*h*3.
++     * @throws IllegalArgumentException if the buffer is fixed-size, but the size doesn't match.
++     */
++    static void convertBitmapToTensorBuffer(Bitmap bitmap, TensorBuffer buffer) {
++        int w = bitmap.getWidth();
++        int h = bitmap.getHeight();
++        int[] intValues = new int[w * h];
++        bitmap.getPixels(intValues, 0, w, 0, 0, w, h);
++        // TODO(b/138904567): Find a way to avoid creating multiple intermediate buffers every time.
++        int[] shape = new int[] {h, w, 3};
++        switch (buffer.getDataType()) {
++            case UINT8:
++                byte[] byteArr = new byte[w * h * 3];
++                for (int i = 0, j = 0; i < intValues.length; i++) {
++                    byteArr[j++] = (byte) ((intValues[i] >> 16) & 0xff);
++                    byteArr[j++] = (byte) ((intValues[i] >> 8) & 0xff);
++                    byteArr[j++] = (byte) (intValues[i] & 0xff);
++                }
++                ByteBuffer byteBuffer = ByteBuffer.wrap(byteArr);
++                byteBuffer.order(ByteOrder.nativeOrder());
++                buffer.loadBuffer(byteBuffer, shape);
++                break;
++            case FLOAT32:
++                float[] floatArr = new float[w * h * 3];
++                for (int i = 0, j = 0; i < intValues.length; i++) {
++                    floatArr[j++] = (float) ((intValues[i] >> 16) & 0xff);
++                    floatArr[j++] = (float) ((intValues[i] >> 8) & 0xff);
++                    floatArr[j++] = (float) (intValues[i] & 0xff);
++                }
++                buffer.loadArray(floatArr, shape);
++                break;
++            default:
++                // Should never happen.
++                throw new IllegalStateException(
++                        "The type of TensorBuffer, " + buffer.getBuffer() + ", is unsupported.");
+         }
+-        buffer.loadArray(floatArr, shape);
+-        break;
+-      default:
+-        // Should never happen.
+-        throw new IllegalStateException(
+-            "The type of TensorBuffer, " + buffer.getBuffer() + ", is unsupported.");
+     }
+-  }
+ 
+-  // Hide the constructor as the class is static.
+-  private ImageConversions() {}
++    // Hide the constructor as the class is static.
++    private ImageConversions() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageOperator.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageOperator.java
+index 1e546634e90e7..e852569490f0b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageOperator.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageOperator.java
+@@ -16,28 +16,29 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import android.graphics.PointF;
++
+ import org.tensorflow.lite.support.common.Operator;
+ 
+ /** Operates a TensorImage object. Used in ImageProcessor. */
+ public interface ImageOperator extends Operator<TensorImage> {
+-  /** @see org.tensorflow.lite.support.common.Operator#apply(java.lang.Object) */
+-  @Override
+-  TensorImage apply(TensorImage image);
+-
+-  /** Computes the width of the expected output image when input image size is given. */
+-  int getOutputImageWidth(int inputImageHeight, int inputImageWidth);
+-
+-  /** Computes the height of the expected output image when input image size is given. */
+-  int getOutputImageHeight(int inputImageHeight, int inputImageWidth);
+-
+-  /**
+-   * Transforms a point from coordinates system of the result image back to the one of the input
+-   * image.
+-   *
+-   * @param point the point from the result coordinates system.
+-   * @param inputImageHeight the height of input image.
+-   * @param inputImageWidth the width of input image.
+-   * @return the point with the coordinates from the coordinates system of the input image.
+-   */
+-  PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth);
++    /** @see org.tensorflow.lite.support.common.Operator#apply(java.lang.Object) */
++    @Override
++    TensorImage apply(TensorImage image);
++
++    /** Computes the width of the expected output image when input image size is given. */
++    int getOutputImageWidth(int inputImageHeight, int inputImageWidth);
++
++    /** Computes the height of the expected output image when input image size is given. */
++    int getOutputImageHeight(int inputImageHeight, int inputImageWidth);
++
++    /**
++     * Transforms a point from coordinates system of the result image back to the one of the input
++     * image.
++     *
++     * @param point the point from the result coordinates system.
++     * @param inputImageHeight the height of input image.
++     * @param inputImageWidth the width of input image.
++     * @return the point with the coordinates from the coordinates system of the input image.
++     */
++    PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java
+index ffee8f2c2a706..d7a853ee86de6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java
+@@ -20,9 +20,7 @@ import static java.lang.Math.min;
+ 
+ import android.graphics.PointF;
+ import android.graphics.RectF;
+-import java.util.ArrayList;
+-import java.util.List;
+-import java.util.ListIterator;
++
+ import org.tensorflow.lite.support.common.Operator;
+ import org.tensorflow.lite.support.common.SequentialProcessor;
+ import org.tensorflow.lite.support.common.TensorOperator;
+@@ -30,6 +28,10 @@ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ import org.tensorflow.lite.support.image.ops.Rot90Op;
+ import org.tensorflow.lite.support.image.ops.TensorOperatorWrapper;
+ 
++import java.util.ArrayList;
++import java.util.List;
++import java.util.ListIterator;
++
+ /**
+  * ImageProcessor is a helper class for preprocessing and postprocessing {@link TensorImage}. It
+  * could transform a {@link TensorImage} to another by executing a chain of {@link ImageOperator}.
+@@ -55,156 +57,159 @@ import org.tensorflow.lite.support.image.ops.TensorOperatorWrapper;
+  * @see ImageProcessor#process(TensorImage) to apply the processor on a {@link TensorImage}
+  */
+ public class ImageProcessor extends SequentialProcessor<TensorImage> {
+-  private ImageProcessor(Builder builder) {
+-    super(builder);
+-  }
+-
+-  /**
+-   * Transforms a point from coordinates system of the result image back to the one of the input
+-   * image.
+-   *
+-   * @param point the point from the result coordinates system.
+-   * @param inputImageHeight the height of input image.
+-   * @param inputImageWidth the width of input image.
+-   * @return the point with the coordinates from the coordinates system of the input image.
+-   */
+-  public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+-    List<Integer> widths = new ArrayList<>();
+-    List<Integer> heights = new ArrayList<>();
+-    int currentWidth = inputImageWidth;
+-    int currentHeight = inputImageHeight;
+-    for (Operator<TensorImage> op : operatorList) {
+-      widths.add(currentWidth);
+-      heights.add(currentHeight);
+-      ImageOperator imageOperator = (ImageOperator) op;
+-      int newHeight = imageOperator.getOutputImageHeight(currentHeight, currentWidth);
+-      int newWidth = imageOperator.getOutputImageWidth(currentHeight, currentWidth);
+-      currentHeight = newHeight;
+-      currentWidth = newWidth;
++    private ImageProcessor(Builder builder) {
++        super(builder);
+     }
+-    ListIterator<Operator<TensorImage>> opIterator = operatorList.listIterator(operatorList.size());
+-    ListIterator<Integer> widthIterator = widths.listIterator(widths.size());
+-    ListIterator<Integer> heightIterator = heights.listIterator(heights.size());
+-    while (opIterator.hasPrevious()) {
+-      ImageOperator imageOperator = (ImageOperator) opIterator.previous();
+-      int height = heightIterator.previous();
+-      int width = widthIterator.previous();
+-      point = imageOperator.inverseTransform(point, height, width);
++
++    /**
++     * Transforms a point from coordinates system of the result image back to the one of the input
++     * image.
++     *
++     * @param point the point from the result coordinates system.
++     * @param inputImageHeight the height of input image.
++     * @param inputImageWidth the width of input image.
++     * @return the point with the coordinates from the coordinates system of the input image.
++     */
++    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
++        List<Integer> widths = new ArrayList<>();
++        List<Integer> heights = new ArrayList<>();
++        int currentWidth = inputImageWidth;
++        int currentHeight = inputImageHeight;
++        for (Operator<TensorImage> op : operatorList) {
++            widths.add(currentWidth);
++            heights.add(currentHeight);
++            ImageOperator imageOperator = (ImageOperator) op;
++            int newHeight = imageOperator.getOutputImageHeight(currentHeight, currentWidth);
++            int newWidth = imageOperator.getOutputImageWidth(currentHeight, currentWidth);
++            currentHeight = newHeight;
++            currentWidth = newWidth;
++        }
++        ListIterator<Operator<TensorImage>> opIterator =
++                operatorList.listIterator(operatorList.size());
++        ListIterator<Integer> widthIterator = widths.listIterator(widths.size());
++        ListIterator<Integer> heightIterator = heights.listIterator(heights.size());
++        while (opIterator.hasPrevious()) {
++            ImageOperator imageOperator = (ImageOperator) opIterator.previous();
++            int height = heightIterator.previous();
++            int width = widthIterator.previous();
++            point = imageOperator.inverseTransform(point, height, width);
++        }
++        return point;
++    }
++
++    /**
++     * Transforms a rectangle from coordinates system of the result image back to the one of the
++     * input image.
++     *
++     * @param rect the rectangle from the result coordinates system.
++     * @param inputImageHeight the height of input image.
++     * @param inputImageWidth the width of input image.
++     * @return the rectangle with the coordinates from the coordinates system of the input image.
++     */
++    public RectF inverseTransform(RectF rect, int inputImageHeight, int inputImageWidth) {
++        // when rotation is involved, corner order may change - top left changes to bottom right,
++        // .etc
++        PointF p1 = inverseTransform(
++                new PointF(rect.left, rect.top), inputImageHeight, inputImageWidth);
++        PointF p2 = inverseTransform(
++                new PointF(rect.right, rect.bottom), inputImageHeight, inputImageWidth);
++        return new RectF(min(p1.x, p2.x), min(p1.y, p2.y), max(p1.x, p2.x), max(p1.y, p2.y));
+     }
+-    return point;
+-  }
+-
+-  /**
+-   * Transforms a rectangle from coordinates system of the result image back to the one of the input
+-   * image.
+-   *
+-   * @param rect the rectangle from the result coordinates system.
+-   * @param inputImageHeight the height of input image.
+-   * @param inputImageWidth the width of input image.
+-   * @return the rectangle with the coordinates from the coordinates system of the input image.
+-   */
+-  public RectF inverseTransform(RectF rect, int inputImageHeight, int inputImageWidth) {
+-    // when rotation is involved, corner order may change - top left changes to bottom right, .etc
+-    PointF p1 =
+-        inverseTransform(new PointF(rect.left, rect.top), inputImageHeight, inputImageWidth);
+-    PointF p2 =
+-        inverseTransform(new PointF(rect.right, rect.bottom), inputImageHeight, inputImageWidth);
+-    return new RectF(min(p1.x, p2.x), min(p1.y, p2.y), max(p1.x, p2.x), max(p1.y, p2.y));
+-  }
+-
+-  /**
+-   * Processes a {@link TensorImage} object with prepared {@link TensorOperator}.
+-   *
+-   * @throws IllegalArgumentException if the image is not supported by any op.
+-   */
+-  @Override
+-  public TensorImage process(TensorImage image) {
+-    return super.process(image);
+-  }
+-
+-  /**
+-   * The Builder to create an ImageProcessor, which could be executed later.
+-   *
+-   * @see #add(TensorOperator) to add a general TensorOperator
+-   * @see #add(ImageOperator) to add an ImageOperator
+-   * @see #build() complete the building process and get a built Processor
+-   */
+-  public static class Builder extends SequentialProcessor.Builder<TensorImage> {
+-    public Builder() {
+-      super();
++
++    /**
++     * Processes a {@link TensorImage} object with prepared {@link TensorOperator}.
++     *
++     * @throws IllegalArgumentException if the image is not supported by any op.
++     */
++    @Override
++    public TensorImage process(TensorImage image) {
++        return super.process(image);
+     }
+ 
+     /**
+-     * Adds an {@link ImageOperator} into the Operator chain.
++     * The Builder to create an ImageProcessor, which could be executed later.
+      *
+-     * @param op the Operator instance to be executed then
++     * @see #add(TensorOperator) to add a general TensorOperator
++     * @see #add(ImageOperator) to add an ImageOperator
++     * @see #build() complete the building process and get a built Processor
+      */
+-    public Builder add(ImageOperator op) {
+-      super.add(op);
+-      return this;
++    public static class Builder extends SequentialProcessor.Builder<TensorImage> {
++        public Builder() {
++            super();
++        }
++
++        /**
++         * Adds an {@link ImageOperator} into the Operator chain.
++         *
++         * @param op the Operator instance to be executed then
++         */
++        public Builder add(ImageOperator op) {
++            super.add(op);
++            return this;
++        }
++
++        /**
++         * Adds a {@link TensorOperator} into the Operator chain. In execution, the processor calls
++         * {@link TensorImage#getTensorBuffer()} to transform the {@link TensorImage} by
++         * transforming the underlying {@link
++         * org.tensorflow.lite.support.tensorbuffer.TensorBuffer}.
++         *
++         * @param op the Operator instance to be executed then
++         */
++        public Builder add(TensorOperator op) {
++            return add(new TensorOperatorWrapper(op));
++        }
++
++        /** Completes the building process and gets the {@link ImageProcessor} instance. */
++        @Override
++        public ImageProcessor build() {
++            return new ImageProcessor(this);
++        }
+     }
+ 
+     /**
+-     * Adds a {@link TensorOperator} into the Operator chain. In execution, the processor calls
+-     * {@link TensorImage#getTensorBuffer()} to transform the {@link TensorImage} by transforming
+-     * the underlying {@link org.tensorflow.lite.support.tensorbuffer.TensorBuffer}.
++     * Updates the number of rotations for the first {@link Rot90Op} in this {@link ImageProcessor}.
++     *
++     * <p><b>WARNING:</b>this method is <b>not</b> thread-safe. Updating the number of rotations and
++     * then processing images (using {@link #process}) must be protected from concurrent access with
++     * additional synchronization.
+      *
+-     * @param op the Operator instance to be executed then
++     * @param k the number of rotations
++     * @throws IllegalStateException if {@link Rot90Op} has not been added to this {@link
++     *     ImageProcessor}
+      */
+-    public Builder add(TensorOperator op) {
+-      return add(new TensorOperatorWrapper(op));
++    public void updateNumberOfRotations(int k) {
++        updateNumberOfRotations(k, /*occurrence=*/0);
+     }
+ 
+-    /** Completes the building process and gets the {@link ImageProcessor} instance. */
+-    @Override
+-    public ImageProcessor build() {
+-      return new ImageProcessor(this);
++    /**
++     * Updates the number of rotations for the {@link Rot90Op} specified by {@code occurrence} in
++     * this
++     * {@link ImageProcessor}.
++     *
++     * <p><b>WARNING:</b>this method is <b>not</b> thread-safe. Updating the number of rotations and
++     * then processing images (using {@link #process}) must be protected from concurrent access with
++     * additional synchronization.
++     *
++     * @param k the number of rotations
++     * @param occurrence the index of perticular {@link Rot90Op} in this {@link ImageProcessor}. For
++     *     example, if the second {@link Rot90Op} needs to be updated, {@code occurrence} should be
++     *     set to 1.
++     * @throws IndexOutOfBoundsException if {@code occurrence} is negative or is not less than the
++     *     number of {@link Rot90Op} in this {@link ImageProcessor}
++     * @throws IllegalStateException if {@link Rot90Op} has not been added to this {@link
++     *     ImageProcessor}
++     */
++    public synchronized void updateNumberOfRotations(int k, int occurrence) {
++        SupportPreconditions.checkState(operatorIndex.containsKey(Rot90Op.class.getName()),
++                "The Rot90Op has not been added to the ImageProcessor.");
++
++        List<Integer> indexes = operatorIndex.get(Rot90Op.class.getName());
++        SupportPreconditions.checkElementIndex(occurrence, indexes.size(), "occurrence");
++
++        // The index of the Rot90Op to be replaced in operatorList.
++        int index = indexes.get(occurrence);
++        Rot90Op newRot = new Rot90Op(k);
++        operatorList.set(index, newRot);
+     }
+-  }
+-
+-  /**
+-   * Updates the number of rotations for the first {@link Rot90Op} in this {@link ImageProcessor}.
+-   *
+-   * <p><b>WARNING:</b>this method is <b>not</b> thread-safe. Updating the number of rotations and
+-   * then processing images (using {@link #process}) must be protected from concurrent access with
+-   * additional synchronization.
+-   *
+-   * @param k the number of rotations
+-   * @throws IllegalStateException if {@link Rot90Op} has not been added to this {@link
+-   *     ImageProcessor}
+-   */
+-  public void updateNumberOfRotations(int k) {
+-    updateNumberOfRotations(k, /*occurrence=*/ 0);
+-  }
+-
+-  /**
+-   * Updates the number of rotations for the {@link Rot90Op} specified by {@code occurrence} in this
+-   * {@link ImageProcessor}.
+-   *
+-   * <p><b>WARNING:</b>this method is <b>not</b> thread-safe. Updating the number of rotations and
+-   * then processing images (using {@link #process}) must be protected from concurrent access with
+-   * additional synchronization.
+-   *
+-   * @param k the number of rotations
+-   * @param occurrence the index of perticular {@link Rot90Op} in this {@link ImageProcessor}. For
+-   *     example, if the second {@link Rot90Op} needs to be updated, {@code occurrence} should be
+-   *     set to 1.
+-   * @throws IndexOutOfBoundsException if {@code occurrence} is negative or is not less than the
+-   *     number of {@link Rot90Op} in this {@link ImageProcessor}
+-   * @throws IllegalStateException if {@link Rot90Op} has not been added to this {@link
+-   *     ImageProcessor}
+-   */
+-  public synchronized void updateNumberOfRotations(int k, int occurrence) {
+-    SupportPreconditions.checkState(
+-        operatorIndex.containsKey(Rot90Op.class.getName()),
+-        "The Rot90Op has not been added to the ImageProcessor.");
+-
+-    List<Integer> indexes = operatorIndex.get(Rot90Op.class.getName());
+-    SupportPreconditions.checkElementIndex(occurrence, indexes.size(), "occurrence");
+-
+-    // The index of the Rot90Op to be replaced in operatorList.
+-    int index = indexes.get(occurrence);
+-    Rot90Op newRot = new Rot90Op(k);
+-    operatorList.set(index, newRot);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java
+index 96daf85a02f5a..f61f59fa13ce7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java
+@@ -26,52 +26,51 @@ import com.google.auto.value.AutoValue;
+  */
+ @AutoValue
+ public abstract class ImageProperties {
++    private static final int DEFAULT_HEIGHT = -1;
++    private static final int DEFAULT_WIDTH = -1;
+ 
+-  private static final int DEFAULT_HEIGHT = -1;
+-  private static final int DEFAULT_WIDTH = -1;
+-
+-  public abstract int getHeight();
+-
+-  public abstract int getWidth();
+-
+-  public abstract ColorSpaceType getColorSpaceType();
+-
+-  public static Builder builder() {
+-    return new AutoValue_ImageProperties.Builder()
+-        .setHeight(DEFAULT_HEIGHT)
+-        .setWidth(DEFAULT_WIDTH);
+-  }
+-
+-  /**
+-   * Builder for {@link ImageProperties}. Different image objects may require different properties.
+-   * See the detais below:
+-   *
+-   * <ul>
+-   *   {@link org.tensorflow.lite.support.tensorbuffer.TensorBuffer}:
+-   *   <li>Mandatory proterties: height / width / colorSpaceType. The shape of the TensorBuffer
+-   *       object will not be used to determine image height and width.
+-   * </ul>
+-   */
+-  @AutoValue.Builder
+-  public abstract static class Builder {
+-    public abstract Builder setHeight(int height);
+-
+-    public abstract Builder setWidth(int width);
+-
+-    public abstract Builder setColorSpaceType(ColorSpaceType colorSpaceType);
+-
+-    abstract ImageProperties autoBuild();
+-
+-    public ImageProperties build() {
+-      ImageProperties properties = autoBuild();
+-      // If width or hight are not configured by the Builder, they will be -1.
+-      // Enforcing all properties to be populated (AutoValue will error out if objects, like
+-      // colorSpaceType, are not set up), since they are required for TensorBuffer images.
+-      // If in the future we have some image object types that only require a portion of these
+-      // properties, we can delay the check when TensorImage#load() is executed.
+-      checkState(properties.getHeight() >= 0, "Negative image height is not allowed.");
+-      checkState(properties.getWidth() >= 0, "Negative image width is not allowed.");
+-      return properties;
++    public abstract int getHeight();
++
++    public abstract int getWidth();
++
++    public abstract ColorSpaceType getColorSpaceType();
++
++    public static Builder builder() {
++        return new AutoValue_ImageProperties.Builder()
++                .setHeight(DEFAULT_HEIGHT)
++                .setWidth(DEFAULT_WIDTH);
++    }
++
++    /**
++     * Builder for {@link ImageProperties}. Different image objects may require different
++     * properties. See the detais below:
++     *
++     * <ul>
++     *   {@link org.tensorflow.lite.support.tensorbuffer.TensorBuffer}:
++     *   <li>Mandatory proterties: height / width / colorSpaceType. The shape of the TensorBuffer
++     *       object will not be used to determine image height and width.
++     * </ul>
++     */
++    @AutoValue.Builder
++    public abstract static class Builder {
++        public abstract Builder setHeight(int height);
++
++        public abstract Builder setWidth(int width);
++
++        public abstract Builder setColorSpaceType(ColorSpaceType colorSpaceType);
++
++        abstract ImageProperties autoBuild();
++
++        public ImageProperties build() {
++            ImageProperties properties = autoBuild();
++            // If width or hight are not configured by the Builder, they will be -1.
++            // Enforcing all properties to be populated (AutoValue will error out if objects, like
++            // colorSpaceType, are not set up), since they are required for TensorBuffer images.
++            // If in the future we have some image object types that only require a portion of these
++            // properties, we can delay the check when TensorImage#load() is executed.
++            checkState(properties.getHeight() >= 0, "Negative image height is not allowed.");
++            checkState(properties.getWidth() >= 0, "Negative image width is not allowed.");
++            return properties;
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java
+index 50d787b5afab1..519aacaf7f20b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java
+@@ -21,65 +21,65 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import android.graphics.Bitmap;
+ import android.graphics.ImageFormat;
+ import android.media.Image;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /** Holds an {@link Image} and converts it to other image formats as needed. */
+ final class MediaImageContainer implements ImageContainer {
+-
+-  private final Image image;
+-
+-  /**
+-   * Creates a {@link MediaImageContainer} object with a YUV_420_888 {@link Image}.
+-   *
+-   * @throws IllegalArgumentException if the {@link ImageFormat} of {@code image} is not ARGB_8888
+-   */
+-  static MediaImageContainer create(Image image) {
+-    return new MediaImageContainer(image);
+-  }
+-
+-  private MediaImageContainer(Image image) {
+-    checkNotNull(image, "Cannot load null Image.");
+-    checkArgument(
+-        image.getFormat() == ImageFormat.YUV_420_888, "Only supports loading YUV_420_888 Image.");
+-    this.image = image;
+-  }
+-
+-  @Override
+-  public MediaImageContainer clone() {
+-    throw new UnsupportedOperationException(
+-        "android.media.Image is an abstract class and cannot be cloned.");
+-  }
+-
+-  @Override
+-  public Bitmap getBitmap() {
+-    throw new UnsupportedOperationException(
+-        "Converting an android.media.Image to Bitmap is not supported.");
+-  }
+-
+-  @Override
+-  public TensorBuffer getTensorBuffer(DataType dataType) {
+-    throw new UnsupportedOperationException(
+-        "Converting an android.media.Image to TesorBuffer is not supported.");
+-  }
+-
+-  @Override
+-  public Image getMediaImage() {
+-    return image;
+-  }
+-
+-  @Override
+-  public int getWidth() {
+-    return image.getWidth();
+-  }
+-
+-  @Override
+-  public int getHeight() {
+-    return image.getHeight();
+-  }
+-
+-  @Override
+-  public ColorSpaceType getColorSpaceType() {
+-    return ColorSpaceType.fromImageFormat(image.getFormat());
+-  }
++    private final Image image;
++
++    /**
++     * Creates a {@link MediaImageContainer} object with a YUV_420_888 {@link Image}.
++     *
++     * @throws IllegalArgumentException if the {@link ImageFormat} of {@code image} is not ARGB_8888
++     */
++    static MediaImageContainer create(Image image) {
++        return new MediaImageContainer(image);
++    }
++
++    private MediaImageContainer(Image image) {
++        checkNotNull(image, "Cannot load null Image.");
++        checkArgument(image.getFormat() == ImageFormat.YUV_420_888,
++                "Only supports loading YUV_420_888 Image.");
++        this.image = image;
++    }
++
++    @Override
++    public MediaImageContainer clone() {
++        throw new UnsupportedOperationException(
++                "android.media.Image is an abstract class and cannot be cloned.");
++    }
++
++    @Override
++    public Bitmap getBitmap() {
++        throw new UnsupportedOperationException(
++                "Converting an android.media.Image to Bitmap is not supported.");
++    }
++
++    @Override
++    public TensorBuffer getTensorBuffer(DataType dataType) {
++        throw new UnsupportedOperationException(
++                "Converting an android.media.Image to TesorBuffer is not supported.");
++    }
++
++    @Override
++    public Image getMediaImage() {
++        return image;
++    }
++
++    @Override
++    public int getWidth() {
++        return image.getWidth();
++    }
++
++    @Override
++    public int getHeight() {
++        return image.getHeight();
++    }
++
++    @Override
++    public ColorSpaceType getColorSpaceType() {
++        return ColorSpaceType.fromImageFormat(image.getFormat());
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java
+index ed066e5308fb9..03017bf733f02 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java
+@@ -21,91 +21,99 @@ import com.google.android.odml.image.MediaImageExtractor;
+ import com.google.android.odml.image.MlImage;
+ import com.google.android.odml.image.MlImage.ImageFormat;
+ import com.google.auto.value.AutoValue;
++
+ import java.nio.ByteBuffer;
+ 
+ /** Converts {@code MlImage} to {@link TensorImage} and vice versa. */
+ public class MlImageAdapter {
++    /** Proxies an {@link ImageFormat} and its equivalent {@link ColorSpaceType}. */
++    @AutoValue
++    abstract static class ImageFormatProxy {
++        abstract ColorSpaceType getColorSpaceType();
+ 
+-  /** Proxies an {@link ImageFormat} and its equivalent {@link ColorSpaceType}. */
+-  @AutoValue
+-  abstract static class ImageFormatProxy {
+-
+-    abstract ColorSpaceType getColorSpaceType();
++        @ImageFormat
++        abstract int getImageFormat();
+ 
+-    @ImageFormat
+-    abstract int getImageFormat();
+-
+-    static ImageFormatProxy createFromImageFormat(@ImageFormat int format) {
+-      switch (format) {
+-        case MlImage.IMAGE_FORMAT_RGB:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.RGB, format);
+-        case MlImage.IMAGE_FORMAT_NV12:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.NV12, format);
+-        case MlImage.IMAGE_FORMAT_NV21:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.NV21, format);
+-        case MlImage.IMAGE_FORMAT_YV12:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.YV12, format);
+-        case MlImage.IMAGE_FORMAT_YV21:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.YV21, format);
+-        case MlImage.IMAGE_FORMAT_YUV_420_888:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.YUV_420_888, format);
+-        case MlImage.IMAGE_FORMAT_ALPHA:
+-          return new AutoValue_MlImageAdapter_ImageFormatProxy(ColorSpaceType.GRAYSCALE, format);
+-        case MlImage.IMAGE_FORMAT_RGBA:
+-        case MlImage.IMAGE_FORMAT_JPEG:
+-        case MlImage.IMAGE_FORMAT_UNKNOWN:
+-          throw new IllegalArgumentException(
+-              "Cannot create ColorSpaceType from MlImage format: " + format);
+-        default:
+-          throw new AssertionError("Illegal @ImageFormat: " + format);
+-      }
++        static ImageFormatProxy createFromImageFormat(@ImageFormat int format) {
++            switch (format) {
++                case MlImage.IMAGE_FORMAT_RGB:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.RGB, format);
++                case MlImage.IMAGE_FORMAT_NV12:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.NV12, format);
++                case MlImage.IMAGE_FORMAT_NV21:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.NV21, format);
++                case MlImage.IMAGE_FORMAT_YV12:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.YV12, format);
++                case MlImage.IMAGE_FORMAT_YV21:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.YV21, format);
++                case MlImage.IMAGE_FORMAT_YUV_420_888:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.YUV_420_888, format);
++                case MlImage.IMAGE_FORMAT_ALPHA:
++                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
++                            ColorSpaceType.GRAYSCALE, format);
++                case MlImage.IMAGE_FORMAT_RGBA:
++                case MlImage.IMAGE_FORMAT_JPEG:
++                case MlImage.IMAGE_FORMAT_UNKNOWN:
++                    throw new IllegalArgumentException(
++                            "Cannot create ColorSpaceType from MlImage format: " + format);
++                default:
++                    throw new AssertionError("Illegal @ImageFormat: " + format);
++            }
++        }
+     }
+-  }
+ 
+-  /**
+-   * Creates a {@link TensorImage} from an {@link MlImage}.
+-   *
+-   * <p>IMPORTANT: The returned {@link TensorImage} shares storage with {@code mlImage}, so do not
+-   * modify the contained object in the {@link TensorImage}, as {@code MlImage} expects its
+-   * contained data are immutable. Also, callers should use {@code MlImage#getInternal()#acquire()}
+-   * and {@code MlImage#release()} to avoid the {@code mlImage} being released unexpectedly.
+-   *
+-   * @throws IllegalArgumentException if the {@code mlImage} is built from an unsupported container.
+-   */
+-  public static TensorImage createTensorImageFrom(MlImage mlImage) {
+-    // TODO(b/190670174): Choose the best storage from multiple containers.
+-    com.google.android.odml.image.ImageProperties mlImageProperties =
+-        mlImage.getContainedImageProperties().get(0);
+-    switch (mlImageProperties.getStorageType()) {
+-      case MlImage.STORAGE_TYPE_BITMAP:
+-        return TensorImage.fromBitmap(BitmapExtractor.extract(mlImage));
+-      case MlImage.STORAGE_TYPE_MEDIA_IMAGE:
+-        TensorImage mediaTensorImage = new TensorImage();
+-        mediaTensorImage.load(MediaImageExtractor.extract(mlImage));
+-        return mediaTensorImage;
+-      case MlImage.STORAGE_TYPE_BYTEBUFFER:
+-        ByteBuffer buffer = ByteBufferExtractor.extract(mlImage);
+-        ImageFormatProxy formatProxy =
+-            ImageFormatProxy.createFromImageFormat(mlImageProperties.getImageFormat());
+-        TensorImage byteBufferTensorImage = new TensorImage();
+-        ImageProperties properties =
+-            ImageProperties.builder()
+-                .setColorSpaceType(formatProxy.getColorSpaceType())
+-                .setHeight(mlImage.getHeight())
+-                .setWidth(mlImage.getWidth())
+-                .build();
+-        byteBufferTensorImage.load(buffer, properties);
+-        return byteBufferTensorImage;
+-      default:
+-        throw new IllegalArgumentException(
+-            "Illegal storage type: " + mlImageProperties.getStorageType());
++    /**
++     * Creates a {@link TensorImage} from an {@link MlImage}.
++     *
++     * <p>IMPORTANT: The returned {@link TensorImage} shares storage with {@code mlImage}, so do not
++     * modify the contained object in the {@link TensorImage}, as {@code MlImage} expects its
++     * contained data are immutable. Also, callers should use {@code
++     * MlImage#getInternal()#acquire()} and {@code MlImage#release()} to avoid the {@code mlImage}
++     * being released unexpectedly.
++     *
++     * @throws IllegalArgumentException if the {@code mlImage} is built from an unsupported
++     *         container.
++     */
++    public static TensorImage createTensorImageFrom(MlImage mlImage) {
++        // TODO(b/190670174): Choose the best storage from multiple containers.
++        com.google.android.odml.image.ImageProperties mlImageProperties =
++                mlImage.getContainedImageProperties().get(0);
++        switch (mlImageProperties.getStorageType()) {
++            case MlImage.STORAGE_TYPE_BITMAP:
++                return TensorImage.fromBitmap(BitmapExtractor.extract(mlImage));
++            case MlImage.STORAGE_TYPE_MEDIA_IMAGE:
++                TensorImage mediaTensorImage = new TensorImage();
++                mediaTensorImage.load(MediaImageExtractor.extract(mlImage));
++                return mediaTensorImage;
++            case MlImage.STORAGE_TYPE_BYTEBUFFER:
++                ByteBuffer buffer = ByteBufferExtractor.extract(mlImage);
++                ImageFormatProxy formatProxy =
++                        ImageFormatProxy.createFromImageFormat(mlImageProperties.getImageFormat());
++                TensorImage byteBufferTensorImage = new TensorImage();
++                ImageProperties properties =
++                        ImageProperties.builder()
++                                .setColorSpaceType(formatProxy.getColorSpaceType())
++                                .setHeight(mlImage.getHeight())
++                                .setWidth(mlImage.getWidth())
++                                .build();
++                byteBufferTensorImage.load(buffer, properties);
++                return byteBufferTensorImage;
++            default:
++                throw new IllegalArgumentException(
++                        "Illegal storage type: " + mlImageProperties.getStorageType());
++        }
+     }
+-  }
+ 
+-  /** Creatas a {@link ColorSpaceType} from {@code MlImage.ImageFormat}. */
+-  public static ColorSpaceType createColorSpaceTypeFrom(@ImageFormat int imageFormat) {
+-    return ImageFormatProxy.createFromImageFormat(imageFormat).getColorSpaceType();
+-  }
++    /** Creatas a {@link ColorSpaceType} from {@code MlImage.ImageFormat}. */
++    public static ColorSpaceType createColorSpaceTypeFrom(@ImageFormat int imageFormat) {
++        return ImageFormatProxy.createFromImageFormat(imageFormat).getColorSpaceType();
++    }
+ 
+-  private MlImageAdapter() {}
++    private MlImageAdapter() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java
+index 39e2ceb9db521..6dfef70ba67f7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java
+@@ -20,118 +20,108 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import android.graphics.Bitmap;
+ import android.media.Image;
+ import android.util.Log;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /** Holds a {@link TensorBuffer} and converts it to other image formats as needed. */
+ final class TensorBufferContainer implements ImageContainer {
++    private final TensorBuffer buffer;
++    private final ColorSpaceType colorSpaceType;
++    private final int height;
++    private final int width;
++    private static final String TAG = TensorBufferContainer.class.getSimpleName();
++
++    /**
++     * Creates a {@link TensorBufferContainer} object with the specified {@link
++     * TensorImage#ColorSpaceType}.
++     *
++     * <p>Only supports {@link ColorSapceType#RGB} and {@link ColorSpaceType#GRAYSCALE}. Use {@link
++     * #create(TensorBuffer, ImageProperties)} for other color space types.
++     *
++     * @throws IllegalArgumentException if the shape of the {@link TensorBuffer} does not match the
++     *     specified color space type, or if the color space type is not supported
++     */
++    static TensorBufferContainer create(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
++        checkArgument(
++                colorSpaceType == ColorSpaceType.RGB || colorSpaceType == ColorSpaceType.GRAYSCALE,
++                "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
++                        + " `create(TensorBuffer, ImageProperties)` for other color space types.");
++
++        return new TensorBufferContainer(buffer, colorSpaceType,
++                colorSpaceType.getHeight(buffer.getShape()),
++                colorSpaceType.getWidth(buffer.getShape()));
++    }
+ 
+-  private final TensorBuffer buffer;
+-  private final ColorSpaceType colorSpaceType;
+-  private final int height;
+-  private final int width;
+-  private static final String TAG = TensorBufferContainer.class.getSimpleName();
+-
+-  /**
+-   * Creates a {@link TensorBufferContainer} object with the specified {@link
+-   * TensorImage#ColorSpaceType}.
+-   *
+-   * <p>Only supports {@link ColorSapceType#RGB} and {@link ColorSpaceType#GRAYSCALE}. Use {@link
+-   * #create(TensorBuffer, ImageProperties)} for other color space types.
+-   *
+-   * @throws IllegalArgumentException if the shape of the {@link TensorBuffer} does not match the
+-   *     specified color space type, or if the color space type is not supported
+-   */
+-  static TensorBufferContainer create(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
+-    checkArgument(
+-        colorSpaceType == ColorSpaceType.RGB || colorSpaceType == ColorSpaceType.GRAYSCALE,
+-        "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
+-            + " `create(TensorBuffer, ImageProperties)` for other color space types.");
+-
+-    return new TensorBufferContainer(
+-        buffer,
+-        colorSpaceType,
+-        colorSpaceType.getHeight(buffer.getShape()),
+-        colorSpaceType.getWidth(buffer.getShape()));
+-  }
+-
+-  static TensorBufferContainer create(TensorBuffer buffer, ImageProperties imageProperties) {
+-    return new TensorBufferContainer(
+-        buffer,
+-        imageProperties.getColorSpaceType(),
+-        imageProperties.getHeight(),
+-        imageProperties.getWidth());
+-  }
+-
+-  private TensorBufferContainer(
+-      TensorBuffer buffer, ColorSpaceType colorSpaceType, int height, int width) {
+-    checkArgument(
+-        colorSpaceType != ColorSpaceType.YUV_420_888,
+-        "The actual encoding format of YUV420 is required. Choose a ColorSpaceType from: NV12,"
+-            + " NV21, YV12, YV21. Use YUV_420_888 only when loading an android.media.Image.");
+-
+-    colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
+-    this.buffer = buffer;
+-    this.colorSpaceType = colorSpaceType;
+-    this.height = height;
+-    this.width = width;
+-  }
+-
+-  @Override
+-  public TensorBufferContainer clone() {
+-    return new TensorBufferContainer(
+-        TensorBuffer.createFrom(buffer, buffer.getDataType()),
+-        colorSpaceType,
+-        getHeight(),
+-        getWidth());
+-  }
+-
+-  @Override
+-  public Bitmap getBitmap() {
+-    if (buffer.getDataType() != DataType.UINT8) {
+-      // Print warning instead of throwing an exception. When using float models, users may want to
+-      // convert the resulting float image into Bitmap. That's fine to do so, as long as they are
+-      // aware of the potential accuracy lost when casting to uint8.
+-      Log.w(
+-          TAG,
+-          "<Warning> TensorBufferContainer is holding a non-uint8 image. The conversion to Bitmap"
+-              + " will cause numeric casting and clamping on the data value.");
++    static TensorBufferContainer create(TensorBuffer buffer, ImageProperties imageProperties) {
++        return new TensorBufferContainer(buffer, imageProperties.getColorSpaceType(),
++                imageProperties.getHeight(), imageProperties.getWidth());
+     }
+ 
+-    return colorSpaceType.convertTensorBufferToBitmap(buffer);
+-  }
+-
+-  @Override
+-  public TensorBuffer getTensorBuffer(DataType dataType) {
+-    // If the data type of buffer is desired, return it directly. Not making a defensive copy for
+-    // performance considerations. During image processing, users may need to set and get the
+-    // TensorBuffer many times.
+-    // Otherwise, create another one with the expected data type.
+-    return buffer.getDataType() == dataType ? buffer : TensorBuffer.createFrom(buffer, dataType);
+-  }
+-
+-  @Override
+-  public Image getMediaImage() {
+-    throw new UnsupportedOperationException(
+-        "Converting from TensorBuffer to android.media.Image is unsupported.");
+-  }
+-
+-  @Override
+-  public int getWidth() {
+-    // In case the underlying buffer in Tensorbuffer gets updated after TensorImage is created.
+-    colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
+-    return width;
+-  }
+-
+-  @Override
+-  public int getHeight() {
+-    // In case the underlying buffer in Tensorbuffer gets updated after TensorImage is created.
+-    colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
+-    return height;
+-  }
+-
+-  @Override
+-  public ColorSpaceType getColorSpaceType() {
+-    return colorSpaceType;
+-  }
++    private TensorBufferContainer(
++            TensorBuffer buffer, ColorSpaceType colorSpaceType, int height, int width) {
++        checkArgument(colorSpaceType != ColorSpaceType.YUV_420_888,
++                "The actual encoding format of YUV420 is required. Choose a ColorSpaceType from: NV12,"
++                        + " NV21, YV12, YV21. Use YUV_420_888 only when loading an android.media.Image.");
++
++        colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
++        this.buffer = buffer;
++        this.colorSpaceType = colorSpaceType;
++        this.height = height;
++        this.width = width;
++    }
++
++    @Override
++    public TensorBufferContainer clone() {
++        return new TensorBufferContainer(TensorBuffer.createFrom(buffer, buffer.getDataType()),
++                colorSpaceType, getHeight(), getWidth());
++    }
++
++    @Override
++    public Bitmap getBitmap() {
++        if (buffer.getDataType() != DataType.UINT8) {
++            // Print warning instead of throwing an exception. When using float models, users may
++            // want to convert the resulting float image into Bitmap. That's fine to do so, as long
++            // as they are aware of the potential accuracy lost when casting to uint8.
++            Log.w(TAG,
++                    "<Warning> TensorBufferContainer is holding a non-uint8 image. The conversion to Bitmap"
++                            + " will cause numeric casting and clamping on the data value.");
++        }
++
++        return colorSpaceType.convertTensorBufferToBitmap(buffer);
++    }
++
++    @Override
++    public TensorBuffer getTensorBuffer(DataType dataType) {
++        // If the data type of buffer is desired, return it directly. Not making a defensive copy
++        // for performance considerations. During image processing, users may need to set and get
++        // the TensorBuffer many times. Otherwise, create another one with the expected data type.
++        return buffer.getDataType() == dataType ? buffer
++                                                : TensorBuffer.createFrom(buffer, dataType);
++    }
++
++    @Override
++    public Image getMediaImage() {
++        throw new UnsupportedOperationException(
++                "Converting from TensorBuffer to android.media.Image is unsupported.");
++    }
++
++    @Override
++    public int getWidth() {
++        // In case the underlying buffer in Tensorbuffer gets updated after TensorImage is created.
++        colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
++        return width;
++    }
++
++    @Override
++    public int getHeight() {
++        // In case the underlying buffer in Tensorbuffer gets updated after TensorImage is created.
++        colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
++        return height;
++    }
++
++    @Override
++    public ColorSpaceType getColorSpaceType() {
++        return colorSpaceType;
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java
+index fbb73020e93d9..a5a12520856b5 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java
+@@ -19,10 +19,12 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ 
+ import android.graphics.Bitmap;
+ import android.media.Image;
+-import java.nio.ByteBuffer;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.nio.ByteBuffer;
++
+ /**
+  * TensorImage is the wrapper class for Image object. When using image processing utils in
+  * TFLite.support library, it's common to convert image objects in variant types to TensorImage at
+@@ -49,350 +51,357 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ // TODO(b/138907116): Support loading images from TensorBuffer with properties.
+ // TODO(b/138905544): Support directly loading RGBBytes, YUVBytes and other types if necessary.
+ public class TensorImage {
++    private final DataType dataType;
++    private ImageContainer container = null;
++
++    /**
++     * Initializes a {@link TensorImage} object.
++     *
++     * <p>Note: the data type of this {@link TensorImage} is {@link DataType#UINT8}. Use {@link
++     * #TensorImage(DataType)} if other data types are preferred.
++     */
++    public TensorImage() {
++        this(DataType.UINT8);
++    }
++
++    /**
++     * Initializes a {@link TensorImage} object with the specified data type.
++     *
++     * <p>When getting a {@link TensorBuffer} or a {@link ByteBuffer} from this {@link TensorImage},
++     * such as using {@link #getTensorBuffer} and {@link #getBuffer}, the data values will be
++     * converted to the specified data type.
++     *
++     * <p>Note: the shape of a {@link TensorImage} is not fixed. It can be adjusted to the shape of
++     * the image being loaded to this {@link TensorImage}.
++     *
++     * @param dataType the expected data type of the resulting {@link TensorBuffer}. The type is
++     *     always fixed during the lifetime of the {@link TensorImage}. To convert the data type,
++     * use
++     *     {@link #createFrom(TensorImage, DataType)} to create a copy and convert data type at the
++     *     same time.
++     * @throws IllegalArgumentException if {@code dataType} is neither {@link DataType#UINT8} nor
++     *     {@link DataType#FLOAT32}
++     */
++    public TensorImage(DataType dataType) {
++        checkArgument(dataType == DataType.UINT8 || dataType == DataType.FLOAT32,
++                "Illegal data type for TensorImage: Only FLOAT32 and UINT8 are accepted");
++        this.dataType = dataType;
++    }
++
++    /**
++     * Initializes a {@link TensorImage} object of {@link DataType#UINT8} with a {@link
++     * android.graphics.Bitmap} .
++     *
++     * @see #load(Bitmap) for reusing the object when it's expensive to create objects frequently,
++     *     because every call of {@code fromBitmap} creates a new {@link TensorImage}.
++     */
++    public static TensorImage fromBitmap(Bitmap bitmap) {
++        TensorImage image = new TensorImage();
++        image.load(bitmap);
++        return image;
++    }
++
++    /**
++     * Creates a deep-copy of a given {@link TensorImage} with the desired data type.
++     *
++     * @param src the {@link TensorImage} to copy from
++     * @param dataType the expected data type of newly created {@link TensorImage}
++     * @return a {@link TensorImage} whose data is copied from {@code src} and data type is {@code
++     *     dataType}
++     */
++    public static TensorImage createFrom(TensorImage src, DataType dataType) {
++        TensorImage dst = new TensorImage(dataType);
++        dst.container = src.container.clone();
++        return dst;
++    }
++
++    /**
++     * Loads a {@link android.graphics.Bitmap} image object into this {@link TensorImage}.
++     *
++     * <p>Note: if the {@link TensorImage} has data type other than {@link DataType#UINT8}, numeric
++     * casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}, where the {@link android.graphics.Bitmap} will be converted into a {@link
++     * TensorBuffer}.
++     *
++     * <p>Important: when loading a bitmap, DO NOT MODIFY the bitmap from the caller side anymore.
++     * The
++     * {@link TensorImage} object will rely on the bitmap. It will probably modify the bitmap as
++     * well. In this method, we perform a zero-copy approach for that bitmap, by simply holding its
++     * reference. Use {@code bitmap.copy(bitmap.getConfig(), true)} to create a copy if necessary.
++     *
++     * <p>Note: to get the best performance, please load images in the same shape to avoid memory
++     * re-allocation.
++     *
++     * @throws IllegalArgumentException if {@code bitmap} is not in ARGB_8888
++     */
++    public void load(Bitmap bitmap) {
++        container = BitmapContainer.create(bitmap);
++    }
++
++    /**
++     * Loads a float array as RGB pixels into this {@link TensorImage}, representing the pixels
++     * inside.
++     *
++     * <p>Note: if the {@link TensorImage} has a data type other than {@link DataType#FLOAT32},
++     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}.
++     *
++     * @param pixels the RGB pixels representing the image
++     * @param shape the shape of the image, should either in form (h, w, 3), or in form (1, h, w, 3)
++     * @throws IllegalArgumentException if the shape is neither (h, w, 3) nor (1, h, w, 3)
++     */
++    public void load(float[] pixels, int[] shape) {
++        TensorBuffer buffer = TensorBuffer.createDynamic(getDataType());
++        buffer.loadArray(pixels, shape);
++        load(buffer);
++    }
+ 
+-  private final DataType dataType;
+-  private ImageContainer container = null;
+-
+-  /**
+-   * Initializes a {@link TensorImage} object.
+-   *
+-   * <p>Note: the data type of this {@link TensorImage} is {@link DataType#UINT8}. Use {@link
+-   * #TensorImage(DataType)} if other data types are preferred.
+-   */
+-  public TensorImage() {
+-    this(DataType.UINT8);
+-  }
+-
+-  /**
+-   * Initializes a {@link TensorImage} object with the specified data type.
+-   *
+-   * <p>When getting a {@link TensorBuffer} or a {@link ByteBuffer} from this {@link TensorImage},
+-   * such as using {@link #getTensorBuffer} and {@link #getBuffer}, the data values will be
+-   * converted to the specified data type.
+-   *
+-   * <p>Note: the shape of a {@link TensorImage} is not fixed. It can be adjusted to the shape of
+-   * the image being loaded to this {@link TensorImage}.
+-   *
+-   * @param dataType the expected data type of the resulting {@link TensorBuffer}. The type is
+-   *     always fixed during the lifetime of the {@link TensorImage}. To convert the data type, use
+-   *     {@link #createFrom(TensorImage, DataType)} to create a copy and convert data type at the
+-   *     same time.
+-   * @throws IllegalArgumentException if {@code dataType} is neither {@link DataType#UINT8} nor
+-   *     {@link DataType#FLOAT32}
+-   */
+-  public TensorImage(DataType dataType) {
+-    checkArgument(
+-        dataType == DataType.UINT8 || dataType == DataType.FLOAT32,
+-        "Illegal data type for TensorImage: Only FLOAT32 and UINT8 are accepted");
+-    this.dataType = dataType;
+-  }
+-
+-  /**
+-   * Initializes a {@link TensorImage} object of {@link DataType#UINT8} with a {@link
+-   * android.graphics.Bitmap} .
+-   *
+-   * @see #load(Bitmap) for reusing the object when it's expensive to create objects frequently,
+-   *     because every call of {@code fromBitmap} creates a new {@link TensorImage}.
+-   */
+-  public static TensorImage fromBitmap(Bitmap bitmap) {
+-    TensorImage image = new TensorImage();
+-    image.load(bitmap);
+-    return image;
+-  }
+-
+-  /**
+-   * Creates a deep-copy of a given {@link TensorImage} with the desired data type.
+-   *
+-   * @param src the {@link TensorImage} to copy from
+-   * @param dataType the expected data type of newly created {@link TensorImage}
+-   * @return a {@link TensorImage} whose data is copied from {@code src} and data type is {@code
+-   *     dataType}
+-   */
+-  public static TensorImage createFrom(TensorImage src, DataType dataType) {
+-    TensorImage dst = new TensorImage(dataType);
+-    dst.container = src.container.clone();
+-    return dst;
+-  }
+-
+-  /**
+-   * Loads a {@link android.graphics.Bitmap} image object into this {@link TensorImage}.
+-   *
+-   * <p>Note: if the {@link TensorImage} has data type other than {@link DataType#UINT8}, numeric
+-   * casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+-   * #getBuffer}, where the {@link android.graphics.Bitmap} will be converted into a {@link
+-   * TensorBuffer}.
+-   *
+-   * <p>Important: when loading a bitmap, DO NOT MODIFY the bitmap from the caller side anymore. The
+-   * {@link TensorImage} object will rely on the bitmap. It will probably modify the bitmap as well.
+-   * In this method, we perform a zero-copy approach for that bitmap, by simply holding its
+-   * reference. Use {@code bitmap.copy(bitmap.getConfig(), true)} to create a copy if necessary.
+-   *
+-   * <p>Note: to get the best performance, please load images in the same shape to avoid memory
+-   * re-allocation.
+-   *
+-   * @throws IllegalArgumentException if {@code bitmap} is not in ARGB_8888
+-   */
+-  public void load(Bitmap bitmap) {
+-    container = BitmapContainer.create(bitmap);
+-  }
+-
+-  /**
+-   * Loads a float array as RGB pixels into this {@link TensorImage}, representing the pixels
+-   * inside.
+-   *
+-   * <p>Note: if the {@link TensorImage} has a data type other than {@link DataType#FLOAT32},
+-   * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+-   * #getBuffer}.
+-   *
+-   * @param pixels the RGB pixels representing the image
+-   * @param shape the shape of the image, should either in form (h, w, 3), or in form (1, h, w, 3)
+-   * @throws IllegalArgumentException if the shape is neither (h, w, 3) nor (1, h, w, 3)
+-   */
+-  public void load(float[] pixels, int[] shape) {
+-    TensorBuffer buffer = TensorBuffer.createDynamic(getDataType());
+-    buffer.loadArray(pixels, shape);
+-    load(buffer);
+-  }
+-
+-  /**
+-   * Loads an int array as RGB pixels into this {@link TensorImage}, representing the pixels inside.
+-   *
+-   * <p>Note: numeric casting and clamping will be applied to convert the values into the data type
+-   * of this {@link TensorImage} when calling {@link #getTensorBuffer} and {@link #getBuffer}.
+-   *
+-   * @param pixels the RGB pixels representing the image
+-   * @param shape the shape of the image, should either in form (h, w, 3), or in form (1, h, w, 3)
+-   * @throws IllegalArgumentException if the shape is neither (h, w, 3) nor (1, h, w, 3)
+-   */
+-  public void load(int[] pixels, int[] shape) {
+-    TensorBuffer buffer = TensorBuffer.createDynamic(getDataType());
+-    buffer.loadArray(pixels, shape);
+-    load(buffer);
+-  }
+-
+-  /**
+-   * Loads a {@link TensorBuffer} containing pixel values. The color layout should be RGB.
+-   *
+-   * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
+-   * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+-   * #getBuffer}.
+-   *
+-   * @param buffer the {@link TensorBuffer} to be loaded. Its shape should be either (h, w, 3) or
+-   *     (1, h, w, 3)
+-   * @throws IllegalArgumentException if the shape is neither (h, w, 3) nor (1, h, w, 3)
+-   */
+-  public void load(TensorBuffer buffer) {
+-    load(buffer, ColorSpaceType.RGB);
+-  }
+-
+-  /**
+-   * Loads a {@link TensorBuffer} containing pixel values with the specific {@link ColorSpaceType}.
+-   *
+-   * <p>Only supports {@link ColorSpaceType#RGB} and {@link ColorSpaceType#GRAYSCALE}. Use {@link
+-   * #load(TensorBuffer, ImageProperties)} for other color space types.
+-   *
+-   * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
+-   * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+-   * #getBuffer}.
+-   *
+-   * @param buffer the {@link TensorBuffer} to be loaded. Its shape should be either (h, w, 3) or
+-   *     (1, h, w, 3) for RGB images, and either (h, w) or (1, h, w) for GRAYSCALE images
+-   * @throws IllegalArgumentException if the shape of buffer does not match the color space type, or
+-   *     if the color space type is not supported
+-   */
+-  public void load(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
+-    checkArgument(
+-        colorSpaceType == ColorSpaceType.RGB || colorSpaceType == ColorSpaceType.GRAYSCALE,
+-        "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
+-            + " `load(TensorBuffer, ImageProperties)` for other color space types.");
+-
+-    container = TensorBufferContainer.create(buffer, colorSpaceType);
+-  }
+-
+-  /**
+-   * Loads a {@link TensorBuffer} containing pixel values with the specific {@link ImageProperties}.
+-   *
+-   * <p>The shape of the {@link TensorBuffer} will not be used to determine image height and width.
+-   * Set image properties through {@link ImageProperties}.
+-   *
+-   * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
+-   * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+-   * #getBuffer}.
+-   *
+-   * @throws IllegalArgumentException if buffer size is less than the image size indicated by image
+-   *     height, width, and color space type in {@link ImageProperties}
+-   */
+-  public void load(TensorBuffer buffer, ImageProperties imageProperties) {
+-    container = TensorBufferContainer.create(buffer, imageProperties);
+-  }
+-
+-  /**
+-   * Loads a {@link ByteBuffer} containing pixel values with the specific {@link ImageProperties}.
+-   *
+-   * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
+-   * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+-   * #getBuffer}.
+-   *
+-   * @throws IllegalArgumentException if buffer size is less than the image size indicated by image
+-   *     height, width, and color space type in {@link ImageProperties}
+-   */
+-  public void load(ByteBuffer buffer, ImageProperties imageProperties) {
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    tensorBuffer.loadBuffer(buffer, new int[] {buffer.limit()});
+-    container = TensorBufferContainer.create(tensorBuffer, imageProperties);
+-  }
+-
+-  /**
+-   * Loads an {@link android.media.Image} object into this {@link TensorImage}.
+-   *
+-   * <p>The main usage of this method is to load an {@link android.media.Image} object as model
+-   * input to the <a href="TFLite Task
+-   * Library">https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview</a>.
+-   * {@link TensorImage} backed by {@link android.media.Image} is not supported by {@link
+-   * ImageProcessor}.
+-   *
+-   * <p>* @throws IllegalArgumentException if the {@link android.graphics.ImageFormat} of {@code
+-   * image} is not YUV_420_888
+-   */
+-  public void load(Image image) {
+-    container = MediaImageContainer.create(image);
+-  }
+-
+-  /**
+-   * Returns a {@link android.graphics.Bitmap} representation of this {@link TensorImage}.
+-   *
+-   * <p>Numeric casting and clamping will be applied if the stored data is not uint8.
+-   *
+-   * <p>Note that, the reliable way to get pixels from an {@code ALPHA_8} Bitmap is to use {@code
+-   * copyPixelsToBuffer}. Bitmap methods such as, `setPixels()` and `getPixels` do not work.
+-   *
+-   * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for performance
+-   * concern, but if modification is necessary, please make a copy.
+-   *
+-   * @return a reference to a {@link android.graphics.Bitmap} in {@code ARGB_8888} config ("A"
+-   *     channel is always opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType} of
+-   *     this {@link TensorBuffer}.
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   */
+-  public Bitmap getBitmap() {
+-    if (container == null) {
+-      throw new IllegalStateException("No image has been loaded yet.");
++    /**
++     * Loads an int array as RGB pixels into this {@link TensorImage}, representing the pixels
++     * inside.
++     *
++     * <p>Note: numeric casting and clamping will be applied to convert the values into the data
++     * type of this {@link TensorImage} when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}.
++     *
++     * @param pixels the RGB pixels representing the image
++     * @param shape the shape of the image, should either in form (h, w, 3), or in form (1, h, w, 3)
++     * @throws IllegalArgumentException if the shape is neither (h, w, 3) nor (1, h, w, 3)
++     */
++    public void load(int[] pixels, int[] shape) {
++        TensorBuffer buffer = TensorBuffer.createDynamic(getDataType());
++        buffer.loadArray(pixels, shape);
++        load(buffer);
+     }
+ 
+-    return container.getBitmap();
+-  }
+-
+-  /**
+-   * Returns a {@link ByteBuffer} representation of this {@link TensorImage} with the expected data
+-   * type.
+-   *
+-   * <p>Numeric casting and clamping will be applied if the stored data is different from the data
+-   * type of the {@link TensorImage}.
+-   *
+-   * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for performance
+-   * concern, but if modification is necessary, please make a copy.
+-   *
+-   * <p>It's essentially a short cut for {@code getTensorBuffer().getBuffer()}.
+-   *
+-   * @return a reference to a {@link ByteBuffer} which holds the image data
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   */
+-  public ByteBuffer getBuffer() {
+-    return getTensorBuffer().getBuffer();
+-  }
+-
+-  /**
+-   * Returns a {@link TensorBuffer} representation of this {@link TensorImage} with the expected
+-   * data type.
+-   *
+-   * <p>Numeric casting and clamping will be applied if the stored data is different from the data
+-   * type of the {@link TensorImage}.
+-   *
+-   * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for performance
+-   * concern, but if modification is necessary, please make a copy.
+-   *
+-   * @return a reference to a {@link TensorBuffer} which holds the image data
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   */
+-  public TensorBuffer getTensorBuffer() {
+-    if (container == null) {
+-      throw new IllegalStateException("No image has been loaded yet.");
++    /**
++     * Loads a {@link TensorBuffer} containing pixel values. The color layout should be RGB.
++     *
++     * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
++     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}.
++     *
++     * @param buffer the {@link TensorBuffer} to be loaded. Its shape should be either (h, w, 3) or
++     *     (1, h, w, 3)
++     * @throws IllegalArgumentException if the shape is neither (h, w, 3) nor (1, h, w, 3)
++     */
++    public void load(TensorBuffer buffer) {
++        load(buffer, ColorSpaceType.RGB);
+     }
+ 
+-    return container.getTensorBuffer(dataType);
+-  }
+-
+-  /**
+-   * Returns an {@link android.media.Image} representation of this {@link TensorImage}.
+-   *
+-   * <p>This method only works when the {@link TensorImage} is backed by an {@link
+-   * android.media.Image}, meaning you need to first load an {@link android.media.Image} through
+-   * {@link #load(Image)}.
+-   *
+-   * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for performance
+-   * concern, but if modification is necessary, please make a copy.
+-   *
+-   * @return a reference to a {@link android.graphics.Bitmap} in {@code ARGB_8888} config ("A"
+-   *     channel is always opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType} of
+-   *     this {@link TensorBuffer}.
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   */
+-  public Image getMediaImage() {
+-    if (container == null) {
+-      throw new IllegalStateException("No image has been loaded yet.");
++    /**
++     * Loads a {@link TensorBuffer} containing pixel values with the specific {@link
++     * ColorSpaceType}.
++     *
++     * <p>Only supports {@link ColorSpaceType#RGB} and {@link ColorSpaceType#GRAYSCALE}. Use {@link
++     * #load(TensorBuffer, ImageProperties)} for other color space types.
++     *
++     * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
++     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}.
++     *
++     * @param buffer the {@link TensorBuffer} to be loaded. Its shape should be either (h, w, 3) or
++     *     (1, h, w, 3) for RGB images, and either (h, w) or (1, h, w) for GRAYSCALE images
++     * @throws IllegalArgumentException if the shape of buffer does not match the color space type,
++     *         or
++     *     if the color space type is not supported
++     */
++    public void load(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
++        checkArgument(
++                colorSpaceType == ColorSpaceType.RGB || colorSpaceType == ColorSpaceType.GRAYSCALE,
++                "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
++                        + " `load(TensorBuffer, ImageProperties)` for other color space types.");
++
++        container = TensorBufferContainer.create(buffer, colorSpaceType);
+     }
+ 
+-    return container.getMediaImage();
+-  }
+-
+-  /**
+-   * Gets the data type of this {@link TensorImage}.
+-   *
+-   * @return a data type. Currently only {@link DataType#UINT8} and {@link DataType#FLOAT32} are
+-   *     supported.
+-   */
+-  public DataType getDataType() {
+-    return dataType;
+-  }
+-
+-  /**
+-   * Gets the color space type of this {@link TensorImage}.
+-   *
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   */
+-  public ColorSpaceType getColorSpaceType() {
+-    if (container == null) {
+-      throw new IllegalStateException("No image has been loaded yet.");
++    /**
++     * Loads a {@link TensorBuffer} containing pixel values with the specific {@link
++     * ImageProperties}.
++     *
++     * <p>The shape of the {@link TensorBuffer} will not be used to determine image height and
++     * width. Set image properties through {@link ImageProperties}.
++     *
++     * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
++     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}.
++     *
++     * @throws IllegalArgumentException if buffer size is less than the image size indicated by
++     *         image
++     *     height, width, and color space type in {@link ImageProperties}
++     */
++    public void load(TensorBuffer buffer, ImageProperties imageProperties) {
++        container = TensorBufferContainer.create(buffer, imageProperties);
+     }
+ 
+-    return container.getColorSpaceType();
+-  }
+-
+-  /**
+-   * Gets the image width.
+-   *
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   * @throws IllegalArgumentException if the underlying data is corrupted
+-   */
+-  public int getWidth() {
+-    if (container == null) {
+-      throw new IllegalStateException("No image has been loaded yet.");
++    /**
++     * Loads a {@link ByteBuffer} containing pixel values with the specific {@link ImageProperties}.
++     *
++     * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
++     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
++     * #getBuffer}.
++     *
++     * @throws IllegalArgumentException if buffer size is less than the image size indicated by
++     *         image
++     *     height, width, and color space type in {@link ImageProperties}
++     */
++    public void load(ByteBuffer buffer, ImageProperties imageProperties) {
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
++        tensorBuffer.loadBuffer(buffer, new int[] {buffer.limit()});
++        container = TensorBufferContainer.create(tensorBuffer, imageProperties);
+     }
+ 
+-    return container.getWidth();
+-  }
+-
+-  /**
+-   * Gets the image height.
+-   *
+-   * @throws IllegalStateException if the {@link TensorImage} never loads data
+-   * @throws IllegalArgumentException if the underlying data is corrupted
+-   */
+-  public int getHeight() {
+-    if (container == null) {
+-      throw new IllegalStateException("No image has been loaded yet.");
++    /**
++     * Loads an {@link android.media.Image} object into this {@link TensorImage}.
++     *
++     * <p>The main usage of this method is to load an {@link android.media.Image} object as model
++     * input to the <a href="TFLite Task
++     * Library">https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview</a>.
++     * {@link TensorImage} backed by {@link android.media.Image} is not supported by {@link
++     * ImageProcessor}.
++     *
++     * <p>* @throws IllegalArgumentException if the {@link android.graphics.ImageFormat} of {@code
++     * image} is not YUV_420_888
++     */
++    public void load(Image image) {
++        container = MediaImageContainer.create(image);
+     }
+ 
+-    return container.getHeight();
+-  }
++    /**
++     * Returns a {@link android.graphics.Bitmap} representation of this {@link TensorImage}.
++     *
++     * <p>Numeric casting and clamping will be applied if the stored data is not uint8.
++     *
++     * <p>Note that, the reliable way to get pixels from an {@code ALPHA_8} Bitmap is to use {@code
++     * copyPixelsToBuffer}. Bitmap methods such as, `setPixels()` and `getPixels` do not work.
++     *
++     * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for
++     * performance concern, but if modification is necessary, please make a copy.
++     *
++     * @return a reference to a {@link android.graphics.Bitmap} in {@code ARGB_8888} config ("A"
++     *     channel is always opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType}
++     * of this {@link TensorBuffer}.
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     */
++    public Bitmap getBitmap() {
++        if (container == null) {
++            throw new IllegalStateException("No image has been loaded yet.");
++        }
++
++        return container.getBitmap();
++    }
++
++    /**
++     * Returns a {@link ByteBuffer} representation of this {@link TensorImage} with the expected
++     * data type.
++     *
++     * <p>Numeric casting and clamping will be applied if the stored data is different from the data
++     * type of the {@link TensorImage}.
++     *
++     * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for
++     * performance concern, but if modification is necessary, please make a copy.
++     *
++     * <p>It's essentially a short cut for {@code getTensorBuffer().getBuffer()}.
++     *
++     * @return a reference to a {@link ByteBuffer} which holds the image data
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     */
++    public ByteBuffer getBuffer() {
++        return getTensorBuffer().getBuffer();
++    }
++
++    /**
++     * Returns a {@link TensorBuffer} representation of this {@link TensorImage} with the expected
++     * data type.
++     *
++     * <p>Numeric casting and clamping will be applied if the stored data is different from the data
++     * type of the {@link TensorImage}.
++     *
++     * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for
++     * performance concern, but if modification is necessary, please make a copy.
++     *
++     * @return a reference to a {@link TensorBuffer} which holds the image data
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     */
++    public TensorBuffer getTensorBuffer() {
++        if (container == null) {
++            throw new IllegalStateException("No image has been loaded yet.");
++        }
++
++        return container.getTensorBuffer(dataType);
++    }
++
++    /**
++     * Returns an {@link android.media.Image} representation of this {@link TensorImage}.
++     *
++     * <p>This method only works when the {@link TensorImage} is backed by an {@link
++     * android.media.Image}, meaning you need to first load an {@link android.media.Image} through
++     * {@link #load(Image)}.
++     *
++     * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for
++     * performance concern, but if modification is necessary, please make a copy.
++     *
++     * @return a reference to a {@link android.graphics.Bitmap} in {@code ARGB_8888} config ("A"
++     *     channel is always opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType}
++     * of this {@link TensorBuffer}.
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     */
++    public Image getMediaImage() {
++        if (container == null) {
++            throw new IllegalStateException("No image has been loaded yet.");
++        }
++
++        return container.getMediaImage();
++    }
++
++    /**
++     * Gets the data type of this {@link TensorImage}.
++     *
++     * @return a data type. Currently only {@link DataType#UINT8} and {@link DataType#FLOAT32} are
++     *     supported.
++     */
++    public DataType getDataType() {
++        return dataType;
++    }
++
++    /**
++     * Gets the color space type of this {@link TensorImage}.
++     *
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     */
++    public ColorSpaceType getColorSpaceType() {
++        if (container == null) {
++            throw new IllegalStateException("No image has been loaded yet.");
++        }
++
++        return container.getColorSpaceType();
++    }
++
++    /**
++     * Gets the image width.
++     *
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     * @throws IllegalArgumentException if the underlying data is corrupted
++     */
++    public int getWidth() {
++        if (container == null) {
++            throw new IllegalStateException("No image has been loaded yet.");
++        }
++
++        return container.getWidth();
++    }
++
++    /**
++     * Gets the image height.
++     *
++     * @throws IllegalStateException if the {@link TensorImage} never loads data
++     * @throws IllegalArgumentException if the underlying data is corrupted
++     */
++    public int getHeight() {
++        if (container == null) {
++            throw new IllegalStateException("No image has been loaded yet.");
++        }
++
++        return container.getHeight();
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java
+index 06391de9cc3e0..adccf23dc97f0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java
+@@ -19,6 +19,7 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.PointF;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.support.image.ColorSpaceType;
+ import org.tensorflow.lite.support.image.ImageOperator;
+@@ -32,64 +33,60 @@ import org.tensorflow.lite.support.image.TensorImage;
+  * @see ResizeWithCropOrPadOp for resizing without content distortion.
+  */
+ public class ResizeOp implements ImageOperator {
++    /** Algorithms for resizing. */
++    public enum ResizeMethod { BILINEAR, NEAREST_NEIGHBOR }
+ 
+-  /** Algorithms for resizing. */
+-  public enum ResizeMethod {
+-    BILINEAR,
+-    NEAREST_NEIGHBOR
+-  }
+-
+-  private final int targetHeight;
+-  private final int targetWidth;
+-  private final boolean useBilinear;
++    private final int targetHeight;
++    private final int targetWidth;
++    private final boolean useBilinear;
+ 
+-  /**
+-   * Creates a ResizeOp which can resize images to specified size in specified method.
+-   *
+-   * @param targetHeight The expected height of resized image.
+-   * @param targetWidth The expected width of resized image.
+-   * @param resizeMethod The algorithm to use for resizing. Options: {@link ResizeMethod}
+-   */
+-  public ResizeOp(int targetHeight, int targetWidth, ResizeMethod resizeMethod) {
+-    this.targetHeight = targetHeight;
+-    this.targetWidth = targetWidth;
+-    useBilinear = (resizeMethod == ResizeMethod.BILINEAR);
+-  }
++    /**
++     * Creates a ResizeOp which can resize images to specified size in specified method.
++     *
++     * @param targetHeight The expected height of resized image.
++     * @param targetWidth The expected width of resized image.
++     * @param resizeMethod The algorithm to use for resizing. Options: {@link ResizeMethod}
++     */
++    public ResizeOp(int targetHeight, int targetWidth, ResizeMethod resizeMethod) {
++        this.targetHeight = targetHeight;
++        this.targetWidth = targetWidth;
++        useBilinear = (resizeMethod == ResizeMethod.BILINEAR);
++    }
+ 
+-  /**
+-   * Applies the defined resizing on given image and returns the result.
+-   *
+-   * <p>Note: the content of input {@code image} will change, and {@code image} is the same instance
+-   * with the output.
+-   *
+-   * @param image input image.
+-   * @return output image.
+-   */
+-  @Override
+-  @NonNull
+-  public TensorImage apply(@NonNull TensorImage image) {
+-    checkArgument(
+-        image.getColorSpaceType() == ColorSpaceType.RGB,
+-        "Only RGB images are supported in ResizeOp, but not " + image.getColorSpaceType().name());
+-    Bitmap scaled =
+-        Bitmap.createScaledBitmap(image.getBitmap(), targetWidth, targetHeight, useBilinear);
+-    image.load(scaled);
+-    return image;
+-  }
++    /**
++     * Applies the defined resizing on given image and returns the result.
++     *
++     * <p>Note: the content of input {@code image} will change, and {@code image} is the same
++     * instance with the output.
++     *
++     * @param image input image.
++     * @return output image.
++     */
++    @Override
++    @NonNull
++    public TensorImage apply(@NonNull TensorImage image) {
++        checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
++                "Only RGB images are supported in ResizeOp, but not "
++                        + image.getColorSpaceType().name());
++        Bitmap scaled = Bitmap.createScaledBitmap(
++                image.getBitmap(), targetWidth, targetHeight, useBilinear);
++        image.load(scaled);
++        return image;
++    }
+ 
+-  @Override
+-  public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
+-    return targetHeight;
+-  }
++    @Override
++    public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
++        return targetHeight;
++    }
+ 
+-  @Override
+-  public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
+-    return targetWidth;
+-  }
++    @Override
++    public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
++        return targetWidth;
++    }
+ 
+-  @Override
+-  public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+-    return new PointF(
+-        point.x * inputImageWidth / targetWidth, point.y * inputImageHeight / targetHeight);
+-  }
++    @Override
++    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
++        return new PointF(
++                point.x * inputImageWidth / targetWidth, point.y * inputImageHeight / targetHeight);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java
+index 66491090ac9c0..e5de5bbcf50d9 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java
+@@ -22,6 +22,7 @@ import android.graphics.Bitmap.Config;
+ import android.graphics.Canvas;
+ import android.graphics.PointF;
+ import android.graphics.Rect;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.support.image.ColorSpaceType;
+ import org.tensorflow.lite.support.image.ImageOperator;
+@@ -37,96 +38,95 @@ import org.tensorflow.lite.support.image.TensorImage;
+  * @see ResizeOp for reszing images while stretching / compressing the content.
+  */
+ public class ResizeWithCropOrPadOp implements ImageOperator {
+-  private final int targetHeight;
+-  private final int targetWidth;
+-  private final Bitmap output;
+-
+-  /**
+-   * Creates a ResizeWithCropOrPadOp which could crop/pad images to specified size. It adopts
+-   * center-crop and zero-padding.
+-   *
+-   * @param targetHeight The expected height of cropped/padded image.
+-   * @param targetWidth The expected width of cropped/padded image.
+-   */
+-  public ResizeWithCropOrPadOp(int targetHeight, int targetWidth) {
+-    this.targetHeight = targetHeight;
+-    this.targetWidth = targetWidth;
+-    output = Bitmap.createBitmap(this.targetWidth, this.targetHeight, Config.ARGB_8888);
+-  }
++    private final int targetHeight;
++    private final int targetWidth;
++    private final Bitmap output;
+ 
+-  /**
+-   * Applies the defined resizing with cropping or/and padding on given image and returns the
+-   * result.
+-   *
+-   * <p>Note: the content of input {@code image} will change, and {@code image} is the same instance
+-   * with the output.
+-   *
+-   * @param image input image.
+-   * @return output image.
+-   */
+-  @Override
+-  @NonNull
+-  public TensorImage apply(@NonNull TensorImage image) {
+-    checkArgument(
+-        image.getColorSpaceType() == ColorSpaceType.RGB,
+-        "Only RGB images are supported in ResizeWithCropOrPadOp, but not "
+-            + image.getColorSpaceType().name());
+-    Bitmap input = image.getBitmap();
+-    int srcL;
+-    int srcR;
+-    int srcT;
+-    int srcB;
+-    int dstL;
+-    int dstR;
+-    int dstT;
+-    int dstB;
+-    int w = input.getWidth();
+-    int h = input.getHeight();
+-    if (targetWidth > w) { // padding
+-      srcL = 0;
+-      srcR = w;
+-      dstL = (targetWidth - w) / 2;
+-      dstR = dstL + w;
+-    } else { // cropping
+-      dstL = 0;
+-      dstR = targetWidth;
+-      srcL = (w - targetWidth) / 2;
+-      srcR = srcL + targetWidth;
++    /**
++     * Creates a ResizeWithCropOrPadOp which could crop/pad images to specified size. It adopts
++     * center-crop and zero-padding.
++     *
++     * @param targetHeight The expected height of cropped/padded image.
++     * @param targetWidth The expected width of cropped/padded image.
++     */
++    public ResizeWithCropOrPadOp(int targetHeight, int targetWidth) {
++        this.targetHeight = targetHeight;
++        this.targetWidth = targetWidth;
++        output = Bitmap.createBitmap(this.targetWidth, this.targetHeight, Config.ARGB_8888);
+     }
+-    if (targetHeight > h) { // padding
+-      srcT = 0;
+-      srcB = h;
+-      dstT = (targetHeight - h) / 2;
+-      dstB = dstT + h;
+-    } else { // cropping
+-      dstT = 0;
+-      dstB = targetHeight;
+-      srcT = (h - targetHeight) / 2;
+-      srcB = srcT + targetHeight;
++
++    /**
++     * Applies the defined resizing with cropping or/and padding on given image and returns the
++     * result.
++     *
++     * <p>Note: the content of input {@code image} will change, and {@code image} is the same
++     * instance with the output.
++     *
++     * @param image input image.
++     * @return output image.
++     */
++    @Override
++    @NonNull
++    public TensorImage apply(@NonNull TensorImage image) {
++        checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
++                "Only RGB images are supported in ResizeWithCropOrPadOp, but not "
++                        + image.getColorSpaceType().name());
++        Bitmap input = image.getBitmap();
++        int srcL;
++        int srcR;
++        int srcT;
++        int srcB;
++        int dstL;
++        int dstR;
++        int dstT;
++        int dstB;
++        int w = input.getWidth();
++        int h = input.getHeight();
++        if (targetWidth > w) { // padding
++            srcL = 0;
++            srcR = w;
++            dstL = (targetWidth - w) / 2;
++            dstR = dstL + w;
++        } else { // cropping
++            dstL = 0;
++            dstR = targetWidth;
++            srcL = (w - targetWidth) / 2;
++            srcR = srcL + targetWidth;
++        }
++        if (targetHeight > h) { // padding
++            srcT = 0;
++            srcB = h;
++            dstT = (targetHeight - h) / 2;
++            dstB = dstT + h;
++        } else { // cropping
++            dstT = 0;
++            dstB = targetHeight;
++            srcT = (h - targetHeight) / 2;
++            srcB = srcT + targetHeight;
++        }
++        Rect src = new Rect(srcL, srcT, srcR, srcB);
++        Rect dst = new Rect(dstL, dstT, dstR, dstB);
++        new Canvas(output).drawBitmap(input, src, dst, null);
++        image.load(output);
++        return image;
+     }
+-    Rect src = new Rect(srcL, srcT, srcR, srcB);
+-    Rect dst = new Rect(dstL, dstT, dstR, dstB);
+-    new Canvas(output).drawBitmap(input, src, dst, null);
+-    image.load(output);
+-    return image;
+-  }
+ 
+-  @Override
+-  public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
+-    return targetHeight;
+-  }
++    @Override
++    public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
++        return targetHeight;
++    }
+ 
+-  @Override
+-  public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
+-    return targetWidth;
+-  }
++    @Override
++    public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
++        return targetWidth;
++    }
+ 
+-  @Override
+-  public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+-    return transformImpl(point, targetHeight, targetWidth, inputImageHeight, inputImageWidth);
+-  }
++    @Override
++    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
++        return transformImpl(point, targetHeight, targetWidth, inputImageHeight, inputImageWidth);
++    }
+ 
+-  private static PointF transformImpl(PointF point, int srcH, int srcW, int dstH, int dstW) {
+-    return new PointF(point.x + (dstW - srcW) / 2, point.y + (dstH - srcH) / 2);
+-  }
++    private static PointF transformImpl(PointF point, int srcH, int srcW, int dstH, int dstW) {
++        return new PointF(point.x + (dstW - srcW) / 2, point.y + (dstH - srcH) / 2);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java
+index 849b4bc9ef3db..86413c90c69ca 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java
+@@ -20,6 +20,7 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import android.graphics.Bitmap;
+ import android.graphics.Matrix;
+ import android.graphics.PointF;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.support.image.ColorSpaceType;
+ import org.tensorflow.lite.support.image.ImageOperator;
+@@ -27,83 +28,83 @@ import org.tensorflow.lite.support.image.TensorImage;
+ 
+ /** Rotates image counter-clockwise. */
+ public class Rot90Op implements ImageOperator {
++    private final int numRotation;
+ 
+-  private final int numRotation;
+-
+-  /** Creates a Rot90 Op which will rotate image by 90 degree counter-clockwise. */
+-  public Rot90Op() {
+-    this(1);
+-  }
++    /** Creates a Rot90 Op which will rotate image by 90 degree counter-clockwise. */
++    public Rot90Op() {
++        this(1);
++    }
+ 
+-  /**
+-   * Creates a Rot90 Op which will rotate image by 90 degree for {@code k} times counter-clockwise.
+-   *
+-   * @param k The number of times the image is rotated by 90 degrees. If it's positive, the image
+-   *     will be rotated counter-clockwise. If it's negative, the op will rotate image clockwise.
+-   */
+-  public Rot90Op(int k) {
+-    numRotation = k % 4;
+-  }
++    /**
++     * Creates a Rot90 Op which will rotate image by 90 degree for {@code k} times
++     * counter-clockwise.
++     *
++     * @param k The number of times the image is rotated by 90 degrees. If it's positive, the image
++     *     will be rotated counter-clockwise. If it's negative, the op will rotate image clockwise.
++     */
++    public Rot90Op(int k) {
++        numRotation = k % 4;
++    }
+ 
+-  /**
+-   * Applies the defined rotation on given image and returns the result.
+-   *
+-   * <p>Note: the content of input {@code image} will change, and {@code image} is the same instance
+-   * with the output.
+-   *
+-   * @param image input image.
+-   * @return output image.
+-   */
+-  @NonNull
+-  @Override
+-  public TensorImage apply(@NonNull TensorImage image) {
+-    checkArgument(
+-        image.getColorSpaceType() == ColorSpaceType.RGB,
+-        "Only RGB images are supported in Rot90Op, but not " + image.getColorSpaceType().name());
+-    Bitmap input = image.getBitmap();
+-    if (numRotation == 0) {
+-      return image;
++    /**
++     * Applies the defined rotation on given image and returns the result.
++     *
++     * <p>Note: the content of input {@code image} will change, and {@code image} is the same
++     * instance with the output.
++     *
++     * @param image input image.
++     * @return output image.
++     */
++    @NonNull
++    @Override
++    public TensorImage apply(@NonNull TensorImage image) {
++        checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
++                "Only RGB images are supported in Rot90Op, but not "
++                        + image.getColorSpaceType().name());
++        Bitmap input = image.getBitmap();
++        if (numRotation == 0) {
++            return image;
++        }
++        int w = input.getWidth();
++        int h = input.getHeight();
++        Matrix matrix = new Matrix();
++        matrix.postTranslate(w * 0.5f, h * 0.5f);
++        matrix.postRotate(-90 * numRotation);
++        int newW = (numRotation % 2 == 0) ? w : h;
++        int newH = (numRotation % 2 == 0) ? h : w;
++        matrix.postTranslate(newW * 0.5f, newH * 0.5f);
++        Bitmap output = Bitmap.createBitmap(input, 0, 0, w, h, matrix, false);
++        image.load(output);
++        return image;
+     }
+-    int w = input.getWidth();
+-    int h = input.getHeight();
+-    Matrix matrix = new Matrix();
+-    matrix.postTranslate(w * 0.5f, h * 0.5f);
+-    matrix.postRotate(-90 * numRotation);
+-    int newW = (numRotation % 2 == 0) ? w : h;
+-    int newH = (numRotation % 2 == 0) ? h : w;
+-    matrix.postTranslate(newW * 0.5f, newH * 0.5f);
+-    Bitmap output = Bitmap.createBitmap(input, 0, 0, w, h, matrix, false);
+-    image.load(output);
+-    return image;
+-  }
+ 
+-  @Override
+-  public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
+-    return (numRotation % 2 == 0) ? inputImageHeight : inputImageWidth;
+-  }
++    @Override
++    public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
++        return (numRotation % 2 == 0) ? inputImageHeight : inputImageWidth;
++    }
+ 
+-  @Override
+-  public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
+-    return (numRotation % 2 == 0) ? inputImageWidth : inputImageHeight;
+-  }
++    @Override
++    public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
++        return (numRotation % 2 == 0) ? inputImageWidth : inputImageHeight;
++    }
+ 
+-  @Override
+-  public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+-    int inverseNumRotation = (4 - numRotation) % 4;
+-    int height = getOutputImageHeight(inputImageHeight, inputImageWidth);
+-    int width = getOutputImageWidth(inputImageHeight, inputImageWidth);
+-    return transformImpl(point, height, width, inverseNumRotation);
+-  }
++    @Override
++    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
++        int inverseNumRotation = (4 - numRotation) % 4;
++        int height = getOutputImageHeight(inputImageHeight, inputImageWidth);
++        int width = getOutputImageWidth(inputImageHeight, inputImageWidth);
++        return transformImpl(point, height, width, inverseNumRotation);
++    }
+ 
+-  private static PointF transformImpl(PointF point, int height, int width, int numRotation) {
+-    if (numRotation == 0) {
+-      return point;
+-    } else if (numRotation == 1) {
+-      return new PointF(point.y, width - point.x);
+-    } else if (numRotation == 2) {
+-      return new PointF(width - point.x, height - point.y);
+-    } else { // numRotation == 3
+-      return new PointF(height - point.y, point.x);
++    private static PointF transformImpl(PointF point, int height, int width, int numRotation) {
++        if (numRotation == 0) {
++            return point;
++        } else if (numRotation == 1) {
++            return new PointF(point.y, width - point.x);
++        } else if (numRotation == 2) {
++            return new PointF(width - point.x, height - point.y);
++        } else { // numRotation == 3
++            return new PointF(height - point.y, point.x);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java
+index 5d10ac890e57b..feb2b3b7b0762 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.image.ops;
+ 
+ import android.graphics.PointF;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.support.common.TensorOperator;
+ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+@@ -31,48 +32,47 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * @see org.tensorflow.lite.support.image.TensorImage
+  */
+ public class TensorOperatorWrapper implements ImageOperator {
++    private final TensorOperator tensorOp;
+ 
+-  private final TensorOperator tensorOp;
+-
+-  /**
+-   * Wraps a {@link TensorOperator} object as an {@link ImageOperator}, so that the {@link
+-   * TensorOperator} could handle {@link TensorImage} objects by handling its underlying {@link
+-   * org.tensorflow.lite.support.tensorbuffer.TensorBuffer}.
+-   *
+-   * <p>Requirement: The {@code op} should not change coordinate system when applied on an image.
+-   *
+-   * @param op The created operator.
+-   */
+-  public TensorOperatorWrapper(TensorOperator op) {
+-    tensorOp = op;
+-  }
++    /**
++     * Wraps a {@link TensorOperator} object as an {@link ImageOperator}, so that the {@link
++     * TensorOperator} could handle {@link TensorImage} objects by handling its underlying {@link
++     * org.tensorflow.lite.support.tensorbuffer.TensorBuffer}.
++     *
++     * <p>Requirement: The {@code op} should not change coordinate system when applied on an image.
++     *
++     * @param op The created operator.
++     */
++    public TensorOperatorWrapper(TensorOperator op) {
++        tensorOp = op;
++    }
+ 
+-  @Override
+-  @NonNull
+-  public TensorImage apply(@NonNull TensorImage image) {
+-    SupportPreconditions.checkNotNull(image, "Op cannot apply on null image.");
+-    TensorBuffer resBuffer = tensorOp.apply(image.getTensorBuffer());
+-    // Some ops may change the data type of the underlying TensorBuffer, such as CastOp. Therefore,
+-    // need to create a new TensorImage with the correct data type.
+-    // However the underlying ops should not touch the color type.
+-    ColorSpaceType colorSpaceType = image.getColorSpaceType();
+-    TensorImage resImage = new TensorImage(resBuffer.getDataType());
+-    resImage.load(resBuffer, colorSpaceType);
+-    return resImage;
+-  }
++    @Override
++    @NonNull
++    public TensorImage apply(@NonNull TensorImage image) {
++        SupportPreconditions.checkNotNull(image, "Op cannot apply on null image.");
++        TensorBuffer resBuffer = tensorOp.apply(image.getTensorBuffer());
++        // Some ops may change the data type of the underlying TensorBuffer, such as CastOp.
++        // Therefore, need to create a new TensorImage with the correct data type. However the
++        // underlying ops should not touch the color type.
++        ColorSpaceType colorSpaceType = image.getColorSpaceType();
++        TensorImage resImage = new TensorImage(resBuffer.getDataType());
++        resImage.load(resBuffer, colorSpaceType);
++        return resImage;
++    }
+ 
+-  @Override
+-  public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
+-    return inputImageHeight;
+-  }
++    @Override
++    public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
++        return inputImageHeight;
++    }
+ 
+-  @Override
+-  public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
+-    return inputImageWidth;
+-  }
++    @Override
++    public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
++        return inputImageWidth;
++    }
+ 
+-  @Override
+-  public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+-    return point;
+-  }
++    @Override
++    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
++        return point;
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java
+index bd3c10b254ac5..1a6f905b1bffd 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java
+@@ -23,6 +23,7 @@ import android.graphics.ColorFilter;
+ import android.graphics.ColorMatrixColorFilter;
+ import android.graphics.Paint;
+ import android.graphics.PointF;
++
+ import org.tensorflow.lite.support.image.ColorSpaceType;
+ import org.tensorflow.lite.support.image.ImageOperator;
+ import org.tensorflow.lite.support.image.TensorImage;
+@@ -41,77 +42,73 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * https://docs.opencv.org/master/de/d25/imgproc_color_conversions.html#color_convert_rgb_gray
+  */
+ public class TransformToGrayscaleOp implements ImageOperator {
++    // A matrix is created that will be applied later to canvas to generate grayscale image
++    // The luminance of each pixel is calculated as the weighted sum of the 3 RGB values
++    // Y = 0.299R + 0.587G + 0.114B
++    private static final float[] BITMAP_RGBA_GRAYSCALE_TRANSFORMATION =
++            new float[] {0.299F, 0.587F, 0.114F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F,
++                    0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 1.0F, 0.0F};
+ 
+-  // A matrix is created that will be applied later to canvas to generate grayscale image
+-  // The luminance of each pixel is calculated as the weighted sum of the 3 RGB values
+-  // Y = 0.299R + 0.587G + 0.114B
+-  private static final float[] BITMAP_RGBA_GRAYSCALE_TRANSFORMATION =
+-      new float[] {
+-        0.299F, 0.587F, 0.114F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F,
+-        0.0F, 0.0F, 0.0F, 0.0F, 1.0F, 0.0F
+-      };
+-
+-  /** Creates a TransformToGrayscaleOp. */
+-  public TransformToGrayscaleOp() {}
++    /** Creates a TransformToGrayscaleOp. */
++    public TransformToGrayscaleOp() {}
+ 
+-  /**
+-   * Applies the transformation to grayscale and returns a {@link TensorImage}.
+-   *
+-   * <p>If the input image is already {@link
+-   * org.tensorflow.lite.support.image.ColorSpaceType#GRAYSCALE}, this op will be a no-op.
+-   *
+-   * @throws IllegalArgumentException if the {@code image} is not {@link
+-   *     org.tensorflow.lite.support.image.ColorSpaceType#RGB} or {@link
+-   *     org.tensorflow.lite.support.image.ColorSpaceType#GRAYSCALE}.
+-   */
+-  @Override
+-  public TensorImage apply(TensorImage image) {
+-    if (image.getColorSpaceType() == ColorSpaceType.GRAYSCALE) {
+-      return image;
+-    } else {
+-      checkArgument(
+-          image.getColorSpaceType() == ColorSpaceType.RGB,
+-          "Only RGB images are supported in TransformToGrayscaleOp, but not "
+-              + image.getColorSpaceType().name());
+-    }
+-    int h = image.getHeight();
+-    int w = image.getWidth();
+-    Bitmap bmpGrayscale = Bitmap.createBitmap(w, h, Bitmap.Config.ARGB_8888);
+-    Canvas canvas = new Canvas(bmpGrayscale);
+-    Paint paint = new Paint();
+-    ColorMatrixColorFilter colorMatrixFilter =
+-        new ColorMatrixColorFilter(BITMAP_RGBA_GRAYSCALE_TRANSFORMATION);
+-    paint.setColorFilter((ColorFilter) colorMatrixFilter);
+-    canvas.drawBitmap(image.getBitmap(), 0.0F, 0.0F, paint);
++    /**
++     * Applies the transformation to grayscale and returns a {@link TensorImage}.
++     *
++     * <p>If the input image is already {@link
++     * org.tensorflow.lite.support.image.ColorSpaceType#GRAYSCALE}, this op will be a no-op.
++     *
++     * @throws IllegalArgumentException if the {@code image} is not {@link
++     *     org.tensorflow.lite.support.image.ColorSpaceType#RGB} or {@link
++     *     org.tensorflow.lite.support.image.ColorSpaceType#GRAYSCALE}.
++     */
++    @Override
++    public TensorImage apply(TensorImage image) {
++        if (image.getColorSpaceType() == ColorSpaceType.GRAYSCALE) {
++            return image;
++        } else {
++            checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
++                    "Only RGB images are supported in TransformToGrayscaleOp, but not "
++                            + image.getColorSpaceType().name());
++        }
++        int h = image.getHeight();
++        int w = image.getWidth();
++        Bitmap bmpGrayscale = Bitmap.createBitmap(w, h, Bitmap.Config.ARGB_8888);
++        Canvas canvas = new Canvas(bmpGrayscale);
++        Paint paint = new Paint();
++        ColorMatrixColorFilter colorMatrixFilter =
++                new ColorMatrixColorFilter(BITMAP_RGBA_GRAYSCALE_TRANSFORMATION);
++        paint.setColorFilter((ColorFilter) colorMatrixFilter);
++        canvas.drawBitmap(image.getBitmap(), 0.0F, 0.0F, paint);
+ 
+-    // Get the pixels from the generated grayscale image
+-    int[] intValues = new int[w * h];
+-    bmpGrayscale.getPixels(intValues, 0, w, 0, 0, w, h);
+-    // Shape with one channel
+-    int[] shape = new int[] {1, h, w, 1};
++        // Get the pixels from the generated grayscale image
++        int[] intValues = new int[w * h];
++        bmpGrayscale.getPixels(intValues, 0, w, 0, 0, w, h);
++        // Shape with one channel
++        int[] shape = new int[] {1, h, w, 1};
+ 
+-    // Get R channel from ARGB color
+-    for (int i = 0; i < intValues.length; i++) {
+-      intValues[i] = ((intValues[i] >> 16) & 0xff);
++        // Get R channel from ARGB color
++        for (int i = 0; i < intValues.length; i++) {
++            intValues[i] = ((intValues[i] >> 16) & 0xff);
++        }
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, image.getDataType());
++        buffer.loadArray(intValues, shape);
++        image.load(buffer, ColorSpaceType.GRAYSCALE);
++        return image;
+     }
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, image.getDataType());
+-    buffer.loadArray(intValues, shape);
+-    image.load(buffer, ColorSpaceType.GRAYSCALE);
+-    return image;
+-  }
+ 
+-  @Override
+-  public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
+-    return inputImageHeight;
+-  }
++    @Override
++    public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
++        return inputImageHeight;
++    }
+ 
+-  @Override
+-  public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
+-    return inputImageWidth;
+-  }
++    @Override
++    public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
++        return inputImageWidth;
++    }
+ 
+-  @Override
+-  public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+-    return point;
+-  }
++    @Override
++    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
++        return point;
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java
+index 8135ddcc28619..af56b70a77cf3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java
+@@ -15,9 +15,10 @@ limitations under the License.
+ 
+ package org.tensorflow.lite.support.label;
+ 
+-import java.util.Objects;
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ 
++import java.util.Objects;
++
+ /**
+  * Category is a util class, contains a label, its display name, a float value as score, and the
+  * index of the label in the corresponding label file. Typically it's used as result of
+@@ -25,102 +26,97 @@ import org.tensorflow.lite.annotations.UsedByReflection;
+  */
+ @UsedByReflection("TFLiteSupport/Task")
+ public final class Category {
+-  private static final int DEFAULT_INDEX = -1;
+-  private static final float TOLERANCE = 1e-6f;
+-  private final int index;
+-  private final String label;
+-  private final String displayName;
+-  private final float score;
+-
+-  /**
+-   * Constructs a {@link Category} object.
+-   *
+-   * @param label the label of this category object
+-   * @param displayName the display name of the label, which may be translated for different
+-   *     locales. For exmaple, a label, "apple", may be translated into Spanish for display purpose,
+-   *     so that the displayName is "manzana".
+-   * @param score the probability score of this label category
+-   * @param index the index of the label in the corresponding label file
+-   */
+-  @UsedByReflection("TFLiteSupport/Task")
+-  public static Category create(String label, String displayName, float score, int index) {
+-    return new Category(label, displayName, score, index);
+-  }
+-
+-  /** Constructs a {@link Category} object with the default index (-1). */
+-  @UsedByReflection("TFLiteSupport/Task")
+-  public static Category create(String label, String displayName, float score) {
+-    return new Category(label, displayName, score, DEFAULT_INDEX);
+-  }
+-
+-  /** Constructs a {@link Category} object with an empty displayName and the default index (-1). */
+-  @UsedByReflection("TFLiteSupport/Task")
+-  public Category(String label, float score) {
+-    this(label, /*displayName=*/ "", score, DEFAULT_INDEX);
+-  }
+-
+-  private Category(String label, String displayName, float score, int index) {
+-    this.label = label;
+-    this.displayName = displayName;
+-    this.score = score;
+-    this.index = index;
+-  }
+-
+-  /** Gets the reference of category's label. */
+-  public String getLabel() {
+-    return label;
+-  }
+-
+-  /**
+-   * Gets the reference of category's displayName, a name in locale of the label.
+-   *
+-   * <p>The display name can be an empty string if this {@link Category} object is constructed
+-   * without displayName, such as when using {@link #Category(String label, float score)}.
+-   */
+-  public String getDisplayName() {
+-    return displayName;
+-  }
+-
+-  /** Gets the score of the category. */
+-  public float getScore() {
+-    return score;
+-  }
+-
+-  /**
+-   * Gets the index of the category. The index value might be -1, which means it has not been set up
+-   * properly and is invalid.
+-   */
+-  public int getIndex() {
+-    return index;
+-  }
+-
+-  @Override
+-  public boolean equals(Object o) {
+-    if (o instanceof Category) {
+-      Category other = (Category) o;
+-      return (other.getLabel().equals(this.label)
+-          && other.getDisplayName().equals(this.displayName)
+-          && Math.abs(other.getScore() - this.score) < TOLERANCE
+-          && other.getIndex() == this.index);
++    private static final int DEFAULT_INDEX = -1;
++    private static final float TOLERANCE = 1e-6f;
++    private final int index;
++    private final String label;
++    private final String displayName;
++    private final float score;
++
++    /**
++     * Constructs a {@link Category} object.
++     *
++     * @param label the label of this category object
++     * @param displayName the display name of the label, which may be translated for different
++     *     locales. For exmaple, a label, "apple", may be translated into Spanish for display
++     * purpose, so that the displayName is "manzana".
++     * @param score the probability score of this label category
++     * @param index the index of the label in the corresponding label file
++     */
++    @UsedByReflection("TFLiteSupport/Task")
++    public static Category create(String label, String displayName, float score, int index) {
++        return new Category(label, displayName, score, index);
++    }
++
++    /** Constructs a {@link Category} object with the default index (-1). */
++    @UsedByReflection("TFLiteSupport/Task")
++    public static Category create(String label, String displayName, float score) {
++        return new Category(label, displayName, score, DEFAULT_INDEX);
++    }
++
++    /**
++     * Constructs a {@link Category} object with an empty displayName and the default index (-1).
++     */
++    @UsedByReflection("TFLiteSupport/Task")
++    public Category(String label, float score) {
++        this(label, /*displayName=*/"", score, DEFAULT_INDEX);
++    }
++
++    private Category(String label, String displayName, float score, int index) {
++        this.label = label;
++        this.displayName = displayName;
++        this.score = score;
++        this.index = index;
++    }
++
++    /** Gets the reference of category's label. */
++    public String getLabel() {
++        return label;
++    }
++
++    /**
++     * Gets the reference of category's displayName, a name in locale of the label.
++     *
++     * <p>The display name can be an empty string if this {@link Category} object is constructed
++     * without displayName, such as when using {@link #Category(String label, float score)}.
++     */
++    public String getDisplayName() {
++        return displayName;
++    }
++
++    /** Gets the score of the category. */
++    public float getScore() {
++        return score;
++    }
++
++    /**
++     * Gets the index of the category. The index value might be -1, which means it has not been set
++     * up properly and is invalid.
++     */
++    public int getIndex() {
++        return index;
++    }
++
++    @Override
++    public boolean equals(Object o) {
++        if (o instanceof Category) {
++            Category other = (Category) o;
++            return (other.getLabel().equals(this.label)
++                    && other.getDisplayName().equals(this.displayName)
++                    && Math.abs(other.getScore() - this.score) < TOLERANCE
++                    && other.getIndex() == this.index);
++        }
++        return false;
++    }
++
++    @Override
++    public int hashCode() {
++        return Objects.hash(label, displayName, score, index);
++    }
++
++    @Override
++    public String toString() {
++        return "<Category \"" + label + "\" (displayName=" + displayName + " score=" + score
++                + " index=" + index + ")>";
+     }
+-    return false;
+-  }
+-
+-  @Override
+-  public int hashCode() {
+-    return Objects.hash(label, displayName, score, index);
+-  }
+-
+-  @Override
+-  public String toString() {
+-    return "<Category \""
+-        + label
+-        + "\" (displayName="
+-        + displayName
+-        + " score="
+-        + score
+-        + " index="
+-        + index
+-        + ")>";
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java
+index af21d74e25f5d..56ee89f091e03 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java
+@@ -16,49 +16,52 @@ limitations under the License.
+ package org.tensorflow.lite.support.label;
+ 
+ import android.util.Log;
+-import java.util.ArrayList;
+-import java.util.Arrays;
+-import java.util.List;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.ArrayList;
++import java.util.Arrays;
++import java.util.List;
++
+ /** Label operation utils. */
+ public class LabelUtil {
+-  /**
+-   * Maps an int value tensor to a list of string labels. It takes an array of strings as the
+-   * dictionary. Example: if the given tensor is [3, 1, 0], and given labels is ["background",
+-   * "apple", "banana", "cherry", "date"], the result will be ["date", "banana", "apple"].
+-   *
+-   * @param tensorBuffer A tensor with index values. The values should be non-negative integers, and
+-   *     each value {@code x} will be converted to {@code labels[x + offset]}. If the tensor is
+-   *     given as a float {@link TensorBuffer}, values will be cast to integers. All values that are
+-   *     out of bound will map to empty string.
+-   * @param labels A list of strings, used as a dictionary to look up. The index of the array
+-   *     element will be used as the key. To get better performance, use an object that implements
+-   *     RandomAccess, such as {@link ArrayList}.
+-   * @param offset The offset value when look up int values in the {@code labels}.
+-   * @return the mapped strings. The length of the list is {@link TensorBuffer#getFlatSize}.
+-   * @throws IllegalArgumentException if {@code tensorBuffer} or {@code labels} is null.
+-   */
+-  public static List<String> mapValueToLabels(
+-      @NonNull TensorBuffer tensorBuffer, @NonNull List<String> labels, int offset) {
+-    SupportPreconditions.checkNotNull(tensorBuffer, "Given tensor should not be null");
+-    SupportPreconditions.checkNotNull(labels, "Given labels should not be null");
+-    int[] values = tensorBuffer.getIntArray();
+-    Log.d("values", Arrays.toString(values));
+-    List<String> result = new ArrayList<>();
+-    for (int v : values) {
+-      int index = v + offset;
+-      if (index < 0 || index >= labels.size()) {
+-        result.add("");
+-      } else {
+-        result.add(labels.get(index));
+-      }
++    /**
++     * Maps an int value tensor to a list of string labels. It takes an array of strings as the
++     * dictionary. Example: if the given tensor is [3, 1, 0], and given labels is ["background",
++     * "apple", "banana", "cherry", "date"], the result will be ["date", "banana", "apple"].
++     *
++     * @param tensorBuffer A tensor with index values. The values should be non-negative integers,
++     *         and
++     *     each value {@code x} will be converted to {@code labels[x + offset]}. If the tensor is
++     *     given as a float {@link TensorBuffer}, values will be cast to integers. All values that
++     * are out of bound will map to empty string.
++     * @param labels A list of strings, used as a dictionary to look up. The index of the array
++     *     element will be used as the key. To get better performance, use an object that implements
++     *     RandomAccess, such as {@link ArrayList}.
++     * @param offset The offset value when look up int values in the {@code labels}.
++     * @return the mapped strings. The length of the list is {@link TensorBuffer#getFlatSize}.
++     * @throws IllegalArgumentException if {@code tensorBuffer} or {@code labels} is null.
++     */
++    public static List<String> mapValueToLabels(
++            @NonNull TensorBuffer tensorBuffer, @NonNull List<String> labels, int offset) {
++        SupportPreconditions.checkNotNull(tensorBuffer, "Given tensor should not be null");
++        SupportPreconditions.checkNotNull(labels, "Given labels should not be null");
++        int[] values = tensorBuffer.getIntArray();
++        Log.d("values", Arrays.toString(values));
++        List<String> result = new ArrayList<>();
++        for (int v : values) {
++            int index = v + offset;
++            if (index < 0 || index >= labels.size()) {
++                result.add("");
++            } else {
++                result.add(labels.get(index));
++            }
++        }
++        return result;
+     }
+-    return result;
+-  }
+ 
+-  // Private constructor to prevent initialization.
+-  private LabelUtil() {}
++    // Private constructor to prevent initialization.
++    private LabelUtil() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java
+index bdab7cf464c1b..edd683cd08126 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java
+@@ -16,16 +16,18 @@ limitations under the License.
+ package org.tensorflow.lite.support.label;
+ 
+ import android.content.Context;
++
++import org.checkerframework.checker.nullness.qual.NonNull;
++import org.tensorflow.lite.DataType;
++import org.tensorflow.lite.support.common.internal.SupportPreconditions;
++import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
++
+ import java.nio.ByteBuffer;
+ import java.util.ArrayList;
+ import java.util.Arrays;
+ import java.util.LinkedHashMap;
+ import java.util.List;
+ import java.util.Map;
+-import org.checkerframework.checker.nullness.qual.NonNull;
+-import org.tensorflow.lite.DataType;
+-import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+-import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /**
+  * TensorLabel is an util wrapper for TensorBuffers with meaningful labels on an axis.
+@@ -56,169 +58,170 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  *     a label file (plain text file whose each line is a label) in assets simply.
+  */
+ public class TensorLabel {
+-  private final Map<Integer, List<String>> axisLabels;
+-  private final TensorBuffer tensorBuffer;
+-  private final int[] shape;
+-
+-  /**
+-   * Creates a TensorLabel object which is able to label on the axes of multi-dimensional tensors.
+-   *
+-   * @param axisLabels A map, whose key is axis id (starting from 0) and value is corresponding
+-   *     labels. Note: The size of labels should be same with the size of the tensor on that axis.
+-   * @param tensorBuffer The TensorBuffer to be labeled.
+-   * @throws NullPointerException if {@code axisLabels} or {@code tensorBuffer} is null, or any
+-   *     value in {@code axisLabels} is null.
+-   * @throws IllegalArgumentException if any key in {@code axisLabels} is out of range (compared to
+-   *     the shape of {@code tensorBuffer}, or any value (labels) has different size with the {@code
+-   *     tensorBuffer} on the given dimension.
+-   */
+-  public TensorLabel(
+-      @NonNull Map<Integer, List<String>> axisLabels, @NonNull TensorBuffer tensorBuffer) {
+-    SupportPreconditions.checkNotNull(axisLabels, "Axis labels cannot be null.");
+-    SupportPreconditions.checkNotNull(tensorBuffer, "Tensor Buffer cannot be null.");
+-    this.axisLabels = axisLabels;
+-    this.tensorBuffer = tensorBuffer;
+-    this.shape = tensorBuffer.getShape();
+-    for (Map.Entry<Integer, List<String>> entry : axisLabels.entrySet()) {
+-      int axis = entry.getKey();
+-      SupportPreconditions.checkArgument(
+-          axis >= 0 && axis < shape.length, "Invalid axis id: " + axis);
+-      SupportPreconditions.checkNotNull(entry.getValue(), "Label list is null on axis " + axis);
+-      SupportPreconditions.checkArgument(
+-          shape[axis] == entry.getValue().size(),
+-          "Label number " + entry.getValue().size() + " mismatch the shape on axis " + axis);
++    private final Map<Integer, List<String>> axisLabels;
++    private final TensorBuffer tensorBuffer;
++    private final int[] shape;
++
++    /**
++     * Creates a TensorLabel object which is able to label on the axes of multi-dimensional tensors.
++     *
++     * @param axisLabels A map, whose key is axis id (starting from 0) and value is corresponding
++     *     labels. Note: The size of labels should be same with the size of the tensor on that axis.
++     * @param tensorBuffer The TensorBuffer to be labeled.
++     * @throws NullPointerException if {@code axisLabels} or {@code tensorBuffer} is null, or any
++     *     value in {@code axisLabels} is null.
++     * @throws IllegalArgumentException if any key in {@code axisLabels} is out of range (compared
++     *         to
++     *     the shape of {@code tensorBuffer}, or any value (labels) has different size with the
++     * {@code tensorBuffer} on the given dimension.
++     */
++    public TensorLabel(
++            @NonNull Map<Integer, List<String>> axisLabels, @NonNull TensorBuffer tensorBuffer) {
++        SupportPreconditions.checkNotNull(axisLabels, "Axis labels cannot be null.");
++        SupportPreconditions.checkNotNull(tensorBuffer, "Tensor Buffer cannot be null.");
++        this.axisLabels = axisLabels;
++        this.tensorBuffer = tensorBuffer;
++        this.shape = tensorBuffer.getShape();
++        for (Map.Entry<Integer, List<String>> entry : axisLabels.entrySet()) {
++            int axis = entry.getKey();
++            SupportPreconditions.checkArgument(
++                    axis >= 0 && axis < shape.length, "Invalid axis id: " + axis);
++            SupportPreconditions.checkNotNull(
++                    entry.getValue(), "Label list is null on axis " + axis);
++            SupportPreconditions.checkArgument(shape[axis] == entry.getValue().size(),
++                    "Label number " + entry.getValue().size() + " mismatch the shape on axis "
++                            + axis);
++        }
+     }
+-  }
+-
+-  /**
+-   * Creates a TensorLabel object which is able to label on one axis of multi-dimensional tensors.
+-   *
+-   * <p>Note: The labels are applied on the first axis whose size is larger than 1. For example, if
+-   * the shape of the tensor is [1, 10, 3], the labels will be applied on axis 1 (id starting from
+-   * 0), and size of {@code axisLabels} should be 10 as well.
+-   *
+-   * @param axisLabels A list of labels, whose size should be same with the size of the tensor on
+-   *     the to-be-labeled axis.
+-   * @param tensorBuffer The TensorBuffer to be labeled.
+-   */
+-  public TensorLabel(@NonNull List<String> axisLabels, @NonNull TensorBuffer tensorBuffer) {
+-    this(makeMap(getFirstAxisWithSizeGreaterThanOne(tensorBuffer), axisLabels), tensorBuffer);
+-  }
+-
+-  /**
+-   * Gets the map with a pair of the label and the corresponding TensorBuffer. Only allow the
+-   * mapping on the first axis with size greater than 1 currently.
+-   */
+-  @NonNull
+-  public Map<String, TensorBuffer> getMapWithTensorBuffer() {
+-    int labeledAxis = getFirstAxisWithSizeGreaterThanOne(tensorBuffer);
+-
+-    Map<String, TensorBuffer> labelToTensorMap = new LinkedHashMap<>();
+-    SupportPreconditions.checkArgument(
+-        axisLabels.containsKey(labeledAxis),
+-        "get a <String, TensorBuffer> map requires the labels are set on the first non-1 axis.");
+-    List<String> labels = axisLabels.get(labeledAxis);
+-
+-    DataType dataType = tensorBuffer.getDataType();
+-    int typeSize = tensorBuffer.getTypeSize();
+-    int flatSize = tensorBuffer.getFlatSize();
+-
+-    // Gets the underlying bytes that could be used to generate the sub-array later.
+-    ByteBuffer byteBuffer = tensorBuffer.getBuffer();
+-    byteBuffer.rewind();
+-
+-    // Note: computation below is only correct when labeledAxis is the first axis with size greater
+-    // than 1.
+-    int subArrayLength = flatSize / shape[labeledAxis] * typeSize;
+-    int i = 0;
+-    SupportPreconditions.checkNotNull(labels, "Label list should never be null");
+-    for (String label : labels) {
+-      // Gets the corresponding TensorBuffer.
+-      byteBuffer.position(i * subArrayLength);
+-      ByteBuffer subBuffer = byteBuffer.slice();
+-      // ByteBuffer.slice doesn't keep order. Modify it to align with the original one.
+-      subBuffer.order(byteBuffer.order()).limit(subArrayLength);
+-      TensorBuffer labelBuffer = TensorBuffer.createDynamic(dataType);
+-      labelBuffer.loadBuffer(subBuffer, Arrays.copyOfRange(shape, labeledAxis + 1, shape.length));
+-      labelToTensorMap.put(label, labelBuffer);
+-      i += 1;
++
++    /**
++     * Creates a TensorLabel object which is able to label on one axis of multi-dimensional tensors.
++     *
++     * <p>Note: The labels are applied on the first axis whose size is larger than 1. For example,
++     * if the shape of the tensor is [1, 10, 3], the labels will be applied on axis 1 (id starting
++     * from 0), and size of {@code axisLabels} should be 10 as well.
++     *
++     * @param axisLabels A list of labels, whose size should be same with the size of the tensor on
++     *     the to-be-labeled axis.
++     * @param tensorBuffer The TensorBuffer to be labeled.
++     */
++    public TensorLabel(@NonNull List<String> axisLabels, @NonNull TensorBuffer tensorBuffer) {
++        this(makeMap(getFirstAxisWithSizeGreaterThanOne(tensorBuffer), axisLabels), tensorBuffer);
+     }
+-    return labelToTensorMap;
+-  }
+-
+-  /**
+-   * Gets a map that maps label to float. Only allow the mapping on the first axis with size greater
+-   * than 1, and the axis should be effectively the last axis (which means every sub tensor
+-   * specified by this axis should have a flat size of 1).
+-   *
+-   * <p>{@link TensorLabel#getCategoryList()} is an alternative API to get the result.
+-   *
+-   * @throws IllegalStateException if size of a sub tensor on each label is not 1.
+-   */
+-  @NonNull
+-  public Map<String, Float> getMapWithFloatValue() {
+-    int labeledAxis = getFirstAxisWithSizeGreaterThanOne(tensorBuffer);
+-    SupportPreconditions.checkState(
+-        labeledAxis == shape.length - 1,
+-        "get a <String, Scalar> map is only valid when the only labeled axis is the last one.");
+-    List<String> labels = axisLabels.get(labeledAxis);
+-    float[] data = tensorBuffer.getFloatArray();
+-    SupportPreconditions.checkState(labels.size() == data.length);
+-    Map<String, Float> result = new LinkedHashMap<>();
+-    int i = 0;
+-    for (String label : labels) {
+-      result.put(label, data[i]);
+-      i += 1;
++
++    /**
++     * Gets the map with a pair of the label and the corresponding TensorBuffer. Only allow the
++     * mapping on the first axis with size greater than 1 currently.
++     */
++    @NonNull
++    public Map<String, TensorBuffer> getMapWithTensorBuffer() {
++        int labeledAxis = getFirstAxisWithSizeGreaterThanOne(tensorBuffer);
++
++        Map<String, TensorBuffer> labelToTensorMap = new LinkedHashMap<>();
++        SupportPreconditions.checkArgument(axisLabels.containsKey(labeledAxis),
++                "get a <String, TensorBuffer> map requires the labels are set on the first non-1 axis.");
++        List<String> labels = axisLabels.get(labeledAxis);
++
++        DataType dataType = tensorBuffer.getDataType();
++        int typeSize = tensorBuffer.getTypeSize();
++        int flatSize = tensorBuffer.getFlatSize();
++
++        // Gets the underlying bytes that could be used to generate the sub-array later.
++        ByteBuffer byteBuffer = tensorBuffer.getBuffer();
++        byteBuffer.rewind();
++
++        // Note: computation below is only correct when labeledAxis is the first axis with size
++        // greater than 1.
++        int subArrayLength = flatSize / shape[labeledAxis] * typeSize;
++        int i = 0;
++        SupportPreconditions.checkNotNull(labels, "Label list should never be null");
++        for (String label : labels) {
++            // Gets the corresponding TensorBuffer.
++            byteBuffer.position(i * subArrayLength);
++            ByteBuffer subBuffer = byteBuffer.slice();
++            // ByteBuffer.slice doesn't keep order. Modify it to align with the original one.
++            subBuffer.order(byteBuffer.order()).limit(subArrayLength);
++            TensorBuffer labelBuffer = TensorBuffer.createDynamic(dataType);
++            labelBuffer.loadBuffer(
++                    subBuffer, Arrays.copyOfRange(shape, labeledAxis + 1, shape.length));
++            labelToTensorMap.put(label, labelBuffer);
++            i += 1;
++        }
++        return labelToTensorMap;
+     }
+-    return result;
+-  }
+-
+-  /**
+-   * Gets a list of {@link Category} from the {@link TensorLabel} object.
+-   *
+-   * <p>The axis of label should be effectively the last axis (which means every sub tensor
+-   * specified by this axis should have a flat size of 1), so that each labelled sub tensor could be
+-   * converted into a float value score. Example: A {@link TensorLabel} with shape {@code {2, 5, 3}}
+-   * and axis 2 is valid. If axis is 1 or 0, it cannot be converted into a {@link Category}.
+-   *
+-   * <p>{@link TensorLabel#getMapWithFloatValue()} is an alternative but returns a {@link Map} as
+-   * the result.
+-   *
+-   * @throws IllegalStateException if size of a sub tensor on each label is not 1.
+-   */
+-  @NonNull
+-  public List<Category> getCategoryList() {
+-    int labeledAxis = getFirstAxisWithSizeGreaterThanOne(tensorBuffer);
+-    SupportPreconditions.checkState(
+-        labeledAxis == shape.length - 1,
+-        "get a Category list is only valid when the only labeled axis is the last one.");
+-    List<String> labels = axisLabels.get(labeledAxis);
+-    float[] data = tensorBuffer.getFloatArray();
+-    SupportPreconditions.checkState(labels.size() == data.length);
+-    List<Category> result = new ArrayList<>();
+-    int i = 0;
+-    for (String label : labels) {
+-      result.add(new Category(label, data[i]));
+-      i += 1;
++
++    /**
++     * Gets a map that maps label to float. Only allow the mapping on the first axis with size
++     * greater than 1, and the axis should be effectively the last axis (which means every sub
++     * tensor specified by this axis should have a flat size of 1).
++     *
++     * <p>{@link TensorLabel#getCategoryList()} is an alternative API to get the result.
++     *
++     * @throws IllegalStateException if size of a sub tensor on each label is not 1.
++     */
++    @NonNull
++    public Map<String, Float> getMapWithFloatValue() {
++        int labeledAxis = getFirstAxisWithSizeGreaterThanOne(tensorBuffer);
++        SupportPreconditions.checkState(labeledAxis == shape.length - 1,
++                "get a <String, Scalar> map is only valid when the only labeled axis is the last one.");
++        List<String> labels = axisLabels.get(labeledAxis);
++        float[] data = tensorBuffer.getFloatArray();
++        SupportPreconditions.checkState(labels.size() == data.length);
++        Map<String, Float> result = new LinkedHashMap<>();
++        int i = 0;
++        for (String label : labels) {
++            result.put(label, data[i]);
++            i += 1;
++        }
++        return result;
+     }
+-    return result;
+-  }
+-
+-  private static int getFirstAxisWithSizeGreaterThanOne(@NonNull TensorBuffer tensorBuffer) {
+-    int[] shape = tensorBuffer.getShape();
+-    for (int i = 0; i < shape.length; i++) {
+-      if (shape[i] > 1) {
+-        return i;
+-      }
++
++    /**
++     * Gets a list of {@link Category} from the {@link TensorLabel} object.
++     *
++     * <p>The axis of label should be effectively the last axis (which means every sub tensor
++     * specified by this axis should have a flat size of 1), so that each labelled sub tensor could
++     * be converted into a float value score. Example: A {@link TensorLabel} with shape {@code {2,
++     * 5, 3}} and axis 2 is valid. If axis is 1 or 0, it cannot be converted into a {@link
++     * Category}.
++     *
++     * <p>{@link TensorLabel#getMapWithFloatValue()} is an alternative but returns a {@link Map} as
++     * the result.
++     *
++     * @throws IllegalStateException if size of a sub tensor on each label is not 1.
++     */
++    @NonNull
++    public List<Category> getCategoryList() {
++        int labeledAxis = getFirstAxisWithSizeGreaterThanOne(tensorBuffer);
++        SupportPreconditions.checkState(labeledAxis == shape.length - 1,
++                "get a Category list is only valid when the only labeled axis is the last one.");
++        List<String> labels = axisLabels.get(labeledAxis);
++        float[] data = tensorBuffer.getFloatArray();
++        SupportPreconditions.checkState(labels.size() == data.length);
++        List<Category> result = new ArrayList<>();
++        int i = 0;
++        for (String label : labels) {
++            result.add(new Category(label, data[i]));
++            i += 1;
++        }
++        return result;
++    }
++
++    private static int getFirstAxisWithSizeGreaterThanOne(@NonNull TensorBuffer tensorBuffer) {
++        int[] shape = tensorBuffer.getShape();
++        for (int i = 0; i < shape.length; i++) {
++            if (shape[i] > 1) {
++                return i;
++            }
++        }
++        throw new IllegalArgumentException(
++                "Cannot find an axis to label. A valid axis to label should have size larger than 1.");
++    }
++
++    // Helper function to wrap the List<String> to a one-entry map.
++    private static Map<Integer, List<String>> makeMap(int axis, List<String> labels) {
++        Map<Integer, List<String>> map = new LinkedHashMap<>();
++        map.put(axis, labels);
++        return map;
+     }
+-    throw new IllegalArgumentException(
+-        "Cannot find an axis to label. A valid axis to label should have size larger than 1.");
+-  }
+-
+-  // Helper function to wrap the List<String> to a one-entry map.
+-  private static Map<Integer, List<String>> makeMap(int axis, List<String> labels) {
+-    Map<Integer, List<String>> map = new LinkedHashMap<>();
+-    map.put(axis, labels);
+-    return map;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java
+index ed47f65a726a6..e44edc64f4969 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java
+@@ -16,16 +16,18 @@ limitations under the License.
+ package org.tensorflow.lite.support.label.ops;
+ 
+ import android.content.Context;
+-import java.io.IOException;
+-import java.util.HashMap;
+-import java.util.List;
+-import java.util.Map;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.support.common.FileUtil;
+ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ import org.tensorflow.lite.support.label.TensorLabel;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.io.IOException;
++import java.util.HashMap;
++import java.util.List;
++import java.util.Map;
++
+ /**
+  * Labels TensorBuffer with axisLabels for outputs.
+  *
+@@ -33,42 +35,42 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  * a pair of the label name and the corresponding TensorBuffer value.
+  */
+ public class LabelAxisOp {
+-  // Axis and its corresponding label names.
+-  private final Map<Integer, List<String>> axisLabels;
+-
+-  protected LabelAxisOp(Builder builder) {
+-    axisLabels = builder.axisLabels;
+-  }
+-
+-  public TensorLabel apply(@NonNull TensorBuffer buffer) {
+-    SupportPreconditions.checkNotNull(buffer, "Tensor buffer cannot be null.");
+-    return new TensorLabel(axisLabels, buffer);
+-  }
+-
+-  /** The inner builder class to build a LabelTensor Operator. */
+-  public static class Builder {
++    // Axis and its corresponding label names.
+     private final Map<Integer, List<String>> axisLabels;
+ 
+-    protected Builder() {
+-      axisLabels = new HashMap<>();
++    protected LabelAxisOp(Builder builder) {
++        axisLabels = builder.axisLabels;
+     }
+ 
+-    public Builder addAxisLabel(@NonNull Context context, int axis, @NonNull String filePath)
+-        throws IOException {
+-      SupportPreconditions.checkNotNull(context, "Context cannot be null.");
+-      SupportPreconditions.checkNotNull(filePath, "File path cannot be null.");
+-      List<String> labels = FileUtil.loadLabels(context, filePath);
+-      axisLabels.put(axis, labels);
+-      return this;
++    public TensorLabel apply(@NonNull TensorBuffer buffer) {
++        SupportPreconditions.checkNotNull(buffer, "Tensor buffer cannot be null.");
++        return new TensorLabel(axisLabels, buffer);
+     }
+ 
+-    public Builder addAxisLabel(int axis, @NonNull List<String> labels) {
+-      axisLabels.put(axis, labels);
+-      return this;
+-    }
++    /** The inner builder class to build a LabelTensor Operator. */
++    public static class Builder {
++        private final Map<Integer, List<String>> axisLabels;
++
++        protected Builder() {
++            axisLabels = new HashMap<>();
++        }
++
++        public Builder addAxisLabel(@NonNull Context context, int axis, @NonNull String filePath)
++                throws IOException {
++            SupportPreconditions.checkNotNull(context, "Context cannot be null.");
++            SupportPreconditions.checkNotNull(filePath, "File path cannot be null.");
++            List<String> labels = FileUtil.loadLabels(context, filePath);
++            axisLabels.put(axis, labels);
++            return this;
++        }
++
++        public Builder addAxisLabel(int axis, @NonNull List<String> labels) {
++            axisLabels.put(axis, labels);
++            return this;
++        }
+ 
+-    public LabelAxisOp build() {
+-      return new LabelAxisOp(this);
++        public LabelAxisOp build() {
++            return new LabelAxisOp(this);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/GpuDelegateProxy.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/GpuDelegateProxy.java
+index 9cfcf923dedee..ada9b33fb0eea 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/GpuDelegateProxy.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/GpuDelegateProxy.java
+@@ -16,54 +16,55 @@ limitations under the License.
+ package org.tensorflow.lite.support.model;
+ 
+ import android.util.Log;
+-import java.io.Closeable;
+-import java.io.IOException;
++
+ import org.checkerframework.checker.nullness.qual.Nullable;
+ import org.tensorflow.lite.Delegate;
+ 
++import java.io.Closeable;
++import java.io.IOException;
++
+ /**
+  * Helper class to create and call necessary methods of {@code GpuDelegate} which is not a strict
+  * dependency.
+  */
+ class GpuDelegateProxy implements Delegate, Closeable {
++    private static final String TAG = "GpuDelegateProxy";
+ 
+-  private static final String TAG = "GpuDelegateProxy";
+-
+-  private final Delegate proxiedDelegate;
+-  private final Closeable proxiedCloseable;
++    private final Delegate proxiedDelegate;
++    private final Closeable proxiedCloseable;
+ 
+-  @Nullable
+-  public static GpuDelegateProxy maybeNewInstance() {
+-    try {
+-      Class<?> clazz = Class.forName("org.tensorflow.lite.gpu.GpuDelegate");
+-      Object instance = clazz.getDeclaredConstructor().newInstance();
+-      return new GpuDelegateProxy(instance);
+-    } catch (ReflectiveOperationException e) {
+-      Log.e(TAG, "Failed to create the GpuDelegate dynamically.", e);
+-      return null;
++    @Nullable
++    public static GpuDelegateProxy maybeNewInstance() {
++        try {
++            Class<?> clazz = Class.forName("org.tensorflow.lite.gpu.GpuDelegate");
++            Object instance = clazz.getDeclaredConstructor().newInstance();
++            return new GpuDelegateProxy(instance);
++        } catch (ReflectiveOperationException e) {
++            Log.e(TAG, "Failed to create the GpuDelegate dynamically.", e);
++            return null;
++        }
+     }
+-  }
+ 
+-  /** Calls {@code close()} method of the delegate. */
+-  @Override
+-  public void close() {
+-    try {
+-      proxiedCloseable.close();
+-    } catch (IOException e) {
+-      // Should not trigger, because GpuDelegate#close never throws. The catch is required because
+-      // of Closeable#close.
+-      Log.e(TAG, "Failed to close the GpuDelegate.", e);
++    /** Calls {@code close()} method of the delegate. */
++    @Override
++    public void close() {
++        try {
++            proxiedCloseable.close();
++        } catch (IOException e) {
++            // Should not trigger, because GpuDelegate#close never throws. The catch is required
++            // because of Closeable#close.
++            Log.e(TAG, "Failed to close the GpuDelegate.", e);
++        }
+     }
+-  }
+ 
+-  /** Calls {@code getNativeHandle()} method of the delegate. */
+-  @Override
+-  public long getNativeHandle() {
+-    return proxiedDelegate.getNativeHandle();
+-  }
++    /** Calls {@code getNativeHandle()} method of the delegate. */
++    @Override
++    public long getNativeHandle() {
++        return proxiedDelegate.getNativeHandle();
++    }
+ 
+-  private GpuDelegateProxy(Object instance) {
+-    this.proxiedCloseable = (Closeable) instance;
+-    this.proxiedDelegate = (Delegate) instance;
+-  }
++    private GpuDelegateProxy(Object instance) {
++        this.proxiedCloseable = (Closeable) instance;
++        this.proxiedDelegate = (Delegate) instance;
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java
+index 1c37c1b3d800d..af2061e948970 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java
+@@ -16,9 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.model;
+ 
+ import android.content.Context;
+-import java.io.IOException;
+-import java.nio.MappedByteBuffer;
+-import java.util.Map;
++
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.checkerframework.checker.nullness.qual.Nullable;
+ import org.tensorflow.lite.InterpreterApi;
+@@ -27,6 +25,10 @@ import org.tensorflow.lite.Tensor;
+ import org.tensorflow.lite.support.common.FileUtil;
+ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ 
++import java.io.IOException;
++import java.nio.MappedByteBuffer;
++import java.util.Map;
++
+ /**
+  * The wrapper class for a TFLite model and a TFLite interpreter.
+  *
+@@ -34,253 +36,244 @@ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+  * interpreter instance to run it.
+  */
+ public class Model {
++    /** The runtime device type used for executing classification. */
++    public enum Device { CPU, NNAPI, GPU }
+ 
+-  /** The runtime device type used for executing classification. */
+-  public enum Device {
+-    CPU,
+-    NNAPI,
+-    GPU
+-  }
+-
+-  /**
+-   * Options for running the model. Configurable parameters includes:
+-   *
+-   * <ul>
+-   *   <li>{@code device} {@link Builder#setDevice(Device)} specifies the hardware to run the model.
+-   *       The default value is {@link Device#CPU}.
+-   *   <li>{@code numThreads} {@link Builder#setNumThreads(int)} specifies the number of threads
+-   *       used by TFLite inference. It's only effective when device is set to {@link Device#CPU}
+-   *       and default value is 1.
+-   * </ul>
+-   */
+-  public static class Options {
+-    private final Device device;
+-    private final int numThreads;
+-
+-    /** Builder of {@link Options}. See its doc for details. */
+-    public static class Builder {
+-      private Device device = Device.CPU;
+-      private int numThreads = 1;
+-
+-      public Builder setDevice(Device device) {
+-        this.device = device;
+-        return this;
+-      }
+-
+-      public Builder setNumThreads(int numThreads) {
+-        this.numThreads = numThreads;
+-        return this;
+-      }
+-
+-      public Options build() {
+-        return new Options(this);
+-      }
++    /**
++     * Options for running the model. Configurable parameters includes:
++     *
++     * <ul>
++     *   <li>{@code device} {@link Builder#setDevice(Device)} specifies the hardware to run the
++     * model. The default value is {@link Device#CPU}. <li>{@code numThreads} {@link
++     * Builder#setNumThreads(int)} specifies the number of threads used by TFLite inference. It's
++     * only effective when device is set to {@link Device#CPU} and default value is 1.
++     * </ul>
++     */
++    public static class Options {
++        private final Device device;
++        private final int numThreads;
++
++        /** Builder of {@link Options}. See its doc for details. */
++        public static class Builder {
++            private Device device = Device.CPU;
++            private int numThreads = 1;
++
++            public Builder setDevice(Device device) {
++                this.device = device;
++                return this;
++            }
++
++            public Builder setNumThreads(int numThreads) {
++                this.numThreads = numThreads;
++                return this;
++            }
++
++            public Options build() {
++                return new Options(this);
++            }
++        }
++
++        private Options(Builder builder) {
++            device = builder.device;
++            numThreads = builder.numThreads;
++        }
+     }
+ 
+-    private Options(Builder builder) {
+-      device = builder.device;
+-      numThreads = builder.numThreads;
+-    }
+-  }
++    /** An instance of the driver class to run model inference with Tensorflow Lite. */
++    private final InterpreterApi interpreter;
+ 
+-  /** An instance of the driver class to run model inference with Tensorflow Lite. */
+-  private final InterpreterApi interpreter;
++    /** Path to tflite model file in asset folder. */
++    private final String modelPath;
+ 
+-  /** Path to tflite model file in asset folder. */
+-  private final String modelPath;
++    /** The memory-mapped model data. */
++    private final MappedByteBuffer byteModel;
+ 
+-  /** The memory-mapped model data. */
+-  private final MappedByteBuffer byteModel;
++    private final GpuDelegateProxy gpuDelegateProxy;
+ 
+-  private final GpuDelegateProxy gpuDelegateProxy;
++    /**
++     * Builder for {@link Model}.
++     *
++     * @deprecated Please use {@link Model#createModel(Context, String, Options)}.
++     */
++    @Deprecated
++    public static class Builder {
++        private Device device = Device.CPU;
++        private int numThreads = 1;
++        private final String modelPath;
++        private final MappedByteBuffer byteModel;
++
++        /**
++         * Creates a builder which loads tflite model from asset folder using memory-mapped files.
++         *
++         * @param context Application context to access assets.
++         * @param modelPath Asset path of the model (.tflite file).
++         * @throws IOException if an I/O error occurs when loading the tflite model.
++         */
++        @NonNull
++        public Builder(@NonNull Context context, @NonNull String modelPath) throws IOException {
++            this.modelPath = modelPath;
++            byteModel = FileUtil.loadMappedFile(context, modelPath);
++        }
++
++        /** Sets running device. By default, TFLite will run on CPU. */
++        @NonNull
++        public Builder setDevice(Device device) {
++            this.device = device;
++            return this;
++        }
++
++        /** Sets number of threads. By default it's 1. */
++        @NonNull
++        public Builder setNumThreads(int numThreads) {
++            this.numThreads = numThreads;
++            return this;
++        }
++
++        // Note: The implementation is copied from `Model#createModel`. As the builder is going to
++        // be deprecated, this function is also to be removed.
++        @NonNull
++        public Model build() {
++            Options options =
++                    new Options.Builder().setNumThreads(numThreads).setDevice(device).build();
++            return createModel(byteModel, modelPath, options);
++        }
++    }
+ 
+-  /**
+-   * Builder for {@link Model}.
+-   *
+-   * @deprecated Please use {@link Model#createModel(Context, String, Options)}.
+-   */
+-  @Deprecated
+-  public static class Builder {
+-    private Device device = Device.CPU;
+-    private int numThreads = 1;
+-    private final String modelPath;
+-    private final MappedByteBuffer byteModel;
++    /**
++     * Loads a model from assets and initialize TFLite interpreter.
++     *
++     * <p>The default options are: (1) CPU device; (2) one thread.
++     *
++     * @param context The App Context.
++     * @param modelPath The path of the model file.
++     * @throws IOException if any exception occurs when open the model file.
++     */
++    public static Model createModel(@NonNull Context context, @NonNull String modelPath)
++            throws IOException {
++        return createModel(context, modelPath, new Options.Builder().build());
++    }
+ 
+     /**
+-     * Creates a builder which loads tflite model from asset folder using memory-mapped files.
++     * Loads a model from assets and initialize TFLite interpreter with given options.
+      *
+-     * @param context Application context to access assets.
+-     * @param modelPath Asset path of the model (.tflite file).
+-     * @throws IOException if an I/O error occurs when loading the tflite model.
++     * @see Options for details.
++     * @param context The App Context.
++     * @param modelPath The path of the model file.
++     * @param options The options for running the model.
++     * @throws IOException if any exception occurs when open the model file.
+      */
+-    @NonNull
+-    public Builder(@NonNull Context context, @NonNull String modelPath) throws IOException {
+-      this.modelPath = modelPath;
+-      byteModel = FileUtil.loadMappedFile(context, modelPath);
++    public static Model createModel(@NonNull Context context, @NonNull String modelPath,
++            @NonNull Options options) throws IOException {
++        SupportPreconditions.checkNotEmpty(
++                modelPath, "Model path in the asset folder cannot be empty.");
++        MappedByteBuffer byteModel = FileUtil.loadMappedFile(context, modelPath);
++        return createModel(byteModel, modelPath, options);
+     }
+ 
+-    /** Sets running device. By default, TFLite will run on CPU. */
+-    @NonNull
+-    public Builder setDevice(Device device) {
+-      this.device = device;
+-      return this;
++    /**
++     * Creates a model with loaded {@link MappedByteBuffer}.
++     *
++     * @see Options for details.
++     * @param byteModel The loaded TFLite model.
++     * @param modelPath The original path of the model. It can be fetched later by {@link
++     *     Model#getPath()}.
++     * @param options The options for running the model.
++     * @throws IllegalArgumentException if {@code options.device} is {@link Device#GPU} but
++     *     "tensorflow-lite-gpu" is not linked to the project.
++     */
++    public static Model createModel(@NonNull MappedByteBuffer byteModel, @NonNull String modelPath,
++            @NonNull Options options) {
++        InterpreterApi.Options interpreterOptions = new InterpreterApi.Options();
++        GpuDelegateProxy gpuDelegateProxy = null;
++        switch (options.device) {
++            case NNAPI:
++                interpreterOptions.setUseNNAPI(true);
++                break;
++            case GPU:
++                gpuDelegateProxy = GpuDelegateProxy.maybeNewInstance();
++                SupportPreconditions.checkArgument(gpuDelegateProxy != null,
++                        "Cannot inference with GPU. Did you add \"tensorflow-lite-gpu\" as dependency?");
++                interpreterOptions.addDelegate(gpuDelegateProxy);
++                break;
++            case CPU:
++                break;
++        }
++        interpreterOptions.setNumThreads(options.numThreads);
++        InterpreterApi interpreter = new InterpreterFactory().create(byteModel, interpreterOptions);
++        return new Model(modelPath, byteModel, interpreter, gpuDelegateProxy);
+     }
+ 
+-    /** Sets number of threads. By default it's 1. */
++    /** Returns the memory-mapped model data. */
+     @NonNull
+-    public Builder setNumThreads(int numThreads) {
+-      this.numThreads = numThreads;
+-      return this;
++    public MappedByteBuffer getData() {
++        return byteModel;
+     }
+ 
+-    // Note: The implementation is copied from `Model#createModel`. As the builder is going to be
+-    // deprecated, this function is also to be removed.
++    /** Returns the path of the model file stored in Assets. */
+     @NonNull
+-    public Model build() {
+-      Options options = new Options.Builder().setNumThreads(numThreads).setDevice(device).build();
+-      return createModel(byteModel, modelPath, options);
++    public String getPath() {
++        return modelPath;
++    }
++
++    /**
++     * Gets the Tensor associated with the provided input index.
++     *
++     * @throws IllegalStateException if the interpreter is closed.
++     */
++    public Tensor getInputTensor(int inputIndex) {
++        return interpreter.getInputTensor(inputIndex);
++    }
++
++    /**
++     * Gets the Tensor associated with the provided output index.
++     *
++     * @throws IllegalStateException if the interpreter is closed.
++     */
++    public Tensor getOutputTensor(int outputIndex) {
++        return interpreter.getOutputTensor(outputIndex);
+     }
+-  }
+-
+-  /**
+-   * Loads a model from assets and initialize TFLite interpreter.
+-   *
+-   * <p>The default options are: (1) CPU device; (2) one thread.
+-   *
+-   * @param context The App Context.
+-   * @param modelPath The path of the model file.
+-   * @throws IOException if any exception occurs when open the model file.
+-   */
+-  public static Model createModel(@NonNull Context context, @NonNull String modelPath)
+-      throws IOException {
+-    return createModel(context, modelPath, new Options.Builder().build());
+-  }
+-
+-  /**
+-   * Loads a model from assets and initialize TFLite interpreter with given options.
+-   *
+-   * @see Options for details.
+-   * @param context The App Context.
+-   * @param modelPath The path of the model file.
+-   * @param options The options for running the model.
+-   * @throws IOException if any exception occurs when open the model file.
+-   */
+-  public static Model createModel(
+-      @NonNull Context context, @NonNull String modelPath, @NonNull Options options)
+-      throws IOException {
+-    SupportPreconditions.checkNotEmpty(
+-        modelPath, "Model path in the asset folder cannot be empty.");
+-    MappedByteBuffer byteModel = FileUtil.loadMappedFile(context, modelPath);
+-    return createModel(byteModel, modelPath, options);
+-  }
+-
+-  /**
+-   * Creates a model with loaded {@link MappedByteBuffer}.
+-   *
+-   * @see Options for details.
+-   * @param byteModel The loaded TFLite model.
+-   * @param modelPath The original path of the model. It can be fetched later by {@link
+-   *     Model#getPath()}.
+-   * @param options The options for running the model.
+-   * @throws IllegalArgumentException if {@code options.device} is {@link Device#GPU} but
+-   *     "tensorflow-lite-gpu" is not linked to the project.
+-   */
+-  public static Model createModel(
+-      @NonNull MappedByteBuffer byteModel, @NonNull String modelPath, @NonNull Options options) {
+-    InterpreterApi.Options interpreterOptions = new InterpreterApi.Options();
+-    GpuDelegateProxy gpuDelegateProxy = null;
+-    switch (options.device) {
+-      case NNAPI:
+-        interpreterOptions.setUseNNAPI(true);
+-        break;
+-      case GPU:
+-        gpuDelegateProxy = GpuDelegateProxy.maybeNewInstance();
+-        SupportPreconditions.checkArgument(
+-            gpuDelegateProxy != null,
+-            "Cannot inference with GPU. Did you add \"tensorflow-lite-gpu\" as dependency?");
+-        interpreterOptions.addDelegate(gpuDelegateProxy);
+-        break;
+-      case CPU:
+-        break;
++
++    /**
++     * Returns the output shape. Useful if output shape is only determined when graph is created.
++     *
++     * @throws IllegalStateException if the interpreter is closed.
++     */
++    public int[] getOutputTensorShape(int outputIndex) {
++        return interpreter.getOutputTensor(outputIndex).shape();
+     }
+-    interpreterOptions.setNumThreads(options.numThreads);
+-    InterpreterApi interpreter = new InterpreterFactory().create(byteModel, interpreterOptions);
+-    return new Model(modelPath, byteModel, interpreter, gpuDelegateProxy);
+-  }
+-
+-  /** Returns the memory-mapped model data. */
+-  @NonNull
+-  public MappedByteBuffer getData() {
+-    return byteModel;
+-  }
+-
+-  /** Returns the path of the model file stored in Assets. */
+-  @NonNull
+-  public String getPath() {
+-    return modelPath;
+-  }
+-
+-  /**
+-   * Gets the Tensor associated with the provided input index.
+-   *
+-   * @throws IllegalStateException if the interpreter is closed.
+-   */
+-  public Tensor getInputTensor(int inputIndex) {
+-    return interpreter.getInputTensor(inputIndex);
+-  }
+-
+-  /**
+-   * Gets the Tensor associated with the provided output index.
+-   *
+-   * @throws IllegalStateException if the interpreter is closed.
+-   */
+-  public Tensor getOutputTensor(int outputIndex) {
+-    return interpreter.getOutputTensor(outputIndex);
+-  }
+-
+-  /**
+-   * Returns the output shape. Useful if output shape is only determined when graph is created.
+-   *
+-   * @throws IllegalStateException if the interpreter is closed.
+-   */
+-  public int[] getOutputTensorShape(int outputIndex) {
+-    return interpreter.getOutputTensor(outputIndex).shape();
+-  }
+-
+-  /**
+-   * Runs model inference on multiple inputs, and returns multiple outputs.
+-   *
+-   * @param inputs an array of input data. The inputs should be in the same order as inputs of the
+-   *     model. Each input can be an array or multidimensional array, or a {@link
+-   *     java.nio.ByteBuffer} of primitive types including int, float, long, and byte. {@link
+-   *     java.nio.ByteBuffer} is the preferred way to pass large input data, whereas string types
+-   *     require using the (multi-dimensional) array input path. When {@link java.nio.ByteBuffer} is
+-   *     used, its content should remain unchanged until model inference is done.
+-   * @param outputs a map mapping output indices to multidimensional arrays of output data or {@link
+-   *     java.nio.ByteBuffer}s of primitive types including int, float, long, and byte. It only
+-   *     needs to keep entries for the outputs to be used.
+-   */
+-  public void run(@NonNull Object[] inputs, @NonNull Map<Integer, Object> outputs) {
+-    interpreter.runForMultipleInputsOutputs(inputs, outputs);
+-  }
+-
+-  public void close() {
+-    if (interpreter != null) {
+-      interpreter.close();
++
++    /**
++     * Runs model inference on multiple inputs, and returns multiple outputs.
++     *
++     * @param inputs an array of input data. The inputs should be in the same order as inputs of the
++     *     model. Each input can be an array or multidimensional array, or a {@link
++     *     java.nio.ByteBuffer} of primitive types including int, float, long, and byte. {@link
++     *     java.nio.ByteBuffer} is the preferred way to pass large input data, whereas string types
++     *     require using the (multi-dimensional) array input path. When {@link java.nio.ByteBuffer}
++     * is used, its content should remain unchanged until model inference is done.
++     * @param outputs a map mapping output indices to multidimensional arrays of output data or
++     *         {@link
++     *     java.nio.ByteBuffer}s of primitive types including int, float, long, and byte. It only
++     *     needs to keep entries for the outputs to be used.
++     */
++    public void run(@NonNull Object[] inputs, @NonNull Map<Integer, Object> outputs) {
++        interpreter.runForMultipleInputsOutputs(inputs, outputs);
+     }
+-    if (gpuDelegateProxy != null) {
+-      gpuDelegateProxy.close();
++
++    public void close() {
++        if (interpreter != null) {
++            interpreter.close();
++        }
++        if (gpuDelegateProxy != null) {
++            gpuDelegateProxy.close();
++        }
++    }
++
++    private Model(@NonNull String modelPath, @NonNull MappedByteBuffer byteModel,
++            @NonNull InterpreterApi interpreter, @Nullable GpuDelegateProxy gpuDelegateProxy) {
++        this.modelPath = modelPath;
++        this.byteModel = byteModel;
++        this.interpreter = interpreter;
++        this.gpuDelegateProxy = gpuDelegateProxy;
+     }
+-  }
+-
+-  private Model(
+-      @NonNull String modelPath,
+-      @NonNull MappedByteBuffer byteModel,
+-      @NonNull InterpreterApi interpreter,
+-      @Nullable GpuDelegateProxy gpuDelegateProxy) {
+-    this.modelPath = modelPath;
+-    this.byteModel = byteModel;
+-    this.interpreter = interpreter;
+-    this.gpuDelegateProxy = gpuDelegateProxy;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java
+index 9e0204bdc2e71..ec6c800ef557a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java
+@@ -19,473 +19,476 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkNotNull;
+ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkState;
+ 
++import org.checkerframework.checker.nullness.qual.NonNull;
++import org.tensorflow.lite.DataType;
++
+ import java.nio.ByteBuffer;
+ import java.nio.ByteOrder;
+ import java.util.Arrays;
+-import org.checkerframework.checker.nullness.qual.NonNull;
+-import org.tensorflow.lite.DataType;
+ 
+ /** Represents the data buffer for either a model's input or its output. */
+ public abstract class TensorBuffer {
+-  /** Where the data is stored. */
+-  protected ByteBuffer buffer;
+-
+-  /** Shape of the tensor stored in this buffer. */
+-  protected int[] shape;
+-
+-  /** Number of elements in the buffer. It will be changed to a proper value in the constructor. */
+-  protected int flatSize = -1;
+-
+-  /**
+-   * Indicator of whether this buffer is dynamic or fixed-size. Fixed-size buffers will have
+-   * pre-allocated memory and fixed size. While the size of dynamic buffers can be changed.
+-   */
+-  protected final boolean isDynamic;
+-
+-  /**
+-   * Creates a {@link TensorBuffer} with specified {@code shape} and {@link DataType}. Here are some
+-   * examples:
+-   *
+-   * <pre>
+-   * // Creating a float TensorBuffer with shape {2, 3}:
+-   * int[] shape = new int[] {2, 3};
+-   * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-   * </pre>
+-   *
+-   * <pre>
+-   * // Creating an uint8 TensorBuffer of a scalar:
+-   * int[] shape = new int[] {};
+-   * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-   * </pre>
+-   *
+-   * <pre>
+-   * // Creating an empty uint8 TensorBuffer:
+-   * int[] shape = new int[] {0};
+-   * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-   * </pre>
+-   *
+-   * <p>The size of a fixed-size TensorBuffer cannot be changed once it is created.
+-   *
+-   * @param shape The shape of the {@link TensorBuffer} to be created.
+-   * @param dataType The dataType of the {@link TensorBuffer} to be created.
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if {@code shape} has non-positive elements.
+-   */
+-  @NonNull
+-  public static TensorBuffer createFixedSize(@NonNull int[] shape, DataType dataType) {
+-    switch (dataType) {
+-      case FLOAT32:
+-        return new TensorBufferFloat(shape);
+-      case UINT8:
+-        return new TensorBufferUint8(shape);
+-      default:
+-        throw new AssertionError("TensorBuffer does not support data type: " + dataType);
++    /** Where the data is stored. */
++    protected ByteBuffer buffer;
++
++    /** Shape of the tensor stored in this buffer. */
++    protected int[] shape;
++
++    /**
++     * Number of elements in the buffer. It will be changed to a proper value in the constructor.
++     */
++    protected int flatSize = -1;
++
++    /**
++     * Indicator of whether this buffer is dynamic or fixed-size. Fixed-size buffers will have
++     * pre-allocated memory and fixed size. While the size of dynamic buffers can be changed.
++     */
++    protected final boolean isDynamic;
++
++    /**
++     * Creates a {@link TensorBuffer} with specified {@code shape} and {@link DataType}. Here are
++     * some examples:
++     *
++     * <pre>
++     * // Creating a float TensorBuffer with shape {2, 3}:
++     * int[] shape = new int[] {2, 3};
++     * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++     * </pre>
++     *
++     * <pre>
++     * // Creating an uint8 TensorBuffer of a scalar:
++     * int[] shape = new int[] {};
++     * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++     * </pre>
++     *
++     * <pre>
++     * // Creating an empty uint8 TensorBuffer:
++     * int[] shape = new int[] {0};
++     * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++     * </pre>
++     *
++     * <p>The size of a fixed-size TensorBuffer cannot be changed once it is created.
++     *
++     * @param shape The shape of the {@link TensorBuffer} to be created.
++     * @param dataType The dataType of the {@link TensorBuffer} to be created.
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if {@code shape} has non-positive elements.
++     */
++    @NonNull
++    public static TensorBuffer createFixedSize(@NonNull int[] shape, DataType dataType) {
++        switch (dataType) {
++            case FLOAT32:
++                return new TensorBufferFloat(shape);
++            case UINT8:
++                return new TensorBufferUint8(shape);
++            default:
++                throw new AssertionError("TensorBuffer does not support data type: " + dataType);
++        }
++    }
++
++    /**
++     * Creates an empty dynamic {@link TensorBuffer} with specified {@link DataType}. The shape of
++     * the created {@link TensorBuffer} is {0}.
++     *
++     * <p>Dynamic TensorBuffers will reallocate memory when loading arrays or data buffers of
++     * different buffer sizes. Here are some examples:
++     *
++     * <pre>
++     * // Creating a float dynamic TensorBuffer:
++     * TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++     * // Loading a float array:
++     * float[] arr1 = new float[] {1, 2, 3};
++     * tensorBuffer.loadArray(arr, new int[] {arr1.length});
++     * // loading another float array:
++     * float[] arr2 = new float[] {1, 2, 3, 4, 5};
++     * tensorBuffer.loadArray(arr, new int[] {arr2.length});
++     * // loading a third float array with the same size as arr2, assuming shape doesn't change:
++     * float[] arr3 = new float[] {5, 4, 3, 2, 1};
++     * tensorBuffer.loadArray(arr);
++     * // loading a forth float array with different size as arr3 and omitting the shape will result
++     * // in error:
++     * float[] arr4 = new float[] {3, 2, 1};
++     * tensorBuffer.loadArray(arr); // Error: The size of byte buffer and the shape do not match.
++     * </pre>
++     *
++     * @param dataType The dataType of the {@link TensorBuffer} to be created.
++     */
++    @NonNull
++    public static TensorBuffer createDynamic(DataType dataType) {
++        switch (dataType) {
++            case FLOAT32:
++                return new TensorBufferFloat();
++            case UINT8:
++                return new TensorBufferUint8();
++            default:
++                throw new AssertionError("TensorBuffer does not support data type: " + dataType);
++        }
+     }
+-  }
+-
+-  /**
+-   * Creates an empty dynamic {@link TensorBuffer} with specified {@link DataType}. The shape of the
+-   * created {@link TensorBuffer} is {0}.
+-   *
+-   * <p>Dynamic TensorBuffers will reallocate memory when loading arrays or data buffers of
+-   * different buffer sizes. Here are some examples:
+-   *
+-   * <pre>
+-   * // Creating a float dynamic TensorBuffer:
+-   * TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-   * // Loading a float array:
+-   * float[] arr1 = new float[] {1, 2, 3};
+-   * tensorBuffer.loadArray(arr, new int[] {arr1.length});
+-   * // loading another float array:
+-   * float[] arr2 = new float[] {1, 2, 3, 4, 5};
+-   * tensorBuffer.loadArray(arr, new int[] {arr2.length});
+-   * // loading a third float array with the same size as arr2, assuming shape doesn't change:
+-   * float[] arr3 = new float[] {5, 4, 3, 2, 1};
+-   * tensorBuffer.loadArray(arr);
+-   * // loading a forth float array with different size as arr3 and omitting the shape will result
+-   * // in error:
+-   * float[] arr4 = new float[] {3, 2, 1};
+-   * tensorBuffer.loadArray(arr); // Error: The size of byte buffer and the shape do not match.
+-   * </pre>
+-   *
+-   * @param dataType The dataType of the {@link TensorBuffer} to be created.
+-   */
+-  @NonNull
+-  public static TensorBuffer createDynamic(DataType dataType) {
+-    switch (dataType) {
+-      case FLOAT32:
+-        return new TensorBufferFloat();
+-      case UINT8:
+-        return new TensorBufferUint8();
+-      default:
+-        throw new AssertionError("TensorBuffer does not support data type: " + dataType);
++
++    /**
++     * Creates a {@link TensorBuffer} deep-copying data from another, with specified {@link
++     * DataType}.
++     *
++     * @param buffer the source {@link TensorBuffer} to copy from.
++     * @param dataType the expected {@link DataType} of newly created {@link TensorBuffer}.
++     * @throws NullPointerException if {@code buffer} is null.
++     */
++    @NonNull
++    public static TensorBuffer createFrom(@NonNull TensorBuffer buffer, DataType dataType) {
++        checkNotNull(buffer, "Cannot create a buffer from null");
++        TensorBuffer result;
++        if (buffer.isDynamic()) {
++            result = createDynamic(dataType);
++        } else {
++            result = createFixedSize(buffer.shape, dataType);
++        }
++        // The only scenario we need float array is FLOAT32->FLOAT32, or we can always use INT as
++        // intermediate container.
++        // The assumption is not true when we support other data types.
++        if (buffer.getDataType() == DataType.FLOAT32 && dataType == DataType.FLOAT32) {
++            float[] data = buffer.getFloatArray();
++            result.loadArray(data, buffer.shape);
++        } else {
++            int[] data = buffer.getIntArray();
++            result.loadArray(data, buffer.shape);
++        }
++        return result;
+     }
+-  }
+-
+-  /**
+-   * Creates a {@link TensorBuffer} deep-copying data from another, with specified {@link DataType}.
+-   *
+-   * @param buffer the source {@link TensorBuffer} to copy from.
+-   * @param dataType the expected {@link DataType} of newly created {@link TensorBuffer}.
+-   * @throws NullPointerException if {@code buffer} is null.
+-   */
+-  @NonNull
+-  public static TensorBuffer createFrom(@NonNull TensorBuffer buffer, DataType dataType) {
+-    checkNotNull(buffer, "Cannot create a buffer from null");
+-    TensorBuffer result;
+-    if (buffer.isDynamic()) {
+-      result = createDynamic(dataType);
+-    } else {
+-      result = createFixedSize(buffer.shape, dataType);
++
++    /** Returns the data buffer. */
++    @NonNull
++    public ByteBuffer getBuffer() {
++        return buffer;
+     }
+-    // The only scenario we need float array is FLOAT32->FLOAT32, or we can always use INT as
+-    // intermediate container.
+-    // The assumption is not true when we support other data types.
+-    if (buffer.getDataType() == DataType.FLOAT32 && dataType == DataType.FLOAT32) {
+-      float[] data = buffer.getFloatArray();
+-      result.loadArray(data, buffer.shape);
+-    } else {
+-      int[] data = buffer.getIntArray();
+-      result.loadArray(data, buffer.shape);
++
++    /**
++     * Gets the flatSize of the buffer.
++     *
++     * @throws IllegalStateException if the underlying data is corrupted
++     */
++    public int getFlatSize() {
++        assertShapeIsCorrect();
++        return flatSize;
+     }
+-    return result;
+-  }
+-
+-  /** Returns the data buffer. */
+-  @NonNull
+-  public ByteBuffer getBuffer() {
+-    return buffer;
+-  }
+-
+-  /**
+-   * Gets the flatSize of the buffer.
+-   *
+-   * @throws IllegalStateException if the underlying data is corrupted
+-   */
+-  public int getFlatSize() {
+-    assertShapeIsCorrect();
+-    return flatSize;
+-  }
+-
+-  /**
+-   * Gets the current shape. (returning a copy here to avoid unexpected modification.)
+-   *
+-   * @throws IllegalStateException if the underlying data is corrupted
+-   */
+-  @NonNull
+-  public int[] getShape() {
+-    assertShapeIsCorrect();
+-    return Arrays.copyOf(shape, shape.length);
+-  }
+-
+-  /** Returns the data type of this buffer. */
+-  public abstract DataType getDataType();
+-
+-  /**
+-   * Returns a float array of the values stored in this buffer. If the buffer is of different types
+-   * than float, the values will be converted into float. For example, values in {@link
+-   * TensorBufferUint8} will be converted from uint8 to float.
+-   */
+-  @NonNull
+-  public abstract float[] getFloatArray();
+-
+-  /**
+-   * Returns a float value at a given index. If the buffer is of different types than float, the
+-   * value will be converted into float. For example, when reading a value from {@link
+-   * TensorBufferUint8}, the value will be first read out as uint8, and then will be converted from
+-   * uint8 to float.
+-   *
+-   * <pre>
+-   * For example, a TensorBuffer with shape {2, 3} that represents the following array,
+-   * [[0.0f, 1.0f, 2.0f], [3.0f, 4.0f, 5.0f]].
+-   *
+-   * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrieved by:
+-   * float v = tensorBuffer.getFloatValue(3);
+-   * </pre>
+-   *
+-   * @param absIndex The absolute index of the value to be read.
+-   */
+-  public abstract float getFloatValue(int absIndex);
+-
+-  /**
+-   * Returns an int array of the values stored in this buffer. If the buffer is of different type
+-   * than int, the values will be converted into int, and loss of precision may apply. For example,
+-   * getting an int array from a {@link TensorBufferFloat} with values {400.32f, 23.04f}, the output
+-   * is {400, 23}.
+-   */
+-  @NonNull
+-  public abstract int[] getIntArray();
+-
+-  /**
+-   * Returns an int value at a given index. If the buffer is of different types than int, the value
+-   * will be converted into int. For example, when reading a value from {@link TensorBufferFloat},
+-   * the value will be first read out as float, and then will be converted from float to int. Loss
+-   * of precision may apply.
+-   *
+-   * <pre>
+-   * For example, a TensorBuffer with shape {2, 3} that represents the following array,
+-   * [[0.0f, 1.0f, 2.0f], [3.0f, 4.0f, 5.0f]].
+-   *
+-   * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrieved by:
+-   * int v = tensorBuffer.getIntValue(3);
+-   * Note that v is converted from 3.0f to 3 as a result of type conversion.
+-   * </pre>
+-   *
+-   * @param absIndex The absolute index of the value to be read.
+-   */
+-  public abstract int getIntValue(int absIndex);
+-
+-  /**
+-   * Returns the number of bytes of a single element in the array. For example, a float buffer will
+-   * return 4, and a byte buffer will return 1.
+-   */
+-  public abstract int getTypeSize();
+-
+-  /** Returns if the {@link TensorBuffer} is dynamic sized (could resize arbitrarily). */
+-  public boolean isDynamic() {
+-    return isDynamic;
+-  }
+-
+-  /**
+-   * Loads an int array into this buffer with specific shape. If the buffer is of different types
+-   * than int, the values will be converted into the buffer's type before being loaded into the
+-   * buffer, and loss of precision may apply. For example, loading an int array with values {400,
+-   * -23} into a {@link TensorBufferUint8} , the values will be clamped to [0, 255] and then be
+-   * casted to uint8 by {255, 0}.
+-   *
+-   * @param src The source array to be loaded.
+-   * @param shape Shape of the tensor that {@code src} represents.
+-   * @throws NullPointerException if {@code src} is null.
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if the size of the array to be loaded does not match the
+-   *     specified shape.
+-   */
+-  public abstract void loadArray(@NonNull int[] src, @NonNull int[] shape);
+-
+-  /**
+-   * Loads an int array into this buffer. If the buffer is of different types than int, the values
+-   * will be converted into the buffer's type before being loaded into the buffer, and loss of
+-   * precision may apply. For example, loading an int array with values {400, -23} into a {@link
+-   * TensorBufferUint8} , the values will be clamped to [0, 255] and then be casted to uint8 by
+-   * {255, 0}.
+-   *
+-   * <p>Using this method assumes that the shape of {@code src} is the same as the shape of this
+-   * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code src.length}) should always match
+-   * the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
+-   * TensorBuffer}. Use {@link #loadArray(int[], int[])} if {@code src} has a different shape.
+-   *
+-   * @param src The source array to be loaded.
+-   */
+-  public void loadArray(@NonNull int[] src) {
+-    loadArray(src, shape);
+-  }
+-
+-  /**
+-   * Loads a float array into this buffer with specific shape. If the buffer is of different types
+-   * than float, the values will be converted into the buffer's type before being loaded into the
+-   * buffer, and loss of precision may apply. For example, loading a float array into a {@link
+-   * TensorBufferUint8} with values {400.32f, -23.04f}, the values will be clamped to [0, 255] and
+-   * then be casted to uint8 by {255, 0}.
+-   *
+-   * @param src The source array to be loaded.
+-   * @param shape Shape of the tensor that {@code src} represents.
+-   * @throws NullPointerException if {@code src} is null.
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if the size of the array to be loaded does not match the
+-   *     specified shape.
+-   */
+-  public abstract void loadArray(@NonNull float[] src, @NonNull int[] shape);
+-
+-  /**
+-   * Loads a float array into this buffer. If the buffer is of different types than float, the
+-   * values will be converted into the buffer's type before being loaded into the buffer, and loss
+-   * of precision may apply. For example, loading a float array into a {@link TensorBufferUint8}
+-   * with values {400.32f, -23.04f}, the values will be clamped to [0, 255] and then be casted to
+-   * uint8 by {255, 0}.
+-   *
+-   * <p>Using this method assumes that the shape of {@code src} is the same as the shape of this
+-   * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code src.length}) should always match
+-   * the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
+-   * TensorBuffer}. Use {@link #loadArray(float[], int[])} if {@code src} has a different shape.
+-   *
+-   * @param src The source array to be loaded.
+-   */
+-  public void loadArray(@NonNull float[] src) {
+-    loadArray(src, shape);
+-  }
+-
+-  /**
+-   * Loads a byte buffer into this {@link TensorBuffer} with specific shape.
+-   *
+-   * <p>Important: The loaded buffer is a reference. DO NOT MODIFY. We don't create a copy here for
+-   * performance concern, but if modification is necessary, please make a copy.
+-   *
+-   * <p>For the best performance, always load a direct {@link ByteBuffer} or a {@link ByteBuffer}
+-   * backed by an array.
+-   *
+-   * @param buffer The byte buffer to load.
+-   * @throws NullPointerException if {@code buffer} is null.
+-   * @throws IllegalArgumentException if the size of {@code buffer} and {@code typeSize} do not
+-   *     match or the size of {@code buffer} and {@code flatSize} do not match.
+-   */
+-  public void loadBuffer(@NonNull ByteBuffer buffer, @NonNull int[] shape) {
+-    checkNotNull(buffer, "Byte buffer cannot be null.");
+-    checkArgument(isShapeValid(shape), "Values in TensorBuffer shape should be non-negative.");
+-
+-    int flatSize = computeFlatSize(shape);
+-    checkArgument(
+-        (buffer.limit() == getTypeSize() * flatSize),
+-        "The size of byte buffer and the shape do not match. Expected: "
+-            + getTypeSize() * flatSize
+-            + " Actual: "
+-            + buffer.limit());
+-
+-    if (!isDynamic) {
+-      // Make sure the new shape fits the buffer size when TensorBuffer has fixed size.
+-      checkArgument(Arrays.equals(shape, this.shape));
++
++    /**
++     * Gets the current shape. (returning a copy here to avoid unexpected modification.)
++     *
++     * @throws IllegalStateException if the underlying data is corrupted
++     */
++    @NonNull
++    public int[] getShape() {
++        assertShapeIsCorrect();
++        return Arrays.copyOf(shape, shape.length);
+     }
+ 
+-    // Update to the new shape, since shape dim values might change.
+-    this.shape = shape.clone();
+-    this.flatSize = flatSize;
+-
+-    buffer.rewind();
+-    this.buffer = buffer;
+-  }
+-
+-  /**
+-   * Loads a byte buffer into this {@link TensorBuffer}. Buffer size must match the flat size of
+-   * this {@link TensorBuffer}.
+-   *
+-   * <p>Using this method assumes that the shape of {@code buffer} is the same as the shape of this
+-   * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code buffer.limit()}) should always
+-   * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
+-   * TensorBuffer}. Use {@link #loadBuffer(ByteBuffer, int[])} if {@code buffer} has a different
+-   * shape.
+-   *
+-   * <p>Important: The loaded buffer is a reference. DO NOT MODIFY. We don't create a copy here for
+-   * performance concern, but if modification is necessary, please make a copy.
+-   *
+-   * <p>For the best performance, always load a direct {@link ByteBuffer} or a {@link ByteBuffer}
+-   * backed by an array.
+-   *
+-   * <p>If the {@code buffer} is read-only, we adopt a copy-on-write strategy for performance.
+-   *
+-   * @param buffer The byte buffer to load.
+-   */
+-  public void loadBuffer(@NonNull ByteBuffer buffer) {
+-    loadBuffer(buffer, shape);
+-  }
+-
+-  /**
+-   * Constructs a fixed size {@link TensorBuffer} with specified {@code shape}.
+-   *
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if {@code shape} has non-positive elements.
+-   */
+-  protected TensorBuffer(@NonNull int[] shape) {
+-    isDynamic = false;
+-    allocateMemory(shape);
+-  }
+-
+-  /** Constructs a dynamic {@link TensorBuffer} which can be resized. */
+-  protected TensorBuffer() {
+-    isDynamic = true;
+-    // Initialize the dynamic TensorBuffer with an empty ByteBuffer.
+-    allocateMemory(new int[] {0});
+-  }
+-
+-  /** Calculates number of elements in the buffer. */
+-  protected static int computeFlatSize(@NonNull int[] shape) {
+-    checkNotNull(shape, "Shape cannot be null.");
+-    int prod = 1;
+-    for (int s : shape) {
+-      prod = prod * s;
++    /** Returns the data type of this buffer. */
++    public abstract DataType getDataType();
++
++    /**
++     * Returns a float array of the values stored in this buffer. If the buffer is of different
++     * types than float, the values will be converted into float. For example, values in {@link
++     * TensorBufferUint8} will be converted from uint8 to float.
++     */
++    @NonNull
++    public abstract float[] getFloatArray();
++
++    /**
++     * Returns a float value at a given index. If the buffer is of different types than float, the
++     * value will be converted into float. For example, when reading a value from {@link
++     * TensorBufferUint8}, the value will be first read out as uint8, and then will be converted
++     * from uint8 to float.
++     *
++     * <pre>
++     * For example, a TensorBuffer with shape {2, 3} that represents the following array,
++     * [[0.0f, 1.0f, 2.0f], [3.0f, 4.0f, 5.0f]].
++     *
++     * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrieved by:
++     * float v = tensorBuffer.getFloatValue(3);
++     * </pre>
++     *
++     * @param absIndex The absolute index of the value to be read.
++     */
++    public abstract float getFloatValue(int absIndex);
++
++    /**
++     * Returns an int array of the values stored in this buffer. If the buffer is of different type
++     * than int, the values will be converted into int, and loss of precision may apply. For
++     * example, getting an int array from a {@link TensorBufferFloat} with values {400.32f, 23.04f},
++     * the output is {400, 23}.
++     */
++    @NonNull
++    public abstract int[] getIntArray();
++
++    /**
++     * Returns an int value at a given index. If the buffer is of different types than int, the
++     * value will be converted into int. For example, when reading a value from {@link
++     * TensorBufferFloat}, the value will be first read out as float, and then will be converted
++     * from float to int. Loss of precision may apply.
++     *
++     * <pre>
++     * For example, a TensorBuffer with shape {2, 3} that represents the following array,
++     * [[0.0f, 1.0f, 2.0f], [3.0f, 4.0f, 5.0f]].
++     *
++     * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrieved by:
++     * int v = tensorBuffer.getIntValue(3);
++     * Note that v is converted from 3.0f to 3 as a result of type conversion.
++     * </pre>
++     *
++     * @param absIndex The absolute index of the value to be read.
++     */
++    public abstract int getIntValue(int absIndex);
++
++    /**
++     * Returns the number of bytes of a single element in the array. For example, a float buffer
++     * will return 4, and a byte buffer will return 1.
++     */
++    public abstract int getTypeSize();
++
++    /** Returns if the {@link TensorBuffer} is dynamic sized (could resize arbitrarily). */
++    public boolean isDynamic() {
++        return isDynamic;
+     }
+-    return prod;
+-  }
+-
+-  /**
+-   * For dynamic buffer, resize the memory if needed. For fixed-size buffer, check if the {@code
+-   * shape} of src fits the buffer size.
+-   */
+-  protected void resize(@NonNull int[] shape) {
+-    if (isDynamic) {
+-      allocateMemory(shape);
+-    } else {
+-      // Make sure the new shape fits the buffer size when TensorBuffer has fixed size.
+-      checkArgument(Arrays.equals(shape, this.shape));
+-      this.shape = shape.clone();
++
++    /**
++     * Loads an int array into this buffer with specific shape. If the buffer is of different types
++     * than int, the values will be converted into the buffer's type before being loaded into the
++     * buffer, and loss of precision may apply. For example, loading an int array with values {400,
++     * -23} into a {@link TensorBufferUint8} , the values will be clamped to [0, 255] and then be
++     * casted to uint8 by {255, 0}.
++     *
++     * @param src The source array to be loaded.
++     * @param shape Shape of the tensor that {@code src} represents.
++     * @throws NullPointerException if {@code src} is null.
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if the size of the array to be loaded does not match the
++     *     specified shape.
++     */
++    public abstract void loadArray(@NonNull int[] src, @NonNull int[] shape);
++
++    /**
++     * Loads an int array into this buffer. If the buffer is of different types than int, the values
++     * will be converted into the buffer's type before being loaded into the buffer, and loss of
++     * precision may apply. For example, loading an int array with values {400, -23} into a {@link
++     * TensorBufferUint8} , the values will be clamped to [0, 255] and then be casted to uint8 by
++     * {255, 0}.
++     *
++     * <p>Using this method assumes that the shape of {@code src} is the same as the shape of this
++     * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code src.length}) should always
++     * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
++     * TensorBuffer}. Use {@link #loadArray(int[], int[])} if {@code src} has a different shape.
++     *
++     * @param src The source array to be loaded.
++     */
++    public void loadArray(@NonNull int[] src) {
++        loadArray(src, shape);
++    }
++
++    /**
++     * Loads a float array into this buffer with specific shape. If the buffer is of different types
++     * than float, the values will be converted into the buffer's type before being loaded into the
++     * buffer, and loss of precision may apply. For example, loading a float array into a {@link
++     * TensorBufferUint8} with values {400.32f, -23.04f}, the values will be clamped to [0, 255] and
++     * then be casted to uint8 by {255, 0}.
++     *
++     * @param src The source array to be loaded.
++     * @param shape Shape of the tensor that {@code src} represents.
++     * @throws NullPointerException if {@code src} is null.
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if the size of the array to be loaded does not match the
++     *     specified shape.
++     */
++    public abstract void loadArray(@NonNull float[] src, @NonNull int[] shape);
++
++    /**
++     * Loads a float array into this buffer. If the buffer is of different types than float, the
++     * values will be converted into the buffer's type before being loaded into the buffer, and loss
++     * of precision may apply. For example, loading a float array into a {@link TensorBufferUint8}
++     * with values {400.32f, -23.04f}, the values will be clamped to [0, 255] and then be casted to
++     * uint8 by {255, 0}.
++     *
++     * <p>Using this method assumes that the shape of {@code src} is the same as the shape of this
++     * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code src.length}) should always
++     * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
++     * TensorBuffer}. Use {@link #loadArray(float[], int[])} if {@code src} has a different shape.
++     *
++     * @param src The source array to be loaded.
++     */
++    public void loadArray(@NonNull float[] src) {
++        loadArray(src, shape);
+     }
+-  }
+ 
+-  /** Copies the underlying {@link ByteBuffer} if it's readonly. */
+-  protected synchronized void copyByteBufferIfReadOnly() {
+-    if (!buffer.isReadOnly()) {
+-      return;
++    /**
++     * Loads a byte buffer into this {@link TensorBuffer} with specific shape.
++     *
++     * <p>Important: The loaded buffer is a reference. DO NOT MODIFY. We don't create a copy here
++     * for performance concern, but if modification is necessary, please make a copy.
++     *
++     * <p>For the best performance, always load a direct {@link ByteBuffer} or a {@link ByteBuffer}
++     * backed by an array.
++     *
++     * @param buffer The byte buffer to load.
++     * @throws NullPointerException if {@code buffer} is null.
++     * @throws IllegalArgumentException if the size of {@code buffer} and {@code typeSize} do not
++     *     match or the size of {@code buffer} and {@code flatSize} do not match.
++     */
++    public void loadBuffer(@NonNull ByteBuffer buffer, @NonNull int[] shape) {
++        checkNotNull(buffer, "Byte buffer cannot be null.");
++        checkArgument(isShapeValid(shape), "Values in TensorBuffer shape should be non-negative.");
++
++        int flatSize = computeFlatSize(shape);
++        checkArgument((buffer.limit() == getTypeSize() * flatSize),
++                "The size of byte buffer and the shape do not match. Expected: "
++                        + getTypeSize() * flatSize + " Actual: " + buffer.limit());
++
++        if (!isDynamic) {
++            // Make sure the new shape fits the buffer size when TensorBuffer has fixed size.
++            checkArgument(Arrays.equals(shape, this.shape));
++        }
++
++        // Update to the new shape, since shape dim values might change.
++        this.shape = shape.clone();
++        this.flatSize = flatSize;
++
++        buffer.rewind();
++        this.buffer = buffer;
+     }
+-    ByteBuffer newByteBuffer = ByteBuffer.allocateDirect(buffer.capacity());
+-    newByteBuffer.order(buffer.order());
+-    newByteBuffer.put(buffer);
+-    newByteBuffer.rewind();
+-    buffer = newByteBuffer;
+-  }
+-
+-  /**
+-   * Allocates buffer with corresponding size of the {@code shape}. If shape is an empty array, this
+-   * {@link TensorBuffer} will be created as a scalar and its flatSize will be 1.
+-   *
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if {@code shape} has negative elements.
+-   */
+-  private void allocateMemory(@NonNull int[] shape) {
+-    checkNotNull(shape, "TensorBuffer shape cannot be null.");
+-    checkArgument(isShapeValid(shape), "Values in TensorBuffer shape should be non-negative.");
+-
+-    // Check if the new shape is the same as current shape.
+-    int newFlatSize = computeFlatSize(shape);
+-    this.shape = shape.clone();
+-    if (flatSize == newFlatSize) {
+-      return;
++
++    /**
++     * Loads a byte buffer into this {@link TensorBuffer}. Buffer size must match the flat size of
++     * this {@link TensorBuffer}.
++     *
++     * <p>Using this method assumes that the shape of {@code buffer} is the same as the shape of
++     * this
++     * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code buffer.limit()}) should always
++     * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
++     * TensorBuffer}. Use {@link #loadBuffer(ByteBuffer, int[])} if {@code buffer} has a different
++     * shape.
++     *
++     * <p>Important: The loaded buffer is a reference. DO NOT MODIFY. We don't create a copy here
++     * for performance concern, but if modification is necessary, please make a copy.
++     *
++     * <p>For the best performance, always load a direct {@link ByteBuffer} or a {@link ByteBuffer}
++     * backed by an array.
++     *
++     * <p>If the {@code buffer} is read-only, we adopt a copy-on-write strategy for performance.
++     *
++     * @param buffer The byte buffer to load.
++     */
++    public void loadBuffer(@NonNull ByteBuffer buffer) {
++        loadBuffer(buffer, shape);
++    }
++
++    /**
++     * Constructs a fixed size {@link TensorBuffer} with specified {@code shape}.
++     *
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if {@code shape} has non-positive elements.
++     */
++    protected TensorBuffer(@NonNull int[] shape) {
++        isDynamic = false;
++        allocateMemory(shape);
++    }
++
++    /** Constructs a dynamic {@link TensorBuffer} which can be resized. */
++    protected TensorBuffer() {
++        isDynamic = true;
++        // Initialize the dynamic TensorBuffer with an empty ByteBuffer.
++        allocateMemory(new int[] {0});
++    }
++
++    /** Calculates number of elements in the buffer. */
++    protected static int computeFlatSize(@NonNull int[] shape) {
++        checkNotNull(shape, "Shape cannot be null.");
++        int prod = 1;
++        for (int s : shape) {
++            prod = prod * s;
++        }
++        return prod;
++    }
++
++    /**
++     * For dynamic buffer, resize the memory if needed. For fixed-size buffer, check if the {@code
++     * shape} of src fits the buffer size.
++     */
++    protected void resize(@NonNull int[] shape) {
++        if (isDynamic) {
++            allocateMemory(shape);
++        } else {
++            // Make sure the new shape fits the buffer size when TensorBuffer has fixed size.
++            checkArgument(Arrays.equals(shape, this.shape));
++            this.shape = shape.clone();
++        }
++    }
++
++    /** Copies the underlying {@link ByteBuffer} if it's readonly. */
++    protected synchronized void copyByteBufferIfReadOnly() {
++        if (!buffer.isReadOnly()) {
++            return;
++        }
++        ByteBuffer newByteBuffer = ByteBuffer.allocateDirect(buffer.capacity());
++        newByteBuffer.order(buffer.order());
++        newByteBuffer.put(buffer);
++        newByteBuffer.rewind();
++        buffer = newByteBuffer;
++    }
++
++    /**
++     * Allocates buffer with corresponding size of the {@code shape}. If shape is an empty array,
++     * this
++     * {@link TensorBuffer} will be created as a scalar and its flatSize will be 1.
++     *
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if {@code shape} has negative elements.
++     */
++    private void allocateMemory(@NonNull int[] shape) {
++        checkNotNull(shape, "TensorBuffer shape cannot be null.");
++        checkArgument(isShapeValid(shape), "Values in TensorBuffer shape should be non-negative.");
++
++        // Check if the new shape is the same as current shape.
++        int newFlatSize = computeFlatSize(shape);
++        this.shape = shape.clone();
++        if (flatSize == newFlatSize) {
++            return;
++        }
++
++        // Update to the new shape.
++        flatSize = newFlatSize;
++        buffer = ByteBuffer.allocateDirect(flatSize * getTypeSize());
++        buffer.order(ByteOrder.nativeOrder());
+     }
+ 
+-    // Update to the new shape.
+-    flatSize = newFlatSize;
+-    buffer = ByteBuffer.allocateDirect(flatSize * getTypeSize());
+-    buffer.order(ByteOrder.nativeOrder());
+-  }
+-
+-  /**
+-   * Verifies if the shape of the {@link TensorBuffer} matched the size of the underlying {@link
+-   * ByteBuffer}.
+-   */
+-  private void assertShapeIsCorrect() {
+-    int flatSize = computeFlatSize(shape);
+-    checkState(
+-        (buffer.limit() == getTypeSize() * flatSize),
+-        String.format(
+-            "The size of underlying ByteBuffer (%d) and the shape (%s) do not match. The"
+-                + " ByteBuffer may have been changed.",
+-            buffer.limit(), Arrays.toString(shape)));
+-  }
+-
+-  /**
+-   * Checks if {@code shape} meets one of following two requirements: 1. Elements in {@code shape}
+-   * are all non-negative numbers. 2. {@code shape} is an empty array, which corresponds to scalar.
+-   */
+-  private static boolean isShapeValid(@NonNull int[] shape) {
+-    if (shape.length == 0) {
+-      // This shape refers to a scalar.
+-      return true;
++    /**
++     * Verifies if the shape of the {@link TensorBuffer} matched the size of the underlying {@link
++     * ByteBuffer}.
++     */
++    private void assertShapeIsCorrect() {
++        int flatSize = computeFlatSize(shape);
++        checkState((buffer.limit() == getTypeSize() * flatSize),
++                String.format(
++                        "The size of underlying ByteBuffer (%d) and the shape (%s) do not match. The"
++                                + " ByteBuffer may have been changed.",
++                        buffer.limit(), Arrays.toString(shape)));
+     }
+ 
+-    // This shape refers to a multidimensional array.
+-    for (int s : shape) {
+-      // All elements in shape should be non-negative.
+-      if (s < 0) {
+-        return false;
+-      }
++    /**
++     * Checks if {@code shape} meets one of following two requirements: 1. Elements in {@code shape}
++     * are all non-negative numbers. 2. {@code shape} is an empty array, which corresponds to
++     * scalar.
++     */
++    private static boolean isShapeValid(@NonNull int[] shape) {
++        if (shape.length == 0) {
++            // This shape refers to a scalar.
++            return true;
++        }
++
++        // This shape refers to a multidimensional array.
++        for (int s : shape) {
++            // All elements in shape should be non-negative.
++            if (s < 0) {
++                return false;
++            }
++        }
++        return true;
+     }
+-    return true;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java
+index 8d2bc5ad0c84d..632db6c886b17 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java
+@@ -15,103 +15,102 @@ limitations under the License.
+ 
+ package org.tensorflow.lite.support.tensorbuffer;
+ 
+-import java.nio.FloatBuffer;
+ import org.checkerframework.checker.nullness.qual.NonNull;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ 
++import java.nio.FloatBuffer;
++
+ /** Represents data buffer with float values. */
+ public final class TensorBufferFloat extends TensorBuffer {
+-  private static final DataType DATA_TYPE = DataType.FLOAT32;
+-
+-  /**
+-   * Creates a {@link TensorBufferFloat} with specified {@code shape}.
+-   *
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if {@code shape} has non-positive elements.
+-   */
+-  TensorBufferFloat(@NonNull int[] shape) {
+-    super(shape);
+-  }
+-
+-  TensorBufferFloat() {
+-    super();
+-  }
+-
+-  @Override
+-  public DataType getDataType() {
+-    return DATA_TYPE;
+-  }
+-
+-  @Override
+-  @NonNull
+-  public float[] getFloatArray() {
+-    buffer.rewind();
+-    float[] arr = new float[flatSize];
+-
+-    FloatBuffer floatBuffer = buffer.asFloatBuffer();
+-    floatBuffer.get(arr);
+-    return arr;
+-  }
+-
+-  @Override
+-  public float getFloatValue(int absIndex) {
+-    return buffer.getFloat(absIndex << 2);
+-  }
+-
+-  @Override
+-  @NonNull
+-  public int[] getIntArray() {
+-    buffer.rewind();
+-    float[] floatArr = new float[flatSize];
+-    buffer.asFloatBuffer().get(floatArr);
+-
+-    int[] intArr = new int[flatSize];
+-    for (int i = 0; i < flatSize; i++) {
+-      intArr[i] = (int) floatArr[i];
++    private static final DataType DATA_TYPE = DataType.FLOAT32;
++
++    /**
++     * Creates a {@link TensorBufferFloat} with specified {@code shape}.
++     *
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if {@code shape} has non-positive elements.
++     */
++    TensorBufferFloat(@NonNull int[] shape) {
++        super(shape);
+     }
+-    return intArr;
+-  }
+-
+-  @Override
+-  public int getIntValue(int absIndex) {
+-    return (int) buffer.getFloat(absIndex << 2);
+-  }
+-
+-  @Override
+-  public int getTypeSize() {
+-    return DATA_TYPE.byteSize();
+-  }
+-
+-  @Override
+-  public void loadArray(@NonNull float[] src, @NonNull int[] shape) {
+-    SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
+-    SupportPreconditions.checkArgument(
+-        src.length == computeFlatSize(shape),
+-        "The size of the array to be loaded does not match the specified shape.");
+-    copyByteBufferIfReadOnly();
+-    resize(shape);
+-    buffer.rewind();
+-
+-    FloatBuffer floatBuffer = buffer.asFloatBuffer();
+-    floatBuffer.put(src);
+-  }
+-
+-  @Override
+-  public void loadArray(@NonNull int[] src, @NonNull int[] shape) {
+-    SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
+-    SupportPreconditions.checkArgument(
+-        src.length == computeFlatSize(shape),
+-        "The size of the array to be loaded does not match the specified shape.");
+-    copyByteBufferIfReadOnly();
+-    resize(shape);
+-    buffer.rewind();
+-
+-    float[] floatArray = new float[src.length];
+-    int cnt = 0;
+-    for (int a : src) {
+-      floatArray[cnt++] = (float) a;
++
++    TensorBufferFloat() {
++        super();
++    }
++
++    @Override
++    public DataType getDataType() {
++        return DATA_TYPE;
++    }
++
++    @Override
++    @NonNull
++    public float[] getFloatArray() {
++        buffer.rewind();
++        float[] arr = new float[flatSize];
++
++        FloatBuffer floatBuffer = buffer.asFloatBuffer();
++        floatBuffer.get(arr);
++        return arr;
++    }
++
++    @Override
++    public float getFloatValue(int absIndex) {
++        return buffer.getFloat(absIndex << 2);
++    }
++
++    @Override
++    @NonNull
++    public int[] getIntArray() {
++        buffer.rewind();
++        float[] floatArr = new float[flatSize];
++        buffer.asFloatBuffer().get(floatArr);
++
++        int[] intArr = new int[flatSize];
++        for (int i = 0; i < flatSize; i++) {
++            intArr[i] = (int) floatArr[i];
++        }
++        return intArr;
++    }
++
++    @Override
++    public int getIntValue(int absIndex) {
++        return (int) buffer.getFloat(absIndex << 2);
++    }
++
++    @Override
++    public int getTypeSize() {
++        return DATA_TYPE.byteSize();
++    }
++
++    @Override
++    public void loadArray(@NonNull float[] src, @NonNull int[] shape) {
++        SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
++        SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
++                "The size of the array to be loaded does not match the specified shape.");
++        copyByteBufferIfReadOnly();
++        resize(shape);
++        buffer.rewind();
++
++        FloatBuffer floatBuffer = buffer.asFloatBuffer();
++        floatBuffer.put(src);
++    }
++
++    @Override
++    public void loadArray(@NonNull int[] src, @NonNull int[] shape) {
++        SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
++        SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
++                "The size of the array to be loaded does not match the specified shape.");
++        copyByteBufferIfReadOnly();
++        resize(shape);
++        buffer.rewind();
++
++        float[] floatArray = new float[src.length];
++        int cnt = 0;
++        for (int a : src) {
++            floatArray[cnt++] = (float) a;
++        }
++        buffer.asFloatBuffer().put(floatArray);
+     }
+-    buffer.asFloatBuffer().put(floatArray);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java
+index b2fa466e5be92..2924ef0af6c11 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java
+@@ -21,103 +21,101 @@ import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+ 
+ /** Represents data buffer with 8-bit unsigned integer values. */
+ public final class TensorBufferUint8 extends TensorBuffer {
+-  private static final DataType DATA_TYPE = DataType.UINT8;
+-
+-  /**
+-   * Creates a {@link TensorBufferUint8} with specified {@code shape}.
+-   *
+-   * @throws NullPointerException if {@code shape} is null.
+-   * @throws IllegalArgumentException if {@code shape} has non-positive elements.
+-   */
+-  TensorBufferUint8(@NonNull int[] shape) {
+-    super(shape);
+-  }
+-
+-  TensorBufferUint8() {
+-    super();
+-  }
+-
+-  @Override
+-  public DataType getDataType() {
+-    return DATA_TYPE;
+-  }
+-
+-  @Override
+-  @NonNull
+-  public float[] getFloatArray() {
+-    buffer.rewind();
+-    byte[] byteArr = new byte[flatSize];
+-    buffer.get(byteArr);
+-
+-    float[] floatArr = new float[flatSize];
+-    for (int i = 0; i < flatSize; i++) {
+-      floatArr[i] = (float) (byteArr[i] & 0xff);
++    private static final DataType DATA_TYPE = DataType.UINT8;
++
++    /**
++     * Creates a {@link TensorBufferUint8} with specified {@code shape}.
++     *
++     * @throws NullPointerException if {@code shape} is null.
++     * @throws IllegalArgumentException if {@code shape} has non-positive elements.
++     */
++    TensorBufferUint8(@NonNull int[] shape) {
++        super(shape);
+     }
+-    return floatArr;
+-  }
+-
+-  @Override
+-  public float getFloatValue(int index) {
+-    return (float) (buffer.get(index) & 0xff);
+-  }
+-
+-  @Override
+-  @NonNull
+-  public int[] getIntArray() {
+-    buffer.rewind();
+-    byte[] byteArr = new byte[flatSize];
+-    buffer.get(byteArr);
+-
+-    int[] intArr = new int[flatSize];
+-    for (int i = 0; i < flatSize; i++) {
+-      intArr[i] = byteArr[i] & 0xff;
++
++    TensorBufferUint8() {
++        super();
++    }
++
++    @Override
++    public DataType getDataType() {
++        return DATA_TYPE;
++    }
++
++    @Override
++    @NonNull
++    public float[] getFloatArray() {
++        buffer.rewind();
++        byte[] byteArr = new byte[flatSize];
++        buffer.get(byteArr);
++
++        float[] floatArr = new float[flatSize];
++        for (int i = 0; i < flatSize; i++) {
++            floatArr[i] = (float) (byteArr[i] & 0xff);
++        }
++        return floatArr;
++    }
++
++    @Override
++    public float getFloatValue(int index) {
++        return (float) (buffer.get(index) & 0xff);
+     }
+-    return intArr;
+-  }
+-
+-  @Override
+-  public int getIntValue(int index) {
+-    return buffer.get(index) & 0xff;
+-  }
+-
+-  @Override
+-  public int getTypeSize() {
+-    return DATA_TYPE.byteSize();
+-  }
+-
+-  @Override
+-  public void loadArray(@NonNull float[] src, @NonNull int[] shape) {
+-    SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
+-    SupportPreconditions.checkArgument(
+-        src.length == computeFlatSize(shape),
+-        "The size of the array to be loaded does not match the specified shape.");
+-    copyByteBufferIfReadOnly();
+-    resize(shape);
+-    buffer.rewind();
+-
+-    byte[] byteArr = new byte[src.length];
+-    int cnt = 0;
+-    for (float a : src) {
+-      byteArr[cnt++] = (byte) Math.max(Math.min(a, 255.0), 0.0);
++
++    @Override
++    @NonNull
++    public int[] getIntArray() {
++        buffer.rewind();
++        byte[] byteArr = new byte[flatSize];
++        buffer.get(byteArr);
++
++        int[] intArr = new int[flatSize];
++        for (int i = 0; i < flatSize; i++) {
++            intArr[i] = byteArr[i] & 0xff;
++        }
++        return intArr;
+     }
+-    buffer.put(byteArr);
+-  }
+-
+-  @Override
+-  public void loadArray(@NonNull int[] src, @NonNull int[] shape) {
+-    SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
+-    SupportPreconditions.checkArgument(
+-        src.length == computeFlatSize(shape),
+-        "The size of the array to be loaded does not match the specified shape.");
+-    copyByteBufferIfReadOnly();
+-    resize(shape);
+-    buffer.rewind();
+-
+-    byte[] byteArr = new byte[src.length];
+-    int cnt = 0;
+-    for (float a : src) {
+-      byteArr[cnt++] = (byte) Math.max(Math.min(a, 255), 0);
++
++    @Override
++    public int getIntValue(int index) {
++        return buffer.get(index) & 0xff;
++    }
++
++    @Override
++    public int getTypeSize() {
++        return DATA_TYPE.byteSize();
++    }
++
++    @Override
++    public void loadArray(@NonNull float[] src, @NonNull int[] shape) {
++        SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
++        SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
++                "The size of the array to be loaded does not match the specified shape.");
++        copyByteBufferIfReadOnly();
++        resize(shape);
++        buffer.rewind();
++
++        byte[] byteArr = new byte[src.length];
++        int cnt = 0;
++        for (float a : src) {
++            byteArr[cnt++] = (byte) Math.max(Math.min(a, 255.0), 0.0);
++        }
++        buffer.put(byteArr);
++    }
++
++    @Override
++    public void loadArray(@NonNull int[] src, @NonNull int[] shape) {
++        SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
++        SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
++                "The size of the array to be loaded does not match the specified shape.");
++        copyByteBufferIfReadOnly();
++        resize(shape);
++        buffer.rewind();
++
++        byte[] byteArr = new byte[src.length];
++        int cnt = 0;
++        for (float a : src) {
++            byteArr[cnt++] = (byte) Math.max(Math.min(a, 255), 0);
++        }
++        buffer.put(byteArr);
+     }
+-    buffer.put(byteArr);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java
+index 4f15f3d6b7d64..b3eb11fb32f5f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java
+@@ -22,13 +22,7 @@ import android.media.AudioFormat;
+ import android.media.AudioRecord;
+ import android.media.MediaRecorder;
+ import android.os.ParcelFileDescriptor;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.MappedByteBuffer;
+-import java.util.ArrayList;
+-import java.util.Collections;
+-import java.util.List;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ import org.tensorflow.lite.support.audio.TensorAudio;
+@@ -40,6 +34,14 @@ import org.tensorflow.lite.task.core.TaskJniUtils;
+ import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+ import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.MappedByteBuffer;
++import java.util.ArrayList;
++import java.util.Collections;
++import java.util.List;
++
+ /**
+  * Performs classification on audio waveforms.
+  *
+@@ -72,468 +74,437 @@ import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
+  * CLI demo tool</a> for easily trying out this API.
+  */
+ public final class AudioClassifier extends BaseTaskApi {
++    private static final String AUDIO_CLASSIFIER_NATIVE_LIB = "task_audio_jni";
++    private static final int OPTIONAL_FD_LENGTH = -1;
++    private static final int OPTIONAL_FD_OFFSET = -1;
++
++    /**
++     * Creates an {@link AudioClassifier} instance from the default {@link AudioClassifierOptions}.
++     *
++     * @param modelPath path of the classification model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static AudioClassifier createFromFile(Context context, String modelPath)
++            throws IOException {
++        return createFromFileAndOptions(
++                context, modelPath, AudioClassifierOptions.builder().build());
++    }
+ 
+-  private static final String AUDIO_CLASSIFIER_NATIVE_LIB = "task_audio_jni";
+-  private static final int OPTIONAL_FD_LENGTH = -1;
+-  private static final int OPTIONAL_FD_OFFSET = -1;
+-
+-  /**
+-   * Creates an {@link AudioClassifier} instance from the default {@link AudioClassifierOptions}.
+-   *
+-   * @param modelPath path of the classification model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static AudioClassifier createFromFile(Context context, String modelPath)
+-      throws IOException {
+-    return createFromFileAndOptions(context, modelPath, AudioClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link AudioClassifier} instance from the default {@link AudioClassifierOptions}.
+-   *
+-   * @param modelFile the classification model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static AudioClassifier createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, AudioClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link AudioClassifier} instance with a model buffer and the default {@link
+-   * AudioClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     classification model
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   */
+-  public static AudioClassifier createFromBuffer(final ByteBuffer modelBuffer) {
+-    return createFromBufferAndOptions(modelBuffer, AudioClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link AudioClassifier} instance from {@link AudioClassifierOptions}.
+-   *
+-   * @param modelPath path of the classification model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static AudioClassifier createFromFileAndOptions(
+-      Context context, String modelPath, AudioClassifierOptions options) throws IOException {
+-    return new AudioClassifier(
+-        TaskJniUtils.createHandleFromFdAndOptions(
+-            context,
+-            new FdAndOptionsHandleProvider<AudioClassifierOptions>() {
+-              @Override
+-              public long createHandle(
+-                  int fileDescriptor,
+-                  long fileDescriptorLength,
+-                  long fileDescriptorOffset,
+-                  AudioClassifierOptions options) {
+-                return initJniWithModelFdAndOptions(
+-                    fileDescriptor,
+-                    fileDescriptorLength,
+-                    fileDescriptorOffset,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-              }
+-            },
+-            AUDIO_CLASSIFIER_NATIVE_LIB,
+-            modelPath,
+-            options));
+-  }
+-
+-  /**
+-   * Creates an {@link AudioClassifier} instance.
+-   *
+-   * @param modelFile the classification model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static AudioClassifier createFromFileAndOptions(
+-      File modelFile, final AudioClassifierOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return new AudioClassifier(
+-          TaskJniUtils.createHandleFromLibrary(
+-              new TaskJniUtils.EmptyHandleProvider() {
+-                @Override
+-                public long createHandle() {
+-                  return initJniWithModelFdAndOptions(
+-                      descriptor.getFd(),
+-                      /*fileDescriptorLength=*/ OPTIONAL_FD_LENGTH,
+-                      /*fileDescriptorOffset=*/ OPTIONAL_FD_OFFSET,
+-                      options,
+-                      TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-                }
+-              },
+-              AUDIO_CLASSIFIER_NATIVE_LIB));
++    /**
++     * Creates an {@link AudioClassifier} instance from the default {@link AudioClassifierOptions}.
++     *
++     * @param modelFile the classification model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static AudioClassifier createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, AudioClassifierOptions.builder().build());
+     }
+-  }
+-
+-  /**
+-   * Creates an {@link AudioClassifier} instance with a model buffer and {@link
+-   * AudioClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     classification model
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   */
+-  public static AudioClassifier createFromBufferAndOptions(
+-      final ByteBuffer modelBuffer, final AudioClassifierOptions options) {
+-    if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+-      throw new IllegalArgumentException(
+-          "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++
++    /**
++     * Creates an {@link AudioClassifier} instance with a model buffer and the default {@link
++     * AudioClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     classification model
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     */
++    public static AudioClassifier createFromBuffer(final ByteBuffer modelBuffer) {
++        return createFromBufferAndOptions(modelBuffer, AudioClassifierOptions.builder().build());
+     }
+-    return new AudioClassifier(
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                return initJniWithByteBuffer(
+-                    modelBuffer,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-              }
+-            },
+-            AUDIO_CLASSIFIER_NATIVE_LIB));
+-  }
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++
+-   */
+-  private AudioClassifier(long nativeHandle) {
+-    super(nativeHandle);
+-  }
+-
+-  /** Options for setting up an {@link AudioClassifier}. */
+-  @UsedByReflection("audio_classifier_jni.cc")
+-  public static class AudioClassifierOptions {
+-    // Not using AutoValue for this class because scoreThreshold cannot have default value
+-    // (otherwise, the default value would override the one in the model metadata) and `Optional` is
+-    // not an option here, because
+-    // 1. java.util.Optional require Java 8 while we need to support Java 7.
+-    // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See the
+-    // comments for labelAllowList.
+-    private final BaseOptions baseOptions;
+-    private final String displayNamesLocale;
+-    private final int maxResults;
+-    private final float scoreThreshold;
+-    private final boolean isScoreThresholdSet;
+-    // As an open source project, we've been trying avoiding depending on common java libraries,
+-    // such as Guava, because it may introduce conflicts with clients who also happen to use those
+-    // libraries. Therefore, instead of using ImmutableList here, we convert the List into
+-    // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
+-    // vulnerable.
+-    private final List<String> labelAllowList;
+-    private final List<String> labelDenyList;
+-
+-    public static Builder builder() {
+-      return new Builder();
++
++    /**
++     * Creates an {@link AudioClassifier} instance from {@link AudioClassifierOptions}.
++     *
++     * @param modelPath path of the classification model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static AudioClassifier createFromFileAndOptions(
++            Context context, String modelPath, AudioClassifierOptions options) throws IOException {
++        return new AudioClassifier(TaskJniUtils.createHandleFromFdAndOptions(
++                context, new FdAndOptionsHandleProvider<AudioClassifierOptions>() {
++                    @Override
++                    public long createHandle(int fileDescriptor, long fileDescriptorLength,
++                            long fileDescriptorOffset, AudioClassifierOptions options) {
++                        return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
++                                fileDescriptorOffset, options,
++                                TaskJniUtils.createProtoBaseOptionsHandle(
++                                        options.getBaseOptions()));
++                    }
++                }, AUDIO_CLASSIFIER_NATIVE_LIB, modelPath, options));
+     }
+ 
+-    /** A builder that helps to configure an instance of AudioClassifierOptions. */
+-    public static class Builder {
+-      private BaseOptions baseOptions = BaseOptions.builder().build();
+-      private String displayNamesLocale = "en";
+-      private int maxResults = -1;
+-      private float scoreThreshold;
+-      private boolean isScoreThresholdSet;
+-      private List<String> labelAllowList = new ArrayList<>();
+-      private List<String> labelDenyList = new ArrayList<>();
+-
+-      private Builder() {}
+-
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public Builder setBaseOptions(BaseOptions baseOptions) {
+-        this.baseOptions = baseOptions;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the locale to use for display names specified through the TFLite Model Metadata, if
+-       * any.
+-       *
+-       * <p>Defaults to English({@code "en"}). See the <a
+-       * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
+-       * Metadata schema file.</a> for the accepted pattern of locale.
+-       */
+-      public Builder setDisplayNamesLocale(String displayNamesLocale) {
+-        this.displayNamesLocale = displayNamesLocale;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the maximum number of top scored results to return.
+-       *
+-       * @param maxResults if < 0, all results will be returned. If 0, an invalid argument error is
+-       *     returned. Defaults to -1.
+-       * @throws IllegalArgumentException if maxResults is 0
+-       */
+-      public Builder setMaxResults(int maxResults) {
+-        if (maxResults == 0) {
+-          throw new IllegalArgumentException("maxResults cannot be 0.");
++    /**
++     * Creates an {@link AudioClassifier} instance.
++     *
++     * @param modelFile the classification model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static AudioClassifier createFromFileAndOptions(
++            File modelFile, final AudioClassifierOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return new AudioClassifier(
++                    TaskJniUtils.createHandleFromLibrary(new TaskJniUtils.EmptyHandleProvider() {
++                        @Override
++                        public long createHandle() {
++                            return initJniWithModelFdAndOptions(descriptor.getFd(),
++                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
++                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options,
++                                    TaskJniUtils.createProtoBaseOptionsHandle(
++                                            options.getBaseOptions()));
++                        }
++                    }, AUDIO_CLASSIFIER_NATIVE_LIB));
+         }
+-        this.maxResults = maxResults;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the score threshold.
+-       *
+-       * <p>It overrides the one provided in the model metadata (if any). Results below this value
+-       * are rejected.
+-       */
+-      public Builder setScoreThreshold(float scoreThreshold) {
+-        this.scoreThreshold = scoreThreshold;
+-        isScoreThresholdSet = true;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the optional allowlist of labels.
+-       *
+-       * <p>If non-empty, classifications whose label is not in this set will be filtered out.
+-       * Duplicate or unknown labels are ignored. Mutually exclusive with labelDenyList.
+-       */
+-      public Builder setLabelAllowList(List<String> labelAllowList) {
+-        this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the optional denylist of labels.
+-       *
+-       * <p>If non-empty, classifications whose label is in this set will be filtered out. Duplicate
+-       * or unknown labels are ignored. Mutually exclusive with labelAllowList.
+-       */
+-      public Builder setLabelDenyList(List<String> labelDenyList) {
+-        this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
+-        return this;
+-      }
+-
+-      public AudioClassifierOptions build() {
+-        return new AudioClassifierOptions(this);
+-      }
+     }
+ 
+-    @UsedByReflection("audio_classifier_jni.cc")
+-    public String getDisplayNamesLocale() {
+-      return displayNamesLocale;
++    /**
++     * Creates an {@link AudioClassifier} instance with a model buffer and {@link
++     * AudioClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     classification model
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     */
++    public static AudioClassifier createFromBufferAndOptions(
++            final ByteBuffer modelBuffer, final AudioClassifierOptions options) {
++        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
++            throw new IllegalArgumentException(
++                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++        }
++        return new AudioClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                return initJniWithByteBuffer(modelBuffer, options,
++                        TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
++            }
++        }, AUDIO_CLASSIFIER_NATIVE_LIB));
+     }
+ 
+-    @UsedByReflection("audio_classifier_jni.cc")
+-    public int getMaxResults() {
+-      return maxResults;
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++
++     */
++    private AudioClassifier(long nativeHandle) {
++        super(nativeHandle);
+     }
+ 
++    /** Options for setting up an {@link AudioClassifier}. */
+     @UsedByReflection("audio_classifier_jni.cc")
+-    public float getScoreThreshold() {
+-      return scoreThreshold;
++    public static class AudioClassifierOptions {
++        // Not using AutoValue for this class because scoreThreshold cannot have default value
++        // (otherwise, the default value would override the one in the model metadata) and
++        // `Optional` is not an option here, because
++        // 1. java.util.Optional require Java 8 while we need to support Java 7.
++        // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See
++        // the comments for labelAllowList.
++        private final BaseOptions baseOptions;
++        private final String displayNamesLocale;
++        private final int maxResults;
++        private final float scoreThreshold;
++        private final boolean isScoreThresholdSet;
++        // As an open source project, we've been trying avoiding depending on common java libraries,
++        // such as Guava, because it may introduce conflicts with clients who also happen to use
++        // those libraries. Therefore, instead of using ImmutableList here, we convert the List into
++        // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
++        // vulnerable.
++        private final List<String> labelAllowList;
++        private final List<String> labelDenyList;
++
++        public static Builder builder() {
++            return new Builder();
++        }
++
++        /** A builder that helps to configure an instance of AudioClassifierOptions. */
++        public static class Builder {
++            private BaseOptions baseOptions = BaseOptions.builder().build();
++            private String displayNamesLocale = "en";
++            private int maxResults = -1;
++            private float scoreThreshold;
++            private boolean isScoreThresholdSet;
++            private List<String> labelAllowList = new ArrayList<>();
++            private List<String> labelDenyList = new ArrayList<>();
++
++            private Builder() {}
++
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public Builder setBaseOptions(BaseOptions baseOptions) {
++                this.baseOptions = baseOptions;
++                return this;
++            }
++
++            /**
++             * Sets the locale to use for display names specified through the TFLite Model Metadata,
++             * if any.
++             *
++             * <p>Defaults to English({@code "en"}). See the <a
++             * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
++             * Metadata schema file.</a> for the accepted pattern of locale.
++             */
++            public Builder setDisplayNamesLocale(String displayNamesLocale) {
++                this.displayNamesLocale = displayNamesLocale;
++                return this;
++            }
++
++            /**
++             * Sets the maximum number of top scored results to return.
++             *
++             * @param maxResults if < 0, all results will be returned. If 0, an invalid argument
++             *         error is
++             *     returned. Defaults to -1.
++             * @throws IllegalArgumentException if maxResults is 0
++             */
++            public Builder setMaxResults(int maxResults) {
++                if (maxResults == 0) {
++                    throw new IllegalArgumentException("maxResults cannot be 0.");
++                }
++                this.maxResults = maxResults;
++                return this;
++            }
++
++            /**
++             * Sets the score threshold.
++             *
++             * <p>It overrides the one provided in the model metadata (if any). Results below this
++             * value are rejected.
++             */
++            public Builder setScoreThreshold(float scoreThreshold) {
++                this.scoreThreshold = scoreThreshold;
++                isScoreThresholdSet = true;
++                return this;
++            }
++
++            /**
++             * Sets the optional allowlist of labels.
++             *
++             * <p>If non-empty, classifications whose label is not in this set will be filtered out.
++             * Duplicate or unknown labels are ignored. Mutually exclusive with labelDenyList.
++             */
++            public Builder setLabelAllowList(List<String> labelAllowList) {
++                this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
++                return this;
++            }
++
++            /**
++             * Sets the optional denylist of labels.
++             *
++             * <p>If non-empty, classifications whose label is in this set will be filtered out.
++             * Duplicate or unknown labels are ignored. Mutually exclusive with labelAllowList.
++             */
++            public Builder setLabelDenyList(List<String> labelDenyList) {
++                this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
++                return this;
++            }
++
++            public AudioClassifierOptions build() {
++                return new AudioClassifierOptions(this);
++            }
++        }
++
++        @UsedByReflection("audio_classifier_jni.cc")
++        public String getDisplayNamesLocale() {
++            return displayNamesLocale;
++        }
++
++        @UsedByReflection("audio_classifier_jni.cc")
++        public int getMaxResults() {
++            return maxResults;
++        }
++
++        @UsedByReflection("audio_classifier_jni.cc")
++        public float getScoreThreshold() {
++            return scoreThreshold;
++        }
++
++        @UsedByReflection("audio_classifier_jni.cc")
++        public boolean getIsScoreThresholdSet() {
++            return isScoreThresholdSet;
++        }
++
++        @UsedByReflection("audio_classifier_jni.cc")
++        public List<String> getLabelAllowList() {
++            return new ArrayList<>(labelAllowList);
++        }
++
++        @UsedByReflection("audio_classifier_jni.cc")
++        public List<String> getLabelDenyList() {
++            return new ArrayList<>(labelDenyList);
++        }
++
++        public BaseOptions getBaseOptions() {
++            return baseOptions;
++        }
++
++        private AudioClassifierOptions(Builder builder) {
++            displayNamesLocale = builder.displayNamesLocale;
++            maxResults = builder.maxResults;
++            scoreThreshold = builder.scoreThreshold;
++            isScoreThresholdSet = builder.isScoreThresholdSet;
++            labelAllowList = builder.labelAllowList;
++            labelDenyList = builder.labelDenyList;
++            baseOptions = builder.baseOptions;
++        }
+     }
+ 
+-    @UsedByReflection("audio_classifier_jni.cc")
+-    public boolean getIsScoreThresholdSet() {
+-      return isScoreThresholdSet;
++    /**
++     * Performs actual classification on the provided audio tensor.
++     *
++     * @param tensor a {@link TensorAudio} containing the input audio clip in float with values
++     *     between [-1, 1). The {@code tensor} argument should have the same flat size as the TFLite
++     *     model's input tensor. It's recommended to create {@code tensor} using {@code
++     *     createInputTensorAudio} method.
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if error occurs when classifying the audio clip from the native
++     *     code
++     */
++    public List<Classifications> classify(TensorAudio tensor) {
++        TensorBuffer buffer = tensor.getTensorBuffer();
++        TensorAudioFormat format = tensor.getFormat();
++        checkState(buffer.getBuffer().hasArray(),
++                "Input tensor buffer should be a non-direct buffer with a backed array (i.e. not readonly"
++                        + " buffer).");
++        return classifyNative(getNativeHandle(), buffer.getBuffer().array(), format.getChannels(),
++                format.getSampleRate());
+     }
+ 
+-    @UsedByReflection("audio_classifier_jni.cc")
+-    public List<String> getLabelAllowList() {
+-      return new ArrayList<>(labelAllowList);
++    /**
++     * Creates a {@link TensorAudio} instance to store input audio samples.
++     *
++     * @return a {@link TensorAudio} with the same size as model input tensor
++     * @throws IllegalArgumentException if the model is not compatible
++     */
++    public TensorAudio createInputTensorAudio() {
++        TensorAudioFormat format = getRequiredTensorAudioFormat();
++
++        long bufferSize = getRequiredInputBufferSize();
++        long samples = bufferSize / format.getChannels();
++        return TensorAudio.create(format, (int) samples);
+     }
+ 
+-    @UsedByReflection("audio_classifier_jni.cc")
+-    public List<String> getLabelDenyList() {
+-      return new ArrayList<>(labelDenyList);
++    /** Returns the required input buffer size in number of float elements. */
++    public long getRequiredInputBufferSize() {
++        return getRequiredInputBufferSizeNative(getNativeHandle());
+     }
+ 
+-    public BaseOptions getBaseOptions() {
+-      return baseOptions;
++    /**
++     * Creates an {@link android.media.AudioRecord} instance to record audio stream. The returned
++     * AudioRecord instance is initialized and client needs to call {@link
++     * android.media.AudioRecord#startRecording} method to start recording.
++     *
++     * @return an {@link android.media.AudioRecord} instance in {@link
++     *     android.media.AudioRecord#STATE_INITIALIZED}
++     * @throws IllegalArgumentException if the model required channel count is unsupported
++     * @throws IllegalStateException if AudioRecord instance failed to initialize
++     */
++    public AudioRecord createAudioRecord() {
++        TensorAudioFormat format = getRequiredTensorAudioFormat();
++        int channelConfig = 0;
++
++        switch (format.getChannels()) {
++            case 1:
++                channelConfig = AudioFormat.CHANNEL_IN_MONO;
++                break;
++            case 2:
++                channelConfig = AudioFormat.CHANNEL_IN_STEREO;
++                break;
++            default:
++                throw new IllegalArgumentException(String.format(
++                        "Number of channels required by the model is %d. getAudioRecord method only"
++                                + " supports 1 or 2 audio channels.",
++                        format.getChannels()));
++        }
++
++        int bufferSizeInBytes = AudioRecord.getMinBufferSize(
++                format.getSampleRate(), channelConfig, AudioFormat.ENCODING_PCM_FLOAT);
++        if (bufferSizeInBytes == AudioRecord.ERROR
++                || bufferSizeInBytes == AudioRecord.ERROR_BAD_VALUE) {
++            throw new IllegalStateException(String.format(
++                    "AudioRecord.getMinBufferSize failed. Returned: %d", bufferSizeInBytes));
++        }
++        // The buffer of AudioRecord should be strictly longer than what model requires so that
++        // clients could run `TensorAudio::load(record)` together with `AudioClassifier::classify`.
++        int bufferSizeMultiplier = 2;
++        int modelRequiredBufferSize = (int) getRequiredInputBufferSize()
++                * DataType.FLOAT32.byteSize() * bufferSizeMultiplier;
++        if (bufferSizeInBytes < modelRequiredBufferSize) {
++            bufferSizeInBytes = modelRequiredBufferSize;
++        }
++        AudioRecord audioRecord = new AudioRecord(
++                // including MIC, UNPROCESSED, and CAMCORDER.
++                MediaRecorder.AudioSource.VOICE_RECOGNITION, format.getSampleRate(), channelConfig,
++                AudioFormat.ENCODING_PCM_FLOAT, bufferSizeInBytes);
++        checkState(audioRecord.getState() == AudioRecord.STATE_INITIALIZED,
++                "AudioRecord failed to initialize");
++        return audioRecord;
+     }
+ 
+-    private AudioClassifierOptions(Builder builder) {
+-      displayNamesLocale = builder.displayNamesLocale;
+-      maxResults = builder.maxResults;
+-      scoreThreshold = builder.scoreThreshold;
+-      isScoreThresholdSet = builder.isScoreThresholdSet;
+-      labelAllowList = builder.labelAllowList;
+-      labelDenyList = builder.labelDenyList;
+-      baseOptions = builder.baseOptions;
++    /** Returns the {@link TensorAudioFormat} required by the model. */
++    public TensorAudioFormat getRequiredTensorAudioFormat() {
++        return TensorAudioFormat.builder()
++                .setChannels(getRequiredChannels())
++                .setSampleRate(getRequiredSampleRate())
++                .build();
+     }
+-  }
+-
+-  /**
+-   * Performs actual classification on the provided audio tensor.
+-   *
+-   * @param tensor a {@link TensorAudio} containing the input audio clip in float with values
+-   *     between [-1, 1). The {@code tensor} argument should have the same flat size as the TFLite
+-   *     model's input tensor. It's recommended to create {@code tensor} using {@code
+-   *     createInputTensorAudio} method.
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if error occurs when classifying the audio clip from the native
+-   *     code
+-   */
+-  public List<Classifications> classify(TensorAudio tensor) {
+-    TensorBuffer buffer = tensor.getTensorBuffer();
+-    TensorAudioFormat format = tensor.getFormat();
+-    checkState(
+-        buffer.getBuffer().hasArray(),
+-        "Input tensor buffer should be a non-direct buffer with a backed array (i.e. not readonly"
+-            + " buffer).");
+-    return classifyNative(
+-        getNativeHandle(),
+-        buffer.getBuffer().array(),
+-        format.getChannels(),
+-        format.getSampleRate());
+-  }
+-
+-  /**
+-   * Creates a {@link TensorAudio} instance to store input audio samples.
+-   *
+-   * @return a {@link TensorAudio} with the same size as model input tensor
+-   * @throws IllegalArgumentException if the model is not compatible
+-   */
+-  public TensorAudio createInputTensorAudio() {
+-    TensorAudioFormat format = getRequiredTensorAudioFormat();
+-
+-    long bufferSize = getRequiredInputBufferSize();
+-    long samples = bufferSize / format.getChannels();
+-    return TensorAudio.create(format, (int) samples);
+-  }
+-
+-  /** Returns the required input buffer size in number of float elements. */
+-  public long getRequiredInputBufferSize() {
+-    return getRequiredInputBufferSizeNative(getNativeHandle());
+-  }
+-
+-  /**
+-   * Creates an {@link android.media.AudioRecord} instance to record audio stream. The returned
+-   * AudioRecord instance is initialized and client needs to call {@link
+-   * android.media.AudioRecord#startRecording} method to start recording.
+-   *
+-   * @return an {@link android.media.AudioRecord} instance in {@link
+-   *     android.media.AudioRecord#STATE_INITIALIZED}
+-   * @throws IllegalArgumentException if the model required channel count is unsupported
+-   * @throws IllegalStateException if AudioRecord instance failed to initialize
+-   */
+-  public AudioRecord createAudioRecord() {
+-    TensorAudioFormat format = getRequiredTensorAudioFormat();
+-    int channelConfig = 0;
+-
+-    switch (format.getChannels()) {
+-      case 1:
+-        channelConfig = AudioFormat.CHANNEL_IN_MONO;
+-        break;
+-      case 2:
+-        channelConfig = AudioFormat.CHANNEL_IN_STEREO;
+-        break;
+-      default:
+-        throw new IllegalArgumentException(
+-            String.format(
+-                "Number of channels required by the model is %d. getAudioRecord method only"
+-                    + " supports 1 or 2 audio channels.",
+-                format.getChannels()));
++
++    private int getRequiredChannels() {
++        return getRequiredChannelsNative(getNativeHandle());
+     }
+ 
+-    int bufferSizeInBytes =
+-        AudioRecord.getMinBufferSize(
+-            format.getSampleRate(), channelConfig, AudioFormat.ENCODING_PCM_FLOAT);
+-    if (bufferSizeInBytes == AudioRecord.ERROR
+-        || bufferSizeInBytes == AudioRecord.ERROR_BAD_VALUE) {
+-      throw new IllegalStateException(
+-          String.format("AudioRecord.getMinBufferSize failed. Returned: %d", bufferSizeInBytes));
++    private int getRequiredSampleRate() {
++        return getRequiredSampleRateNative(getNativeHandle());
+     }
+-    // The buffer of AudioRecord should be strictly longer than what model requires so that clients
+-    // could run `TensorAudio::load(record)` together with `AudioClassifier::classify`.
+-    int bufferSizeMultiplier = 2;
+-    int modelRequiredBufferSize =
+-        (int) getRequiredInputBufferSize() * DataType.FLOAT32.byteSize() * bufferSizeMultiplier;
+-    if (bufferSizeInBytes < modelRequiredBufferSize) {
+-      bufferSizeInBytes = modelRequiredBufferSize;
++
++    // TODO(b/183343074): JNI method invocation is very expensive, taking about .2ms
++    // each time. Consider combining the native getter methods into 1 and cache it in Java layer.
++    private static native long getRequiredInputBufferSizeNative(long nativeHandle);
++
++    private static native int getRequiredChannelsNative(long nativeHandle);
++
++    private static native int getRequiredSampleRateNative(long nativeHandle);
++
++    private static native List<Classifications> classifyNative(
++            long nativeHandle, byte[] audioBuffer, int channels, int sampleRate);
++
++    private static native long initJniWithModelFdAndOptions(int fileDescriptor,
++            long fileDescriptorLength, long fileDescriptorOffset, AudioClassifierOptions options,
++            long baseOptionsHandle);
++
++    private static native long initJniWithByteBuffer(
++            ByteBuffer modelBuffer, AudioClassifierOptions options, long baseOptionsHandle);
++
++    /**
++     * Releases memory pointed by {@code nativeHandle}, namely a C++ `AudioClassifier` instance.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
+     }
+-    AudioRecord audioRecord =
+-        new AudioRecord(
+-            // including MIC, UNPROCESSED, and CAMCORDER.
+-            MediaRecorder.AudioSource.VOICE_RECOGNITION,
+-            format.getSampleRate(),
+-            channelConfig,
+-            AudioFormat.ENCODING_PCM_FLOAT,
+-            bufferSizeInBytes);
+-    checkState(
+-        audioRecord.getState() == AudioRecord.STATE_INITIALIZED,
+-        "AudioRecord failed to initialize");
+-    return audioRecord;
+-  }
+-
+-  /** Returns the {@link TensorAudioFormat} required by the model. */
+-  public TensorAudioFormat getRequiredTensorAudioFormat() {
+-    return TensorAudioFormat.builder()
+-        .setChannels(getRequiredChannels())
+-        .setSampleRate(getRequiredSampleRate())
+-        .build();
+-  }
+-
+-  private int getRequiredChannels() {
+-    return getRequiredChannelsNative(getNativeHandle());
+-  }
+-
+-  private int getRequiredSampleRate() {
+-    return getRequiredSampleRateNative(getNativeHandle());
+-  }
+-
+-  // TODO(b/183343074): JNI method invocation is very expensive, taking about .2ms
+-  // each time. Consider combining the native getter methods into 1 and cache it in Java layer.
+-  private static native long getRequiredInputBufferSizeNative(long nativeHandle);
+-
+-  private static native int getRequiredChannelsNative(long nativeHandle);
+-
+-  private static native int getRequiredSampleRateNative(long nativeHandle);
+-
+-  private static native List<Classifications> classifyNative(
+-      long nativeHandle, byte[] audioBuffer, int channels, int sampleRate);
+-
+-  private static native long initJniWithModelFdAndOptions(
+-      int fileDescriptor,
+-      long fileDescriptorLength,
+-      long fileDescriptorOffset,
+-      AudioClassifierOptions options,
+-      long baseOptionsHandle);
+-
+-  private static native long initJniWithByteBuffer(
+-      ByteBuffer modelBuffer, AudioClassifierOptions options, long baseOptionsHandle);
+-
+-  /**
+-   * Releases memory pointed by {@code nativeHandle}, namely a C++ `AudioClassifier` instance.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
+-
+-  /**
+-   * Native method to release memory pointed by {@code nativeHandle}, namely a C++ `AudioClassifier`
+-   * instance.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private static native void deinitJni(long nativeHandle);
++
++    /**
++     * Native method to release memory pointed by {@code nativeHandle}, namely a C++
++     * `AudioClassifier` instance.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private static native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java
+index 446d328441a97..7d5b07fa735cd 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java
+@@ -16,11 +16,13 @@ limitations under the License.
+ package org.tensorflow.lite.task.audio.classifier;
+ 
+ import com.google.auto.value.AutoValue;
++
++import org.tensorflow.lite.annotations.UsedByReflection;
++import org.tensorflow.lite.support.label.Category;
++
+ import java.util.ArrayList;
+ import java.util.Collections;
+ import java.util.List;
+-import org.tensorflow.lite.annotations.UsedByReflection;
+-import org.tensorflow.lite.support.label.Category;
+ 
+ /**
+  * The classification results of one head in a multihead (a.k.a. multi-output) {@link
+@@ -31,18 +33,18 @@ import org.tensorflow.lite.support.label.Category;
+ @AutoValue
+ @UsedByReflection("audio_classifier_jni.cc")
+ public abstract class Classifications {
++    @UsedByReflection("audio_classifier_jni.cc")
++    static Classifications create(List<Category> categories, int headIndex, String headName) {
++        return new AutoValue_Classifications(
++                Collections.unmodifiableList(new ArrayList<Category>(categories)), headIndex,
++                headName);
++    }
+ 
+-  @UsedByReflection("audio_classifier_jni.cc")
+-  static Classifications create(List<Category> categories, int headIndex, String headName) {
+-    return new AutoValue_Classifications(
+-        Collections.unmodifiableList(new ArrayList<Category>(categories)), headIndex, headName);
+-  }
+-
+-  // Same reason for not using ImmutableList as stated in
+-  // {@link ImageClassifier#ImageClassifierOptions#labelAllowList}.
+-  public abstract List<Category> getCategories();
++    // Same reason for not using ImmutableList as stated in
++    // {@link ImageClassifier#ImageClassifierOptions#labelAllowList}.
++    public abstract List<Category> getCategories();
+ 
+-  public abstract int getHeadIndex();
++    public abstract int getHeadIndex();
+ 
+-  public abstract String getHeadName();
++    public abstract String getHeadName();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java
+index 242414bd21bdb..b2d722332c954 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java
+@@ -20,65 +20,66 @@ import com.google.auto.value.AutoValue;
+ /** Options to configure Task APIs in general. */
+ @AutoValue
+ public abstract class BaseOptions {
+-  private static final int DEFAULT_NUM_THREADS = -1;
++    private static final int DEFAULT_NUM_THREADS = -1;
+ 
+-  /** Builder for {@link BaseOptions}. */
+-  @AutoValue.Builder
+-  public abstract static class Builder {
++    /** Builder for {@link BaseOptions}. */
++    @AutoValue.Builder
++    public abstract static class Builder {
++        /**
++         * Sets the advanced accelerator options.
++         *
++         * <p>Note: this method will override those highlevel API to choose an delegate, such as
++         * {@link #useGpu} and {@link #useNnapi}.
++         */
++        public abstract Builder setComputeSettings(ComputeSettings computeSettings);
+ 
+-    /**
+-     * Sets the advanced accelerator options.
+-     *
+-     * <p>Note: this method will override those highlevel API to choose an delegate, such as {@link
+-     * #useGpu} and {@link #useNnapi}.
+-     */
+-    public abstract Builder setComputeSettings(ComputeSettings computeSettings);
++        /**
++         * Sets the number of threads to be used for TFLite ops that support multi-threading when
++         * running inference with CPU. Defaults to -1.
++         *
++         * <p>{@code numThreads} should be greater than 0 or equal to -1. Setting numThreads to -1
++         * has the effect to let TFLite runtime set the value.
++         */
++        public abstract Builder setNumThreads(int numThreads);
+ 
+-    /**
+-     * Sets the number of threads to be used for TFLite ops that support multi-threading when
+-     * running inference with CPU. Defaults to -1.
+-     *
+-     * <p>{@code numThreads} should be greater than 0 or equal to -1. Setting numThreads to -1 has
+-     * the effect to let TFLite runtime set the value.
+-     */
+-    public abstract Builder setNumThreads(int numThreads);
++        /**
++         * Uses GPU for inference. The advanced GPU configuration settings will be set to default
++         * values.
++         *
++         * <p>Note: this method will override the settings from {@link #setComputeSettings}.
++         *
++         * <p>To manipulate the advanced GPU configuration settings, use {@link
++         * #setComputeSettings}.
++         */
++        public Builder useGpu() {
++            return setComputeSettings(
++                    ComputeSettings.builder().setDelegate(ComputeSettings.Delegate.GPU).build());
++        }
+ 
+-    /**
+-     * Uses GPU for inference. The advanced GPU configuration settings will be set to default
+-     * values.
+-     *
+-     * <p>Note: this method will override the settings from {@link #setComputeSettings}.
+-     *
+-     * <p>To manipulate the advanced GPU configuration settings, use {@link #setComputeSettings}.
+-     */
+-    public Builder useGpu() {
+-      return setComputeSettings(
+-          ComputeSettings.builder().setDelegate(ComputeSettings.Delegate.GPU).build());
+-    }
++        /**
++         * Uses NNAPI for inference. The advanced NNAPI configuration settings will be set to
++         * default values.
++         *
++         * <p>Note: this method will override the settings from {@link #setComputeSettings}.
++         *
++         * <p>To manipulate the advanced NNAPI configuration settings, use {@link
++         * #setComputeSettings}.
++         */
++        public Builder useNnapi() {
++            return setComputeSettings(
++                    ComputeSettings.builder().setDelegate(ComputeSettings.Delegate.NNAPI).build());
++        }
+ 
+-    /**
+-     * Uses NNAPI for inference. The advanced NNAPI configuration settings will be set to default
+-     * values.
+-     *
+-     * <p>Note: this method will override the settings from {@link #setComputeSettings}.
+-     *
+-     * <p>To manipulate the advanced NNAPI configuration settings, use {@link #setComputeSettings}.
+-     */
+-    public Builder useNnapi() {
+-      return setComputeSettings(
+-          ComputeSettings.builder().setDelegate(ComputeSettings.Delegate.NNAPI).build());
++        public abstract BaseOptions build();
+     }
+ 
+-    public abstract BaseOptions build();
+-  }
+-
+-  public static Builder builder() {
+-    return new AutoValue_BaseOptions.Builder()
+-        .setComputeSettings(ComputeSettings.builder().build())
+-        .setNumThreads(DEFAULT_NUM_THREADS);
+-  }
++    public static Builder builder() {
++        return new AutoValue_BaseOptions.Builder()
++                .setComputeSettings(ComputeSettings.builder().build())
++                .setNumThreads(DEFAULT_NUM_THREADS);
++    }
+ 
+-  abstract ComputeSettings getComputeSettings();
++    abstract ComputeSettings getComputeSettings();
+ 
+-  abstract int getNumThreads();
++    abstract int getNumThreads();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseTaskApi.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseTaskApi.java
+index b3fe9def83c69..a8ae65cd1cf3b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseTaskApi.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseTaskApi.java
+@@ -16,76 +16,78 @@ limitations under the License.
+ package org.tensorflow.lite.task.core;
+ 
+ import android.util.Log;
++
+ import java.io.Closeable;
+ 
+ /**
+  * Base class for Task API, provides shared logic to load/unload native libs to its C++ counterpart.
+  */
+ public abstract class BaseTaskApi implements Closeable {
+-  private static final String TAG = BaseTaskApi.class.getSimpleName();
+-
+-  /**
+-   * Represents a pointer to the corresponding C++ task_api object. The nativeHandle pointer is
+-   * initialized from subclasses and must be released by calling {@link #deinit} after it is no
+-   * longer needed.
+-   */
+-  private final long nativeHandle;
+-
+-  /** Indicates whether the {@link #nativeHandle} pointer has been released yet. */
+-  private boolean closed;
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++.
+-   */
+-  protected BaseTaskApi(long nativeHandle) {
+-    if (nativeHandle == TaskJniUtils.INVALID_POINTER) {
+-      throw new IllegalArgumentException("Failed to load C++ pointer from JNI");
++    private static final String TAG = BaseTaskApi.class.getSimpleName();
++
++    /**
++     * Represents a pointer to the corresponding C++ task_api object. The nativeHandle pointer is
++     * initialized from subclasses and must be released by calling {@link #deinit} after it is no
++     * longer needed.
++     */
++    private final long nativeHandle;
++
++    /** Indicates whether the {@link #nativeHandle} pointer has been released yet. */
++    private boolean closed;
++
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++.
++     */
++    protected BaseTaskApi(long nativeHandle) {
++        if (nativeHandle == TaskJniUtils.INVALID_POINTER) {
++            throw new IllegalArgumentException("Failed to load C++ pointer from JNI");
++        }
++        this.nativeHandle = nativeHandle;
++    }
++
++    public boolean isClosed() {
++        return closed;
+     }
+-    this.nativeHandle = nativeHandle;
+-  }
+-
+-  public boolean isClosed() {
+-    return closed;
+-  }
+-
+-  /** Release the memory allocated from C++ and deregister the library from the static holder. */
+-  @Override
+-  public synchronized void close() {
+-    if (closed) {
+-      return;
++
++    /** Release the memory allocated from C++ and deregister the library from the static holder. */
++    @Override
++    public synchronized void close() {
++        if (closed) {
++            return;
++        }
++        deinit(nativeHandle);
++        closed = true;
+     }
+-    deinit(nativeHandle);
+-    closed = true;
+-  }
+ 
+-  public long getNativeHandle() {
+-    return nativeHandle;
+-  }
++    public long getNativeHandle() {
++        return nativeHandle;
++    }
+ 
+-  protected void checkNotClosed() {
+-    if (isClosed()) {
+-      throw new IllegalStateException("Internal error: The task lib has already been closed.");
++    protected void checkNotClosed() {
++        if (isClosed()) {
++            throw new IllegalStateException(
++                    "Internal error: The task lib has already been closed.");
++        }
+     }
+-  }
+-
+-  @Override
+-  protected void finalize() throws Throwable {
+-    try {
+-      if (!closed) {
+-        Log.w(TAG, "Closing an already closed native lib");
+-        close();
+-      }
+-    } finally {
+-      super.finalize();
++
++    @Override
++    protected void finalize() throws Throwable {
++        try {
++            if (!closed) {
++                Log.w(TAG, "Closing an already closed native lib");
++                close();
++            }
++        } finally {
++            super.finalize();
++        }
+     }
+-  }
+-
+-  /**
+-   * Releases memory pointed by the pointer in the native layer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  protected abstract void deinit(long nativeHandle);
++
++    /**
++     * Releases memory pointed by the pointer in the native layer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    protected abstract void deinit(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java
+index 80a9e82ff3802..0c2d04283594d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java
+@@ -20,38 +20,36 @@ import com.google.auto.value.AutoValue;
+ /** Options to configure how to accelerate the model inference using dedicated delegates. */
+ @AutoValue
+ public abstract class ComputeSettings {
++    /** TFLite accelerator delegate options. */
++    public enum Delegate {
++        NONE(0),
++        NNAPI(1),
++        GPU(2);
+ 
+-  /** TFLite accelerator delegate options. */
+-  public enum Delegate {
+-    NONE(0),
+-    NNAPI(1),
+-    GPU(2);
++        private final int value;
+ 
+-    private final int value;
++        Delegate(int value) {
++            this.value = value;
++        }
+ 
+-    Delegate(int value) {
+-      this.value = value;
++        public int getValue() {
++            return value;
++        }
+     }
+ 
+-    public int getValue() {
+-      return value;
+-    }
+-  }
+-
+-  /** Builder for {@link ComputeSettings}. */
+-  @AutoValue.Builder
+-  public abstract static class Builder {
+-
+-    public abstract Builder setDelegate(Delegate delegate);
++    /** Builder for {@link ComputeSettings}. */
++    @AutoValue.Builder
++    public abstract static class Builder {
++        public abstract Builder setDelegate(Delegate delegate);
+ 
+-    public abstract ComputeSettings build();
+-  }
++        public abstract ComputeSettings build();
++    }
+ 
+-  public static Builder builder() {
+-    return new AutoValue_ComputeSettings.Builder().setDelegate(DEFAULT_DELEGATE);
+-  }
++    public static Builder builder() {
++        return new AutoValue_ComputeSettings.Builder().setDelegate(DEFAULT_DELEGATE);
++    }
+ 
+-  public abstract Delegate getDelegate();
++    public abstract Delegate getDelegate();
+ 
+-  private static final Delegate DEFAULT_DELEGATE = Delegate.NONE;
++    private static final Delegate DEFAULT_DELEGATE = Delegate.NONE;
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java
+index 76109f453b01f..9d5b775456c43 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java
+@@ -18,6 +18,7 @@ package org.tensorflow.lite.task.core;
+ import android.content.Context;
+ import android.content.res.AssetFileDescriptor;
+ import android.util.Log;
++
+ import java.io.FileInputStream;
+ import java.io.IOException;
+ import java.nio.ByteBuffer;
+@@ -26,156 +27,146 @@ import java.nio.channels.FileChannel;
+ 
+ /** JNI utils for Task API. */
+ public class TaskJniUtils {
+-  public static final long INVALID_POINTER = 0;
+-  private static final String TAG = TaskJniUtils.class.getSimpleName();
+-  /** Syntax sugar to get nativeHandle from empty param list. */
+-  public interface EmptyHandleProvider {
+-    long createHandle();
+-  }
+-
+-  /** Syntax sugar to get nativeHandle from an array of {@link ByteBuffer}s. */
+-  public interface MultipleBuffersHandleProvider {
+-    long createHandle(ByteBuffer... buffers);
+-  }
+-
+-  /** Syntax sugar to get nativeHandle from file descriptor and options. */
+-  public interface FdAndOptionsHandleProvider<T> {
+-    long createHandle(
+-        int fileDescriptor, long fileDescriptorLength, long fileDescriptorOffset, T options);
+-  }
+-
+-  /**
+-   * Initializes the JNI and returns C++ handle with file descriptor and options for task API.
+-   *
+-   * @param context the Android app context
+-   * @param provider provider to get C++ handle, usually returned from native call
+-   * @param libName name of C++ lib to be loaded
+-   * @param filePath path of the file to be loaded
+-   * @param options options to set up the task API, used by the provider
+-   * @return C++ handle as long
+-   * @throws IOException If model file fails to load.
+-   */
+-  public static <T> long createHandleFromFdAndOptions(
+-      Context context,
+-      final FdAndOptionsHandleProvider<T> provider,
+-      String libName,
+-      String filePath,
+-      final T options)
+-      throws IOException {
+-    try (AssetFileDescriptor assetFileDescriptor = context.getAssets().openFd(filePath)) {
+-      return createHandleFromLibrary(
+-          new EmptyHandleProvider() {
++    public static final long INVALID_POINTER = 0;
++    private static final String TAG = TaskJniUtils.class.getSimpleName();
++    /** Syntax sugar to get nativeHandle from empty param list. */
++    public interface EmptyHandleProvider {
++        long createHandle();
++    }
++
++    /** Syntax sugar to get nativeHandle from an array of {@link ByteBuffer}s. */
++    public interface MultipleBuffersHandleProvider {
++        long createHandle(ByteBuffer... buffers);
++    }
++
++    /** Syntax sugar to get nativeHandle from file descriptor and options. */
++    public interface FdAndOptionsHandleProvider<T> {
++        long createHandle(int fileDescriptor, long fileDescriptorLength, long fileDescriptorOffset,
++                T options);
++    }
++
++    /**
++     * Initializes the JNI and returns C++ handle with file descriptor and options for task API.
++     *
++     * @param context the Android app context
++     * @param provider provider to get C++ handle, usually returned from native call
++     * @param libName name of C++ lib to be loaded
++     * @param filePath path of the file to be loaded
++     * @param options options to set up the task API, used by the provider
++     * @return C++ handle as long
++     * @throws IOException If model file fails to load.
++     */
++    public static <T> long createHandleFromFdAndOptions(Context context,
++            final FdAndOptionsHandleProvider<T> provider, String libName, String filePath,
++            final T options) throws IOException {
++        try (AssetFileDescriptor assetFileDescriptor = context.getAssets().openFd(filePath)) {
++            return createHandleFromLibrary(new EmptyHandleProvider() {
++                @Override
++                public long createHandle() {
++                    return provider.createHandle(
++                            /*fileDescriptor=*/assetFileDescriptor.getParcelFileDescriptor()
++                                    .getFd(),
++                            /*fileDescriptorLength=*/assetFileDescriptor.getLength(),
++                            /*fileDescriptorOffset=*/assetFileDescriptor.getStartOffset(), options);
++                }
++            }, libName);
++        }
++    }
++
++    /**
++     * Initializes the JNI and returns C++ handle by first loading the C++ library and then invokes
++     * {@link EmptyHandleProvider#createHandle()}.
++     *
++     * @param provider provider to get C++ handle, usually returned from native call
++     * @return C++ handle as long
++     */
++    public static long createHandleFromLibrary(EmptyHandleProvider provider, String libName) {
++        tryLoadLibrary(libName);
++        try {
++            return provider.createHandle();
++        } catch (RuntimeException e) {
++            String errorMessage = "Error getting native address of native library: " + libName;
++            Log.e(TAG, errorMessage, e);
++            throw new IllegalStateException(errorMessage, e);
++        }
++    }
++
++    /**
++     * Initializes the JNI and returns C++ handle by first loading the C++ library and then invokes
++     * {@link MultipleBuffersHandleProvider#createHandle(ByteBuffer...)}.
++     *
++     * @param context app context
++     * @param provider provider to get C++ pointer, usually returned from native call
++     * @param libName name of C++ lib to load
++     * @param filePaths file paths to load
++     * @return C++ pointer as long
++     * @throws IOException If model file fails to load.
++     */
++    public static long createHandleWithMultipleAssetFilesFromLibrary(Context context,
++            final MultipleBuffersHandleProvider provider, String libName, String... filePaths)
++            throws IOException {
++        final MappedByteBuffer[] buffers = new MappedByteBuffer[filePaths.length];
++        for (int i = 0; i < filePaths.length; i++) {
++            buffers[i] = loadMappedFile(context, filePaths[i]);
++        }
++        return createHandleFromLibrary(new EmptyHandleProvider() {
+             @Override
+             public long createHandle() {
+-              return provider.createHandle(
+-                  /*fileDescriptor=*/ assetFileDescriptor.getParcelFileDescriptor().getFd(),
+-                  /*fileDescriptorLength=*/ assetFileDescriptor.getLength(),
+-                  /*fileDescriptorOffset=*/ assetFileDescriptor.getStartOffset(),
+-                  options);
++                return provider.createHandle(buffers);
+             }
+-          },
+-          libName);
+-    }
+-  }
+-
+-  /**
+-   * Initializes the JNI and returns C++ handle by first loading the C++ library and then invokes
+-   * {@link EmptyHandleProvider#createHandle()}.
+-   *
+-   * @param provider provider to get C++ handle, usually returned from native call
+-   * @return C++ handle as long
+-   */
+-  public static long createHandleFromLibrary(EmptyHandleProvider provider, String libName) {
+-    tryLoadLibrary(libName);
+-    try {
+-      return provider.createHandle();
+-    } catch (RuntimeException e) {
+-      String errorMessage = "Error getting native address of native library: " + libName;
+-      Log.e(TAG, errorMessage, e);
+-      throw new IllegalStateException(errorMessage, e);
+-    }
+-  }
+-
+-  /**
+-   * Initializes the JNI and returns C++ handle by first loading the C++ library and then invokes
+-   * {@link MultipleBuffersHandleProvider#createHandle(ByteBuffer...)}.
+-   *
+-   * @param context app context
+-   * @param provider provider to get C++ pointer, usually returned from native call
+-   * @param libName name of C++ lib to load
+-   * @param filePaths file paths to load
+-   * @return C++ pointer as long
+-   * @throws IOException If model file fails to load.
+-   */
+-  public static long createHandleWithMultipleAssetFilesFromLibrary(
+-      Context context,
+-      final MultipleBuffersHandleProvider provider,
+-      String libName,
+-      String... filePaths)
+-      throws IOException {
+-    final MappedByteBuffer[] buffers = new MappedByteBuffer[filePaths.length];
+-    for (int i = 0; i < filePaths.length; i++) {
+-      buffers[i] = loadMappedFile(context, filePaths[i]);
++        }, libName);
+     }
+-    return createHandleFromLibrary(
+-        new EmptyHandleProvider() {
+-          @Override
+-          public long createHandle() {
+-            return provider.createHandle(buffers);
+-          }
+-        },
+-        libName);
+-  }
+-
+-  /**
+-   * Loads a file from the asset folder through memory mapping.
+-   *
+-   * @param context Application context to access assets.
+-   * @param filePath Asset path of the file.
+-   * @return the loaded memory mapped file.
+-   * @throws IOException If model file fails to load.
+-   */
+-  public static MappedByteBuffer loadMappedFile(Context context, String filePath)
+-      throws IOException {
+-    try (AssetFileDescriptor fileDescriptor = context.getAssets().openFd(filePath);
+-        FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor())) {
+-      FileChannel fileChannel = inputStream.getChannel();
+-      long startOffset = fileDescriptor.getStartOffset();
+-      long declaredLength = fileDescriptor.getDeclaredLength();
+-      return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
++
++    /**
++     * Loads a file from the asset folder through memory mapping.
++     *
++     * @param context Application context to access assets.
++     * @param filePath Asset path of the file.
++     * @return the loaded memory mapped file.
++     * @throws IOException If model file fails to load.
++     */
++    public static MappedByteBuffer loadMappedFile(Context context, String filePath)
++            throws IOException {
++        try (AssetFileDescriptor fileDescriptor = context.getAssets().openFd(filePath);
++                FileInputStream inputStream =
++                        new FileInputStream(fileDescriptor.getFileDescriptor())) {
++            FileChannel fileChannel = inputStream.getChannel();
++            long startOffset = fileDescriptor.getStartOffset();
++            long declaredLength = fileDescriptor.getDeclaredLength();
++            return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
++        }
+     }
+-  }
+-
+-  /**
+-   * Try loading a native library, if it's already loaded return directly.
+-   *
+-   * @param libName name of the lib
+-   */
+-  public static void tryLoadLibrary(String libName) {
+-    try {
+-      System.loadLibrary(libName);
+-    } catch (UnsatisfiedLinkError e) {
+-      String errorMessage = "Error loading native library: " + libName;
+-      Log.e(TAG, errorMessage, e);
+-      throw new UnsatisfiedLinkError(errorMessage);
++
++    /**
++     * Try loading a native library, if it's already loaded return directly.
++     *
++     * @param libName name of the lib
++     */
++    public static void tryLoadLibrary(String libName) {
++        try {
++            System.loadLibrary(libName);
++        } catch (UnsatisfiedLinkError e) {
++            String errorMessage = "Error loading native library: " + libName;
++            Log.e(TAG, errorMessage, e);
++            throw new UnsatisfiedLinkError(errorMessage);
++        }
+     }
+-  }
+ 
+-  public static long createProtoBaseOptionsHandle(BaseOptions baseOptions) {
+-    return createProtoBaseOptionsHandleWithLegacyNumThreads(baseOptions, /*legacyNumThreads =*/ -1);
+-  }
++    public static long createProtoBaseOptionsHandle(BaseOptions baseOptions) {
++        return createProtoBaseOptionsHandleWithLegacyNumThreads(
++                baseOptions, /*legacyNumThreads =*/-1);
++    }
+ 
+-  public static long createProtoBaseOptionsHandleWithLegacyNumThreads(
+-      BaseOptions baseOptions, int legacyNumThreads) {
+-    // NumThreads should be configured through BaseOptions. However, if NumThreads is configured
+-    // through the legacy API of the Task Java API (then it will not equal to -1, the default
+-    // value), use it to overide the one in baseOptions.
+-    return createProtoBaseOptions(
+-        baseOptions.getComputeSettings().getDelegate().getValue(),
+-        legacyNumThreads == -1 ? baseOptions.getNumThreads() : legacyNumThreads);
+-  }
++    public static long createProtoBaseOptionsHandleWithLegacyNumThreads(
++            BaseOptions baseOptions, int legacyNumThreads) {
++        // NumThreads should be configured through BaseOptions. However, if NumThreads is configured
++        // through the legacy API of the Task Java API (then it will not equal to -1, the default
++        // value), use it to overide the one in baseOptions.
++        return createProtoBaseOptions(baseOptions.getComputeSettings().getDelegate().getValue(),
++                legacyNumThreads == -1 ? baseOptions.getNumThreads() : legacyNumThreads);
++    }
+ 
+-  private TaskJniUtils() {}
++    private TaskJniUtils() {}
+ 
+-  private static native long createProtoBaseOptions(int delegate, int numThreads);
++    private static native long createProtoBaseOptions(int delegate, int numThreads);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java
+index 287ba444c386b..b1784d02f2362 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.task.core.vision;
+ 
+ import android.graphics.Rect;
++
+ import com.google.auto.value.AutoValue;
+ 
+ /**
+@@ -45,74 +46,74 @@ import com.google.auto.value.AutoValue;
+  */
+ @AutoValue
+ public abstract class ImageProcessingOptions {
+-
+-  /**
+-   * Orientation type that follows EXIF specification.
+-   *
+-   * <p>The name of each enum value defines the position of the 0th row and the 0th column of the
+-   * image content. See the <a href="http://jpegclub.org/exif_orientation.html">EXIF orientation
+-   * documentation</a> for details.
+-   */
+-  public enum Orientation {
+-    TOP_LEFT(0),
+-    TOP_RIGHT(1),
+-    BOTTOM_RIGHT(2),
+-    BOTTOM_LEFT(3),
+-    LEFT_TOP(4),
+-    RIGHT_TOP(5),
+-    RIGHT_BOTTOM(6),
+-    LEFT_BOTTOM(7);
+-
+-    private final int value;
+-
+-    Orientation(int value) {
+-      this.value = value;
+-    }
+-
+-    public int getValue() {
+-      return value;
+-    }
+-  };
+-
+-  private static final Rect defaultRoi = new Rect();
+-  private static final Orientation DEFAULT_ORIENTATION = Orientation.TOP_LEFT;
+-
+-  public abstract Rect getRoi();
+-
+-  public abstract Orientation getOrientation();
+-
+-  public static Builder builder() {
+-    return new AutoValue_ImageProcessingOptions.Builder()
+-        .setRoi(defaultRoi)
+-        .setOrientation(DEFAULT_ORIENTATION);
+-  }
+-
+-  /** Builder for {@link ImageProcessingOptions}. */
+-  @AutoValue.Builder
+-  public abstract static class Builder {
+-
+     /**
+-     * Sets the region of interest (ROI) of the image. Defaults to the entire image.
++     * Orientation type that follows EXIF specification.
+      *
+-     * <p>Cropping according to this region of interest is prepended to the pre-processing
+-     * operations.
++     * <p>The name of each enum value defines the position of the 0th row and the 0th column of the
++     * image content. See the <a href="http://jpegclub.org/exif_orientation.html">EXIF orientation
++     * documentation</a> for details.
+      */
+-    public abstract Builder setRoi(Rect roi);
++    public enum Orientation {
++        TOP_LEFT(0),
++        TOP_RIGHT(1),
++        BOTTOM_RIGHT(2),
++        BOTTOM_LEFT(3),
++        LEFT_TOP(4),
++        RIGHT_TOP(5),
++        RIGHT_BOTTOM(6),
++        LEFT_BOTTOM(7);
++
++        private final int value;
++
++        Orientation(int value) {
++            this.value = value;
++        }
++
++        public int getValue() {
++            return value;
++        }
++    }
++    ;
+ 
+-    /**
+-     * Sets the orientation of the image. Defaults to {@link Orientation#TOP_LEFT}.
+-     *
+-     * <p>Rotation will be applied accordingly so that inference is performed on an "upright" image.
+-     */
+-    public abstract Builder setOrientation(Orientation orientation);
++    private static final Rect defaultRoi = new Rect();
++    private static final Orientation DEFAULT_ORIENTATION = Orientation.TOP_LEFT;
+ 
+-    abstract Rect getRoi();
++    public abstract Rect getRoi();
+ 
+-    abstract ImageProcessingOptions autoBuild();
++    public abstract Orientation getOrientation();
++
++    public static Builder builder() {
++        return new AutoValue_ImageProcessingOptions.Builder()
++                .setRoi(defaultRoi)
++                .setOrientation(DEFAULT_ORIENTATION);
++    }
+ 
+-    public ImageProcessingOptions build() {
+-      setRoi(new Rect(getRoi())); // Make a defensive copy, since Rect is mutable.
+-      return autoBuild();
++    /** Builder for {@link ImageProcessingOptions}. */
++    @AutoValue.Builder
++    public abstract static class Builder {
++        /**
++         * Sets the region of interest (ROI) of the image. Defaults to the entire image.
++         *
++         * <p>Cropping according to this region of interest is prepended to the pre-processing
++         * operations.
++         */
++        public abstract Builder setRoi(Rect roi);
++
++        /**
++         * Sets the orientation of the image. Defaults to {@link Orientation#TOP_LEFT}.
++         *
++         * <p>Rotation will be applied accordingly so that inference is performed on an "upright"
++         * image.
++         */
++        public abstract Builder setOrientation(Orientation orientation);
++
++        abstract Rect getRoi();
++
++        abstract ImageProcessingOptions autoBuild();
++
++        public ImageProcessingOptions build() {
++            setRoi(new Rect(getRoi())); // Make a defensive copy, since Rect is mutable.
++            return autoBuild();
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java
+index d0ac3f83b4ed5..ce912c96e29de 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java
+@@ -17,12 +17,9 @@ package org.tensorflow.lite.task.text.nlclassifier;
+ 
+ import android.content.Context;
+ import android.os.ParcelFileDescriptor;
++
+ import com.google.auto.value.AutoValue;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.MappedByteBuffer;
+-import java.util.List;
++
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ import org.tensorflow.lite.support.label.Category;
+ import org.tensorflow.lite.task.core.BaseOptions;
+@@ -30,6 +27,12 @@ import org.tensorflow.lite.task.core.BaseTaskApi;
+ import org.tensorflow.lite.task.core.TaskJniUtils;
+ import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.MappedByteBuffer;
++import java.util.List;
++
+ /**
+  * Classifier API for NLClassification tasks with Bert models, categorizes string into different
+  * classes. The API expects a Bert based TFLite model with metadata populated.
+@@ -45,209 +48,199 @@ import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+  * </ul>
+  */
+ public class BertNLClassifier extends BaseTaskApi {
++    private static final String BERT_NL_CLASSIFIER_NATIVE_LIBNAME = "task_text_jni";
++
++    /** Options to configure BertNLClassifier. */
++    @AutoValue
++    @UsedByReflection("bert_nl_classifier_jni.cc")
++    public abstract static class BertNLClassifierOptions {
++        static final int DEFAULT_MAX_SEQ_LEN = 128;
++
++        abstract int getMaxSeqLen();
++
++        abstract BaseOptions getBaseOptions();
++
++        public static Builder builder() {
++            return new AutoValue_BertNLClassifier_BertNLClassifierOptions.Builder()
++                    .setMaxSeqLen(DEFAULT_MAX_SEQ_LEN)
++                    .setBaseOptions(BaseOptions.builder().build());
++        }
++
++        /** Builder for {@link BertNLClassifierOptions}. */
++        @AutoValue.Builder
++        public abstract static class Builder {
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public abstract Builder setBaseOptions(BaseOptions baseOptions);
++
++            /**
++             * Set the maximum sequence length.
++             *
++             * @deprecated maximum sequence length is now read from the model (i.e. input tensor
++             *         size)
++             *     automatically
++             */
++            @Deprecated
++            public abstract Builder setMaxSeqLen(int value);
++
++            public abstract BertNLClassifierOptions build();
++        }
++    }
+ 
+-  private static final String BERT_NL_CLASSIFIER_NATIVE_LIBNAME = "task_text_jni";
+-
+-  /** Options to configure BertNLClassifier. */
+-  @AutoValue
+-  @UsedByReflection("bert_nl_classifier_jni.cc")
+-  public abstract static class BertNLClassifierOptions {
+-    static final int DEFAULT_MAX_SEQ_LEN = 128;
+-
+-    abstract int getMaxSeqLen();
++    /**
++     * Creates {@link BertNLClassifier} from a model file with metadata and default {@link
++     * BertNLClassifierOptions}.
++     *
++     * @param context Android context
++     * @param modelPath Path to the classification model
++     * @return a {@link BertNLClassifier} instance
++     * @throws IOException If model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertNLClassifier createFromFile(final Context context, final String modelPath)
++            throws IOException {
++        return createFromBuffer(TaskJniUtils.loadMappedFile(context, modelPath));
++    }
+ 
+-    abstract BaseOptions getBaseOptions();
++    /**
++     * Creates {@link BertNLClassifier} from a {@link File} object with metadata and default {@link
++     * BertNLClassifierOptions}.
++     *
++     * @param modelFile The classification model {@link File} instance
++     * @return a {@link BertNLClassifier} instance
++     * @throws IOException If model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertNLClassifier createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, BertNLClassifierOptions.builder().build());
++    }
+ 
+-    public static Builder builder() {
+-      return new AutoValue_BertNLClassifier_BertNLClassifierOptions.Builder()
+-          .setMaxSeqLen(DEFAULT_MAX_SEQ_LEN)
+-          .setBaseOptions(BaseOptions.builder().build());
++    /**
++     * Creates {@link BertNLClassifier} from a model file with metadata and {@link
++     * BertNLClassifierOptions}.
++     *
++     * @param context Android context.
++     * @param modelPath Path to the classification model
++     * @param options to configure the classifier
++     * @return a {@link BertNLClassifier} instance
++     * @throws IOException If model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertNLClassifier createFromFileAndOptions(final Context context,
++            final String modelPath, BertNLClassifierOptions options) throws IOException {
++        return createFromBufferAndOptions(TaskJniUtils.loadMappedFile(context, modelPath), options);
+     }
+ 
+-    /** Builder for {@link BertNLClassifierOptions}. */
+-    @AutoValue.Builder
+-    public abstract static class Builder {
++    /**
++     * Creates {@link BertNLClassifier} from a {@link File} object with metadata and {@link
++     * BertNLClassifierOptions}.
++     *
++     * @param modelFile The classification model {@link File} instance
++     * @param options to configure the classifier
++     * @return a {@link BertNLClassifier} instance
++     * @throws IOException If model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertNLClassifier createFromFileAndOptions(
++            File modelFile, final BertNLClassifierOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return new BertNLClassifier(
++                    TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++                        @Override
++                        public long createHandle() {
++                            return initJniWithFileDescriptor(descriptor.getFd(), options,
++                                    TaskJniUtils.createProtoBaseOptionsHandle(
++                                            options.getBaseOptions()));
++                        }
++                    }, BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
++        }
++    }
+ 
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public abstract Builder setBaseOptions(BaseOptions baseOptions);
++    /**
++     * Creates {@link BertNLClassifier} with a model buffer and default {@link
++     * BertNLClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the model
++     * @return a {@link BertNLClassifier} instance
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertNLClassifier createFromBuffer(final ByteBuffer modelBuffer) {
++        return createFromBufferAndOptions(modelBuffer, BertNLClassifierOptions.builder().build());
++    }
+ 
+-      /**
+-       * Set the maximum sequence length.
+-       *
+-       * @deprecated maximum sequence length is now read from the model (i.e. input tensor size)
+-       *     automatically
+-       */
+-      @Deprecated
+-      public abstract Builder setMaxSeqLen(int value);
++    /**
++     * Creates {@link BertNLClassifier} with a model buffer and {@link BertNLClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the model
++     * @param options to configure the classifier
++     * @return a {@link BertNLClassifier} instance
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertNLClassifier createFromBufferAndOptions(
++            final ByteBuffer modelBuffer, final BertNLClassifierOptions options) {
++        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
++            throw new IllegalArgumentException(
++                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++        }
++        return new BertNLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                return initJniWithByteBuffer(modelBuffer, options,
++                        TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
++            }
++        }, BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
++    }
+ 
+-      public abstract BertNLClassifierOptions build();
++    /**
++     * Performs classification on a string input, returns classified {@link Category}s.
++     *
++     * @param text input text to the model.
++     * @return A list of Category results.
++     */
++    public List<Category> classify(String text) {
++        return classifyNative(getNativeHandle(), text);
+     }
+-  }
+-
+-  /**
+-   * Creates {@link BertNLClassifier} from a model file with metadata and default {@link
+-   * BertNLClassifierOptions}.
+-   *
+-   * @param context Android context
+-   * @param modelPath Path to the classification model
+-   * @return a {@link BertNLClassifier} instance
+-   * @throws IOException If model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertNLClassifier createFromFile(final Context context, final String modelPath)
+-      throws IOException {
+-    return createFromBuffer(TaskJniUtils.loadMappedFile(context, modelPath));
+-  }
+-
+-  /**
+-   * Creates {@link BertNLClassifier} from a {@link File} object with metadata and default {@link
+-   * BertNLClassifierOptions}.
+-   *
+-   * @param modelFile The classification model {@link File} instance
+-   * @return a {@link BertNLClassifier} instance
+-   * @throws IOException If model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertNLClassifier createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, BertNLClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates {@link BertNLClassifier} from a model file with metadata and {@link
+-   * BertNLClassifierOptions}.
+-   *
+-   * @param context Android context.
+-   * @param modelPath Path to the classification model
+-   * @param options to configure the classifier
+-   * @return a {@link BertNLClassifier} instance
+-   * @throws IOException If model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertNLClassifier createFromFileAndOptions(
+-      final Context context, final String modelPath, BertNLClassifierOptions options)
+-      throws IOException {
+-    return createFromBufferAndOptions(TaskJniUtils.loadMappedFile(context, modelPath), options);
+-  }
+-
+-  /**
+-   * Creates {@link BertNLClassifier} from a {@link File} object with metadata and {@link
+-   * BertNLClassifierOptions}.
+-   *
+-   * @param modelFile The classification model {@link File} instance
+-   * @param options to configure the classifier
+-   * @return a {@link BertNLClassifier} instance
+-   * @throws IOException If model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertNLClassifier createFromFileAndOptions(
+-      File modelFile, final BertNLClassifierOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return new BertNLClassifier(
+-          TaskJniUtils.createHandleFromLibrary(
+-              new EmptyHandleProvider() {
+-                @Override
+-                public long createHandle() {
+-                  return initJniWithFileDescriptor(
+-                      descriptor.getFd(),
+-                      options,
+-                      TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-                }
+-              },
+-              BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
++
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++.
++     */
++    private BertNLClassifier(long nativeHandle) {
++        super(nativeHandle);
+     }
+-  }
+-
+-  /**
+-   * Creates {@link BertNLClassifier} with a model buffer and default {@link
+-   * BertNLClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the model
+-   * @return a {@link BertNLClassifier} instance
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertNLClassifier createFromBuffer(final ByteBuffer modelBuffer) {
+-    return createFromBufferAndOptions(modelBuffer, BertNLClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates {@link BertNLClassifier} with a model buffer and {@link BertNLClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the model
+-   * @param options to configure the classifier
+-   * @return a {@link BertNLClassifier} instance
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertNLClassifier createFromBufferAndOptions(
+-      final ByteBuffer modelBuffer, final BertNLClassifierOptions options) {
+-    if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+-      throw new IllegalArgumentException(
+-          "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++
++    private static native long initJniWithByteBuffer(
++            ByteBuffer modelBuffer, BertNLClassifierOptions options, long baseOptionsHandle);
++
++    private static native long initJniWithFileDescriptor(
++            int fd, BertNLClassifierOptions options, long baseOptionsHandle);
++
++    private static native List<Category> classifyNative(long nativeHandle, String text);
++
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
+     }
+-    return new BertNLClassifier(
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                return initJniWithByteBuffer(
+-                    modelBuffer,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-              }
+-            },
+-            BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
+-  }
+-
+-  /**
+-   * Performs classification on a string input, returns classified {@link Category}s.
+-   *
+-   * @param text input text to the model.
+-   * @return A list of Category results.
+-   */
+-  public List<Category> classify(String text) {
+-    return classifyNative(getNativeHandle(), text);
+-  }
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++.
+-   */
+-  private BertNLClassifier(long nativeHandle) {
+-    super(nativeHandle);
+-  }
+-
+-  private static native long initJniWithByteBuffer(
+-      ByteBuffer modelBuffer, BertNLClassifierOptions options, long baseOptionsHandle);
+-
+-  private static native long initJniWithFileDescriptor(
+-      int fd, BertNLClassifierOptions options, long baseOptionsHandle);
+-
+-  private static native List<Category> classifyNative(long nativeHandle, String text);
+-
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
+-
+-  /**
+-   * Native implementation to release memory pointed by the pointer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private native void deinitJni(long nativeHandle);
++
++    /**
++     * Native implementation to release memory pointed by the pointer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java
+index ff573bf415759..b8aa32be94dc5 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java
+@@ -17,13 +17,11 @@ package org.tensorflow.lite.task.text.nlclassifier;
+ 
+ import android.content.Context;
+ import android.os.ParcelFileDescriptor;
++
+ import androidx.annotation.Nullable;
++
+ import com.google.auto.value.AutoValue;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.MappedByteBuffer;
+-import java.util.List;
++
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ import org.tensorflow.lite.support.label.Category;
+ import org.tensorflow.lite.task.core.BaseOptions;
+@@ -31,6 +29,12 @@ import org.tensorflow.lite.task.core.BaseTaskApi;
+ import org.tensorflow.lite.task.core.TaskJniUtils;
+ import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.MappedByteBuffer;
++import java.util.List;
++
+ /**
+  * Classifier API for natural language classification tasks, categorizes string into different
+  * classes.
+@@ -67,294 +71,296 @@ import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+  * configurable for different TFLite models.
+  */
+ public class NLClassifier extends BaseTaskApi {
+-
+-  /** Options to identify input and output tensors of the model. */
+-  @AutoValue
+-  @UsedByReflection("nl_classifier_jni.cc")
+-  public abstract static class NLClassifierOptions {
+-    private static final int DEFAULT_INPUT_TENSOR_INDEX = 0;
+-    private static final int DEFAULT_OUTPUT_SCORE_TENSOR_INDEX = 0;
+-    // By default there is no output label tensor. The label file can be attached
+-    // to the output score tensor metadata.
+-    private static final int DEFAULT_OUTPUT_LABEL_TENSOR_INDEX = -1;
+-    private static final String DEFAULT_INPUT_TENSOR_NAME = "INPUT";
+-    private static final String DEFAULT_OUTPUT_SCORE_TENSOR_NAME = "OUTPUT_SCORE";
+-    private static final String DEFAULT_OUTPUT_LABEL_TENSOR_NAME = "OUTPUT_LABEL";
+-
+-    @UsedByReflection("nl_classifier_jni.cc")
+-    abstract int getInputTensorIndex();
+-
+-    @UsedByReflection("nl_classifier_jni.cc")
+-    abstract int getOutputScoreTensorIndex();
+-
++    /** Options to identify input and output tensors of the model. */
++    @AutoValue
+     @UsedByReflection("nl_classifier_jni.cc")
+-    abstract int getOutputLabelTensorIndex();
+-
+-    @UsedByReflection("nl_classifier_jni.cc")
+-    abstract String getInputTensorName();
++    public abstract static class NLClassifierOptions {
++        private static final int DEFAULT_INPUT_TENSOR_INDEX = 0;
++        private static final int DEFAULT_OUTPUT_SCORE_TENSOR_INDEX = 0;
++        // By default there is no output label tensor. The label file can be attached
++        // to the output score tensor metadata.
++        private static final int DEFAULT_OUTPUT_LABEL_TENSOR_INDEX = -1;
++        private static final String DEFAULT_INPUT_TENSOR_NAME = "INPUT";
++        private static final String DEFAULT_OUTPUT_SCORE_TENSOR_NAME = "OUTPUT_SCORE";
++        private static final String DEFAULT_OUTPUT_LABEL_TENSOR_NAME = "OUTPUT_LABEL";
++
++        @UsedByReflection("nl_classifier_jni.cc")
++        abstract int getInputTensorIndex();
++
++        @UsedByReflection("nl_classifier_jni.cc")
++        abstract int getOutputScoreTensorIndex();
++
++        @UsedByReflection("nl_classifier_jni.cc")
++        abstract int getOutputLabelTensorIndex();
++
++        @UsedByReflection("nl_classifier_jni.cc")
++        abstract String getInputTensorName();
++
++        @UsedByReflection("nl_classifier_jni.cc")
++        abstract String getOutputScoreTensorName();
++
++        @UsedByReflection("nl_classifier_jni.cc")
++        abstract String getOutputLabelTensorName();
++
++        @Nullable
++        abstract BaseOptions getBaseOptions();
++
++        public static Builder builder() {
++            return new AutoValue_NLClassifier_NLClassifierOptions.Builder()
++                    .setInputTensorIndex(DEFAULT_INPUT_TENSOR_INDEX)
++                    .setOutputScoreTensorIndex(DEFAULT_OUTPUT_SCORE_TENSOR_INDEX)
++                    .setOutputLabelTensorIndex(DEFAULT_OUTPUT_LABEL_TENSOR_INDEX)
++                    .setInputTensorName(DEFAULT_INPUT_TENSOR_NAME)
++                    .setOutputScoreTensorName(DEFAULT_OUTPUT_SCORE_TENSOR_NAME)
++                    .setOutputLabelTensorName(DEFAULT_OUTPUT_LABEL_TENSOR_NAME);
++        }
++
++        /** Builder for {@link NLClassifierOptions}. */
++        @AutoValue.Builder
++        public abstract static class Builder {
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public abstract Builder setBaseOptions(@Nullable BaseOptions baseOptions);
++
++            /**
++             * Configure the input/output tensors for NLClassifier:
++             *
++             * <p>- No special configuration is needed if the model has only one input tensor and
++             * one output tensor.
++             *
++             * <p>- When the model has multiple input or output tensors, use the following
++             * configurations to specifiy the desired tensors: <br>
++             * -- tensor names: {@code inputTensorName}, {@code outputScoreTensorName}, {@code
++             * outputLabelTensorName}<br>
++             * -- tensor indices: {@code inputTensorIndex}, {@code outputScoreTensorIndex}, {@code
++             * outputLabelTensorIndex} <br>
++             * Tensor names has higher priorities than tensor indices in locating the tensors. It
++             * means the tensors will be first located according to tensor names. If not found, then
++             * the tensors will be located according to tensor indices.
++             *
++             * <p>- Failing to match the input text tensor or output score tensor with neither
++             * tensor names nor tensor indices will trigger a runtime error. However, failing to
++             * locate the output label tensor will not trigger an error because the label tensor is
++             * optional.
++             */
++
++            /**
++             * Set the name of the input text tensor, if the model has multiple inputs. Only the
++             * input tensor specified will be used for inference; other input tensors will be
++             * ignored. Dafualt to {@code "INPUT"}.
++             *
++             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
++             * details.
++             */
++            public abstract Builder setInputTensorName(String inputTensorName);
++
++            /**
++             * Set the name of the output score tensor, if the model has multiple outputs. Dafualt
++             * to
++             * {@code "OUTPUT_SCORE"}.
++             *
++             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
++             * details.
++             */
++            public abstract Builder setOutputScoreTensorName(String outputScoreTensorName);
++
++            /**
++             * Set the name of the output label tensor, if the model has multiple outputs. Dafualt
++             * to
++             * {@code "OUTPUT_LABEL"}.
++             *
++             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
++             * details.
++             *
++             * <p>By default, label file should be packed with the output score tensor through Model
++             * Metadata. See the <a
++             * href="https://www.tensorflow.org/lite/convert/metadata_writer_tutorial#natural_language_classifiers">MetadataWriter
++             * for NLClassifier</a>. NLClassifier reads and parses labels from the label file
++             * automatically. However, some models may output a specific label tensor instead. In
++             * this case, NLClassifier reads labels from the output label tensor.
++             */
++            public abstract Builder setOutputLabelTensorName(String outputLabelTensorName);
++
++            /**
++             * Set the index of the input text tensor among all input tensors, if the model has
++             * multiple inputs. Only the input tensor specified will be used for inference; other
++             * input tensors will be ignored. Dafualt to 0.
++             *
++             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
++             * details.
++             */
++            public abstract Builder setInputTensorIndex(int inputTensorIndex);
++
++            /**
++             * Set the index of the output score tensor among all output tensors, if the model has
++             * multiple outputs. Dafualt to 0.
++             *
++             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
++             * details.
++             */
++            public abstract Builder setOutputScoreTensorIndex(int outputScoreTensorIndex);
++
++            /**
++             * Set the index of the optional output label tensor among all output tensors, if the
++             * model has multiple outputs.
++             *
++             * <p>See the document above {@code outputLabelTensorName} for more information about
++             * what the output label tensor is.
++             *
++             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
++             * details.
++             *
++             * <p>{@code outputLabelTensorIndex} dafualts to -1, meaning to disable the output label
++             * tensor.
++             */
++            public abstract Builder setOutputLabelTensorIndex(int outputLabelTensorIndex);
++
++            public abstract NLClassifierOptions build();
++        }
++    }
+ 
+-    @UsedByReflection("nl_classifier_jni.cc")
+-    abstract String getOutputScoreTensorName();
++    private static final String NL_CLASSIFIER_NATIVE_LIBNAME = "task_text_jni";
++
++    /**
++     * Creates {@link NLClassifier} from default {@link NLClassifierOptions}.
++     *
++     * @param context Android context
++     * @param modelPath path to the classification model relative to asset dir
++     * @return an {@link NLClassifier} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static NLClassifier createFromFile(Context context, String modelPath)
++            throws IOException {
++        return createFromFileAndOptions(context, modelPath, NLClassifierOptions.builder().build());
++    }
+ 
+-    @UsedByReflection("nl_classifier_jni.cc")
+-    abstract String getOutputLabelTensorName();
+-
+-    @Nullable
+-    abstract BaseOptions getBaseOptions();
+-
+-    public static Builder builder() {
+-      return new AutoValue_NLClassifier_NLClassifierOptions.Builder()
+-          .setInputTensorIndex(DEFAULT_INPUT_TENSOR_INDEX)
+-          .setOutputScoreTensorIndex(DEFAULT_OUTPUT_SCORE_TENSOR_INDEX)
+-          .setOutputLabelTensorIndex(DEFAULT_OUTPUT_LABEL_TENSOR_INDEX)
+-          .setInputTensorName(DEFAULT_INPUT_TENSOR_NAME)
+-          .setOutputScoreTensorName(DEFAULT_OUTPUT_SCORE_TENSOR_NAME)
+-          .setOutputLabelTensorName(DEFAULT_OUTPUT_LABEL_TENSOR_NAME);
++    /**
++     * Creates {@link NLClassifier} from default {@link NLClassifierOptions}.
++     *
++     * @param modelFile the classification model {@link File} instance
++     * @return an {@link NLClassifier} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static NLClassifier createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, NLClassifierOptions.builder().build());
+     }
+ 
+-    /** Builder for {@link NLClassifierOptions}. */
+-    @AutoValue.Builder
+-    public abstract static class Builder {
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public abstract Builder setBaseOptions(@Nullable BaseOptions baseOptions);
+-
+-      /**
+-       * Configure the input/output tensors for NLClassifier:
+-       *
+-       * <p>- No special configuration is needed if the model has only one input tensor and one
+-       * output tensor.
+-       *
+-       * <p>- When the model has multiple input or output tensors, use the following configurations
+-       * to specifiy the desired tensors: <br>
+-       * -- tensor names: {@code inputTensorName}, {@code outputScoreTensorName}, {@code
+-       * outputLabelTensorName}<br>
+-       * -- tensor indices: {@code inputTensorIndex}, {@code outputScoreTensorIndex}, {@code
+-       * outputLabelTensorIndex} <br>
+-       * Tensor names has higher priorities than tensor indices in locating the tensors. It means
+-       * the tensors will be first located according to tensor names. If not found, then the tensors
+-       * will be located according to tensor indices.
+-       *
+-       * <p>- Failing to match the input text tensor or output score tensor with neither tensor
+-       * names nor tensor indices will trigger a runtime error. However, failing to locate the
+-       * output label tensor will not trigger an error because the label tensor is optional.
+-       */
+-
+-      /**
+-       * Set the name of the input text tensor, if the model has multiple inputs. Only the input
+-       * tensor specified will be used for inference; other input tensors will be ignored. Dafualt
+-       * to {@code "INPUT"}.
+-       *
+-       * <p>See the section, Configure the input/output tensors for NLClassifier, for more details.
+-       */
+-      public abstract Builder setInputTensorName(String inputTensorName);
+-
+-      /**
+-       * Set the name of the output score tensor, if the model has multiple outputs. Dafualt to
+-       * {@code "OUTPUT_SCORE"}.
+-       *
+-       * <p>See the section, Configure the input/output tensors for NLClassifier, for more details.
+-       */
+-      public abstract Builder setOutputScoreTensorName(String outputScoreTensorName);
+-
+-      /**
+-       * Set the name of the output label tensor, if the model has multiple outputs. Dafualt to
+-       * {@code "OUTPUT_LABEL"}.
+-       *
+-       * <p>See the section, Configure the input/output tensors for NLClassifier, for more details.
+-       *
+-       * <p>By default, label file should be packed with the output score tensor through Model
+-       * Metadata. See the <a
+-       * href="https://www.tensorflow.org/lite/convert/metadata_writer_tutorial#natural_language_classifiers">MetadataWriter
+-       * for NLClassifier</a>. NLClassifier reads and parses labels from the label file
+-       * automatically. However, some models may output a specific label tensor instead. In this
+-       * case, NLClassifier reads labels from the output label tensor.
+-       */
+-      public abstract Builder setOutputLabelTensorName(String outputLabelTensorName);
+-
+-      /**
+-       * Set the index of the input text tensor among all input tensors, if the model has multiple
+-       * inputs. Only the input tensor specified will be used for inference; other input tensors
+-       * will be ignored. Dafualt to 0.
+-       *
+-       * <p>See the section, Configure the input/output tensors for NLClassifier, for more details.
+-       */
+-      public abstract Builder setInputTensorIndex(int inputTensorIndex);
+-
+-      /**
+-       * Set the index of the output score tensor among all output tensors, if the model has
+-       * multiple outputs. Dafualt to 0.
+-       *
+-       * <p>See the section, Configure the input/output tensors for NLClassifier, for more details.
+-       */
+-      public abstract Builder setOutputScoreTensorIndex(int outputScoreTensorIndex);
+-
+-      /**
+-       * Set the index of the optional output label tensor among all output tensors, if the model
+-       * has multiple outputs.
+-       *
+-       * <p>See the document above {@code outputLabelTensorName} for more information about what the
+-       * output label tensor is.
+-       *
+-       * <p>See the section, Configure the input/output tensors for NLClassifier, for more details.
+-       *
+-       * <p>{@code outputLabelTensorIndex} dafualts to -1, meaning to disable the output label
+-       * tensor.
+-       */
+-      public abstract Builder setOutputLabelTensorIndex(int outputLabelTensorIndex);
+-
+-      public abstract NLClassifierOptions build();
++    /**
++     * Creates {@link NLClassifier} from {@link NLClassifierOptions}.
++     *
++     * @param context Android context
++     * @param modelPath path to the classification model relative to asset dir
++     * @param options configurations for the model.
++     * @return an {@link NLClassifier} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static NLClassifier createFromFileAndOptions(
++            Context context, String modelPath, NLClassifierOptions options) throws IOException {
++        return createFromBufferAndOptions(TaskJniUtils.loadMappedFile(context, modelPath), options);
+     }
+-  }
+-
+-  private static final String NL_CLASSIFIER_NATIVE_LIBNAME = "task_text_jni";
+-
+-  /**
+-   * Creates {@link NLClassifier} from default {@link NLClassifierOptions}.
+-   *
+-   * @param context Android context
+-   * @param modelPath path to the classification model relative to asset dir
+-   * @return an {@link NLClassifier} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static NLClassifier createFromFile(Context context, String modelPath) throws IOException {
+-    return createFromFileAndOptions(context, modelPath, NLClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates {@link NLClassifier} from default {@link NLClassifierOptions}.
+-   *
+-   * @param modelFile the classification model {@link File} instance
+-   * @return an {@link NLClassifier} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static NLClassifier createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, NLClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates {@link NLClassifier} from {@link NLClassifierOptions}.
+-   *
+-   * @param context Android context
+-   * @param modelPath path to the classification model relative to asset dir
+-   * @param options configurations for the model.
+-   * @return an {@link NLClassifier} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static NLClassifier createFromFileAndOptions(
+-      Context context, String modelPath, NLClassifierOptions options) throws IOException {
+-    return createFromBufferAndOptions(TaskJniUtils.loadMappedFile(context, modelPath), options);
+-  }
+-
+-  /**
+-   * Creates {@link NLClassifier} from {@link NLClassifierOptions}.
+-   *
+-   * @param modelFile the classification model {@link File} instance
+-   * @param options configurations for the model
+-   * @return an {@link NLClassifier} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static NLClassifier createFromFileAndOptions(
+-      File modelFile, final NLClassifierOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return new NLClassifier(
+-          TaskJniUtils.createHandleFromLibrary(
+-              new EmptyHandleProvider() {
++
++    /**
++     * Creates {@link NLClassifier} from {@link NLClassifierOptions}.
++     *
++     * @param modelFile the classification model {@link File} instance
++     * @param options configurations for the model
++     * @return an {@link NLClassifier} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static NLClassifier createFromFileAndOptions(
++            File modelFile, final NLClassifierOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return new NLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+                 @Override
+                 public long createHandle() {
+-                  long baseOptionsHandle =
+-                      options.getBaseOptions() == null
+-                          ? 0 // pass an invalid native handle
+-                          : TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions());
+-                  return initJniWithFileDescriptor(options, descriptor.getFd(), baseOptionsHandle);
++                    long baseOptionsHandle = options.getBaseOptions() == null
++                            ? 0 // pass an invalid native handle
++                            : TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions());
++                    return initJniWithFileDescriptor(
++                            options, descriptor.getFd(), baseOptionsHandle);
+                 }
+-              },
+-              NL_CLASSIFIER_NATIVE_LIBNAME));
+-    }
+-  }
+-
+-  /**
+-   * Creates {@link NLClassifier} with a model {@link ByteBuffer} and {@link NLClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     classification model
+-   * @param options configurations for the model
+-   * @return {@link NLClassifier} instance
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   */
+-  public static NLClassifier createFromBufferAndOptions(
+-      final ByteBuffer modelBuffer, final NLClassifierOptions options) {
+-    if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+-      throw new IllegalArgumentException(
+-          "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++            }, NL_CLASSIFIER_NATIVE_LIBNAME));
++        }
+     }
+ 
+-    return new NLClassifier(
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                long baseOptionsHandle =
+-                    options.getBaseOptions() == null
++    /**
++     * Creates {@link NLClassifier} with a model {@link ByteBuffer} and {@link NLClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     classification model
++     * @param options configurations for the model
++     * @return {@link NLClassifier} instance
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     */
++    public static NLClassifier createFromBufferAndOptions(
++            final ByteBuffer modelBuffer, final NLClassifierOptions options) {
++        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
++            throw new IllegalArgumentException(
++                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++        }
++
++        return new NLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                long baseOptionsHandle = options.getBaseOptions() == null
+                         ? 0 // pass an invalid native handle
+                         : TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions());
+                 return initJniWithByteBuffer(options, modelBuffer, baseOptionsHandle);
+-              }
+-            },
+-            NL_CLASSIFIER_NATIVE_LIBNAME));
+-  }
+-
+-  /**
+-   * Performs classification on a string input, returns classified {@link Category}s.
+-   *
+-   * @param text input text to the model
+-   * @return a list of Category results
+-   */
+-  public List<Category> classify(String text) {
+-    return classifyNative(getNativeHandle(), text);
+-  }
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++.
+-   */
+-  protected NLClassifier(long nativeHandle) {
+-    super(nativeHandle);
+-  }
+-
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
+-
+-  private static native long initJniWithByteBuffer(
+-      NLClassifierOptions options, ByteBuffer modelBuffer, long baseOptionsHandle);
+-
+-  private static native long initJniWithFileDescriptor(
+-      NLClassifierOptions options, int fd, long baseOptionsHandle);
+-
+-  private static native List<Category> classifyNative(long nativeHandle, String text);
+-
+-  /**
+-   * Native implementation to release memory pointed by the pointer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private native void deinitJni(long nativeHandle);
++            }
++        }, NL_CLASSIFIER_NATIVE_LIBNAME));
++    }
++
++    /**
++     * Performs classification on a string input, returns classified {@link Category}s.
++     *
++     * @param text input text to the model
++     * @return a list of Category results
++     */
++    public List<Category> classify(String text) {
++        return classifyNative(getNativeHandle(), text);
++    }
++
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++.
++     */
++    protected NLClassifier(long nativeHandle) {
++        super(nativeHandle);
++    }
++
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
++    }
++
++    private static native long initJniWithByteBuffer(
++            NLClassifierOptions options, ByteBuffer modelBuffer, long baseOptionsHandle);
++
++    private static native long initJniWithFileDescriptor(
++            NLClassifierOptions options, int fd, long baseOptionsHandle);
++
++    private static native List<Category> classifyNative(long nativeHandle, String text);
++
++    /**
++     * Native implementation to release memory pointed by the pointer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java
+index aafa2c88c55e8..39648d9bb4042 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java
+@@ -17,11 +17,9 @@ package org.tensorflow.lite.task.text.qa;
+ 
+ import android.content.Context;
+ import android.os.ParcelFileDescriptor;
++
+ import com.google.auto.value.AutoValue;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.util.List;
++
+ import org.tensorflow.lite.task.core.BaseOptions;
+ import org.tensorflow.lite.task.core.BaseTaskApi;
+ import org.tensorflow.lite.task.core.TaskJniUtils;
+@@ -29,6 +27,11 @@ import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+ import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
+ import org.tensorflow.lite.task.core.TaskJniUtils.MultipleBuffersHandleProvider;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.util.List;
++
+ /**
+  * Returns the most possible answers on a given question for QA models (BERT, Albert, etc.).
+  *
+@@ -45,225 +48,204 @@ import org.tensorflow.lite.task.core.TaskJniUtils.MultipleBuffersHandleProvider;
+  * </ul>
+  */
+ public class BertQuestionAnswerer extends BaseTaskApi implements QuestionAnswerer {
+-  private static final String BERT_QUESTION_ANSWERER_NATIVE_LIBNAME = "task_text_jni";
+-  private static final int OPTIONAL_FD_LENGTH = -1;
+-  private static final int OPTIONAL_FD_OFFSET = -1;
+-
+-  /**
+-   * Creates a {@link BertQuestionAnswerer} instance from the default {@link
+-   * BertQuestionAnswererOptions}.
+-   *
+-   * @param context android context
+-   * @param modelPath file path to the model with metadata. Note: The model should not be compressed
+-   * @return a {@link BertQuestionAnswerer} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertQuestionAnswerer createFromFile(Context context, String modelPath)
+-      throws IOException {
+-    return createFromFileAndOptions(
+-        context, modelPath, BertQuestionAnswererOptions.builder().build());
+-  }
++    private static final String BERT_QUESTION_ANSWERER_NATIVE_LIBNAME = "task_text_jni";
++    private static final int OPTIONAL_FD_LENGTH = -1;
++    private static final int OPTIONAL_FD_OFFSET = -1;
++
++    /**
++     * Creates a {@link BertQuestionAnswerer} instance from the default {@link
++     * BertQuestionAnswererOptions}.
++     *
++     * @param context android context
++     * @param modelPath file path to the model with metadata. Note: The model should not be
++     *         compressed
++     * @return a {@link BertQuestionAnswerer} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertQuestionAnswerer createFromFile(Context context, String modelPath)
++            throws IOException {
++        return createFromFileAndOptions(
++                context, modelPath, BertQuestionAnswererOptions.builder().build());
++    }
+ 
+-  /**
+-   * Creates a {@link BertQuestionAnswerer} instance from the default {@link
+-   * BertQuestionAnswererOptions}.
+-   *
+-   * @param modelFile a {@link File} object of the model
+-   * @return a {@link BertQuestionAnswerer} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertQuestionAnswerer createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, BertQuestionAnswererOptions.builder().build());
+-  }
++    /**
++     * Creates a {@link BertQuestionAnswerer} instance from the default {@link
++     * BertQuestionAnswererOptions}.
++     *
++     * @param modelFile a {@link File} object of the model
++     * @return a {@link BertQuestionAnswerer} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertQuestionAnswerer createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, BertQuestionAnswererOptions.builder().build());
++    }
+ 
+-  /**
+-   * Creates a {@link BertQuestionAnswerer} instance from {@link BertQuestionAnswererOptions}.
+-   *
+-   * @param context android context
+-   * @param modelPath file path to the model with metadata. Note: The model should not be compressed
+-   * @return a {@link BertQuestionAnswerer} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertQuestionAnswerer createFromFileAndOptions(
+-      Context context, String modelPath, BertQuestionAnswererOptions options) throws IOException {
+-    return new BertQuestionAnswerer(
+-        TaskJniUtils.createHandleFromFdAndOptions(
+-            context,
+-            new FdAndOptionsHandleProvider<BertQuestionAnswererOptions>() {
+-              @Override
+-              public long createHandle(
+-                  int fileDescriptor,
+-                  long fileDescriptorLength,
+-                  long fileDescriptorOffset,
+-                  BertQuestionAnswererOptions options) {
+-                return initJniWithFileDescriptor(
+-                    fileDescriptor,
+-                    fileDescriptorLength,
+-                    fileDescriptorOffset,
+-                    TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-              }
+-            },
+-            BERT_QUESTION_ANSWERER_NATIVE_LIBNAME,
+-            modelPath,
+-            options));
+-  }
++    /**
++     * Creates a {@link BertQuestionAnswerer} instance from {@link BertQuestionAnswererOptions}.
++     *
++     * @param context android context
++     * @param modelPath file path to the model with metadata. Note: The model should not be
++     *         compressed
++     * @return a {@link BertQuestionAnswerer} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertQuestionAnswerer createFromFileAndOptions(Context context, String modelPath,
++            BertQuestionAnswererOptions options) throws IOException {
++        return new BertQuestionAnswerer(TaskJniUtils.createHandleFromFdAndOptions(
++                context, new FdAndOptionsHandleProvider<BertQuestionAnswererOptions>() {
++                    @Override
++                    public long createHandle(int fileDescriptor, long fileDescriptorLength,
++                            long fileDescriptorOffset, BertQuestionAnswererOptions options) {
++                        return initJniWithFileDescriptor(fileDescriptor, fileDescriptorLength,
++                                fileDescriptorOffset,
++                                TaskJniUtils.createProtoBaseOptionsHandle(
++                                        options.getBaseOptions()));
++                    }
++                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, modelPath, options));
++    }
+ 
+-  /**
+-   * Creates a {@link BertQuestionAnswerer} instance from {@link BertQuestionAnswererOptions}.
+-   *
+-   * @param modelFile a {@link File} object of the model
+-   * @return a {@link BertQuestionAnswerer} instance
+-   * @throws IOException if model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertQuestionAnswerer createFromFileAndOptions(
+-      File modelFile, final BertQuestionAnswererOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return new BertQuestionAnswerer(
+-          TaskJniUtils.createHandleFromLibrary(
+-              new EmptyHandleProvider() {
+-                @Override
+-                public long createHandle() {
+-                  return initJniWithFileDescriptor(
+-                      /*fileDescriptor=*/ descriptor.getFd(),
+-                      /*fileDescriptorLength=*/ OPTIONAL_FD_LENGTH,
+-                      /*fileDescriptorOffset=*/ OPTIONAL_FD_OFFSET,
+-                      TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+-                }
+-              },
+-              BERT_QUESTION_ANSWERER_NATIVE_LIBNAME));
++    /**
++     * Creates a {@link BertQuestionAnswerer} instance from {@link BertQuestionAnswererOptions}.
++     *
++     * @param modelFile a {@link File} object of the model
++     * @return a {@link BertQuestionAnswerer} instance
++     * @throws IOException if model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertQuestionAnswerer createFromFileAndOptions(
++            File modelFile, final BertQuestionAnswererOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return new BertQuestionAnswerer(
++                    TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++                        @Override
++                        public long createHandle() {
++                            return initJniWithFileDescriptor(
++                                    /*fileDescriptor=*/descriptor.getFd(),
++                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
++                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET,
++                                    TaskJniUtils.createProtoBaseOptionsHandle(
++                                            options.getBaseOptions()));
++                        }
++                    }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME));
++        }
+     }
+-  }
+ 
+-  /**
+-   * Creates a {@link BertQuestionAnswerer} instance with a Bert model and a vocabulary file.
+-   *
+-   * <p>One suitable model is: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
+-   *
+-   * @param context android context
+-   * @param modelPath file path to the Bert model. Note: The model should not be compressed
+-   * @param vocabPath file path to the vocabulary file. Note: The file should not be compressed
+-   * @return a {@link BertQuestionAnswerer} instance
+-   * @throws IOException If model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertQuestionAnswerer createBertQuestionAnswererFromFile(
+-      Context context, String modelPath, String vocabPath) throws IOException {
+-    return new BertQuestionAnswerer(
+-        TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
+-            context,
+-            new MultipleBuffersHandleProvider() {
+-              @Override
+-              public long createHandle(ByteBuffer... buffers) {
+-                return initJniWithBertByteBuffers(buffers);
+-              }
+-            },
+-            BERT_QUESTION_ANSWERER_NATIVE_LIBNAME,
+-            modelPath,
+-            vocabPath));
+-  }
++    /**
++     * Creates a {@link BertQuestionAnswerer} instance with a Bert model and a vocabulary file.
++     *
++     * <p>One suitable model is: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
++     *
++     * @param context android context
++     * @param modelPath file path to the Bert model. Note: The model should not be compressed
++     * @param vocabPath file path to the vocabulary file. Note: The file should not be compressed
++     * @return a {@link BertQuestionAnswerer} instance
++     * @throws IOException If model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertQuestionAnswerer createBertQuestionAnswererFromFile(
++            Context context, String modelPath, String vocabPath) throws IOException {
++        return new BertQuestionAnswerer(TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
++                context, new MultipleBuffersHandleProvider() {
++                    @Override
++                    public long createHandle(ByteBuffer... buffers) {
++                        return initJniWithBertByteBuffers(buffers);
++                    }
++                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, modelPath, vocabPath));
++    }
+ 
+-  /**
+-   * Creates a {@link BertQuestionAnswerer} instance with an Albert model and a sentence piece model
+-   * file.
+-   *
+-   * <p>One suitable model is: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
+-   *
+-   * @param context android context
+-   * @param modelPath file path to the Albert model. Note: The model should not be compressed
+-   * @param sentencePieceModelPath file path to the sentence piece model file. Note: The model
+-   *     should not be compressed
+-   * @return a {@link BertQuestionAnswerer} instance
+-   * @throws IOException If model file fails to load
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static BertQuestionAnswerer createAlbertQuestionAnswererFromFile(
+-      Context context, String modelPath, String sentencePieceModelPath) throws IOException {
+-    return new BertQuestionAnswerer(
+-        TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
+-            context,
+-            new MultipleBuffersHandleProvider() {
+-              @Override
+-              public long createHandle(ByteBuffer... buffers) {
+-                return initJniWithAlbertByteBuffers(buffers);
+-              }
+-            },
+-            BERT_QUESTION_ANSWERER_NATIVE_LIBNAME,
+-            modelPath,
+-            sentencePieceModelPath));
+-  }
++    /**
++     * Creates a {@link BertQuestionAnswerer} instance with an Albert model and a sentence piece
++     * model file.
++     *
++     * <p>One suitable model is: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
++     *
++     * @param context android context
++     * @param modelPath file path to the Albert model. Note: The model should not be compressed
++     * @param sentencePieceModelPath file path to the sentence piece model file. Note: The model
++     *     should not be compressed
++     * @return a {@link BertQuestionAnswerer} instance
++     * @throws IOException If model file fails to load
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static BertQuestionAnswerer createAlbertQuestionAnswererFromFile(
++            Context context, String modelPath, String sentencePieceModelPath) throws IOException {
++        return new BertQuestionAnswerer(TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
++                context, new MultipleBuffersHandleProvider() {
++                    @Override
++                    public long createHandle(ByteBuffer... buffers) {
++                        return initJniWithAlbertByteBuffers(buffers);
++                    }
++                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, modelPath, sentencePieceModelPath));
++    }
+ 
+-  /** Options for setting up a {@link BertQuestionAnswerer}. */
+-  @AutoValue
+-  public abstract static class BertQuestionAnswererOptions {
+-    abstract BaseOptions getBaseOptions();
++    /** Options for setting up a {@link BertQuestionAnswerer}. */
++    @AutoValue
++    public abstract static class BertQuestionAnswererOptions {
++        abstract BaseOptions getBaseOptions();
+ 
+-    public static Builder builder() {
+-      return new AutoValue_BertQuestionAnswerer_BertQuestionAnswererOptions.Builder()
+-          .setBaseOptions(BaseOptions.builder().build());
+-    }
++        public static Builder builder() {
++            return new AutoValue_BertQuestionAnswerer_BertQuestionAnswererOptions.Builder()
++                    .setBaseOptions(BaseOptions.builder().build());
++        }
+ 
+-    /** Builder for {@link BertQuestionAnswererOptions}. */
+-    @AutoValue.Builder
+-    public abstract static class Builder {
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public abstract Builder setBaseOptions(BaseOptions baseOptions);
++        /** Builder for {@link BertQuestionAnswererOptions}. */
++        @AutoValue.Builder
++        public abstract static class Builder {
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public abstract Builder setBaseOptions(BaseOptions baseOptions);
+ 
+-      public abstract BertQuestionAnswererOptions build();
++            public abstract BertQuestionAnswererOptions build();
++        }
+     }
+-  }
+ 
+-  @Override
+-  public List<QaAnswer> answer(String context, String question) {
+-    checkNotClosed();
+-    return answerNative(getNativeHandle(), context, question);
+-  }
++    @Override
++    public List<QaAnswer> answer(String context, String question) {
++        checkNotClosed();
++        return answerNative(getNativeHandle(), context, question);
++    }
+ 
+-  private BertQuestionAnswerer(long nativeHandle) {
+-    super(nativeHandle);
+-  }
++    private BertQuestionAnswerer(long nativeHandle) {
++        super(nativeHandle);
++    }
+ 
+-  // modelBuffers[0] is tflite model file buffer, and modelBuffers[1] is vocab file buffer.
+-  private static native long initJniWithBertByteBuffers(ByteBuffer... modelBuffers);
++    // modelBuffers[0] is tflite model file buffer, and modelBuffers[1] is vocab file buffer.
++    private static native long initJniWithBertByteBuffers(ByteBuffer... modelBuffers);
+ 
+-  // modelBuffers[0] is tflite model file buffer, and modelBuffers[1] is sentencepiece model file
+-  // buffer.
+-  private static native long initJniWithAlbertByteBuffers(ByteBuffer... modelBuffers);
++    // modelBuffers[0] is tflite model file buffer, and modelBuffers[1] is sentencepiece model file
++    // buffer.
++    private static native long initJniWithAlbertByteBuffers(ByteBuffer... modelBuffers);
+ 
+-  private static native long initJniWithFileDescriptor(
+-      int fileDescriptor,
+-      long fileDescriptorLength,
+-      long fileDescriptorOffset,
+-      long baseOptionsHandle);
++    private static native long initJniWithFileDescriptor(int fileDescriptor,
++            long fileDescriptorLength, long fileDescriptorOffset, long baseOptionsHandle);
+ 
+-  private static native List<QaAnswer> answerNative(
+-      long nativeHandle, String context, String question);
++    private static native List<QaAnswer> answerNative(
++            long nativeHandle, String context, String question);
+ 
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
++    }
+ 
+-  /**
+-   * Native implementation to release memory pointed by the pointer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private native void deinitJni(long nativeHandle);
++    /**
++     * Native implementation to release memory pointed by the pointer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QaAnswer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QaAnswer.java
+index 4259a69794059..955da9988ca0a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QaAnswer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QaAnswer.java
+@@ -22,37 +22,37 @@ import org.tensorflow.lite.annotations.UsedByReflection;
+  * position information to the context.
+  */
+ public class QaAnswer {
+-  public Pos pos;
+-  public String text;
+-
+-  @UsedByReflection("bert_question_answerer_jni.cc")
+-  public QaAnswer(String text, Pos pos) {
+-    this.text = text;
+-    this.pos = pos;
+-  }
+-
+-  public QaAnswer(String text, int start, int end, float logit) {
+-    this(text, new Pos(start, end, logit));
+-  }
+-
+-  /**
+-   * Position information of the answer relative to context. It is sortable in descending order
+-   * based on logit.
+-   */
+-  public static class Pos implements Comparable<Pos> {
+-    public int start;
+-    public int end;
+-    public float logit;
+-
+-    public Pos(int start, int end, float logit) {
+-      this.start = start;
+-      this.end = end;
+-      this.logit = logit;
++    public Pos pos;
++    public String text;
++
++    @UsedByReflection("bert_question_answerer_jni.cc")
++    public QaAnswer(String text, Pos pos) {
++        this.text = text;
++        this.pos = pos;
++    }
++
++    public QaAnswer(String text, int start, int end, float logit) {
++        this(text, new Pos(start, end, logit));
+     }
+ 
+-    @Override
+-    public int compareTo(Pos other) {
+-      return Float.compare(other.logit, this.logit);
++    /**
++     * Position information of the answer relative to context. It is sortable in descending order
++     * based on logit.
++     */
++    public static class Pos implements Comparable<Pos> {
++        public int start;
++        public int end;
++        public float logit;
++
++        public Pos(int start, int end, float logit) {
++            this.start = start;
++            this.end = end;
++            this.logit = logit;
++        }
++
++        @Override
++        public int compareTo(Pos other) {
++            return Float.compare(other.logit, this.logit);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QuestionAnswerer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QuestionAnswerer.java
+index 8df6d3794e1b5..7a59a99d7fddf 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QuestionAnswerer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/QuestionAnswerer.java
+@@ -19,14 +19,13 @@ import java.util.List;
+ 
+ /** API to answer questions based on context. */
+ public interface QuestionAnswerer {
+-
+-  /**
+-   * Answers question based on context, and returns a list of possible {@link QaAnswer}s. Could be
+-   * empty if no answer was found from the given context.
+-   *
+-   * @param context context the question bases on
+-   * @param question question to ask
+-   * @return a list of possible answers in {@link QaAnswer}
+-   */
+-  List<QaAnswer> answer(String context, String question);
++    /**
++     * Answers question based on context, and returns a list of possible {@link QaAnswer}s. Could be
++     * empty if no answer was found from the given context.
++     *
++     * @param context context the question bases on
++     * @param question question to ask
++     * @return a list of possible answers in {@link QaAnswer}
++     */
++    List<QaAnswer> answer(String context, String question);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/Classifications.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/Classifications.java
+index d33f0fbbdd497..0d35443a7de5d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/Classifications.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/Classifications.java
+@@ -16,11 +16,13 @@ limitations under the License.
+ package org.tensorflow.lite.task.vision.classifier;
+ 
+ import com.google.auto.value.AutoValue;
++
++import org.tensorflow.lite.annotations.UsedByReflection;
++import org.tensorflow.lite.support.label.Category;
++
+ import java.util.ArrayList;
+ import java.util.Collections;
+ import java.util.List;
+-import org.tensorflow.lite.annotations.UsedByReflection;
+-import org.tensorflow.lite.support.label.Category;
+ 
+ /**
+  * The classification results of one head in a multihead (a.k.a. multi-output) {@link
+@@ -31,16 +33,15 @@ import org.tensorflow.lite.support.label.Category;
+ @AutoValue
+ @UsedByReflection("image_classifier_jni.cc")
+ public abstract class Classifications {
++    @UsedByReflection("image_classifier_jni.cc")
++    static Classifications create(List<Category> categories, int headIndex) {
++        return new AutoValue_Classifications(
++                Collections.unmodifiableList(new ArrayList<Category>(categories)), headIndex);
++    }
+ 
+-  @UsedByReflection("image_classifier_jni.cc")
+-  static Classifications create(List<Category> categories, int headIndex) {
+-    return new AutoValue_Classifications(
+-        Collections.unmodifiableList(new ArrayList<Category>(categories)), headIndex);
+-  }
+-
+-  // Same reason for not using ImmutableList as stated in
+-  // {@link ImageClassifier#ImageClassifierOptions#labelAllowList}.
+-  public abstract List<Category> getCategories();
++    // Same reason for not using ImmutableList as stated in
++    // {@link ImageClassifier#ImageClassifierOptions#labelAllowList}.
++    public abstract List<Category> getCategories();
+ 
+-  public abstract int getHeadIndex();
++    public abstract int getHeadIndex();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java
+index 2bf3fa8a465b4..48038f6a1c04e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java
+@@ -18,14 +18,9 @@ package org.tensorflow.lite.task.vision.classifier;
+ import android.content.Context;
+ import android.graphics.Rect;
+ import android.os.ParcelFileDescriptor;
++
+ import com.google.android.odml.image.MlImage;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.MappedByteBuffer;
+-import java.util.ArrayList;
+-import java.util.Collections;
+-import java.util.List;
++
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ import org.tensorflow.lite.support.image.MlImageAdapter;
+ import org.tensorflow.lite.support.image.TensorImage;
+@@ -37,6 +32,14 @@ import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
+ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi.InferenceProvider;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.MappedByteBuffer;
++import java.util.ArrayList;
++import java.util.Collections;
++import java.util.List;
++
+ /**
+  * Performs classification on images.
+  *
+@@ -71,476 +74,449 @@ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi.InferenceProvider;
+  * Hub.</a>.
+  */
+ public final class ImageClassifier extends BaseVisionTaskApi {
++    private static final String IMAGE_CLASSIFIER_NATIVE_LIB = "task_vision_jni";
++    private static final int OPTIONAL_FD_LENGTH = -1;
++    private static final int OPTIONAL_FD_OFFSET = -1;
++
++    /**
++     * Creates an {@link ImageClassifier} instance from the default {@link ImageClassifierOptions}.
++     *
++     * @param modelPath path of the classification model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageClassifier createFromFile(Context context, String modelPath)
++            throws IOException {
++        return createFromFileAndOptions(
++                context, modelPath, ImageClassifierOptions.builder().build());
++    }
+ 
+-  private static final String IMAGE_CLASSIFIER_NATIVE_LIB = "task_vision_jni";
+-  private static final int OPTIONAL_FD_LENGTH = -1;
+-  private static final int OPTIONAL_FD_OFFSET = -1;
+-
+-  /**
+-   * Creates an {@link ImageClassifier} instance from the default {@link ImageClassifierOptions}.
+-   *
+-   * @param modelPath path of the classification model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageClassifier createFromFile(Context context, String modelPath)
+-      throws IOException {
+-    return createFromFileAndOptions(context, modelPath, ImageClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ImageClassifier} instance from the default {@link ImageClassifierOptions}.
+-   *
+-   * @param modelFile the classification model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageClassifier createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, ImageClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ImageClassifier} instance with a model buffer and the default {@link
+-   * ImageClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     classification model
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageClassifier createFromBuffer(final ByteBuffer modelBuffer) {
+-    return createFromBufferAndOptions(modelBuffer, ImageClassifierOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ImageClassifier} instance from {@link ImageClassifierOptions}.
+-   *
+-   * @param modelPath path of the classification model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageClassifier createFromFileAndOptions(
+-      Context context, String modelPath, ImageClassifierOptions options) throws IOException {
+-    return new ImageClassifier(
+-        TaskJniUtils.createHandleFromFdAndOptions(
+-            context,
+-            new FdAndOptionsHandleProvider<ImageClassifierOptions>() {
+-              @Override
+-              public long createHandle(
+-                  int fileDescriptor,
+-                  long fileDescriptorLength,
+-                  long fileDescriptorOffset,
+-                  ImageClassifierOptions options) {
+-                return initJniWithModelFdAndOptions(
+-                    fileDescriptor,
+-                    fileDescriptorLength,
+-                    fileDescriptorOffset,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                        options.getBaseOptions(), options.getNumThreads()));
+-              }
+-            },
+-            IMAGE_CLASSIFIER_NATIVE_LIB,
+-            modelPath,
+-            options));
+-  }
+-
+-  /**
+-   * Creates an {@link ImageClassifier} instance.
+-   *
+-   * @param modelFile the classification model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageClassifier createFromFileAndOptions(
+-      File modelFile, final ImageClassifierOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return new ImageClassifier(
+-          TaskJniUtils.createHandleFromLibrary(
+-              new TaskJniUtils.EmptyHandleProvider() {
+-                @Override
+-                public long createHandle() {
+-                  return initJniWithModelFdAndOptions(
+-                      descriptor.getFd(),
+-                      /*fileDescriptorLength=*/ OPTIONAL_FD_LENGTH,
+-                      /*fileDescriptorOffset=*/ OPTIONAL_FD_OFFSET,
+-                      options,
+-                      TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                          options.getBaseOptions(), options.getNumThreads()));
+-                }
+-              },
+-              IMAGE_CLASSIFIER_NATIVE_LIB));
++    /**
++     * Creates an {@link ImageClassifier} instance from the default {@link ImageClassifierOptions}.
++     *
++     * @param modelFile the classification model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageClassifier createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, ImageClassifierOptions.builder().build());
+     }
+-  }
+-
+-  /**
+-   * Creates an {@link ImageClassifier} instance with a model buffer and {@link
+-   * ImageClassifierOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     classification model
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageClassifier createFromBufferAndOptions(
+-      final ByteBuffer modelBuffer, final ImageClassifierOptions options) {
+-    if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+-      throw new IllegalArgumentException(
+-          "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++
++    /**
++     * Creates an {@link ImageClassifier} instance with a model buffer and the default {@link
++     * ImageClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     classification model
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageClassifier createFromBuffer(final ByteBuffer modelBuffer) {
++        return createFromBufferAndOptions(modelBuffer, ImageClassifierOptions.builder().build());
+     }
+-    return new ImageClassifier(
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                return initJniWithByteBuffer(
+-                    modelBuffer,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                        options.getBaseOptions(), options.getNumThreads()));
+-              }
+-            },
+-            IMAGE_CLASSIFIER_NATIVE_LIB));
+-  }
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++
+-   */
+-  ImageClassifier(long nativeHandle) {
+-    super(nativeHandle);
+-  }
+-
+-  /** Options for setting up an ImageClassifier. */
+-  @UsedByReflection("image_classifier_jni.cc")
+-  public static class ImageClassifierOptions {
+-    // Not using AutoValue for this class because scoreThreshold cannot have default value
+-    // (otherwise, the default value would override the one in the model metadata) and `Optional` is
+-    // not an option here, because
+-    // 1. java.util.Optional require Java 8 while we need to support Java 7.
+-    // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See the
+-    // comments for labelAllowList.
+-    private final BaseOptions baseOptions;
+-    private final String displayNamesLocale;
+-    private final int maxResults;
+-    private final float scoreThreshold;
+-    private final boolean isScoreThresholdSet;
+-    // As an open source project, we've been trying avoiding depending on common java libraries,
+-    // such as Guava, because it may introduce conflicts with clients who also happen to use those
+-    // libraries. Therefore, instead of using ImmutableList here, we convert the List into
+-    // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
+-    // vulnerable.
+-    private final List<String> labelAllowList;
+-    private final List<String> labelDenyList;
+-    private final int numThreads;
+-
+-    public static Builder builder() {
+-      return new Builder();
++
++    /**
++     * Creates an {@link ImageClassifier} instance from {@link ImageClassifierOptions}.
++     *
++     * @param modelPath path of the classification model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageClassifier createFromFileAndOptions(
++            Context context, String modelPath, ImageClassifierOptions options) throws IOException {
++        return new ImageClassifier(TaskJniUtils.createHandleFromFdAndOptions(
++                context, new FdAndOptionsHandleProvider<ImageClassifierOptions>() {
++                    @Override
++                    public long createHandle(int fileDescriptor, long fileDescriptorLength,
++                            long fileDescriptorOffset, ImageClassifierOptions options) {
++                        return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
++                                fileDescriptorOffset, options,
++                                TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                        options.getBaseOptions(), options.getNumThreads()));
++                    }
++                }, IMAGE_CLASSIFIER_NATIVE_LIB, modelPath, options));
+     }
+ 
+-    /** A builder that helps to configure an instance of ImageClassifierOptions. */
+-    public static class Builder {
+-      private BaseOptions baseOptions = BaseOptions.builder().build();
+-      private String displayNamesLocale = "en";
+-      private int maxResults = -1;
+-      private float scoreThreshold;
+-      private boolean isScoreThresholdSet = false;
+-      private List<String> labelAllowList = new ArrayList<>();
+-      private List<String> labelDenyList = new ArrayList<>();
+-      private int numThreads = -1;
+-
+-      Builder() {}
+-
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public Builder setBaseOptions(BaseOptions baseOptions) {
+-        this.baseOptions = baseOptions;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the locale to use for display names specified through the TFLite Model Metadata, if
+-       * any.
+-       *
+-       * <p>Defaults to English({@code "en"}). See the <a
+-       * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
+-       * Metadata schema file.</a> for the accepted pattern of locale.
+-       */
+-      public Builder setDisplayNamesLocale(String displayNamesLocale) {
+-        this.displayNamesLocale = displayNamesLocale;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the maximum number of top scored results to return.
+-       *
+-       * <p>If < 0, all results will be returned. If 0, an invalid argument error is returned.
+-       * Defaults to -1.
+-       *
+-       * @throws IllegalArgumentException if maxResults is 0.
+-       */
+-      public Builder setMaxResults(int maxResults) {
+-        if (maxResults == 0) {
+-          throw new IllegalArgumentException("maxResults cannot be 0.");
++    /**
++     * Creates an {@link ImageClassifier} instance.
++     *
++     * @param modelFile the classification model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageClassifier createFromFileAndOptions(
++            File modelFile, final ImageClassifierOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return new ImageClassifier(
++                    TaskJniUtils.createHandleFromLibrary(new TaskJniUtils.EmptyHandleProvider() {
++                        @Override
++                        public long createHandle() {
++                            return initJniWithModelFdAndOptions(descriptor.getFd(),
++                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
++                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options,
++                                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                            options.getBaseOptions(), options.getNumThreads()));
++                        }
++                    }, IMAGE_CLASSIFIER_NATIVE_LIB));
+         }
+-        this.maxResults = maxResults;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the score threshold.
+-       *
+-       * <p>It overrides the one provided in the model metadata (if any). Results below this value
+-       * are rejected.
+-       */
+-      public Builder setScoreThreshold(float scoreThreshold) {
+-        this.scoreThreshold = scoreThreshold;
+-        isScoreThresholdSet = true;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the optional allowlist of labels.
+-       *
+-       * <p>If non-empty, classifications whose label is not in this set will be filtered out.
+-       * Duplicate or unknown labels are ignored. Mutually exclusive with labelDenyList.
+-       */
+-      public Builder setLabelAllowList(List<String> labelAllowList) {
+-        this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the optional denylist of labels.
+-       *
+-       * <p>If non-empty, classifications whose label is in this set will be filtered out. Duplicate
+-       * or unknown labels are ignored. Mutually exclusive with labelAllowList.
+-       */
+-      public Builder setLabelDenyList(List<String> labelDenyList) {
+-        this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the number of threads to be used for TFLite ops that support multi-threading when
+-       * running inference with CPU. Defaults to -1.
+-       *
+-       * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has the
+-       * effect to let TFLite runtime set the value.
+-       *
+-       * @deprecated use {@link BaseOptions} to configure number of threads instead. This method
+-       *     will override the number of threads configured from {@link BaseOptions}.
+-       */
+-      @Deprecated
+-      public Builder setNumThreads(int numThreads) {
+-        this.numThreads = numThreads;
+-        return this;
+-      }
+-
+-      public ImageClassifierOptions build() {
+-        return new ImageClassifierOptions(this);
+-      }
+     }
+ 
+-    @UsedByReflection("image_classifier_jni.cc")
+-    public String getDisplayNamesLocale() {
+-      return displayNamesLocale;
++    /**
++     * Creates an {@link ImageClassifier} instance with a model buffer and {@link
++     * ImageClassifierOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     classification model
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageClassifier createFromBufferAndOptions(
++            final ByteBuffer modelBuffer, final ImageClassifierOptions options) {
++        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
++            throw new IllegalArgumentException(
++                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++        }
++        return new ImageClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                return initJniWithByteBuffer(modelBuffer, options,
++                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                options.getBaseOptions(), options.getNumThreads()));
++            }
++        }, IMAGE_CLASSIFIER_NATIVE_LIB));
+     }
+ 
+-    @UsedByReflection("image_classifier_jni.cc")
+-    public int getMaxResults() {
+-      return maxResults;
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++
++     */
++    ImageClassifier(long nativeHandle) {
++        super(nativeHandle);
+     }
+ 
++    /** Options for setting up an ImageClassifier. */
+     @UsedByReflection("image_classifier_jni.cc")
+-    public float getScoreThreshold() {
+-      return scoreThreshold;
++    public static class ImageClassifierOptions {
++        // Not using AutoValue for this class because scoreThreshold cannot have default value
++        // (otherwise, the default value would override the one in the model metadata) and
++        // `Optional` is not an option here, because
++        // 1. java.util.Optional require Java 8 while we need to support Java 7.
++        // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See
++        // the comments for labelAllowList.
++        private final BaseOptions baseOptions;
++        private final String displayNamesLocale;
++        private final int maxResults;
++        private final float scoreThreshold;
++        private final boolean isScoreThresholdSet;
++        // As an open source project, we've been trying avoiding depending on common java libraries,
++        // such as Guava, because it may introduce conflicts with clients who also happen to use
++        // those libraries. Therefore, instead of using ImmutableList here, we convert the List into
++        // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
++        // vulnerable.
++        private final List<String> labelAllowList;
++        private final List<String> labelDenyList;
++        private final int numThreads;
++
++        public static Builder builder() {
++            return new Builder();
++        }
++
++        /** A builder that helps to configure an instance of ImageClassifierOptions. */
++        public static class Builder {
++            private BaseOptions baseOptions = BaseOptions.builder().build();
++            private String displayNamesLocale = "en";
++            private int maxResults = -1;
++            private float scoreThreshold;
++            private boolean isScoreThresholdSet = false;
++            private List<String> labelAllowList = new ArrayList<>();
++            private List<String> labelDenyList = new ArrayList<>();
++            private int numThreads = -1;
++
++            Builder() {}
++
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public Builder setBaseOptions(BaseOptions baseOptions) {
++                this.baseOptions = baseOptions;
++                return this;
++            }
++
++            /**
++             * Sets the locale to use for display names specified through the TFLite Model Metadata,
++             * if any.
++             *
++             * <p>Defaults to English({@code "en"}). See the <a
++             * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
++             * Metadata schema file.</a> for the accepted pattern of locale.
++             */
++            public Builder setDisplayNamesLocale(String displayNamesLocale) {
++                this.displayNamesLocale = displayNamesLocale;
++                return this;
++            }
++
++            /**
++             * Sets the maximum number of top scored results to return.
++             *
++             * <p>If < 0, all results will be returned. If 0, an invalid argument error is returned.
++             * Defaults to -1.
++             *
++             * @throws IllegalArgumentException if maxResults is 0.
++             */
++            public Builder setMaxResults(int maxResults) {
++                if (maxResults == 0) {
++                    throw new IllegalArgumentException("maxResults cannot be 0.");
++                }
++                this.maxResults = maxResults;
++                return this;
++            }
++
++            /**
++             * Sets the score threshold.
++             *
++             * <p>It overrides the one provided in the model metadata (if any). Results below this
++             * value are rejected.
++             */
++            public Builder setScoreThreshold(float scoreThreshold) {
++                this.scoreThreshold = scoreThreshold;
++                isScoreThresholdSet = true;
++                return this;
++            }
++
++            /**
++             * Sets the optional allowlist of labels.
++             *
++             * <p>If non-empty, classifications whose label is not in this set will be filtered out.
++             * Duplicate or unknown labels are ignored. Mutually exclusive with labelDenyList.
++             */
++            public Builder setLabelAllowList(List<String> labelAllowList) {
++                this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
++                return this;
++            }
++
++            /**
++             * Sets the optional denylist of labels.
++             *
++             * <p>If non-empty, classifications whose label is in this set will be filtered out.
++             * Duplicate or unknown labels are ignored. Mutually exclusive with labelAllowList.
++             */
++            public Builder setLabelDenyList(List<String> labelDenyList) {
++                this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
++                return this;
++            }
++
++            /**
++             * Sets the number of threads to be used for TFLite ops that support multi-threading
++             * when running inference with CPU. Defaults to -1.
++             *
++             * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has
++             * the effect to let TFLite runtime set the value.
++             *
++             * @deprecated use {@link BaseOptions} to configure number of threads instead. This
++             *         method
++             *     will override the number of threads configured from {@link BaseOptions}.
++             */
++            @Deprecated
++            public Builder setNumThreads(int numThreads) {
++                this.numThreads = numThreads;
++                return this;
++            }
++
++            public ImageClassifierOptions build() {
++                return new ImageClassifierOptions(this);
++            }
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public String getDisplayNamesLocale() {
++            return displayNamesLocale;
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public int getMaxResults() {
++            return maxResults;
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public float getScoreThreshold() {
++            return scoreThreshold;
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public boolean getIsScoreThresholdSet() {
++            return isScoreThresholdSet;
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public List<String> getLabelAllowList() {
++            return new ArrayList<>(labelAllowList);
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public List<String> getLabelDenyList() {
++            return new ArrayList<>(labelDenyList);
++        }
++
++        @UsedByReflection("image_classifier_jni.cc")
++        public int getNumThreads() {
++            return numThreads;
++        }
++
++        public BaseOptions getBaseOptions() {
++            return baseOptions;
++        }
++
++        ImageClassifierOptions(Builder builder) {
++            displayNamesLocale = builder.displayNamesLocale;
++            maxResults = builder.maxResults;
++            scoreThreshold = builder.scoreThreshold;
++            isScoreThresholdSet = builder.isScoreThresholdSet;
++            labelAllowList = builder.labelAllowList;
++            labelDenyList = builder.labelDenyList;
++            numThreads = builder.numThreads;
++            baseOptions = builder.baseOptions;
++        }
+     }
+ 
+-    @UsedByReflection("image_classifier_jni.cc")
+-    public boolean getIsScoreThresholdSet() {
+-      return isScoreThresholdSet;
++    /**
++     * Performs actual classification on the provided {@link TensorImage}.
++     *
++     * <p>{@link ImageClassifier} supports the following {@link TensorImage} color space types:
++     *
++     * <ul>
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
++     * </ul>
++     *
++     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Classifications> classify(TensorImage image) {
++        return classify(image, ImageProcessingOptions.builder().build());
+     }
+ 
+-    @UsedByReflection("image_classifier_jni.cc")
+-    public List<String> getLabelAllowList() {
+-      return new ArrayList<>(labelAllowList);
++    /**
++     * Performs actual classification on the provided {@link TensorImage} with {@link
++     * ImageProcessingOptions}.
++     *
++     * <p>{@link ImageClassifier} supports the following options:
++     *
++     * <ul>
++     *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions.Builder#setRoi}). It
++     *       defaults to the entire image.
++     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
++     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}.
++     * </ul>
++     *
++     * <p>{@link ImageClassifier} supports the following {@link TensorImage} color space types:
++     *
++     * <ul>
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
++     * </ul>
++     *
++     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Classifications> classify(TensorImage image, ImageProcessingOptions options) {
++        return run(new InferenceProvider<List<Classifications>>() {
++            @Override
++            public List<Classifications> run(
++                    long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
++                return classify(frameBufferHandle, width, height, options);
++            }
++        }, image, options);
+     }
+ 
+-    @UsedByReflection("image_classifier_jni.cc")
+-    public List<String> getLabelDenyList() {
+-      return new ArrayList<>(labelDenyList);
++    /**
++     * Performs actual classification on the provided {@code MlImage}.
++     *
++     * @param image an {@code MlImage} object that represents an image
++     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
++     */
++    public List<Classifications> classify(MlImage image) {
++        return classify(image, ImageProcessingOptions.builder().build());
+     }
+ 
+-    @UsedByReflection("image_classifier_jni.cc")
+-    public int getNumThreads() {
+-      return numThreads;
++    /**
++     * Performs actual classification on the provided {@code MlImage} with {@link
++     * ImageProcessingOptions}.
++     *
++     * <p>{@link ImageClassifier} supports the following options:
++     *
++     * <ul>
++     *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions.Builder#setRoi}). It
++     *       defaults to the entire image.
++     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
++     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
++     *       MlImage#getRotation()} is not effective.
++     * </ul>
++     *
++     * @param image a {@code MlImage} object that represents an image
++     * @param options configures options including ROI and rotation
++     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
++     */
++    public List<Classifications> classify(MlImage image, ImageProcessingOptions options) {
++        image.getInternal().acquire();
++        TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
++        List<Classifications> result = classify(tensorImage, options);
++        image.close();
++        return result;
+     }
+ 
+-    public BaseOptions getBaseOptions() {
+-      return baseOptions;
++    private List<Classifications> classify(
++            long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
++        checkNotClosed();
++
++        Rect roi = options.getRoi().isEmpty() ? new Rect(0, 0, width, height) : options.getRoi();
++
++        return classifyNative(getNativeHandle(), frameBufferHandle,
++                new int[] {roi.left, roi.top, roi.width(), roi.height()});
+     }
+ 
+-    ImageClassifierOptions(Builder builder) {
+-      displayNamesLocale = builder.displayNamesLocale;
+-      maxResults = builder.maxResults;
+-      scoreThreshold = builder.scoreThreshold;
+-      isScoreThresholdSet = builder.isScoreThresholdSet;
+-      labelAllowList = builder.labelAllowList;
+-      labelDenyList = builder.labelDenyList;
+-      numThreads = builder.numThreads;
+-      baseOptions = builder.baseOptions;
++    private static native long initJniWithModelFdAndOptions(int fileDescriptor,
++            long fileDescriptorLength, long fileDescriptorOffset, ImageClassifierOptions options,
++            long baseOptionsHandle);
++
++    private static native long initJniWithByteBuffer(
++            ByteBuffer modelBuffer, ImageClassifierOptions options, long baseOptionsHandle);
++
++    /**
++     * The native method to classify an image with the ROI and orientation.
++     *
++     * @param roi the ROI of the input image, an array representing the bounding box as {left, top,
++     *     width, height}
++     */
++    private static native List<Classifications> classifyNative(
++            long nativeHandle, long frameBufferHandle, int[] roi);
++
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
+     }
+-  }
+-
+-  /**
+-   * Performs actual classification on the provided {@link TensorImage}.
+-   *
+-   * <p>{@link ImageClassifier} supports the following {@link TensorImage} color space types:
+-   *
+-   * <ul>
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+-   * </ul>
+-   *
+-   * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Classifications> classify(TensorImage image) {
+-    return classify(image, ImageProcessingOptions.builder().build());
+-  }
+-
+-  /**
+-   * Performs actual classification on the provided {@link TensorImage} with {@link
+-   * ImageProcessingOptions}.
+-   *
+-   * <p>{@link ImageClassifier} supports the following options:
+-   *
+-   * <ul>
+-   *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions.Builder#setRoi}). It
+-   *       defaults to the entire image.
+-   *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+-   *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}.
+-   * </ul>
+-   *
+-   * <p>{@link ImageClassifier} supports the following {@link TensorImage} color space types:
+-   *
+-   * <ul>
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+-   * </ul>
+-   *
+-   * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Classifications> classify(TensorImage image, ImageProcessingOptions options) {
+-    return run(
+-        new InferenceProvider<List<Classifications>>() {
+-          @Override
+-          public List<Classifications> run(
+-              long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+-            return classify(frameBufferHandle, width, height, options);
+-          }
+-        },
+-        image,
+-        options);
+-  }
+-
+-  /**
+-   * Performs actual classification on the provided {@code MlImage}.
+-   *
+-   * @param image an {@code MlImage} object that represents an image
+-   * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+-   */
+-  public List<Classifications> classify(MlImage image) {
+-    return classify(image, ImageProcessingOptions.builder().build());
+-  }
+-
+-  /**
+-   * Performs actual classification on the provided {@code MlImage} with {@link
+-   * ImageProcessingOptions}.
+-   *
+-   * <p>{@link ImageClassifier} supports the following options:
+-   *
+-   * <ul>
+-   *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions.Builder#setRoi}). It
+-   *       defaults to the entire image.
+-   *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+-   *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
+-   *       MlImage#getRotation()} is not effective.
+-   * </ul>
+-   *
+-   * @param image a {@code MlImage} object that represents an image
+-   * @param options configures options including ROI and rotation
+-   * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+-   */
+-  public List<Classifications> classify(MlImage image, ImageProcessingOptions options) {
+-    image.getInternal().acquire();
+-    TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+-    List<Classifications> result = classify(tensorImage, options);
+-    image.close();
+-    return result;
+-  }
+-
+-  private List<Classifications> classify(
+-      long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+-    checkNotClosed();
+-
+-    Rect roi = options.getRoi().isEmpty() ? new Rect(0, 0, width, height) : options.getRoi();
+-
+-    return classifyNative(
+-        getNativeHandle(),
+-        frameBufferHandle,
+-        new int[] {roi.left, roi.top, roi.width(), roi.height()});
+-  }
+-
+-  private static native long initJniWithModelFdAndOptions(
+-      int fileDescriptor,
+-      long fileDescriptorLength,
+-      long fileDescriptorOffset,
+-      ImageClassifierOptions options,
+-      long baseOptionsHandle);
+-
+-  private static native long initJniWithByteBuffer(
+-      ByteBuffer modelBuffer, ImageClassifierOptions options, long baseOptionsHandle);
+-
+-  /**
+-   * The native method to classify an image with the ROI and orientation.
+-   *
+-   * @param roi the ROI of the input image, an array representing the bounding box as {left, top,
+-   *     width, height}
+-   */
+-  private static native List<Classifications> classifyNative(
+-      long nativeHandle, long frameBufferHandle, int[] roi);
+-
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
+-
+-  /**
+-   * Native implementation to release memory pointed by the pointer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private native void deinitJni(long nativeHandle);
++
++    /**
++     * Native implementation to release memory pointed by the pointer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java
+index fdc898f451337..59ab62a949a25 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java
+@@ -21,213 +21,184 @@ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.c
+ import android.graphics.ImageFormat;
+ import android.media.Image;
+ import android.media.Image.Plane;
++
+ import com.google.auto.value.AutoValue;
+-import java.nio.ByteBuffer;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.image.ColorSpaceType;
+ import org.tensorflow.lite.support.image.TensorImage;
+ import org.tensorflow.lite.task.core.BaseTaskApi;
+ import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+ 
++import java.nio.ByteBuffer;
++
+ /** Base class for Task Vision APIs. */
+ public abstract class BaseVisionTaskApi extends BaseTaskApi {
+-
+-  /** Syntax sugar to run vision tasks with FrameBuffer and image processing options. */
+-  public interface InferenceProvider<T> {
+-    T run(long frameBufferHandle, int width, int height, ImageProcessingOptions options);
+-  }
+-
+-  protected BaseVisionTaskApi(long nativeHandle) {
+-    super(nativeHandle);
+-  }
+-
+-  /** Runs inference with {@link TensorImage} and {@link ImageProcessingOptions}. */
+-  protected <T> T run(
+-      InferenceProvider<T> provider, TensorImage image, ImageProcessingOptions options) {
+-    FrameBufferData frameBufferData = createFrameBuffer(image, options.getOrientation().getValue());
+-    T results =
+-        provider.run(
+-            frameBufferData.getFrameBufferHandle(), image.getWidth(), image.getHeight(), options);
+-    deleteFrameBuffer(
+-        frameBufferData.getFrameBufferHandle(),
+-        frameBufferData.getByteArrayHandle(),
+-        frameBufferData.getByteArray());
+-    return results;
+-  }
+-
+-  private static FrameBufferData createFrameBuffer(TensorImage image, int orientation) {
+-    ColorSpaceType colorSpaceType = image.getColorSpaceType();
+-    switch (colorSpaceType) {
+-      case RGB:
+-      case NV12:
+-      case NV21:
+-      case YV12:
+-      case YV21:
+-        // All these types can be converted to ByteBuffer inside TensorImage. Creating FrameBuffer
+-        // base on the image ByteBuffer.
+-        return createFrameBufferFromByteBuffer(image, orientation);
+-      case YUV_420_888:
+-        // YUV_420_888 is a specific type for android.media.Image.
+-        return createFrameBufferFromMediaImage(image, orientation);
+-      default:
+-        throw new IllegalArgumentException(
+-            "Color space type, " + colorSpaceType.name() + ", is unsupported.");
++    /** Syntax sugar to run vision tasks with FrameBuffer and image processing options. */
++    public interface InferenceProvider<T> {
++        T run(long frameBufferHandle, int width, int height, ImageProcessingOptions options);
+     }
+-  }
+-
+-  /**
+-   * Creates FrameBuffer from the {@link android.media.Image} stored in the given {@link
+-   * TensorImage}.
+-   */
+-  private static FrameBufferData createFrameBufferFromMediaImage(
+-      TensorImage image, int orientation) {
+-    Image mediaImage = image.getMediaImage();
+-
+-    checkArgument(
+-        mediaImage.getFormat() == ImageFormat.YUV_420_888,
+-        "Only supports loading YUV_420_888 Image.");
+-
+-    Plane[] planes = mediaImage.getPlanes();
+-    checkArgument(
+-        planes.length == 3,
+-        String.format("The input image should have 3 planes, but got %d plane(s).", planes.length));
+-
+-    // Verify and rewind planes.
+-    for (Plane plane : planes) {
+-      ByteBuffer buffer = plane.getBuffer();
+-      checkNotNull(buffer, "The image buffer is corrupted and the plane is null.");
+-      // From the public documentation, plane.getBuffer() should always return a direct ByteBuffer.
+-      // See https://developer.android.com/reference/android/media/Image.Plane#getBuffer()
+-      checkArgument(
+-          buffer.isDirect(),
+-          "The image plane buffer is not a direct ByteBuffer, and is not supported.");
+-      buffer.rewind();
++
++    protected BaseVisionTaskApi(long nativeHandle) {
++        super(nativeHandle);
+     }
+ 
+-    return FrameBufferData.create(
+-        createFrameBufferFromPlanes(
+-            planes[0].getBuffer(),
+-            planes[1].getBuffer(),
+-            planes[2].getBuffer(),
+-            mediaImage.getWidth(),
+-            mediaImage.getHeight(),
+-            planes[0].getRowStride(),
+-            // row_stride and pixel_stride should be identical for U/V planes.
+-            planes[1].getRowStride(),
+-            planes[1].getPixelStride(),
+-            orientation),
+-        // FrameBuffer created with direct ByteBuffer does not require memory freeing.
+-        /*byteArrayHandle=*/ 0,
+-        /*byteArray=*/ new byte[0]);
+-  }
+-
+-  /** Creates FrameBuffer from the {@link ByteBuffer} stored in the given {@link TensorImage}. */
+-  private static FrameBufferData createFrameBufferFromByteBuffer(
+-      TensorImage image, int orientation) {
+-    // base_vision_api_jni.cc expects an uint8 image. Convert image of other types into uint8.
+-    TensorImage imageUint8 =
+-        image.getDataType() == DataType.UINT8
+-            ? image
+-            : TensorImage.createFrom(image, DataType.UINT8);
+-
+-    ByteBuffer byteBuffer = imageUint8.getBuffer();
+-    byteBuffer.rewind();
+-    ColorSpaceType colorSpaceType = image.getColorSpaceType();
+-    if (byteBuffer.isDirect()) {
+-      return FrameBufferData.create(
+-          createFrameBufferFromByteBuffer(
+-              byteBuffer,
+-              imageUint8.getWidth(),
+-              imageUint8.getHeight(),
+-              orientation,
+-              colorSpaceType.getValue()),
+-          // FrameBuffer created with direct ByteBuffer does not require memory freeing.
+-          /*byteArrayHandle=*/ 0,
+-          /*byteArray=*/ new byte[0]);
+-    } else {
+-      // If the byte array is copied in jni (during GetByteArrayElements), need to free
+-      // the copied array once inference is done.
+-      long[] byteArrayHandle = new long[1];
+-      byte[] byteArray = getBytesFromByteBuffer(byteBuffer);
+-      return FrameBufferData.create(
+-          createFrameBufferFromBytes(
+-              byteArray,
+-              imageUint8.getWidth(),
+-              imageUint8.getHeight(),
+-              orientation,
+-              colorSpaceType.getValue(),
+-              byteArrayHandle),
+-          byteArrayHandle[0],
+-          byteArray);
++    /** Runs inference with {@link TensorImage} and {@link ImageProcessingOptions}. */
++    protected <T> T run(
++            InferenceProvider<T> provider, TensorImage image, ImageProcessingOptions options) {
++        FrameBufferData frameBufferData =
++                createFrameBuffer(image, options.getOrientation().getValue());
++        T results = provider.run(frameBufferData.getFrameBufferHandle(), image.getWidth(),
++                image.getHeight(), options);
++        deleteFrameBuffer(frameBufferData.getFrameBufferHandle(),
++                frameBufferData.getByteArrayHandle(), frameBufferData.getByteArray());
++        return results;
+     }
+-  }
+ 
+-  /** Holds the FrameBuffer and the underlying data pointers in C++. */
+-  @AutoValue
+-  abstract static class FrameBufferData {
++    private static FrameBufferData createFrameBuffer(TensorImage image, int orientation) {
++        ColorSpaceType colorSpaceType = image.getColorSpaceType();
++        switch (colorSpaceType) {
++            case RGB:
++            case NV12:
++            case NV21:
++            case YV12:
++            case YV21:
++                // All these types can be converted to ByteBuffer inside TensorImage. Creating
++                // FrameBuffer base on the image ByteBuffer.
++                return createFrameBufferFromByteBuffer(image, orientation);
++            case YUV_420_888:
++                // YUV_420_888 is a specific type for android.media.Image.
++                return createFrameBufferFromMediaImage(image, orientation);
++            default:
++                throw new IllegalArgumentException(
++                        "Color space type, " + colorSpaceType.name() + ", is unsupported.");
++        }
++    }
+ 
+     /**
+-     * Initializes a {@link FrameBufferData} object.
+-     *
+-     * @param frameBufferHandle the native handle to the FrameBuffer object.
+-     * @param byteArrayHandle the native handle to the data array that backs up the FrameBuffer
+-     *     object. If the FrameBuffer is created on a byte array, this byte array need to be freed
+-     *     after inference is done. If the FrameBuffer is created on a direct ByteBuffer, no byte
+-     *     array needs to be freed, and byteArrayHandle will be 0.
+-     * @param byteArray the byte array that is used to create the c++ byte array object, which is
+-     *     needed when releasing byteArrayHandle. If the FrameBuffer is created on a direct
+-     *     ByteBuffer (no byte array needs to be freed), pass in an empty array for {@code
+-     *     byteArray}.
++     * Creates FrameBuffer from the {@link android.media.Image} stored in the given {@link
++     * TensorImage}.
+      */
+-    public static FrameBufferData create(
+-        long frameBufferHandle, long byteArrayHandle, byte[] byteArray) {
+-      return new AutoValue_BaseVisionTaskApi_FrameBufferData(
+-          frameBufferHandle, byteArrayHandle, byteArray);
++    private static FrameBufferData createFrameBufferFromMediaImage(
++            TensorImage image, int orientation) {
++        Image mediaImage = image.getMediaImage();
++
++        checkArgument(mediaImage.getFormat() == ImageFormat.YUV_420_888,
++                "Only supports loading YUV_420_888 Image.");
++
++        Plane[] planes = mediaImage.getPlanes();
++        checkArgument(planes.length == 3,
++                String.format("The input image should have 3 planes, but got %d plane(s).",
++                        planes.length));
++
++        // Verify and rewind planes.
++        for (Plane plane : planes) {
++            ByteBuffer buffer = plane.getBuffer();
++            checkNotNull(buffer, "The image buffer is corrupted and the plane is null.");
++            // From the public documentation, plane.getBuffer() should always return a direct
++            // ByteBuffer. See
++            // https://developer.android.com/reference/android/media/Image.Plane#getBuffer()
++            checkArgument(buffer.isDirect(),
++                    "The image plane buffer is not a direct ByteBuffer, and is not supported.");
++            buffer.rewind();
++        }
++
++        return FrameBufferData.create(
++                createFrameBufferFromPlanes(planes[0].getBuffer(), planes[1].getBuffer(),
++                        planes[2].getBuffer(), mediaImage.getWidth(), mediaImage.getHeight(),
++                        planes[0].getRowStride(),
++                        // row_stride and pixel_stride should be identical for U/V planes.
++                        planes[1].getRowStride(), planes[1].getPixelStride(), orientation),
++                // FrameBuffer created with direct ByteBuffer does not require memory freeing.
++                /*byteArrayHandle=*/0,
++                /*byteArray=*/new byte[0]);
++    }
++
++    /** Creates FrameBuffer from the {@link ByteBuffer} stored in the given {@link TensorImage}. */
++    private static FrameBufferData createFrameBufferFromByteBuffer(
++            TensorImage image, int orientation) {
++        // base_vision_api_jni.cc expects an uint8 image. Convert image of other types into uint8.
++        TensorImage imageUint8 = image.getDataType() == DataType.UINT8
++                ? image
++                : TensorImage.createFrom(image, DataType.UINT8);
++
++        ByteBuffer byteBuffer = imageUint8.getBuffer();
++        byteBuffer.rewind();
++        ColorSpaceType colorSpaceType = image.getColorSpaceType();
++        if (byteBuffer.isDirect()) {
++            return FrameBufferData.create(
++                    createFrameBufferFromByteBuffer(byteBuffer, imageUint8.getWidth(),
++                            imageUint8.getHeight(), orientation, colorSpaceType.getValue()),
++                    // FrameBuffer created with direct ByteBuffer does not require memory freeing.
++                    /*byteArrayHandle=*/0,
++                    /*byteArray=*/new byte[0]);
++        } else {
++            // If the byte array is copied in jni (during GetByteArrayElements), need to free
++            // the copied array once inference is done.
++            long[] byteArrayHandle = new long[1];
++            byte[] byteArray = getBytesFromByteBuffer(byteBuffer);
++            return FrameBufferData.create(
++                    createFrameBufferFromBytes(byteArray, imageUint8.getWidth(),
++                            imageUint8.getHeight(), orientation, colorSpaceType.getValue(),
++                            byteArrayHandle),
++                    byteArrayHandle[0], byteArray);
++        }
++    }
++
++    /** Holds the FrameBuffer and the underlying data pointers in C++. */
++    @AutoValue
++    abstract static class FrameBufferData {
++        /**
++         * Initializes a {@link FrameBufferData} object.
++         *
++         * @param frameBufferHandle the native handle to the FrameBuffer object.
++         * @param byteArrayHandle the native handle to the data array that backs up the FrameBuffer
++         *     object. If the FrameBuffer is created on a byte array, this byte array need to be
++         * freed after inference is done. If the FrameBuffer is created on a direct ByteBuffer, no
++         * byte array needs to be freed, and byteArrayHandle will be 0.
++         * @param byteArray the byte array that is used to create the c++ byte array object, which
++         *         is
++         *     needed when releasing byteArrayHandle. If the FrameBuffer is created on a direct
++         *     ByteBuffer (no byte array needs to be freed), pass in an empty array for {@code
++         *     byteArray}.
++         */
++        public static FrameBufferData create(
++                long frameBufferHandle, long byteArrayHandle, byte[] byteArray) {
++            return new AutoValue_BaseVisionTaskApi_FrameBufferData(
++                    frameBufferHandle, byteArrayHandle, byteArray);
++        }
++
++        abstract long getFrameBufferHandle();
++
++        abstract long getByteArrayHandle();
++
++        // Package private method for transferring data.
++        @SuppressWarnings("mutable")
++        abstract byte[] getByteArray();
+     }
+ 
+-    abstract long getFrameBufferHandle();
+-
+-    abstract long getByteArrayHandle();
+-
+-    // Package private method for transferring data.
+-    @SuppressWarnings("mutable")
+-    abstract byte[] getByteArray();
+-  }
+-
+-  private static native long createFrameBufferFromByteBuffer(
+-      ByteBuffer image, int width, int height, int orientation, int colorSpaceType);
+-
+-  private static native long createFrameBufferFromBytes(
+-      byte[] image,
+-      int width,
+-      int height,
+-      int orientation,
+-      int colorSpaceType,
+-      long[] byteArrayHandle);
+-
+-  private static native long createFrameBufferFromPlanes(
+-      ByteBuffer yBuffer,
+-      ByteBuffer uBuffer,
+-      ByteBuffer vBuffer,
+-      int width,
+-      int height,
+-      int yRowStride,
+-      int uvRowStride,
+-      int uvPixelStride,
+-      int orientation);
+-
+-  private static native void deleteFrameBuffer(
+-      long frameBufferHandle, long byteArrayHandle, byte[] byteArray);
+-
+-  private static byte[] getBytesFromByteBuffer(ByteBuffer byteBuffer) {
+-    // If the ByteBuffer has a back up array, use it directly without copy.
+-    if (byteBuffer.hasArray() && byteBuffer.arrayOffset() == 0) {
+-      return byteBuffer.array();
++    private static native long createFrameBufferFromByteBuffer(
++            ByteBuffer image, int width, int height, int orientation, int colorSpaceType);
++
++    private static native long createFrameBufferFromBytes(byte[] image, int width, int height,
++            int orientation, int colorSpaceType, long[] byteArrayHandle);
++
++    private static native long createFrameBufferFromPlanes(ByteBuffer yBuffer, ByteBuffer uBuffer,
++            ByteBuffer vBuffer, int width, int height, int yRowStride, int uvRowStride,
++            int uvPixelStride, int orientation);
++
++    private static native void deleteFrameBuffer(
++            long frameBufferHandle, long byteArrayHandle, byte[] byteArray);
++
++    private static byte[] getBytesFromByteBuffer(ByteBuffer byteBuffer) {
++        // If the ByteBuffer has a back up array, use it directly without copy.
++        if (byteBuffer.hasArray() && byteBuffer.arrayOffset() == 0) {
++            return byteBuffer.array();
++        }
++        // Copy out the data otherwise.
++        byteBuffer.rewind();
++        byte[] bytes = new byte[byteBuffer.limit()];
++        byteBuffer.get(bytes, 0, bytes.length);
++        return bytes;
+     }
+-    // Copy out the data otherwise.
+-    byteBuffer.rewind();
+-    byte[] bytes = new byte[byteBuffer.limit()];
+-    byteBuffer.get(bytes, 0, bytes.length);
+-    return bytes;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/Detection.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/Detection.java
+index 007e032d8b331..7106fe8a08b35 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/Detection.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/Detection.java
+@@ -16,27 +16,29 @@ limitations under the License.
+ package org.tensorflow.lite.task.vision.detector;
+ 
+ import android.graphics.RectF;
++
+ import com.google.auto.value.AutoValue;
++
++import org.tensorflow.lite.annotations.UsedByReflection;
++import org.tensorflow.lite.support.label.Category;
++
+ import java.util.ArrayList;
+ import java.util.Collections;
+ import java.util.List;
+-import org.tensorflow.lite.annotations.UsedByReflection;
+-import org.tensorflow.lite.support.label.Category;
+ 
+ /** Represents one detected object in the results of a {@link ObjectDetector}. */
+ @AutoValue
+ @UsedByReflection("object_detection_jni.cc")
+ public abstract class Detection {
++    @UsedByReflection("object_detection_jni.cc")
++    public static Detection create(RectF boundingBox, List<Category> categories) {
++        return new AutoValue_Detection(new RectF(boundingBox),
++                Collections.unmodifiableList(new ArrayList<Category>(categories)));
++    }
+ 
+-  @UsedByReflection("object_detection_jni.cc")
+-  public static Detection create(RectF boundingBox, List<Category> categories) {
+-    return new AutoValue_Detection(
+-        new RectF(boundingBox), Collections.unmodifiableList(new ArrayList<Category>(categories)));
+-  }
+-
+-  public abstract RectF getBoundingBox();
++    public abstract RectF getBoundingBox();
+ 
+-  // Same reason for not using ImmutableList as stated in
+-  // {@link ObjectDetector#ObjectDetectorOptions#labelAllowList}.
+-  public abstract List<Category> getCategories();
++    // Same reason for not using ImmutableList as stated in
++    // {@link ObjectDetector#ObjectDetectorOptions#labelAllowList}.
++    public abstract List<Category> getCategories();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java
+index e2046d15a7351..c0585b8eda6aa 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java
+@@ -17,14 +17,9 @@ package org.tensorflow.lite.task.vision.detector;
+ 
+ import android.content.Context;
+ import android.os.ParcelFileDescriptor;
++
+ import com.google.android.odml.image.MlImage;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.MappedByteBuffer;
+-import java.util.ArrayList;
+-import java.util.Collections;
+-import java.util.List;
++
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ import org.tensorflow.lite.support.image.MlImageAdapter;
+ import org.tensorflow.lite.support.image.TensorImage;
+@@ -35,6 +30,14 @@ import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
+ import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.MappedByteBuffer;
++import java.util.ArrayList;
++import java.util.Collections;
++import java.util.List;
++
+ /**
+  * Performs object detection on images.
+  *
+@@ -86,469 +89,447 @@ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
+  * Hub.</a>.
+  */
+ public final class ObjectDetector extends BaseVisionTaskApi {
++    private static final String OBJECT_DETECTOR_NATIVE_LIB = "task_vision_jni";
++    private static final int OPTIONAL_FD_LENGTH = -1;
++    private static final int OPTIONAL_FD_OFFSET = -1;
++
++    /**
++     * Creates an {@link ObjectDetector} instance from the default {@link ObjectDetectorOptions}.
++     *
++     * @param modelPath path to the detection model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ObjectDetector createFromFile(Context context, String modelPath)
++            throws IOException {
++        return createFromFileAndOptions(
++                context, modelPath, ObjectDetectorOptions.builder().build());
++    }
+ 
+-  private static final String OBJECT_DETECTOR_NATIVE_LIB = "task_vision_jni";
+-  private static final int OPTIONAL_FD_LENGTH = -1;
+-  private static final int OPTIONAL_FD_OFFSET = -1;
+-
+-  /**
+-   * Creates an {@link ObjectDetector} instance from the default {@link ObjectDetectorOptions}.
+-   *
+-   * @param modelPath path to the detection model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ObjectDetector createFromFile(Context context, String modelPath)
+-      throws IOException {
+-    return createFromFileAndOptions(context, modelPath, ObjectDetectorOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ObjectDetector} instance from the default {@link ObjectDetectorOptions}.
+-   *
+-   * @param modelFile the detection model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ObjectDetector createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, ObjectDetectorOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ObjectDetector} instance with a model buffer and the default {@link
+-   * ObjectDetectorOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the detection
+-   *     model
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer} * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ObjectDetector createFromBuffer(final ByteBuffer modelBuffer) {
+-    return createFromBufferAndOptions(modelBuffer, ObjectDetectorOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ObjectDetector} instance from {@link ObjectDetectorOptions}.
+-   *
+-   * @param modelPath path to the detection model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ObjectDetector createFromFileAndOptions(
+-      Context context, String modelPath, ObjectDetectorOptions options) throws IOException {
+-    return new ObjectDetector(
+-        TaskJniUtils.createHandleFromFdAndOptions(
+-            context,
+-            new FdAndOptionsHandleProvider<ObjectDetectorOptions>() {
+-              @Override
+-              public long createHandle(
+-                  int fileDescriptor,
+-                  long fileDescriptorLength,
+-                  long fileDescriptorOffset,
+-                  ObjectDetectorOptions options) {
+-                return initJniWithModelFdAndOptions(
+-                    fileDescriptor,
+-                    fileDescriptorLength,
+-                    fileDescriptorOffset,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                        options.getBaseOptions(), options.getNumThreads()));
+-              }
+-            },
+-            OBJECT_DETECTOR_NATIVE_LIB,
+-            modelPath,
+-            options));
+-  }
+-
+-  /**
+-   * Creates an {@link ObjectDetector} instance from {@link ObjectDetectorOptions}.
+-   *
+-   * @param modelFile the detection model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ObjectDetector createFromFileAndOptions(
+-      File modelFile, final ObjectDetectorOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return new ObjectDetector(
+-          TaskJniUtils.createHandleFromLibrary(
+-              new TaskJniUtils.EmptyHandleProvider() {
+-                @Override
+-                public long createHandle() {
+-                  return initJniWithModelFdAndOptions(
+-                      descriptor.getFd(),
+-                      /*fileDescriptorLength=*/ OPTIONAL_FD_LENGTH,
+-                      /*fileDescriptorOffset=*/ OPTIONAL_FD_OFFSET,
+-                      options,
+-                      TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                          options.getBaseOptions(), options.getNumThreads()));
+-                }
+-              },
+-              OBJECT_DETECTOR_NATIVE_LIB));
++    /**
++     * Creates an {@link ObjectDetector} instance from the default {@link ObjectDetectorOptions}.
++     *
++     * @param modelFile the detection model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ObjectDetector createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, ObjectDetectorOptions.builder().build());
+     }
+-  }
+-
+-  /**
+-   * Creates an {@link ObjectDetector} instance with a model buffer and {@link
+-   * ObjectDetectorOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the detection
+-   *     model
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ObjectDetector createFromBufferAndOptions(
+-      final ByteBuffer modelBuffer, final ObjectDetectorOptions options) {
+-    if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+-      throw new IllegalArgumentException(
+-          "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++
++    /**
++     * Creates an {@link ObjectDetector} instance with a model buffer and the default {@link
++     * ObjectDetectorOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the detection
++     *     model
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer} * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ObjectDetector createFromBuffer(final ByteBuffer modelBuffer) {
++        return createFromBufferAndOptions(modelBuffer, ObjectDetectorOptions.builder().build());
+     }
+-    return new ObjectDetector(
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                return initJniWithByteBuffer(
+-                    modelBuffer,
+-                    options,
+-                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                        options.getBaseOptions(), options.getNumThreads()));
+-              }
+-            },
+-            OBJECT_DETECTOR_NATIVE_LIB));
+-  }
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++
+-   */
+-  private ObjectDetector(long nativeHandle) {
+-    super(nativeHandle);
+-  }
+-
+-  /** Options for setting up an ObjectDetector. */
+-  @UsedByReflection("object_detector_jni.cc")
+-  public static class ObjectDetectorOptions {
+-    // Not using AutoValue for this class because scoreThreshold cannot have default value
+-    // (otherwise, the default value would override the one in the model metadata) and `Optional` is
+-    // not an option here, because
+-    // 1. java.util.Optional require Java 8 while we need to support Java 7.
+-    // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See the
+-    // comments for labelAllowList.
+-    private final BaseOptions baseOptions;
+-    private final String displayNamesLocale;
+-    private final int maxResults;
+-    private final float scoreThreshold;
+-    private final boolean isScoreThresholdSet;
+-    // As an open source project, we've been trying avoiding depending on common java libraries,
+-    // such as Guava, because it may introduce conflicts with clients who also happen to use those
+-    // libraries. Therefore, instead of using ImmutableList here, we convert the List into
+-    // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
+-    // vulnerable.
+-    private final List<String> labelAllowList;
+-    private final List<String> labelDenyList;
+-    private final int numThreads;
+-
+-    public static Builder builder() {
+-      return new Builder();
++
++    /**
++     * Creates an {@link ObjectDetector} instance from {@link ObjectDetectorOptions}.
++     *
++     * @param modelPath path to the detection model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ObjectDetector createFromFileAndOptions(
++            Context context, String modelPath, ObjectDetectorOptions options) throws IOException {
++        return new ObjectDetector(TaskJniUtils.createHandleFromFdAndOptions(
++                context, new FdAndOptionsHandleProvider<ObjectDetectorOptions>() {
++                    @Override
++                    public long createHandle(int fileDescriptor, long fileDescriptorLength,
++                            long fileDescriptorOffset, ObjectDetectorOptions options) {
++                        return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
++                                fileDescriptorOffset, options,
++                                TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                        options.getBaseOptions(), options.getNumThreads()));
++                    }
++                }, OBJECT_DETECTOR_NATIVE_LIB, modelPath, options));
+     }
+ 
+-    /** A builder that helps to configure an instance of ObjectDetectorOptions. */
+-    public static class Builder {
+-      private BaseOptions baseOptions = BaseOptions.builder().build();
+-      private String displayNamesLocale = "en";
+-      private int maxResults = -1;
+-      private float scoreThreshold;
+-      private boolean isScoreThresholdSet = false;
+-      private List<String> labelAllowList = new ArrayList<>();
+-      private List<String> labelDenyList = new ArrayList<>();
+-      private int numThreads = -1;
+-
+-      private Builder() {}
+-
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public Builder setBaseOptions(BaseOptions baseOptions) {
+-        this.baseOptions = baseOptions;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the locale to use for display names specified through the TFLite Model Metadata, if
+-       * any.
+-       *
+-       * <p>Defaults to English({@code "en"}). See the <a
+-       * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
+-       * Metadata schema file.</a> for the accepted pattern of locale.
+-       */
+-      public Builder setDisplayNamesLocale(String displayNamesLocale) {
+-        this.displayNamesLocale = displayNamesLocale;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the maximum number of top-scored detection results to return.
+-       *
+-       * <p>If < 0, all available results will be returned. If 0, an invalid argument error is
+-       * returned. Note that models may intrinsically be limited to returning a maximum number of
+-       * results N: if the provided value here is above N, only N results will be returned. Defaults
+-       * to -1.
+-       *
+-       * @throws IllegalArgumentException if maxResults is 0.
+-       */
+-      public Builder setMaxResults(int maxResults) {
+-        if (maxResults == 0) {
+-          throw new IllegalArgumentException("maxResults cannot be 0.");
++    /**
++     * Creates an {@link ObjectDetector} instance from {@link ObjectDetectorOptions}.
++     *
++     * @param modelFile the detection model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ObjectDetector createFromFileAndOptions(
++            File modelFile, final ObjectDetectorOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return new ObjectDetector(
++                    TaskJniUtils.createHandleFromLibrary(new TaskJniUtils.EmptyHandleProvider() {
++                        @Override
++                        public long createHandle() {
++                            return initJniWithModelFdAndOptions(descriptor.getFd(),
++                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
++                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options,
++                                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                            options.getBaseOptions(), options.getNumThreads()));
++                        }
++                    }, OBJECT_DETECTOR_NATIVE_LIB));
+         }
+-        this.maxResults = maxResults;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the score threshold that overrides the one provided in the model metadata (if any).
+-       * Results below this value are rejected.
+-       */
+-      public Builder setScoreThreshold(float scoreThreshold) {
+-        this.scoreThreshold = scoreThreshold;
+-        this.isScoreThresholdSet = true;
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the optional allow list of labels.
+-       *
+-       * <p>If non-empty, detection results whose label is not in this set will be filtered out.
+-       * Duplicate or unknown labels are ignored. Mutually exclusive with {@code labelDenyList}. It
+-       * will cause {@link IllegalStateException} when calling {@link #createFromFileAndOptions}, if
+-       * both {@code labelDenyList} and {@code labelAllowList} are set.
+-       */
+-      public Builder setLabelAllowList(List<String> labelAllowList) {
+-        this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the optional deny list of labels.
+-       *
+-       * <p>If non-empty, detection results whose label is in this set will be filtered out.
+-       * Duplicate or unknown labels are ignored. Mutually exclusive with {@code labelAllowList}. It
+-       * will cause {@link IllegalStateException} when calling {@link #createFromFileAndOptions}, if
+-       * both {@code labelDenyList} and {@code labelAllowList} are set.
+-       */
+-      public Builder setLabelDenyList(List<String> labelDenyList) {
+-        this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
+-        return this;
+-      }
+-
+-      /**
+-       * Sets the number of threads to be used for TFLite ops that support multi-threading when
+-       * running inference with CPU. Defaults to -1.
+-       *
+-       * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has the
+-       * effect to let TFLite runtime set the value.
+-       *
+-       * @deprecated use {@link BaseOptions} to configure number of threads instead. This method
+-       *     will override the number of threads configured from {@link BaseOptions}.
+-       */
+-      @Deprecated
+-      public Builder setNumThreads(int numThreads) {
+-        this.numThreads = numThreads;
+-        return this;
+-      }
+-
+-      public ObjectDetectorOptions build() {
+-        return new ObjectDetectorOptions(this);
+-      }
+     }
+ 
+-    @UsedByReflection("object_detector_jni.cc")
+-    public String getDisplayNamesLocale() {
+-      return displayNamesLocale;
++    /**
++     * Creates an {@link ObjectDetector} instance with a model buffer and {@link
++     * ObjectDetectorOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the detection
++     *     model
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ObjectDetector createFromBufferAndOptions(
++            final ByteBuffer modelBuffer, final ObjectDetectorOptions options) {
++        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
++            throw new IllegalArgumentException(
++                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++        }
++        return new ObjectDetector(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                return initJniWithByteBuffer(modelBuffer, options,
++                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                options.getBaseOptions(), options.getNumThreads()));
++            }
++        }, OBJECT_DETECTOR_NATIVE_LIB));
+     }
+ 
+-    @UsedByReflection("object_detector_jni.cc")
+-    public int getMaxResults() {
+-      return maxResults;
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++
++     */
++    private ObjectDetector(long nativeHandle) {
++        super(nativeHandle);
+     }
+ 
++    /** Options for setting up an ObjectDetector. */
+     @UsedByReflection("object_detector_jni.cc")
+-    public float getScoreThreshold() {
+-      return scoreThreshold;
++    public static class ObjectDetectorOptions {
++        // Not using AutoValue for this class because scoreThreshold cannot have default value
++        // (otherwise, the default value would override the one in the model metadata) and
++        // `Optional` is not an option here, because
++        // 1. java.util.Optional require Java 8 while we need to support Java 7.
++        // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See
++        // the comments for labelAllowList.
++        private final BaseOptions baseOptions;
++        private final String displayNamesLocale;
++        private final int maxResults;
++        private final float scoreThreshold;
++        private final boolean isScoreThresholdSet;
++        // As an open source project, we've been trying avoiding depending on common java libraries,
++        // such as Guava, because it may introduce conflicts with clients who also happen to use
++        // those libraries. Therefore, instead of using ImmutableList here, we convert the List into
++        // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
++        // vulnerable.
++        private final List<String> labelAllowList;
++        private final List<String> labelDenyList;
++        private final int numThreads;
++
++        public static Builder builder() {
++            return new Builder();
++        }
++
++        /** A builder that helps to configure an instance of ObjectDetectorOptions. */
++        public static class Builder {
++            private BaseOptions baseOptions = BaseOptions.builder().build();
++            private String displayNamesLocale = "en";
++            private int maxResults = -1;
++            private float scoreThreshold;
++            private boolean isScoreThresholdSet = false;
++            private List<String> labelAllowList = new ArrayList<>();
++            private List<String> labelDenyList = new ArrayList<>();
++            private int numThreads = -1;
++
++            private Builder() {}
++
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public Builder setBaseOptions(BaseOptions baseOptions) {
++                this.baseOptions = baseOptions;
++                return this;
++            }
++
++            /**
++             * Sets the locale to use for display names specified through the TFLite Model Metadata,
++             * if any.
++             *
++             * <p>Defaults to English({@code "en"}). See the <a
++             * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
++             * Metadata schema file.</a> for the accepted pattern of locale.
++             */
++            public Builder setDisplayNamesLocale(String displayNamesLocale) {
++                this.displayNamesLocale = displayNamesLocale;
++                return this;
++            }
++
++            /**
++             * Sets the maximum number of top-scored detection results to return.
++             *
++             * <p>If < 0, all available results will be returned. If 0, an invalid argument error is
++             * returned. Note that models may intrinsically be limited to returning a maximum number
++             * of results N: if the provided value here is above N, only N results will be returned.
++             * Defaults to -1.
++             *
++             * @throws IllegalArgumentException if maxResults is 0.
++             */
++            public Builder setMaxResults(int maxResults) {
++                if (maxResults == 0) {
++                    throw new IllegalArgumentException("maxResults cannot be 0.");
++                }
++                this.maxResults = maxResults;
++                return this;
++            }
++
++            /**
++             * Sets the score threshold that overrides the one provided in the model metadata (if
++             * any). Results below this value are rejected.
++             */
++            public Builder setScoreThreshold(float scoreThreshold) {
++                this.scoreThreshold = scoreThreshold;
++                this.isScoreThresholdSet = true;
++                return this;
++            }
++
++            /**
++             * Sets the optional allow list of labels.
++             *
++             * <p>If non-empty, detection results whose label is not in this set will be filtered
++             * out. Duplicate or unknown labels are ignored. Mutually exclusive with {@code
++             * labelDenyList}. It will cause {@link IllegalStateException} when calling {@link
++             * #createFromFileAndOptions}, if both {@code labelDenyList} and {@code labelAllowList}
++             * are set.
++             */
++            public Builder setLabelAllowList(List<String> labelAllowList) {
++                this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
++                return this;
++            }
++
++            /**
++             * Sets the optional deny list of labels.
++             *
++             * <p>If non-empty, detection results whose label is in this set will be filtered out.
++             * Duplicate or unknown labels are ignored. Mutually exclusive with {@code
++             * labelAllowList}. It will cause {@link IllegalStateException} when calling {@link
++             * #createFromFileAndOptions}, if both {@code labelDenyList} and {@code labelAllowList}
++             * are set.
++             */
++            public Builder setLabelDenyList(List<String> labelDenyList) {
++                this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
++                return this;
++            }
++
++            /**
++             * Sets the number of threads to be used for TFLite ops that support multi-threading
++             * when running inference with CPU. Defaults to -1.
++             *
++             * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has
++             * the effect to let TFLite runtime set the value.
++             *
++             * @deprecated use {@link BaseOptions} to configure number of threads instead. This
++             *         method
++             *     will override the number of threads configured from {@link BaseOptions}.
++             */
++            @Deprecated
++            public Builder setNumThreads(int numThreads) {
++                this.numThreads = numThreads;
++                return this;
++            }
++
++            public ObjectDetectorOptions build() {
++                return new ObjectDetectorOptions(this);
++            }
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public String getDisplayNamesLocale() {
++            return displayNamesLocale;
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public int getMaxResults() {
++            return maxResults;
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public float getScoreThreshold() {
++            return scoreThreshold;
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public boolean getIsScoreThresholdSet() {
++            return isScoreThresholdSet;
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public List<String> getLabelAllowList() {
++            return new ArrayList<>(labelAllowList);
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public List<String> getLabelDenyList() {
++            return new ArrayList<>(labelDenyList);
++        }
++
++        @UsedByReflection("object_detector_jni.cc")
++        public int getNumThreads() {
++            return numThreads;
++        }
++
++        public BaseOptions getBaseOptions() {
++            return baseOptions;
++        }
++
++        private ObjectDetectorOptions(Builder builder) {
++            displayNamesLocale = builder.displayNamesLocale;
++            maxResults = builder.maxResults;
++            scoreThreshold = builder.scoreThreshold;
++            isScoreThresholdSet = builder.isScoreThresholdSet;
++            labelAllowList = builder.labelAllowList;
++            labelDenyList = builder.labelDenyList;
++            numThreads = builder.numThreads;
++            baseOptions = builder.baseOptions;
++        }
+     }
+ 
+-    @UsedByReflection("object_detector_jni.cc")
+-    public boolean getIsScoreThresholdSet() {
+-      return isScoreThresholdSet;
++    /**
++     * Performs actual detection on the provided image.
++     *
++     * <p>{@link ObjectDetector} supports the following {@link TensorImage} color space types:
++     *
++     * <ul>
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
++     * </ul>
++     *
++     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Detection> detect(TensorImage image) {
++        return detect(image, ImageProcessingOptions.builder().build());
+     }
+ 
+-    @UsedByReflection("object_detector_jni.cc")
+-    public List<String> getLabelAllowList() {
+-      return new ArrayList<>(labelAllowList);
++    /**
++     * Performs actual detection on the provided image.
++     *
++     * <p>{@link ObjectDetector} supports the following {@link TensorImage} color space types:
++     *
++     * <ul>
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
++     * </ul>
++     *
++     * <p>{@link ObjectDetector} supports the following options:
++     *
++     * <ul>
++     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
++     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}.
++     * </ul>
++     *
++     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
++     * @param options the options to configure how to preprocess the image
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Detection> detect(TensorImage image, ImageProcessingOptions options) {
++        return run(new InferenceProvider<List<Detection>>() {
++            @Override
++            public List<Detection> run(
++                    long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
++                return detect(frameBufferHandle, options);
++            }
++        }, image, options);
+     }
+ 
+-    @UsedByReflection("object_detector_jni.cc")
+-    public List<String> getLabelDenyList() {
+-      return new ArrayList<>(labelDenyList);
++    /**
++     * Performs actual detection on the provided {@code MlImage}.
++     *
++     * @param image an {@code MlImage} object that represents an image
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
++     */
++    public List<Detection> detect(MlImage image) {
++        return detect(image, ImageProcessingOptions.builder().build());
+     }
+ 
+-    @UsedByReflection("object_detector_jni.cc")
+-    public int getNumThreads() {
+-      return numThreads;
++    /**
++     * Performs actual detection on the provided {@code MlImage} with {@link
++     * ImageProcessingOptions}.
++     *
++     * <p>{@link ObjectDetector} supports the following options:
++     *
++     * <ul>
++     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
++     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
++     *       MlImage#getRotation()} is not effective.
++     * </ul>
++     *
++     * @param image an {@code MlImage} object that represents an image
++     * @param options the options to configure how to preprocess the image
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
++     */
++    public List<Detection> detect(MlImage image, ImageProcessingOptions options) {
++        image.getInternal().acquire();
++        TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
++        List<Detection> result = detect(tensorImage, options);
++        image.close();
++        return result;
+     }
+ 
+-    public BaseOptions getBaseOptions() {
+-      return baseOptions;
++    private List<Detection> detect(long frameBufferHandle, ImageProcessingOptions options) {
++        checkNotClosed();
++
++        return detectNative(getNativeHandle(), frameBufferHandle);
+     }
+ 
+-    private ObjectDetectorOptions(Builder builder) {
+-      displayNamesLocale = builder.displayNamesLocale;
+-      maxResults = builder.maxResults;
+-      scoreThreshold = builder.scoreThreshold;
+-      isScoreThresholdSet = builder.isScoreThresholdSet;
+-      labelAllowList = builder.labelAllowList;
+-      labelDenyList = builder.labelDenyList;
+-      numThreads = builder.numThreads;
+-      baseOptions = builder.baseOptions;
++    private static native long initJniWithModelFdAndOptions(int fileDescriptor,
++            long fileDescriptorLength, long fileDescriptorOffset, ObjectDetectorOptions options,
++            long baseOptionsHandle);
++
++    private static native long initJniWithByteBuffer(
++            ByteBuffer modelBuffer, ObjectDetectorOptions options, long baseOptionsHandle);
++
++    private static native List<Detection> detectNative(long nativeHandle, long frameBufferHandle);
++
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
+     }
+-  }
+-
+-  /**
+-   * Performs actual detection on the provided image.
+-   *
+-   * <p>{@link ObjectDetector} supports the following {@link TensorImage} color space types:
+-   *
+-   * <ul>
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+-   * </ul>
+-   *
+-   * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Detection> detect(TensorImage image) {
+-    return detect(image, ImageProcessingOptions.builder().build());
+-  }
+-
+-  /**
+-   * Performs actual detection on the provided image.
+-   *
+-   * <p>{@link ObjectDetector} supports the following {@link TensorImage} color space types:
+-   *
+-   * <ul>
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+-   * </ul>
+-   *
+-   * <p>{@link ObjectDetector} supports the following options:
+-   *
+-   * <ul>
+-   *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+-   *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}.
+-   * </ul>
+-   *
+-   * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+-   * @param options the options to configure how to preprocess the image
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Detection> detect(TensorImage image, ImageProcessingOptions options) {
+-    return run(
+-        new InferenceProvider<List<Detection>>() {
+-          @Override
+-          public List<Detection> run(
+-              long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+-            return detect(frameBufferHandle, options);
+-          }
+-        },
+-        image,
+-        options);
+-  }
+-
+-  /**
+-   * Performs actual detection on the provided {@code MlImage}.
+-   *
+-   * @param image an {@code MlImage} object that represents an image
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+-   */
+-  public List<Detection> detect(MlImage image) {
+-    return detect(image, ImageProcessingOptions.builder().build());
+-  }
+-
+-  /**
+-   * Performs actual detection on the provided {@code MlImage} with {@link ImageProcessingOptions}.
+-   *
+-   * <p>{@link ObjectDetector} supports the following options:
+-   *
+-   * <ul>
+-   *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+-   *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
+-   *       MlImage#getRotation()} is not effective.
+-   * </ul>
+-   *
+-   * @param image an {@code MlImage} object that represents an image
+-   * @param options the options to configure how to preprocess the image
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+-   */
+-  public List<Detection> detect(MlImage image, ImageProcessingOptions options) {
+-    image.getInternal().acquire();
+-    TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+-    List<Detection> result = detect(tensorImage, options);
+-    image.close();
+-    return result;
+-  }
+-
+-  private List<Detection> detect(long frameBufferHandle, ImageProcessingOptions options) {
+-    checkNotClosed();
+-
+-    return detectNative(getNativeHandle(), frameBufferHandle);
+-  }
+-
+-  private static native long initJniWithModelFdAndOptions(
+-      int fileDescriptor,
+-      long fileDescriptorLength,
+-      long fileDescriptorOffset,
+-      ObjectDetectorOptions options,
+-      long baseOptionsHandle);
+-
+-  private static native long initJniWithByteBuffer(
+-      ByteBuffer modelBuffer, ObjectDetectorOptions options, long baseOptionsHandle);
+-
+-  private static native List<Detection> detectNative(long nativeHandle, long frameBufferHandle);
+-
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
+-
+-  /**
+-   * Native implementation to release memory pointed by the pointer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private native void deinitJni(long nativeHandle);
++
++    /**
++     * Native implementation to release memory pointed by the pointer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java
+index 0defaa9f16b96..991fedeeae9c2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java
+@@ -17,72 +17,74 @@ package org.tensorflow.lite.task.vision.segmenter;
+ 
+ import android.graphics.Color;
+ import android.os.Build;
++
+ import androidx.annotation.RequiresApi;
++
+ import com.google.auto.value.AutoValue;
++
+ import org.tensorflow.lite.annotations.UsedByReflection;
+ 
+ /** Represents a label associated with a color for display purposes. */
+ @AutoValue
+ @UsedByReflection("image_segmentation_jni.cc")
+ public abstract class ColoredLabel {
++    /**
++     * Creates a {@link ColoredLabel} object with an ARGB color int.
++     *
++     * @param label the label string, as provided in the label map packed in the TFLite Model
++     *     Metadata.
++     * @param displayName the display name of label, as configured through {@link
++     *     ImageSegmenter.ImageSegmenterOptions.Builder#setDisplayNamesLocale}
++     * @param argb the color components for the label in ARGB. See <a
++     *     href="https://developer.android.com/reference/android/graphics/Color#color-ints">Android
++     *     Color ints.</a> for more details.
++     */
++    @UsedByReflection("image_segmentation_jni.cc")
++    public static ColoredLabel create(String label, String displayName, int argb) {
++        return new AutoValue_ColoredLabel(label, displayName, argb);
++    }
+ 
+-  /**
+-   * Creates a {@link ColoredLabel} object with an ARGB color int.
+-   *
+-   * @param label the label string, as provided in the label map packed in the TFLite Model
+-   *     Metadata.
+-   * @param displayName the display name of label, as configured through {@link
+-   *     ImageSegmenter.ImageSegmenterOptions.Builder#setDisplayNamesLocale}
+-   * @param argb the color components for the label in ARGB. See <a
+-   *     href="https://developer.android.com/reference/android/graphics/Color#color-ints">Android
+-   *     Color ints.</a> for more details.
+-   */
+-  @UsedByReflection("image_segmentation_jni.cc")
+-  public static ColoredLabel create(String label, String displayName, int argb) {
+-    return new AutoValue_ColoredLabel(label, displayName, argb);
+-  }
+-
+-  /**
+-   * Creates a {@link ColoredLabel} object with a {@link android.graphics.Color} instance.
+-   *
+-   * @param label the label string, as provided in the label map packed in the TFLite Model
+-   *     Metadata.
+-   * @param displayName the display name of label, as configured through {@link
+-   *     ImageSegmenter.ImageSegmenterOptions.Builder#setDisplayNamesLocale}
+-   * @param color the color components for the label. The Color instatnce is supported on Android
+-   *     API level 26 and above. For API level lower than 26, use {@link #create(String, String,
+-   *     int)}. See <a
+-   *     href="https://developer.android.com/reference/android/graphics/Color#color-instances">Android
+-   *     Color instances.</a> for more details.
+-   */
+-  @RequiresApi(Build.VERSION_CODES.O)
+-  public static ColoredLabel create(String label, String displayName, Color color) {
+-    return new AutoValue_ColoredLabel(label, displayName, color.toArgb());
+-  }
++    /**
++     * Creates a {@link ColoredLabel} object with a {@link android.graphics.Color} instance.
++     *
++     * @param label the label string, as provided in the label map packed in the TFLite Model
++     *     Metadata.
++     * @param displayName the display name of label, as configured through {@link
++     *     ImageSegmenter.ImageSegmenterOptions.Builder#setDisplayNamesLocale}
++     * @param color the color components for the label. The Color instatnce is supported on Android
++     *     API level 26 and above. For API level lower than 26, use {@link #create(String, String,
++     *     int)}. See <a
++     *     href="https://developer.android.com/reference/android/graphics/Color#color-instances">Android
++     *     Color instances.</a> for more details.
++     */
++    @RequiresApi(Build.VERSION_CODES.O)
++    public static ColoredLabel create(String label, String displayName, Color color) {
++        return new AutoValue_ColoredLabel(label, displayName, color.toArgb());
++    }
+ 
+-  public abstract String getlabel();
++    public abstract String getlabel();
+ 
+-  public abstract String getDisplayName();
++    public abstract String getDisplayName();
+ 
+-  /**
+-   * Gets the ARGB int that represents the color.
+-   *
+-   * <p>See <a
+-   * href="https://developer.android.com/reference/android/graphics/Color#color-ints">Android Color
+-   * ints.</a> for more details.
+-   */
+-  public abstract int getArgb();
++    /**
++     * Gets the ARGB int that represents the color.
++     *
++     * <p>See <a
++     * href="https://developer.android.com/reference/android/graphics/Color#color-ints">Android
++     * Color ints.</a> for more details.
++     */
++    public abstract int getArgb();
+ 
+-  /**
+-   * Gets the {@link android.graphics.Color} instance of the underlying color.
+-   *
+-   * <p>The Color instatnce is supported on Android API level 26 and above. For API level lower than
+-   * 26, use {@link #getArgb()}. See <a
+-   * href="https://developer.android.com/reference/android/graphics/Color#color-instances">Android
+-   * Color instances.</a> for more details.
+-   */
+-  @RequiresApi(Build.VERSION_CODES.O)
+-  public Color getColor() {
+-    return Color.valueOf(getArgb());
+-  }
++    /**
++     * Gets the {@link android.graphics.Color} instance of the underlying color.
++     *
++     * <p>The Color instatnce is supported on Android API level 26 and above. For API level lower
++     * than 26, use {@link #getArgb()}. See <a
++     * href="https://developer.android.com/reference/android/graphics/Color#color-instances">Android
++     * Color instances.</a> for more details.
++     */
++    @RequiresApi(Build.VERSION_CODES.O)
++    public Color getColor() {
++        return Color.valueOf(getArgb());
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java
+index 0caa7a33e1729..4c3b36304a0e3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java
+@@ -18,16 +18,10 @@ package org.tensorflow.lite.task.vision.segmenter;
+ import android.content.Context;
+ import android.content.res.AssetFileDescriptor;
+ import android.os.ParcelFileDescriptor;
++
+ import com.google.android.odml.image.MlImage;
+ import com.google.auto.value.AutoValue;
+-import java.io.File;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.ByteOrder;
+-import java.nio.MappedByteBuffer;
+-import java.util.ArrayList;
+-import java.util.Arrays;
+-import java.util.List;
++
+ import org.tensorflow.lite.support.image.MlImageAdapter;
+ import org.tensorflow.lite.support.image.TensorImage;
+ import org.tensorflow.lite.task.core.BaseOptions;
+@@ -37,6 +31,15 @@ import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
+ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi.InferenceProvider;
+ 
++import java.io.File;
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.ByteOrder;
++import java.nio.MappedByteBuffer;
++import java.util.ArrayList;
++import java.util.Arrays;
++import java.util.List;
++
+ /**
+  * Performs segmentation on images.
+  *
+@@ -75,394 +78,365 @@ import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi.InferenceProvider;
+  * href="https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/1">TensorFlow Hub.</a>.
+  */
+ public final class ImageSegmenter extends BaseVisionTaskApi {
++    private static final String IMAGE_SEGMENTER_NATIVE_LIB = "task_vision_jni";
++    private static final int OPTIONAL_FD_LENGTH = -1;
++    private static final int OPTIONAL_FD_OFFSET = -1;
++
++    private final OutputType outputType;
++
++    /**
++     * Creates an {@link ImageSegmenter} instance from the default {@link ImageSegmenterOptions}.
++     *
++     * @param modelPath path of the segmentation model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageSegmenter createFromFile(Context context, String modelPath)
++            throws IOException {
++        return createFromFileAndOptions(
++                context, modelPath, ImageSegmenterOptions.builder().build());
++    }
+ 
+-  private static final String IMAGE_SEGMENTER_NATIVE_LIB = "task_vision_jni";
+-  private static final int OPTIONAL_FD_LENGTH = -1;
+-  private static final int OPTIONAL_FD_OFFSET = -1;
+-
+-  private final OutputType outputType;
+-
+-  /**
+-   * Creates an {@link ImageSegmenter} instance from the default {@link ImageSegmenterOptions}.
+-   *
+-   * @param modelPath path of the segmentation model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageSegmenter createFromFile(Context context, String modelPath)
+-      throws IOException {
+-    return createFromFileAndOptions(context, modelPath, ImageSegmenterOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ImageSegmenter} instance from the default {@link ImageSegmenterOptions}.
+-   *
+-   * @param modelFile the segmentation model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageSegmenter createFromFile(File modelFile) throws IOException {
+-    return createFromFileAndOptions(modelFile, ImageSegmenterOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ImageSegmenter} instance with a model buffer and the default {@link
+-   * ImageSegmenterOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     segmentation model
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   */
+-  public static ImageSegmenter createFromBuffer(final ByteBuffer modelBuffer) {
+-    return createFromBufferAndOptions(modelBuffer, ImageSegmenterOptions.builder().build());
+-  }
+-
+-  /**
+-   * Creates an {@link ImageSegmenter} instance from {@link ImageSegmenterOptions}.
+-   *
+-   * @param modelPath path of the segmentation model with metadata in the assets
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageSegmenter createFromFileAndOptions(
+-      Context context, String modelPath, final ImageSegmenterOptions options) throws IOException {
+-    try (AssetFileDescriptor assetFileDescriptor = context.getAssets().openFd(modelPath)) {
+-      return createFromModelFdAndOptions(
+-          /*fileDescriptor=*/ assetFileDescriptor.getParcelFileDescriptor().getFd(),
+-          /*fileDescriptorLength=*/ assetFileDescriptor.getLength(),
+-          /*fileDescriptorOffset=*/ assetFileDescriptor.getStartOffset(),
+-          options);
++    /**
++     * Creates an {@link ImageSegmenter} instance from the default {@link ImageSegmenterOptions}.
++     *
++     * @param modelFile the segmentation model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageSegmenter createFromFile(File modelFile) throws IOException {
++        return createFromFileAndOptions(modelFile, ImageSegmenterOptions.builder().build());
+     }
+-  }
+-
+-  /**
+-   * Creates an {@link ImageSegmenter} instance from {@link ImageSegmenterOptions}.
+-   *
+-   * @param modelFile the segmentation model {@link File} instance
+-   * @throws IOException if an I/O error occurs when loading the tflite model
+-   * @throws IllegalArgumentException if an argument is invalid
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   */
+-  public static ImageSegmenter createFromFileAndOptions(
+-      File modelFile, final ImageSegmenterOptions options) throws IOException {
+-    try (ParcelFileDescriptor descriptor =
+-        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+-      return createFromModelFdAndOptions(
+-          /*fileDescriptor=*/ descriptor.getFd(),
+-          /*fileDescriptorLength=*/ OPTIONAL_FD_LENGTH,
+-          /*fileDescriptorOffset=*/ OPTIONAL_FD_OFFSET,
+-          options);
++
++    /**
++     * Creates an {@link ImageSegmenter} instance with a model buffer and the default {@link
++     * ImageSegmenterOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     segmentation model
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     */
++    public static ImageSegmenter createFromBuffer(final ByteBuffer modelBuffer) {
++        return createFromBufferAndOptions(modelBuffer, ImageSegmenterOptions.builder().build());
++    }
++
++    /**
++     * Creates an {@link ImageSegmenter} instance from {@link ImageSegmenterOptions}.
++     *
++     * @param modelPath path of the segmentation model with metadata in the assets
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageSegmenter createFromFileAndOptions(Context context, String modelPath,
++            final ImageSegmenterOptions options) throws IOException {
++        try (AssetFileDescriptor assetFileDescriptor = context.getAssets().openFd(modelPath)) {
++            return createFromModelFdAndOptions(
++                    /*fileDescriptor=*/assetFileDescriptor.getParcelFileDescriptor().getFd(),
++                    /*fileDescriptorLength=*/assetFileDescriptor.getLength(),
++                    /*fileDescriptorOffset=*/assetFileDescriptor.getStartOffset(), options);
++        }
++    }
++
++    /**
++     * Creates an {@link ImageSegmenter} instance from {@link ImageSegmenterOptions}.
++     *
++     * @param modelFile the segmentation model {@link File} instance
++     * @throws IOException if an I/O error occurs when loading the tflite model
++     * @throws IllegalArgumentException if an argument is invalid
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     */
++    public static ImageSegmenter createFromFileAndOptions(
++            File modelFile, final ImageSegmenterOptions options) throws IOException {
++        try (ParcelFileDescriptor descriptor =
++                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
++            return createFromModelFdAndOptions(
++                    /*fileDescriptor=*/descriptor.getFd(),
++                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
++                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options);
++        }
++    }
++
++    /**
++     * Creates an {@link ImageSegmenter} instance with a model buffer and {@link
++     * ImageSegmenterOptions}.
++     *
++     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
++     *     segmentation model
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
++     *     {@link MappedByteBuffer}
++     */
++    public static ImageSegmenter createFromBufferAndOptions(
++            final ByteBuffer modelBuffer, final ImageSegmenterOptions options) {
++        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
++            throw new IllegalArgumentException(
++                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++        }
++        return new ImageSegmenter(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                return initJniWithByteBuffer(modelBuffer, options.getDisplayNamesLocale(),
++                        options.getOutputType().getValue(),
++                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                options.getBaseOptions(), options.getNumThreads()));
++            }
++        }, IMAGE_SEGMENTER_NATIVE_LIB), options.getOutputType());
++    }
++
++    /**
++     * Constructor to initialize the JNI with a pointer from C++.
++     *
++     * @param nativeHandle a pointer referencing memory allocated in C++
++     */
++    private ImageSegmenter(long nativeHandle, OutputType outputType) {
++        super(nativeHandle);
++        this.outputType = outputType;
++    }
++
++    /** Options for setting up an {@link ImageSegmenter}. */
++    @AutoValue
++    public abstract static class ImageSegmenterOptions {
++        private static final String DEFAULT_DISPLAY_NAME_LOCALE = "en";
++        private static final OutputType DEFAULT_OUTPUT_TYPE = OutputType.CATEGORY_MASK;
++        private static final int NUM_THREADS = -1;
++
++        public abstract BaseOptions getBaseOptions();
++
++        public abstract String getDisplayNamesLocale();
++
++        public abstract OutputType getOutputType();
++
++        public abstract int getNumThreads();
++
++        public static Builder builder() {
++            return new AutoValue_ImageSegmenter_ImageSegmenterOptions.Builder()
++                    .setDisplayNamesLocale(DEFAULT_DISPLAY_NAME_LOCALE)
++                    .setOutputType(DEFAULT_OUTPUT_TYPE)
++                    .setNumThreads(NUM_THREADS)
++                    .setBaseOptions(BaseOptions.builder().build());
++        }
++
++        /** Builder for {@link ImageSegmenterOptions}. */
++        @AutoValue.Builder
++        public abstract static class Builder {
++            /** Sets the general options to configure Task APIs, such as accelerators. */
++            public abstract Builder setBaseOptions(BaseOptions baseOptions);
++
++            /**
++             * Sets the locale to use for display names specified through the TFLite Model Metadata,
++             * if any.
++             *
++             * <p>Defaults to English({@code "en"}). See the <a
++             * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
++             * Metadata schema file.</a> for the accepted pattern of locale.
++             */
++            public abstract Builder setDisplayNamesLocale(String displayNamesLocale);
++
++            public abstract Builder setOutputType(OutputType outputType);
++
++            /**
++             * Sets the number of threads to be used for TFLite ops that support multi-threading
++             * when running inference with CPU. Defaults to -1.
++             *
++             * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has
++             * the effect to let TFLite runtime set the value.
++             *
++             * @deprecated use {@link BaseOptions} to configure number of threads instead. This
++             *         method
++             *     will override the number of threads configured from {@link BaseOptions}.
++             */
++            @Deprecated
++            public abstract Builder setNumThreads(int numThreads);
++
++            public abstract ImageSegmenterOptions build();
++        }
++    }
++
++    /**
++     * Performs actual segmentation on the provided image.
++     *
++     * <p>{@link ImageSegmenter} supports the following {@link TensorImage} color space types:
++     *
++     * <ul>
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
++     * </ul>
++     *
++     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
++     * @return results of performing image segmentation. Note that at the time, a single {@link
++     *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
++     *     for later extension to e.g. instance segmentation models, which may return one
++     * segmentation per object.
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Segmentation> segment(TensorImage image) {
++        return segment(image, ImageProcessingOptions.builder().build());
++    }
++
++    /**
++     * Performs actual segmentation on the provided image with {@link ImageProcessingOptions}.
++     *
++     * <p>{@link ImageSegmenter} supports the following {@link TensorImage} color space types:
++     *
++     * <ul>
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
++     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
++     * </ul>
++     *
++     * <p>{@link ImageSegmenter} supports the following options:
++     *
++     * <ul>
++     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
++     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}
++     * </ul>
++     *
++     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
++     * @param options the options configure how to preprocess the image
++     * @return results of performing image segmentation. Note that at the time, a single {@link
++     *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
++     *     for later extension to e.g. instance segmentation models, which may return one
++     * segmentation per object.
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Segmentation> segment(TensorImage image, ImageProcessingOptions options) {
++        return run(new InferenceProvider<List<Segmentation>>() {
++            @Override
++            public List<Segmentation> run(
++                    long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
++                return segment(frameBufferHandle, options);
++            }
++        }, image, options);
+     }
+-  }
+-
+-  /**
+-   * Creates an {@link ImageSegmenter} instance with a model buffer and {@link
+-   * ImageSegmenterOptions}.
+-   *
+-   * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+-   *     segmentation model
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+-   *     {@link MappedByteBuffer}
+-   */
+-  public static ImageSegmenter createFromBufferAndOptions(
+-      final ByteBuffer modelBuffer, final ImageSegmenterOptions options) {
+-    if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+-      throw new IllegalArgumentException(
+-          "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
++
++    /**
++     * Performs actual segmentation on the provided {@code MlImage}.
++     *
++     * @param image an {@code MlImage} to segment.
++     * @return results of performing image segmentation. Note that at the time, a single {@link
++     *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
++     *     for later extension to e.g. instance segmentation models, which may return one
++     * segmentation per object.
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
++     */
++    public List<Segmentation> segment(MlImage image) {
++        return segment(image, ImageProcessingOptions.builder().build());
+     }
+-    return new ImageSegmenter(
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                return initJniWithByteBuffer(
+-                    modelBuffer,
+-                    options.getDisplayNamesLocale(),
+-                    options.getOutputType().getValue(),
+-                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                        options.getBaseOptions(), options.getNumThreads()));
+-              }
+-            },
+-            IMAGE_SEGMENTER_NATIVE_LIB),
+-        options.getOutputType());
+-  }
+-
+-  /**
+-   * Constructor to initialize the JNI with a pointer from C++.
+-   *
+-   * @param nativeHandle a pointer referencing memory allocated in C++
+-   */
+-  private ImageSegmenter(long nativeHandle, OutputType outputType) {
+-    super(nativeHandle);
+-    this.outputType = outputType;
+-  }
+-
+-  /** Options for setting up an {@link ImageSegmenter}. */
+-  @AutoValue
+-  public abstract static class ImageSegmenterOptions {
+-    private static final String DEFAULT_DISPLAY_NAME_LOCALE = "en";
+-    private static final OutputType DEFAULT_OUTPUT_TYPE = OutputType.CATEGORY_MASK;
+-    private static final int NUM_THREADS = -1;
+-
+-    public abstract BaseOptions getBaseOptions();
+-
+-    public abstract String getDisplayNamesLocale();
+-
+-    public abstract OutputType getOutputType();
+-
+-    public abstract int getNumThreads();
+-
+-    public static Builder builder() {
+-      return new AutoValue_ImageSegmenter_ImageSegmenterOptions.Builder()
+-          .setDisplayNamesLocale(DEFAULT_DISPLAY_NAME_LOCALE)
+-          .setOutputType(DEFAULT_OUTPUT_TYPE)
+-          .setNumThreads(NUM_THREADS)
+-          .setBaseOptions(BaseOptions.builder().build());
++
++    /**
++     * Performs actual segmentation on the provided {@code MlImage} with {@link
++     * ImageProcessingOptions}.
++     *
++     * <p>{@link ImageSegmenter} supports the following options:
++     *
++     * <ul>
++     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
++     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
++     *       MlImage#getRotation()} is not effective.
++     * </ul>
++     *
++     * @param image an {@code MlImage} to segment.
++     * @param options the options configure how to preprocess the image.
++     * @return results of performing image segmentation. Note that at the time, a single {@link
++     *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
++     *     for later extension to e.g. instance segmentation models, which may return one
++     * segmentation per object.
++     * @throws IllegalStateException if there is an internal error
++     * @throws RuntimeException if there is an otherwise unspecified error
++     * @throws IllegalArgumentException if the color space type of image is unsupported
++     */
++    public List<Segmentation> segment(MlImage image, ImageProcessingOptions options) {
++        image.getInternal().acquire();
++        TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
++        List<Segmentation> result = segment(tensorImage, options);
++        image.close();
++        return result;
+     }
+ 
+-    /** Builder for {@link ImageSegmenterOptions}. */
+-    @AutoValue.Builder
+-    public abstract static class Builder {
+-
+-      /** Sets the general options to configure Task APIs, such as accelerators. */
+-      public abstract Builder setBaseOptions(BaseOptions baseOptions);
+-
+-      /**
+-       * Sets the locale to use for display names specified through the TFLite Model Metadata, if
+-       * any.
+-       *
+-       * <p>Defaults to English({@code "en"}). See the <a
+-       * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
+-       * Metadata schema file.</a> for the accepted pattern of locale.
+-       */
+-      public abstract Builder setDisplayNamesLocale(String displayNamesLocale);
+-
+-      public abstract Builder setOutputType(OutputType outputType);
+-
+-      /**
+-       * Sets the number of threads to be used for TFLite ops that support multi-threading when
+-       * running inference with CPU. Defaults to -1.
+-       *
+-       * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has the
+-       * effect to let TFLite runtime set the value.
+-       *
+-       * @deprecated use {@link BaseOptions} to configure number of threads instead. This method
+-       *     will override the number of threads configured from {@link BaseOptions}.
+-       */
+-      @Deprecated
+-      public abstract Builder setNumThreads(int numThreads);
+-
+-      public abstract ImageSegmenterOptions build();
++    public List<Segmentation> segment(long frameBufferHandle, ImageProcessingOptions options) {
++        checkNotClosed();
++
++        List<byte[]> maskByteArrays = new ArrayList<>();
++        List<ColoredLabel> coloredLabels = new ArrayList<>();
++        int[] maskShape = new int[2];
++        segmentNative(
++                getNativeHandle(), frameBufferHandle, maskByteArrays, maskShape, coloredLabels);
++
++        List<ByteBuffer> maskByteBuffers = new ArrayList<>();
++        for (byte[] bytes : maskByteArrays) {
++            ByteBuffer byteBuffer = ByteBuffer.wrap(bytes);
++            // Change the byte order to little_endian, since the buffers were generated in jni.
++            byteBuffer.order(ByteOrder.LITTLE_ENDIAN);
++            maskByteBuffers.add(byteBuffer);
++        }
++
++        return Arrays.asList(Segmentation.create(outputType,
++                outputType.createMasksFromBuffer(maskByteBuffers, maskShape), coloredLabels));
+     }
+-  }
+-
+-  /**
+-   * Performs actual segmentation on the provided image.
+-   *
+-   * <p>{@link ImageSegmenter} supports the following {@link TensorImage} color space types:
+-   *
+-   * <ul>
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+-   * </ul>
+-   *
+-   * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+-   * @return results of performing image segmentation. Note that at the time, a single {@link
+-   *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
+-   *     for later extension to e.g. instance segmentation models, which may return one segmentation
+-   *     per object.
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Segmentation> segment(TensorImage image) {
+-    return segment(image, ImageProcessingOptions.builder().build());
+-  }
+-
+-  /**
+-   * Performs actual segmentation on the provided image with {@link ImageProcessingOptions}.
+-   *
+-   * <p>{@link ImageSegmenter} supports the following {@link TensorImage} color space types:
+-   *
+-   * <ul>
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+-   *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+-   * </ul>
+-   *
+-   * <p>{@link ImageSegmenter} supports the following options:
+-   *
+-   * <ul>
+-   *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+-   *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}
+-   * </ul>
+-   *
+-   * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+-   * @param options the options configure how to preprocess the image
+-   * @return results of performing image segmentation. Note that at the time, a single {@link
+-   *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
+-   *     for later extension to e.g. instance segmentation models, which may return one segmentation
+-   *     per object.
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Segmentation> segment(TensorImage image, ImageProcessingOptions options) {
+-    return run(
+-        new InferenceProvider<List<Segmentation>>() {
+-          @Override
+-          public List<Segmentation> run(
+-              long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+-            return segment(frameBufferHandle, options);
+-          }
+-        },
+-        image,
+-        options);
+-  }
+-
+-  /**
+-   * Performs actual segmentation on the provided {@code MlImage}.
+-   *
+-   * @param image an {@code MlImage} to segment.
+-   * @return results of performing image segmentation. Note that at the time, a single {@link
+-   *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
+-   *     for later extension to e.g. instance segmentation models, which may return one segmentation
+-   *     per object.
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+-   */
+-  public List<Segmentation> segment(MlImage image) {
+-    return segment(image, ImageProcessingOptions.builder().build());
+-  }
+-
+-  /**
+-   * Performs actual segmentation on the provided {@code MlImage} with {@link
+-   * ImageProcessingOptions}.
+-   *
+-   * <p>{@link ImageSegmenter} supports the following options:
+-   *
+-   * <ul>
+-   *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+-   *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
+-   *       MlImage#getRotation()} is not effective.
+-   * </ul>
+-   *
+-   * @param image an {@code MlImage} to segment.
+-   * @param options the options configure how to preprocess the image.
+-   * @return results of performing image segmentation. Note that at the time, a single {@link
+-   *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
+-   *     for later extension to e.g. instance segmentation models, which may return one segmentation
+-   *     per object.
+-   * @throws IllegalStateException if there is an internal error
+-   * @throws RuntimeException if there is an otherwise unspecified error
+-   * @throws IllegalArgumentException if the color space type of image is unsupported
+-   */
+-  public List<Segmentation> segment(MlImage image, ImageProcessingOptions options) {
+-    image.getInternal().acquire();
+-    TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+-    List<Segmentation> result = segment(tensorImage, options);
+-    image.close();
+-    return result;
+-  }
+-
+-  public List<Segmentation> segment(long frameBufferHandle, ImageProcessingOptions options) {
+-    checkNotClosed();
+-
+-    List<byte[]> maskByteArrays = new ArrayList<>();
+-    List<ColoredLabel> coloredLabels = new ArrayList<>();
+-    int[] maskShape = new int[2];
+-    segmentNative(getNativeHandle(), frameBufferHandle, maskByteArrays, maskShape, coloredLabels);
+-
+-    List<ByteBuffer> maskByteBuffers = new ArrayList<>();
+-    for (byte[] bytes : maskByteArrays) {
+-      ByteBuffer byteBuffer = ByteBuffer.wrap(bytes);
+-      // Change the byte order to little_endian, since the buffers were generated in jni.
+-      byteBuffer.order(ByteOrder.LITTLE_ENDIAN);
+-      maskByteBuffers.add(byteBuffer);
++
++    private static ImageSegmenter createFromModelFdAndOptions(final int fileDescriptor,
++            final long fileDescriptorLength, final long fileDescriptorOffset,
++            final ImageSegmenterOptions options) {
++        long nativeHandle = TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
++            @Override
++            public long createHandle() {
++                return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
++                        fileDescriptorOffset, options.getDisplayNamesLocale(),
++                        options.getOutputType().getValue(),
++                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
++                                options.getBaseOptions(), options.getNumThreads()));
++            }
++        }, IMAGE_SEGMENTER_NATIVE_LIB);
++        return new ImageSegmenter(nativeHandle, options.getOutputType());
++    }
++
++    private static native long initJniWithModelFdAndOptions(int fileDescriptor,
++            long fileDescriptorLength, long fileDescriptorOffset, String displayNamesLocale,
++            int outputType, long baseOptionsHandle);
++
++    private static native long initJniWithByteBuffer(ByteBuffer modelBuffer,
++            String displayNamesLocale, int outputType, long baseOptionsHandle);
++
++    /**
++     * The native method to segment the image.
++     *
++     * <p>{@code maskBuffers}, {@code maskShape}, {@code coloredLabels} will be updated in the
++     * native layer.
++     */
++    private static native void segmentNative(long nativeHandle, long frameBufferHandle,
++            List<byte[]> maskByteArrays, int[] maskShape, List<ColoredLabel> coloredLabels);
++
++    @Override
++    protected void deinit(long nativeHandle) {
++        deinitJni(nativeHandle);
+     }
+ 
+-    return Arrays.asList(
+-        Segmentation.create(
+-            outputType,
+-            outputType.createMasksFromBuffer(maskByteBuffers, maskShape),
+-            coloredLabels));
+-  }
+-
+-  private static ImageSegmenter createFromModelFdAndOptions(
+-      final int fileDescriptor,
+-      final long fileDescriptorLength,
+-      final long fileDescriptorOffset,
+-      final ImageSegmenterOptions options) {
+-    long nativeHandle =
+-        TaskJniUtils.createHandleFromLibrary(
+-            new EmptyHandleProvider() {
+-              @Override
+-              public long createHandle() {
+-                return initJniWithModelFdAndOptions(
+-                    fileDescriptor,
+-                    fileDescriptorLength,
+-                    fileDescriptorOffset,
+-                    options.getDisplayNamesLocale(),
+-                    options.getOutputType().getValue(),
+-                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+-                        options.getBaseOptions(), options.getNumThreads()));
+-              }
+-            },
+-            IMAGE_SEGMENTER_NATIVE_LIB);
+-    return new ImageSegmenter(nativeHandle, options.getOutputType());
+-  }
+-
+-  private static native long initJniWithModelFdAndOptions(
+-      int fileDescriptor,
+-      long fileDescriptorLength,
+-      long fileDescriptorOffset,
+-      String displayNamesLocale,
+-      int outputType,
+-      long baseOptionsHandle);
+-
+-  private static native long initJniWithByteBuffer(
+-      ByteBuffer modelBuffer, String displayNamesLocale, int outputType, long baseOptionsHandle);
+-
+-  /**
+-   * The native method to segment the image.
+-   *
+-   * <p>{@code maskBuffers}, {@code maskShape}, {@code coloredLabels} will be updated in the native
+-   * layer.
+-   */
+-  private static native void segmentNative(
+-      long nativeHandle,
+-      long frameBufferHandle,
+-      List<byte[]> maskByteArrays,
+-      int[] maskShape,
+-      List<ColoredLabel> coloredLabels);
+-
+-  @Override
+-  protected void deinit(long nativeHandle) {
+-    deinitJni(nativeHandle);
+-  }
+-
+-  /**
+-   * Native implementation to release memory pointed by the pointer.
+-   *
+-   * @param nativeHandle pointer to memory allocated
+-   */
+-  private native void deinitJni(long nativeHandle);
++    /**
++     * Native implementation to release memory pointed by the pointer.
++     *
++     * @param nativeHandle pointer to memory allocated
++     */
++    private native void deinitJni(long nativeHandle);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java
+index 26ace1eaa1783..8c69cf5d152a0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java
+@@ -20,126 +20,128 @@ import static org.tensorflow.lite.DataType.UINT8;
+ import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+ import static org.tensorflow.lite.support.image.ColorSpaceType.GRAYSCALE;
+ 
++import org.tensorflow.lite.support.image.TensorImage;
++import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
++
+ import java.nio.ByteBuffer;
+ import java.util.ArrayList;
+ import java.util.List;
+-import org.tensorflow.lite.support.image.TensorImage;
+-import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ /**
+  * Output mask type. This allows specifying the type of post-processing to perform on the raw model
+  * results.
+  */
+ public enum OutputType {
+-
+-  /**
+-   * Gives a single output mask where each pixel represents the class which the pixel in the
+-   * original image was predicted to belong to.
+-   */
+-  CATEGORY_MASK(0) {
+     /**
+-     * {@inheritDoc}
+-     *
+-     * @throws IllegalArgumentException if more than one {@link TensorImage} are provided, or if the
+-     *     color space of the {@link TensorImage} is not {@link ColorSpaceType#GRAYSCALE}
++     * Gives a single output mask where each pixel represents the class which the pixel in the
++     * original image was predicted to belong to.
+      */
+-    @Override
+-    void assertMasksMatchColoredLabels(List<TensorImage> masks, List<ColoredLabel> coloredLabels) {
+-      checkArgument(
+-          masks.size() == 1,
+-          "CATRGORY_MASK only allows one TensorImage in the list, providing " + masks.size());
+-
+-      TensorImage mask = masks.get(0);
+-      checkArgument(
+-          mask.getColorSpaceType() == GRAYSCALE,
+-          "CATRGORY_MASK only supports masks of ColorSpaceType, GRAYSCALE, providing "
+-              + mask.getColorSpaceType());
+-    }
++    CATEGORY_MASK(0) {
++        /**
++         * {@inheritDoc}
++         *
++         * @throws IllegalArgumentException if more than one {@link TensorImage} are provided, or if
++         *         the
++         *     color space of the {@link TensorImage} is not {@link ColorSpaceType#GRAYSCALE}
++         */
++        @Override
++        void assertMasksMatchColoredLabels(
++                List<TensorImage> masks, List<ColoredLabel> coloredLabels) {
++            checkArgument(masks.size() == 1,
++                    "CATRGORY_MASK only allows one TensorImage in the list, providing "
++                            + masks.size());
++
++            TensorImage mask = masks.get(0);
++            checkArgument(mask.getColorSpaceType() == GRAYSCALE,
++                    "CATRGORY_MASK only supports masks of ColorSpaceType, GRAYSCALE, providing "
++                            + mask.getColorSpaceType());
++        }
++
++        /**
++         * {@inheritDoc}
++         *
++         * @throws IllegalArgumentException if more than one {@link ByteBuffer} are provided in the
++         *         list
++         */
++        @Override
++        List<TensorImage> createMasksFromBuffer(List<ByteBuffer> buffers, int[] maskShape) {
++            checkArgument(buffers.size() == 1,
++                    "CATRGORY_MASK only allows one mask in the buffer list, providing "
++                            + buffers.size());
++
++            List<TensorImage> masks = new ArrayList<>();
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(UINT8);
++            tensorBuffer.loadBuffer(buffers.get(0), maskShape);
++            TensorImage tensorImage = new TensorImage(UINT8);
++            tensorImage.load(tensorBuffer, GRAYSCALE);
++            masks.add(tensorImage);
++
++            return masks;
++        }
++    },
+ 
+     /**
+-     * {@inheritDoc}
+-     *
+-     * @throws IllegalArgumentException if more than one {@link ByteBuffer} are provided in the list
++     * Gives a list of output masks where, for each mask, each pixel represents the prediction
++     * confidence, usually in the [0, 1] range.
+      */
+-    @Override
+-    List<TensorImage> createMasksFromBuffer(List<ByteBuffer> buffers, int[] maskShape) {
+-      checkArgument(
+-          buffers.size() == 1,
+-          "CATRGORY_MASK only allows one mask in the buffer list, providing " + buffers.size());
+-
+-      List<TensorImage> masks = new ArrayList<>();
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(UINT8);
+-      tensorBuffer.loadBuffer(buffers.get(0), maskShape);
+-      TensorImage tensorImage = new TensorImage(UINT8);
+-      tensorImage.load(tensorBuffer, GRAYSCALE);
+-      masks.add(tensorImage);
+-
+-      return masks;
++    CONFIDENCE_MASK(1) {
++        /**
++         * {@inheritDoc}
++         *
++         * @throws IllegalArgumentException if more the size of the masks list does not match the
++         *         size
++         *     of the coloredlabels list, or if the color space type of the any mask is not {@link
++         *     ColorSpaceType#GRAYSCALE}
++         */
++        @Override
++        void assertMasksMatchColoredLabels(
++                List<TensorImage> masks, List<ColoredLabel> coloredLabels) {
++            checkArgument(masks.size() == coloredLabels.size(),
++                    String.format(
++                            "When using CONFIDENCE_MASK, the number of masks (%d) should match the number of"
++                                    + " coloredLabels (%d).",
++                            masks.size(), coloredLabels.size()));
++
++            for (TensorImage mask : masks) {
++                checkArgument(mask.getColorSpaceType() == GRAYSCALE,
++                        "CONFIDENCE_MASK only supports masks of ColorSpaceType, GRAYSCALE, providing "
++                                + mask.getColorSpaceType());
++            }
++        }
++
++        @Override
++        List<TensorImage> createMasksFromBuffer(List<ByteBuffer> buffers, int[] maskShape) {
++            List<TensorImage> masks = new ArrayList<>();
++            for (ByteBuffer buffer : buffers) {
++                TensorBuffer tensorBuffer = TensorBuffer.createDynamic(FLOAT32);
++                tensorBuffer.loadBuffer(buffer, maskShape);
++                TensorImage tensorImage = new TensorImage(FLOAT32);
++                tensorImage.load(tensorBuffer, GRAYSCALE);
++                masks.add(tensorImage);
++            }
++            return masks;
++        }
++    };
++
++    public int getValue() {
++        return value;
+     }
+-  },
+ 
+-  /**
+-   * Gives a list of output masks where, for each mask, each pixel represents the prediction
+-   * confidence, usually in the [0, 1] range.
+-   */
+-  CONFIDENCE_MASK(1) {
+     /**
+-     * {@inheritDoc}
++     * Verifies that the given list of masks matches the list of colored labels.
+      *
+-     * @throws IllegalArgumentException if more the size of the masks list does not match the size
+-     *     of the coloredlabels list, or if the color space type of the any mask is not {@link
+-     *     ColorSpaceType#GRAYSCALE}
++     * @throws IllegalArgumentException if {@code masks} and {@code coloredLabels} do not match the
++     *     output type
+      */
+-    @Override
+-    void assertMasksMatchColoredLabels(List<TensorImage> masks, List<ColoredLabel> coloredLabels) {
+-      checkArgument(
+-          masks.size() == coloredLabels.size(),
+-          String.format(
+-              "When using CONFIDENCE_MASK, the number of masks (%d) should match the number of"
+-                  + " coloredLabels (%d).",
+-              masks.size(), coloredLabels.size()));
+-
+-      for (TensorImage mask : masks) {
+-        checkArgument(
+-            mask.getColorSpaceType() == GRAYSCALE,
+-            "CONFIDENCE_MASK only supports masks of ColorSpaceType, GRAYSCALE, providing "
+-                + mask.getColorSpaceType());
+-      }
+-    }
+-
+-    @Override
+-    List<TensorImage> createMasksFromBuffer(List<ByteBuffer> buffers, int[] maskShape) {
+-      List<TensorImage> masks = new ArrayList<>();
+-      for (ByteBuffer buffer : buffers) {
+-        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(FLOAT32);
+-        tensorBuffer.loadBuffer(buffer, maskShape);
+-        TensorImage tensorImage = new TensorImage(FLOAT32);
+-        tensorImage.load(tensorBuffer, GRAYSCALE);
+-        masks.add(tensorImage);
+-      }
+-      return masks;
+-    }
+-  };
++    abstract void assertMasksMatchColoredLabels(
++            List<TensorImage> masks, List<ColoredLabel> coloredLabels);
+ 
+-  public int getValue() {
+-    return value;
+-  }
++    /** Creates the masks in {@link TensorImage} based on the data in {@link ByteBuffer}. */
++    abstract List<TensorImage> createMasksFromBuffer(List<ByteBuffer> buffers, int[] maskShape);
+ 
+-  /**
+-   * Verifies that the given list of masks matches the list of colored labels.
+-   *
+-   * @throws IllegalArgumentException if {@code masks} and {@code coloredLabels} do not match the
+-   *     output type
+-   */
+-  abstract void assertMasksMatchColoredLabels(
+-      List<TensorImage> masks, List<ColoredLabel> coloredLabels);
++    private final int value;
+ 
+-  /** Creates the masks in {@link TensorImage} based on the data in {@link ByteBuffer}. */
+-  abstract List<TensorImage> createMasksFromBuffer(List<ByteBuffer> buffers, int[] maskShape);
+-
+-  private final int value;
+-
+-  private OutputType(int value) {
+-    this.value = value;
+-  }
++    private OutputType(int value) {
++        this.value = value;
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/Segmentation.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/Segmentation.java
+index 018482c7e82db..f5062bc8745f0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/Segmentation.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/Segmentation.java
+@@ -16,67 +16,69 @@ limitations under the License.
+ package org.tensorflow.lite.task.vision.segmenter;
+ 
+ import com.google.auto.value.AutoValue;
++
++import org.tensorflow.lite.support.image.TensorImage;
++
+ import java.util.ArrayList;
+ import java.util.Collections;
+ import java.util.List;
+-import org.tensorflow.lite.support.image.TensorImage;
+ 
+ /** Represents the segmentation result of an {@link ImageSegmenter}. */
+ @AutoValue
+ public abstract class Segmentation {
++    /**
++     * Creates a {@link Segmentation} object.
++     *
++     * <p>{@link Segmentation} provides two types of outputs as indicated through {@link
++     * OutputType}:
++     *
++     * <p>{@link OutputType#CATEGORY_MASK}: the result contains a single category mask, which is a
++     * grayscale {@link TensorImage} with shape (height, width), in row major order. The value of
++     * each pixel in this mask represents the class to which the pixel in the mask belongs. The
++     * pixel values are in 1:1 corresponding with the colored labels, i.e. a pixel with value {@code
++     * i} is associated with {@code coloredLabels.get(i)}.
++     *
++     * <p>{@link OutputType#CONFIDENCE_MASK}: the result contains a list of confidence masks, which
++     * are in 1:1 correspondance with the colored labels, i.e. {@link masks.get(i)} is associated
++     * with
++     * {@code coloredLabels.get(i)}. Each confidence mask is a grayscale {@link TensorImage} with
++     * shape (height, width), in row major order. The value of each pixel in these masks represents
++     * the confidence score for this particular class.
++     *
++     * <p>IMPORTANT: segmentation masks are not direcly suited for display, in particular:<br>
++     * \* they are relative to the unrotated input frame, i.e. *not* taking into account the {@code
++     * Orientation} flag of the input FrameBuffer, <br>
++     * \* their dimensions are intrinsic to the model, i.e. *not* dependent on the input FrameBuffer
++     * dimensions.
++     *
++     * <p>Example of such post-processing, assuming: <br>
++     * \* an input FrameBuffer with width=640, height=480, orientation=kLeftBottom (i.e. the image
++     * will be rotated 90° clockwise during preprocessing to make it "upright"), <br>
++     * \* a model outputting masks of size 224x224. <br>
++     * In order to be directly displayable on top of the input image assumed to be displayed *with*
++     * the {@code Orientation} flag taken into account (according to the <a
++     * href="http://jpegclub.org/exif_orientation.html">EXIF specification</a>), the masks need to
++     * be: re-scaled to 640 x 480, then rotated 90° clockwise.
++     *
++     * @throws IllegalArgumentException if {@code masks} and {@code coloredLabels} do not match the
++     *     {@code outputType}
++     */
++    static Segmentation create(
++            OutputType outputType, List<TensorImage> masks, List<ColoredLabel> coloredLabels) {
++        outputType.assertMasksMatchColoredLabels(masks, coloredLabels);
+ 
+-  /**
+-   * Creates a {@link Segmentation} object.
+-   *
+-   * <p>{@link Segmentation} provides two types of outputs as indicated through {@link OutputType}:
+-   *
+-   * <p>{@link OutputType#CATEGORY_MASK}: the result contains a single category mask, which is a
+-   * grayscale {@link TensorImage} with shape (height, width), in row major order. The value of each
+-   * pixel in this mask represents the class to which the pixel in the mask belongs. The pixel
+-   * values are in 1:1 corresponding with the colored labels, i.e. a pixel with value {@code i} is
+-   * associated with {@code coloredLabels.get(i)}.
+-   *
+-   * <p>{@link OutputType#CONFIDENCE_MASK}: the result contains a list of confidence masks, which
+-   * are in 1:1 correspondance with the colored labels, i.e. {@link masks.get(i)} is associated with
+-   * {@code coloredLabels.get(i)}. Each confidence mask is a grayscale {@link TensorImage} with
+-   * shape (height, width), in row major order. The value of each pixel in these masks represents
+-   * the confidence score for this particular class.
+-   *
+-   * <p>IMPORTANT: segmentation masks are not direcly suited for display, in particular:<br>
+-   * \* they are relative to the unrotated input frame, i.e. *not* taking into account the {@code
+-   * Orientation} flag of the input FrameBuffer, <br>
+-   * \* their dimensions are intrinsic to the model, i.e. *not* dependent on the input FrameBuffer
+-   * dimensions.
+-   *
+-   * <p>Example of such post-processing, assuming: <br>
+-   * \* an input FrameBuffer with width=640, height=480, orientation=kLeftBottom (i.e. the image
+-   * will be rotated 90° clockwise during preprocessing to make it "upright"), <br>
+-   * \* a model outputting masks of size 224x224. <br>
+-   * In order to be directly displayable on top of the input image assumed to be displayed *with*
+-   * the {@code Orientation} flag taken into account (according to the <a
+-   * href="http://jpegclub.org/exif_orientation.html">EXIF specification</a>), the masks need to be:
+-   * re-scaled to 640 x 480, then rotated 90° clockwise.
+-   *
+-   * @throws IllegalArgumentException if {@code masks} and {@code coloredLabels} do not match the
+-   *     {@code outputType}
+-   */
+-  static Segmentation create(
+-      OutputType outputType, List<TensorImage> masks, List<ColoredLabel> coloredLabels) {
+-    outputType.assertMasksMatchColoredLabels(masks, coloredLabels);
+-
+-    return new AutoValue_Segmentation(
+-        outputType,
+-        Collections.unmodifiableList(new ArrayList<TensorImage>(masks)),
+-        Collections.unmodifiableList(new ArrayList<ColoredLabel>(coloredLabels)));
+-  }
++        return new AutoValue_Segmentation(outputType,
++                Collections.unmodifiableList(new ArrayList<TensorImage>(masks)),
++                Collections.unmodifiableList(new ArrayList<ColoredLabel>(coloredLabels)));
++    }
+ 
+-  public abstract OutputType getOutputType();
++    public abstract OutputType getOutputType();
+ 
+-  // As an open source project, we've been trying avoiding depending on common java libraries,
+-  // such as Guava, because it may introduce conflicts with clients who also happen to use those
+-  // libraries. Therefore, instead of using ImmutableList here, we convert the List into
+-  // unmodifiableList in create() to make it less vulnerable.
+-  public abstract List<TensorImage> getMasks();
++    // As an open source project, we've been trying avoiding depending on common java libraries,
++    // such as Guava, because it may introduce conflicts with clients who also happen to use those
++    // libraries. Therefore, instead of using ImmutableList here, we convert the List into
++    // unmodifiableList in create() to make it less vulnerable.
++    public abstract List<TensorImage> getMasks();
+ 
+-  public abstract List<ColoredLabel> getColoredLabels();
++    public abstract List<ColoredLabel> getColoredLabels();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java
+index edbb5d82db2c1..903f7913219bf 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.audio;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.mockito.ArgumentMatchers.any;
+ import static org.mockito.ArgumentMatchers.anyInt;
+@@ -25,6 +26,7 @@ import static org.mockito.Mockito.when;
+ 
+ import android.media.AudioFormat;
+ import android.media.AudioRecord;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.junit.runners.Suite;
+@@ -35,249 +37,249 @@ import org.tensorflow.lite.support.audio.TensorAudio.TensorAudioFormat;
+ /** Test for {@link TensorAudio}. */
+ @RunWith(Suite.class)
+ @SuiteClasses({
+-  TensorAudioTest.General.class,
++        TensorAudioTest.General.class,
+ })
+ public class TensorAudioTest {
+-
+-  /** General tests of TensorAudio. */
+-  @RunWith(RobolectricTestRunner.class)
+-  public static final class General extends TensorAudioTest {
+-    @Test
+-    public void createSucceedsWithTensorAudioFormat() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(
+-              TensorAudioFormat.builder().setChannels(1).setSampleRate(2).build(), 100);
+-      assertThat(tensor.getFormat().getChannels()).isEqualTo(1);
+-      assertThat(tensor.getFormat().getSampleRate()).isEqualTo(2);
+-      assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(100);
+-    }
+-
+-    @Test
+-    public void createSucceedsWithTensorAudioFormatWithMultipleChannels() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(
+-              TensorAudioFormat.builder().setChannels(5).setSampleRate(2).build(), 100);
+-      assertThat(tensor.getFormat().getChannels()).isEqualTo(5);
+-      assertThat(tensor.getFormat().getSampleRate()).isEqualTo(2);
+-      assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(500);
+-    }
+-
+-    @Test
+-    public void createSucceededsWithDefaultArguments() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(TensorAudioFormat.builder().setSampleRate(20).build(), 1000);
+-      // Number of channels defaults to 1.
+-      assertThat(tensor.getFormat().getChannels()).isEqualTo(1);
+-      assertThat(tensor.getFormat().getSampleRate()).isEqualTo(20);
+-      assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(1000);
+-    }
+-
+-    @Test
+-    public void createSucceedsWithAudioFormat() throws Exception {
+-      AudioFormat format =
+-          new AudioFormat.Builder()
+-              .setChannelMask(AudioFormat.CHANNEL_IN_STEREO)
+-              .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
+-              .setSampleRate(16000)
+-              .build();
+-      TensorAudio tensor = TensorAudio.create(format, 100);
+-      // STEREO has 2 channels
+-      assertThat(tensor.getFormat().getChannels()).isEqualTo(2);
+-      assertThat(tensor.getFormat().getSampleRate()).isEqualTo(16000);
+-      // flatSize = channelCount * sampleCount
+-      assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(200);
+-    }
+-
+-    @Test
+-    public void createFailedWithInvalidSampleRate() throws Exception {
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> TensorAudio.create(TensorAudioFormat.builder().setSampleRate(0).build(), 100));
+-      // Sample rate 0 is not allowed
+-      assertThat(exception).hasMessageThat().ignoringCase().contains("sample rate");
+-    }
+-
+-    @Test
+-    public void createFailedWithInvalidChannels() throws Exception {
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () ->
+-                  TensorAudio.create(
+-                      TensorAudioFormat.builder().setSampleRate(1).setChannels(-1).build(), 100));
+-      // Negative channels is not allowed
+-      assertThat(exception).hasMessageThat().ignoringCase().contains("channels");
+-    }
+-
+-    @Test
+-    public void loadSucceedsFromArray() throws Exception {
+-      TensorAudioFormat format =
+-          TensorAudioFormat.builder().setChannels(2).setSampleRate(2).build();
+-      TensorAudio tensor = TensorAudio.create(format, 2);
+-      assertThat(tensor.getTensorBuffer().getFloatArray()).isEqualTo(new float[4]);
+-
+-      tensor.load(new float[] {2.f, 0});
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .usingTolerance(0.001f)
+-          .containsExactly(new float[] {0, 0, 2.f, 0});
+-
+-      tensor.load(new float[] {2.f, 3.f}, 0, 2);
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .usingTolerance(0.001f)
+-          .containsExactly(new float[] {2.f, 0, 2.f, 3.f});
+-
+-      tensor.load(new short[] {Short.MAX_VALUE, Short.MIN_VALUE});
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .usingTolerance(0.001f)
+-          .containsExactly(new float[] {2.f, 3.f, 1.f, -1.f});
+-
+-      tensor.load(new short[] {1, 2, 3, 0, 1, Short.MIN_VALUE, 3, 4, 5}, 3, 6);
+-      // The entire sequence becomes {2.f, 0, 2.f, 3.f, 1.f, -1.f, 0, 0, -1.f, 0, 0, 0} but the ring
+-      // buffer is only keep the last 4 results.
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .usingTolerance(0.001f)
+-          .containsExactly(new float[] {-1.f, 0, 0, 0});
+-    }
+-
+-    @Test
+-    public void loadFailsWithIndexOutOfRange() throws Exception {
+-      TensorAudioFormat format = TensorAudioFormat.builder().setSampleRate(2).build();
+-      TensorAudio tensor = TensorAudio.create(format, 5);
+-
+-      assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[100], 99, 2));
+-
+-      assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[100], 99, 2));
+-    }
+-
+-    @Test
+-    public void loadFailsWithIncompatibleInputSize() throws Exception {
+-      TensorAudioFormat format =
+-          TensorAudioFormat.builder().setChannels(3).setSampleRate(2).build();
+-      TensorAudio tensor = TensorAudio.create(format, 5);
+-
+-      assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[1]));
+-
+-      assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[2]));
+-
+-      assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[2], 1, 1));
+-
+-      assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[5], 2, 4));
+-    }
+-
+-    @Test
+-    public void loadAudioRecordSucceeds() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+-      tensor.load(new float[] {1, 2, 3, 4, 5});
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .isEqualTo(new float[] {2.f, 3.f, 4.f, 5.f});
+-
+-      AudioRecord record = mock(AudioRecord.class);
+-      when(record.getBufferSizeInFrames()).thenReturn(5);
+-      when(record.getChannelCount()).thenReturn(1);
+-      when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_FLOAT);
+-      when(record.getFormat())
+-          .thenReturn(
+-              new AudioFormat.Builder()
+-                  .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+-                  .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
+-                  .setSampleRate(16000)
+-                  .build());
+-      // Unused
+-      when(record.read(any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+-          .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
+-      // Used
+-      when(record.read(any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+-          .thenReturn(1);
+-      assertThat(tensor.load(record)).isEqualTo(1);
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .isEqualTo(new float[] {3.f, 4.f, 5.f, 0});
+-
+-      record = mock(AudioRecord.class);
+-      when(record.getBufferSizeInFrames()).thenReturn(5);
+-      when(record.getChannelCount()).thenReturn(1);
+-      when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_16BIT);
+-      when(record.getFormat())
+-          .thenReturn(
+-              new AudioFormat.Builder()
+-                  .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+-                  .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
+-                  .setSampleRate(16000)
+-                  .build());
+-      // Used
+-      when(record.read(any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+-          .thenReturn(2);
+-      // Unused
+-      when(record.read(any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+-          .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
+-      assertThat(tensor.load(record)).isEqualTo(2);
+-      assertThat(tensor.getTensorBuffer().getFloatArray()).isEqualTo(new float[] {5.f, 0, 0, 0});
+-    }
+-
+-    @Test
+-    public void loadAudioRecordFailsWithErrorState() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+-      tensor.load(new float[] {1, 2, 3, 4, 5});
+-      assertThat(tensor.getTensorBuffer().getFloatArray())
+-          .isEqualTo(new float[] {2.f, 3.f, 4.f, 5.f});
+-
+-      AudioRecord record = mock(AudioRecord.class);
+-      when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_FLOAT);
+-      when(record.getFormat())
+-          .thenReturn(
+-              new AudioFormat.Builder()
+-                  .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+-                  .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
+-                  .setSampleRate(16000)
+-                  .build());
+-      // Unused
+-      when(record.read(any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+-          .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
+-      // Used
+-      when(record.read(any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+-          .thenReturn(AudioRecord.ERROR_DEAD_OBJECT);
+-      IllegalStateException exception =
+-          assertThrows(IllegalStateException.class, () -> tensor.load(record));
+-      assertThat(exception).hasMessageThat().contains("ERROR_DEAD_OBJECT");
+-    }
+-
+-    @Test
+-    public void loadAudioRecordFailsWithUnsupportedAudioEncoding() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+-      AudioRecord record = mock(AudioRecord.class);
+-      when(record.getFormat())
+-          .thenReturn(
+-              new AudioFormat.Builder()
+-                  .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+-                  .setEncoding(AudioFormat.ENCODING_PCM_8BIT) // Not supported
+-                  .setSampleRate(16000)
+-                  .build());
+-      when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_8BIT);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> tensor.load(record));
+-      assertThat(exception).hasMessageThat().ignoringCase().contains("unsupported encoding");
+-    }
+-
+-    @Test
+-    public void loadAudioRecordFailsWithIncompatibleAudioFormat() throws Exception {
+-      TensorAudio tensor =
+-          TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+-      AudioRecord record = mock(AudioRecord.class);
+-      when(record.getFormat())
+-          .thenReturn(
+-              new AudioFormat.Builder()
+-                  .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+-                  .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
+-                  .setSampleRate(44100) // Mismatch
+-                  .build());
+-
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> tensor.load(record));
+-      assertThat(exception).hasMessageThat().ignoringCase().contains("Incompatible audio format");
++    /** General tests of TensorAudio. */
++    @RunWith(RobolectricTestRunner.class)
++    public static final class General extends TensorAudioTest {
++        @Test
++        public void createSucceedsWithTensorAudioFormat() throws Exception {
++            TensorAudio tensor = TensorAudio.create(
++                    TensorAudioFormat.builder().setChannels(1).setSampleRate(2).build(), 100);
++            assertThat(tensor.getFormat().getChannels()).isEqualTo(1);
++            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(2);
++            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(100);
++        }
++
++        @Test
++        public void createSucceedsWithTensorAudioFormatWithMultipleChannels() throws Exception {
++            TensorAudio tensor = TensorAudio.create(
++                    TensorAudioFormat.builder().setChannels(5).setSampleRate(2).build(), 100);
++            assertThat(tensor.getFormat().getChannels()).isEqualTo(5);
++            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(2);
++            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(500);
++        }
++
++        @Test
++        public void createSucceededsWithDefaultArguments() throws Exception {
++            TensorAudio tensor =
++                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(20).build(), 1000);
++            // Number of channels defaults to 1.
++            assertThat(tensor.getFormat().getChannels()).isEqualTo(1);
++            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(20);
++            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(1000);
++        }
++
++        @Test
++        public void createSucceedsWithAudioFormat() throws Exception {
++            AudioFormat format = new AudioFormat.Builder()
++                                         .setChannelMask(AudioFormat.CHANNEL_IN_STEREO)
++                                         .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
++                                         .setSampleRate(16000)
++                                         .build();
++            TensorAudio tensor = TensorAudio.create(format, 100);
++            // STEREO has 2 channels
++            assertThat(tensor.getFormat().getChannels()).isEqualTo(2);
++            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(16000);
++            // flatSize = channelCount * sampleCount
++            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(200);
++        }
++
++        @Test
++        public void createFailedWithInvalidSampleRate() throws Exception {
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    ()
++                            -> TensorAudio.create(
++                                    TensorAudioFormat.builder().setSampleRate(0).build(), 100));
++            // Sample rate 0 is not allowed
++            assertThat(exception).hasMessageThat().ignoringCase().contains("sample rate");
++        }
++
++        @Test
++        public void createFailedWithInvalidChannels() throws Exception {
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    ()
++                            -> TensorAudio.create(TensorAudioFormat.builder()
++                                                          .setSampleRate(1)
++                                                          .setChannels(-1)
++                                                          .build(),
++                                    100));
++            // Negative channels is not allowed
++            assertThat(exception).hasMessageThat().ignoringCase().contains("channels");
++        }
++
++        @Test
++        public void loadSucceedsFromArray() throws Exception {
++            TensorAudioFormat format =
++                    TensorAudioFormat.builder().setChannels(2).setSampleRate(2).build();
++            TensorAudio tensor = TensorAudio.create(format, 2);
++            assertThat(tensor.getTensorBuffer().getFloatArray()).isEqualTo(new float[4]);
++
++            tensor.load(new float[] {2.f, 0});
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .usingTolerance(0.001f)
++                    .containsExactly(new float[] {0, 0, 2.f, 0});
++
++            tensor.load(new float[] {2.f, 3.f}, 0, 2);
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .usingTolerance(0.001f)
++                    .containsExactly(new float[] {2.f, 0, 2.f, 3.f});
++
++            tensor.load(new short[] {Short.MAX_VALUE, Short.MIN_VALUE});
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .usingTolerance(0.001f)
++                    .containsExactly(new float[] {2.f, 3.f, 1.f, -1.f});
++
++            tensor.load(new short[] {1, 2, 3, 0, 1, Short.MIN_VALUE, 3, 4, 5}, 3, 6);
++            // The entire sequence becomes {2.f, 0, 2.f, 3.f, 1.f, -1.f, 0, 0, -1.f, 0, 0, 0} but
++            // the ring buffer is only keep the last 4 results.
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .usingTolerance(0.001f)
++                    .containsExactly(new float[] {-1.f, 0, 0, 0});
++        }
++
++        @Test
++        public void loadFailsWithIndexOutOfRange() throws Exception {
++            TensorAudioFormat format = TensorAudioFormat.builder().setSampleRate(2).build();
++            TensorAudio tensor = TensorAudio.create(format, 5);
++
++            assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[100], 99, 2));
++
++            assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[100], 99, 2));
++        }
++
++        @Test
++        public void loadFailsWithIncompatibleInputSize() throws Exception {
++            TensorAudioFormat format =
++                    TensorAudioFormat.builder().setChannels(3).setSampleRate(2).build();
++            TensorAudio tensor = TensorAudio.create(format, 5);
++
++            assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[1]));
++
++            assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[2]));
++
++            assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[2], 1, 1));
++
++            assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[5], 2, 4));
++        }
++
++        @Test
++        public void loadAudioRecordSucceeds() throws Exception {
++            TensorAudio tensor =
++                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
++            tensor.load(new float[] {1, 2, 3, 4, 5});
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .isEqualTo(new float[] {2.f, 3.f, 4.f, 5.f});
++
++            AudioRecord record = mock(AudioRecord.class);
++            when(record.getBufferSizeInFrames()).thenReturn(5);
++            when(record.getChannelCount()).thenReturn(1);
++            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_FLOAT);
++            when(record.getFormat())
++                    .thenReturn(new AudioFormat.Builder()
++                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
++                                        .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
++                                        .setSampleRate(16000)
++                                        .build());
++            // Unused
++            when(record.read(
++                         any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
++                    .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
++            // Used
++            when(record.read(
++                         any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
++                    .thenReturn(1);
++            assertThat(tensor.load(record)).isEqualTo(1);
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .isEqualTo(new float[] {3.f, 4.f, 5.f, 0});
++
++            record = mock(AudioRecord.class);
++            when(record.getBufferSizeInFrames()).thenReturn(5);
++            when(record.getChannelCount()).thenReturn(1);
++            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_16BIT);
++            when(record.getFormat())
++                    .thenReturn(new AudioFormat.Builder()
++                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
++                                        .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
++                                        .setSampleRate(16000)
++                                        .build());
++            // Used
++            when(record.read(
++                         any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
++                    .thenReturn(2);
++            // Unused
++            when(record.read(
++                         any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
++                    .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
++            assertThat(tensor.load(record)).isEqualTo(2);
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .isEqualTo(new float[] {5.f, 0, 0, 0});
++        }
++
++        @Test
++        public void loadAudioRecordFailsWithErrorState() throws Exception {
++            TensorAudio tensor =
++                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
++            tensor.load(new float[] {1, 2, 3, 4, 5});
++            assertThat(tensor.getTensorBuffer().getFloatArray())
++                    .isEqualTo(new float[] {2.f, 3.f, 4.f, 5.f});
++
++            AudioRecord record = mock(AudioRecord.class);
++            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_FLOAT);
++            when(record.getFormat())
++                    .thenReturn(new AudioFormat.Builder()
++                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
++                                        .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
++                                        .setSampleRate(16000)
++                                        .build());
++            // Unused
++            when(record.read(
++                         any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
++                    .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
++            // Used
++            when(record.read(
++                         any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
++                    .thenReturn(AudioRecord.ERROR_DEAD_OBJECT);
++            IllegalStateException exception =
++                    assertThrows(IllegalStateException.class, () -> tensor.load(record));
++            assertThat(exception).hasMessageThat().contains("ERROR_DEAD_OBJECT");
++        }
++
++        @Test
++        public void loadAudioRecordFailsWithUnsupportedAudioEncoding() throws Exception {
++            TensorAudio tensor =
++                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
++            AudioRecord record = mock(AudioRecord.class);
++            when(record.getFormat())
++                    .thenReturn(new AudioFormat.Builder()
++                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
++                                        .setEncoding(AudioFormat.ENCODING_PCM_8BIT) // Not supported
++                                        .setSampleRate(16000)
++                                        .build());
++            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_8BIT);
++
++            IllegalArgumentException exception =
++                    assertThrows(IllegalArgumentException.class, () -> tensor.load(record));
++            assertThat(exception).hasMessageThat().ignoringCase().contains("unsupported encoding");
++        }
++
++        @Test
++        public void loadAudioRecordFailsWithIncompatibleAudioFormat() throws Exception {
++            TensorAudio tensor =
++                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
++            AudioRecord record = mock(AudioRecord.class);
++            when(record.getFormat())
++                    .thenReturn(new AudioFormat.Builder()
++                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
++                                        .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
++                                        .setSampleRate(44100) // Mismatch
++                                        .build());
++
++            IllegalArgumentException exception =
++                    assertThrows(IllegalArgumentException.class, () -> tensor.load(record));
++            assertThat(exception).hasMessageThat().ignoringCase().contains(
++                    "Incompatible audio format");
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java
+index d97665d1ed771..1d26476733c98 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java
+@@ -18,78 +18,81 @@ package org.tensorflow.lite.support.common;
+ import static com.google.common.truth.Truth.assertThat;
+ 
+ import android.content.Context;
++
+ import androidx.test.core.app.ApplicationProvider;
++
++import org.junit.Assert;
++import org.junit.Test;
++import org.junit.runner.RunWith;
++import org.robolectric.RobolectricTestRunner;
++
+ import java.io.ByteArrayInputStream;
+ import java.io.IOException;
+ import java.io.InputStream;
+ import java.nio.MappedByteBuffer;
+ import java.nio.charset.Charset;
+ import java.util.List;
+-import org.junit.Assert;
+-import org.junit.Test;
+-import org.junit.runner.RunWith;
+-import org.robolectric.RobolectricTestRunner;
+ 
+ /** Tests of {@link org.tensorflow.lite.support.common.FileUtil}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class FileUtilTest {
+-  private final Context context = ApplicationProvider.getApplicationContext();
+-  private static final String LABEL_PATH = "flower_labels.txt";
+-
+-  @Test
+-  public void testLoadLabels() throws IOException {
+-    List<String> labels = FileUtil.loadLabels(context, LABEL_PATH);
+-    assertThat(labels)
+-        .containsExactly("daisy", "dandelion", "roses", "sunflowers", "tulips")
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void testLoadLabelsFromInputStream() throws IOException {
+-    InputStream inputStream = context.getAssets().open(LABEL_PATH);
+-    assertThat(FileUtil.loadLabels(inputStream))
+-        .containsExactly("daisy", "dandelion", "roses", "sunflowers", "tulips")
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void whitespaceLabelsShouldNotCount() throws IOException {
+-    String s = "a\nb\n \n\n\nc";
+-    InputStream stream = new ByteArrayInputStream(s.getBytes(Charset.defaultCharset()));
+-    assertThat(FileUtil.loadLabels(stream)).hasSize(3);
+-  }
+-
+-  @Test
+-  public void testLoadLabelsNullContext() throws IOException {
+-    Context nullContext = null;
+-    Assert.assertThrows(
+-        NullPointerException.class, () -> FileUtil.loadLabels(nullContext, LABEL_PATH));
+-  }
+-
+-  @Test
+-  public void testLoadLabelsNullFilePath() throws IOException {
+-    String nullFilePath = null;
+-    Assert.assertThrows(
+-        NullPointerException.class, () -> FileUtil.loadLabels(context, nullFilePath));
+-  }
+-
+-  @Test
+-  public void testLoadMappedFile() throws IOException {
+-    MappedByteBuffer byteModel = FileUtil.loadMappedFile(context, LABEL_PATH);
+-    assertThat(byteModel).isNotNull();
+-  }
+-
+-  @Test
+-  public void testLoadMappedFileWithNullContext() throws IOException {
+-    Context nullContext = null;
+-    Assert.assertThrows(
+-        NullPointerException.class, () -> FileUtil.loadMappedFile(nullContext, LABEL_PATH));
+-  }
+-
+-  @Test
+-  public void loadMappedFileWithNullFilePath() throws IOException {
+-    String nullFilePath = null;
+-    Assert.assertThrows(
+-        NullPointerException.class, () -> FileUtil.loadMappedFile(context, nullFilePath));
+-  }
++    private final Context context = ApplicationProvider.getApplicationContext();
++    private static final String LABEL_PATH = "flower_labels.txt";
++
++    @Test
++    public void testLoadLabels() throws IOException {
++        List<String> labels = FileUtil.loadLabels(context, LABEL_PATH);
++        assertThat(labels)
++                .containsExactly("daisy", "dandelion", "roses", "sunflowers", "tulips")
++                .inOrder();
++    }
++
++    @Test
++    public void testLoadLabelsFromInputStream() throws IOException {
++        InputStream inputStream = context.getAssets().open(LABEL_PATH);
++        assertThat(FileUtil.loadLabels(inputStream))
++                .containsExactly("daisy", "dandelion", "roses", "sunflowers", "tulips")
++                .inOrder();
++    }
++
++    @Test
++    public void whitespaceLabelsShouldNotCount() throws IOException {
++        String s = "a\nb\n \n\n\nc";
++        InputStream stream = new ByteArrayInputStream(s.getBytes(Charset.defaultCharset()));
++        assertThat(FileUtil.loadLabels(stream)).hasSize(3);
++    }
++
++    @Test
++    public void testLoadLabelsNullContext() throws IOException {
++        Context nullContext = null;
++        Assert.assertThrows(
++                NullPointerException.class, () -> FileUtil.loadLabels(nullContext, LABEL_PATH));
++    }
++
++    @Test
++    public void testLoadLabelsNullFilePath() throws IOException {
++        String nullFilePath = null;
++        Assert.assertThrows(
++                NullPointerException.class, () -> FileUtil.loadLabels(context, nullFilePath));
++    }
++
++    @Test
++    public void testLoadMappedFile() throws IOException {
++        MappedByteBuffer byteModel = FileUtil.loadMappedFile(context, LABEL_PATH);
++        assertThat(byteModel).isNotNull();
++    }
++
++    @Test
++    public void testLoadMappedFileWithNullContext() throws IOException {
++        Context nullContext = null;
++        Assert.assertThrows(
++                NullPointerException.class, () -> FileUtil.loadMappedFile(nullContext, LABEL_PATH));
++    }
++
++    @Test
++    public void loadMappedFileWithNullFilePath() throws IOException {
++        String nullFilePath = null;
++        Assert.assertThrows(
++                NullPointerException.class, () -> FileUtil.loadMappedFile(context, nullFilePath));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java
+index 43a7f7cd1ce29..82f97f2534cf7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java
+@@ -27,59 +27,58 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ /** Tests for {@link TensorProcessor}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class TensorProcessorTest {
++    private static final int EXAMPLE_NUM_FEATURES = 1000;
++    private static final float MEAN = 127.5f;
++    private static final float STDDEV = 127.5f;
+ 
+-  private static final int EXAMPLE_NUM_FEATURES = 1000;
+-  private static final float MEAN = 127.5f;
+-  private static final float STDDEV = 127.5f;
+-
+-  @Test
+-  public void testBuild() {
+-    TensorProcessor processor =
+-        new TensorProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+-    assertThat(processor).isNotNull();
+-  }
++    @Test
++    public void testBuild() {
++        TensorProcessor processor =
++                new TensorProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
++        assertThat(processor).isNotNull();
++    }
+ 
+-  @Test
+-  public void testNormalize() {
+-    TensorBuffer input = createExampleTensorBuffer();
+-    TensorProcessor processor =
+-        new TensorProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+-    TensorBuffer output = processor.process(input);
++    @Test
++    public void testNormalize() {
++        TensorBuffer input = createExampleTensorBuffer();
++        TensorProcessor processor =
++                new TensorProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
++        TensorBuffer output = processor.process(input);
+ 
+-    float[] pixels = output.getFloatArray();
+-    assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_FEATURES);
+-    for (float p : pixels) {
+-      assertThat(p).isAtLeast(-1);
+-      assertThat(p).isAtMost(1);
++        float[] pixels = output.getFloatArray();
++        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_FEATURES);
++        for (float p : pixels) {
++            assertThat(p).isAtLeast(-1);
++            assertThat(p).isAtMost(1);
++        }
+     }
+-  }
+ 
+-  @Test
+-  public void testMultipleNormalize() {
+-    TensorBuffer input = createExampleTensorBuffer();
+-    TensorProcessor processor =
+-        new TensorProcessor.Builder()
+-            .add(new NormalizeOp(MEAN, STDDEV)) // [0, 255] -> [-1, 1]
+-            .add(new NormalizeOp(-1, 2)) // [-1, 1] -> [0, 1]
+-            .build();
+-    TensorBuffer output = processor.process(input);
++    @Test
++    public void testMultipleNormalize() {
++        TensorBuffer input = createExampleTensorBuffer();
++        TensorProcessor processor =
++                new TensorProcessor.Builder()
++                        .add(new NormalizeOp(MEAN, STDDEV)) // [0, 255] -> [-1, 1]
++                        .add(new NormalizeOp(-1, 2)) // [-1, 1] -> [0, 1]
++                        .build();
++        TensorBuffer output = processor.process(input);
+ 
+-    float[] pixels = output.getFloatArray();
+-    assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_FEATURES);
+-    for (float p : pixels) {
+-      assertThat(p).isAtLeast(0);
+-      assertThat(p).isAtMost(1);
++        float[] pixels = output.getFloatArray();
++        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_FEATURES);
++        for (float p : pixels) {
++            assertThat(p).isAtLeast(0);
++            assertThat(p).isAtMost(1);
++        }
+     }
+-  }
+ 
+-  // Creates a TensorBuffer of size {1, 1000}, containing values in range [0, 255].
+-  private static TensorBuffer createExampleTensorBuffer() {
+-    TensorBuffer buffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    int[] features = new int[EXAMPLE_NUM_FEATURES];
+-    for (int i = 0; i < EXAMPLE_NUM_FEATURES; i++) {
+-      features[i] = i % 256;
++    // Creates a TensorBuffer of size {1, 1000}, containing values in range [0, 255].
++    private static TensorBuffer createExampleTensorBuffer() {
++        TensorBuffer buffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++        int[] features = new int[EXAMPLE_NUM_FEATURES];
++        for (int i = 0; i < EXAMPLE_NUM_FEATURES; i++) {
++            features[i] = i % 256;
++        }
++        buffer.loadArray(features, new int[] {1, EXAMPLE_NUM_FEATURES});
++        return buffer;
+     }
+-    buffer.loadArray(features, new int[] {1, EXAMPLE_NUM_FEATURES});
+-    return buffer;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java
+index a159c71863322..e8ba24d27550b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java
+@@ -27,56 +27,55 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ /** Tests of {@link CastOp}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class CastOpTest {
++    private static final float[] FLOAT_ARRAY = new float[] {1.1f, 3.3f, 5.5f, 7.7f, 9.9f};
++    private static final float[] CASTED_FLOAT_ARRAY = new float[] {1.0f, 3.0f, 5.0f, 7.0f, 9.0f};
++    private static final int[] INT_ARRAY = new int[] {1, 3, 5, 7, 9};
++    private static final int[] SHAPE = new int[] {5};
+ 
+-  private static final float[] FLOAT_ARRAY = new float[] {1.1f, 3.3f, 5.5f, 7.7f, 9.9f};
+-  private static final float[] CASTED_FLOAT_ARRAY = new float[] {1.0f, 3.0f, 5.0f, 7.0f, 9.0f};
+-  private static final int[] INT_ARRAY = new int[] {1, 3, 5, 7, 9};
+-  private static final int[] SHAPE = new int[] {5};
+-
+-  @Test
+-  public void castFloat32ToUint8ShouldSuccess() {
+-    TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    floatBuffer.loadArray(FLOAT_ARRAY, SHAPE);
+-    CastOp op = new CastOp(DataType.UINT8);
+-    TensorBuffer uint8Buffer = op.apply(floatBuffer);
+-    assertThat(uint8Buffer.getDataType()).isEqualTo(DataType.UINT8);
+-    assertThat(uint8Buffer.getIntArray()).isEqualTo(INT_ARRAY);
+-  }
++    @Test
++    public void castFloat32ToUint8ShouldSuccess() {
++        TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++        floatBuffer.loadArray(FLOAT_ARRAY, SHAPE);
++        CastOp op = new CastOp(DataType.UINT8);
++        TensorBuffer uint8Buffer = op.apply(floatBuffer);
++        assertThat(uint8Buffer.getDataType()).isEqualTo(DataType.UINT8);
++        assertThat(uint8Buffer.getIntArray()).isEqualTo(INT_ARRAY);
++    }
+ 
+-  @Test
+-  public void castUint8ToFloat32ShouldSuccess() {
+-    TensorBuffer uint8Buffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    uint8Buffer.loadArray(INT_ARRAY, SHAPE);
+-    CastOp op = new CastOp(DataType.FLOAT32);
+-    TensorBuffer floatBuffer = op.apply(uint8Buffer);
+-    assertThat(floatBuffer.getDataType()).isEqualTo(DataType.FLOAT32);
+-    assertThat(floatBuffer.getFloatArray()).isEqualTo(CASTED_FLOAT_ARRAY);
+-  }
++    @Test
++    public void castUint8ToFloat32ShouldSuccess() {
++        TensorBuffer uint8Buffer = TensorBuffer.createDynamic(DataType.UINT8);
++        uint8Buffer.loadArray(INT_ARRAY, SHAPE);
++        CastOp op = new CastOp(DataType.FLOAT32);
++        TensorBuffer floatBuffer = op.apply(uint8Buffer);
++        assertThat(floatBuffer.getDataType()).isEqualTo(DataType.FLOAT32);
++        assertThat(floatBuffer.getFloatArray()).isEqualTo(CASTED_FLOAT_ARRAY);
++    }
+ 
+-  @Test
+-  public void castFloat32ToFloat32ShouldNotRecreate() {
+-    TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    floatBuffer.loadArray(FLOAT_ARRAY, SHAPE);
+-    CastOp op = new CastOp(DataType.FLOAT32);
+-    TensorBuffer newBuffer = op.apply(floatBuffer);
+-    assertThat(newBuffer.getDataType()).isEqualTo(DataType.FLOAT32);
+-    assertThat(newBuffer).isSameInstanceAs(floatBuffer);
+-  }
++    @Test
++    public void castFloat32ToFloat32ShouldNotRecreate() {
++        TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++        floatBuffer.loadArray(FLOAT_ARRAY, SHAPE);
++        CastOp op = new CastOp(DataType.FLOAT32);
++        TensorBuffer newBuffer = op.apply(floatBuffer);
++        assertThat(newBuffer.getDataType()).isEqualTo(DataType.FLOAT32);
++        assertThat(newBuffer).isSameInstanceAs(floatBuffer);
++    }
+ 
+-  @Test
+-  public void castUint8ToUint8ShouldNotRecreate() {
+-    TensorBuffer uint8Buffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    uint8Buffer.loadArray(INT_ARRAY, SHAPE);
+-    CastOp op = new CastOp(DataType.UINT8);
+-    TensorBuffer newBuffer = op.apply(uint8Buffer);
+-    assertThat(newBuffer.getDataType()).isEqualTo(DataType.UINT8);
+-    assertThat(newBuffer).isSameInstanceAs(uint8Buffer);
+-  }
++    @Test
++    public void castUint8ToUint8ShouldNotRecreate() {
++        TensorBuffer uint8Buffer = TensorBuffer.createDynamic(DataType.UINT8);
++        uint8Buffer.loadArray(INT_ARRAY, SHAPE);
++        CastOp op = new CastOp(DataType.UINT8);
++        TensorBuffer newBuffer = op.apply(uint8Buffer);
++        assertThat(newBuffer.getDataType()).isEqualTo(DataType.UINT8);
++        assertThat(newBuffer).isSameInstanceAs(uint8Buffer);
++    }
+ 
+-  @Test
+-  public void castToUnsupportedDataTypeShouldThrow() {
+-    for (DataType type : new DataType[] {DataType.INT32, DataType.INT64, DataType.STRING}) {
+-      Assert.assertThrows(IllegalArgumentException.class, () -> new CastOp(type));
++    @Test
++    public void castToUnsupportedDataTypeShouldThrow() {
++        for (DataType type : new DataType[] {DataType.INT32, DataType.INT64, DataType.STRING}) {
++            Assert.assertThrows(IllegalArgumentException.class, () -> new CastOp(type));
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java
+index 99ded56ce069a..a69bcd7ec0296 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java
+@@ -26,16 +26,15 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ /** Tests of {@link DequantizeOp}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class DequantizeOpTest {
+-
+-  @Test
+-  public void dequantizeShouldSucess() {
+-    int[] originalData = new int[] {191, 159, 63, 127, 255, 0};
+-    DequantizeOp op = new DequantizeOp(127.0f, 1.0f / 128);
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {6}, DataType.UINT8);
+-    input.loadArray(originalData);
+-    TensorBuffer dequantized = op.apply(input);
+-    assertThat(dequantized.getDataType()).isEqualTo(DataType.FLOAT32);
+-    assertThat(dequantized.getFloatArray())
+-        .isEqualTo(new float[] {0.5f, 0.25f, -0.5f, 0, 1, -0.9921875f});
+-  }
++    @Test
++    public void dequantizeShouldSucess() {
++        int[] originalData = new int[] {191, 159, 63, 127, 255, 0};
++        DequantizeOp op = new DequantizeOp(127.0f, 1.0f / 128);
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {6}, DataType.UINT8);
++        input.loadArray(originalData);
++        TensorBuffer dequantized = op.apply(input);
++        assertThat(dequantized.getDataType()).isEqualTo(DataType.FLOAT32);
++        assertThat(dequantized.getFloatArray())
++                .isEqualTo(new float[] {0.5f, 0.25f, -0.5f, 0, 1, -0.9921875f});
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java
+index 09ef275a826bc..aabc6be926106 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.common.ops;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.tensorflow.lite.DataType.FLOAT32;
+ import static org.tensorflow.lite.DataType.UINT8;
+ 
+@@ -31,122 +32,120 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+  */
+ @RunWith(RobolectricTestRunner.class)
+ public final class NormalizeOpTest {
++    private static final float MEAN = 50;
++    private static final float STDDEV = 50;
++    private static final int NUM_ELEMENTS = 100;
++
++    @Test
++    public void testNormalizeIntBuffer() {
++        int[] inputArr = new int[NUM_ELEMENTS];
++        for (int i = 0; i < NUM_ELEMENTS; i++) {
++            inputArr[i] = i;
++        }
++        TensorBuffer input = TensorBuffer.createDynamic(DataType.UINT8);
++        input.loadArray(inputArr, new int[] {inputArr.length});
++        NormalizeOp op = new NormalizeOp(MEAN, STDDEV);
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(FLOAT32);
++        float[] outputArr = output.getFloatArray();
++        for (int i = 0; i < NUM_ELEMENTS; i++) {
++            assertThat(outputArr[i]).isEqualTo((inputArr[i] - MEAN) / STDDEV);
++        }
++    }
+ 
+-  private static final float MEAN = 50;
+-  private static final float STDDEV = 50;
+-  private static final int NUM_ELEMENTS = 100;
++    @Test
++    public void testNormalizeFloatBuffer() {
++        float[] inputArr = new float[NUM_ELEMENTS];
++        for (int i = 0; i < NUM_ELEMENTS; i++) {
++            inputArr[i] = i;
++        }
++        TensorBuffer input = TensorBuffer.createDynamic(FLOAT32);
++        input.loadArray(inputArr, new int[] {inputArr.length});
++        NormalizeOp op = new NormalizeOp(MEAN, STDDEV);
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(FLOAT32);
++        float[] outputArr = output.getFloatArray();
++        for (int i = 0; i < NUM_ELEMENTS; i++) {
++            assertThat(outputArr[i]).isEqualTo((inputArr[i] - MEAN) / STDDEV);
++        }
++    }
+ 
+-  @Test
+-  public void testNormalizeIntBuffer() {
+-    int[] inputArr = new int[NUM_ELEMENTS];
+-    for (int i = 0; i < NUM_ELEMENTS; i++) {
+-      inputArr[i] = i;
++    @Test
++    public void testZeroStddev() {
++        Assert.assertThrows(IllegalArgumentException.class, () -> new NormalizeOp(1, 0));
+     }
+-    TensorBuffer input = TensorBuffer.createDynamic(DataType.UINT8);
+-    input.loadArray(inputArr, new int[] {inputArr.length});
+-    NormalizeOp op = new NormalizeOp(MEAN, STDDEV);
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(FLOAT32);
+-    float[] outputArr = output.getFloatArray();
+-    for (int i = 0; i < NUM_ELEMENTS; i++) {
+-      assertThat(outputArr[i]).isEqualTo((inputArr[i] - MEAN) / STDDEV);
++
++    @Test
++    public void testIdentityShortcut() {
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
++        NormalizeOp op = new NormalizeOp(0, 1);
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(UINT8);
++        assertThat(output).isSameInstanceAs(input);
+     }
+-  }
+ 
+-  @Test
+-  public void testNormalizeFloatBuffer() {
+-    float[] inputArr = new float[NUM_ELEMENTS];
+-    for (int i = 0; i < NUM_ELEMENTS; i++) {
+-      inputArr[i] = i;
++    @Test
++    public void testNormalizeOp_zeroMeanAndZeroStddev() {
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
++        NormalizeOp op = new NormalizeOp(0, 0);
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(UINT8);
++        assertThat(output).isSameInstanceAs(input);
+     }
+-    TensorBuffer input = TensorBuffer.createDynamic(FLOAT32);
+-    input.loadArray(inputArr, new int[] {inputArr.length});
+-    NormalizeOp op = new NormalizeOp(MEAN, STDDEV);
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(FLOAT32);
+-    float[] outputArr = output.getFloatArray();
+-    for (int i = 0; i < NUM_ELEMENTS; i++) {
+-      assertThat(outputArr[i]).isEqualTo((inputArr[i] - MEAN) / STDDEV);
++
++    @Test
++    public void testNormalizeOp_zeroMeanAndInifityStddev() {
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
++        NormalizeOp op = new NormalizeOp(0, Float.POSITIVE_INFINITY);
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(UINT8);
++        assertThat(output).isSameInstanceAs(input);
+     }
+-  }
+-
+-  @Test
+-  public void testZeroStddev() {
+-    Assert.assertThrows(IllegalArgumentException.class, () -> new NormalizeOp(1, 0));
+-  }
+-
+-  @Test
+-  public void testIdentityShortcut() {
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+-    NormalizeOp op = new NormalizeOp(0, 1);
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(UINT8);
+-    assertThat(output).isSameInstanceAs(input);
+-  }
+-
+-  @Test
+-  public void testNormalizeOp_zeroMeanAndZeroStddev() {
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+-    NormalizeOp op = new NormalizeOp(0, 0);
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(UINT8);
+-    assertThat(output).isSameInstanceAs(input);
+-  }
+-
+-  @Test
+-  public void testNormalizeOp_zeroMeanAndInifityStddev() {
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+-    NormalizeOp op = new NormalizeOp(0, Float.POSITIVE_INFINITY);
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(UINT8);
+-    assertThat(output).isSameInstanceAs(input);
+-  }
+-
+-  @Test
+-  public void testMultiChannelNormalize() {
+-    float[] inputArr = new float[NUM_ELEMENTS];
+-    for (int i = 0; i < NUM_ELEMENTS; i++) {
+-      inputArr[i] = i;
++
++    @Test
++    public void testMultiChannelNormalize() {
++        float[] inputArr = new float[NUM_ELEMENTS];
++        for (int i = 0; i < NUM_ELEMENTS; i++) {
++            inputArr[i] = i;
++        }
++        TensorBuffer input = TensorBuffer.createDynamic(FLOAT32);
++        input.loadArray(inputArr, new int[] {20, 5});
++        float[] means = new float[] {1, 2, 3, 4, 5};
++        float[] stddevs = new float[] {6, 7, 8, 9, 10};
++        NormalizeOp op = new NormalizeOp(means, stddevs);
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(FLOAT32);
++        float[] outputArr = output.getFloatArray();
++        for (int i = 0; i < NUM_ELEMENTS; i++) {
++            assertThat(outputArr[i]).isEqualTo((i - means[i % 5]) / stddevs[i % 5]);
++        }
+     }
+-    TensorBuffer input = TensorBuffer.createDynamic(FLOAT32);
+-    input.loadArray(inputArr, new int[] {20, 5});
+-    float[] means = new float[] {1, 2, 3, 4, 5};
+-    float[] stddevs = new float[] {6, 7, 8, 9, 10};
+-    NormalizeOp op = new NormalizeOp(means, stddevs);
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(FLOAT32);
+-    float[] outputArr = output.getFloatArray();
+-    for (int i = 0; i < NUM_ELEMENTS; i++) {
+-      assertThat(outputArr[i]).isEqualTo((i - means[i % 5]) / stddevs[i % 5]);
++
++    @Test
++    public void testMultiChannelShortcut() {
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
++        NormalizeOp op = new NormalizeOp(new float[] {0, 0, 0}, new float[] {1, 1, 1});
++        TensorBuffer output = op.apply(input);
++        assertThat(output.getDataType()).isEqualTo(UINT8);
++        assertThat(output).isSameInstanceAs(input);
++    }
++
++    @Test
++    public void testMismatchedNumbersOfMeansAndStddevs() {
++        Assert.assertThrows(IllegalArgumentException.class,
++                () -> new NormalizeOp(new float[] {2, 3}, new float[] {1}));
++    }
++
++    @Test
++    public void testMismatchedInputTensorChannelNum() {
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
++        NormalizeOp op = new NormalizeOp(new float[] {0, 0}, new float[] {1, 2});
++        Assert.assertThrows(IllegalArgumentException.class, () -> op.apply(input));
++    }
++
++    @Test
++    public void testAnyChannelInvalidStddev() {
++        Assert.assertThrows(IllegalArgumentException.class,
++                () -> new NormalizeOp(new float[] {2, 3}, new float[] {1, 0}));
+     }
+-  }
+-
+-  @Test
+-  public void testMultiChannelShortcut() {
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+-    NormalizeOp op = new NormalizeOp(new float[] {0, 0, 0}, new float[] {1, 1, 1});
+-    TensorBuffer output = op.apply(input);
+-    assertThat(output.getDataType()).isEqualTo(UINT8);
+-    assertThat(output).isSameInstanceAs(input);
+-  }
+-
+-  @Test
+-  public void testMismatchedNumbersOfMeansAndStddevs() {
+-    Assert.assertThrows(
+-        IllegalArgumentException.class, () -> new NormalizeOp(new float[] {2, 3}, new float[] {1}));
+-  }
+-
+-  @Test
+-  public void testMismatchedInputTensorChannelNum() {
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+-    NormalizeOp op = new NormalizeOp(new float[] {0, 0}, new float[] {1, 2});
+-    Assert.assertThrows(IllegalArgumentException.class, () -> op.apply(input));
+-  }
+-
+-  @Test
+-  public void testAnyChannelInvalidStddev() {
+-    Assert.assertThrows(
+-        IllegalArgumentException.class,
+-        () -> new NormalizeOp(new float[] {2, 3}, new float[] {1, 0}));
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java
+index 8ef72f92e0696..519cd287e1575 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java
+@@ -26,15 +26,14 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ /** Tests of {@link QuantizeOp}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class QuantizeOpTest {
+-
+-  @Test
+-  public void quantizeShouldSuccess() {
+-    float[] originalData = {0.5f, 0.25f, -0.5f, 0, 1, -0.9921875f}; // -0.9921875 == -127 / 128
+-    QuantizeOp op = new QuantizeOp(127.0f, 1.0f / 128);
+-    TensorBuffer input = TensorBuffer.createFixedSize(new int[] {6}, DataType.FLOAT32);
+-    input.loadArray(originalData);
+-    TensorBuffer quantized = op.apply(input);
+-    assertThat(quantized.getDataType()).isEqualTo(DataType.FLOAT32);
+-    assertThat(quantized.getIntArray()).isEqualTo(new int[] {191, 159, 63, 127, 255, 0});
+-  }
++    @Test
++    public void quantizeShouldSuccess() {
++        float[] originalData = {0.5f, 0.25f, -0.5f, 0, 1, -0.9921875f}; // -0.9921875 == -127 / 128
++        QuantizeOp op = new QuantizeOp(127.0f, 1.0f / 128);
++        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {6}, DataType.FLOAT32);
++        input.loadArray(originalData);
++        TensorBuffer quantized = op.apply(input);
++        assertThat(quantized.getDataType()).isEqualTo(DataType.FLOAT32);
++        assertThat(quantized.getIntArray()).isEqualTo(new int[] {191, 159, 63, 127, 255, 0});
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java
+index 7f16c8e95628d..e8edb588c61c6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java
+@@ -18,7 +18,7 @@ package org.tensorflow.lite.support.image;
+ import static com.google.common.truth.Truth.assertThat;
+ 
+ import android.graphics.RectF;
+-import java.util.List;
++
+ import org.junit.Assert;
+ import org.junit.Before;
+ import org.junit.Test;
+@@ -28,213 +28,142 @@ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.image.BoundingBoxUtil.CoordinateType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.List;
++
+ /** Tests of {@link BoundingBoxUtil}. */
+ @RunWith(RobolectricTestRunner.class)
+ public class BoundingBoxUtilTest {
+-
+-  private TensorBuffer tensorBuffer;
+-
+-  @Before
+-  public void setUp() {
+-    // 2 bounding boxes with additional batch dimension.
+-    tensorBuffer = TensorBuffer.createFixedSize(new int[] {1, 2, 4}, DataType.FLOAT32);
+-  }
+-
+-  @Test
+-  public void convertDefaultRatioBoundaries() {
+-    tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.75f, 0.8f, 0.5f, 0.0f, 1.0f, 1.0f});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            -1,
+-            BoundingBoxUtil.Type.BOUNDARIES,
+-            CoordinateType.RATIO,
+-            500,
+-            400);
+-
+-    assertThat(boxList).hasSize(2);
+-    assertThat(boxList.get(0)).isEqualTo(new RectF(100, 100, 300, 400));
+-    assertThat(boxList.get(1)).isEqualTo(new RectF(200, 0, 400, 500));
+-  }
+-
+-  @Test
+-  public void convertComplexTensor() {
+-    tensorBuffer = TensorBuffer.createFixedSize(new int[] {3, 4, 2}, DataType.FLOAT32);
+-    tensorBuffer.loadArray(
+-        new float[] {
+-          // sub tensor 0
+-          0, 1, 10, 11, 20, 21, 30, 31,
+-          // sub tensor 1
+-          100, 101, 110, 111, 120, 121, 130, 131,
+-          // sub tensor 2
+-          200, 201, 210, 211, 220, 221, 230, 231
+-        });
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            1,
+-            BoundingBoxUtil.Type.BOUNDARIES,
+-            CoordinateType.PIXEL,
+-            0,
+-            0);
+-
+-    assertThat(boxList).hasSize(6);
+-    assertThat(boxList.get(0)).isEqualTo(new RectF(0, 10, 20, 30));
+-    assertThat(boxList.get(1)).isEqualTo(new RectF(1, 11, 21, 31));
+-    assertThat(boxList.get(2)).isEqualTo(new RectF(100, 110, 120, 130));
+-    assertThat(boxList.get(3)).isEqualTo(new RectF(101, 111, 121, 131));
+-  }
+-
+-  @Test
+-  public void convertIndexedRatioBoundaries() {
+-    tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.75f, 0.8f, 0.5f, 0.0f, 1.0f, 1.0f});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {1, 0, 3, 2},
+-            -1,
+-            BoundingBoxUtil.Type.BOUNDARIES,
+-            CoordinateType.RATIO,
+-            500,
+-            400);
+-
+-    assertThat(boxList).hasSize(2);
+-    assertThat(boxList.get(0)).isEqualTo(new RectF(80, 125, 320, 375));
+-    assertThat(boxList.get(1)).isEqualTo(new RectF(0, 250, 400, 500));
+-  }
+-
+-  @Test
+-  public void convertPixelBoundaries() {
+-    tensorBuffer.loadArray(new float[] {100, 100, 300, 400, 200, 0, 400, 500});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            -1,
+-            BoundingBoxUtil.Type.BOUNDARIES,
+-            CoordinateType.PIXEL,
+-            500,
+-            400);
+-
+-    assertThat(boxList)
+-        .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void convertRatioUpperLeft() {
+-    tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.5f, 0.6f, 0.5f, 0.0f, 0.5f, 1.0f});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            -1,
+-            BoundingBoxUtil.Type.UPPER_LEFT,
+-            CoordinateType.RATIO,
+-            500,
+-            400);
+-
+-    assertThat(boxList).hasSize(2);
+-    assertThat(boxList)
+-        .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void convertPixelUpperLeft() {
+-    tensorBuffer.loadArray(new float[] {100, 100, 200, 300, 200, 0, 200, 500});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            -1,
+-            BoundingBoxUtil.Type.UPPER_LEFT,
+-            CoordinateType.PIXEL,
+-            500,
+-            400);
+-
+-    assertThat(boxList)
+-        .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void convertRatioCenter() {
+-    tensorBuffer.loadArray(new float[] {0.5f, 0.5f, 0.5f, 0.6f, 0.75f, 0.5f, 0.5f, 1.0f});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            -1,
+-            BoundingBoxUtil.Type.CENTER,
+-            CoordinateType.RATIO,
+-            500,
+-            400);
+-
+-    assertThat(boxList)
+-        .containsExactly(new RectF(100, 99.99999f, 300, 400), new RectF(200, 0, 400, 500))
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void convertPixelCenter() {
+-    tensorBuffer.loadArray(new float[] {200, 250, 200, 300, 300, 250, 200, 500});
+-
+-    List<RectF> boxList =
+-        BoundingBoxUtil.convert(
+-            tensorBuffer,
+-            new int[] {0, 1, 2, 3},
+-            -1,
+-            BoundingBoxUtil.Type.CENTER,
+-            CoordinateType.PIXEL,
+-            500,
+-            400);
+-
+-    assertThat(boxList)
+-        .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+-        .inOrder();
+-  }
+-
+-  @Test
+-  public void convertTensorWithUnexpectedShapeShouldThrow() {
+-    TensorBuffer badShapeTensor = TensorBuffer.createFixedSize(new int[] {1, 5}, DataType.FLOAT32);
+-
+-    Assert.assertThrows(
+-        IllegalArgumentException.class,
+-        () ->
+-            BoundingBoxUtil.convert(
+-                badShapeTensor,
+-                new int[] {0, 1, 2, 3},
+-                -1,
+-                BoundingBoxUtil.Type.BOUNDARIES,
+-                CoordinateType.RATIO,
+-                300,
+-                400));
+-  }
+-
+-  @Test
+-  public void convertIntTensorShouldThrow() {
+-    TensorBuffer badTypeTensor = TensorBuffer.createFixedSize(new int[] {1, 4}, DataType.UINT8);
+-
+-    Assert.assertThrows(
+-        IllegalArgumentException.class,
+-        () ->
+-            BoundingBoxUtil.convert(
+-                badTypeTensor,
+-                new int[] {0, 1, 2, 3},
+-                -1,
+-                BoundingBoxUtil.Type.BOUNDARIES,
+-                CoordinateType.RATIO,
+-                300,
+-                400));
+-  }
++    private TensorBuffer tensorBuffer;
++
++    @Before
++    public void setUp() {
++        // 2 bounding boxes with additional batch dimension.
++        tensorBuffer = TensorBuffer.createFixedSize(new int[] {1, 2, 4}, DataType.FLOAT32);
++    }
++
++    @Test
++    public void convertDefaultRatioBoundaries() {
++        tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.75f, 0.8f, 0.5f, 0.0f, 1.0f, 1.0f});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
++                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 500, 400);
++
++        assertThat(boxList).hasSize(2);
++        assertThat(boxList.get(0)).isEqualTo(new RectF(100, 100, 300, 400));
++        assertThat(boxList.get(1)).isEqualTo(new RectF(200, 0, 400, 500));
++    }
++
++    @Test
++    public void convertComplexTensor() {
++        tensorBuffer = TensorBuffer.createFixedSize(new int[] {3, 4, 2}, DataType.FLOAT32);
++        tensorBuffer.loadArray(new float[] {// sub tensor 0
++                0, 1, 10, 11, 20, 21, 30, 31,
++                // sub tensor 1
++                100, 101, 110, 111, 120, 121, 130, 131,
++                // sub tensor 2
++                200, 201, 210, 211, 220, 221, 230, 231});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, 1,
++                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.PIXEL, 0, 0);
++
++        assertThat(boxList).hasSize(6);
++        assertThat(boxList.get(0)).isEqualTo(new RectF(0, 10, 20, 30));
++        assertThat(boxList.get(1)).isEqualTo(new RectF(1, 11, 21, 31));
++        assertThat(boxList.get(2)).isEqualTo(new RectF(100, 110, 120, 130));
++        assertThat(boxList.get(3)).isEqualTo(new RectF(101, 111, 121, 131));
++    }
++
++    @Test
++    public void convertIndexedRatioBoundaries() {
++        tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.75f, 0.8f, 0.5f, 0.0f, 1.0f, 1.0f});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {1, 0, 3, 2}, -1,
++                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 500, 400);
++
++        assertThat(boxList).hasSize(2);
++        assertThat(boxList.get(0)).isEqualTo(new RectF(80, 125, 320, 375));
++        assertThat(boxList.get(1)).isEqualTo(new RectF(0, 250, 400, 500));
++    }
++
++    @Test
++    public void convertPixelBoundaries() {
++        tensorBuffer.loadArray(new float[] {100, 100, 300, 400, 200, 0, 400, 500});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
++                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.PIXEL, 500, 400);
++
++        assertThat(boxList)
++                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
++                .inOrder();
++    }
++
++    @Test
++    public void convertRatioUpperLeft() {
++        tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.5f, 0.6f, 0.5f, 0.0f, 0.5f, 1.0f});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
++                BoundingBoxUtil.Type.UPPER_LEFT, CoordinateType.RATIO, 500, 400);
++
++        assertThat(boxList).hasSize(2);
++        assertThat(boxList)
++                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
++                .inOrder();
++    }
++
++    @Test
++    public void convertPixelUpperLeft() {
++        tensorBuffer.loadArray(new float[] {100, 100, 200, 300, 200, 0, 200, 500});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
++                BoundingBoxUtil.Type.UPPER_LEFT, CoordinateType.PIXEL, 500, 400);
++
++        assertThat(boxList)
++                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
++                .inOrder();
++    }
++
++    @Test
++    public void convertRatioCenter() {
++        tensorBuffer.loadArray(new float[] {0.5f, 0.5f, 0.5f, 0.6f, 0.75f, 0.5f, 0.5f, 1.0f});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
++                BoundingBoxUtil.Type.CENTER, CoordinateType.RATIO, 500, 400);
++
++        assertThat(boxList)
++                .containsExactly(new RectF(100, 99.99999f, 300, 400), new RectF(200, 0, 400, 500))
++                .inOrder();
++    }
++
++    @Test
++    public void convertPixelCenter() {
++        tensorBuffer.loadArray(new float[] {200, 250, 200, 300, 300, 250, 200, 500});
++
++        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
++                BoundingBoxUtil.Type.CENTER, CoordinateType.PIXEL, 500, 400);
++
++        assertThat(boxList)
++                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
++                .inOrder();
++    }
++
++    @Test
++    public void convertTensorWithUnexpectedShapeShouldThrow() {
++        TensorBuffer badShapeTensor =
++                TensorBuffer.createFixedSize(new int[] {1, 5}, DataType.FLOAT32);
++
++        Assert.assertThrows(IllegalArgumentException.class,
++                ()
++                        -> BoundingBoxUtil.convert(badShapeTensor, new int[] {0, 1, 2, 3}, -1,
++                                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 300, 400));
++    }
++
++    @Test
++    public void convertIntTensorShouldThrow() {
++        TensorBuffer badTypeTensor = TensorBuffer.createFixedSize(new int[] {1, 4}, DataType.UINT8);
++
++        Assert.assertThrows(IllegalArgumentException.class,
++                ()
++                        -> BoundingBoxUtil.convert(badTypeTensor, new int[] {0, 1, 2, 3}, -1,
++                                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 300, 400));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java
+index c41508308291a..329b5aa370744 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java
+@@ -15,10 +15,12 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleBitmap;
+ import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleTensorBuffer;
+ 
+ import android.graphics.Bitmap;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.junit.runners.JUnit4;
+@@ -27,22 +29,21 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ @RunWith(JUnit4.class)
+ public final class ColorSpaceTypeInstrumentedTest {
+-
+-  @Test
+-  public void convertTensorBufferToBitmapShouldSuccessWithGrayscaleWithUint8() {
+-    TensorBuffer buffer = createGrayscaleTensorBuffer(DataType.UINT8, false);
+-    Bitmap bitmap = ColorSpaceType.GRAYSCALE.convertTensorBufferToBitmap(buffer);
+-
+-    Bitmap expectedBitmap = createGrayscaleBitmap();
+-    assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-  }
+-
+-  @Test
+-  public void convertTensorBufferToBitmapShouldSuccessWithGrayscaleWithFloat() {
+-    TensorBuffer buffer = createGrayscaleTensorBuffer(DataType.FLOAT32, false);
+-    Bitmap bitmap = ColorSpaceType.GRAYSCALE.convertTensorBufferToBitmap(buffer);
+-
+-    Bitmap expectedBitmap = createGrayscaleBitmap();
+-    assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-  }
++    @Test
++    public void convertTensorBufferToBitmapShouldSuccessWithGrayscaleWithUint8() {
++        TensorBuffer buffer = createGrayscaleTensorBuffer(DataType.UINT8, false);
++        Bitmap bitmap = ColorSpaceType.GRAYSCALE.convertTensorBufferToBitmap(buffer);
++
++        Bitmap expectedBitmap = createGrayscaleBitmap();
++        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++    }
++
++    @Test
++    public void convertTensorBufferToBitmapShouldSuccessWithGrayscaleWithFloat() {
++        TensorBuffer buffer = createGrayscaleTensorBuffer(DataType.FLOAT32, false);
++        Bitmap bitmap = ColorSpaceType.GRAYSCALE.convertTensorBufferToBitmap(buffer);
++
++        Bitmap expectedBitmap = createGrayscaleBitmap();
++        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java
+index 46977fdb2bdfa..92612255269f6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.tensorflow.lite.support.image.TestImageCreator.createRgbBitmap;
+ import static org.tensorflow.lite.support.image.TestImageCreator.createRgbTensorBuffer;
+@@ -23,8 +24,7 @@ import static org.tensorflow.lite.support.image.TestImageCreator.createRgbTensor
+ import android.graphics.Bitmap;
+ import android.graphics.Bitmap.Config;
+ import android.graphics.ImageFormat;
+-import java.util.Arrays;
+-import java.util.Collection;
++
+ import org.junit.Rule;
+ import org.junit.Test;
+ import org.junit.rules.ErrorCollector;
+@@ -38,386 +38,353 @@ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.Arrays;
++import java.util.Collection;
++
+ /** Tests of {@link ImageConversions}. */
+ @RunWith(Suite.class)
+-@SuiteClasses({
+-  ColorSpaceTypeTest.ValidShapeTest.class,
+-  ColorSpaceTypeTest.InvalidShapeTest.class,
+-  ColorSpaceTypeTest.BitmapConfigTest.class,
+-  ColorSpaceTypeTest.ImageFormatTest.class,
+-  ColorSpaceTypeTest.YuvImageTest.class,
+-  ColorSpaceTypeTest.AssertNumElementsTest.class,
+-  ColorSpaceTypeTest.General.class
+-})
++@SuiteClasses({ColorSpaceTypeTest.ValidShapeTest.class, ColorSpaceTypeTest.InvalidShapeTest.class,
++        ColorSpaceTypeTest.BitmapConfigTest.class, ColorSpaceTypeTest.ImageFormatTest.class,
++        ColorSpaceTypeTest.YuvImageTest.class, ColorSpaceTypeTest.AssertNumElementsTest.class,
++        ColorSpaceTypeTest.General.class})
+ public class ColorSpaceTypeTest {
+-
+-  /** Parameterized tests for valid shapes. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class ValidShapeTest extends ColorSpaceTypeTest {
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    /** The shape that matches the colorSpaceType. */
+-    @Parameter(1)
+-    public int[] validShape;
+-
+-    /** The height of validShape. */
+-    @Parameter(2)
+-    public int expectedHeight;
+-
+-    /** The width of validShape. */
+-    @Parameter(3)
+-    public int expectedWidth;
+-
+-    @Parameters(name = "colorSpaceType={0}; validShape={1}; height={2}; width={3}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20, 3}, 10, 20},
+-            {ColorSpaceType.RGB, new int[] {10, 20, 3}, 10, 20},
+-            {ColorSpaceType.GRAYSCALE, new int[] {10, 20}, 10, 20},
+-            {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 1}, 10, 20},
+-          });
+-    }
+-
+-    @Test
+-    public void getHeightSucceedsWithValidShape() {
+-      assertThat(colorSpaceType.getHeight(validShape)).isEqualTo(expectedHeight);
++    /** Parameterized tests for valid shapes. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class ValidShapeTest extends ColorSpaceTypeTest {
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        /** The shape that matches the colorSpaceType. */
++        @Parameter(1)
++        public int[] validShape;
++
++        /** The height of validShape. */
++        @Parameter(2)
++        public int expectedHeight;
++
++        /** The width of validShape. */
++        @Parameter(3)
++        public int expectedWidth;
++
++        @Parameters(name = "colorSpaceType={0}; validShape={1}; height={2}; width={3}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 3}, 10, 20},
++                    {ColorSpaceType.RGB, new int[] {10, 20, 3}, 10, 20},
++                    {ColorSpaceType.GRAYSCALE, new int[] {10, 20}, 10, 20},
++                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 1}, 10, 20},
++            });
++        }
++
++        @Test
++        public void getHeightSucceedsWithValidShape() {
++            assertThat(colorSpaceType.getHeight(validShape)).isEqualTo(expectedHeight);
++        }
++
++        @Test
++        public void getWidthSucceedsWithValidShape() {
++            assertThat(colorSpaceType.getWidth(validShape)).isEqualTo(expectedWidth);
++        }
+     }
+ 
+-    @Test
+-    public void getWidthSucceedsWithValidShape() {
+-      assertThat(colorSpaceType.getWidth(validShape)).isEqualTo(expectedWidth);
+-    }
+-  }
+-
+-  /** Parameterized tests for invalid shapes. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class InvalidShapeTest extends ColorSpaceTypeTest {
+-
+-    private static final String RGB_ASSERT_SHAPE_MESSAGE =
+-        "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+-            + " representing R, G, B in order. The provided image shape is ";
+-    private static final String GRAYSCALE_ASSERT_SHAPE_MESSAGE =
+-        "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+-            + " shape is ";
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    /** The shape that does not match the colorSpaceType. */
+-    @Parameter(1)
+-    public int[] invalidShape;
+-
+-    @Parameter(2)
+-    public String errorMessage;
+-
+-    @Parameters(name = "colorSpaceType={0}; invalidShape={1}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.RGB, new int[] {2, 10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, -10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, -20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {-10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, -20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {2, 10, 20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 3}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {1, -10, 20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {1, 10, -20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {10, 20, 4}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {10}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {-10, 20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {10, -20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-          });
++    /** Parameterized tests for invalid shapes. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class InvalidShapeTest extends ColorSpaceTypeTest {
++        private static final String RGB_ASSERT_SHAPE_MESSAGE =
++                "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
++                + " representing R, G, B in order. The provided image shape is ";
++        private static final String GRAYSCALE_ASSERT_SHAPE_MESSAGE =
++                "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
++                + " shape is ";
++
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        /** The shape that does not match the colorSpaceType. */
++        @Parameter(1)
++        public int[] invalidShape;
++
++        @Parameter(2)
++        public String errorMessage;
++
++        @Parameters(name = "colorSpaceType={0}; invalidShape={1}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.RGB, new int[] {2, 10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, -10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, -20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {-10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, -20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {2, 10, 20},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 3},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {1, -10, 20},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, -20},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {10, 20, 4},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {10}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {-10, 20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {10, -20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++            });
++        }
++
++        @Test
++        public void assertShapeFaislsWithInvalidShape() {
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> colorSpaceType.assertShape(invalidShape));
++            assertThat(exception).hasMessageThat().contains(
++                    errorMessage + Arrays.toString(invalidShape));
++        }
++
++        @Test
++        public void getHeightFaislsWithInvalidShape() {
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> colorSpaceType.getHeight(invalidShape));
++            assertThat(exception).hasMessageThat().contains(
++                    errorMessage + Arrays.toString(invalidShape));
++        }
++
++        @Test
++        public void getWidthFaislsWithInvalidShape() {
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> colorSpaceType.getWidth(invalidShape));
++            assertThat(exception).hasMessageThat().contains(
++                    errorMessage + Arrays.toString(invalidShape));
++        }
+     }
+ 
+-    @Test
+-    public void assertShapeFaislsWithInvalidShape() {
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> colorSpaceType.assertShape(invalidShape));
+-      assertThat(exception).hasMessageThat().contains(errorMessage + Arrays.toString(invalidShape));
++    /** Parameterized tests for Bitmap Config. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class BitmapConfigTest extends ColorSpaceTypeTest {
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        /** The Bitmap configuration match the colorSpaceType. */
++        @Parameter(1)
++        public Config config;
++
++        @Parameters(name = "colorSpaceType={0}; config={1}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.RGB, Config.ARGB_8888},
++                    {ColorSpaceType.GRAYSCALE, Config.ALPHA_8},
++            });
++        }
++
++        @Test
++        public void fromBitmapConfigSucceedsWithSupportedConfig() {
++            assertThat(ColorSpaceType.fromBitmapConfig(config)).isEqualTo(colorSpaceType);
++        }
++
++        @Test
++        public void toBitmapConfigSucceedsWithSupportedConfig() {
++            assertThat(colorSpaceType.toBitmapConfig()).isEqualTo(config);
++        }
+     }
+ 
+-    @Test
+-    public void getHeightFaislsWithInvalidShape() {
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> colorSpaceType.getHeight(invalidShape));
+-      assertThat(exception).hasMessageThat().contains(errorMessage + Arrays.toString(invalidShape));
++    /** Parameterized tests for ImageFormat. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class ImageFormatTest extends ColorSpaceTypeTest {
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        /** The ImageFormat that matches the colorSpaceType. */
++        @Parameter(1)
++        public int imageFormat;
++
++        @Parameters(name = "colorSpaceType={0}; imageFormat={1}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.NV21, ImageFormat.NV21},
++                    {ColorSpaceType.YV12, ImageFormat.YV12},
++                    {ColorSpaceType.YUV_420_888, ImageFormat.YUV_420_888},
++            });
++        }
++
++        @Test
++        public void fromImageFormatSucceedsWithSupportedImageFormat() {
++            assertThat(ColorSpaceType.fromImageFormat(imageFormat)).isEqualTo(colorSpaceType);
++        }
+     }
+ 
+-    @Test
+-    public void getWidthFaislsWithInvalidShape() {
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> colorSpaceType.getWidth(invalidShape));
+-      assertThat(exception).hasMessageThat().contains(errorMessage + Arrays.toString(invalidShape));
+-    }
+-  }
+-
+-  /** Parameterized tests for Bitmap Config. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class BitmapConfigTest extends ColorSpaceTypeTest {
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    /** The Bitmap configuration match the colorSpaceType. */
+-    @Parameter(1)
+-    public Config config;
+-
+-    @Parameters(name = "colorSpaceType={0}; config={1}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.RGB, Config.ARGB_8888},
+-            {ColorSpaceType.GRAYSCALE, Config.ALPHA_8},
+-          });
++    /** Parameterized tests for YUV image formats: NV12, NV21, YV12, YV21, YUV_420_888. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class YuvImageTest extends ColorSpaceTypeTest {
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        @Parameters(name = "colorSpaceType={0}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.NV12},
++                    {ColorSpaceType.NV21},
++                    {ColorSpaceType.YV12},
++                    {ColorSpaceType.YV21},
++                    {ColorSpaceType.YUV_420_888},
++            });
++        }
++
++        @Test
++        public void convertTensorBufferToBitmapShouldFail() {
++            UnsupportedOperationException exception =
++                    assertThrows(UnsupportedOperationException.class,
++                            ()
++                                    -> colorSpaceType.convertTensorBufferToBitmap(
++                                            TensorBuffer.createDynamic(DataType.FLOAT32)));
++            assertThat(exception).hasMessageThat().contains(
++                    "convertTensorBufferToBitmap() is unsupported for the color space type "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void getWidthShouldFail() {
++            UnsupportedOperationException exception =
++                    assertThrows(UnsupportedOperationException.class,
++                            () -> colorSpaceType.getWidth(new int[] {}));
++            assertThat(exception).hasMessageThat().contains(
++                    "getWidth() only supports RGB and GRAYSCALE formats, but not "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void getHeightShouldFail() {
++            UnsupportedOperationException exception =
++                    assertThrows(UnsupportedOperationException.class,
++                            () -> colorSpaceType.getHeight(new int[] {}));
++            assertThat(exception).hasMessageThat().contains(
++                    "getHeight() only supports RGB and GRAYSCALE formats, but not "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void assertShapeShouldFail() {
++            UnsupportedOperationException exception =
++                    assertThrows(UnsupportedOperationException.class,
++                            () -> colorSpaceType.assertShape(new int[] {}));
++            assertThat(exception).hasMessageThat().contains(
++                    "assertShape() only supports RGB and GRAYSCALE formats, but not "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void getChannelValueShouldFail() {
++            UnsupportedOperationException exception = assertThrows(
++                    UnsupportedOperationException.class, () -> colorSpaceType.getChannelValue());
++            assertThat(exception).hasMessageThat().contains(
++                    "getChannelValue() is unsupported for the color space type "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void getNormalizedShapeShouldFail() {
++            UnsupportedOperationException exception =
++                    assertThrows(UnsupportedOperationException.class,
++                            () -> colorSpaceType.getNormalizedShape(new int[] {}));
++            assertThat(exception).hasMessageThat().contains(
++                    "getNormalizedShape() is unsupported for the color space type "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void getShapeInfoMessageShouldFail() {
++            UnsupportedOperationException exception =
++                    assertThrows(UnsupportedOperationException.class,
++                            () -> colorSpaceType.getShapeInfoMessage());
++            assertThat(exception).hasMessageThat().contains(
++                    "getShapeInfoMessage() is unsupported for the color space type "
++                    + colorSpaceType.name());
++        }
++
++        @Test
++        public void toBitmapConfigShouldFail() {
++            UnsupportedOperationException exception = assertThrows(
++                    UnsupportedOperationException.class, () -> colorSpaceType.toBitmapConfig());
++            assertThat(exception).hasMessageThat().contains(
++                    "toBitmapConfig() is unsupported for the color space type "
++                    + colorSpaceType.name());
++        }
+     }
+ 
+-    @Test
+-    public void fromBitmapConfigSucceedsWithSupportedConfig() {
+-      assertThat(ColorSpaceType.fromBitmapConfig(config)).isEqualTo(colorSpaceType);
+-    }
+-
+-    @Test
+-    public void toBitmapConfigSucceedsWithSupportedConfig() {
+-      assertThat(colorSpaceType.toBitmapConfig()).isEqualTo(config);
+-    }
+-  }
+-
+-  /** Parameterized tests for ImageFormat. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class ImageFormatTest extends ColorSpaceTypeTest {
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    /** The ImageFormat that matches the colorSpaceType. */
+-    @Parameter(1)
+-    public int imageFormat;
+-
+-    @Parameters(name = "colorSpaceType={0}; imageFormat={1}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.NV21, ImageFormat.NV21},
+-            {ColorSpaceType.YV12, ImageFormat.YV12},
+-            {ColorSpaceType.YUV_420_888, ImageFormat.YUV_420_888},
+-          });
+-    }
+-
+-    @Test
+-    public void fromImageFormatSucceedsWithSupportedImageFormat() {
+-      assertThat(ColorSpaceType.fromImageFormat(imageFormat)).isEqualTo(colorSpaceType);
+-    }
+-  }
+-
+-  /** Parameterized tests for YUV image formats: NV12, NV21, YV12, YV21, YUV_420_888. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class YuvImageTest extends ColorSpaceTypeTest {
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    @Parameters(name = "colorSpaceType={0}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.NV12},
+-            {ColorSpaceType.NV21},
+-            {ColorSpaceType.YV12},
+-            {ColorSpaceType.YV21},
+-            {ColorSpaceType.YUV_420_888},
+-          });
+-    }
+-
+-    @Test
+-    public void convertTensorBufferToBitmapShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(
+-              UnsupportedOperationException.class,
+-              () ->
+-                  colorSpaceType.convertTensorBufferToBitmap(
+-                      TensorBuffer.createDynamic(DataType.FLOAT32)));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "convertTensorBufferToBitmap() is unsupported for the color space type "
+-                  + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void getWidthShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(
+-              UnsupportedOperationException.class, () -> colorSpaceType.getWidth(new int[] {}));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "getWidth() only supports RGB and GRAYSCALE formats, but not "
+-                  + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void getHeightShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(
+-              UnsupportedOperationException.class, () -> colorSpaceType.getHeight(new int[] {}));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "getHeight() only supports RGB and GRAYSCALE formats, but not "
+-                  + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void assertShapeShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(
+-              UnsupportedOperationException.class, () -> colorSpaceType.assertShape(new int[] {}));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "assertShape() only supports RGB and GRAYSCALE formats, but not "
+-                  + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void getChannelValueShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(UnsupportedOperationException.class, () -> colorSpaceType.getChannelValue());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "getChannelValue() is unsupported for the color space type " + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void getNormalizedShapeShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(
+-              UnsupportedOperationException.class,
+-              () -> colorSpaceType.getNormalizedShape(new int[] {}));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "getNormalizedShape() is unsupported for the color space type "
+-                  + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void getShapeInfoMessageShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(
+-              UnsupportedOperationException.class, () -> colorSpaceType.getShapeInfoMessage());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "getShapeInfoMessage() is unsupported for the color space type "
+-                  + colorSpaceType.name());
+-    }
+-
+-    @Test
+-    public void toBitmapConfigShouldFail() {
+-      UnsupportedOperationException exception =
+-          assertThrows(UnsupportedOperationException.class, () -> colorSpaceType.toBitmapConfig());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "toBitmapConfig() is unsupported for the color space type " + colorSpaceType.name());
+-    }
+-  }
+-
+-  /** Parameterized tests for assertNumElements/getNumElements with all image formats. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class AssertNumElementsTest extends ColorSpaceTypeTest {
+-    private static final int HEIGHT = 2;
+-    private static final int WIDTH = 3;
+-    private static final int LESS_NUM_ELEMENTS = 5; // less than expected
+-    private static final int MORE_NUM_ELEMENTS = 20; // more than expected. OK.
+-    @Rule public ErrorCollector errorCollector = new ErrorCollector();
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    @Parameter(1)
+-    public int expectedNumElements;
+-
+-    @Parameters(name = "colorSpaceType={0};expectedNumElements={1}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.RGB, 18},
+-            {ColorSpaceType.GRAYSCALE, 6},
+-            {ColorSpaceType.NV12, 10},
+-            {ColorSpaceType.NV21, 10},
+-            {ColorSpaceType.YV12, 10},
+-            {ColorSpaceType.YV21, 10},
+-          });
+-    }
+-
+-    @Test
+-    public void getNumElementsShouldSucceedWithExpectedNumElements() {
+-      assertThat(colorSpaceType.getNumElements(HEIGHT, WIDTH)).isEqualTo(expectedNumElements);
+-    }
+-
+-    @Test
+-    public void assertNumElementsShouldSucceedWithMoreNumElements() {
+-      errorCollector.checkSucceeds(
+-          () -> {
+-            colorSpaceType.assertNumElements(MORE_NUM_ELEMENTS, HEIGHT, WIDTH);
+-            return null;
+-          });
+-    }
+-
+-    @Test
+-    public void assertNumElementsShouldFailWithLessNumElements() {
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> colorSpaceType.assertNumElements(LESS_NUM_ELEMENTS, HEIGHT, WIDTH));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              String.format(
+-                  "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
+-                      + " expected number of elements should be at least %d.",
+-                  LESS_NUM_ELEMENTS, colorSpaceType.name(), HEIGHT, WIDTH, expectedNumElements));
+-    }
+-  }
+-
+-  /** General tests of ColorSpaceTypeTest. */
+-  @RunWith(RobolectricTestRunner.class)
+-  public static final class General extends ColorSpaceTypeTest {
+-
+-    @Test
+-    public void convertTensorBufferToBitmapShouldSuccessWithRGB() {
+-      TensorBuffer buffer = createRgbTensorBuffer(DataType.UINT8, false);
+-      Bitmap bitmap = ColorSpaceType.RGB.convertTensorBufferToBitmap(buffer);
+-
+-      Bitmap expectedBitmap = createRgbBitmap();
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++    /** Parameterized tests for assertNumElements/getNumElements with all image formats. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class AssertNumElementsTest extends ColorSpaceTypeTest {
++        private static final int HEIGHT = 2;
++        private static final int WIDTH = 3;
++        private static final int LESS_NUM_ELEMENTS = 5; // less than expected
++        private static final int MORE_NUM_ELEMENTS = 20; // more than expected. OK.
++        @Rule
++        public ErrorCollector errorCollector = new ErrorCollector();
++
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        @Parameter(1)
++        public int expectedNumElements;
++
++        @Parameters(name = "colorSpaceType={0};expectedNumElements={1}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.RGB, 18},
++                    {ColorSpaceType.GRAYSCALE, 6},
++                    {ColorSpaceType.NV12, 10},
++                    {ColorSpaceType.NV21, 10},
++                    {ColorSpaceType.YV12, 10},
++                    {ColorSpaceType.YV21, 10},
++            });
++        }
++
++        @Test
++        public void getNumElementsShouldSucceedWithExpectedNumElements() {
++            assertThat(colorSpaceType.getNumElements(HEIGHT, WIDTH)).isEqualTo(expectedNumElements);
++        }
++
++        @Test
++        public void assertNumElementsShouldSucceedWithMoreNumElements() {
++            errorCollector.checkSucceeds(() -> {
++                colorSpaceType.assertNumElements(MORE_NUM_ELEMENTS, HEIGHT, WIDTH);
++                return null;
++            });
++        }
++
++        @Test
++        public void assertNumElementsShouldFailWithLessNumElements() {
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> colorSpaceType.assertNumElements(LESS_NUM_ELEMENTS, HEIGHT, WIDTH));
++            assertThat(exception).hasMessageThat().contains(String.format(
++                    "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
++                            + " expected number of elements should be at least %d.",
++                    LESS_NUM_ELEMENTS, colorSpaceType.name(), HEIGHT, WIDTH, expectedNumElements));
++        }
+     }
+ 
+-    @Test
+-    public void fromBitmapConfigFailsWithUnsupportedConfig() {
+-      Config unsupportedConfig = Config.ARGB_4444;
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> ColorSpaceType.fromBitmapConfig(unsupportedConfig));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("Bitmap configuration: " + unsupportedConfig + ", is not supported yet.");
++    /** General tests of ColorSpaceTypeTest. */
++    @RunWith(RobolectricTestRunner.class)
++    public static final class General extends ColorSpaceTypeTest {
++        @Test
++        public void convertTensorBufferToBitmapShouldSuccessWithRGB() {
++            TensorBuffer buffer = createRgbTensorBuffer(DataType.UINT8, false);
++            Bitmap bitmap = ColorSpaceType.RGB.convertTensorBufferToBitmap(buffer);
++
++            Bitmap expectedBitmap = createRgbBitmap();
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
++
++        @Test
++        public void fromBitmapConfigFailsWithUnsupportedConfig() {
++            Config unsupportedConfig = Config.ARGB_4444;
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> ColorSpaceType.fromBitmapConfig(unsupportedConfig));
++            assertThat(exception).hasMessageThat().contains(
++                    "Bitmap configuration: " + unsupportedConfig + ", is not supported yet.");
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java
+index 1a4d367bf0fe1..49efc4273911c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java
+@@ -21,7 +21,9 @@ import static android.graphics.Color.BLUE;
+ import static android.graphics.Color.GREEN;
+ import static android.graphics.Color.RED;
+ import static android.graphics.Color.WHITE;
++
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.tensorflow.lite.support.image.ImageConversions.convertGrayscaleTensorBufferToBitmap;
+ 
+@@ -30,10 +32,10 @@ import android.content.res.AssetManager;
+ import android.graphics.Bitmap;
+ import android.graphics.BitmapFactory;
+ import android.util.Log;
++
+ import androidx.test.core.app.ApplicationProvider;
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
+-import java.io.IOException;
+-import java.util.Arrays;
++
+ import org.junit.Assert;
+ import org.junit.Before;
+ import org.junit.Test;
+@@ -43,192 +45,190 @@ import org.junit.runners.Suite.SuiteClasses;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.io.IOException;
++import java.util.Arrays;
++
+ /** Instrumented unit test for {@link ImageConversions}. */
+ @RunWith(Suite.class)
+-@SuiteClasses({
+-  ImageConversionsInstrumentedTest.TensorBufferToBitmap.class,
+-  ImageConversionsInstrumentedTest.BitmapToTensorBuffer.class
+-})
++@SuiteClasses({ImageConversionsInstrumentedTest.TensorBufferToBitmap.class,
++        ImageConversionsInstrumentedTest.BitmapToTensorBuffer.class})
+ public class ImageConversionsInstrumentedTest {
++    /** Tests for the TensorBuffer data type and normalized form. */
++    // Note that parameterized test with android_library_instrumentation_tests is currently not
++    // supported internally.
++    @RunWith(AndroidJUnit4.class)
++    public static final class TensorBufferToBitmap extends ImageConversionsInstrumentedTest {
++        @Test
++        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithFloatNormalized() {
++            DataType dataType = DataType.FLOAT32;
++            boolean isNormalized = true;
++
++            TensorBuffer buffer =
++                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
++            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
++
++            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
+ 
+-  /** Tests for the TensorBuffer data type and normalized form. */
+-  // Note that parameterized test with android_library_instrumentation_tests is currently not
+-  // supported internally.
+-  @RunWith(AndroidJUnit4.class)
+-  public static final class TensorBufferToBitmap extends ImageConversionsInstrumentedTest {
+-
+-    @Test
+-    public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithFloatNormalized() {
+-      DataType dataType = DataType.FLOAT32;
+-      boolean isNormalized = true;
++        @Test
++        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithFloatUnnormalized() {
++            DataType dataType = DataType.FLOAT32;
++            boolean isNormalized = false;
+ 
+-      TensorBuffer buffer = TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+-      Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
++            TensorBuffer buffer =
++                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
++            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+ 
+-      Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-    }
+-
+-    @Test
+-    public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithFloatUnnormalized() {
+-      DataType dataType = DataType.FLOAT32;
+-      boolean isNormalized = false;
++            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
+ 
+-      TensorBuffer buffer = TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+-      Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
++        @Test
++        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithUint8Normalized() {
++            DataType dataType = DataType.UINT8;
++            boolean isNormalized = true;
+ 
+-      Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-    }
++            TensorBuffer buffer =
++                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
++            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+ 
+-    @Test
+-    public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithUint8Normalized() {
+-      DataType dataType = DataType.UINT8;
+-      boolean isNormalized = true;
+-
+-      TensorBuffer buffer = TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+-      Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
++            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
+ 
+-      Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-    }
++        @Test
++        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithUint8Unnormalized() {
++            DataType dataType = DataType.UINT8;
++            boolean isNormalized = false;
+ 
+-    @Test
+-    public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithUint8Unnormalized() {
+-      DataType dataType = DataType.UINT8;
+-      boolean isNormalized = false;
++            TensorBuffer buffer =
++                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
++            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+ 
+-      TensorBuffer buffer = TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+-      Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
++            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
+ 
+-      Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-    }
++        @Test
++        public void
++        convertGrayscaleTensorBufferToBitmapShouldRejectBufferWithInvalidShapeWithFloat() {
++            DataType dataType = DataType.FLOAT32;
++            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10}, dataType);
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> convertGrayscaleTensorBufferToBitmap(buffer));
++            assertThat(exception).hasMessageThat().contains(
++                    "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
++                    + " shape is " + Arrays.toString(buffer.getShape()));
++        }
+ 
+-    @Test
+-    public void convertGrayscaleTensorBufferToBitmapShouldRejectBufferWithInvalidShapeWithFloat() {
+-      DataType dataType = DataType.FLOAT32;
+-      TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10}, dataType);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> convertGrayscaleTensorBufferToBitmap(buffer));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+-                  + " shape is "
+-                  + Arrays.toString(buffer.getShape()));
++        @Test
++        public void
++        convertGrayscaleTensorBufferToBitmapShouldRejectBufferWithInvalidShapeWithUint8() {
++            DataType dataType = DataType.UINT8;
++            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10}, dataType);
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> convertGrayscaleTensorBufferToBitmap(buffer));
++            assertThat(exception).hasMessageThat().contains(
++                    "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
++                    + " shape is " + Arrays.toString(buffer.getShape()));
++        }
+     }
+ 
+-    @Test
+-    public void convertGrayscaleTensorBufferToBitmapShouldRejectBufferWithInvalidShapeWithUint8() {
+-      DataType dataType = DataType.UINT8;
+-      TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10}, dataType);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> convertGrayscaleTensorBufferToBitmap(buffer));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+-                  + " shape is "
+-                  + Arrays.toString(buffer.getShape()));
+-    }
+-  }
+-
+-  /** BitmapToTensorBuffer tests of ImageConversionsInstrumentedTest. */
+-  @RunWith(AndroidJUnit4.class)
+-  public static final class BitmapToTensorBuffer extends ImageConversionsInstrumentedTest {
+-
+-    private Bitmap greyGrid;
+-    private Bitmap colorGrid;
+-    private TensorBuffer buffer;
+-
+-    static final String GREY_GRID_PATH = "grey_grid.png";
+-    static final String COLOR_GRID_PATH = "color_grid.png";
+-
+-    @Before
+-    public void loadAssets() {
+-      Context context = ApplicationProvider.getApplicationContext();
+-      AssetManager assetManager = context.getAssets();
+-      try {
+-        greyGrid = BitmapFactory.decodeStream(assetManager.open(GREY_GRID_PATH));
+-        colorGrid = BitmapFactory.decodeStream(assetManager.open(COLOR_GRID_PATH));
+-      } catch (IOException e) {
+-        Log.e("Test", "Cannot load asset files");
+-      }
+-      Assert.assertEquals(ARGB_8888, greyGrid.getConfig());
+-      Assert.assertEquals(ARGB_8888, colorGrid.getConfig());
+-      buffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    }
++    /** BitmapToTensorBuffer tests of ImageConversionsInstrumentedTest. */
++    @RunWith(AndroidJUnit4.class)
++    public static final class BitmapToTensorBuffer extends ImageConversionsInstrumentedTest {
++        private Bitmap greyGrid;
++        private Bitmap colorGrid;
++        private TensorBuffer buffer;
++
++        static final String GREY_GRID_PATH = "grey_grid.png";
++        static final String COLOR_GRID_PATH = "color_grid.png";
++
++        @Before
++        public void loadAssets() {
++            Context context = ApplicationProvider.getApplicationContext();
++            AssetManager assetManager = context.getAssets();
++            try {
++                greyGrid = BitmapFactory.decodeStream(assetManager.open(GREY_GRID_PATH));
++                colorGrid = BitmapFactory.decodeStream(assetManager.open(COLOR_GRID_PATH));
++            } catch (IOException e) {
++                Log.e("Test", "Cannot load asset files");
++            }
++            Assert.assertEquals(ARGB_8888, greyGrid.getConfig());
++            Assert.assertEquals(ARGB_8888, colorGrid.getConfig());
++            buffer = TensorBuffer.createDynamic(DataType.UINT8);
++        }
+ 
+-    @Test
+-    public void testBitmapDimensionLayout() {
+-      // This test is not only for proving the correctness of bitmap -> TensorBuffer conversion, but
+-      // also for us to better understand how Android Bitmap is storing pixels - height first or
+-      // width first.
+-      // We use a black image which has a white corner to understand what happens. By setting up the
+-      // correct loop to pass the test, we can reveal the order of pixels returned from `getPixels`.
+-      // The result shows that Android stores bitmap in an h-first manner. The returned array of
+-      // `getPixels` is like [ 1st row, 2nd row, ... ] which is the same with TFLite.
+-      Assert.assertEquals(100, greyGrid.getWidth());
+-      Assert.assertEquals(100, greyGrid.getHeight());
+-      Assert.assertEquals(BLACK, greyGrid.getPixel(25, 25)); // left top
+-      Assert.assertEquals(BLACK, greyGrid.getPixel(75, 25)); // right top
+-      Assert.assertEquals(WHITE, greyGrid.getPixel(25, 75)); // left bottom
+-      Assert.assertEquals(BLACK, greyGrid.getPixel(75, 75)); // right bottom
+-
+-      ImageConversions.convertBitmapToTensorBuffer(greyGrid, buffer);
+-      Assert.assertArrayEquals(new int[] {100, 100, 3}, buffer.getShape());
+-      Assert.assertEquals(DataType.UINT8, buffer.getDataType());
+-
+-      int[] pixels = buffer.getIntArray();
+-      int index = 0;
+-      for (int h = 0; h < 100; h++) {
+-        for (int w = 0; w < 100; w++) {
+-          int expected = (w < 50 && h >= 50) ? 255 : 0;
+-          Assert.assertEquals(expected, pixels[index++]);
+-          Assert.assertEquals(expected, pixels[index++]);
+-          Assert.assertEquals(expected, pixels[index++]);
++        @Test
++        public void testBitmapDimensionLayout() {
++            // This test is not only for proving the correctness of bitmap -> TensorBuffer
++            // conversion, but also for us to better understand how Android Bitmap is storing pixels
++            // - height first or width first. We use a black image which has a white corner to
++            // understand what happens. By setting up the correct loop to pass the test, we can
++            // reveal the order of pixels returned from `getPixels`. The result shows that Android
++            // stores bitmap in an h-first manner. The returned array of `getPixels` is like [ 1st
++            // row, 2nd row, ... ] which is the same with TFLite.
++            Assert.assertEquals(100, greyGrid.getWidth());
++            Assert.assertEquals(100, greyGrid.getHeight());
++            Assert.assertEquals(BLACK, greyGrid.getPixel(25, 25)); // left top
++            Assert.assertEquals(BLACK, greyGrid.getPixel(75, 25)); // right top
++            Assert.assertEquals(WHITE, greyGrid.getPixel(25, 75)); // left bottom
++            Assert.assertEquals(BLACK, greyGrid.getPixel(75, 75)); // right bottom
++
++            ImageConversions.convertBitmapToTensorBuffer(greyGrid, buffer);
++            Assert.assertArrayEquals(new int[] {100, 100, 3}, buffer.getShape());
++            Assert.assertEquals(DataType.UINT8, buffer.getDataType());
++
++            int[] pixels = buffer.getIntArray();
++            int index = 0;
++            for (int h = 0; h < 100; h++) {
++                for (int w = 0; w < 100; w++) {
++                    int expected = (w < 50 && h >= 50) ? 255 : 0;
++                    Assert.assertEquals(expected, pixels[index++]);
++                    Assert.assertEquals(expected, pixels[index++]);
++                    Assert.assertEquals(expected, pixels[index++]);
++                }
++            }
+         }
+-      }
+-    }
+ 
+-    @Test
+-    public void testBitmapARGB8888ChannelLayout() {
+-      // This test is not only for proving the correctness of bitmap -> TensorBuffer conversion, but
+-      // also for us to better understand how Android Bitmap is storing pixels - RGB channel or
+-      // other possible ordering.
+-      // We use an colored grid image to understand what happens. It's a simple grid image with 4
+-      // grid in different colors. Passed through our Bitmap -> TensorBuffer conversion which simply
+-      // unpack channels from an integer returned from `getPixel`, its channel sequence could be
+-      // revealed directly.
+-      // The result shows that Android Bitmap has no magic when loading channels. If loading from
+-      // PNG images, channel order still remains R-G-B.
+-      Assert.assertEquals(100, colorGrid.getWidth());
+-      Assert.assertEquals(100, colorGrid.getHeight());
+-      Assert.assertEquals(BLUE, colorGrid.getPixel(25, 25)); // left top
+-      Assert.assertEquals(BLACK, colorGrid.getPixel(75, 25)); // right top
+-      Assert.assertEquals(GREEN, colorGrid.getPixel(25, 75)); // left bottom
+-      Assert.assertEquals(RED, colorGrid.getPixel(75, 75)); // right bottom
+-
+-      ImageConversions.convertBitmapToTensorBuffer(colorGrid, buffer);
+-      Assert.assertArrayEquals(new int[] {100, 100, 3}, buffer.getShape());
+-      Assert.assertEquals(DataType.UINT8, buffer.getDataType());
+-
+-      int[] pixels = buffer.getIntArray();
+-      Assert.assertArrayEquals(new int[] {0, 0, 255}, getChannels(pixels, 25, 25)); // left top
+-      Assert.assertArrayEquals(new int[] {0, 0, 0}, getChannels(pixels, 25, 75)); // right top
+-      Assert.assertArrayEquals(new int[] {0, 255, 0}, getChannels(pixels, 75, 25)); // left bottom
+-      Assert.assertArrayEquals(new int[] {255, 0, 0}, getChannels(pixels, 75, 75)); // right bottom
+-    }
++        @Test
++        public void testBitmapARGB8888ChannelLayout() {
++            // This test is not only for proving the correctness of bitmap -> TensorBuffer
++            // conversion, but also for us to better understand how Android Bitmap is storing pixels
++            // - RGB channel or other possible ordering. We use an colored grid image to understand
++            // what happens. It's a simple grid image with 4 grid in different colors. Passed
++            // through our Bitmap -> TensorBuffer conversion which simply unpack channels from an
++            // integer returned from `getPixel`, its channel sequence could be revealed directly.
++            // The result shows that Android Bitmap has no magic when loading channels. If loading
++            // from PNG images, channel order still remains R-G-B.
++            Assert.assertEquals(100, colorGrid.getWidth());
++            Assert.assertEquals(100, colorGrid.getHeight());
++            Assert.assertEquals(BLUE, colorGrid.getPixel(25, 25)); // left top
++            Assert.assertEquals(BLACK, colorGrid.getPixel(75, 25)); // right top
++            Assert.assertEquals(GREEN, colorGrid.getPixel(25, 75)); // left bottom
++            Assert.assertEquals(RED, colorGrid.getPixel(75, 75)); // right bottom
++
++            ImageConversions.convertBitmapToTensorBuffer(colorGrid, buffer);
++            Assert.assertArrayEquals(new int[] {100, 100, 3}, buffer.getShape());
++            Assert.assertEquals(DataType.UINT8, buffer.getDataType());
++
++            int[] pixels = buffer.getIntArray();
++            Assert.assertArrayEquals(
++                    new int[] {0, 0, 255}, getChannels(pixels, 25, 25)); // left top
++            Assert.assertArrayEquals(new int[] {0, 0, 0}, getChannels(pixels, 25, 75)); // right top
++            Assert.assertArrayEquals(
++                    new int[] {0, 255, 0}, getChannels(pixels, 75, 25)); // left bottom
++            Assert.assertArrayEquals(
++                    new int[] {255, 0, 0}, getChannels(pixels, 75, 75)); // right bottom
++        }
+ 
+-    /** Helper function only for {@link #testBitmapARGB8888ChannelLayout()}. */
+-    private static int[] getChannels(int[] pixels, int h, int w) {
+-      int id = (h * 100 + w) * 3;
+-      return new int[] {pixels[id++], pixels[id++], pixels[id]};
++        /** Helper function only for {@link #testBitmapARGB8888ChannelLayout()}. */
++        private static int[] getChannels(int[] pixels, int h, int w) {
++            int id = (h * 100 + w) * 3;
++            return new int[] {pixels[id++], pixels[id++], pixels[id]};
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java
+index b3300872c2357..c91db9d184f63 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java
+@@ -16,13 +16,13 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.tensorflow.lite.support.image.ImageConversions.convertBitmapToTensorBuffer;
+ import static org.tensorflow.lite.support.image.ImageConversions.convertRgbTensorBufferToBitmap;
+ 
+ import android.graphics.Bitmap;
+-import java.util.Arrays;
+-import java.util.Collection;
++
+ import org.junit.Assert;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -35,93 +35,93 @@ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.Arrays;
++import java.util.Collection;
++
+ /** Tests of {@link ImageConversions}. */
+ @RunWith(Suite.class)
+ @SuiteClasses({ImageConversionsTest.TensorBufferToBitmap.class, ImageConversionsTest.General.class})
+ public class ImageConversionsTest {
+-
+-  /** Parameterized tests for the TensorBuffer data type and normalized form. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class TensorBufferToBitmap extends ImageConversionsTest {
+-
+-    /** The data type that used to create the TensorBuffer. */
+-    @Parameter(0)
+-    public DataType dataType;
+-
+-    /** Indicates whether the shape is in the normalized form of (1, h, w, 3). */
+-    @Parameter(1)
+-    public boolean isNormalized;
+-
+-    @Parameters(name = "dataType={0}; isNormalized={1}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {DataType.FLOAT32, true}, {DataType.UINT8, true},
+-            {DataType.FLOAT32, false}, {DataType.UINT8, false},
+-          });
+-    }
+-
+-    @Test
+-    public void convertRgbTensorBufferToBitmapShouldSuccess() {
+-      TensorBuffer buffer = TestImageCreator.createRgbTensorBuffer(dataType, isNormalized);
+-      Bitmap bitmap = convertRgbTensorBufferToBitmap(buffer);
+-
+-      Bitmap expectedBitmap = TestImageCreator.createRgbBitmap();
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-    }
+-
+-    @Test
+-    public void convertRgbTensorBufferToBitmapShouldRejectBufferWithInvalidShape() {
+-      TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10, 3}, dataType);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> convertRgbTensorBufferToBitmap(buffer));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+-                  + " representing R, G, B in order. The provided image shape is "
+-                  + Arrays.toString(buffer.getShape()));
+-    }
+-  }
+-
+-  /** General tests of ImageConversionsTest. */
+-  @RunWith(RobolectricTestRunner.class)
+-  public static final class General extends ImageConversionsTest {
+-
+-    private static final Bitmap rgbBitmap = TestImageCreator.createRgbBitmap();
+-    private static final TensorBuffer rgbTensorBuffer =
+-        TestImageCreator.createRgbTensorBuffer(DataType.UINT8, false);
+-
+-    @Test
+-    public void convertBitmapToTensorBufferShouldSuccess() {
+-      TensorBuffer intBuffer = TensorBuffer.createFixedSize(new int[] {10, 10, 3}, DataType.UINT8);
+-      convertBitmapToTensorBuffer(rgbBitmap, intBuffer);
+-      assertThat(areEqualIntTensorBuffer(intBuffer, rgbTensorBuffer)).isTrue();
+-    }
+-
+-    @Test
+-    public void convertBitmapToTensorBufferShouldThrowShapeNotExactlySame() {
+-      TensorBuffer intBuffer = TensorBuffer.createFixedSize(new int[] {5, 20, 3}, DataType.UINT8);
+-      Assert.assertThrows(
+-          IllegalArgumentException.class, () -> convertBitmapToTensorBuffer(rgbBitmap, intBuffer));
++    /** Parameterized tests for the TensorBuffer data type and normalized form. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class TensorBufferToBitmap extends ImageConversionsTest {
++        /** The data type that used to create the TensorBuffer. */
++        @Parameter(0)
++        public DataType dataType;
++
++        /** Indicates whether the shape is in the normalized form of (1, h, w, 3). */
++        @Parameter(1)
++        public boolean isNormalized;
++
++        @Parameters(name = "dataType={0}; isNormalized={1}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {DataType.FLOAT32, true},
++                    {DataType.UINT8, true},
++                    {DataType.FLOAT32, false},
++                    {DataType.UINT8, false},
++            });
++        }
++
++        @Test
++        public void convertRgbTensorBufferToBitmapShouldSuccess() {
++            TensorBuffer buffer = TestImageCreator.createRgbTensorBuffer(dataType, isNormalized);
++            Bitmap bitmap = convertRgbTensorBufferToBitmap(buffer);
++
++            Bitmap expectedBitmap = TestImageCreator.createRgbBitmap();
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
++
++        @Test
++        public void convertRgbTensorBufferToBitmapShouldRejectBufferWithInvalidShape() {
++            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10, 3}, dataType);
++
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> convertRgbTensorBufferToBitmap(buffer));
++            assertThat(exception).hasMessageThat().contains(
++                    "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
++                    + " representing R, G, B in order. The provided image shape is "
++                    + Arrays.toString(buffer.getShape()));
++        }
+     }
+ 
+-    @Test
+-    public void convertBitmapToTensorBufferShouldCastIntToFloatIfNeeded() {
+-      TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-      convertBitmapToTensorBuffer(rgbBitmap, floatBuffer);
+-      assertThat(areEqualIntTensorBuffer(floatBuffer, rgbTensorBuffer)).isTrue();
++    /** General tests of ImageConversionsTest. */
++    @RunWith(RobolectricTestRunner.class)
++    public static final class General extends ImageConversionsTest {
++        private static final Bitmap rgbBitmap = TestImageCreator.createRgbBitmap();
++        private static final TensorBuffer rgbTensorBuffer =
++                TestImageCreator.createRgbTensorBuffer(DataType.UINT8, false);
++
++        @Test
++        public void convertBitmapToTensorBufferShouldSuccess() {
++            TensorBuffer intBuffer =
++                    TensorBuffer.createFixedSize(new int[] {10, 10, 3}, DataType.UINT8);
++            convertBitmapToTensorBuffer(rgbBitmap, intBuffer);
++            assertThat(areEqualIntTensorBuffer(intBuffer, rgbTensorBuffer)).isTrue();
++        }
++
++        @Test
++        public void convertBitmapToTensorBufferShouldThrowShapeNotExactlySame() {
++            TensorBuffer intBuffer =
++                    TensorBuffer.createFixedSize(new int[] {5, 20, 3}, DataType.UINT8);
++            Assert.assertThrows(IllegalArgumentException.class,
++                    () -> convertBitmapToTensorBuffer(rgbBitmap, intBuffer));
++        }
++
++        @Test
++        public void convertBitmapToTensorBufferShouldCastIntToFloatIfNeeded() {
++            TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++            convertBitmapToTensorBuffer(rgbBitmap, floatBuffer);
++            assertThat(areEqualIntTensorBuffer(floatBuffer, rgbTensorBuffer)).isTrue();
++        }
+     }
+-  }
+ 
+-  private static boolean areEqualIntTensorBuffer(TensorBuffer tb1, TensorBuffer tb2) {
+-    if (!Arrays.equals(tb1.getShape(), tb2.getShape())) {
+-      return false;
++    private static boolean areEqualIntTensorBuffer(TensorBuffer tb1, TensorBuffer tb2) {
++        if (!Arrays.equals(tb1.getShape(), tb2.getShape())) {
++            return false;
++        }
++        int[] arr1 = tb1.getIntArray();
++        int[] arr2 = tb2.getIntArray();
++        return Arrays.equals(arr1, arr2);
+     }
+-    int[] arr1 = tb1.getIntArray();
+-    int[] arr2 = tb2.getIntArray();
+-    return Arrays.equals(arr1, arr2);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java
+index 8ac27fdb07ad1..e9cbfc1dc50bd 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java
+@@ -16,10 +16,13 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.graphics.Bitmap;
++
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -30,120 +33,114 @@ import org.tensorflow.lite.support.image.ops.Rot90Op;
+ /** Instrumented unit test for {@link ImageProcessor}. */
+ @RunWith(AndroidJUnit4.class)
+ public final class ImageProcessorInstrumentedTest {
++    private Bitmap exampleBitmap;
++    private TensorImage input;
++    private ImageProcessor processor;
++
++    private static final int EXAMPLE_WIDTH = 10;
++    private static final int EXAMPLE_HEIGHT = 15;
++
++    @Before
++    public void setUp() {
++        // The default number of rotation is once.
++        processor = new ImageProcessor.Builder().add(new Rot90Op()).build();
++        exampleBitmap = createExampleBitmap();
++        input = new TensorImage(DataType.UINT8);
++        input.load(exampleBitmap);
++    }
++
++    @Test
++    public void updateNumberOfRotations_rotateTwice() {
++        int numberOfRotations = 2;
++
++        processor.updateNumberOfRotations(numberOfRotations);
++        TensorImage output = processor.process(input);
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertExampleBitmapWithTwoRotations(outputBitmap);
++    }
++
++    @Test
++    public void updateNumberOfRotationsWithOpIndex_rotateTwiceAndOpIndex0() {
++        int numberOfRotations = 2;
++        int occurrence = 0;
++
++        processor.updateNumberOfRotations(numberOfRotations, occurrence);
++        TensorImage output = processor.process(input);
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertExampleBitmapWithTwoRotations(outputBitmap);
++    }
++
++    @Test
++    public void updateNumberOfRotationsWithOpIndex_negativeOpIndex() {
++        int numberOfRotations = 2;
++        int negativeOpIndex = -1;
++
++        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
++                () -> processor.updateNumberOfRotations(numberOfRotations, negativeOpIndex));
++        assertThat(exception).hasMessageThat().isEqualTo("occurrence (-1) must not be negative");
++    }
++
++    @Test
++    public void updateNumberOfRotationsWithOpIndex_occurrenceEqualToTheNumberOfRot90Op() {
++        int numberOfRotations = 2;
++        int occurrence = 1;
++
++        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
++                () -> processor.updateNumberOfRotations(numberOfRotations, occurrence));
++        assertThat(exception).hasMessageThat().isEqualTo(
++                "occurrence (1) must be less than size (1)");
++    }
++
++    @Test
++    public void updateNumberOfRotationsWithOpIndex_noRot90OpIsAddedToImageProcessor() {
++        int numberOfRotations = 2;
++        int occurrence = 1;
++        // Add an op other than Rot90Op into ImageProcessor.
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new ResizeWithCropOrPadOp(5, 5)).build();
++
++        IllegalStateException exception = assertThrows(IllegalStateException.class,
++                () -> processor.updateNumberOfRotations(numberOfRotations, occurrence));
++        assertThat(exception).hasMessageThat().isEqualTo(
++                "The Rot90Op has not been added to the ImageProcessor.");
++    }
++
++    @Test
++    public void updateNumberOfRotationsWithOpIndex_twoRot90Ops() {
++        // The overall effect of the two rotations is equivalent to rotating for twice.
++        int numberOfRotations0 = 5;
++        int numberOfRotations1 = 1;
++
++        // Add two Rot90Ops into ImageProcessor.
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new Rot90Op()).add(new Rot90Op()).build();
++        processor.updateNumberOfRotations(numberOfRotations0, /*occurrence=*/0);
++        processor.updateNumberOfRotations(numberOfRotations1, /*occurrence=*/1);
++
++        TensorImage output = processor.process(input);
++        Bitmap outputBitmap = output.getBitmap();
++        assertExampleBitmapWithTwoRotations(outputBitmap);
++    }
+ 
+-  private Bitmap exampleBitmap;
+-  private TensorImage input;
+-  private ImageProcessor processor;
+-
+-  private static final int EXAMPLE_WIDTH = 10;
+-  private static final int EXAMPLE_HEIGHT = 15;
+-
+-  @Before
+-  public void setUp() {
+-    // The default number of rotation is once.
+-    processor = new ImageProcessor.Builder().add(new Rot90Op()).build();
+-    exampleBitmap = createExampleBitmap();
+-    input = new TensorImage(DataType.UINT8);
+-    input.load(exampleBitmap);
+-  }
+-
+-  @Test
+-  public void updateNumberOfRotations_rotateTwice() {
+-    int numberOfRotations = 2;
+-
+-    processor.updateNumberOfRotations(numberOfRotations);
+-    TensorImage output = processor.process(input);
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertExampleBitmapWithTwoRotations(outputBitmap);
+-  }
+-
+-  @Test
+-  public void updateNumberOfRotationsWithOpIndex_rotateTwiceAndOpIndex0() {
+-    int numberOfRotations = 2;
+-    int occurrence = 0;
+-
+-    processor.updateNumberOfRotations(numberOfRotations, occurrence);
+-    TensorImage output = processor.process(input);
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertExampleBitmapWithTwoRotations(outputBitmap);
+-  }
+-
+-  @Test
+-  public void updateNumberOfRotationsWithOpIndex_negativeOpIndex() {
+-    int numberOfRotations = 2;
+-    int negativeOpIndex = -1;
+-
+-    IndexOutOfBoundsException exception =
+-        assertThrows(
+-            IndexOutOfBoundsException.class,
+-            () -> processor.updateNumberOfRotations(numberOfRotations, negativeOpIndex));
+-    assertThat(exception).hasMessageThat().isEqualTo("occurrence (-1) must not be negative");
+-  }
+-
+-  @Test
+-  public void updateNumberOfRotationsWithOpIndex_occurrenceEqualToTheNumberOfRot90Op() {
+-    int numberOfRotations = 2;
+-    int occurrence = 1;
+-
+-    IndexOutOfBoundsException exception =
+-        assertThrows(
+-            IndexOutOfBoundsException.class,
+-            () -> processor.updateNumberOfRotations(numberOfRotations, occurrence));
+-    assertThat(exception).hasMessageThat().isEqualTo("occurrence (1) must be less than size (1)");
+-  }
+-
+-  @Test
+-  public void updateNumberOfRotationsWithOpIndex_noRot90OpIsAddedToImageProcessor() {
+-    int numberOfRotations = 2;
+-    int occurrence = 1;
+-    // Add an op other than Rot90Op into ImageProcessor.
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new ResizeWithCropOrPadOp(5, 5)).build();
+-
+-    IllegalStateException exception =
+-        assertThrows(
+-            IllegalStateException.class,
+-            () -> processor.updateNumberOfRotations(numberOfRotations, occurrence));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo("The Rot90Op has not been added to the ImageProcessor.");
+-  }
+-
+-  @Test
+-  public void updateNumberOfRotationsWithOpIndex_twoRot90Ops() {
+-    // The overall effect of the two rotations is equivalent to rotating for twice.
+-    int numberOfRotations0 = 5;
+-    int numberOfRotations1 = 1;
+-
+-    // Add two Rot90Ops into ImageProcessor.
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new Rot90Op()).add(new Rot90Op()).build();
+-    processor.updateNumberOfRotations(numberOfRotations0, /*occurrence=*/ 0);
+-    processor.updateNumberOfRotations(numberOfRotations1, /*occurrence=*/ 1);
+-
+-    TensorImage output = processor.process(input);
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertExampleBitmapWithTwoRotations(outputBitmap);
+-  }
+-
+-  private void assertExampleBitmapWithTwoRotations(Bitmap bitmapRotated) {
+-    assertThat(bitmapRotated.getWidth()).isEqualTo(EXAMPLE_WIDTH);
+-    assertThat(bitmapRotated.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
+-    for (int i = 0; i < exampleBitmap.getWidth(); i++) {
+-      for (int j = 0; j < exampleBitmap.getHeight(); j++) {
+-        assertThat(exampleBitmap.getPixel(i, j))
+-            .isEqualTo(bitmapRotated.getPixel(EXAMPLE_WIDTH - 1 - i, EXAMPLE_HEIGHT - 1 - j));
+-      }
++    private void assertExampleBitmapWithTwoRotations(Bitmap bitmapRotated) {
++        assertThat(bitmapRotated.getWidth()).isEqualTo(EXAMPLE_WIDTH);
++        assertThat(bitmapRotated.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
++        for (int i = 0; i < exampleBitmap.getWidth(); i++) {
++            for (int j = 0; j < exampleBitmap.getHeight(); j++) {
++                assertThat(exampleBitmap.getPixel(i, j))
++                        .isEqualTo(bitmapRotated.getPixel(
++                                EXAMPLE_WIDTH - 1 - i, EXAMPLE_HEIGHT - 1 - j));
++            }
++        }
+     }
+-  }
+ 
+-  private static Bitmap createExampleBitmap() {
+-    int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+-    for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+-      colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++    private static Bitmap createExampleBitmap() {
++        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
++        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
++            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++        }
++        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+     }
+-    return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java
+index a655f4a506900..a93ba5465125c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java
+@@ -16,10 +16,12 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.RectF;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+@@ -34,115 +36,112 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ /** Tests for {@link ImageProcessor}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class ImageProcessorTest {
++    private static final int EXAMPLE_WIDTH = 10;
++    private static final int EXAMPLE_HEIGHT = 15;
++    private static final int EXAMPLE_NUM_PIXELS = EXAMPLE_HEIGHT * EXAMPLE_WIDTH;
++    private static final int EXAMPLE_NUM_CHANNELS = 3;
++    private static final float MEAN = 127.5f;
++    private static final float STDDEV = 127.5f;
++
++    @Test
++    public void testBuild() {
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
++        assertThat(processor).isNotNull();
++    }
+ 
+-  private static final int EXAMPLE_WIDTH = 10;
+-  private static final int EXAMPLE_HEIGHT = 15;
+-  private static final int EXAMPLE_NUM_PIXELS = EXAMPLE_HEIGHT * EXAMPLE_WIDTH;
+-  private static final int EXAMPLE_NUM_CHANNELS = 3;
+-  private static final float MEAN = 127.5f;
+-  private static final float STDDEV = 127.5f;
+-
+-  @Test
+-  public void testBuild() {
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+-    assertThat(processor).isNotNull();
+-  }
+-
+-  @Test
+-  public void testNormalize() {
+-    TensorImage input = new TensorImage(DataType.FLOAT32);
+-    input.load(createExampleBitmap());
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+-    TensorImage output = processor.process(input);
+-
+-    float[] pixels = output.getTensorBuffer().getFloatArray();
+-    assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_CHANNELS * EXAMPLE_NUM_PIXELS);
+-    for (float p : pixels) {
+-      assertThat(p).isAtLeast(-1);
+-      assertThat(p).isAtMost(1);
++    @Test
++    public void testNormalize() {
++        TensorImage input = new TensorImage(DataType.FLOAT32);
++        input.load(createExampleBitmap());
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
++        TensorImage output = processor.process(input);
++
++        float[] pixels = output.getTensorBuffer().getFloatArray();
++        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_CHANNELS * EXAMPLE_NUM_PIXELS);
++        for (float p : pixels) {
++            assertThat(p).isAtLeast(-1);
++            assertThat(p).isAtMost(1);
++        }
+     }
+-  }
+-
+-  @Test
+-  public void testMultipleNormalize() {
+-    TensorImage input = new TensorImage(DataType.FLOAT32);
+-    input.load(createExampleBitmap());
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder()
+-            .add(new NormalizeOp(MEAN, STDDEV)) // [0, 255] -> [-1, 1]
+-            .add(new NormalizeOp(-1, 2)) // [-1, 1] -> [0, 1]
+-            .build();
+-    TensorImage output = processor.process(input);
+-
+-    float[] pixels = output.getTensorBuffer().getFloatArray();
+-    assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_CHANNELS * EXAMPLE_NUM_PIXELS);
+-    for (float p : pixels) {
+-      assertThat(p).isAtLeast(0);
+-      assertThat(p).isAtMost(1);
++
++    @Test
++    public void testMultipleNormalize() {
++        TensorImage input = new TensorImage(DataType.FLOAT32);
++        input.load(createExampleBitmap());
++        ImageProcessor processor =
++                new ImageProcessor.Builder()
++                        .add(new NormalizeOp(MEAN, STDDEV)) // [0, 255] -> [-1, 1]
++                        .add(new NormalizeOp(-1, 2)) // [-1, 1] -> [0, 1]
++                        .build();
++        TensorImage output = processor.process(input);
++
++        float[] pixels = output.getTensorBuffer().getFloatArray();
++        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_CHANNELS * EXAMPLE_NUM_PIXELS);
++        for (float p : pixels) {
++            assertThat(p).isAtLeast(0);
++            assertThat(p).isAtMost(1);
++        }
+     }
+-  }
+-
+-  @Test
+-  public void inverseTransformRectCorrectly() {
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder()
+-            .add(new ResizeOp(200, 300, ResizeMethod.BILINEAR))
+-            .add(new ResizeWithCropOrPadOp(100, 200))
+-            .add(new Rot90Op(1))
+-            .add(new NormalizeOp(127, 128))
+-            .build();
+-    RectF transformed = new RectF(0, 50, 100, 150);
+-    RectF original = processor.inverseTransform(transformed, 400, 600);
+-    assertThat(original.top).isEqualTo(100);
+-    assertThat(original.left).isEqualTo(200);
+-    assertThat(original.right).isEqualTo(400);
+-    assertThat(original.bottom).isEqualTo(300);
+-  }
+-
+-  @Test
+-  public void resizeShouldFailWithNonRgbImages() {
+-    int[] data = new int[] {1, 2, 3};
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    tensorBuffer.loadArray(data, new int[] {1, 3});
+-    TensorImage image = new TensorImage();
+-    image.load(tensorBuffer, ColorSpaceType.GRAYSCALE);
+-
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new ResizeOp(200, 300, ResizeMethod.BILINEAR)).build();
+-
+-    IllegalArgumentException exception =
+-        assertThrows(IllegalArgumentException.class, () -> processor.process(image));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .contains(
+-            "Only RGB images are supported in ResizeOp, but not "
++
++    @Test
++    public void inverseTransformRectCorrectly() {
++        ImageProcessor processor = new ImageProcessor.Builder()
++                                           .add(new ResizeOp(200, 300, ResizeMethod.BILINEAR))
++                                           .add(new ResizeWithCropOrPadOp(100, 200))
++                                           .add(new Rot90Op(1))
++                                           .add(new NormalizeOp(127, 128))
++                                           .build();
++        RectF transformed = new RectF(0, 50, 100, 150);
++        RectF original = processor.inverseTransform(transformed, 400, 600);
++        assertThat(original.top).isEqualTo(100);
++        assertThat(original.left).isEqualTo(200);
++        assertThat(original.right).isEqualTo(400);
++        assertThat(original.bottom).isEqualTo(300);
++    }
++
++    @Test
++    public void resizeShouldFailWithNonRgbImages() {
++        int[] data = new int[] {1, 2, 3};
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
++        tensorBuffer.loadArray(data, new int[] {1, 3});
++        TensorImage image = new TensorImage();
++        image.load(tensorBuffer, ColorSpaceType.GRAYSCALE);
++
++        ImageProcessor processor = new ImageProcessor.Builder()
++                                           .add(new ResizeOp(200, 300, ResizeMethod.BILINEAR))
++                                           .build();
++
++        IllegalArgumentException exception =
++                assertThrows(IllegalArgumentException.class, () -> processor.process(image));
++        assertThat(exception).hasMessageThat().contains(
++                "Only RGB images are supported in ResizeOp, but not "
+                 + image.getColorSpaceType().name());
+-  }
+-
+-  @Test
+-  public void normalizeShouldSuccessWithNonRgbImages() {
+-    int[] data = new int[] {1, 2, 3};
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    tensorBuffer.loadArray(data, new int[] {1, 3});
+-    TensorImage image = new TensorImage();
+-    image.load(tensorBuffer, ColorSpaceType.GRAYSCALE);
+-
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new NormalizeOp(0.5f, 1f)).build();
+-    TensorImage output = processor.process(image);
+-
+-    float[] pixels = output.getTensorBuffer().getFloatArray();
+-    assertThat(pixels).isEqualTo(new float[]{0.5f, 1.5f, 2.5f});
+-  }
+-
+-  private static Bitmap createExampleBitmap() {
+-    int[] colors = new int[EXAMPLE_NUM_PIXELS];
+-    for (int i = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+-      colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
+     }
+ 
+-    return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-  }
++    @Test
++    public void normalizeShouldSuccessWithNonRgbImages() {
++        int[] data = new int[] {1, 2, 3};
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
++        tensorBuffer.loadArray(data, new int[] {1, 3});
++        TensorImage image = new TensorImage();
++        image.load(tensorBuffer, ColorSpaceType.GRAYSCALE);
++
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new NormalizeOp(0.5f, 1f)).build();
++        TensorImage output = processor.process(image);
++
++        float[] pixels = output.getTensorBuffer().getFloatArray();
++        assertThat(pixels).isEqualTo(new float[] {0.5f, 1.5f, 2.5f});
++    }
++
++    private static Bitmap createExampleBitmap() {
++        int[] colors = new int[EXAMPLE_NUM_PIXELS];
++        for (int i = 0; i < EXAMPLE_NUM_PIXELS; i++) {
++            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++        }
++
++        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java
+index 7e61aa8d3ce58..e8caefcab8a04 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java
+@@ -16,20 +16,19 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.mockito.Mockito.when;
+ 
+ import android.graphics.Bitmap;
+ import android.media.Image;
++
+ import com.google.android.odml.image.BitmapMlImageBuilder;
+ import com.google.android.odml.image.ByteBufferMlImageBuilder;
+ import com.google.android.odml.image.MediaMlImageBuilder;
+ import com.google.android.odml.image.MlImage;
+ import com.google.android.odml.image.MlImage.ImageFormat;
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.util.Arrays;
+-import java.util.Collection;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -42,139 +41,141 @@ import org.robolectric.ParameterizedRobolectricTestRunner.Parameter;
+ import org.robolectric.ParameterizedRobolectricTestRunner.Parameters;
+ import org.robolectric.RobolectricTestRunner;
+ 
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.util.Arrays;
++import java.util.Collection;
++
+ /** Test for {@link MlImageAdapter}. */
+ @RunWith(Suite.class)
+ @SuiteClasses({
+-  MlImageAdapterTest.CreateTensorImageFromSupportedByteBufferMlImage.class,
+-  MlImageAdapterTest.CreateTensorImageFromUnsupportedByteBufferMlImage.class,
+-  MlImageAdapterTest.General.class,
++        MlImageAdapterTest.CreateTensorImageFromSupportedByteBufferMlImage.class,
++        MlImageAdapterTest.CreateTensorImageFromUnsupportedByteBufferMlImage.class,
++        MlImageAdapterTest.General.class,
+ })
+ public class MlImageAdapterTest {
+-
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class CreateTensorImageFromSupportedByteBufferMlImage
+-      extends MlImageAdapterTest {
+-
+-    @Parameter(0)
+-    @ImageFormat
+-    public int imageFormat;
+-
+-    @Parameter(1)
+-    public ColorSpaceType colorSpaceType;
+-
+-    @Parameters(name = "imageFormat={0}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {MlImage.IMAGE_FORMAT_RGB, ColorSpaceType.RGB},
+-            {MlImage.IMAGE_FORMAT_ALPHA, ColorSpaceType.GRAYSCALE},
+-            {MlImage.IMAGE_FORMAT_NV21, ColorSpaceType.NV21},
+-            {MlImage.IMAGE_FORMAT_NV12, ColorSpaceType.NV12},
+-            {MlImage.IMAGE_FORMAT_YV12, ColorSpaceType.YV12},
+-            {MlImage.IMAGE_FORMAT_YV21, ColorSpaceType.YV21},
+-          });
+-    }
+-
+-    @Test
+-    public void createTensorImageFrom_supportedByteBufferMlImage_succeeds() throws IOException {
+-      ByteBuffer buffer = ByteBuffer.allocateDirect(6).asReadOnlyBuffer();
+-      buffer.rewind();
+-      MlImage image = new ByteBufferMlImageBuilder(buffer, 1, 2, imageFormat).build();
+-
+-      TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+-
+-      assertThat(tensorImage.getWidth()).isEqualTo(1);
+-      assertThat(tensorImage.getHeight()).isEqualTo(2);
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(colorSpaceType);
+-      assertThat(tensorImage.getBuffer().position()).isEqualTo(0);
+-      assertThat(tensorImage.getBuffer()).isEquivalentAccordingToCompareTo(buffer);
+-    }
+-  }
+-
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class CreateTensorImageFromUnsupportedByteBufferMlImage
+-      extends MlImageAdapterTest {
+-    @Parameter(0)
+-    @ImageFormat
+-    public int imageFormat;
+-
+-    @Parameters(name = "imageFormat={0}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {MlImage.IMAGE_FORMAT_RGBA},
+-            {MlImage.IMAGE_FORMAT_JPEG},
+-            {MlImage.IMAGE_FORMAT_YUV_420_888},
+-            {MlImage.IMAGE_FORMAT_UNKNOWN},
+-          });
+-    }
+-
+-    @Test
+-    public void createTensorImageFrom_unsupportedByteBufferMlImage_throws() throws IOException {
+-      ByteBuffer buffer = ByteBuffer.allocateDirect(6).asReadOnlyBuffer();
+-      buffer.rewind();
+-      MlImage image = new ByteBufferMlImageBuilder(buffer, 1, 2, imageFormat).build();
+-
+-      assertThrows(
+-          IllegalArgumentException.class, () -> MlImageAdapter.createTensorImageFrom(image));
+-    }
+-  }
+-
+-  @RunWith(RobolectricTestRunner.class)
+-  public static final class General extends MlImageAdapterTest {
+-
+-    @Mock Image mediaImageMock;
+-
+-    @Before
+-    public void setUp() {
+-      MockitoAnnotations.openMocks(this);
+-    }
+-
+-    @Test
+-    public void createTensorImageFrom_bitmapMlImage_succeeds() throws IOException {
+-      Bitmap bitmap =
+-          Bitmap.createBitmap(new int[] {0xff000100, 0xff000001}, 1, 2, Bitmap.Config.ARGB_8888);
+-      MlImage image = new BitmapMlImageBuilder(bitmap).build();
+-      ByteBuffer expectedBuffer = ByteBuffer.allocateDirect(6);
+-      for (byte b : new byte[] {0, 1, 0, 0, 0, 1}) {
+-        expectedBuffer.put(b);
+-      }
+-      expectedBuffer.rewind();
+-
+-      TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+-
+-      assertThat(tensorImage.getWidth()).isEqualTo(1);
+-      assertThat(tensorImage.getHeight()).isEqualTo(2);
+-      assertThat(tensorImage.getBuffer().position()).isEqualTo(0);
+-      assertThat(tensorImage.getBuffer()).isEquivalentAccordingToCompareTo(expectedBuffer);
+-    }
+-
+-    @Test
+-    public void createTensorImageFrom_yuv420888MediaImageMlImage_succeeds() throws IOException {
+-      setUpMediaImageMock(mediaImageMock, android.graphics.ImageFormat.YUV_420_888, 1, 2);
+-      MlImage image = new MediaMlImageBuilder(mediaImageMock).build();
+-
+-      TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+-
+-      assertThat(tensorImage.getWidth()).isEqualTo(1);
+-      assertThat(tensorImage.getHeight()).isEqualTo(2);
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.YUV_420_888);
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class CreateTensorImageFromSupportedByteBufferMlImage
++            extends MlImageAdapterTest {
++        @Parameter(0)
++        @ImageFormat
++        public int imageFormat;
++
++        @Parameter(1)
++        public ColorSpaceType colorSpaceType;
++
++        @Parameters(name = "imageFormat={0}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {MlImage.IMAGE_FORMAT_RGB, ColorSpaceType.RGB},
++                    {MlImage.IMAGE_FORMAT_ALPHA, ColorSpaceType.GRAYSCALE},
++                    {MlImage.IMAGE_FORMAT_NV21, ColorSpaceType.NV21},
++                    {MlImage.IMAGE_FORMAT_NV12, ColorSpaceType.NV12},
++                    {MlImage.IMAGE_FORMAT_YV12, ColorSpaceType.YV12},
++                    {MlImage.IMAGE_FORMAT_YV21, ColorSpaceType.YV21},
++            });
++        }
++
++        @Test
++        public void createTensorImageFrom_supportedByteBufferMlImage_succeeds() throws IOException {
++            ByteBuffer buffer = ByteBuffer.allocateDirect(6).asReadOnlyBuffer();
++            buffer.rewind();
++            MlImage image = new ByteBufferMlImageBuilder(buffer, 1, 2, imageFormat).build();
++
++            TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
++
++            assertThat(tensorImage.getWidth()).isEqualTo(1);
++            assertThat(tensorImage.getHeight()).isEqualTo(2);
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(colorSpaceType);
++            assertThat(tensorImage.getBuffer().position()).isEqualTo(0);
++            assertThat(tensorImage.getBuffer()).isEquivalentAccordingToCompareTo(buffer);
++        }
+     }
+ 
+-    @Test
+-    public void createTensorImageFrom_nonYuv420888MediaImageMlImage_throws() throws IOException {
+-      setUpMediaImageMock(mediaImageMock, android.graphics.ImageFormat.YUV_422_888, 1, 2);
+-      MlImage image = new MediaMlImageBuilder(mediaImageMock).build();
+-
+-      assertThrows(
+-          IllegalArgumentException.class, () -> MlImageAdapter.createTensorImageFrom(image));
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class CreateTensorImageFromUnsupportedByteBufferMlImage
++            extends MlImageAdapterTest {
++        @Parameter(0)
++        @ImageFormat
++        public int imageFormat;
++
++        @Parameters(name = "imageFormat={0}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {MlImage.IMAGE_FORMAT_RGBA},
++                    {MlImage.IMAGE_FORMAT_JPEG},
++                    {MlImage.IMAGE_FORMAT_YUV_420_888},
++                    {MlImage.IMAGE_FORMAT_UNKNOWN},
++            });
++        }
++
++        @Test
++        public void createTensorImageFrom_unsupportedByteBufferMlImage_throws() throws IOException {
++            ByteBuffer buffer = ByteBuffer.allocateDirect(6).asReadOnlyBuffer();
++            buffer.rewind();
++            MlImage image = new ByteBufferMlImageBuilder(buffer, 1, 2, imageFormat).build();
++
++            assertThrows(IllegalArgumentException.class,
++                    () -> MlImageAdapter.createTensorImageFrom(image));
++        }
+     }
+ 
+-    private static void setUpMediaImageMock(
+-        Image mediaImageMock, int imageFormat, int width, int height) {
+-      when(mediaImageMock.getFormat()).thenReturn(imageFormat);
+-      when(mediaImageMock.getWidth()).thenReturn(width);
+-      when(mediaImageMock.getHeight()).thenReturn(height);
++    @RunWith(RobolectricTestRunner.class)
++    public static final class General extends MlImageAdapterTest {
++        @Mock
++        Image mediaImageMock;
++
++        @Before
++        public void setUp() {
++            MockitoAnnotations.openMocks(this);
++        }
++
++        @Test
++        public void createTensorImageFrom_bitmapMlImage_succeeds() throws IOException {
++            Bitmap bitmap = Bitmap.createBitmap(
++                    new int[] {0xff000100, 0xff000001}, 1, 2, Bitmap.Config.ARGB_8888);
++            MlImage image = new BitmapMlImageBuilder(bitmap).build();
++            ByteBuffer expectedBuffer = ByteBuffer.allocateDirect(6);
++            for (byte b : new byte[] {0, 1, 0, 0, 0, 1}) {
++                expectedBuffer.put(b);
++            }
++            expectedBuffer.rewind();
++
++            TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
++
++            assertThat(tensorImage.getWidth()).isEqualTo(1);
++            assertThat(tensorImage.getHeight()).isEqualTo(2);
++            assertThat(tensorImage.getBuffer().position()).isEqualTo(0);
++            assertThat(tensorImage.getBuffer()).isEquivalentAccordingToCompareTo(expectedBuffer);
++        }
++
++        @Test
++        public void createTensorImageFrom_yuv420888MediaImageMlImage_succeeds() throws IOException {
++            setUpMediaImageMock(mediaImageMock, android.graphics.ImageFormat.YUV_420_888, 1, 2);
++            MlImage image = new MediaMlImageBuilder(mediaImageMock).build();
++
++            TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
++
++            assertThat(tensorImage.getWidth()).isEqualTo(1);
++            assertThat(tensorImage.getHeight()).isEqualTo(2);
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.YUV_420_888);
++        }
++
++        @Test
++        public void createTensorImageFrom_nonYuv420888MediaImageMlImage_throws()
++                throws IOException {
++            setUpMediaImageMock(mediaImageMock, android.graphics.ImageFormat.YUV_422_888, 1, 2);
++            MlImage image = new MediaMlImageBuilder(mediaImageMock).build();
++
++            assertThrows(IllegalArgumentException.class,
++                    () -> MlImageAdapter.createTensorImageFrom(image));
++        }
++
++        private static void setUpMediaImageMock(
++                Image mediaImageMock, int imageFormat, int width, int height) {
++            when(mediaImageMock.getFormat()).thenReturn(imageFormat);
++            when(mediaImageMock.getWidth()).thenReturn(width);
++            when(mediaImageMock.getHeight()).thenReturn(height);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java
+index ca5f7dc7551be..83b54d0a8db78 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java
+@@ -15,6 +15,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.tensorflow.lite.DataType.FLOAT32;
+ import static org.tensorflow.lite.DataType.UINT8;
+ import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleBitmap;
+@@ -23,6 +24,7 @@ import static org.tensorflow.lite.support.image.TestImageCreator.createRgbBitmap
+ import static org.tensorflow.lite.support.image.TestImageCreator.createRgbTensorBuffer;
+ 
+ import android.graphics.Bitmap;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.junit.runners.JUnit4;
+@@ -31,110 +33,110 @@ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
+ @RunWith(JUnit4.class)
+ public final class TensorImageInstrumentedTest {
++    /**
++     * Difference between the pair of float and uint8 values. It is used to test the data
++     * conversion.
++     */
++    private static final float DELTA = 0.1f;
++
++    // Note that parameterized test with android_library_instrumentation_tests is currently not
++    // supported in internally.
++    @Test
++    public void loadAndGetBitmapSucceedsWithFloatBufferFloatImage() {
++        DataType tensorBufferDataType = FLOAT32;
++        DataType tensorImageDataType = FLOAT32;
++        boolean isNormalized = true;
++        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
++
++        TensorBuffer tensorBuffer =
++                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
++        TensorImage tensorImage = new TensorImage(tensorImageDataType);
++
++        tensorImage.load(tensorBuffer, colorSpaceType);
++        Bitmap bitmap = tensorImage.getBitmap();
++
++        Bitmap expectedBitmap = createBitmap(colorSpaceType);
++        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++    }
++
++    @Test
++    public void loadAndGetBitmapSucceedsWithFloatBufferUINT8Image() {
++        DataType tensorBufferDataType = FLOAT32;
++        DataType tensorImageDataType = UINT8;
++        boolean isNormalized = false;
++        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
++
++        TensorBuffer tensorBuffer =
++                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
++        TensorImage tensorImage = new TensorImage(tensorImageDataType);
+ 
+-  /**
+-   * Difference between the pair of float and uint8 values. It is used to test the data conversion.
+-   */
+-  private static final float DELTA = 0.1f;
+-
+-  // Note that parameterized test with android_library_instrumentation_tests is currently not
+-  // supported in internally.
+-  @Test
+-  public void loadAndGetBitmapSucceedsWithFloatBufferFloatImage() {
+-    DataType tensorBufferDataType = FLOAT32;
+-    DataType tensorImageDataType = FLOAT32;
+-    boolean isNormalized = true;
+-    ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+-
+-    TensorBuffer tensorBuffer =
+-        createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+-    TensorImage tensorImage = new TensorImage(tensorImageDataType);
+-
+-    tensorImage.load(tensorBuffer, colorSpaceType);
+-    Bitmap bitmap = tensorImage.getBitmap();
+-
+-    Bitmap expectedBitmap = createBitmap(colorSpaceType);
+-    assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-  }
+-
+-  @Test
+-  public void loadAndGetBitmapSucceedsWithFloatBufferUINT8Image() {
+-    DataType tensorBufferDataType = FLOAT32;
+-    DataType tensorImageDataType = UINT8;
+-    boolean isNormalized = false;
+-    ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+-
+-    TensorBuffer tensorBuffer =
+-        createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+-    TensorImage tensorImage = new TensorImage(tensorImageDataType);
+-
+-    tensorImage.load(tensorBuffer, colorSpaceType);
+-    Bitmap bitmap = tensorImage.getBitmap();
+-
+-    Bitmap expectedBitmap = createBitmap(colorSpaceType);
+-    assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-  }
+-
+-  @Test
+-  public void loadAndGetBitmapSucceedsWithUINT8BufferFloatImage() {
+-    DataType tensorBufferDataType = UINT8;
+-    DataType tensorImageDataType = FLOAT32;
+-    boolean isNormalized = true;
+-    ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+-
+-    TensorBuffer tensorBuffer =
+-        createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+-    TensorImage tensorImage = new TensorImage(tensorImageDataType);
+-
+-    tensorImage.load(tensorBuffer, colorSpaceType);
+-    Bitmap bitmap = tensorImage.getBitmap();
+-
+-    Bitmap expectedBitmap = createBitmap(colorSpaceType);
+-    assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-  }
+-
+-  @Test
+-  public void loadAndGetBitmapSucceedsWithUINT8BufferUINT8Image() {
+-    DataType tensorBufferDataType = UINT8;
+-    DataType tensorImageDataType = UINT8;
+-    boolean isNormalized = false;
+-    ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+-
+-    TensorBuffer tensorBuffer =
+-        createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+-    TensorImage tensorImage = new TensorImage(tensorImageDataType);
+-
+-    tensorImage.load(tensorBuffer, colorSpaceType);
+-    Bitmap bitmap = tensorImage.getBitmap();
+-
+-    Bitmap expectedBitmap = createBitmap(colorSpaceType);
+-    assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-  }
+-
+-  private static TensorBuffer createTensorBuffer(
+-      DataType dataType, boolean isNormalized, ColorSpaceType colorSpaceType, float delta) {
+-    switch (colorSpaceType) {
+-      case RGB:
+-        return createRgbTensorBuffer(dataType, isNormalized, delta);
+-      case GRAYSCALE:
+-        return createGrayscaleTensorBuffer(dataType, isNormalized, delta);
+-      default:
+-        break;
++        tensorImage.load(tensorBuffer, colorSpaceType);
++        Bitmap bitmap = tensorImage.getBitmap();
++
++        Bitmap expectedBitmap = createBitmap(colorSpaceType);
++        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+     }
+-    throw new IllegalArgumentException(
+-        "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+-  }
+-
+-  private static Bitmap createBitmap(ColorSpaceType colorSpaceType) {
+-    switch (colorSpaceType) {
+-      case RGB:
+-        return createRgbBitmap();
+-      case GRAYSCALE:
+-        return createGrayscaleBitmap();
+-      default:
+-        break;
++
++    @Test
++    public void loadAndGetBitmapSucceedsWithUINT8BufferFloatImage() {
++        DataType tensorBufferDataType = UINT8;
++        DataType tensorImageDataType = FLOAT32;
++        boolean isNormalized = true;
++        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
++
++        TensorBuffer tensorBuffer =
++                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
++        TensorImage tensorImage = new TensorImage(tensorImageDataType);
++
++        tensorImage.load(tensorBuffer, colorSpaceType);
++        Bitmap bitmap = tensorImage.getBitmap();
++
++        Bitmap expectedBitmap = createBitmap(colorSpaceType);
++        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++    }
++
++    @Test
++    public void loadAndGetBitmapSucceedsWithUINT8BufferUINT8Image() {
++        DataType tensorBufferDataType = UINT8;
++        DataType tensorImageDataType = UINT8;
++        boolean isNormalized = false;
++        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
++
++        TensorBuffer tensorBuffer =
++                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
++        TensorImage tensorImage = new TensorImage(tensorImageDataType);
++
++        tensorImage.load(tensorBuffer, colorSpaceType);
++        Bitmap bitmap = tensorImage.getBitmap();
++
++        Bitmap expectedBitmap = createBitmap(colorSpaceType);
++        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++    }
++
++    private static TensorBuffer createTensorBuffer(
++            DataType dataType, boolean isNormalized, ColorSpaceType colorSpaceType, float delta) {
++        switch (colorSpaceType) {
++            case RGB:
++                return createRgbTensorBuffer(dataType, isNormalized, delta);
++            case GRAYSCALE:
++                return createGrayscaleTensorBuffer(dataType, isNormalized, delta);
++            default:
++                break;
++        }
++        throw new IllegalArgumentException(
++                "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
++    }
++
++    private static Bitmap createBitmap(ColorSpaceType colorSpaceType) {
++        switch (colorSpaceType) {
++            case RGB:
++                return createRgbBitmap();
++            case GRAYSCALE:
++                return createGrayscaleBitmap();
++            default:
++                break;
++        }
++        throw new IllegalArgumentException(
++                "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+     }
+-    throw new IllegalArgumentException(
+-        "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java
+index f27edef4de779..b3130f4f2073c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertArrayEquals;
+ import static org.junit.Assert.assertThrows;
+ import static org.mockito.Mockito.when;
+@@ -31,9 +32,7 @@ import android.graphics.Bitmap.Config;
+ import android.graphics.Color;
+ import android.graphics.ImageFormat;
+ import android.media.Image;
+-import java.nio.ByteBuffer;
+-import java.util.Arrays;
+-import java.util.Collection;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -48,713 +47,689 @@ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.nio.ByteBuffer;
++import java.util.Arrays;
++import java.util.Collection;
++
+ /** Tests of {@link org.tensorflow.lite.support.image.TensorImage}. */
+ @RunWith(Suite.class)
+-@SuiteClasses({
+-  TensorImageTest.General.class,
+-  TensorImageTest.LoadTensorBufferWithRgbAndGrayscale.class,
+-  TensorImageTest.LoadTensorBufferWithInvalidShapeTest.class,
+-  TensorImageTest.LoadTensorBufferWithYUV.class,
+-  TensorImageTest.LoadTensorBufferWithImageProperties.class
+-})
++@SuiteClasses(
++        {TensorImageTest.General.class, TensorImageTest.LoadTensorBufferWithRgbAndGrayscale.class,
++                TensorImageTest.LoadTensorBufferWithInvalidShapeTest.class,
++                TensorImageTest.LoadTensorBufferWithYUV.class,
++                TensorImageTest.LoadTensorBufferWithImageProperties.class})
+ public class TensorImageTest {
+-
+-  @RunWith(RobolectricTestRunner.class)
+-  public static final class General extends TensorImageTest {
+-
+-    private static final Bitmap exampleBitmap = createExampleBitmap();
+-    private static final float[] exampleFloatPixels = createExampleFloatPixels();
+-    private static final int[] exampleUint8Pixels = createExampleUint8Pixels();
+-
+-    private static final int EXAMPLE_WIDTH = 5;
+-    private static final int EXAMPLE_HEIGHT = 10;
+-    private static final int EXAMPLE_NUM_PIXELS = EXAMPLE_HEIGHT * EXAMPLE_WIDTH;
+-    private static final int EXAMPLE_NUM_CHANNELS = 3;
+-    private static final int[] EXAMPLE_SHAPE = {
+-      EXAMPLE_HEIGHT, EXAMPLE_WIDTH, EXAMPLE_NUM_CHANNELS
+-    };
+-    private static final float MEAN = 127.5f;
+-    private static final float STDDEV = 127.5f;
+-
+-    @Mock Image imageMock;
+-
+-    @Before
+-    public void setUp() {
+-      MockitoAnnotations.initMocks(this);
+-    }
+-
+-    @Test
+-    public void defaultConstructorCreatesUint8TensorImage() {
+-      TensorImage image = new TensorImage();
+-      assertThat(image.getDataType()).isEqualTo(UINT8);
+-    }
+-
+-    @Test
+-    public void createFromSucceedsWithUint8TensorImage() {
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-      uint8Image.load(new int[] {1, 2, 3, 4, -5, 600}, new int[] {2, 1, 3});
+-
+-      TensorImage floatImage = TensorImage.createFrom(uint8Image, FLOAT32);
+-      float[] pixels = floatImage.getTensorBuffer().getFloatArray();
+-      assertThat(pixels).isEqualTo(new float[] {1.0f, 2.0f, 3.0f, 4.0f, 0.0f, 255.0f});
+-    }
+-
+-    @Test
+-    public void createFromSucceedsWithFloatTensorImage() {
+-      TensorImage floatImage = new TensorImage(FLOAT32);
+-      floatImage.load(new float[] {1, 2.495f, 3.5f, 4.5f, -5, 600}, new int[] {2, 1, 3});
+-
+-      TensorImage uint8Image = TensorImage.createFrom(floatImage, UINT8);
+-      int[] pixels = uint8Image.getTensorBuffer().getIntArray();
+-      assertThat(pixels).isEqualTo(new int[] {1, 2, 3, 4, 0, 255});
+-    }
+-
+-    @Test
+-    public void loadBitmapSucceedsWithUint8TensorImage() {
+-      Bitmap rgbBitmap = createRgbBitmap();
+-      TensorBuffer rgbTensorBuffer = createRgbTensorBuffer(UINT8, false, 0.0f);
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-
+-      uint8Image.load(rgbBitmap);
+-      assertThat(uint8Image.getBitmap().sameAs(rgbBitmap)).isTrue();
+-      assertEqualTensorBuffers(uint8Image.getTensorBuffer(), rgbTensorBuffer);
+-      assertThat(uint8Image.getDataType()).isEqualTo(UINT8);
+-    }
+-
+-    @Test
+-    public void loadBitmapSucceedsWithFloatTensorImage() {
+-      Bitmap rgbBitmap = createRgbBitmap();
+-      TensorBuffer rgbTensorBuffer = createRgbTensorBuffer(FLOAT32, false, 0.0f);
+-      TensorImage floatImage = new TensorImage(FLOAT32);
+-
+-      floatImage.load(rgbBitmap);
+-      assertThat(floatImage.getBitmap().sameAs(rgbBitmap)).isTrue();
+-      assertEqualTensorBuffers(floatImage.getTensorBuffer(), rgbTensorBuffer);
+-      assertThat(floatImage.getDataType()).isEqualTo(FLOAT32);
+-    }
+-
+-    @Test
+-    public void loadFloatArrayWithUint8TensorImage() {
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-
+-      uint8Image.load(exampleFloatPixels, EXAMPLE_SHAPE);
+-      assertThat(uint8Image.getBitmap()).isNotNull();
+-      assertThat(uint8Image.getTensorBuffer().getFloatArray())
+-          .isEqualTo(
+-              new float
+-                  [exampleFloatPixels
+-                      .length]); // All zero because of normalization and casting when loading.
+-    }
+-
+-    @Test
+-    public void loadFloatArrayWithFloatTensorImage() {
+-      TensorImage floatImage = new TensorImage(FLOAT32);
+-
+-      floatImage.load(exampleFloatPixels, EXAMPLE_SHAPE);
+-      assertThat(floatImage.getTensorBuffer().getFloatArray()).isEqualTo(exampleFloatPixels);
+-    }
+-
+-    @Test
+-    public void loadUint8ArrayWithUint8TensorImage() {
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-
+-      uint8Image.load(exampleUint8Pixels, EXAMPLE_SHAPE);
+-      assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
+-      assertThat(uint8Image.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
+-    }
+-
+-    @Test
+-    public void loadUint8ArrayWithFloatTensorImage() {
+-      TensorImage floatImage = new TensorImage(FLOAT32);
+-
+-      floatImage.load(exampleUint8Pixels, EXAMPLE_SHAPE);
+-      assertThat(floatImage.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
+-    }
+-
+-    @Test
+-    public void loadTensorBufferWithUint8TensorImage() {
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-
+-      uint8Image.load(exampleBitmap);
+-      TensorBuffer buffer = uint8Image.getTensorBuffer();
+-      uint8Image.load(buffer);
+-      assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
+-    }
+-
+-    @Test
+-    public void loadTensorBufferWithFloatTensorImage() {
+-      TensorImage floatImage = new TensorImage(FLOAT32);
+-
+-      floatImage.load(exampleBitmap);
+-      TensorBuffer buffer = floatImage.getTensorBuffer();
+-      floatImage.load(buffer);
+-      assertThat(floatImage.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
+-    }
+-
+-    @Test
+-    public void loadAndGetMediaImageSucceedsWithYuv420888Format() {
+-      setUpImageMock(imageMock, ImageFormat.YUV_420_888);
+-      TensorImage tensorImage = new TensorImage(UINT8);
+-
+-      tensorImage.load(imageMock);
+-      Image imageReturned = tensorImage.getMediaImage();
+-
+-      assertThat(imageReturned).isEqualTo(imageMock);
+-    }
+-
+-    @Test
+-    public void loadMediaImageFailsWithNonYuv420888Format() {
+-      setUpImageMock(imageMock, ImageFormat.YUV_422_888);
+-      TensorImage tensorImage = new TensorImage(UINT8);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> tensorImage.load(imageMock));
+-      assertThat(exception).hasMessageThat().contains("Only supports loading YUV_420_888 Image.");
+-    }
+-
+-    @Test
+-    public void getBitmapWithUint8TensorImage() {
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-
+-      uint8Image.load(exampleBitmap);
+-      assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
+-      // Also check zero copy is effective here (input and output are references of the same
+-      // object).
+-      assertThat(uint8Image.getBitmap()).isSameInstanceAs(exampleBitmap);
+-      // Also check we don't create new Bitmap only with reading operations.
+-      assertThat(uint8Image.getBuffer().limit())
+-          .isEqualTo(EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS);
+-      assertThat(uint8Image.getBitmap()).isSameInstanceAs(exampleBitmap);
+-
+-      uint8Image.load(exampleUint8Pixels, EXAMPLE_SHAPE);
+-      assertThat(uint8Image.getBitmap()).isNotSameInstanceAs(exampleBitmap);
+-    }
+-
+-    @Test
+-    public void getBitmapWithFloatTensorImage() {
+-      TensorImage floatImage = new TensorImage(FLOAT32);
+-
+-      floatImage.load(exampleBitmap);
+-      assertThat(floatImage.getBitmap()).isSameInstanceAs(exampleBitmap);
+-    }
+-
+-    @Test
+-    public void getBitmapWithEmptyTensorImage() {
+-      TensorImage uint8Image = new TensorImage(UINT8);
+-
+-      assertThrows(IllegalStateException.class, uint8Image::getBitmap);
+-    }
+-
+-    @Test
+-    public void getMediaImageFailsWithBackedBitmap() {
+-      TensorImage tensorImage = TensorImage.fromBitmap(exampleBitmap);
+-
+-      UnsupportedOperationException exception =
+-          assertThrows(UnsupportedOperationException.class, () -> tensorImage.getMediaImage());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("Converting from Bitmap to android.media.Image is unsupported.");
+-    }
+-
+-    @Test
+-    public void getMediaImageFailsWithBackedTensorBuffer() {
+-      TensorImage tensorImage = new TensorImage(UINT8);
+-      tensorImage.load(exampleFloatPixels, EXAMPLE_SHAPE);
+-
+-      UnsupportedOperationException exception =
+-          assertThrows(UnsupportedOperationException.class, () -> tensorImage.getMediaImage());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("Converting from TensorBuffer to android.media.Image is unsupported.");
+-    }
+-
+-    @Test
+-    public void getShapeOfInternalBitmapShouldSuccess() {
+-      Bitmap bitmap = Bitmap.createBitmap(300, 400, Config.ARGB_8888);
+-      TensorImage image = TensorImage.fromBitmap(bitmap);
+-
+-      int width = image.getWidth();
+-      int height = image.getHeight();
+-
+-      assertThat(width).isEqualTo(300);
+-      assertThat(height).isEqualTo(400);
+-    }
+-
+-    @Test
+-    public void getShapeOfInternalTensorBufferShouldSuccess() {
+-      TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {1, 400, 300, 3}, UINT8);
+-      TensorImage image = new TensorImage();
+-      image.load(buffer);
+-
+-      int width = image.getWidth();
+-      int height = image.getHeight();
+-
+-      assertThat(width).isEqualTo(300);
+-      assertThat(height).isEqualTo(400);
+-    }
+-
+-    @Test
+-    public void getShapeOfNullImageShouldThrow() {
+-      TensorImage image = new TensorImage();
+-
+-      assertThrows(IllegalStateException.class, image::getHeight);
+-    }
+-
+-    @Test
+-    public void getShapeOfACorruptedBufferShouldThrowRatherThanCrash() {
+-      int[] data = new int[] {1, 2, 3, 4, 5, 6};
+-      TensorBuffer buffer = TensorBuffer.createDynamic(UINT8);
+-      buffer.loadArray(data, new int[] {1, 1, 2, 3});
+-      TensorImage image = new TensorImage();
+-      image.load(buffer);
+-      // Reload data but with an invalid shape, which leads to `buffer` corrupted.
+-      int[] newData = new int[] {1, 2, 3};
+-      buffer.loadArray(newData, new int[] {1, 1, 1, 3});
+-
+-      assertThrows(IllegalArgumentException.class, image::getHeight);
+-    }
+-
+-    @Test
+-    public void getColorSpaceTypeSucceedsWithBitmapARGB_8888() {
+-      Bitmap rgbBitmap = createRgbBitmap();
+-      TensorImage tensorImage = TensorImage.fromBitmap(rgbBitmap);
+-
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+-    }
+-
+-    @Test
+-    public void getColorSpaceTypeSucceedsWithRgbTensorBuffer() {
+-      TensorBuffer rgbBuffer = createRgbTensorBuffer(UINT8, false);
+-      TensorImage tensorImage = new TensorImage();
+-      tensorImage.load(rgbBuffer);
+-
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+-    }
+-
+-    @Test
+-    public void getColorSpaceTypeSucceedsWithGrayscaleTensorBuffer() {
+-      TensorBuffer grayBuffer = createGrayscaleTensorBuffer(UINT8, false);
+-      TensorImage tensorImage = new TensorImage();
+-      tensorImage.load(grayBuffer, ColorSpaceType.GRAYSCALE);
+-
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
+-    }
+-
+-    @Test
+-    public void getColorSpaceTypeSucceedsWithRepeatedLoading() {
+-      TensorBuffer grayBuffer = createGrayscaleTensorBuffer(UINT8, false);
+-      TensorBuffer rgbBuffer = createRgbTensorBuffer(UINT8, false);
+-      Bitmap rgbBitmap = createRgbBitmap();
+-      TensorImage tensorImage = new TensorImage();
+-
+-      tensorImage.load(rgbBuffer);
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+-      tensorImage.load(grayBuffer, ColorSpaceType.GRAYSCALE);
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
+-      tensorImage.load(rgbBitmap);
+-      assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+-    }
+-
+-    @Test
+-    public void getColorSpaceTypeFailsWhenNoImageHasBeenLoaded() {
+-      TensorImage tensorImage = new TensorImage();
+-
+-      IllegalStateException exception =
+-          assertThrows(IllegalStateException.class, tensorImage::getColorSpaceType);
+-      assertThat(exception).hasMessageThat().contains("No image has been loaded yet.");
+-    }
+-
+-    /**
+-     * Creates an example bit map, which is a 10x10 ARGB bitmap and pixels are set by: pixel[i] =
+-     * {A: 0, B: i + 2, G: i + 1, G: i}, where i is the flatten index
+-     */
+-    private static Bitmap createExampleBitmap() {
+-      int[] colors = new int[EXAMPLE_NUM_PIXELS];
+-      for (int i = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+-        colors[i] = Color.rgb(i, i + 1, i + 2);
+-      }
+-
+-      return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-    }
+-
+-    private static float[] createExampleFloatPixels() {
+-      float[] pixels = new float[EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS];
+-      for (int i = 0, j = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+-        pixels[j++] = (i - MEAN) / STDDEV;
+-        pixels[j++] = (i + 1 - MEAN) / STDDEV;
+-        pixels[j++] = (i + 2 - MEAN) / STDDEV;
+-      }
+-      return pixels;
+-    }
+-
+-    private static int[] createExampleUint8Pixels() {
+-      int[] pixels = new int[EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS];
+-      for (int i = 0, j = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+-        pixels[j++] = i;
+-        pixels[j++] = i + 1;
+-        pixels[j++] = i + 2;
+-      }
+-      return pixels;
+-    }
+-  }
+-
+-  /** Parameterized tests for loading TensorBuffers with RGB and Grayscale images. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class LoadTensorBufferWithRgbAndGrayscale extends TensorImageTest {
+-
+-    /**
+-     * Difference between the pair of float and uint8 values. It is used to test the data
+-     * conversion.
+-     */
+-    private static final float DELTA = 0.1f;
+-
+-    /** The data type that used to create the TensorBuffer. */
+-    @Parameter(0)
+-    public DataType tensorBufferDataType;
+-
+-    /** Indicates whether the shape is in the normalized form of (1, h, w, 3). */
+-    @Parameter(1)
+-    public boolean isNormalized;
+-
+-    /** The color space type of the TensorBuffer. */
+-    @Parameter(2)
+-    public ColorSpaceType colorSpaceType;
+-
+-    /** The data type that used to create the TensorImage. */
+-    @Parameter(3)
+-    public DataType tensorImageDataType;
+-
+-    @Parameters(
+-        name =
+-            "tensorBufferDataType={0}; isNormalized={1}; colorSpaceType={2};"
+-                + " tensorImageDataType={3}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {FLOAT32, true, ColorSpaceType.RGB, FLOAT32},
+-            {FLOAT32, false, ColorSpaceType.RGB, UINT8},
+-            {UINT8, true, ColorSpaceType.RGB, FLOAT32},
+-            {UINT8, false, ColorSpaceType.RGB, UINT8},
+-          });
+-    }
+-
+-    @Test
+-    public void loadAndGetBitmapSucceedsWithTensorBufferAndColorSpaceType() {
+-      TensorBuffer tensorBuffer =
+-          createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+-      TensorImage tensorImage = new TensorImage(tensorImageDataType);
+-
+-      tensorImage.load(tensorBuffer, colorSpaceType);
+-      Bitmap bitmap = tensorImage.getBitmap();
+-
+-      Bitmap expectedBitmap = createBitmap(colorSpaceType);
+-      assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+-    }
+-
+-    @Test
+-    public void loadAndGetTensorBufferSucceedsWithTensorBufferAndColorSpaceType() {
+-      TensorBuffer tensorBuffer =
+-          createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+-      TensorImage tensorImage = new TensorImage(tensorImageDataType);
+-
+-      tensorImage.load(tensorBuffer, colorSpaceType);
+-      TensorBuffer buffer = tensorImage.getTensorBuffer();
+-
+-      // If tensorBufferDataType is UINT8, expectedTensorBuffer should not contain delta.
+-      float expectedResidual = tensorBufferDataType == UINT8 ? 0.f : DELTA;
+-      TensorBuffer expectedTensorBuffer =
+-          createTensorBuffer(tensorImageDataType, isNormalized, colorSpaceType, expectedResidual);
+-      assertEqualTensorBuffers(buffer, expectedTensorBuffer);
+-    }
+-
+-    private static TensorBuffer createTensorBuffer(
+-        DataType dataType, boolean isNormalized, ColorSpaceType colorSpaceType, float delta) {
+-      switch (colorSpaceType) {
+-        case RGB:
+-          return createRgbTensorBuffer(dataType, isNormalized, delta);
+-        case GRAYSCALE:
+-          return createGrayscaleTensorBuffer(dataType, isNormalized, delta);
+-        default:
+-          break;
+-      }
+-      throw new IllegalArgumentException(
+-          "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+-    }
+-
+-    private static Bitmap createBitmap(ColorSpaceType colorSpaceType) {
+-      switch (colorSpaceType) {
+-        case RGB:
+-          return createRgbBitmap();
+-        case GRAYSCALE:
+-          return createGrayscaleBitmap();
+-        default:
+-          break;
+-      }
+-      throw new IllegalArgumentException(
+-          "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+-    }
+-  }
+-
+-  /** Parameterized tests for loading TensorBuffers with YUV images. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class LoadTensorBufferWithYUV extends TensorImageTest {
+-
+-    private static final int HEIGHT = 2;
+-    private static final int WIDTH = 3;
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    @Parameters(name = "colorSpaceType={0}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.NV12},
+-            {ColorSpaceType.NV21},
+-            {ColorSpaceType.YV12},
+-            {ColorSpaceType.YV21},
+-          });
+-    }
+-
+-    @Test
+-    public void loadTensorBufferWithColorSpaceShouldFail() {
+-      TensorImage tensorImage = new TensorImage();
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> tensorImage.load(TensorBuffer.createDynamic(DataType.FLOAT32), colorSpaceType));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
+-                  + " `load(TensorBuffer, ImageProperties)` for other color space types.");
+-    }
+-
+-    @Test
+-    public void loadTensorBufferAndGetBitmapShouldFail() {
+-      int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-      tensorBuffer.loadArray(data, new int[] {data.length});
+-
+-      ImageProperties imageProperties =
+-          ImageProperties.builder()
+-              .setHeight(HEIGHT)
+-              .setWidth(WIDTH)
+-              .setColorSpaceType(colorSpaceType)
+-              .build();
+-
+-      TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+-      tensorImage.load(tensorBuffer, imageProperties);
+-
+-      UnsupportedOperationException exception =
+-          assertThrows(UnsupportedOperationException.class, () -> tensorImage.getBitmap());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "convertTensorBufferToBitmap() is unsupported for the color space type "
+-                  + colorSpaceType.name());
+-    }
+-  }
+-
+-  /** Parameterized tests for loading TensorBuffers with ImageProperties. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class LoadTensorBufferWithImageProperties extends TensorImageTest {
+-
+-    private static final int HEIGHT = 2;
+-    private static final int WIDTH = 3;
+-    private static final int WRONG_WIDTH = 10;
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    @Parameters(name = "colorSpaceType={0}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.RGB},
+-            {ColorSpaceType.GRAYSCALE},
+-            {ColorSpaceType.NV12},
+-            {ColorSpaceType.NV21},
+-            {ColorSpaceType.YV12},
+-            {ColorSpaceType.YV21},
+-          });
+-    }
+-
+-    @Test
+-    public void loadAndGetTensorBufferShouldSucceedWithCorrectProperties() {
+-      int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-      tensorBuffer.loadArray(data, new int[] {data.length});
+-
+-      ImageProperties imageProperties =
+-          ImageProperties.builder()
+-              .setHeight(HEIGHT)
+-              .setWidth(WIDTH)
+-              .setColorSpaceType(colorSpaceType)
+-              .build();
+-
+-      TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+-      tensorImage.load(tensorBuffer, imageProperties);
+-
+-      assertEqualTensorBuffers(tensorImage.getTensorBuffer(), tensorBuffer);
+-    }
+-
+-    @Test
+-    public void loadAndGetTensorBufferShouldSucceedWithLargerBuffer() {
+-      // Should allow buffer to be greater than the size specified by height and width.
+-      int moreElements = 1;
+-      int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH) + moreElements];
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-      tensorBuffer.loadArray(data, new int[] {data.length});
+-
+-      ImageProperties imageProperties =
+-          ImageProperties.builder()
+-              .setHeight(HEIGHT)
+-              .setWidth(WIDTH)
+-              .setColorSpaceType(colorSpaceType)
+-              .build();
+-
+-      TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+-      tensorImage.load(tensorBuffer, imageProperties);
+-
+-      assertEqualTensorBuffers(tensorImage.getTensorBuffer(), tensorBuffer);
+-    }
+-
+-    @Test
+-    public void loadAndGetByteBufferShouldSucceedWithCorrectProperties() {
+-      ByteBuffer byteBuffer = ByteBuffer.allocate(colorSpaceType.getNumElements(HEIGHT, WIDTH));
+-
+-      ImageProperties imageProperties =
+-          ImageProperties.builder()
+-              .setHeight(HEIGHT)
+-              .setWidth(WIDTH)
+-              .setColorSpaceType(colorSpaceType)
+-              .build();
+-
+-      TensorImage tensorImage = new TensorImage(DataType.UINT8);
+-      tensorImage.load(byteBuffer, imageProperties);
+-
+-      assertEqualByteBuffers(tensorImage.getBuffer(), byteBuffer);
+-    }
+-
+-    @Test
+-    public void loadTensorBufferWithShouldFailWithWrongImageShape() {
+-      int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-      tensorBuffer.loadArray(data, new int[] {data.length});
+-
+-      ImageProperties imageProperties =
+-          ImageProperties.builder()
+-              .setHeight(HEIGHT)
+-              .setWidth(WRONG_WIDTH)
+-              .setColorSpaceType(colorSpaceType)
+-              .build();
+-
+-      TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> tensorImage.load(tensorBuffer, imageProperties));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              String.format(
+-                  "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
+-                      + " expected number of elements should be at least %d.",
+-                  data.length,
+-                  colorSpaceType.name(),
+-                  HEIGHT,
+-                  WRONG_WIDTH,
+-                  colorSpaceType.getNumElements(HEIGHT, WRONG_WIDTH)));
+-    }
+-
+-    @Test
+-    public void getShapeOfInternalTensorBufferShouldSuccess() {
+-      int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-      tensorBuffer.loadArray(data, new int[] {data.length});
+-
+-      ImageProperties imageProperties =
+-          ImageProperties.builder()
+-              .setHeight(HEIGHT)
+-              .setWidth(WIDTH)
+-              .setColorSpaceType(colorSpaceType)
+-              .build();
+-
+-      TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+-      tensorImage.load(tensorBuffer, imageProperties);
+-
+-      assertThat(tensorImage.getWidth()).isEqualTo(WIDTH);
+-      assertThat(tensorImage.getHeight()).isEqualTo(HEIGHT);
+-    }
+-  }
+-
+-  /** Parameterized tests for loading TensorBuffer with invalid shapes. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class LoadTensorBufferWithInvalidShapeTest extends TensorImageTest {
+-
+-    private static final String RGB_ASSERT_SHAPE_MESSAGE =
+-        "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+-            + " representing R, G, B in order. The provided image shape is ";
+-    private static final String GRAYSCALE_ASSERT_SHAPE_MESSAGE =
+-        "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+-            + " shape is ";
+-
+-    @Parameter(0)
+-    public ColorSpaceType colorSpaceType;
+-
+-    /** The shape that does not match the colorSpaceType. */
+-    @Parameter(1)
+-    public int[] invalidShape;
+-
+-    @Parameter(2)
+-    public String errorMessage;
+-
+-    @Parameters(name = "colorSpaceType={0}; invalidShape={1}")
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {ColorSpaceType.RGB, new int[] {2, 10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {1, 10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.RGB, new int[] {10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {2, 10, 20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 3}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {10, 20, 4}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-            {ColorSpaceType.GRAYSCALE, new int[] {10}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+-          });
+-    }
+-
+-    @Test
+-    public void loadTensorBufferWithInvalidShape() {
+-      TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(invalidShape, UINT8);
+-      TensorImage tensorImage = new TensorImage();
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> tensorImage.load(tensorBuffer, colorSpaceType));
+-      assertThat(exception).hasMessageThat().contains(errorMessage + Arrays.toString(invalidShape));
++    @RunWith(RobolectricTestRunner.class)
++    public static final class General extends TensorImageTest {
++        private static final Bitmap exampleBitmap = createExampleBitmap();
++        private static final float[] exampleFloatPixels = createExampleFloatPixels();
++        private static final int[] exampleUint8Pixels = createExampleUint8Pixels();
++
++        private static final int EXAMPLE_WIDTH = 5;
++        private static final int EXAMPLE_HEIGHT = 10;
++        private static final int EXAMPLE_NUM_PIXELS = EXAMPLE_HEIGHT * EXAMPLE_WIDTH;
++        private static final int EXAMPLE_NUM_CHANNELS = 3;
++        private static final int[] EXAMPLE_SHAPE = {
++                EXAMPLE_HEIGHT, EXAMPLE_WIDTH, EXAMPLE_NUM_CHANNELS};
++        private static final float MEAN = 127.5f;
++        private static final float STDDEV = 127.5f;
++
++        @Mock
++        Image imageMock;
++
++        @Before
++        public void setUp() {
++            MockitoAnnotations.initMocks(this);
++        }
++
++        @Test
++        public void defaultConstructorCreatesUint8TensorImage() {
++            TensorImage image = new TensorImage();
++            assertThat(image.getDataType()).isEqualTo(UINT8);
++        }
++
++        @Test
++        public void createFromSucceedsWithUint8TensorImage() {
++            TensorImage uint8Image = new TensorImage(UINT8);
++            uint8Image.load(new int[] {1, 2, 3, 4, -5, 600}, new int[] {2, 1, 3});
++
++            TensorImage floatImage = TensorImage.createFrom(uint8Image, FLOAT32);
++            float[] pixels = floatImage.getTensorBuffer().getFloatArray();
++            assertThat(pixels).isEqualTo(new float[] {1.0f, 2.0f, 3.0f, 4.0f, 0.0f, 255.0f});
++        }
++
++        @Test
++        public void createFromSucceedsWithFloatTensorImage() {
++            TensorImage floatImage = new TensorImage(FLOAT32);
++            floatImage.load(new float[] {1, 2.495f, 3.5f, 4.5f, -5, 600}, new int[] {2, 1, 3});
++
++            TensorImage uint8Image = TensorImage.createFrom(floatImage, UINT8);
++            int[] pixels = uint8Image.getTensorBuffer().getIntArray();
++            assertThat(pixels).isEqualTo(new int[] {1, 2, 3, 4, 0, 255});
++        }
++
++        @Test
++        public void loadBitmapSucceedsWithUint8TensorImage() {
++            Bitmap rgbBitmap = createRgbBitmap();
++            TensorBuffer rgbTensorBuffer = createRgbTensorBuffer(UINT8, false, 0.0f);
++            TensorImage uint8Image = new TensorImage(UINT8);
++
++            uint8Image.load(rgbBitmap);
++            assertThat(uint8Image.getBitmap().sameAs(rgbBitmap)).isTrue();
++            assertEqualTensorBuffers(uint8Image.getTensorBuffer(), rgbTensorBuffer);
++            assertThat(uint8Image.getDataType()).isEqualTo(UINT8);
++        }
++
++        @Test
++        public void loadBitmapSucceedsWithFloatTensorImage() {
++            Bitmap rgbBitmap = createRgbBitmap();
++            TensorBuffer rgbTensorBuffer = createRgbTensorBuffer(FLOAT32, false, 0.0f);
++            TensorImage floatImage = new TensorImage(FLOAT32);
++
++            floatImage.load(rgbBitmap);
++            assertThat(floatImage.getBitmap().sameAs(rgbBitmap)).isTrue();
++            assertEqualTensorBuffers(floatImage.getTensorBuffer(), rgbTensorBuffer);
++            assertThat(floatImage.getDataType()).isEqualTo(FLOAT32);
++        }
++
++        @Test
++        public void loadFloatArrayWithUint8TensorImage() {
++            TensorImage uint8Image = new TensorImage(UINT8);
++
++            uint8Image.load(exampleFloatPixels, EXAMPLE_SHAPE);
++            assertThat(uint8Image.getBitmap()).isNotNull();
++            assertThat(uint8Image.getTensorBuffer().getFloatArray())
++                    .isEqualTo(new float[exampleFloatPixels.length]); // All zero because of
++                                                                      // normalization and casting
++                                                                      // when loading.
++        }
++
++        @Test
++        public void loadFloatArrayWithFloatTensorImage() {
++            TensorImage floatImage = new TensorImage(FLOAT32);
++
++            floatImage.load(exampleFloatPixels, EXAMPLE_SHAPE);
++            assertThat(floatImage.getTensorBuffer().getFloatArray()).isEqualTo(exampleFloatPixels);
++        }
++
++        @Test
++        public void loadUint8ArrayWithUint8TensorImage() {
++            TensorImage uint8Image = new TensorImage(UINT8);
++
++            uint8Image.load(exampleUint8Pixels, EXAMPLE_SHAPE);
++            assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
++            assertThat(uint8Image.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
++        }
++
++        @Test
++        public void loadUint8ArrayWithFloatTensorImage() {
++            TensorImage floatImage = new TensorImage(FLOAT32);
++
++            floatImage.load(exampleUint8Pixels, EXAMPLE_SHAPE);
++            assertThat(floatImage.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
++        }
++
++        @Test
++        public void loadTensorBufferWithUint8TensorImage() {
++            TensorImage uint8Image = new TensorImage(UINT8);
++
++            uint8Image.load(exampleBitmap);
++            TensorBuffer buffer = uint8Image.getTensorBuffer();
++            uint8Image.load(buffer);
++            assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
++        }
++
++        @Test
++        public void loadTensorBufferWithFloatTensorImage() {
++            TensorImage floatImage = new TensorImage(FLOAT32);
++
++            floatImage.load(exampleBitmap);
++            TensorBuffer buffer = floatImage.getTensorBuffer();
++            floatImage.load(buffer);
++            assertThat(floatImage.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
++        }
++
++        @Test
++        public void loadAndGetMediaImageSucceedsWithYuv420888Format() {
++            setUpImageMock(imageMock, ImageFormat.YUV_420_888);
++            TensorImage tensorImage = new TensorImage(UINT8);
++
++            tensorImage.load(imageMock);
++            Image imageReturned = tensorImage.getMediaImage();
++
++            assertThat(imageReturned).isEqualTo(imageMock);
++        }
++
++        @Test
++        public void loadMediaImageFailsWithNonYuv420888Format() {
++            setUpImageMock(imageMock, ImageFormat.YUV_422_888);
++            TensorImage tensorImage = new TensorImage(UINT8);
++
++            IllegalArgumentException exception =
++                    assertThrows(IllegalArgumentException.class, () -> tensorImage.load(imageMock));
++            assertThat(exception).hasMessageThat().contains(
++                    "Only supports loading YUV_420_888 Image.");
++        }
++
++        @Test
++        public void getBitmapWithUint8TensorImage() {
++            TensorImage uint8Image = new TensorImage(UINT8);
++
++            uint8Image.load(exampleBitmap);
++            assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
++            // Also check zero copy is effective here (input and output are references of the same
++            // object).
++            assertThat(uint8Image.getBitmap()).isSameInstanceAs(exampleBitmap);
++            // Also check we don't create new Bitmap only with reading operations.
++            assertThat(uint8Image.getBuffer().limit())
++                    .isEqualTo(EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS);
++            assertThat(uint8Image.getBitmap()).isSameInstanceAs(exampleBitmap);
++
++            uint8Image.load(exampleUint8Pixels, EXAMPLE_SHAPE);
++            assertThat(uint8Image.getBitmap()).isNotSameInstanceAs(exampleBitmap);
++        }
++
++        @Test
++        public void getBitmapWithFloatTensorImage() {
++            TensorImage floatImage = new TensorImage(FLOAT32);
++
++            floatImage.load(exampleBitmap);
++            assertThat(floatImage.getBitmap()).isSameInstanceAs(exampleBitmap);
++        }
++
++        @Test
++        public void getBitmapWithEmptyTensorImage() {
++            TensorImage uint8Image = new TensorImage(UINT8);
++
++            assertThrows(IllegalStateException.class, uint8Image::getBitmap);
++        }
++
++        @Test
++        public void getMediaImageFailsWithBackedBitmap() {
++            TensorImage tensorImage = TensorImage.fromBitmap(exampleBitmap);
++
++            UnsupportedOperationException exception = assertThrows(
++                    UnsupportedOperationException.class, () -> tensorImage.getMediaImage());
++            assertThat(exception).hasMessageThat().contains(
++                    "Converting from Bitmap to android.media.Image is unsupported.");
++        }
++
++        @Test
++        public void getMediaImageFailsWithBackedTensorBuffer() {
++            TensorImage tensorImage = new TensorImage(UINT8);
++            tensorImage.load(exampleFloatPixels, EXAMPLE_SHAPE);
++
++            UnsupportedOperationException exception = assertThrows(
++                    UnsupportedOperationException.class, () -> tensorImage.getMediaImage());
++            assertThat(exception).hasMessageThat().contains(
++                    "Converting from TensorBuffer to android.media.Image is unsupported.");
++        }
++
++        @Test
++        public void getShapeOfInternalBitmapShouldSuccess() {
++            Bitmap bitmap = Bitmap.createBitmap(300, 400, Config.ARGB_8888);
++            TensorImage image = TensorImage.fromBitmap(bitmap);
++
++            int width = image.getWidth();
++            int height = image.getHeight();
++
++            assertThat(width).isEqualTo(300);
++            assertThat(height).isEqualTo(400);
++        }
++
++        @Test
++        public void getShapeOfInternalTensorBufferShouldSuccess() {
++            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {1, 400, 300, 3}, UINT8);
++            TensorImage image = new TensorImage();
++            image.load(buffer);
++
++            int width = image.getWidth();
++            int height = image.getHeight();
++
++            assertThat(width).isEqualTo(300);
++            assertThat(height).isEqualTo(400);
++        }
++
++        @Test
++        public void getShapeOfNullImageShouldThrow() {
++            TensorImage image = new TensorImage();
++
++            assertThrows(IllegalStateException.class, image::getHeight);
++        }
++
++        @Test
++        public void getShapeOfACorruptedBufferShouldThrowRatherThanCrash() {
++            int[] data = new int[] {1, 2, 3, 4, 5, 6};
++            TensorBuffer buffer = TensorBuffer.createDynamic(UINT8);
++            buffer.loadArray(data, new int[] {1, 1, 2, 3});
++            TensorImage image = new TensorImage();
++            image.load(buffer);
++            // Reload data but with an invalid shape, which leads to `buffer` corrupted.
++            int[] newData = new int[] {1, 2, 3};
++            buffer.loadArray(newData, new int[] {1, 1, 1, 3});
++
++            assertThrows(IllegalArgumentException.class, image::getHeight);
++        }
++
++        @Test
++        public void getColorSpaceTypeSucceedsWithBitmapARGB_8888() {
++            Bitmap rgbBitmap = createRgbBitmap();
++            TensorImage tensorImage = TensorImage.fromBitmap(rgbBitmap);
++
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
++        }
++
++        @Test
++        public void getColorSpaceTypeSucceedsWithRgbTensorBuffer() {
++            TensorBuffer rgbBuffer = createRgbTensorBuffer(UINT8, false);
++            TensorImage tensorImage = new TensorImage();
++            tensorImage.load(rgbBuffer);
++
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
++        }
++
++        @Test
++        public void getColorSpaceTypeSucceedsWithGrayscaleTensorBuffer() {
++            TensorBuffer grayBuffer = createGrayscaleTensorBuffer(UINT8, false);
++            TensorImage tensorImage = new TensorImage();
++            tensorImage.load(grayBuffer, ColorSpaceType.GRAYSCALE);
++
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
++        }
++
++        @Test
++        public void getColorSpaceTypeSucceedsWithRepeatedLoading() {
++            TensorBuffer grayBuffer = createGrayscaleTensorBuffer(UINT8, false);
++            TensorBuffer rgbBuffer = createRgbTensorBuffer(UINT8, false);
++            Bitmap rgbBitmap = createRgbBitmap();
++            TensorImage tensorImage = new TensorImage();
++
++            tensorImage.load(rgbBuffer);
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
++            tensorImage.load(grayBuffer, ColorSpaceType.GRAYSCALE);
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
++            tensorImage.load(rgbBitmap);
++            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
++        }
++
++        @Test
++        public void getColorSpaceTypeFailsWhenNoImageHasBeenLoaded() {
++            TensorImage tensorImage = new TensorImage();
++
++            IllegalStateException exception =
++                    assertThrows(IllegalStateException.class, tensorImage::getColorSpaceType);
++            assertThat(exception).hasMessageThat().contains("No image has been loaded yet.");
++        }
++
++        /**
++         * Creates an example bit map, which is a 10x10 ARGB bitmap and pixels are set by: pixel[i]
++         * = {A: 0, B: i + 2, G: i + 1, G: i}, where i is the flatten index
++         */
++        private static Bitmap createExampleBitmap() {
++            int[] colors = new int[EXAMPLE_NUM_PIXELS];
++            for (int i = 0; i < EXAMPLE_NUM_PIXELS; i++) {
++                colors[i] = Color.rgb(i, i + 1, i + 2);
++            }
++
++            return Bitmap.createBitmap(
++                    colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
++        }
++
++        private static float[] createExampleFloatPixels() {
++            float[] pixels = new float[EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS];
++            for (int i = 0, j = 0; i < EXAMPLE_NUM_PIXELS; i++) {
++                pixels[j++] = (i - MEAN) / STDDEV;
++                pixels[j++] = (i + 1 - MEAN) / STDDEV;
++                pixels[j++] = (i + 2 - MEAN) / STDDEV;
++            }
++            return pixels;
++        }
++
++        private static int[] createExampleUint8Pixels() {
++            int[] pixels = new int[EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS];
++            for (int i = 0, j = 0; i < EXAMPLE_NUM_PIXELS; i++) {
++                pixels[j++] = i;
++                pixels[j++] = i + 1;
++                pixels[j++] = i + 2;
++            }
++            return pixels;
++        }
++    }
++
++    /** Parameterized tests for loading TensorBuffers with RGB and Grayscale images. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class LoadTensorBufferWithRgbAndGrayscale extends TensorImageTest {
++        /**
++         * Difference between the pair of float and uint8 values. It is used to test the data
++         * conversion.
++         */
++        private static final float DELTA = 0.1f;
++
++        /** The data type that used to create the TensorBuffer. */
++        @Parameter(0)
++        public DataType tensorBufferDataType;
++
++        /** Indicates whether the shape is in the normalized form of (1, h, w, 3). */
++        @Parameter(1)
++        public boolean isNormalized;
++
++        /** The color space type of the TensorBuffer. */
++        @Parameter(2)
++        public ColorSpaceType colorSpaceType;
++
++        /** The data type that used to create the TensorImage. */
++        @Parameter(3)
++        public DataType tensorImageDataType;
++
++        @Parameters(name = "tensorBufferDataType={0}; isNormalized={1}; colorSpaceType={2};"
++                        + " tensorImageDataType={3}")
++        public static Collection<Object[]>
++        data() {
++            return Arrays.asList(new Object[][] {
++                    {FLOAT32, true, ColorSpaceType.RGB, FLOAT32},
++                    {FLOAT32, false, ColorSpaceType.RGB, UINT8},
++                    {UINT8, true, ColorSpaceType.RGB, FLOAT32},
++                    {UINT8, false, ColorSpaceType.RGB, UINT8},
++            });
++        }
++
++        @Test
++        public void loadAndGetBitmapSucceedsWithTensorBufferAndColorSpaceType() {
++            TensorBuffer tensorBuffer =
++                    createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
++            TensorImage tensorImage = new TensorImage(tensorImageDataType);
++
++            tensorImage.load(tensorBuffer, colorSpaceType);
++            Bitmap bitmap = tensorImage.getBitmap();
++
++            Bitmap expectedBitmap = createBitmap(colorSpaceType);
++            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
++        }
++
++        @Test
++        public void loadAndGetTensorBufferSucceedsWithTensorBufferAndColorSpaceType() {
++            TensorBuffer tensorBuffer =
++                    createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
++            TensorImage tensorImage = new TensorImage(tensorImageDataType);
++
++            tensorImage.load(tensorBuffer, colorSpaceType);
++            TensorBuffer buffer = tensorImage.getTensorBuffer();
++
++            // If tensorBufferDataType is UINT8, expectedTensorBuffer should not contain delta.
++            float expectedResidual = tensorBufferDataType == UINT8 ? 0.f : DELTA;
++            TensorBuffer expectedTensorBuffer = createTensorBuffer(
++                    tensorImageDataType, isNormalized, colorSpaceType, expectedResidual);
++            assertEqualTensorBuffers(buffer, expectedTensorBuffer);
++        }
++
++        private static TensorBuffer createTensorBuffer(DataType dataType, boolean isNormalized,
++                ColorSpaceType colorSpaceType, float delta) {
++            switch (colorSpaceType) {
++                case RGB:
++                    return createRgbTensorBuffer(dataType, isNormalized, delta);
++                case GRAYSCALE:
++                    return createGrayscaleTensorBuffer(dataType, isNormalized, delta);
++                default:
++                    break;
++            }
++            throw new IllegalArgumentException(
++                    "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
++        }
++
++        private static Bitmap createBitmap(ColorSpaceType colorSpaceType) {
++            switch (colorSpaceType) {
++                case RGB:
++                    return createRgbBitmap();
++                case GRAYSCALE:
++                    return createGrayscaleBitmap();
++                default:
++                    break;
++            }
++            throw new IllegalArgumentException(
++                    "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
++        }
++    }
++
++    /** Parameterized tests for loading TensorBuffers with YUV images. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class LoadTensorBufferWithYUV extends TensorImageTest {
++        private static final int HEIGHT = 2;
++        private static final int WIDTH = 3;
++
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        @Parameters(name = "colorSpaceType={0}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.NV12},
++                    {ColorSpaceType.NV21},
++                    {ColorSpaceType.YV12},
++                    {ColorSpaceType.YV21},
++            });
++        }
++
++        @Test
++        public void loadTensorBufferWithColorSpaceShouldFail() {
++            TensorImage tensorImage = new TensorImage();
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    ()
++                            -> tensorImage.load(
++                                    TensorBuffer.createDynamic(DataType.FLOAT32), colorSpaceType));
++            assertThat(exception).hasMessageThat().contains(
++                    "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
++                    + " `load(TensorBuffer, ImageProperties)` for other color space types.");
++        }
++
++        @Test
++        public void loadTensorBufferAndGetBitmapShouldFail() {
++            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++            tensorBuffer.loadArray(data, new int[] {data.length});
++
++            ImageProperties imageProperties = ImageProperties.builder()
++                                                      .setHeight(HEIGHT)
++                                                      .setWidth(WIDTH)
++                                                      .setColorSpaceType(colorSpaceType)
++                                                      .build();
++
++            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
++            tensorImage.load(tensorBuffer, imageProperties);
++
++            UnsupportedOperationException exception = assertThrows(
++                    UnsupportedOperationException.class, () -> tensorImage.getBitmap());
++            assertThat(exception).hasMessageThat().contains(
++                    "convertTensorBufferToBitmap() is unsupported for the color space type "
++                    + colorSpaceType.name());
++        }
++    }
++
++    /** Parameterized tests for loading TensorBuffers with ImageProperties. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class LoadTensorBufferWithImageProperties extends TensorImageTest {
++        private static final int HEIGHT = 2;
++        private static final int WIDTH = 3;
++        private static final int WRONG_WIDTH = 10;
++
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        @Parameters(name = "colorSpaceType={0}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.RGB},
++                    {ColorSpaceType.GRAYSCALE},
++                    {ColorSpaceType.NV12},
++                    {ColorSpaceType.NV21},
++                    {ColorSpaceType.YV12},
++                    {ColorSpaceType.YV21},
++            });
++        }
++
++        @Test
++        public void loadAndGetTensorBufferShouldSucceedWithCorrectProperties() {
++            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++            tensorBuffer.loadArray(data, new int[] {data.length});
++
++            ImageProperties imageProperties = ImageProperties.builder()
++                                                      .setHeight(HEIGHT)
++                                                      .setWidth(WIDTH)
++                                                      .setColorSpaceType(colorSpaceType)
++                                                      .build();
++
++            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
++            tensorImage.load(tensorBuffer, imageProperties);
++
++            assertEqualTensorBuffers(tensorImage.getTensorBuffer(), tensorBuffer);
++        }
++
++        @Test
++        public void loadAndGetTensorBufferShouldSucceedWithLargerBuffer() {
++            // Should allow buffer to be greater than the size specified by height and width.
++            int moreElements = 1;
++            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH) + moreElements];
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++            tensorBuffer.loadArray(data, new int[] {data.length});
++
++            ImageProperties imageProperties = ImageProperties.builder()
++                                                      .setHeight(HEIGHT)
++                                                      .setWidth(WIDTH)
++                                                      .setColorSpaceType(colorSpaceType)
++                                                      .build();
++
++            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
++            tensorImage.load(tensorBuffer, imageProperties);
++
++            assertEqualTensorBuffers(tensorImage.getTensorBuffer(), tensorBuffer);
++        }
++
++        @Test
++        public void loadAndGetByteBufferShouldSucceedWithCorrectProperties() {
++            ByteBuffer byteBuffer =
++                    ByteBuffer.allocate(colorSpaceType.getNumElements(HEIGHT, WIDTH));
++
++            ImageProperties imageProperties = ImageProperties.builder()
++                                                      .setHeight(HEIGHT)
++                                                      .setWidth(WIDTH)
++                                                      .setColorSpaceType(colorSpaceType)
++                                                      .build();
++
++            TensorImage tensorImage = new TensorImage(DataType.UINT8);
++            tensorImage.load(byteBuffer, imageProperties);
++
++            assertEqualByteBuffers(tensorImage.getBuffer(), byteBuffer);
++        }
++
++        @Test
++        public void loadTensorBufferWithShouldFailWithWrongImageShape() {
++            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++            tensorBuffer.loadArray(data, new int[] {data.length});
++
++            ImageProperties imageProperties = ImageProperties.builder()
++                                                      .setHeight(HEIGHT)
++                                                      .setWidth(WRONG_WIDTH)
++                                                      .setColorSpaceType(colorSpaceType)
++                                                      .build();
++
++            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> tensorImage.load(tensorBuffer, imageProperties));
++            assertThat(exception).hasMessageThat().contains(String.format(
++                    "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
++                            + " expected number of elements should be at least %d.",
++                    data.length, colorSpaceType.name(), HEIGHT, WRONG_WIDTH,
++                    colorSpaceType.getNumElements(HEIGHT, WRONG_WIDTH)));
++        }
++
++        @Test
++        public void getShapeOfInternalTensorBufferShouldSuccess() {
++            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++            tensorBuffer.loadArray(data, new int[] {data.length});
++
++            ImageProperties imageProperties = ImageProperties.builder()
++                                                      .setHeight(HEIGHT)
++                                                      .setWidth(WIDTH)
++                                                      .setColorSpaceType(colorSpaceType)
++                                                      .build();
++
++            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
++            tensorImage.load(tensorBuffer, imageProperties);
++
++            assertThat(tensorImage.getWidth()).isEqualTo(WIDTH);
++            assertThat(tensorImage.getHeight()).isEqualTo(HEIGHT);
++        }
++    }
++
++    /** Parameterized tests for loading TensorBuffer with invalid shapes. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class LoadTensorBufferWithInvalidShapeTest extends TensorImageTest {
++        private static final String RGB_ASSERT_SHAPE_MESSAGE =
++                "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
++                + " representing R, G, B in order. The provided image shape is ";
++        private static final String GRAYSCALE_ASSERT_SHAPE_MESSAGE =
++                "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
++                + " shape is ";
++
++        @Parameter(0)
++        public ColorSpaceType colorSpaceType;
++
++        /** The shape that does not match the colorSpaceType. */
++        @Parameter(1)
++        public int[] invalidShape;
++
++        @Parameter(2)
++        public String errorMessage;
++
++        @Parameters(name = "colorSpaceType={0}; invalidShape={1}")
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {
++                    {ColorSpaceType.RGB, new int[] {2, 10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {1, 10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.RGB, new int[] {10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {2, 10, 20},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 3},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {10, 20, 4},
++                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++                    {ColorSpaceType.GRAYSCALE, new int[] {10}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
++            });
++        }
++
++        @Test
++        public void loadTensorBufferWithInvalidShape() {
++            TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(invalidShape, UINT8);
++            TensorImage tensorImage = new TensorImage();
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> tensorImage.load(tensorBuffer, colorSpaceType));
++            assertThat(exception).hasMessageThat().contains(
++                    errorMessage + Arrays.toString(invalidShape));
++        }
++    }
++
++    private static void assertEqualTensorBuffers(
++            TensorBuffer tensorBuffer1, TensorBuffer tensorBuffer2) {
++        assertEqualByteBuffers(tensorBuffer1.getBuffer(), tensorBuffer2.getBuffer());
++        assertArrayEquals(tensorBuffer1.getShape(), tensorBuffer2.getShape());
++    }
++
++    private static void assertEqualByteBuffers(ByteBuffer buffer1, ByteBuffer buffer2) {
++        buffer1.rewind();
++        buffer2.rewind();
++        assertThat(buffer1.equals(buffer2)).isTrue();
++    }
++
++    private static void setUpImageMock(Image imageMock, int imageFormat) {
++        when(imageMock.getFormat()).thenReturn(imageFormat);
+     }
+-  }
+-
+-  private static void assertEqualTensorBuffers(
+-      TensorBuffer tensorBuffer1, TensorBuffer tensorBuffer2) {
+-    assertEqualByteBuffers(tensorBuffer1.getBuffer(), tensorBuffer2.getBuffer());
+-    assertArrayEquals(tensorBuffer1.getShape(), tensorBuffer2.getShape());
+-  }
+-
+-  private static void assertEqualByteBuffers(ByteBuffer buffer1, ByteBuffer buffer2) {
+-    buffer1.rewind();
+-    buffer2.rewind();
+-    assertThat(buffer1.equals(buffer2)).isTrue();
+-  }
+-
+-  private static void setUpImageMock(Image imageMock, int imageFormat) {
+-    when(imageMock.getFormat()).thenReturn(imageFormat);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java
+index 7a5d0e9a9ea33..4ac2eca0b8cc6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java
+@@ -17,109 +17,112 @@ package org.tensorflow.lite.support.image;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.Color;
+-import java.nio.ByteBuffer;
++
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.nio.ByteBuffer;
++
+ /** Creates test images for other test files. */
+ final class TestImageCreator {
+-  /**
+-   * Creates an example bitmap, which is a 10x10 ARGB bitmap and pixels are set by: <br>
+-   * pixel[i] = {A: 255, B: i + 2, G: i + 1, R: i}, where i is the flatten index.
+-   */
+-  static Bitmap createRgbBitmap() {
+-    int[] colors = new int[100];
+-    for (int i = 0; i < 100; i++) {
+-      colors[i] = Color.rgb(i, i + 1, i + 2);
++    /**
++     * Creates an example bitmap, which is a 10x10 ARGB bitmap and pixels are set by: <br>
++     * pixel[i] = {A: 255, B: i + 2, G: i + 1, R: i}, where i is the flatten index.
++     */
++    static Bitmap createRgbBitmap() {
++        int[] colors = new int[100];
++        for (int i = 0; i < 100; i++) {
++            colors[i] = Color.rgb(i, i + 1, i + 2);
++        }
++        return Bitmap.createBitmap(colors, 10, 10, Bitmap.Config.ARGB_8888);
+     }
+-    return Bitmap.createBitmap(colors, 10, 10, Bitmap.Config.ARGB_8888);
+-  }
+ 
+-  /**
+-   * Creates a 10*10*3 float or uint8 TensorBuffer representing the same image in createRgbBitmap.
+-   *
+-   * <p>Adds a default delta, 0.1f, to the generated float values, such that the float array is
+-   * [0.1, 1.1, 2.1, 3.1, ...], while the uint8 array is[0, 1, 2, 3, ...].
+-   *
+-   * @param isNormalized if true, the shape is (1, h, w, 3), otherwise it's (h, w, 3)
+-   */
+-  static TensorBuffer createRgbTensorBuffer(DataType dataType, boolean isNormalized) {
+-    return createRgbTensorBuffer(dataType, isNormalized, /*delta=*/ 0.1f);
+-  }
+-
+-  /**
+-   * Creates a 10*10*3 float or uint8 TensorBuffer representing the same image in createRgbBitmap.
+-   *
+-   * @param isNormalized if true, the shape is (1, h, w, 3), otherwise it's (h, w)
+-   * @param delta the delta that applied to the float values, such that the float array is [0 + +
+-   *     delta, 1+ delta, 2+ delta, 3+ delta, ...], while the uint8 array is [0, 1, 2, 3, ...]
+-   */
+-  static TensorBuffer createRgbTensorBuffer(DataType dataType, boolean isNormalized, float delta) {
+-    float[] rgbValues = new float[300];
+-    for (int i = 0, j = 0; i < 100; i++) {
+-      rgbValues[j++] = i + delta;
+-      rgbValues[j++] = i + 1 + delta;
+-      rgbValues[j++] = i + 2 + delta;
++    /**
++     * Creates a 10*10*3 float or uint8 TensorBuffer representing the same image in createRgbBitmap.
++     *
++     * <p>Adds a default delta, 0.1f, to the generated float values, such that the float array is
++     * [0.1, 1.1, 2.1, 3.1, ...], while the uint8 array is[0, 1, 2, 3, ...].
++     *
++     * @param isNormalized if true, the shape is (1, h, w, 3), otherwise it's (h, w, 3)
++     */
++    static TensorBuffer createRgbTensorBuffer(DataType dataType, boolean isNormalized) {
++        return createRgbTensorBuffer(dataType, isNormalized, /*delta=*/0.1f);
+     }
+ 
+-    int[] shape = isNormalized ? new int[] {1, 10, 10, 3} : new int[] {10, 10, 3};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, dataType);
+-    // If dataType is UINT8, rgbValues will be converted into uint8, such as from
+-    // [0.1, 1.1, 2.1, 3.1, ...] to [0, 1, 2, 3, ...].
+-    buffer.loadArray(rgbValues, shape);
+-    return buffer;
+-  }
++    /**
++     * Creates a 10*10*3 float or uint8 TensorBuffer representing the same image in createRgbBitmap.
++     *
++     * @param isNormalized if true, the shape is (1, h, w, 3), otherwise it's (h, w)
++     * @param delta the delta that applied to the float values, such that the float array is [0 + +
++     *     delta, 1+ delta, 2+ delta, 3+ delta, ...], while the uint8 array is [0, 1, 2, 3, ...]
++     */
++    static TensorBuffer createRgbTensorBuffer(
++            DataType dataType, boolean isNormalized, float delta) {
++        float[] rgbValues = new float[300];
++        for (int i = 0, j = 0; i < 100; i++) {
++            rgbValues[j++] = i + delta;
++            rgbValues[j++] = i + 1 + delta;
++            rgbValues[j++] = i + 2 + delta;
++        }
++
++        int[] shape = isNormalized ? new int[] {1, 10, 10, 3} : new int[] {10, 10, 3};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, dataType);
++        // If dataType is UINT8, rgbValues will be converted into uint8, such as from
++        // [0.1, 1.1, 2.1, 3.1, ...] to [0, 1, 2, 3, ...].
++        buffer.loadArray(rgbValues, shape);
++        return buffer;
++    }
+ 
+-  /**
+-   * Creates an example bitmap, which is a 10x10 ALPHA_8 bitmap and pixels are set by: <br>
+-   * pixel[i] = i, where i is the flatten index.
+-   */
+-  static Bitmap createGrayscaleBitmap() {
+-    byte[] grayValues = new byte[100];
+-    for (int i = 0; i < 100; i++) {
+-      grayValues[i] = (byte) i;
++    /**
++     * Creates an example bitmap, which is a 10x10 ALPHA_8 bitmap and pixels are set by: <br>
++     * pixel[i] = i, where i is the flatten index.
++     */
++    static Bitmap createGrayscaleBitmap() {
++        byte[] grayValues = new byte[100];
++        for (int i = 0; i < 100; i++) {
++            grayValues[i] = (byte) i;
++        }
++        ByteBuffer buffer = ByteBuffer.wrap(grayValues);
++        Bitmap bitmap = Bitmap.createBitmap(10, 10, Bitmap.Config.ALPHA_8);
++        buffer.rewind();
++        bitmap.copyPixelsFromBuffer(buffer);
++        return bitmap;
+     }
+-    ByteBuffer buffer = ByteBuffer.wrap(grayValues);
+-    Bitmap bitmap = Bitmap.createBitmap(10, 10, Bitmap.Config.ALPHA_8);
+-    buffer.rewind();
+-    bitmap.copyPixelsFromBuffer(buffer);
+-    return bitmap;
+-  }
+ 
+-  /**
+-   * Creates a 10*10 float or uint8 TensorBuffer representing the same image in
+-   * createGrayscaleBitmap.
+-   *
+-   * <p>Adds a default delta, 0.1f, to the generated float values, such that the float array is
+-   * [0.1, 1.1, 2.1, 3.1, ...], while the uint8 array is[0, 1, 2, 3, ...].
+-   *
+-   * @param isNormalized if true, the shape is (1, h, w, 1), otherwise it's (h, w)
+-   */
+-  static TensorBuffer createGrayscaleTensorBuffer(DataType dataType, boolean isNormalized) {
+-    return createGrayscaleTensorBuffer(dataType, isNormalized, /*delta=*/ 0.1f);
+-  }
++    /**
++     * Creates a 10*10 float or uint8 TensorBuffer representing the same image in
++     * createGrayscaleBitmap.
++     *
++     * <p>Adds a default delta, 0.1f, to the generated float values, such that the float array is
++     * [0.1, 1.1, 2.1, 3.1, ...], while the uint8 array is[0, 1, 2, 3, ...].
++     *
++     * @param isNormalized if true, the shape is (1, h, w, 1), otherwise it's (h, w)
++     */
++    static TensorBuffer createGrayscaleTensorBuffer(DataType dataType, boolean isNormalized) {
++        return createGrayscaleTensorBuffer(dataType, isNormalized, /*delta=*/0.1f);
++    }
+ 
+-  /**
+-   * Creates a 10*10 float or uint8 TensorBuffer representing the same image in
+-   * createGrayscaleBitmap.
+-   *
+-   * @param isNormalized if true, the shape is (1, h, w, 1), otherwise it's (h, w)
+-   * @param delta the delta that applied to the float values, such that the float array is [0 +
+-   *     delta, 1+ delta, 2+ delta, 3+ delta, ...], while the uint8 array is [0, 1, 2, 3, ...]
+-   */
+-  static TensorBuffer createGrayscaleTensorBuffer(
+-      DataType dataType, boolean isNormalized, float delta) {
+-    float[] grayValues = new float[100];
+-    for (int i = 0; i < 100; i++) {
+-      grayValues[i] = i + delta;
++    /**
++     * Creates a 10*10 float or uint8 TensorBuffer representing the same image in
++     * createGrayscaleBitmap.
++     *
++     * @param isNormalized if true, the shape is (1, h, w, 1), otherwise it's (h, w)
++     * @param delta the delta that applied to the float values, such that the float array is [0 +
++     *     delta, 1+ delta, 2+ delta, 3+ delta, ...], while the uint8 array is [0, 1, 2, 3, ...]
++     */
++    static TensorBuffer createGrayscaleTensorBuffer(
++            DataType dataType, boolean isNormalized, float delta) {
++        float[] grayValues = new float[100];
++        for (int i = 0; i < 100; i++) {
++            grayValues[i] = i + delta;
++        }
++        int[] shape = isNormalized ? new int[] {1, 10, 10, 1} : new int[] {10, 10};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, dataType);
++        // If dataType is UINT8, grayValues will be converted into uint8, such as from
++        // [0.1, 1.1, 2.1, 3.1, ...] to [0, 1, 2, 3, ...].
++        buffer.loadArray(grayValues, shape);
++        return buffer;
+     }
+-    int[] shape = isNormalized ? new int[] {1, 10, 10, 1} : new int[] {10, 10};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, dataType);
+-    // If dataType is UINT8, grayValues will be converted into uint8, such as from
+-    // [0.1, 1.1, 2.1, 3.1, ...] to [0, 1, 2, 3, ...].
+-    buffer.loadArray(grayValues, shape);
+-    return buffer;
+-  }
+ 
+-  private TestImageCreator() {}
++    private TestImageCreator() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java
+index a34f47d44c0ac..070e17893ad76 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java
+@@ -19,7 +19,9 @@ import static com.google.common.truth.Truth.assertThat;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.PointF;
++
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -31,63 +33,62 @@ import org.tensorflow.lite.support.image.ops.ResizeOp.ResizeMethod;
+ /** Instrumented unit test for {@link ResizeOp}. */
+ @RunWith(AndroidJUnit4.class)
+ public class ResizeOpInstrumentedTest {
++    private static final int EXAMPLE_WIDTH = 10;
++    private static final int EXAMPLE_HEIGHT = 15;
+ 
+-  private static final int EXAMPLE_WIDTH = 10;
+-  private static final int EXAMPLE_HEIGHT = 15;
+-
+-  private Bitmap exampleBitmap;
+-  private TensorImage input;
++    private Bitmap exampleBitmap;
++    private TensorImage input;
+ 
+-  @Before
+-  public void setUp() {
+-    exampleBitmap = createExampleBitmap();
+-    input = new TensorImage(DataType.UINT8);
+-    input.load(exampleBitmap);
+-  }
++    @Before
++    public void setUp() {
++        exampleBitmap = createExampleBitmap();
++        input = new TensorImage(DataType.UINT8);
++        input.load(exampleBitmap);
++    }
+ 
+-  @Test
+-  public void resizeShouldSuccess() {
+-    int targetWidth = EXAMPLE_WIDTH * 2;
+-    int targetHeight = EXAMPLE_HEIGHT * 2;
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder()
+-            .add(new ResizeOp(targetHeight, targetWidth, ResizeMethod.NEAREST_NEIGHBOR))
+-            .build();
+-    TensorImage output = processor.process(input);
++    @Test
++    public void resizeShouldSuccess() {
++        int targetWidth = EXAMPLE_WIDTH * 2;
++        int targetHeight = EXAMPLE_HEIGHT * 2;
++        ImageProcessor processor =
++                new ImageProcessor.Builder()
++                        .add(new ResizeOp(targetHeight, targetWidth, ResizeMethod.NEAREST_NEIGHBOR))
++                        .build();
++        TensorImage output = processor.process(input);
+ 
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
+-    assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
+-    for (int i = 0; i < outputBitmap.getWidth(); i++) {
+-      for (int j = 0; j < outputBitmap.getHeight(); j++) {
+-        int expected = exampleBitmap.getPixel(i / 2, j / 2);
+-        assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+-      }
++        Bitmap outputBitmap = output.getBitmap();
++        assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
++        assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
++        for (int i = 0; i < outputBitmap.getWidth(); i++) {
++            for (int j = 0; j < outputBitmap.getHeight(); j++) {
++                int expected = exampleBitmap.getPixel(i / 2, j / 2);
++                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
++            }
++        }
+     }
+-  }
+ 
+-  @Test
+-  public void inverseTransformPointShouldSuccess() {
+-    ResizeOp op = new ResizeOp(200, 300, ResizeMethod.NEAREST_NEIGHBOR);
+-    PointF transformed = new PointF(32.0f, 42.0f);
+-    // The original image size is 900x400 assumed
+-    PointF original = op.inverseTransform(transformed, 400, 900);
+-    assertThat(original.x).isEqualTo(96);
+-    assertThat(original.y).isEqualTo(84);
+-    PointF outside = op.inverseTransform(new PointF(500, 1000), 400, 900);
+-    assertThat(outside.x).isEqualTo(1500);
+-    assertThat(outside.y).isEqualTo(2000);
+-  }
++    @Test
++    public void inverseTransformPointShouldSuccess() {
++        ResizeOp op = new ResizeOp(200, 300, ResizeMethod.NEAREST_NEIGHBOR);
++        PointF transformed = new PointF(32.0f, 42.0f);
++        // The original image size is 900x400 assumed
++        PointF original = op.inverseTransform(transformed, 400, 900);
++        assertThat(original.x).isEqualTo(96);
++        assertThat(original.y).isEqualTo(84);
++        PointF outside = op.inverseTransform(new PointF(500, 1000), 400, 900);
++        assertThat(outside.x).isEqualTo(1500);
++        assertThat(outside.y).isEqualTo(2000);
++    }
+ 
+-  /**
+-   * Creates an example bitmap, which is a 10x15 ARGB bitmap and pixels are set by: - pixel[i] = {A:
+-   * 255, B: i + 2, G: i + 1, G: i}, where i is the flatten index
+-   */
+-  private static Bitmap createExampleBitmap() {
+-    int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+-    for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+-      colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++    /**
++     * Creates an example bitmap, which is a 10x15 ARGB bitmap and pixels are set by: - pixel[i] =
++     * {A: 255, B: i + 2, G: i + 1, G: i}, where i is the flatten index
++     */
++    private static Bitmap createExampleBitmap() {
++        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
++        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
++            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++        }
++        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+     }
+-    return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java
+index 5c483780b30f4..85c777904f2ec 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java
+@@ -19,7 +19,9 @@ import static com.google.common.truth.Truth.assertThat;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.PointF;
++
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -30,131 +32,128 @@ import org.tensorflow.lite.support.image.TensorImage;
+ /** Instrumented unit test for {@link ResizeWithCropOrPadOp}. */
+ @RunWith(AndroidJUnit4.class)
+ public class ResizeWithCropOrPadOpInstrumentedTest {
++    private Bitmap exampleBitmap;
++    private TensorImage input;
+ 
+-  private Bitmap exampleBitmap;
+-  private TensorImage input;
+-
+-  private static final int EXAMPLE_WIDTH = 10;
+-  private static final int EXAMPLE_HEIGHT = 15;
+-
+-  @Before
+-  public void setUp() {
+-    exampleBitmap = createExampleBitmap();
+-    input = new TensorImage(DataType.UINT8);
+-    input.load(exampleBitmap);
+-  }
+-
+-  @Test
+-  public void testResizeWithCrop() {
+-    int targetWidth = 6;
+-    int targetHeight = 5;
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder()
+-            .add(new ResizeWithCropOrPadOp(targetHeight, targetWidth))
+-            .build();
+-    TensorImage output = processor.process(input);
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
+-    assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
+-    for (int i = 0; i < outputBitmap.getWidth(); i++) {
+-      for (int j = 0; j < outputBitmap.getHeight(); j++) {
+-        int expected =
+-            exampleBitmap.getPixel(
+-                i + (EXAMPLE_WIDTH - targetWidth) / 2, j + (EXAMPLE_HEIGHT - targetHeight) / 2);
+-        assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+-      }
++    private static final int EXAMPLE_WIDTH = 10;
++    private static final int EXAMPLE_HEIGHT = 15;
++
++    @Before
++    public void setUp() {
++        exampleBitmap = createExampleBitmap();
++        input = new TensorImage(DataType.UINT8);
++        input.load(exampleBitmap);
+     }
+-  }
+-
+-  @Test
+-  public void testResizeWithPad() {
+-    int targetWidth = 15;
+-    int targetHeight = 20;
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder()
+-            .add(new ResizeWithCropOrPadOp(targetHeight, targetWidth))
+-            .build();
+-    TensorImage output = processor.process(input);
+-    // Pad 2 rows / columns on top / left, and 3 rows / columns on bottom / right
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
+-    assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
+-    int leftPad = (targetWidth - EXAMPLE_WIDTH) / 2;
+-    int topPad = (targetHeight - EXAMPLE_HEIGHT) / 2;
+-    for (int i = 0; i < outputBitmap.getWidth(); i++) {
+-      for (int j = 0; j < outputBitmap.getHeight(); j++) {
+-        int expected = 0; // ZERO padding
+-        if (i >= leftPad
+-            && i < leftPad + EXAMPLE_WIDTH
+-            && j >= topPad
+-            && j < topPad + EXAMPLE_HEIGHT) {
+-          expected = exampleBitmap.getPixel(i - leftPad, j - topPad);
++
++    @Test
++    public void testResizeWithCrop() {
++        int targetWidth = 6;
++        int targetHeight = 5;
++        ImageProcessor processor =
++                new ImageProcessor.Builder()
++                        .add(new ResizeWithCropOrPadOp(targetHeight, targetWidth))
++                        .build();
++        TensorImage output = processor.process(input);
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
++        assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
++        for (int i = 0; i < outputBitmap.getWidth(); i++) {
++            for (int j = 0; j < outputBitmap.getHeight(); j++) {
++                int expected = exampleBitmap.getPixel(i + (EXAMPLE_WIDTH - targetWidth) / 2,
++                        j + (EXAMPLE_HEIGHT - targetHeight) / 2);
++                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
++            }
++        }
++    }
++
++    @Test
++    public void testResizeWithPad() {
++        int targetWidth = 15;
++        int targetHeight = 20;
++        ImageProcessor processor =
++                new ImageProcessor.Builder()
++                        .add(new ResizeWithCropOrPadOp(targetHeight, targetWidth))
++                        .build();
++        TensorImage output = processor.process(input);
++        // Pad 2 rows / columns on top / left, and 3 rows / columns on bottom / right
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
++        assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
++        int leftPad = (targetWidth - EXAMPLE_WIDTH) / 2;
++        int topPad = (targetHeight - EXAMPLE_HEIGHT) / 2;
++        for (int i = 0; i < outputBitmap.getWidth(); i++) {
++            for (int j = 0; j < outputBitmap.getHeight(); j++) {
++                int expected = 0; // ZERO padding
++                if (i >= leftPad && i < leftPad + EXAMPLE_WIDTH && j >= topPad
++                        && j < topPad + EXAMPLE_HEIGHT) {
++                    expected = exampleBitmap.getPixel(i - leftPad, j - topPad);
++                }
++                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
++            }
+         }
+-        assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+-      }
+     }
+-  }
+-
+-  @Test
+-  public void testResizeWithCropAndPad() {
+-    int targetSize = 12;
+-    // Pad 1 column on left & right, crop 1 row on top and 2 rows on bottom
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new ResizeWithCropOrPadOp(targetSize, targetSize)).build();
+-    TensorImage output = processor.process(input);
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertThat(outputBitmap.getWidth()).isEqualTo(targetSize);
+-    assertThat(outputBitmap.getHeight()).isEqualTo(targetSize);
+-
+-    int leftPad = (targetSize - EXAMPLE_WIDTH) / 2;
+-    int topCrop = (EXAMPLE_HEIGHT - targetSize) / 2;
+-    for (int i = 0; i < outputBitmap.getWidth(); i++) {
+-      for (int j = 0; j < outputBitmap.getHeight(); j++) {
+-        int expected = 0;
+-        if (i >= leftPad && i < leftPad + EXAMPLE_WIDTH) {
+-          expected = exampleBitmap.getPixel(i - leftPad, j + topCrop);
++
++    @Test
++    public void testResizeWithCropAndPad() {
++        int targetSize = 12;
++        // Pad 1 column on left & right, crop 1 row on top and 2 rows on bottom
++        ImageProcessor processor = new ImageProcessor.Builder()
++                                           .add(new ResizeWithCropOrPadOp(targetSize, targetSize))
++                                           .build();
++        TensorImage output = processor.process(input);
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertThat(outputBitmap.getWidth()).isEqualTo(targetSize);
++        assertThat(outputBitmap.getHeight()).isEqualTo(targetSize);
++
++        int leftPad = (targetSize - EXAMPLE_WIDTH) / 2;
++        int topCrop = (EXAMPLE_HEIGHT - targetSize) / 2;
++        for (int i = 0; i < outputBitmap.getWidth(); i++) {
++            for (int j = 0; j < outputBitmap.getHeight(); j++) {
++                int expected = 0;
++                if (i >= leftPad && i < leftPad + EXAMPLE_WIDTH) {
++                    expected = exampleBitmap.getPixel(i - leftPad, j + topCrop);
++                }
++                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
++            }
+         }
+-        assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+-      }
+     }
+-  }
+-
+-  @Test
+-  public void inverseTransformCorrectlyWhenCropped() {
+-    ResizeWithCropOrPadOp op = new ResizeWithCropOrPadOp(300, 300);
+-    // The point (100, 50) is transformed from 600x500 image
+-    PointF original = op.inverseTransform(new PointF(100, 50), 500, 600);
+-    assertThat(original.x).isEqualTo(250);
+-    assertThat(original.y).isEqualTo(150);
+-    PointF cropped = op.inverseTransform(new PointF(-10, -10), 500, 600);
+-    assertThat(cropped.x).isEqualTo(140);
+-    assertThat(cropped.y).isEqualTo(90);
+-  }
+-
+-  @Test
+-  public void inverseTransformCorrectlyWhenPadded() {
+-    ResizeWithCropOrPadOp op = new ResizeWithCropOrPadOp(300, 300);
+-    // The point (100, 50) is transformed from 100x200 image
+-    PointF original = op.inverseTransform(new PointF(100, 50), 200, 100);
+-    assertThat(original.x).isEqualTo(0);
+-    assertThat(original.y).isEqualTo(0);
+-    PointF outside = op.inverseTransform(new PointF(50, 10), 200, 100);
+-    assertThat(outside.x).isEqualTo(-50);
+-    assertThat(outside.y).isEqualTo(-40);
+-  }
+-
+-  /**
+-   * Creates an example bitmap, which is a 10x15 ARGB bitmap and pixels are set by: - pixel[i] = {A:
+-   * 255, R: i + 2, G: i + 1, B: i}, where i is the flatten index
+-   */
+-  private static Bitmap createExampleBitmap() {
+-    int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+-    for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+-      colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++
++    @Test
++    public void inverseTransformCorrectlyWhenCropped() {
++        ResizeWithCropOrPadOp op = new ResizeWithCropOrPadOp(300, 300);
++        // The point (100, 50) is transformed from 600x500 image
++        PointF original = op.inverseTransform(new PointF(100, 50), 500, 600);
++        assertThat(original.x).isEqualTo(250);
++        assertThat(original.y).isEqualTo(150);
++        PointF cropped = op.inverseTransform(new PointF(-10, -10), 500, 600);
++        assertThat(cropped.x).isEqualTo(140);
++        assertThat(cropped.y).isEqualTo(90);
++    }
++
++    @Test
++    public void inverseTransformCorrectlyWhenPadded() {
++        ResizeWithCropOrPadOp op = new ResizeWithCropOrPadOp(300, 300);
++        // The point (100, 50) is transformed from 100x200 image
++        PointF original = op.inverseTransform(new PointF(100, 50), 200, 100);
++        assertThat(original.x).isEqualTo(0);
++        assertThat(original.y).isEqualTo(0);
++        PointF outside = op.inverseTransform(new PointF(50, 10), 200, 100);
++        assertThat(outside.x).isEqualTo(-50);
++        assertThat(outside.y).isEqualTo(-40);
++    }
++
++    /**
++     * Creates an example bitmap, which is a 10x15 ARGB bitmap and pixels are set by: - pixel[i] =
++     * {A: 255, R: i + 2, G: i + 1, B: i}, where i is the flatten index
++     */
++    private static Bitmap createExampleBitmap() {
++        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
++        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
++            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++        }
++        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+     }
+-    return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java
+index eb54788764f1e..d00fe0e44422e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java
+@@ -19,7 +19,9 @@ import static com.google.common.truth.Truth.assertThat;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.PointF;
++
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -30,68 +32,68 @@ import org.tensorflow.lite.support.image.TensorImage;
+ /** Instrumented unit test for {@link Rot90Op}. */
+ @RunWith(AndroidJUnit4.class)
+ public class Rot90OpInstrumentedTest {
++    private Bitmap exampleBitmap;
++    private TensorImage input;
++
++    private static final int EXAMPLE_WIDTH = 10;
++    private static final int EXAMPLE_HEIGHT = 15;
+ 
+-  private Bitmap exampleBitmap;
+-  private TensorImage input;
+-
+-  private static final int EXAMPLE_WIDTH = 10;
+-  private static final int EXAMPLE_HEIGHT = 15;
+-
+-  @Before
+-  public void setUp() {
+-    exampleBitmap = createExampleBitmap();
+-    input = new TensorImage(DataType.UINT8);
+-    input.load(exampleBitmap);
+-  }
+-
+-  @Test
+-  public void testRot90() {
+-    ImageProcessor processor = new ImageProcessor.Builder().add(new Rot90Op()).build();
+-    TensorImage output = processor.process(input);
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertThat(outputBitmap.getWidth()).isEqualTo(EXAMPLE_HEIGHT);
+-    assertThat(outputBitmap.getHeight()).isEqualTo(EXAMPLE_WIDTH);
+-    for (int i = 0; i < exampleBitmap.getWidth(); i++) {
+-      for (int j = 0; j < exampleBitmap.getHeight(); j++) {
+-        assertThat(exampleBitmap.getPixel(i, j))
+-            .isEqualTo(outputBitmap.getPixel(j, EXAMPLE_WIDTH - 1 - i));
+-      }
++    @Before
++    public void setUp() {
++        exampleBitmap = createExampleBitmap();
++        input = new TensorImage(DataType.UINT8);
++        input.load(exampleBitmap);
+     }
+-  }
+-
+-  @Test
+-  public void testRot90Twice() {
+-    ImageProcessor processor = new ImageProcessor.Builder().add(new Rot90Op(2)).build();
+-    TensorImage output = processor.process(input);
+-
+-    Bitmap outputBitmap = output.getBitmap();
+-    assertThat(outputBitmap.getWidth()).isEqualTo(EXAMPLE_WIDTH);
+-    assertThat(outputBitmap.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
+-    for (int i = 0; i < exampleBitmap.getWidth(); i++) {
+-      for (int j = 0; j < exampleBitmap.getHeight(); j++) {
+-        assertThat(exampleBitmap.getPixel(i, j))
+-            .isEqualTo(outputBitmap.getPixel(EXAMPLE_WIDTH - 1 - i, EXAMPLE_HEIGHT - 1 - j));
+-      }
++
++    @Test
++    public void testRot90() {
++        ImageProcessor processor = new ImageProcessor.Builder().add(new Rot90Op()).build();
++        TensorImage output = processor.process(input);
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertThat(outputBitmap.getWidth()).isEqualTo(EXAMPLE_HEIGHT);
++        assertThat(outputBitmap.getHeight()).isEqualTo(EXAMPLE_WIDTH);
++        for (int i = 0; i < exampleBitmap.getWidth(); i++) {
++            for (int j = 0; j < exampleBitmap.getHeight(); j++) {
++                assertThat(exampleBitmap.getPixel(i, j))
++                        .isEqualTo(outputBitmap.getPixel(j, EXAMPLE_WIDTH - 1 - i));
++            }
++        }
+     }
+-  }
+-
+-  @Test
+-  public void inverseTransformCorrectlyWhenRotated() {
+-    Rot90Op op = new Rot90Op(3);
+-    PointF original = op.inverseTransform(new PointF(20, 10), 200, 100);
+-    assertThat(original.x).isEqualTo(10);
+-    assertThat(original.y).isEqualTo(180);
+-    PointF outside = op.inverseTransform(new PointF(-10, 110), 200, 100);
+-    assertThat(outside.x).isEqualTo(110);
+-    assertThat(outside.y).isEqualTo(210);
+-  }
+-
+-  private static Bitmap createExampleBitmap() {
+-    int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+-    for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+-      colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++
++    @Test
++    public void testRot90Twice() {
++        ImageProcessor processor = new ImageProcessor.Builder().add(new Rot90Op(2)).build();
++        TensorImage output = processor.process(input);
++
++        Bitmap outputBitmap = output.getBitmap();
++        assertThat(outputBitmap.getWidth()).isEqualTo(EXAMPLE_WIDTH);
++        assertThat(outputBitmap.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
++        for (int i = 0; i < exampleBitmap.getWidth(); i++) {
++            for (int j = 0; j < exampleBitmap.getHeight(); j++) {
++                assertThat(exampleBitmap.getPixel(i, j))
++                        .isEqualTo(outputBitmap.getPixel(
++                                EXAMPLE_WIDTH - 1 - i, EXAMPLE_HEIGHT - 1 - j));
++            }
++        }
++    }
++
++    @Test
++    public void inverseTransformCorrectlyWhenRotated() {
++        Rot90Op op = new Rot90Op(3);
++        PointF original = op.inverseTransform(new PointF(20, 10), 200, 100);
++        assertThat(original.x).isEqualTo(10);
++        assertThat(original.y).isEqualTo(180);
++        PointF outside = op.inverseTransform(new PointF(-10, 110), 200, 100);
++        assertThat(outside.x).isEqualTo(110);
++        assertThat(outside.y).isEqualTo(210);
++    }
++
++    private static Bitmap createExampleBitmap() {
++        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
++        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
++            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
++        }
++        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+     }
+-    return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java
+index 46713fd486fa7..f024f68911d27 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package org.tensorflow.lite.support.image.ops;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.mockito.Mockito.doReturn;
+ import static org.tensorflow.lite.DataType.UINT8;
+@@ -24,7 +25,9 @@ import android.graphics.Bitmap;
+ import android.graphics.Color;
+ import android.graphics.ImageFormat;
+ import android.media.Image;
++
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
++
+ import org.junit.Before;
+ import org.junit.Rule;
+ import org.junit.Test;
+@@ -40,54 +43,55 @@ import org.tensorflow.lite.support.image.TensorImage;
+ /** Instrumented unit test for {@link TransformToGrayscaleOp}. */
+ @RunWith(AndroidJUnit4.class)
+ public class TransformToGrayScaleOpInstrumentedTest {
+-
+-  @Rule public final MockitoRule mockito = MockitoJUnit.rule();
+-
+-  private TensorImage input;
+-
+-  private static final int EXAMPLE_WIDTH = 2;
+-  private static final int EXAMPLE_HEIGHT = 3;
+-  @Mock Image imageMock;
+-
+-  @Before
+-  public void setUp() {
+-    Bitmap exampleBitmap = createExampleBitmap();
+-    input = new TensorImage(DataType.UINT8);
+-    input.load(exampleBitmap);
+-  }
+-
+-  @Test
+-  public void apply_onRgb_succeeds() {
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new TransformToGrayscaleOp()).build();
+-
+-    TensorImage output = processor.process(input);
+-    int[] pixels = output.getTensorBuffer().getIntArray();
+-
+-    assertThat(output.getWidth()).isEqualTo(EXAMPLE_WIDTH);
+-    assertThat(output.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
+-    assertThat(output.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
+-    assertThat(pixels).isEqualTo(new int[] {0, 255, 76, 29, 150, 179});
+-  }
+-
+-  @Test
+-  public void apply_onYuv_throws() {
+-    setUpImageMock(imageMock, ImageFormat.YUV_420_888);
+-    TensorImage tensorImage = new TensorImage(UINT8);
+-    tensorImage.load(imageMock);
+-    ImageProcessor processor =
+-        new ImageProcessor.Builder().add(new TransformToGrayscaleOp()).build();
+-
+-    assertThrows(IllegalArgumentException.class, () -> processor.process(tensorImage));
+-  }
+-
+-  private static Bitmap createExampleBitmap() {
+-    int[] colors =
+-        new int[] {Color.BLACK, Color.WHITE, Color.RED, Color.BLUE, Color.GREEN, Color.CYAN};
+-    return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+-  }
+-
+-  private static void setUpImageMock(Image imageMock, int imageFormat) {
+-    doReturn(imageFormat).when(imageMock).getFormat();
+-  }
++    @Rule
++    public final MockitoRule mockito = MockitoJUnit.rule();
++
++    private TensorImage input;
++
++    private static final int EXAMPLE_WIDTH = 2;
++    private static final int EXAMPLE_HEIGHT = 3;
++    @Mock
++    Image imageMock;
++
++    @Before
++    public void setUp() {
++        Bitmap exampleBitmap = createExampleBitmap();
++        input = new TensorImage(DataType.UINT8);
++        input.load(exampleBitmap);
++    }
++
++    @Test
++    public void apply_onRgb_succeeds() {
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new TransformToGrayscaleOp()).build();
++
++        TensorImage output = processor.process(input);
++        int[] pixels = output.getTensorBuffer().getIntArray();
++
++        assertThat(output.getWidth()).isEqualTo(EXAMPLE_WIDTH);
++        assertThat(output.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
++        assertThat(output.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
++        assertThat(pixels).isEqualTo(new int[] {0, 255, 76, 29, 150, 179});
++    }
++
++    @Test
++    public void apply_onYuv_throws() {
++        setUpImageMock(imageMock, ImageFormat.YUV_420_888);
++        TensorImage tensorImage = new TensorImage(UINT8);
++        tensorImage.load(imageMock);
++        ImageProcessor processor =
++                new ImageProcessor.Builder().add(new TransformToGrayscaleOp()).build();
++
++        assertThrows(IllegalArgumentException.class, () -> processor.process(tensorImage));
++    }
++
++    private static Bitmap createExampleBitmap() {
++        int[] colors = new int[] {
++                Color.BLACK, Color.WHITE, Color.RED, Color.BLUE, Color.GREEN, Color.CYAN};
++        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
++    }
++
++    private static void setUpImageMock(Image imageMock, int imageFormat) {
++        doReturn(imageFormat).when(imageMock).getFormat();
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java
+index 28620dd941e9c..98d1f92f56c6d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java
+@@ -24,114 +24,98 @@ import org.robolectric.RobolectricTestRunner;
+ /** Tests of {@link org.tensorflow.lite.support.label.Category}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class CategoryTest {
+-  private static final String APPLE_LABEL = "apple";
+-  private static final String DEFAULT_DISPLAY_NAME = "";
+-  private static final String APPLE_DISPLAY_NAME = "manzana"; // "apple" in Spanish.
+-  private static final float APPLE_SCORE = 0.5f;
+-  private static final int APPLE_INDEX = 10;
+-
+-  @Test
+-  public void createShouldSucceed() {
+-    Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+-
+-    assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
+-    assertThat(category.getDisplayName()).isEqualTo(APPLE_DISPLAY_NAME);
+-    assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
+-  }
+-
+-  @Test
+-  public void createWithIndexShouldSucceed() {
+-    Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+-
+-    assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
+-    assertThat(category.getDisplayName()).isEqualTo(APPLE_DISPLAY_NAME);
+-    assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
+-    assertThat(category.getIndex()).isEqualTo(APPLE_INDEX);
+-  }
+-
+-  @Test
+-  public void constructorShouldSucceed() {
+-    Category category = new Category(APPLE_LABEL, APPLE_SCORE);
+-
+-    assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
+-    // Using the constructor, displayName will be default to an empty string.
+-    assertThat(category.getDisplayName()).isEqualTo(DEFAULT_DISPLAY_NAME);
+-    assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
+-  }
+-
+-  @Test
+-  public void toStringWithCreateShouldProvideReadableResult() {
+-    Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+-    String categoryString = category.toString();
+-
+-    assertThat(categoryString)
+-        .isEqualTo(
+-            "<Category \""
+-                + APPLE_LABEL
+-                + "\" (displayName="
+-                + APPLE_DISPLAY_NAME
+-                + " score="
+-                + APPLE_SCORE
+-                + " index=-1"
+-                + ")>");
+-  }
+-
+-  @Test
+-  public void toStringWithCreateIndexShouldProvideReadableResult() {
+-    Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+-    String categoryString = category.toString();
+-
+-    assertThat(categoryString)
+-        .isEqualTo(
+-            "<Category \""
+-                + APPLE_LABEL
+-                + "\" (displayName="
+-                + APPLE_DISPLAY_NAME
+-                + " score="
+-                + APPLE_SCORE
+-                + " index="
+-                + APPLE_INDEX
+-                + ")>");
+-  }
+-
+-  @Test
+-  public void toStringWithConstuctorShouldProvideReadableResult() {
+-    Category category = new Category(APPLE_LABEL, APPLE_SCORE);
+-    String categoryString = category.toString();
+-
+-    assertThat(categoryString)
+-        .isEqualTo(
+-            "<Category \""
+-                + APPLE_LABEL
+-                + "\" (displayName="
+-                + DEFAULT_DISPLAY_NAME
+-                + " score="
+-                + APPLE_SCORE
+-                + " index=-1"
+-                + ")>");
+-  }
+-
+-  @Test
+-  public void equalsShouldSucceedWithCreate() {
+-    Category categoryA = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+-    Category categoryB = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+-
+-    assertThat(categoryA).isEqualTo(categoryB);
+-  }
+-
+-  @Test
+-  public void equalsShouldSucceedWithCreateIndex() {
+-    Category categoryA = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+-    Category categoryB = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+-
+-    assertThat(categoryA).isEqualTo(categoryB);
+-  }
+-
+-  @Test
+-  public void equalsShouldSucceedWithConstructor() {
+-    Category categoryA = new Category(APPLE_LABEL, APPLE_SCORE);
+-    Category categoryB = new Category(APPLE_LABEL, APPLE_SCORE);
+-
+-    assertThat(categoryA).isEqualTo(categoryB);
+-  }
++    private static final String APPLE_LABEL = "apple";
++    private static final String DEFAULT_DISPLAY_NAME = "";
++    private static final String APPLE_DISPLAY_NAME = "manzana"; // "apple" in Spanish.
++    private static final float APPLE_SCORE = 0.5f;
++    private static final int APPLE_INDEX = 10;
++
++    @Test
++    public void createShouldSucceed() {
++        Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
++
++        assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
++        assertThat(category.getDisplayName()).isEqualTo(APPLE_DISPLAY_NAME);
++        assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
++    }
++
++    @Test
++    public void createWithIndexShouldSucceed() {
++        Category category =
++                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
++
++        assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
++        assertThat(category.getDisplayName()).isEqualTo(APPLE_DISPLAY_NAME);
++        assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
++        assertThat(category.getIndex()).isEqualTo(APPLE_INDEX);
++    }
++
++    @Test
++    public void constructorShouldSucceed() {
++        Category category = new Category(APPLE_LABEL, APPLE_SCORE);
++
++        assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
++        // Using the constructor, displayName will be default to an empty string.
++        assertThat(category.getDisplayName()).isEqualTo(DEFAULT_DISPLAY_NAME);
++        assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
++    }
++
++    @Test
++    public void toStringWithCreateShouldProvideReadableResult() {
++        Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
++        String categoryString = category.toString();
++
++        assertThat(categoryString)
++                .isEqualTo("<Category \"" + APPLE_LABEL + "\" (displayName=" + APPLE_DISPLAY_NAME
++                        + " score=" + APPLE_SCORE + " index=-1"
++                        + ")>");
++    }
++
++    @Test
++    public void toStringWithCreateIndexShouldProvideReadableResult() {
++        Category category =
++                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
++        String categoryString = category.toString();
++
++        assertThat(categoryString)
++                .isEqualTo("<Category \"" + APPLE_LABEL + "\" (displayName=" + APPLE_DISPLAY_NAME
++                        + " score=" + APPLE_SCORE + " index=" + APPLE_INDEX + ")>");
++    }
++
++    @Test
++    public void toStringWithConstuctorShouldProvideReadableResult() {
++        Category category = new Category(APPLE_LABEL, APPLE_SCORE);
++        String categoryString = category.toString();
++
++        assertThat(categoryString)
++                .isEqualTo("<Category \"" + APPLE_LABEL + "\" (displayName=" + DEFAULT_DISPLAY_NAME
++                        + " score=" + APPLE_SCORE + " index=-1"
++                        + ")>");
++    }
++
++    @Test
++    public void equalsShouldSucceedWithCreate() {
++        Category categoryA = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
++        Category categoryB = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
++
++        assertThat(categoryA).isEqualTo(categoryB);
++    }
++
++    @Test
++    public void equalsShouldSucceedWithCreateIndex() {
++        Category categoryA =
++                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
++        Category categoryB =
++                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
++
++        assertThat(categoryA).isEqualTo(categoryB);
++    }
++
++    @Test
++    public void equalsShouldSucceedWithConstructor() {
++        Category categoryA = new Category(APPLE_LABEL, APPLE_SCORE);
++        Category categoryB = new Category(APPLE_LABEL, APPLE_SCORE);
++
++        assertThat(categoryA).isEqualTo(categoryB);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java
+index caa468bb0a9ec..91c81c4932b81 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java
+@@ -17,35 +17,38 @@ package org.tensorflow.lite.support.label;
+ 
+ import static com.google.common.truth.Truth.assertThat;
+ 
+-import java.util.Arrays;
+-import java.util.List;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.Arrays;
++import java.util.List;
++
+ /** Tests of {@link org.tensorflow.lite.support.label.LabelUtil}. */
+ @RunWith(RobolectricTestRunner.class)
+ public class LabelUtilTest {
+-
+-  @Test
+-  public void mapIndexToStringsWithInvalidValues() {
+-    String[] labels = new String[] {"background", "apple", "banana", "cherry", "date"};
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    tensorBuffer.loadArray(new int[] {0, 1, 2, 3, 2, 5}, new int[] {1, 6});
+-    List<String> categories = LabelUtil.mapValueToLabels(tensorBuffer, Arrays.asList(labels), 1);
+-    assertThat(categories.toArray())
+-        .isEqualTo(new String[] {"apple", "banana", "cherry", "date", "cherry", ""});
+-  }
+-
+-  @Test
+-  public void mapFloatIndexShouldCast() {
+-    String[] labels = new String[] {"background", "apple", "banana", "cherry", "date"};
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    tensorBuffer.loadArray(new float[] {-1.1f, -0.3f, 0.3f, 1.2f, 1.8f, 1}, new int[] {1, 6});
+-    List<String> categories = LabelUtil.mapValueToLabels(tensorBuffer, Arrays.asList(labels), 1);
+-    assertThat(categories.toArray())
+-        .isEqualTo(new String[] {"background", "apple", "apple", "banana", "banana", "banana"});
+-  }
++    @Test
++    public void mapIndexToStringsWithInvalidValues() {
++        String[] labels = new String[] {"background", "apple", "banana", "cherry", "date"};
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
++        tensorBuffer.loadArray(new int[] {0, 1, 2, 3, 2, 5}, new int[] {1, 6});
++        List<String> categories =
++                LabelUtil.mapValueToLabels(tensorBuffer, Arrays.asList(labels), 1);
++        assertThat(categories.toArray())
++                .isEqualTo(new String[] {"apple", "banana", "cherry", "date", "cherry", ""});
++    }
++
++    @Test
++    public void mapFloatIndexShouldCast() {
++        String[] labels = new String[] {"background", "apple", "banana", "cherry", "date"};
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++        tensorBuffer.loadArray(new float[] {-1.1f, -0.3f, 0.3f, 1.2f, 1.8f, 1}, new int[] {1, 6});
++        List<String> categories =
++                LabelUtil.mapValueToLabels(tensorBuffer, Arrays.asList(labels), 1);
++        assertThat(categories.toArray())
++                .isEqualTo(new String[] {
++                        "background", "apple", "apple", "banana", "banana", "banana"});
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java
+index 4f296b7476c2d..857a77a2a4bd4 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java
+@@ -17,10 +17,6 @@ package org.tensorflow.lite.support.label;
+ 
+ import static com.google.common.truth.Truth.assertThat;
+ 
+-import java.util.Arrays;
+-import java.util.HashMap;
+-import java.util.List;
+-import java.util.Map;
+ import org.junit.Assert;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -28,169 +24,180 @@ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.DataType;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.util.Arrays;
++import java.util.HashMap;
++import java.util.List;
++import java.util.Map;
++
+ /** Tests of {@link org.tensorflow.lite.support.label.TensorLabel}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class TensorLabelTest {
+-  @Test
+-  public void createTensorLabelWithNullAxisLabelsShouldFail() {
+-    int[] shape = {2};
+-    int[] arr = {1, 2};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    buffer.loadArray(arr, shape);
+-    Map<Integer, List<String>> nullAxisLabels = null;
+-
+-    Assert.assertThrows(NullPointerException.class, () -> new TensorLabel(nullAxisLabels, buffer));
+-  }
+-
+-  @Test
+-  public void createTensorLabelWithNullTensorBufferShouldFail() {
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
+-    TensorBuffer nullTensorBuffer = null;
+-
+-    Assert.assertThrows(
+-        NullPointerException.class, () -> new TensorLabel(axisLabels, nullTensorBuffer));
+-  }
+-
+-  @Test
+-  public void createTensorLabelWithStringListShouldSuccess() {
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {1, 4, 3}, DataType.FLOAT32);
+-
+-    TensorLabel tensorLabel = new TensorLabel(Arrays.asList("a", "b", "c", "d"), buffer);
+-
+-    assertThat(tensorLabel.getMapWithTensorBuffer()).isNotNull();
+-    assertThat(tensorLabel.getMapWithTensorBuffer().keySet()).contains("c"); // randomly pick one
+-  }
+-
+-  @Test
+-  public void createTensorLabelWithEmptyShapeShouldFail() {
+-    int[] shape = new int[] {};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
+-
+-    Assert.assertThrows(IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+-  }
+-
+-  @Test
+-  public void createTensorLabelWithMismatchedAxisShouldFail() {
+-    int[] shape = {1, 4};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    axisLabels.put(0, Arrays.asList("a", "b", "c", "d"));
+-
+-    Assert.assertThrows(IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+-  }
+-
+-  @Test
+-  public void createTensorLabelWithMismatchedShapeShouldFail() {
+-    int[] shape = {1, 3};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
+-
+-    Assert.assertThrows(IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+-  }
+-
+-  @Test
+-  public void getMapWithFloatBufferValuesShouldSuccess() {
+-    int numberLabel = 4;
+-    float[] inputArr = {0.5f, 0.2f, 0.2f, 0.1f};
+-    int[] shape = {1, numberLabel};
+-    TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    input.loadArray(inputArr, shape);
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    int labelAxis = 1;
+-    axisLabels.put(labelAxis, Arrays.asList("a", "b", "c", "d"));
+-
+-    TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
+-    Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
+-
+-    for (int i = 0; i < numberLabel; i++) {
+-      String label = axisLabels.get(labelAxis).get(i);
+-      assertThat(map).containsKey(label);
+-      float[] array = map.get(label).getFloatArray();
+-      assertThat(array).hasLength(1);
+-      assertThat(array[0]).isEqualTo(inputArr[i]);
++    @Test
++    public void createTensorLabelWithNullAxisLabelsShouldFail() {
++        int[] shape = {2};
++        int[] arr = {1, 2};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        buffer.loadArray(arr, shape);
++        Map<Integer, List<String>> nullAxisLabels = null;
++
++        Assert.assertThrows(
++                NullPointerException.class, () -> new TensorLabel(nullAxisLabels, buffer));
++    }
++
++    @Test
++    public void createTensorLabelWithNullTensorBufferShouldFail() {
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
++        TensorBuffer nullTensorBuffer = null;
++
++        Assert.assertThrows(
++                NullPointerException.class, () -> new TensorLabel(axisLabels, nullTensorBuffer));
++    }
++
++    @Test
++    public void createTensorLabelWithStringListShouldSuccess() {
++        TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {1, 4, 3}, DataType.FLOAT32);
++
++        TensorLabel tensorLabel = new TensorLabel(Arrays.asList("a", "b", "c", "d"), buffer);
++
++        assertThat(tensorLabel.getMapWithTensorBuffer()).isNotNull();
++        assertThat(tensorLabel.getMapWithTensorBuffer().keySet())
++                .contains("c"); // randomly pick one
++    }
++
++    @Test
++    public void createTensorLabelWithEmptyShapeShouldFail() {
++        int[] shape = new int[] {};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
++
++        Assert.assertThrows(
++                IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+     }
+-  }
+-
+-  @Test
+-  public void getMapWithIntBufferValuesShouldSuccess() {
+-    int numberLabel = 3;
+-    int[] inputArr = {1, 2, 0};
+-    int[] shape = {1, 1, numberLabel};
+-    TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    input.loadArray(inputArr, shape);
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    int labelAxis = 2;
+-    axisLabels.put(labelAxis, Arrays.asList("x", "y", "z"));
+-
+-    TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
+-    Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
+-
+-    for (int i = 0; i < numberLabel; i++) {
+-      String label = axisLabels.get(labelAxis).get(i);
+-      assertThat(map).containsKey(label);
+-      int[] array = map.get(label).getIntArray();
+-      assertThat(array).hasLength(1);
+-      assertThat(array[0]).isEqualTo(inputArr[i]);
++
++    @Test
++    public void createTensorLabelWithMismatchedAxisShouldFail() {
++        int[] shape = {1, 4};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        axisLabels.put(0, Arrays.asList("a", "b", "c", "d"));
++
++        Assert.assertThrows(
++                IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+     }
+-  }
+-
+-  @Test
+-  public void getFloatMapShouldSuccess() {
+-    int[] shape = {1, 3};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    buffer.loadArray(new float[] {1.0f, 2.0f, 3.0f});
+-
+-    TensorLabel tensorLabeled = new TensorLabel(Arrays.asList("a", "b", "c"), buffer);
+-    Map<String, Float> map = tensorLabeled.getMapWithFloatValue();
+-
+-    assertThat(map).hasSize(3);
+-    assertThat(map).containsEntry("a", 1.0f);
+-    assertThat(map).containsEntry("b", 2.0f);
+-    assertThat(map).containsEntry("c", 3.0f);
+-  }
+-
+-  @Test
+-  public void getMapFromMultiDimensionalTensorBufferShouldSuccess() {
+-    int numberLabel = 2;
+-    int numDim = 3;
+-    float[] inputArr = {0.5f, 0.1f, 0.3f, 0.2f, 0.2f, 0.1f};
+-    int[] shape = {numberLabel, numDim};
+-    TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    input.loadArray(inputArr, shape);
+-    Map<Integer, List<String>> axisLabels = new HashMap<>();
+-    int labelAxis = 0;
+-    axisLabels.put(labelAxis, Arrays.asList("pos", "neg"));
+-
+-    TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
+-    Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
+-
+-    for (int i = 0; i < numberLabel; i++) {
+-      String label = axisLabels.get(labelAxis).get(i);
+-      assertThat(map).containsKey(label);
+-
+-      float[] array = map.get(label).getFloatArray();
+-      assertThat(array).hasLength(numDim);
+-      for (int j = 0; j < numDim; j++) {
+-        assertThat(array[j]).isEqualTo(inputArr[i * numDim + j]);
+-      }
++
++    @Test
++    public void createTensorLabelWithMismatchedShapeShouldFail() {
++        int[] shape = {1, 3};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
++
++        Assert.assertThrows(
++                IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
++    }
++
++    @Test
++    public void getMapWithFloatBufferValuesShouldSuccess() {
++        int numberLabel = 4;
++        float[] inputArr = {0.5f, 0.2f, 0.2f, 0.1f};
++        int[] shape = {1, numberLabel};
++        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        input.loadArray(inputArr, shape);
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        int labelAxis = 1;
++        axisLabels.put(labelAxis, Arrays.asList("a", "b", "c", "d"));
++
++        TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
++        Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
++
++        for (int i = 0; i < numberLabel; i++) {
++            String label = axisLabels.get(labelAxis).get(i);
++            assertThat(map).containsKey(label);
++            float[] array = map.get(label).getFloatArray();
++            assertThat(array).hasLength(1);
++            assertThat(array[0]).isEqualTo(inputArr[i]);
++        }
+     }
+-  }
+ 
+-  @Test
+-  public void getCategoryListShouldSuccess() {
+-    int[] shape = {1, 3};
+-    TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    buffer.loadArray(new float[] {1.0f, 2.0f, 3.0f});
++    @Test
++    public void getMapWithIntBufferValuesShouldSuccess() {
++        int numberLabel = 3;
++        int[] inputArr = {1, 2, 0};
++        int[] shape = {1, 1, numberLabel};
++        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        input.loadArray(inputArr, shape);
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        int labelAxis = 2;
++        axisLabels.put(labelAxis, Arrays.asList("x", "y", "z"));
++
++        TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
++        Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
++
++        for (int i = 0; i < numberLabel; i++) {
++            String label = axisLabels.get(labelAxis).get(i);
++            assertThat(map).containsKey(label);
++            int[] array = map.get(label).getIntArray();
++            assertThat(array).hasLength(1);
++            assertThat(array[0]).isEqualTo(inputArr[i]);
++        }
++    }
+ 
+-    TensorLabel tensorLabeled = new TensorLabel(Arrays.asList("a", "b", "c"), buffer);
+-    List<Category> categories = tensorLabeled.getCategoryList();
++    @Test
++    public void getFloatMapShouldSuccess() {
++        int[] shape = {1, 3};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        buffer.loadArray(new float[] {1.0f, 2.0f, 3.0f});
+ 
+-    assertThat(categories).hasSize(3);
+-    assertThat(categories)
+-        .containsExactly(new Category("a", 1.0f), new Category("b", 2.0f), new Category("c", 3.0f));
+-  }
++        TensorLabel tensorLabeled = new TensorLabel(Arrays.asList("a", "b", "c"), buffer);
++        Map<String, Float> map = tensorLabeled.getMapWithFloatValue();
++
++        assertThat(map).hasSize(3);
++        assertThat(map).containsEntry("a", 1.0f);
++        assertThat(map).containsEntry("b", 2.0f);
++        assertThat(map).containsEntry("c", 3.0f);
++    }
++
++    @Test
++    public void getMapFromMultiDimensionalTensorBufferShouldSuccess() {
++        int numberLabel = 2;
++        int numDim = 3;
++        float[] inputArr = {0.5f, 0.1f, 0.3f, 0.2f, 0.2f, 0.1f};
++        int[] shape = {numberLabel, numDim};
++        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        input.loadArray(inputArr, shape);
++        Map<Integer, List<String>> axisLabels = new HashMap<>();
++        int labelAxis = 0;
++        axisLabels.put(labelAxis, Arrays.asList("pos", "neg"));
++
++        TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
++        Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
++
++        for (int i = 0; i < numberLabel; i++) {
++            String label = axisLabels.get(labelAxis).get(i);
++            assertThat(map).containsKey(label);
++
++            float[] array = map.get(label).getFloatArray();
++            assertThat(array).hasLength(numDim);
++            for (int j = 0; j < numDim; j++) {
++                assertThat(array[j]).isEqualTo(inputArr[i * numDim + j]);
++            }
++        }
++    }
++
++    @Test
++    public void getCategoryListShouldSuccess() {
++        int[] shape = {1, 3};
++        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        buffer.loadArray(new float[] {1.0f, 2.0f, 3.0f});
++
++        TensorLabel tensorLabeled = new TensorLabel(Arrays.asList("a", "b", "c"), buffer);
++        List<Category> categories = tensorLabeled.getCategoryList();
++
++        assertThat(categories).hasSize(3);
++        assertThat(categories)
++                .containsExactly(
++                        new Category("a", 1.0f), new Category("b", 2.0f), new Category("c", 3.0f));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java
+index 8fa8860a09ef5..c1afe99f34f34 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java
+@@ -18,11 +18,9 @@ package org.tensorflow.lite.support.label.ops;
+ import static com.google.common.truth.Truth.assertThat;
+ 
+ import android.content.Context;
++
+ import androidx.test.core.app.ApplicationProvider;
+-import java.io.IOException;
+-import java.util.Arrays;
+-import java.util.List;
+-import java.util.Map;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+@@ -31,90 +29,94 @@ import org.tensorflow.lite.support.common.FileUtil;
+ import org.tensorflow.lite.support.label.TensorLabel;
+ import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+ 
++import java.io.IOException;
++import java.util.Arrays;
++import java.util.List;
++import java.util.Map;
++
+ /** Tests of {@link org.tensorflow.lite.support.label.ops.LabelAxisOp}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class LabelAxisOpTest {
++    private final Context context = ApplicationProvider.getApplicationContext();
++    private static final String LABEL_PATH = "flower_labels.txt";
++
++    @Test
++    public void testAddAxisLabelByStringList() {
++        int numberLabel = 2;
++        float[] inputArr = {0.7f, 0.3f};
++
++        int[] shape = {numberLabel};
++        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        input.loadArray(inputArr, shape);
++
++        List<String> labels = Arrays.asList("pos", "neg");
++        LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(0, labels).build();
++        TensorLabel output = op.apply(input);
++        Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
++
++        assertThat(map).containsKey("pos");
++        float[] array = map.get("pos").getFloatArray();
++        assertThat(array).hasLength(1);
++        assertThat(array[0]).isEqualTo(0.7f);
++
++        assertThat(map).containsKey("neg");
++        array = map.get("neg").getFloatArray();
++        assertThat(array).hasLength(1);
++        assertThat(array[0]).isEqualTo(0.3f);
++    }
++
++    @Test
++    public void testAddAxisLabelWithMultiDimensionTensor() throws IOException {
++        int numberLabel = 2;
++        int numDim = 3;
++        float[] inputArr = {0.5f, 0.1f, 0.3f, 0.2f, 0.2f, 0.1f};
++
++        int[] shape = {1, numberLabel, numDim};
++        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        input.loadArray(inputArr, shape);
+ 
+-  private final Context context = ApplicationProvider.getApplicationContext();
+-  private static final String LABEL_PATH = "flower_labels.txt";
+-
+-  @Test
+-  public void testAddAxisLabelByStringList() {
+-    int numberLabel = 2;
+-    float[] inputArr = {0.7f, 0.3f};
+-
+-    int[] shape = {numberLabel};
+-    TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    input.loadArray(inputArr, shape);
+-
+-    List<String> labels = Arrays.asList("pos", "neg");
+-    LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(0, labels).build();
+-    TensorLabel output = op.apply(input);
+-    Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
+-
+-    assertThat(map).containsKey("pos");
+-    float[] array = map.get("pos").getFloatArray();
+-    assertThat(array).hasLength(1);
+-    assertThat(array[0]).isEqualTo(0.7f);
+-
+-    assertThat(map).containsKey("neg");
+-    array = map.get("neg").getFloatArray();
+-    assertThat(array).hasLength(1);
+-    assertThat(array[0]).isEqualTo(0.3f);
+-  }
+-
+-  @Test
+-  public void testAddAxisLabelWithMultiDimensionTensor() throws IOException {
+-    int numberLabel = 2;
+-    int numDim = 3;
+-    float[] inputArr = {0.5f, 0.1f, 0.3f, 0.2f, 0.2f, 0.1f};
+-
+-    int[] shape = {1, numberLabel, numDim};
+-    TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    input.loadArray(inputArr, shape);
+-
+-    List<String> labels = Arrays.asList("pos", "neg");
+-    LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(1, labels).build();
+-
+-    TensorLabel output = op.apply(input);
+-    Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
+-
+-    assertThat(map).containsKey("pos");
+-    float[] array = map.get("pos").getFloatArray();
+-    assertThat(array).hasLength(numDim);
+-    assertThat(array).isEqualTo(new float[] {0.5f, 0.1f, 0.3f});
+-
+-    assertThat(map).containsKey("neg");
+-    array = map.get("neg").getFloatArray();
+-    assertThat(array).hasLength(numDim);
+-    assertThat(array).isEqualTo(new float[] {0.2f, 0.2f, 0.1f});
+-  }
+-
+-  @Test
+-  public void testAddAxisLabelByFilePath() throws IOException {
+-    int numberLabel = 5;
+-    int[] inputArr = new int[numberLabel];
+-    for (int i = 0; i < numberLabel; i++) {
+-      inputArr[i] = i;
++        List<String> labels = Arrays.asList("pos", "neg");
++        LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(1, labels).build();
++
++        TensorLabel output = op.apply(input);
++        Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
++
++        assertThat(map).containsKey("pos");
++        float[] array = map.get("pos").getFloatArray();
++        assertThat(array).hasLength(numDim);
++        assertThat(array).isEqualTo(new float[] {0.5f, 0.1f, 0.3f});
++
++        assertThat(map).containsKey("neg");
++        array = map.get("neg").getFloatArray();
++        assertThat(array).hasLength(numDim);
++        assertThat(array).isEqualTo(new float[] {0.2f, 0.2f, 0.1f});
+     }
+ 
+-    int[] shape = {numberLabel};
+-    TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    input.loadArray(inputArr, shape);
++    @Test
++    public void testAddAxisLabelByFilePath() throws IOException {
++        int numberLabel = 5;
++        int[] inputArr = new int[numberLabel];
++        for (int i = 0; i < numberLabel; i++) {
++            inputArr[i] = i;
++        }
++
++        int[] shape = {numberLabel};
++        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        input.loadArray(inputArr, shape);
+ 
+-    LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(context, 0, LABEL_PATH).build();
+-    TensorLabel output = op.apply(input);
+-    Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
++        LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(context, 0, LABEL_PATH).build();
++        TensorLabel output = op.apply(input);
++        Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
+ 
+-    List<String> labels = FileUtil.loadLabels(context, LABEL_PATH);
+-    for (int i = 0; i < numberLabel; i++) {
+-      String label = labels.get(i);
++        List<String> labels = FileUtil.loadLabels(context, LABEL_PATH);
++        for (int i = 0; i < numberLabel; i++) {
++            String label = labels.get(i);
+ 
+-      assertThat(map).containsKey(label);
++            assertThat(map).containsKey(label);
+ 
+-      int[] array = map.get(label).getIntArray();
+-      assertThat(array).hasLength(1);
+-      assertThat(array[0]).isEqualTo(inputArr[i]);
++            int[] array = map.get(label).getIntArray();
++            assertThat(array).hasLength(1);
++            assertThat(array[0]).isEqualTo(inputArr[i]);
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java
+index bd59051ce4ccb..d7449187cb54c 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java
+@@ -17,6 +17,7 @@ package org.tensorflow.lite.support.model;
+ import static com.google.common.truth.Truth.assertThat;
+ 
+ import androidx.test.ext.junit.runners.AndroidJUnit4;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ 
+@@ -27,13 +28,12 @@ import org.junit.runner.RunWith;
+  */
+ @RunWith(AndroidJUnit4.class)
+ public final class GpuDelegateProxyInstrumentedTest {
+-
+-  @Test
+-  public void createGpuDelegateProxyShouldSuccess() {
+-    GpuDelegateProxy proxy = GpuDelegateProxy.maybeNewInstance();
+-
+-    assertThat(proxy).isNotNull();
+-    proxy.getNativeHandle();
+-    proxy.close();
+-  }
++    @Test
++    public void createGpuDelegateProxyShouldSuccess() {
++        GpuDelegateProxy proxy = GpuDelegateProxy.maybeNewInstance();
++
++        assertThat(proxy).isNotNull();
++        proxy.getNativeHandle();
++        proxy.close();
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java
+index c1bbcc223a895..4eb2e2920c3bc 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java
+@@ -23,11 +23,10 @@ import org.robolectric.RobolectricTestRunner;
+ /** Tests of {@link org.tensorflow.lite.support.model.GpuDelegateProxy}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class GpuDelegateProxyTest {
++    @Test
++    public void createGpuDelegateProxyWithoutDependencyShouldReturnNull() {
++        GpuDelegateProxy proxy = GpuDelegateProxy.maybeNewInstance();
+ 
+-  @Test
+-  public void createGpuDelegateProxyWithoutDependencyShouldReturnNull() {
+-    GpuDelegateProxy proxy = GpuDelegateProxy.maybeNewInstance();
+-
+-    assertThat(proxy).isNull();
+-  }
++        assertThat(proxy).isNull();
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java
+index 86e4f72769216..342e82b2de3bb 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java
+@@ -16,143 +16,145 @@ limitations under the License.
+ package org.tensorflow.lite.support.model;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.fail;
+ 
+ import android.content.Context;
++
+ import androidx.test.core.app.ApplicationProvider;
+-import java.io.IOException;
+-import java.nio.MappedByteBuffer;
+-import java.util.HashMap;
+-import java.util.Map;
++
++import org.junit.Ignore;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.support.model.Model.Device;
+ import org.tensorflow.lite.support.model.Model.Options;
+ 
+-import org.junit.Ignore;
++import java.io.IOException;
++import java.nio.MappedByteBuffer;
++import java.util.HashMap;
++import java.util.Map;
+ 
+ /** Tests of {@link org.tensorflow.lite.support.model.Model}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class ModelTest {
++    private final Context context = ApplicationProvider.getApplicationContext();
++    private static final String MODEL_PATH = "add.tflite";
++
++    @Ignore
++    @Test
++    public void testLoadLocalModel() throws IOException {
++        MappedByteBuffer byteModel = new Model.Builder(context, MODEL_PATH).build().getData();
++        assertThat(byteModel).isNotNull();
++    }
++
++    @Ignore
++    @Test
++    public void testBuildMultiThreadModel() throws IOException {
++        MappedByteBuffer byteModel =
++                new Model.Builder(context, MODEL_PATH).setNumThreads(4).build().getData();
++        assertThat(byteModel).isNotNull();
++    }
++
++    @Ignore
++    @Test
++    public void buildModelWithOptionsShouldSuccess() throws IOException {
++        Options options = new Options.Builder().setNumThreads(2).setDevice(Device.NNAPI).build();
++        Model model = Model.createModel(context, MODEL_PATH, options);
++        assertThat(model.getData()).isNotNull();
++    }
+ 
+-  private final Context context = ApplicationProvider.getApplicationContext();
+-  private static final String MODEL_PATH = "add.tflite";
+-
+-  @Ignore
+-  @Test
+-  public void testLoadLocalModel() throws IOException {
+-    MappedByteBuffer byteModel = new Model.Builder(context, MODEL_PATH).build().getData();
+-    assertThat(byteModel).isNotNull();
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testBuildMultiThreadModel() throws IOException {
+-    MappedByteBuffer byteModel =
+-        new Model.Builder(context, MODEL_PATH).setNumThreads(4).build().getData();
+-    assertThat(byteModel).isNotNull();
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void buildModelWithOptionsShouldSuccess() throws IOException {
+-    Options options = new Options.Builder().setNumThreads(2).setDevice(Device.NNAPI).build();
+-    Model model = Model.createModel(context, MODEL_PATH, options);
+-    assertThat(model.getData()).isNotNull();
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testGetModelPath() throws IOException {
+-    String modelPath = new Model.Builder(context, MODEL_PATH).build().getPath();
+-    assertThat(modelPath).isEqualTo(MODEL_PATH);
+-  }
+-
+-  @Test
+-  public void testNonExistingLocalModel() {
+-    try {
+-      new Model.Builder(context, "non_exist_model_file").build();
+-      fail();
+-    } catch (IOException e) {
+-      assertThat(e).hasMessageThat().contains("non_exist_model_file");
++    @Ignore
++    @Test
++    public void testGetModelPath() throws IOException {
++        String modelPath = new Model.Builder(context, MODEL_PATH).build().getPath();
++        assertThat(modelPath).isEqualTo(MODEL_PATH);
+     }
+-  }
+-
+-  @Test
+-  public void testNullLocalModelPath() throws IOException {
+-    try {
+-      new Model.Builder(context, null).build();
+-      fail();
+-    } catch (NullPointerException e) {
+-      assertThat(e).hasMessageThat().contains("File path cannot be null.");
++
++    @Test
++    public void testNonExistingLocalModel() {
++        try {
++            new Model.Builder(context, "non_exist_model_file").build();
++            fail();
++        } catch (IOException e) {
++            assertThat(e).hasMessageThat().contains("non_exist_model_file");
++        }
+     }
+-  }
+-
+-  @Test
+-  public void testNullContext() throws IOException {
+-    try {
+-      new Model.Builder(null, MODEL_PATH).build();
+-      fail();
+-    } catch (NullPointerException e) {
+-      assertThat(e).hasMessageThat().contains("Context should not be null.");
++
++    @Test
++    public void testNullLocalModelPath() throws IOException {
++        try {
++            new Model.Builder(context, null).build();
++            fail();
++        } catch (NullPointerException e) {
++            assertThat(e).hasMessageThat().contains("File path cannot be null.");
++        }
++    }
++
++    @Test
++    public void testNullContext() throws IOException {
++        try {
++            new Model.Builder(null, MODEL_PATH).build();
++            fail();
++        } catch (NullPointerException e) {
++            assertThat(e).hasMessageThat().contains("Context should not be null.");
++        }
++    }
++
++    @Ignore
++    @Test
++    public void testGetInputTensor() throws IOException {
++        Options options = new Options.Builder().build();
++        Model model = Model.createModel(context, MODEL_PATH, options);
++        assertThat(model.getInputTensor(0)).isNotNull();
++    }
++
++    @Ignore
++    @Test
++    public void testGetOutputTensor() throws IOException {
++        Options options = new Options.Builder().build();
++        Model model = Model.createModel(context, MODEL_PATH, options);
++        assertThat(model.getOutputTensor(0)).isNotNull();
++    }
++
++    @Ignore
++    @Test
++    public void testRun() throws IOException {
++        Context context = ApplicationProvider.getApplicationContext();
++        Model model = new Model.Builder(context, MODEL_PATH).build();
++        runModel(model);
++    }
++
++    @Ignore
++    @Test
++    public void testMultiThreadingRun() throws IOException {
++        Context context = ApplicationProvider.getApplicationContext();
++        Model model = new Model.Builder(context, MODEL_PATH).setNumThreads(4).build();
++        runModel(model);
++    }
++
++    @Ignore
++    @Test
++    public void testNnApiRun() throws IOException {
++        Context context = ApplicationProvider.getApplicationContext();
++        Model model = new Model.Builder(context, MODEL_PATH).setDevice(Device.NNAPI).build();
++        runModel(model);
++    }
++
++    private static void runModel(Model model) throws IOException {
++        // Creates the inputs.
++        float[] x = {1.5f};
++        float[] y = {0.5f};
++        float[] expectedSum = {2.0f};
++        Object[] inputs = {x, y};
++
++        // Creates the outputs buffer.
++        float[] sum = new float[1];
++        Map<Integer, Object> outputs = new HashMap<>();
++        outputs.put(0, sum);
++
++        // Runs inference.
++        model.run(inputs, outputs);
++        assertThat(sum).isEqualTo(expectedSum);
+     }
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testGetInputTensor() throws IOException {
+-    Options options = new Options.Builder().build();
+-    Model model = Model.createModel(context, MODEL_PATH, options);
+-    assertThat(model.getInputTensor(0)).isNotNull();
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testGetOutputTensor() throws IOException {
+-    Options options = new Options.Builder().build();
+-    Model model = Model.createModel(context, MODEL_PATH, options);
+-    assertThat(model.getOutputTensor(0)).isNotNull();
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testRun() throws IOException {
+-    Context context = ApplicationProvider.getApplicationContext();
+-    Model model = new Model.Builder(context, MODEL_PATH).build();
+-    runModel(model);
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testMultiThreadingRun() throws IOException {
+-    Context context = ApplicationProvider.getApplicationContext();
+-    Model model = new Model.Builder(context, MODEL_PATH).setNumThreads(4).build();
+-    runModel(model);
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void testNnApiRun() throws IOException {
+-    Context context = ApplicationProvider.getApplicationContext();
+-    Model model = new Model.Builder(context, MODEL_PATH).setDevice(Device.NNAPI).build();
+-    runModel(model);
+-  }
+-
+-  private static void runModel(Model model) throws IOException {
+-    // Creates the inputs.
+-    float[] x = {1.5f};
+-    float[] y = {0.5f};
+-    float[] expectedSum = {2.0f};
+-    Object[] inputs = {x, y};
+-
+-    // Creates the outputs buffer.
+-    float[] sum = new float[1];
+-    Map<Integer, Object> outputs = new HashMap<>();
+-    outputs.put(0, sum);
+-
+-    // Runs inference.
+-    model.run(inputs, outputs);
+-    assertThat(sum).isEqualTo(expectedSum);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java
+index 3a4d09d8e5701..82b59b36155f3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java
+@@ -26,51 +26,51 @@ import org.tensorflow.lite.DataType;
+ /** Tests of {@link org.tensorflow.lite.support.tensorbuffer.TensorBufferFloat}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class TensorBufferFloatTest {
+-  @Test
+-  public void testCreateDynamic() {
+-    TensorBufferFloat tensorBufferFloat = new TensorBufferFloat();
+-    assertThat(tensorBufferFloat).isNotNull();
+-  }
++    @Test
++    public void testCreateDynamic() {
++        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat();
++        assertThat(tensorBufferFloat).isNotNull();
++    }
+ 
+-  @Test
+-  public void testCreateFixedSize() {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
+-    assertThat(tensorBufferFloat).isNotNull();
+-    assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(6);
+-  }
++    @Test
++    public void testCreateFixedSize() {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
++        assertThat(tensorBufferFloat).isNotNull();
++        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(6);
++    }
+ 
+-  @Test
+-  public void testCreateFixedSizeWithScalarShape() {
+-    int[] shape = new int[] {};
+-    TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
+-    assertThat(tensorBufferFloat).isNotNull();
+-    assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(1);
+-  }
++    @Test
++    public void testCreateFixedSizeWithScalarShape() {
++        int[] shape = new int[] {};
++        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
++        assertThat(tensorBufferFloat).isNotNull();
++        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(1);
++    }
+ 
+-  @Test
+-  public void testCreateWithNullShape() {
+-    int[] shape = null;
+-    Assert.assertThrows(NullPointerException.class, () -> new TensorBufferFloat(shape));
+-  }
++    @Test
++    public void testCreateWithNullShape() {
++        int[] shape = null;
++        Assert.assertThrows(NullPointerException.class, () -> new TensorBufferFloat(shape));
++    }
+ 
+-  @Test
+-  public void testCreateWithInvalidShape() {
+-    int[] shape = new int[] {1, -1, 2};
+-    Assert.assertThrows(IllegalArgumentException.class, () -> new TensorBufferFloat(shape));
+-  }
++    @Test
++    public void testCreateWithInvalidShape() {
++        int[] shape = new int[] {1, -1, 2};
++        Assert.assertThrows(IllegalArgumentException.class, () -> new TensorBufferFloat(shape));
++    }
+ 
+-  @Test
+-  public void testCreateUsingShapeWithZero() {
+-    int[] shape = new int[] {1, 0, 2};
+-    TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
+-    assertThat(tensorBufferFloat).isNotNull();
+-    assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(0);
+-  }
++    @Test
++    public void testCreateUsingShapeWithZero() {
++        int[] shape = new int[] {1, 0, 2};
++        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
++        assertThat(tensorBufferFloat).isNotNull();
++        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(0);
++    }
+ 
+-  @Test
+-  public void testGetDataType() {
+-    TensorBufferFloat tensorBufferFloat = new TensorBufferFloat();
+-    assertThat(tensorBufferFloat.getDataType()).isEqualTo(DataType.FLOAT32);
+-  }
++    @Test
++    public void testGetDataType() {
++        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat();
++        assertThat(tensorBufferFloat.getDataType()).isEqualTo(DataType.FLOAT32);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java
+index c55affe733eac..763356f493390 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java
+@@ -16,877 +16,878 @@ limitations under the License.
+ package org.tensorflow.lite.support.tensorbuffer;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+-import java.io.IOException;
+-import java.nio.ByteBuffer;
+-import java.nio.FloatBuffer;
+-import java.util.ArrayList;
+ import org.junit.Assert;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ import org.tensorflow.lite.DataType;
+ 
++import java.io.IOException;
++import java.nio.ByteBuffer;
++import java.nio.FloatBuffer;
++import java.util.ArrayList;
++
+ /** Test helper class for inserting and retrieving arrays. */
+ class ArrayTestRunner {
+-  // List of TensorBuffer types to be tested.
+-  private static final DataType[] BUFFER_TYPE_LIST = {DataType.FLOAT32, DataType.UINT8};
+-  // List of source arrays to be loaded into TensorBuffer during the tests.
+-  private final ArrayList<Object> srcArrays;
+-  // List of array data type with respect to srcArrays.
+-  private final ArrayList<DataType> arrDataTypes;
+-  // List of array shape with respect to srcArrays.
+-  private final ArrayList<int[]> arrShapes;
+-  private final int[] tensorBufferShape;
+-  private final ExpectedResults expectedResForFloatBuf;
+-  private final ExpectedResults expectedResForByteBuf;
+-
+-  public ArrayTestRunner(Builder builder) {
+-    if (builder.srcArrays.size() != builder.arrDataTypes.size()) {
+-      throw new IllegalArgumentException(
+-          "Number of source arrays and number of data types do not match.");
+-    }
+-
+-    this.srcArrays = builder.srcArrays;
+-    this.arrDataTypes = builder.arrDataTypes;
+-    this.arrShapes = builder.arrShapes;
+-    this.tensorBufferShape = builder.tensorBufferShape;
+-    this.expectedResForFloatBuf = builder.expectedResForFloatBuf;
+-    this.expectedResForByteBuf = builder.expectedResForByteBuf;
+-  }
+-
+-  static class ExpectedResults {
+-    public float[] floatArr;
+-    public int[] intArr;
+-    public int[] shape;
+-  }
+-
+-  public static class Builder {
+-    private final ArrayList<Object> srcArrays = new ArrayList<>();
+-    private final ArrayList<DataType> arrDataTypes = new ArrayList<>();
+-    private final ArrayList<int[]> arrShapes = new ArrayList<>();
+-    private int[] tensorBufferShape;
+-    private final ExpectedResults expectedResForFloatBuf = new ExpectedResults();
+-    private final ExpectedResults expectedResForByteBuf = new ExpectedResults();
+-
+-    public static Builder newInstance() {
+-      return new Builder();
+-    }
+-
+-    private Builder() {}
+-
+-    /** Loads a test array into the test runner. */
+-    public Builder addSrcArray(Object src, int[] shape) {
+-      // src should be a primitive 1D array.
+-      DataType dataType = dataTypeOfArray(src);
+-      switch (dataType) {
+-        case INT32:
+-        case FLOAT32:
+-          srcArrays.add(src);
+-          arrDataTypes.add(dataType);
+-          arrShapes.add(shape);
+-          return this;
+-        default:
+-          throw new AssertionError("Cannot resolve srouce arrays in the DataType of " + dataType);
+-      }
+-    }
+-
+-    public Builder setTensorBufferShape(int[] tensorBufferShape) {
+-      this.tensorBufferShape = tensorBufferShape;
+-      return this;
+-    }
+-
+-    public Builder setExpectedResults(
+-        DataType bufferType, float[] expectedFloatArr, int[] expectedIntArr) {
+-      ExpectedResults er;
+-      switch (bufferType) {
+-        case UINT8:
+-          er = expectedResForByteBuf;
+-          break;
+-        case FLOAT32:
+-          er = expectedResForFloatBuf;
+-          break;
+-        default:
+-          throw new AssertionError("Cannot test TensorBuffer in the DataType of " + bufferType);
+-      }
+-
+-      er.floatArr = expectedFloatArr;
+-      er.intArr = expectedIntArr;
+-      return this;
+-    }
+-
+-    public ArrayTestRunner build() {
+-      int[] expectedShape;
+-      if (arrShapes.isEmpty()) {
+-        // If no array will be loaded, the array is an empty array.
+-        expectedShape = new int[] {0};
+-      } else {
+-        expectedShape = arrShapes.get(arrShapes.size() - 1);
+-      }
+-      expectedResForByteBuf.shape = expectedShape;
+-      expectedResForFloatBuf.shape = expectedShape;
+-      return new ArrayTestRunner(this);
+-    }
+-  }
+-
+-  public static DataType[] getBufferTypeList() {
+-    return BUFFER_TYPE_LIST;
+-  }
+-
+-  /**
+-   * Runs tests in the following steps: 1. Create a TensorBuffer. If tensorBufferShape is null,
+-   * create a dynamic buffer. Otherwise, create a fixed-size buffer accordingly. 2. Load arrays in
+-   * srcArrays one by one into the TensotBuffer. 3. Get arrays for each supported primitive types in
+-   * TensorBuffer, such as int array and float array for now. Check if the results are correct. 4.
+-   * Repeat Step 1 to 3 for all buffer types in BUFFER_TYPE_LIST.
+-   */
+-  public void run() {
+-    for (DataType bufferDataType : BUFFER_TYPE_LIST) {
+-      TensorBuffer tensorBuffer;
+-      if (tensorBufferShape == null) {
+-        tensorBuffer = TensorBuffer.createDynamic(bufferDataType);
+-      } else {
+-        tensorBuffer = TensorBuffer.createFixedSize(tensorBufferShape, bufferDataType);
+-      }
+-      for (int i = 0; i < srcArrays.size(); i++) {
+-        switch (arrDataTypes.get(i)) {
+-          case INT32:
+-            int[] arrInt = (int[]) srcArrays.get(i);
+-            tensorBuffer.loadArray(arrInt, arrShapes.get(i));
+-            break;
+-          case FLOAT32:
+-            float[] arrFloat = (float[]) srcArrays.get(i);
+-            tensorBuffer.loadArray(arrFloat, arrShapes.get(i));
+-            break;
+-          default:
+-            break;
++    // List of TensorBuffer types to be tested.
++    private static final DataType[] BUFFER_TYPE_LIST = {DataType.FLOAT32, DataType.UINT8};
++    // List of source arrays to be loaded into TensorBuffer during the tests.
++    private final ArrayList<Object> srcArrays;
++    // List of array data type with respect to srcArrays.
++    private final ArrayList<DataType> arrDataTypes;
++    // List of array shape with respect to srcArrays.
++    private final ArrayList<int[]> arrShapes;
++    private final int[] tensorBufferShape;
++    private final ExpectedResults expectedResForFloatBuf;
++    private final ExpectedResults expectedResForByteBuf;
++
++    public ArrayTestRunner(Builder builder) {
++        if (builder.srcArrays.size() != builder.arrDataTypes.size()) {
++            throw new IllegalArgumentException(
++                    "Number of source arrays and number of data types do not match.");
+         }
+-      }
+-      checkResults(tensorBuffer);
+-    }
+-  }
+-
+-  private void checkResults(TensorBuffer tensorBuffer) {
+-    ExpectedResults er;
+-    switch (tensorBuffer.getDataType()) {
+-      case UINT8:
+-        er = expectedResForByteBuf;
+-        break;
+-      case FLOAT32:
+-        er = expectedResForFloatBuf;
+-        break;
+-      default:
+-        throw new AssertionError(
+-            "Cannot test TensorBuffer in the DataType of " + tensorBuffer.getDataType());
+-    }
+-
+-    // Checks getIntArray() and getFloatArray().
+-    int[] resIntArr = tensorBuffer.getIntArray();
+-    assertThat(resIntArr).isEqualTo(er.intArr);
+-    float[] resFloatArr = tensorBuffer.getFloatArray();
+-    assertThat(resFloatArr).isEqualTo(er.floatArr);
+-    assertThat(tensorBuffer.getShape()).isEqualTo(er.shape);
+-
+-    // Checks getIntValue(int index) and getFloatValue(int index).
+-    int flatSize = tensorBuffer.getFlatSize();
+-    float[] resFloatValues = new float[flatSize];
+-    int[] resIntValues = new int[flatSize];
+-    for (int i = 0; i < flatSize; i++) {
+-      resFloatValues[i] = tensorBuffer.getFloatValue(i);
+-      resIntValues[i] = tensorBuffer.getIntValue(i);
+-    }
+-    assertThat(resFloatValues).isEqualTo(er.floatArr);
+-    assertThat(resIntValues).isEqualTo(er.intArr);
+-  }
+-
+-  /** Gets the data type of an 1D array. */
+-  private static DataType dataTypeOfArray(Object arr) {
+-    if (arr != null) {
+-      Class<?> c = arr.getClass();
+-      if (c.isArray()) {
+-        c = c.getComponentType();
+-        if (float.class.equals(c)) {
+-          return DataType.FLOAT32;
+-        } else if (int.class.equals(c)) {
+-          return DataType.INT32;
+-        } else if (byte.class.equals(c)) {
+-          return DataType.UINT8;
+-        } else if (long.class.equals(c)) {
+-          return DataType.INT64;
+-        } else if (String.class.equals(c)) {
+-          return DataType.STRING;
++
++        this.srcArrays = builder.srcArrays;
++        this.arrDataTypes = builder.arrDataTypes;
++        this.arrShapes = builder.arrShapes;
++        this.tensorBufferShape = builder.tensorBufferShape;
++        this.expectedResForFloatBuf = builder.expectedResForFloatBuf;
++        this.expectedResForByteBuf = builder.expectedResForByteBuf;
++    }
++
++    static class ExpectedResults {
++        public float[] floatArr;
++        public int[] intArr;
++        public int[] shape;
++    }
++
++    public static class Builder {
++        private final ArrayList<Object> srcArrays = new ArrayList<>();
++        private final ArrayList<DataType> arrDataTypes = new ArrayList<>();
++        private final ArrayList<int[]> arrShapes = new ArrayList<>();
++        private int[] tensorBufferShape;
++        private final ExpectedResults expectedResForFloatBuf = new ExpectedResults();
++        private final ExpectedResults expectedResForByteBuf = new ExpectedResults();
++
++        public static Builder newInstance() {
++            return new Builder();
++        }
++
++        private Builder() {}
++
++        /** Loads a test array into the test runner. */
++        public Builder addSrcArray(Object src, int[] shape) {
++            // src should be a primitive 1D array.
++            DataType dataType = dataTypeOfArray(src);
++            switch (dataType) {
++                case INT32:
++                case FLOAT32:
++                    srcArrays.add(src);
++                    arrDataTypes.add(dataType);
++                    arrShapes.add(shape);
++                    return this;
++                default:
++                    throw new AssertionError(
++                            "Cannot resolve srouce arrays in the DataType of " + dataType);
++            }
++        }
++
++        public Builder setTensorBufferShape(int[] tensorBufferShape) {
++            this.tensorBufferShape = tensorBufferShape;
++            return this;
+         }
+-      }
++
++        public Builder setExpectedResults(
++                DataType bufferType, float[] expectedFloatArr, int[] expectedIntArr) {
++            ExpectedResults er;
++            switch (bufferType) {
++                case UINT8:
++                    er = expectedResForByteBuf;
++                    break;
++                case FLOAT32:
++                    er = expectedResForFloatBuf;
++                    break;
++                default:
++                    throw new AssertionError(
++                            "Cannot test TensorBuffer in the DataType of " + bufferType);
++            }
++
++            er.floatArr = expectedFloatArr;
++            er.intArr = expectedIntArr;
++            return this;
++        }
++
++        public ArrayTestRunner build() {
++            int[] expectedShape;
++            if (arrShapes.isEmpty()) {
++                // If no array will be loaded, the array is an empty array.
++                expectedShape = new int[] {0};
++            } else {
++                expectedShape = arrShapes.get(arrShapes.size() - 1);
++            }
++            expectedResForByteBuf.shape = expectedShape;
++            expectedResForFloatBuf.shape = expectedShape;
++            return new ArrayTestRunner(this);
++        }
++    }
++
++    public static DataType[] getBufferTypeList() {
++        return BUFFER_TYPE_LIST;
++    }
++
++    /**
++     * Runs tests in the following steps: 1. Create a TensorBuffer. If tensorBufferShape is null,
++     * create a dynamic buffer. Otherwise, create a fixed-size buffer accordingly. 2. Load arrays in
++     * srcArrays one by one into the TensotBuffer. 3. Get arrays for each supported primitive types
++     * in TensorBuffer, such as int array and float array for now. Check if the results are
++     * correct. 4. Repeat Step 1 to 3 for all buffer types in BUFFER_TYPE_LIST.
++     */
++    public void run() {
++        for (DataType bufferDataType : BUFFER_TYPE_LIST) {
++            TensorBuffer tensorBuffer;
++            if (tensorBufferShape == null) {
++                tensorBuffer = TensorBuffer.createDynamic(bufferDataType);
++            } else {
++                tensorBuffer = TensorBuffer.createFixedSize(tensorBufferShape, bufferDataType);
++            }
++            for (int i = 0; i < srcArrays.size(); i++) {
++                switch (arrDataTypes.get(i)) {
++                    case INT32:
++                        int[] arrInt = (int[]) srcArrays.get(i);
++                        tensorBuffer.loadArray(arrInt, arrShapes.get(i));
++                        break;
++                    case FLOAT32:
++                        float[] arrFloat = (float[]) srcArrays.get(i);
++                        tensorBuffer.loadArray(arrFloat, arrShapes.get(i));
++                        break;
++                    default:
++                        break;
++                }
++            }
++            checkResults(tensorBuffer);
++        }
++    }
++
++    private void checkResults(TensorBuffer tensorBuffer) {
++        ExpectedResults er;
++        switch (tensorBuffer.getDataType()) {
++            case UINT8:
++                er = expectedResForByteBuf;
++                break;
++            case FLOAT32:
++                er = expectedResForFloatBuf;
++                break;
++            default:
++                throw new AssertionError("Cannot test TensorBuffer in the DataType of "
++                        + tensorBuffer.getDataType());
++        }
++
++        // Checks getIntArray() and getFloatArray().
++        int[] resIntArr = tensorBuffer.getIntArray();
++        assertThat(resIntArr).isEqualTo(er.intArr);
++        float[] resFloatArr = tensorBuffer.getFloatArray();
++        assertThat(resFloatArr).isEqualTo(er.floatArr);
++        assertThat(tensorBuffer.getShape()).isEqualTo(er.shape);
++
++        // Checks getIntValue(int index) and getFloatValue(int index).
++        int flatSize = tensorBuffer.getFlatSize();
++        float[] resFloatValues = new float[flatSize];
++        int[] resIntValues = new int[flatSize];
++        for (int i = 0; i < flatSize; i++) {
++            resFloatValues[i] = tensorBuffer.getFloatValue(i);
++            resIntValues[i] = tensorBuffer.getIntValue(i);
++        }
++        assertThat(resFloatValues).isEqualTo(er.floatArr);
++        assertThat(resIntValues).isEqualTo(er.intArr);
++    }
++
++    /** Gets the data type of an 1D array. */
++    private static DataType dataTypeOfArray(Object arr) {
++        if (arr != null) {
++            Class<?> c = arr.getClass();
++            if (c.isArray()) {
++                c = c.getComponentType();
++                if (float.class.equals(c)) {
++                    return DataType.FLOAT32;
++                } else if (int.class.equals(c)) {
++                    return DataType.INT32;
++                } else if (byte.class.equals(c)) {
++                    return DataType.UINT8;
++                } else if (long.class.equals(c)) {
++                    return DataType.INT64;
++                } else if (String.class.equals(c)) {
++                    return DataType.STRING;
++                }
++            }
++        }
++        throw new IllegalArgumentException(
++                "Requires a 1D array. Cannot resolve data type of " + arr.getClass().getName());
+     }
+-    throw new IllegalArgumentException(
+-        "Requires a 1D array. Cannot resolve data type of " + arr.getClass().getName());
+-  }
+ }
+ 
+ /** Tests of {@link org.tensorflow.lite.support.tensorbuffer.TensorBuffer}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class TensorBufferTest {
+-  // FLOAT_ARRAY1 and INT_ARRAY1 correspond to each other.
+-  private static final int[] ARRAY1_SHAPE = new int[] {2, 3};
+-  private static final float[] FLOAT_ARRAY1 = new float[] {500.1f, 4.2f, 3.3f, 2.4f, 1.5f, 6.1f};
+-  private static final float[] FLOAT_ARRAY1_ROUNDED =
+-      new float[] {500.0f, 4.0f, 3.0f, 2.0f, 1.0f, 6.0f};
+-  // FLOAT_ARRAY1_CAPPED and INT_ARRAY1_CAPPED correspond to the expected values when converted into
+-  // uint8.
+-  private static final float[] FLOAT_ARRAY1_CAPPED =
+-      new float[] {255.0f, 4.0f, 3.0f, 2.0f, 1.0f, 6.0f};
+-  private static final int[] INT_ARRAY1 = new int[] {500, 4, 3, 2, 1, 6};
+-  private static final int[] INT_ARRAY1_CAPPED = new int[] {255, 4, 3, 2, 1, 6};
+-  // FLOAT_ARRAY2 and INT_ARRAY2 correspond to each other.
+-  private static final int[] ARRAY2_SHAPE = new int[] {2, 1};
+-  private static final float[] FLOAT_ARRAY2 = new float[] {6.7f, 7.6f};
+-  private static final float[] FLOAT_ARRAY2_ROUNDED = new float[] {6.0f, 7.0f};
+-  private static final int[] INT_ARRAY2 = new int[] {6, 7};
+-  // FLOAT_ARRAY2 and FLOAT_ARRAY3 have the same size.
+-  private static final int[] ARRAY3_SHAPE = new int[] {2, 1};
+-  private static final float[] FLOAT_ARRAY3 = new float[] {8.2f, 9.9f};
+-  private static final float[] FLOAT_ARRAY3_ROUNDED = new float[] {8.0f, 9.0f};
+-  // INT_ARRAY2 and INT_ARRAY3 have the same size.
+-  private static final int[] INT_ARRAY3 = new int[] {8, 9};
+-  private static final int[] EMPTY_ARRAY_SHAPE = new int[] {0};
+-  private static final int[] EMPTY_INT_ARRAY = new int[0];
+-  private static final float[] EMPTY_FLOAT_ARRAY = new float[0];
+-  // Single element array which represents a scalar.
+-  private static final int[] SCALAR_ARRAY_SHAPE = new int[] {};
+-  private static final float[] FLOAT_SCALAR_ARRAY = new float[] {800.2f};
+-  private static final float[] FLOAT_SCALAR_ARRAY_ROUNDED = new float[] {800.0f};
+-  private static final float[] FLOAT_SCALAR_ARRAY_CAPPED = new float[] {255.0f};
+-  private static final int[] INT_SCALAR_ARRAY = new int[] {800};
+-  private static final int[] INT_SCALAR_ARRAY_CAPPED = new int[] {255};
+-  // Several different ByteBuffer.
+-  private static final ByteBuffer EMPTY_BYTE_BUFFER = ByteBuffer.allocateDirect(0);
+-  private static final ByteBuffer FLOAT_BYTE_BUFFER1 = ByteBuffer.allocateDirect(24);
+-
+-  static {
+-    FLOAT_BYTE_BUFFER1.rewind();
+-
+-    FloatBuffer floatBuffer = FLOAT_BYTE_BUFFER1.asFloatBuffer();
+-    floatBuffer.put(FLOAT_ARRAY1);
+-  }
+-
+-  private static final ByteBuffer INT_BYTE_BUFFER2 = ByteBuffer.allocateDirect(2);
+-
+-  static {
+-    INT_BYTE_BUFFER2.rewind();
+-
+-    for (int a : INT_ARRAY2) {
+-      INT_BYTE_BUFFER2.put((byte) a);
+-    }
+-  }
+-
+-  @Test
+-  public void testCreateFixedSizeTensorBufferFloat() {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBuffer tensorBufferFloat = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    assertThat(tensorBufferFloat).isNotNull();
+-    assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(6);
+-  }
+-
+-  @Test
+-  public void testCreateFixedSizeTensorBufferUint8() {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBuffer tensorBufferUint8 = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    assertThat(tensorBufferUint8).isNotNull();
+-    assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(6);
+-  }
+-
+-  @Test
+-  public void testCreateDynamicTensorBufferFloat() {
+-    TensorBuffer tensorBufferFloat = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    assertThat(tensorBufferFloat).isNotNull();
+-  }
+-
+-  @Test
+-  public void testCreateDynamicTensorBufferUint8() {
+-    TensorBuffer tensorBufferUint8 = TensorBuffer.createDynamic(DataType.UINT8);
+-    assertThat(tensorBufferUint8).isNotNull();
+-  }
+-
+-  @Test
+-  public void testCreateTensorBufferFromFixedSize() {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+-    assertThat(dst.getShape()).isEqualTo(new int[] {1, 2, 3});
+-  }
+-
+-  @Test
+-  public void testCreateTensorBufferFromDynamicSize() {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBuffer src = TensorBuffer.createDynamic(DataType.UINT8);
+-    src.resize(shape);
+-    TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+-    assertThat(dst.getShape()).isEqualTo(new int[] {1, 2, 3});
+-  }
+-
+-  @Test
+-  public void testCreateTensorBufferUInt8FromUInt8() {
+-    int[] shape = new int[] {INT_ARRAY1.length};
+-    TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    src.loadArray(INT_ARRAY1);
+-    TensorBuffer dst = TensorBuffer.createFrom(src, DataType.UINT8);
+-    int[] data = dst.getIntArray();
+-    assertThat(data).isEqualTo(INT_ARRAY1_CAPPED);
+-  }
+-
+-  @Test
+-  public void testCreateTensorBufferUInt8FromFloat32() {
+-    TensorBuffer src = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    src.loadArray(FLOAT_ARRAY1, ARRAY1_SHAPE);
+-    TensorBuffer dst = TensorBuffer.createFrom(src, DataType.UINT8);
+-    int[] data = dst.getIntArray();
+-    assertThat(data).isEqualTo(INT_ARRAY1_CAPPED);
+-  }
+-
+-  @Test
+-  public void testCreateTensorBufferFloat32FromUInt8() {
+-    TensorBuffer src = TensorBuffer.createDynamic(DataType.UINT8);
+-    src.loadArray(INT_ARRAY1, ARRAY1_SHAPE);
+-    TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+-    float[] data = dst.getFloatArray();
+-    assertThat(data).isEqualTo(FLOAT_ARRAY1_CAPPED);
+-  }
+-
+-  @Test
+-  public void testCreateTensorBufferFloat32FromFloat32() {
+-    int[] shape = new int[] {FLOAT_ARRAY1.length};
+-    TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+-    src.loadArray(FLOAT_ARRAY1);
+-    TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+-    float[] data = dst.getFloatArray();
+-    assertThat(data).isEqualTo(FLOAT_ARRAY1);
+-  }
+-
+-  @Test
+-  public void testGetBuffer() throws IOException {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBuffer tensorBufferUint8 = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+-    assertThat(tensorBufferUint8.getBuffer()).isNotNull();
+-  }
+-
+-  @Test
+-  public void testLoadAndGetIntArrayWithFixedSizeForScalarArray() throws IOException {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(INT_SCALAR_ARRAY, SCALAR_ARRAY_SHAPE)
+-        .setTensorBufferShape(SCALAR_ARRAY_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_SCALAR_ARRAY_ROUNDED,
+-            /*expectedIntArr=*/ INT_SCALAR_ARRAY)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_SCALAR_ARRAY_CAPPED,
+-            /*expectedIntArr=*/ INT_SCALAR_ARRAY_CAPPED)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testLoadAndGetFloatArrayWithFixedSizeForScalarArray() throws IOException {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(FLOAT_SCALAR_ARRAY, SCALAR_ARRAY_SHAPE)
+-        .setTensorBufferShape(SCALAR_ARRAY_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_SCALAR_ARRAY,
+-            /*expectedIntArr=*/ INT_SCALAR_ARRAY)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_SCALAR_ARRAY_CAPPED,
+-            /*expectedIntArr=*/ INT_SCALAR_ARRAY_CAPPED)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testLoadAndGetIntArrayWithFixedSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
+-        .setTensorBufferShape(ARRAY1_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY1)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1_CAPPED,
+-            /*expectedIntArr=*/ INT_ARRAY1_CAPPED)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testLoadAndGetFloatArrayWithFixedSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
+-        .setTensorBufferShape(ARRAY1_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1,
+-            /*expectedIntArr=*/ INT_ARRAY1)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1_CAPPED,
+-            /*expectedIntArr=*/ INT_ARRAY1_CAPPED)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadAndGetIntArrayWithSameFixedSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(INT_ARRAY2, ARRAY2_SHAPE)
+-        .addSrcArray(INT_ARRAY3, ARRAY3_SHAPE)
+-        .setTensorBufferShape(ARRAY2_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY3_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY3)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY3_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY3)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadAndGetFloatArrayWithSameFixedSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
+-        .addSrcArray(FLOAT_ARRAY3, ARRAY3_SHAPE)
+-        .setTensorBufferShape(ARRAY2_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY3,
+-            /*expectedIntArr=*/ INT_ARRAY3)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY3_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY3)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadIntArrayWithDifferentFixedSize() {
+-    int[] srcArr1 = INT_ARRAY1;
+-    int[] srcArr2 = INT_ARRAY2;
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer =
+-          TensorBuffer.createFixedSize(new int[] {srcArr1.length}, dataType);
+-      tensorBuffer.loadArray(srcArr1, new int[] {srcArr1.length});
+-      // Load srcArr2 which had different size as srcArr1.
+-      Assert.assertThrows(
+-          IllegalArgumentException.class,
+-          () -> tensorBuffer.loadArray(srcArr2, new int[] {srcArr2.length}));
+-    }
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadFloatArrayWithDifferentFixedSize() {
+-    float[] srcArr1 = FLOAT_ARRAY1;
+-    float[] srcArr2 = FLOAT_ARRAY2;
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer =
+-          TensorBuffer.createFixedSize(new int[] {srcArr1.length}, dataType);
+-      tensorBuffer.loadArray(srcArr1, new int[] {srcArr1.length});
+-      // Load srcArr2 which had different size as srcArr1.
+-      Assert.assertThrows(
+-          IllegalArgumentException.class,
+-          () -> tensorBuffer.loadArray(srcArr2, new int[] {srcArr2.length}));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadAndGetIntArrayWithDynamicSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY1)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1_CAPPED,
+-            /*expectedIntArr=*/ INT_ARRAY1_CAPPED)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testLoadAndGetFloatArrayWithDynamicSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1,
+-            /*expectedIntArr=*/ INT_ARRAY1)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY1_CAPPED,
+-            /*expectedIntArr=*/ INT_ARRAY1_CAPPED)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadAndGetIntArrayWithDifferentDynamicSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
+-        .addSrcArray(INT_ARRAY2, ARRAY2_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY2_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY2)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY2_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY2)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadAndGetFloatArrayWithDifferentDynamicSize() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
+-        .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY2,
+-            /*expectedIntArr=*/ INT_ARRAY2)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ FLOAT_ARRAY2_ROUNDED,
+-            /*expectedIntArr=*/ INT_ARRAY2)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testGetForEmptyArrayWithFixedSizeBuffer() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .setTensorBufferShape(EMPTY_ARRAY_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ EMPTY_FLOAT_ARRAY,
+-            /*expectedIntArr=*/ EMPTY_INT_ARRAY)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ EMPTY_FLOAT_ARRAY,
+-            /*expectedIntArr=*/ EMPTY_INT_ARRAY)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testGetForEmptyArrayWithDynamicBuffer() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ EMPTY_FLOAT_ARRAY,
+-            /*expectedIntArr=*/ EMPTY_INT_ARRAY)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ EMPTY_FLOAT_ARRAY,
+-            /*expectedIntArr=*/ EMPTY_INT_ARRAY)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testRepeatedLoadAndGetForEmptyArray() {
+-    ArrayTestRunner.Builder.newInstance()
+-        .addSrcArray(EMPTY_INT_ARRAY, EMPTY_ARRAY_SHAPE)
+-        .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
+-        .addSrcArray(EMPTY_FLOAT_ARRAY, EMPTY_ARRAY_SHAPE)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.FLOAT32,
+-            /*expectedFloatArr=*/ EMPTY_FLOAT_ARRAY,
+-            /*expectedIntArr=*/ EMPTY_INT_ARRAY)
+-        .setExpectedResults(
+-            /*bufferType = */ DataType.UINT8,
+-            /*expectedFloatArr=*/ EMPTY_FLOAT_ARRAY,
+-            /*expectedIntArr=*/ EMPTY_INT_ARRAY)
+-        .build()
+-        .run();
+-  }
+-
+-  @Test
+-  public void testLoadNullIntArrays() {
+-    int[] nullArray = null;
+-    int[] shape = new int[] {};
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      Assert.assertThrows(
+-          NullPointerException.class, () -> tensorBuffer.loadArray(nullArray, shape));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadNullFloatArrays() {
+-    float[] nullArray = null;
+-    int[] shape = new int[] {};
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      Assert.assertThrows(
+-          NullPointerException.class, () -> tensorBuffer.loadArray(nullArray, shape));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadFloatArraysWithNullShape() {
+-    float[] arr = new float[] {1.0f};
+-    int[] nullShape = null;
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      Assert.assertThrows(NullPointerException.class, () -> tensorBuffer.loadArray(arr, nullShape));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadIntArraysWithNullShape() {
+-    int[] arr = new int[] {1};
+-    int[] nullShape = null;
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      Assert.assertThrows(NullPointerException.class, () -> tensorBuffer.loadArray(arr, nullShape));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadIntArraysWithoutShapeAndArrayDoesNotMatchShape() {
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer fixedTensorBuffer = TensorBuffer.createFixedSize(ARRAY1_SHAPE, dataType);
+-      Assert.assertThrows(
+-          IllegalArgumentException.class, () -> fixedTensorBuffer.loadArray(INT_ARRAY2));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadFloatArraysWithoutShapeAndArrayDoesNotMatchShape() {
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer fixedTensorBuffer = TensorBuffer.createFixedSize(ARRAY1_SHAPE, dataType);
+-      Assert.assertThrows(
+-          IllegalArgumentException.class, () -> fixedTensorBuffer.loadArray(FLOAT_ARRAY2));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferForNullBuffer() {
+-    ByteBuffer byteBuffer = null;
+-    int[] shape = new int[] {};
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      Assert.assertThrows(
+-          NullPointerException.class, () -> tensorBuffer.loadBuffer(byteBuffer, shape));
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferForEmptyBuffer() {
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      tensorBuffer.loadBuffer(EMPTY_BYTE_BUFFER, EMPTY_ARRAY_SHAPE);
+-      assertThat(tensorBuffer.getFlatSize()).isEqualTo(0);
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferWithDifferentFixedSize() {
+-    // Create a fixed-size TensorBuffer with size 2, and load a ByteBuffer with size 5.
+-    int[] tensorBufferShape = new int[] {2};
+-    TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(tensorBufferShape, DataType.FLOAT32);
+-    Assert.assertThrows(
+-        IllegalArgumentException.class,
+-        () -> tensorBuffer.loadBuffer(FLOAT_BYTE_BUFFER1, ARRAY1_SHAPE));
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferWithMisMatchDataType() {
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    int[] wrongShape = new int[] {1};
+-    // Size of INT_BYTE_BUFFER is 8 bytes. It does not match the specified shape.
+-    Assert.assertThrows(
+-        IllegalArgumentException.class,
+-        () -> tensorBuffer.loadBuffer(INT_BYTE_BUFFER2, wrongShape));
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferForTensorBufferFloat() {
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    tensorBuffer.loadBuffer(FLOAT_BYTE_BUFFER1, ARRAY1_SHAPE);
+-    assertThat(tensorBuffer.getFloatArray()).isEqualTo(FLOAT_ARRAY1);
+-    assertThat(tensorBuffer.getShape()).isEqualTo(ARRAY1_SHAPE);
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferForTensorBufferUint8() {
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    tensorBuffer.loadBuffer(INT_BYTE_BUFFER2, ARRAY2_SHAPE);
+-    assertThat(tensorBuffer.getIntArray()).isEqualTo(INT_ARRAY2);
+-    assertThat(tensorBuffer.getShape()).isEqualTo(ARRAY2_SHAPE);
+-  }
+-
+-  @Test
+-  public void testGetFloatValueWithInvalidIndex() {
+-    float[] arrayWithSixElements = FLOAT_ARRAY1;
+-    int[] shapeOfArrayWithSixElements = ARRAY1_SHAPE;
+-    int[] invalidIndexes = {-1, 7};
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      tensorBuffer.loadArray(arrayWithSixElements, shapeOfArrayWithSixElements);
+-      for (int invalidIndex : invalidIndexes) {
+-        Assert.assertThrows(
+-            IndexOutOfBoundsException.class, () -> tensorBuffer.getFloatValue(invalidIndex));
+-      }
+-    }
+-  }
+-
+-  @Test
+-  public void testGetFloatValueFromScalarWithInvalidIndex() {
+-    int[] shape = new int[] {};
+-    float[] arr = new float[] {10.0f};
+-    int[] invalidIndexes =
+-        new int[] {-1, 1}; // -1 is negative, and 1 is not smaller than the flatsize.
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      tensorBuffer.loadArray(arr, shape);
+-      for (int invalidIndex : invalidIndexes) {
+-        Assert.assertThrows(
+-            IndexOutOfBoundsException.class, () -> tensorBuffer.getFloatValue(invalidIndex));
+-      }
+-    }
+-  }
+-
+-  @Test
+-  public void testGetIntValueWithInvalidIndex() {
+-    float[] arrayWithSixElements = FLOAT_ARRAY1;
+-    int[] shapeOfArrayWithSixElements = ARRAY1_SHAPE;
+-    int[] invalidIndexes = {-1, 7};
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      tensorBuffer.loadArray(arrayWithSixElements, shapeOfArrayWithSixElements);
+-      for (int invalidIndex : invalidIndexes) {
+-        Assert.assertThrows(
+-            IndexOutOfBoundsException.class, () -> tensorBuffer.getIntValue(invalidIndex));
+-      }
+-    }
+-  }
+-
+-  @Test
+-  public void testGetIntValueFromScalarWithInvalidIndex() {
+-    int[] shape = new int[] {};
+-    float[] arr = new float[] {10.0f};
+-    int[] invalidIndexes =
+-        new int[] {-1, 1}; // -1 is negative, and 1 is not smaller than the flatsize.
+-    for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+-      TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+-      tensorBuffer.loadArray(arr, shape);
+-      for (int invalidIndex : invalidIndexes) {
+-        Assert.assertThrows(
+-            IndexOutOfBoundsException.class, () -> tensorBuffer.getIntValue(invalidIndex));
+-      }
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferSliceForTensorBufferFloat() {
+-    TensorBuffer original = TensorBuffer.createDynamic(DataType.FLOAT32);
+-    original.loadArray(new float[] {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}, new int[] {6});
+-    ByteBuffer buffer = original.getBuffer();
+-    // Slice original buffer to 3 sub-buffer, each of which has 2 element
+-    int numBuffers = 3;
+-    int numElements = 2;
+-    int subArrayLength = numElements * original.getTypeSize();
+-    TensorBuffer tensorSlice = TensorBuffer.createDynamic(original.getDataType());
+-    for (int i = 0; i < numBuffers; i++) {
+-      buffer.position(i * subArrayLength);
+-      ByteBuffer subBuffer = buffer.slice();
+-      // ByteBuffer.slice doesn't keep order.
+-      subBuffer.order(buffer.order()).limit(subArrayLength);
+-      tensorSlice.loadBuffer(subBuffer, new int[] {numElements});
+-      float[] arraySlice = tensorSlice.getFloatArray();
+-      assertThat(arraySlice.length).isEqualTo(numElements);
+-      assertThat(arraySlice[0]).isEqualTo(i * numElements + 1);
+-      assertThat(arraySlice[1]).isEqualTo(i * numElements + 2);
+-    }
+-  }
+-
+-  @Test
+-  public void testLoadByteBufferSliceForTensorBufferUInt8() {
+-    TensorBuffer original = TensorBuffer.createDynamic(DataType.UINT8);
+-    original.loadArray(new int[] {1, 2, 3, 4, 5, 6}, new int[] {6});
+-    ByteBuffer buffer = original.getBuffer();
+-    // Slice original buffer to 3 sub-buffer, each of which has 2 element
+-    int numBuffers = 3;
+-    int numElements = 2;
+-    int subArrayLength = numElements * original.getTypeSize();
+-    TensorBuffer tensorSlice = TensorBuffer.createDynamic(original.getDataType());
+-    for (int i = 0; i < numBuffers; i++) {
+-      buffer.position(i * subArrayLength);
+-      ByteBuffer subBuffer = buffer.slice();
+-      // ByteBuffer.slice doesn't keep order.
+-      subBuffer.order(buffer.order()).limit(subArrayLength);
+-      tensorSlice.loadBuffer(subBuffer, new int[] {numElements});
+-      int[] arraySlice = tensorSlice.getIntArray();
+-      assertThat(arraySlice.length).isEqualTo(numElements);
+-      assertThat(arraySlice[0]).isEqualTo(i * numElements + 1);
+-      assertThat(arraySlice[1]).isEqualTo(i * numElements + 2);
+-    }
+-  }
+-
+-  @Test
+-  public void getShapeFailsAfterByteBufferChanged() {
+-    TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(new int[] {3, 2}, DataType.FLOAT32);
+-    ByteBuffer byteBuffer = tensorBuffer.getBuffer();
+-    byteBuffer.limit(5);
+-
+-    IllegalStateException exception =
+-        assertThrows(IllegalStateException.class, tensorBuffer::getShape);
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .contains(
+-            "The size of underlying ByteBuffer (5) and the shape ([3, 2]) do not match. The"
++    // FLOAT_ARRAY1 and INT_ARRAY1 correspond to each other.
++    private static final int[] ARRAY1_SHAPE = new int[] {2, 3};
++    private static final float[] FLOAT_ARRAY1 = new float[] {500.1f, 4.2f, 3.3f, 2.4f, 1.5f, 6.1f};
++    private static final float[] FLOAT_ARRAY1_ROUNDED =
++            new float[] {500.0f, 4.0f, 3.0f, 2.0f, 1.0f, 6.0f};
++    // FLOAT_ARRAY1_CAPPED and INT_ARRAY1_CAPPED correspond to the expected values when converted
++    // into uint8.
++    private static final float[] FLOAT_ARRAY1_CAPPED =
++            new float[] {255.0f, 4.0f, 3.0f, 2.0f, 1.0f, 6.0f};
++    private static final int[] INT_ARRAY1 = new int[] {500, 4, 3, 2, 1, 6};
++    private static final int[] INT_ARRAY1_CAPPED = new int[] {255, 4, 3, 2, 1, 6};
++    // FLOAT_ARRAY2 and INT_ARRAY2 correspond to each other.
++    private static final int[] ARRAY2_SHAPE = new int[] {2, 1};
++    private static final float[] FLOAT_ARRAY2 = new float[] {6.7f, 7.6f};
++    private static final float[] FLOAT_ARRAY2_ROUNDED = new float[] {6.0f, 7.0f};
++    private static final int[] INT_ARRAY2 = new int[] {6, 7};
++    // FLOAT_ARRAY2 and FLOAT_ARRAY3 have the same size.
++    private static final int[] ARRAY3_SHAPE = new int[] {2, 1};
++    private static final float[] FLOAT_ARRAY3 = new float[] {8.2f, 9.9f};
++    private static final float[] FLOAT_ARRAY3_ROUNDED = new float[] {8.0f, 9.0f};
++    // INT_ARRAY2 and INT_ARRAY3 have the same size.
++    private static final int[] INT_ARRAY3 = new int[] {8, 9};
++    private static final int[] EMPTY_ARRAY_SHAPE = new int[] {0};
++    private static final int[] EMPTY_INT_ARRAY = new int[0];
++    private static final float[] EMPTY_FLOAT_ARRAY = new float[0];
++    // Single element array which represents a scalar.
++    private static final int[] SCALAR_ARRAY_SHAPE = new int[] {};
++    private static final float[] FLOAT_SCALAR_ARRAY = new float[] {800.2f};
++    private static final float[] FLOAT_SCALAR_ARRAY_ROUNDED = new float[] {800.0f};
++    private static final float[] FLOAT_SCALAR_ARRAY_CAPPED = new float[] {255.0f};
++    private static final int[] INT_SCALAR_ARRAY = new int[] {800};
++    private static final int[] INT_SCALAR_ARRAY_CAPPED = new int[] {255};
++    // Several different ByteBuffer.
++    private static final ByteBuffer EMPTY_BYTE_BUFFER = ByteBuffer.allocateDirect(0);
++    private static final ByteBuffer FLOAT_BYTE_BUFFER1 = ByteBuffer.allocateDirect(24);
++
++    static {
++        FLOAT_BYTE_BUFFER1.rewind();
++
++        FloatBuffer floatBuffer = FLOAT_BYTE_BUFFER1.asFloatBuffer();
++        floatBuffer.put(FLOAT_ARRAY1);
++    }
++
++    private static final ByteBuffer INT_BYTE_BUFFER2 = ByteBuffer.allocateDirect(2);
++
++    static {
++        INT_BYTE_BUFFER2.rewind();
++
++        for (int a : INT_ARRAY2) {
++            INT_BYTE_BUFFER2.put((byte) a);
++        }
++    }
++
++    @Test
++    public void testCreateFixedSizeTensorBufferFloat() {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBuffer tensorBufferFloat = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        assertThat(tensorBufferFloat).isNotNull();
++        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(6);
++    }
++
++    @Test
++    public void testCreateFixedSizeTensorBufferUint8() {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBuffer tensorBufferUint8 = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        assertThat(tensorBufferUint8).isNotNull();
++        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(6);
++    }
++
++    @Test
++    public void testCreateDynamicTensorBufferFloat() {
++        TensorBuffer tensorBufferFloat = TensorBuffer.createDynamic(DataType.FLOAT32);
++        assertThat(tensorBufferFloat).isNotNull();
++    }
++
++    @Test
++    public void testCreateDynamicTensorBufferUint8() {
++        TensorBuffer tensorBufferUint8 = TensorBuffer.createDynamic(DataType.UINT8);
++        assertThat(tensorBufferUint8).isNotNull();
++    }
++
++    @Test
++    public void testCreateTensorBufferFromFixedSize() {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
++        assertThat(dst.getShape()).isEqualTo(new int[] {1, 2, 3});
++    }
++
++    @Test
++    public void testCreateTensorBufferFromDynamicSize() {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBuffer src = TensorBuffer.createDynamic(DataType.UINT8);
++        src.resize(shape);
++        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
++        assertThat(dst.getShape()).isEqualTo(new int[] {1, 2, 3});
++    }
++
++    @Test
++    public void testCreateTensorBufferUInt8FromUInt8() {
++        int[] shape = new int[] {INT_ARRAY1.length};
++        TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        src.loadArray(INT_ARRAY1);
++        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.UINT8);
++        int[] data = dst.getIntArray();
++        assertThat(data).isEqualTo(INT_ARRAY1_CAPPED);
++    }
++
++    @Test
++    public void testCreateTensorBufferUInt8FromFloat32() {
++        TensorBuffer src = TensorBuffer.createDynamic(DataType.FLOAT32);
++        src.loadArray(FLOAT_ARRAY1, ARRAY1_SHAPE);
++        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.UINT8);
++        int[] data = dst.getIntArray();
++        assertThat(data).isEqualTo(INT_ARRAY1_CAPPED);
++    }
++
++    @Test
++    public void testCreateTensorBufferFloat32FromUInt8() {
++        TensorBuffer src = TensorBuffer.createDynamic(DataType.UINT8);
++        src.loadArray(INT_ARRAY1, ARRAY1_SHAPE);
++        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
++        float[] data = dst.getFloatArray();
++        assertThat(data).isEqualTo(FLOAT_ARRAY1_CAPPED);
++    }
++
++    @Test
++    public void testCreateTensorBufferFloat32FromFloat32() {
++        int[] shape = new int[] {FLOAT_ARRAY1.length};
++        TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
++        src.loadArray(FLOAT_ARRAY1);
++        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
++        float[] data = dst.getFloatArray();
++        assertThat(data).isEqualTo(FLOAT_ARRAY1);
++    }
++
++    @Test
++    public void testGetBuffer() throws IOException {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBuffer tensorBufferUint8 = TensorBuffer.createFixedSize(shape, DataType.UINT8);
++        assertThat(tensorBufferUint8.getBuffer()).isNotNull();
++    }
++
++    @Test
++    public void testLoadAndGetIntArrayWithFixedSizeForScalarArray() throws IOException {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(INT_SCALAR_ARRAY, SCALAR_ARRAY_SHAPE)
++                .setTensorBufferShape(SCALAR_ARRAY_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY_ROUNDED,
++                        /*expectedIntArr=*/INT_SCALAR_ARRAY)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY_CAPPED,
++                        /*expectedIntArr=*/INT_SCALAR_ARRAY_CAPPED)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testLoadAndGetFloatArrayWithFixedSizeForScalarArray() throws IOException {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(FLOAT_SCALAR_ARRAY, SCALAR_ARRAY_SHAPE)
++                .setTensorBufferShape(SCALAR_ARRAY_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY,
++                        /*expectedIntArr=*/INT_SCALAR_ARRAY)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY_CAPPED,
++                        /*expectedIntArr=*/INT_SCALAR_ARRAY_CAPPED)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testLoadAndGetIntArrayWithFixedSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
++                .setTensorBufferShape(ARRAY1_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY1)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
++                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testLoadAndGetFloatArrayWithFixedSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
++                .setTensorBufferShape(ARRAY1_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1,
++                        /*expectedIntArr=*/INT_ARRAY1)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
++                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testRepeatedLoadAndGetIntArrayWithSameFixedSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(INT_ARRAY2, ARRAY2_SHAPE)
++                .addSrcArray(INT_ARRAY3, ARRAY3_SHAPE)
++                .setTensorBufferShape(ARRAY2_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY3_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY3)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY3_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY3)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testRepeatedLoadAndGetFloatArrayWithSameFixedSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
++                .addSrcArray(FLOAT_ARRAY3, ARRAY3_SHAPE)
++                .setTensorBufferShape(ARRAY2_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY3,
++                        /*expectedIntArr=*/INT_ARRAY3)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY3_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY3)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testRepeatedLoadIntArrayWithDifferentFixedSize() {
++        int[] srcArr1 = INT_ARRAY1;
++        int[] srcArr2 = INT_ARRAY2;
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer =
++                    TensorBuffer.createFixedSize(new int[] {srcArr1.length}, dataType);
++            tensorBuffer.loadArray(srcArr1, new int[] {srcArr1.length});
++            // Load srcArr2 which had different size as srcArr1.
++            Assert.assertThrows(IllegalArgumentException.class,
++                    () -> tensorBuffer.loadArray(srcArr2, new int[] {srcArr2.length}));
++        }
++    }
++
++    @Test
++    public void testRepeatedLoadFloatArrayWithDifferentFixedSize() {
++        float[] srcArr1 = FLOAT_ARRAY1;
++        float[] srcArr2 = FLOAT_ARRAY2;
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer =
++                    TensorBuffer.createFixedSize(new int[] {srcArr1.length}, dataType);
++            tensorBuffer.loadArray(srcArr1, new int[] {srcArr1.length});
++            // Load srcArr2 which had different size as srcArr1.
++            Assert.assertThrows(IllegalArgumentException.class,
++                    () -> tensorBuffer.loadArray(srcArr2, new int[] {srcArr2.length}));
++        }
++    }
++
++    @Test
++    public void testLoadAndGetIntArrayWithDynamicSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY1)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
++                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testLoadAndGetFloatArrayWithDynamicSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1,
++                        /*expectedIntArr=*/INT_ARRAY1)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
++                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testRepeatedLoadAndGetIntArrayWithDifferentDynamicSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
++                .addSrcArray(INT_ARRAY2, ARRAY2_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY2_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY2)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY2_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY2)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testRepeatedLoadAndGetFloatArrayWithDifferentDynamicSize() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
++                .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/FLOAT_ARRAY2,
++                        /*expectedIntArr=*/INT_ARRAY2)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/FLOAT_ARRAY2_ROUNDED,
++                        /*expectedIntArr=*/INT_ARRAY2)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testGetForEmptyArrayWithFixedSizeBuffer() {
++        ArrayTestRunner.Builder.newInstance()
++                .setTensorBufferShape(EMPTY_ARRAY_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
++                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
++                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testGetForEmptyArrayWithDynamicBuffer() {
++        ArrayTestRunner.Builder.newInstance()
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
++                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
++                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testRepeatedLoadAndGetForEmptyArray() {
++        ArrayTestRunner.Builder.newInstance()
++                .addSrcArray(EMPTY_INT_ARRAY, EMPTY_ARRAY_SHAPE)
++                .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
++                .addSrcArray(EMPTY_FLOAT_ARRAY, EMPTY_ARRAY_SHAPE)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.FLOAT32,
++                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
++                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
++                .setExpectedResults(
++                        /*bufferType = */ DataType.UINT8,
++                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
++                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
++                .build()
++                .run();
++    }
++
++    @Test
++    public void testLoadNullIntArrays() {
++        int[] nullArray = null;
++        int[] shape = new int[] {};
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            Assert.assertThrows(
++                    NullPointerException.class, () -> tensorBuffer.loadArray(nullArray, shape));
++        }
++    }
++
++    @Test
++    public void testLoadNullFloatArrays() {
++        float[] nullArray = null;
++        int[] shape = new int[] {};
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            Assert.assertThrows(
++                    NullPointerException.class, () -> tensorBuffer.loadArray(nullArray, shape));
++        }
++    }
++
++    @Test
++    public void testLoadFloatArraysWithNullShape() {
++        float[] arr = new float[] {1.0f};
++        int[] nullShape = null;
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            Assert.assertThrows(
++                    NullPointerException.class, () -> tensorBuffer.loadArray(arr, nullShape));
++        }
++    }
++
++    @Test
++    public void testLoadIntArraysWithNullShape() {
++        int[] arr = new int[] {1};
++        int[] nullShape = null;
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            Assert.assertThrows(
++                    NullPointerException.class, () -> tensorBuffer.loadArray(arr, nullShape));
++        }
++    }
++
++    @Test
++    public void testLoadIntArraysWithoutShapeAndArrayDoesNotMatchShape() {
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer fixedTensorBuffer = TensorBuffer.createFixedSize(ARRAY1_SHAPE, dataType);
++            Assert.assertThrows(
++                    IllegalArgumentException.class, () -> fixedTensorBuffer.loadArray(INT_ARRAY2));
++        }
++    }
++
++    @Test
++    public void testLoadFloatArraysWithoutShapeAndArrayDoesNotMatchShape() {
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer fixedTensorBuffer = TensorBuffer.createFixedSize(ARRAY1_SHAPE, dataType);
++            Assert.assertThrows(IllegalArgumentException.class,
++                    () -> fixedTensorBuffer.loadArray(FLOAT_ARRAY2));
++        }
++    }
++
++    @Test
++    public void testLoadByteBufferForNullBuffer() {
++        ByteBuffer byteBuffer = null;
++        int[] shape = new int[] {};
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            Assert.assertThrows(
++                    NullPointerException.class, () -> tensorBuffer.loadBuffer(byteBuffer, shape));
++        }
++    }
++
++    @Test
++    public void testLoadByteBufferForEmptyBuffer() {
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            tensorBuffer.loadBuffer(EMPTY_BYTE_BUFFER, EMPTY_ARRAY_SHAPE);
++            assertThat(tensorBuffer.getFlatSize()).isEqualTo(0);
++        }
++    }
++
++    @Test
++    public void testLoadByteBufferWithDifferentFixedSize() {
++        // Create a fixed-size TensorBuffer with size 2, and load a ByteBuffer with size 5.
++        int[] tensorBufferShape = new int[] {2};
++        TensorBuffer tensorBuffer =
++                TensorBuffer.createFixedSize(tensorBufferShape, DataType.FLOAT32);
++        Assert.assertThrows(IllegalArgumentException.class,
++                () -> tensorBuffer.loadBuffer(FLOAT_BYTE_BUFFER1, ARRAY1_SHAPE));
++    }
++
++    @Test
++    public void testLoadByteBufferWithMisMatchDataType() {
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++        int[] wrongShape = new int[] {1};
++        // Size of INT_BYTE_BUFFER is 8 bytes. It does not match the specified shape.
++        Assert.assertThrows(IllegalArgumentException.class,
++                () -> tensorBuffer.loadBuffer(INT_BYTE_BUFFER2, wrongShape));
++    }
++
++    @Test
++    public void testLoadByteBufferForTensorBufferFloat() {
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
++        tensorBuffer.loadBuffer(FLOAT_BYTE_BUFFER1, ARRAY1_SHAPE);
++        assertThat(tensorBuffer.getFloatArray()).isEqualTo(FLOAT_ARRAY1);
++        assertThat(tensorBuffer.getShape()).isEqualTo(ARRAY1_SHAPE);
++    }
++
++    @Test
++    public void testLoadByteBufferForTensorBufferUint8() {
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
++        tensorBuffer.loadBuffer(INT_BYTE_BUFFER2, ARRAY2_SHAPE);
++        assertThat(tensorBuffer.getIntArray()).isEqualTo(INT_ARRAY2);
++        assertThat(tensorBuffer.getShape()).isEqualTo(ARRAY2_SHAPE);
++    }
++
++    @Test
++    public void testGetFloatValueWithInvalidIndex() {
++        float[] arrayWithSixElements = FLOAT_ARRAY1;
++        int[] shapeOfArrayWithSixElements = ARRAY1_SHAPE;
++        int[] invalidIndexes = {-1, 7};
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            tensorBuffer.loadArray(arrayWithSixElements, shapeOfArrayWithSixElements);
++            for (int invalidIndex : invalidIndexes) {
++                Assert.assertThrows(IndexOutOfBoundsException.class,
++                        () -> tensorBuffer.getFloatValue(invalidIndex));
++            }
++        }
++    }
++
++    @Test
++    public void testGetFloatValueFromScalarWithInvalidIndex() {
++        int[] shape = new int[] {};
++        float[] arr = new float[] {10.0f};
++        int[] invalidIndexes =
++                new int[] {-1, 1}; // -1 is negative, and 1 is not smaller than the flatsize.
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            tensorBuffer.loadArray(arr, shape);
++            for (int invalidIndex : invalidIndexes) {
++                Assert.assertThrows(IndexOutOfBoundsException.class,
++                        () -> tensorBuffer.getFloatValue(invalidIndex));
++            }
++        }
++    }
++
++    @Test
++    public void testGetIntValueWithInvalidIndex() {
++        float[] arrayWithSixElements = FLOAT_ARRAY1;
++        int[] shapeOfArrayWithSixElements = ARRAY1_SHAPE;
++        int[] invalidIndexes = {-1, 7};
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            tensorBuffer.loadArray(arrayWithSixElements, shapeOfArrayWithSixElements);
++            for (int invalidIndex : invalidIndexes) {
++                Assert.assertThrows(IndexOutOfBoundsException.class,
++                        () -> tensorBuffer.getIntValue(invalidIndex));
++            }
++        }
++    }
++
++    @Test
++    public void testGetIntValueFromScalarWithInvalidIndex() {
++        int[] shape = new int[] {};
++        float[] arr = new float[] {10.0f};
++        int[] invalidIndexes =
++                new int[] {-1, 1}; // -1 is negative, and 1 is not smaller than the flatsize.
++        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
++            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
++            tensorBuffer.loadArray(arr, shape);
++            for (int invalidIndex : invalidIndexes) {
++                Assert.assertThrows(IndexOutOfBoundsException.class,
++                        () -> tensorBuffer.getIntValue(invalidIndex));
++            }
++        }
++    }
++
++    @Test
++    public void testLoadByteBufferSliceForTensorBufferFloat() {
++        TensorBuffer original = TensorBuffer.createDynamic(DataType.FLOAT32);
++        original.loadArray(new float[] {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}, new int[] {6});
++        ByteBuffer buffer = original.getBuffer();
++        // Slice original buffer to 3 sub-buffer, each of which has 2 element
++        int numBuffers = 3;
++        int numElements = 2;
++        int subArrayLength = numElements * original.getTypeSize();
++        TensorBuffer tensorSlice = TensorBuffer.createDynamic(original.getDataType());
++        for (int i = 0; i < numBuffers; i++) {
++            buffer.position(i * subArrayLength);
++            ByteBuffer subBuffer = buffer.slice();
++            // ByteBuffer.slice doesn't keep order.
++            subBuffer.order(buffer.order()).limit(subArrayLength);
++            tensorSlice.loadBuffer(subBuffer, new int[] {numElements});
++            float[] arraySlice = tensorSlice.getFloatArray();
++            assertThat(arraySlice.length).isEqualTo(numElements);
++            assertThat(arraySlice[0]).isEqualTo(i * numElements + 1);
++            assertThat(arraySlice[1]).isEqualTo(i * numElements + 2);
++        }
++    }
++
++    @Test
++    public void testLoadByteBufferSliceForTensorBufferUInt8() {
++        TensorBuffer original = TensorBuffer.createDynamic(DataType.UINT8);
++        original.loadArray(new int[] {1, 2, 3, 4, 5, 6}, new int[] {6});
++        ByteBuffer buffer = original.getBuffer();
++        // Slice original buffer to 3 sub-buffer, each of which has 2 element
++        int numBuffers = 3;
++        int numElements = 2;
++        int subArrayLength = numElements * original.getTypeSize();
++        TensorBuffer tensorSlice = TensorBuffer.createDynamic(original.getDataType());
++        for (int i = 0; i < numBuffers; i++) {
++            buffer.position(i * subArrayLength);
++            ByteBuffer subBuffer = buffer.slice();
++            // ByteBuffer.slice doesn't keep order.
++            subBuffer.order(buffer.order()).limit(subArrayLength);
++            tensorSlice.loadBuffer(subBuffer, new int[] {numElements});
++            int[] arraySlice = tensorSlice.getIntArray();
++            assertThat(arraySlice.length).isEqualTo(numElements);
++            assertThat(arraySlice[0]).isEqualTo(i * numElements + 1);
++            assertThat(arraySlice[1]).isEqualTo(i * numElements + 2);
++        }
++    }
++
++    @Test
++    public void getShapeFailsAfterByteBufferChanged() {
++        TensorBuffer tensorBuffer =
++                TensorBuffer.createFixedSize(new int[] {3, 2}, DataType.FLOAT32);
++        ByteBuffer byteBuffer = tensorBuffer.getBuffer();
++        byteBuffer.limit(5);
++
++        IllegalStateException exception =
++                assertThrows(IllegalStateException.class, tensorBuffer::getShape);
++        assertThat(exception).hasMessageThat().contains(
++                "The size of underlying ByteBuffer (5) and the shape ([3, 2]) do not match. The"
+                 + " ByteBuffer may have been changed.");
+-  }
+-
+-  @Test
+-  public void getFlatSizeFailsAfterByteBufferChanged() {
+-    TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(new int[] {3, 2}, DataType.FLOAT32);
+-    ByteBuffer byteBuffer = tensorBuffer.getBuffer();
+-    byteBuffer.limit(5);
+-
+-    IllegalStateException exception =
+-        assertThrows(IllegalStateException.class, tensorBuffer::getFlatSize);
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .contains(
+-            "The size of underlying ByteBuffer (5) and the shape ([3, 2]) do not match. The"
++    }
++
++    @Test
++    public void getFlatSizeFailsAfterByteBufferChanged() {
++        TensorBuffer tensorBuffer =
++                TensorBuffer.createFixedSize(new int[] {3, 2}, DataType.FLOAT32);
++        ByteBuffer byteBuffer = tensorBuffer.getBuffer();
++        byteBuffer.limit(5);
++
++        IllegalStateException exception =
++                assertThrows(IllegalStateException.class, tensorBuffer::getFlatSize);
++        assertThat(exception).hasMessageThat().contains(
++                "The size of underlying ByteBuffer (5) and the shape ([3, 2]) do not match. The"
+                 + " ByteBuffer may have been changed.");
+-  }
+-
+-  @Test
+-  public void loadReadOnlyBuffersCopiesOnWrite() {
+-    TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+-    ByteBuffer originalByteBuffer = ByteBuffer.allocateDirect(1);
+-    originalByteBuffer.put(new byte[]{99});
+-    originalByteBuffer.rewind();
+-    ByteBuffer readOnlyByteBuffer = originalByteBuffer.asReadOnlyBuffer();
+-
+-    tensorBuffer.loadBuffer(readOnlyByteBuffer, new int[]{1});
+-    assertThat(tensorBuffer.getBuffer()).isSameInstanceAs(readOnlyByteBuffer);
+-
+-    tensorBuffer.loadArray(new int[]{42});
+-    assertThat(tensorBuffer.getBuffer()).isNotSameInstanceAs(readOnlyByteBuffer);
+-    assertThat(tensorBuffer.getBuffer().get(0)).isEqualTo(42);  // updated
+-    assertThat(originalByteBuffer.get(0)).isEqualTo(99);  // original one not changed
+-  }
++    }
++
++    @Test
++    public void loadReadOnlyBuffersCopiesOnWrite() {
++        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
++        ByteBuffer originalByteBuffer = ByteBuffer.allocateDirect(1);
++        originalByteBuffer.put(new byte[] {99});
++        originalByteBuffer.rewind();
++        ByteBuffer readOnlyByteBuffer = originalByteBuffer.asReadOnlyBuffer();
++
++        tensorBuffer.loadBuffer(readOnlyByteBuffer, new int[] {1});
++        assertThat(tensorBuffer.getBuffer()).isSameInstanceAs(readOnlyByteBuffer);
++
++        tensorBuffer.loadArray(new int[] {42});
++        assertThat(tensorBuffer.getBuffer()).isNotSameInstanceAs(readOnlyByteBuffer);
++        assertThat(tensorBuffer.getBuffer().get(0)).isEqualTo(42); // updated
++        assertThat(originalByteBuffer.get(0)).isEqualTo(99); // original one not changed
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java
+index e843133275d61..1921f4e467d01 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java
+@@ -26,51 +26,51 @@ import org.tensorflow.lite.DataType;
+ /** Tests of {@link org.tensorflow.lite.support.tensorbuffer.TensorBufferUint8}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class TensorBufferUint8Test {
+-  @Test
+-  public void testCreateDynamic() {
+-    TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8();
+-    assertThat(tensorBufferUint8).isNotNull();
+-  }
++    @Test
++    public void testCreateDynamic() {
++        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8();
++        assertThat(tensorBufferUint8).isNotNull();
++    }
+ 
+-  @Test
+-  public void testCreateFixedSize() {
+-    int[] shape = new int[] {1, 2, 3};
+-    TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
+-    assertThat(tensorBufferUint8).isNotNull();
+-    assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(6);
+-  }
++    @Test
++    public void testCreateFixedSize() {
++        int[] shape = new int[] {1, 2, 3};
++        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
++        assertThat(tensorBufferUint8).isNotNull();
++        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(6);
++    }
+ 
+-  @Test
+-  public void testCreateFixedSizeWithScalarShape() {
+-    int[] shape = new int[] {};
+-    TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
+-    assertThat(tensorBufferUint8).isNotNull();
+-    assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(1);
+-  }
++    @Test
++    public void testCreateFixedSizeWithScalarShape() {
++        int[] shape = new int[] {};
++        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
++        assertThat(tensorBufferUint8).isNotNull();
++        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(1);
++    }
+ 
+-  @Test
+-  public void testCreateWithNullShape() {
+-    int[] shape = null;
+-    Assert.assertThrows(NullPointerException.class, () -> new TensorBufferUint8(shape));
+-  }
++    @Test
++    public void testCreateWithNullShape() {
++        int[] shape = null;
++        Assert.assertThrows(NullPointerException.class, () -> new TensorBufferUint8(shape));
++    }
+ 
+-  @Test
+-  public void testCreateWithInvalidShape() {
+-    int[] shape = new int[] {1, -1, 2};
+-    Assert.assertThrows(IllegalArgumentException.class, () -> new TensorBufferUint8(shape));
+-  }
++    @Test
++    public void testCreateWithInvalidShape() {
++        int[] shape = new int[] {1, -1, 2};
++        Assert.assertThrows(IllegalArgumentException.class, () -> new TensorBufferUint8(shape));
++    }
+ 
+-  @Test
+-  public void testCreateUsingShapeWithZero() {
+-    int[] shape = new int[] {1, 0, 2};
+-    TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
+-    assertThat(tensorBufferUint8).isNotNull();
+-    assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(0);
+-  }
++    @Test
++    public void testCreateUsingShapeWithZero() {
++        int[] shape = new int[] {1, 0, 2};
++        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
++        assertThat(tensorBufferUint8).isNotNull();
++        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(0);
++    }
+ 
+-  @Test
+-  public void testGetDataType() {
+-    TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8();
+-    assertThat(tensorBufferUint8.getDataType()).isEqualTo(DataType.UINT8);
+-  }
++    @Test
++    public void testGetDataType() {
++        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8();
++        assertThat(tensorBufferUint8.getDataType()).isEqualTo(DataType.UINT8);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc
+index d62da546a484b..c3c21fa43ab49 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc
+@@ -134,7 +134,8 @@ jobject ConvertToClassificationResults(JNIEnv* env,
+ }
+ 
+ // Creates an AudioClassifierOptions proto based on the Java class.
+-AudioClassifierOptions ConvertToProtoOptions(JNIEnv* env, jobject java_options,
++AudioClassifierOptions ConvertToProtoOptions(JNIEnv* env,
++                                             jobject java_options,
+                                              jlong base_options_handle) {
+   AudioClassifierOptions proto_options;
+ 
+@@ -214,7 +215,9 @@ jlong CreateAudioClassifierFromOptions(JNIEnv* env,
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<AudioClassifier*>(native_handle);
+ }
+ 
+@@ -223,9 +226,13 @@ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_deinitJni(
+ // values will be ignored.
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_initJniWithModelFdAndOptions(
+-    JNIEnv* env, jclass thiz, jint file_descriptor,
+-    jlong file_descriptor_length, jlong file_descriptor_offset,
+-    jobject java_options, jlong base_options_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jint file_descriptor,
++    jlong file_descriptor_length,
++    jlong file_descriptor_offset,
++    jobject java_options,
++    jlong base_options_handle) {
+   AudioClassifierOptions proto_options =
+       ConvertToProtoOptions(env, java_options, base_options_handle);
+   auto file_descriptor_meta = proto_options.mutable_base_options()
+@@ -243,7 +250,10 @@ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_initJniWithModelF
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_initJniWithByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject model_buffer, jobject java_options,
++    JNIEnv* env,
++    jclass thiz,
++    jobject model_buffer,
++    jobject java_options,
+     jlong base_options_handle) {
+   AudioClassifierOptions proto_options =
+       ConvertToProtoOptions(env, java_options, base_options_handle);
+@@ -262,7 +272,9 @@ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_initJniWithByteBu
+ // caching it in JAVA layer.
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredSampleRateNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle) {
+   auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+   StatusOr<AudioBuffer::AudioFormat> format_or =
+       classifier->GetRequiredAudioFormat();
+@@ -279,7 +291,9 @@ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredSample
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredChannelsNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle) {
+   auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+   StatusOr<AudioBuffer::AudioFormat> format_or =
+       classifier->GetRequiredAudioFormat();
+@@ -296,15 +310,21 @@ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredChanne
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredInputBufferSizeNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle) {
+   auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+   return classifier->GetRequiredInputBufferSize();
+ }
+ 
+ extern "C" JNIEXPORT jobject JNICALL
+ Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_classifyNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle, jbyteArray java_array,
+-    jint channels, jint sample_rate) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle,
++    jbyteArray java_array,
++    jint channels,
++    jint sample_rate) {
+   // Get the primitive native array. Depending on the JAVA runtime, the returned
+   // array might be a copy of the JAVA array (or not).
+   jbyte* native_array = env->GetByteArrayElements(java_array, nullptr);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc
+index 2fd1d7ca9a593..75f93d6f2e458 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc
+@@ -30,7 +30,10 @@ using ::tflite::task::core::BaseOptions;
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_core_TaskJniUtils_createProtoBaseOptions(
+-    JNIEnv* env, jclass thiz, jint delegate, jint num_threads) {
++    JNIEnv* env,
++    jclass thiz,
++    jint delegate,
++    jint num_threads) {
+   StatusOr<Delegate> delegate_proto_or = ConvertToProtoDelegate(delegate);
+   if (!delegate_proto_or.ok()) {
+     ThrowException(env, kIllegalStateException,
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc
+index 6657ef4ca2d95..2daacdf893903 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc
+@@ -32,7 +32,9 @@ using ::tflite::task::text::BertNLClassifierOptions;
+ using ::tflite::task::text::nlclassifier::RunClassifier;
+ 
+ BertNLClassifierOptions ConvertJavaBertNLClassifierOptions(
+-    JNIEnv* env, jobject java_options, jlong base_options_handle) {
++    JNIEnv* env,
++    jobject java_options,
++    jlong base_options_handle) {
+   BertNLClassifierOptions proto_options;
+ 
+   if (base_options_handle != kInvalidPointer) {
+@@ -47,13 +49,18 @@ BertNLClassifierOptions ConvertJavaBertNLClassifierOptions(
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<BertNLClassifier*>(native_handle);
+ }
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject model_buffer, jobject java_options,
++    JNIEnv* env,
++    jclass thiz,
++    jobject model_buffer,
++    jobject java_options,
+     jlong base_options_handle) {
+   BertNLClassifierOptions proto_options = ConvertJavaBertNLClassifierOptions(
+       env, java_options, base_options_handle);
+@@ -76,7 +83,10 @@ Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithByte
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithFileDescriptor(
+-    JNIEnv* env, jclass thiz, jint fd, jobject java_options,
++    JNIEnv* env,
++    jclass thiz,
++    jint fd,
++    jobject java_options,
+     jlong base_options_handle) {
+   BertNLClassifierOptions proto_options = ConvertJavaBertNLClassifierOptions(
+       env, java_options, base_options_handle);
+@@ -100,6 +110,9 @@ Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithFile
+ 
+ extern "C" JNIEXPORT jobject JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_classifyNative(
+-    JNIEnv* env, jclass clazz, jlong native_handle, jstring text) {
++    JNIEnv* env,
++    jclass clazz,
++    jlong native_handle,
++    jstring text) {
+   return RunClassifier(env, native_handle, text);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc
+index f6d34a5f74e2b..4c71a80ea1528 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc
+@@ -94,14 +94,19 @@ NLClassifierOptions ConvertToProtoOptions(JNIEnv* env,
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<NLClassifier*>(native_handle);
+ }
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_initJniWithByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject nl_classifier_options,
+-    jobject model_buffer, jlong base_options_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jobject nl_classifier_options,
++    jobject model_buffer,
++    jlong base_options_handle) {
+   auto model = GetMappedFileBuffer(env, model_buffer);
+   tflite::support::StatusOr<std::unique_ptr<NLClassifier>> classifier_or;
+ 
+@@ -125,7 +130,10 @@ Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_initJniWithByteBuff
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_initJniWithFileDescriptor(
+-    JNIEnv* env, jclass thiz, jobject nl_classifier_options, jint fd,
++    JNIEnv* env,
++    jclass thiz,
++    jobject nl_classifier_options,
++    jint fd,
+     jlong base_options_handle) {
+   tflite::support::StatusOr<std::unique_ptr<NLClassifier>> classifier_or;
+ 
+@@ -151,6 +159,9 @@ Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_initJniWithFileDesc
+ 
+ extern "C" JNIEXPORT jobject JNICALL
+ Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_classifyNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle, jstring text) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle,
++    jstring text) {
+   return RunClassifier(env, native_handle, text);
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc
+index c392c9a5a972f..401e6fbda3d9b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc
+@@ -52,14 +52,19 @@ BertQuestionAnswererOptions ConvertToProtoOptions(jlong base_options_handle) {
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<QuestionAnswerer*>(native_handle);
+ }
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithFileDescriptor(
+-    JNIEnv* env, jclass thiz, jint file_descriptor,
+-    jlong file_descriptor_length, jlong file_descriptor_offset,
++    JNIEnv* env,
++    jclass thiz,
++    jint file_descriptor,
++    jlong file_descriptor_length,
++    jlong file_descriptor_offset,
+     jlong base_options_handle) {
+   BertQuestionAnswererOptions proto_options =
+       ConvertToProtoOptions(base_options_handle);
+@@ -89,7 +94,9 @@ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithFileDescri
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithBertByteBuffers(
+-    JNIEnv* env, jclass thiz, jobjectArray model_buffers) {
++    JNIEnv* env,
++    jclass thiz,
++    jobjectArray model_buffers) {
+   absl::string_view model =
+       GetMappedFileBuffer(env, env->GetObjectArrayElement(model_buffers, 0));
+   absl::string_view vocab =
+@@ -111,7 +118,9 @@ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithBertByteBu
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithAlbertByteBuffers(
+-    JNIEnv* env, jclass thiz, jobjectArray model_buffers) {
++    JNIEnv* env,
++    jclass thiz,
++    jobjectArray model_buffers) {
+   absl::string_view model =
+       GetMappedFileBuffer(env, env->GetObjectArrayElement(model_buffers, 0));
+   absl::string_view sp_model =
+@@ -133,7 +142,10 @@ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithAlbertByte
+ 
+ extern "C" JNIEXPORT jobject JNICALL
+ Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_answerNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle, jstring context,
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle,
++    jstring context,
+     jstring question) {
+   auto* question_answerer = reinterpret_cast<QuestionAnswerer*>(native_handle);
+ 
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc
+index 18e2ee1a7d4ab..2a713cf8b63cf 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc
+@@ -54,7 +54,8 @@ using ::tflite::task::vision::ImageClassifier;
+ using ::tflite::task::vision::ImageClassifierOptions;
+ 
+ // Creates an ImageClassifierOptions proto based on the Java class.
+-ImageClassifierOptions ConvertToProtoOptions(JNIEnv* env, jobject java_options,
++ImageClassifierOptions ConvertToProtoOptions(JNIEnv* env,
++                                             jobject java_options,
+                                              jlong base_options_handle) {
+   ImageClassifierOptions proto_options;
+ 
+@@ -175,7 +176,9 @@ jlong CreateImageClassifierFromOptions(JNIEnv* env,
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<ImageClassifier*>(native_handle);
+ }
+ 
+@@ -184,9 +187,13 @@ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_deinitJni(
+ // values will be ignored.
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_initJniWithModelFdAndOptions(
+-    JNIEnv* env, jclass thiz, jint file_descriptor,
+-    jlong file_descriptor_length, jlong file_descriptor_offset,
+-    jobject java_options, jlong base_options_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jint file_descriptor,
++    jlong file_descriptor_length,
++    jlong file_descriptor_offset,
++    jobject java_options,
++    jlong base_options_handle) {
+   ImageClassifierOptions proto_options =
+       ConvertToProtoOptions(env, java_options, base_options_handle);
+   auto file_descriptor_meta = proto_options.mutable_base_options()
+@@ -204,7 +211,10 @@ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_initJniWithModel
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_initJniWithByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject model_buffer, jobject java_options,
++    JNIEnv* env,
++    jclass thiz,
++    jobject model_buffer,
++    jobject java_options,
+     jlong base_options_handle) {
+   ImageClassifierOptions proto_options =
+       ConvertToProtoOptions(env, java_options, base_options_handle);
+@@ -220,7 +230,10 @@ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_initJniWithByteB
+ 
+ extern "C" JNIEXPORT jobject JNICALL
+ Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_classifyNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle, jlong frame_buffer_handle,
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle,
++    jlong frame_buffer_handle,
+     jintArray jroi) {
+   auto* classifier = reinterpret_cast<ImageClassifier*>(native_handle);
+   // frame_buffer will be deleted after inference is done in
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc
+index 84bff227f2543..2cda1b500aeb5 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc
+@@ -31,8 +31,13 @@ using ::tflite::task::vision::FrameBuffer;
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFromByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject jimage_byte_buffer, jint width,
+-    jint height, jint jorientation, jint jcolor_space_type) {
++    JNIEnv* env,
++    jclass thiz,
++    jobject jimage_byte_buffer,
++    jint width,
++    jint height,
++    jint jorientation,
++    jint jcolor_space_type) {
+   auto frame_buffer_or = CreateFrameBufferFromByteBuffer(
+       env, jimage_byte_buffer, width, height, jorientation, jcolor_space_type);
+   if (frame_buffer_or.ok()) {
+@@ -49,8 +54,14 @@ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFro
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFromBytes(
+-    JNIEnv* env, jclass thiz, jbyteArray jimage_bytes, jint width, jint height,
+-    jint jorientation, jint jcolor_space_type, jlongArray jbyte_array_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jbyteArray jimage_bytes,
++    jint width,
++    jint height,
++    jint jorientation,
++    jint jcolor_space_type,
++    jlongArray jbyte_array_handle) {
+   auto frame_buffer_or =
+       CreateFrameBufferFromBytes(env, jimage_bytes, width, height, jorientation,
+                                  jcolor_space_type, jbyte_array_handle);
+@@ -68,9 +79,17 @@ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFro
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFromPlanes(
+-    JNIEnv* env, jclass thiz, jobject jy_plane, jobject ju_plane,
+-    jobject jv_plane, jint width, jint height, jint row_stride_y,
+-    jint row_stride_uv, jint pixel_stride_uv, jint orientation) {
++    JNIEnv* env,
++    jclass thiz,
++    jobject jy_plane,
++    jobject ju_plane,
++    jobject jv_plane,
++    jint width,
++    jint height,
++    jint row_stride_y,
++    jint row_stride_uv,
++    jint pixel_stride_uv,
++    jint orientation) {
+   auto frame_buffer_or = CreateFrameBufferFromYuvPlanes(
+       env, jy_plane, ju_plane, jv_plane, width, height, row_stride_y,
+       row_stride_uv, pixel_stride_uv, orientation);
+@@ -88,8 +107,11 @@ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFro
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_deleteFrameBuffer(
+-    JNIEnv* env, jobject thiz, jlong frame_buffer_handle,
+-    jlong byte_array_handle, jbyteArray jbyte_array) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong frame_buffer_handle,
++    jlong byte_array_handle,
++    jbyteArray jbyte_array) {
+   delete reinterpret_cast<FrameBuffer*>(frame_buffer_handle);
+   jbyte* bytes_ptr = reinterpret_cast<jbyte*>(byte_array_handle);
+   if (bytes_ptr != NULL) {
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc
+index ddb0b72a25b65..f720795263791 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc
+@@ -54,7 +54,8 @@ using ::tflite::task::vision::ObjectDetector;
+ using ::tflite::task::vision::ObjectDetectorOptions;
+ 
+ // Creates an ObjectDetectorOptions proto based on the Java class.
+-ObjectDetectorOptions ConvertToProtoOptions(JNIEnv* env, jobject java_options,
++ObjectDetectorOptions ConvertToProtoOptions(JNIEnv* env,
++                                            jobject java_options,
+                                             jlong base_options_handle) {
+   ObjectDetectorOptions proto_options;
+ 
+@@ -183,7 +184,9 @@ jlong CreateObjectDetectorFromOptions(JNIEnv* env,
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<ObjectDetector*>(native_handle);
+ }
+ 
+@@ -192,9 +195,13 @@ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_deinitJni(
+ // values will be ignored.
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_initJniWithModelFdAndOptions(
+-    JNIEnv* env, jclass thiz, jint file_descriptor,
+-    jlong file_descriptor_length, jlong file_descriptor_offset,
+-    jobject java_options, jlong base_options_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jint file_descriptor,
++    jlong file_descriptor_length,
++    jlong file_descriptor_offset,
++    jobject java_options,
++    jlong base_options_handle) {
+   ObjectDetectorOptions proto_options =
+       ConvertToProtoOptions(env, java_options, base_options_handle);
+   auto file_descriptor_meta = proto_options.mutable_base_options()
+@@ -212,7 +219,10 @@ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_initJniWithModelFdA
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_initJniWithByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject model_buffer, jobject java_options,
++    JNIEnv* env,
++    jclass thiz,
++    jobject model_buffer,
++    jobject java_options,
+     jlong base_options_handle) {
+   ObjectDetectorOptions proto_options =
+       ConvertToProtoOptions(env, java_options, base_options_handle);
+@@ -224,7 +234,10 @@ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_initJniWithByteBuff
+ 
+ extern "C" JNIEXPORT jobject JNICALL
+ Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_detectNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle, jlong frame_buffer_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle,
++    jlong frame_buffer_handle) {
+   auto* detector = reinterpret_cast<ObjectDetector*>(native_handle);
+   // frame_buffer will be deleted after inference is done in
+   // base_vision_api_jni.cc.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc
+index 1b08e56ed509b..e0c94e2ec72c6 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc
+@@ -135,8 +135,12 @@ StatusOr<FrameBuffer::Format> GetYUVImageFormat(const uint8* u_buffer,
+ }
+ 
+ StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromByteBuffer(
+-    JNIEnv* env, jobject jimage_byte_buffer, jint width, jint height,
+-    jint jorientation, jint jcolor_space_type) {
++    JNIEnv* env,
++    jobject jimage_byte_buffer,
++    jint width,
++    jint height,
++    jint jorientation,
++    jint jcolor_space_type) {
+   absl::string_view image = GetMappedFileBuffer(env, jimage_byte_buffer);
+   return CreateFromRawBuffer(
+       reinterpret_cast<const uint8*>(image.data()),
+@@ -146,8 +150,13 @@ StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromByteBuffer(
+ }
+ 
+ StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromBytes(
+-    JNIEnv* env, jbyteArray jimage_bytes, jint width, jint height,
+-    jint jorientation, jint jcolor_space_type, jlongArray jbyte_array_handle) {
++    JNIEnv* env,
++    jbyteArray jimage_bytes,
++    jint width,
++    jint height,
++    jint jorientation,
++    jint jcolor_space_type,
++    jlongArray jbyte_array_handle) {
+   jbyte* jimage_ptr = env->GetByteArrayElements(jimage_bytes, NULL);
+   // Free jimage_ptr together with frame_buffer after inference is finished.
+   jlong jimage_ptr_handle = reinterpret_cast<jlong>(jimage_ptr);
+@@ -168,9 +177,16 @@ StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromBytes(
+ }
+ 
+ StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromYuvPlanes(
+-    JNIEnv* env, jobject jy_plane, jobject ju_plane, jobject jv_plane,
+-    jint width, jint height, jint row_stride_y, jint row_stride_uv,
+-    jint pixel_stride_uv, jint jorientation) {
++    JNIEnv* env,
++    jobject jy_plane,
++    jobject ju_plane,
++    jobject jv_plane,
++    jint width,
++    jint height,
++    jint row_stride_y,
++    jint row_stride_uv,
++    jint pixel_stride_uv,
++    jint jorientation) {
+   const uint8* y_plane =
+       reinterpret_cast<const uint8*>(GetMappedFileBuffer(env, jy_plane).data());
+   const uint8* u_plane =
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h
+index dbe32f8a3f2a5..4d7ec17a1c042 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h
+@@ -34,23 +34,35 @@ FrameBuffer::Orientation ConvertToFrameBufferOrientation(JNIEnv* env,
+ 
+ // Creates FrameBuffer from a direct ByteBuffer.
+ ::tflite::support::StatusOr<std::unique_ptr<FrameBuffer>>
+-CreateFrameBufferFromByteBuffer(JNIEnv* env, jobject jimage_byte_buffer,
+-                                jint width, jint height, jint jorientation,
++CreateFrameBufferFromByteBuffer(JNIEnv* env,
++                                jobject jimage_byte_buffer,
++                                jint width,
++                                jint height,
++                                jint jorientation,
+                                 jint jcolor_space_type);
+ 
+ // Creates FrameBuffer from a byte array.
+ ::tflite::support::StatusOr<std::unique_ptr<FrameBuffer>>
+-CreateFrameBufferFromBytes(JNIEnv* env, jbyteArray jimage_bytes, jint width,
+-                           jint height, jint jorientation,
++CreateFrameBufferFromBytes(JNIEnv* env,
++                           jbyteArray jimage_bytes,
++                           jint width,
++                           jint height,
++                           jint jorientation,
+                            jint jcolor_space_type,
+                            jlongArray jbyte_array_handle);
+ 
+ // Creates FrameBuffer from YUV planes.
+ ::tflite::support::StatusOr<std::unique_ptr<FrameBuffer>>
+-CreateFrameBufferFromYuvPlanes(JNIEnv* env, jobject jy_plane, jobject ju_plane,
+-                               jobject jv_plane, jint width, jint height,
+-                               jint row_stride_y, jint row_stride_uv,
+-                               jint pixel_stride_uv, jint jorientation);
++CreateFrameBufferFromYuvPlanes(JNIEnv* env,
++                               jobject jy_plane,
++                               jobject ju_plane,
++                               jobject jv_plane,
++                               jint width,
++                               jint height,
++                               jint row_stride_y,
++                               jint row_stride_uv,
++                               jint pixel_stride_uv,
++                               jint jorientation);
+ }  // namespace vision
+ }  // namespace task
+ }  // namespace tflite
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc
+index 40fa4472d37e1..8d8c8eec34295 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc
+@@ -194,7 +194,9 @@ jlong CreateImageSegmenterFromOptions(JNIEnv* env,
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_deinitJni(
+-    JNIEnv* env, jobject thiz, jlong native_handle) {
++    JNIEnv* env,
++    jobject thiz,
++    jlong native_handle) {
+   delete reinterpret_cast<ImageSegmenter*>(native_handle);
+ }
+ 
+@@ -203,9 +205,14 @@ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_deinitJni(
+ // values will be ignored.
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithModelFdAndOptions(
+-    JNIEnv* env, jclass thiz, jint file_descriptor,
+-    jlong file_descriptor_length, jlong file_descriptor_offset,
+-    jstring display_names_locale, jint output_type, jlong base_options_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jint file_descriptor,
++    jlong file_descriptor_length,
++    jlong file_descriptor_offset,
++    jstring display_names_locale,
++    jint output_type,
++    jlong base_options_handle) {
+   ImageSegmenterOptions proto_options = ConvertToProtoOptions(
+       env, display_names_locale, output_type, base_options_handle);
+   auto file_descriptor_meta = proto_options.mutable_base_options()
+@@ -223,8 +230,12 @@ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithModelFd
+ 
+ extern "C" JNIEXPORT jlong JNICALL
+ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithByteBuffer(
+-    JNIEnv* env, jclass thiz, jobject model_buffer,
+-    jstring display_names_locale, jint output_type, jlong base_options_handle) {
++    JNIEnv* env,
++    jclass thiz,
++    jobject model_buffer,
++    jstring display_names_locale,
++    jint output_type,
++    jlong base_options_handle) {
+   ImageSegmenterOptions proto_options = ConvertToProtoOptions(
+       env, display_names_locale, output_type, base_options_handle);
+   proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+@@ -235,8 +246,13 @@ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithByteBuf
+ 
+ extern "C" JNIEXPORT void JNICALL
+ Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_segmentNative(
+-    JNIEnv* env, jclass thiz, jlong native_handle, jlong frame_buffer_handle,
+-    jobject jmask_buffers, jintArray jmask_shape, jobject jcolored_labels) {
++    JNIEnv* env,
++    jclass thiz,
++    jlong native_handle,
++    jlong frame_buffer_handle,
++    jobject jmask_buffers,
++    jintArray jmask_shape,
++    jobject jcolored_labels) {
+   auto* segmenter = reinterpret_cast<ImageSegmenter*>(native_handle);
+   // frame_buffer will be deleted after inference is done in
+   // base_vision_api_jni.cc.
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
+index 7a9843d61d63c..3aae0aa0ec5c7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
+@@ -17,11 +17,11 @@ limitations under the License.
+ 
+ #include <functional>
+ 
+-#include "absl/memory/memory.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
++#include "absl/memory/memory.h"       // from @com_google_absl
++#include "absl/status/status.h"       // from @com_google_absl
+ #include "absl/strings/str_format.h"  // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+-#include "lib/zip.h"  // from @org_libzip
++#include "lib/zip.h"                  // from @org_libzip
+ #include "tensorflow/lite/schema/schema_generated.h"
+ #include "tensorflow_lite_support/cc/common.h"
+ #include "tensorflow_lite_support/cc/port/status_macros.h"
+@@ -48,7 +48,8 @@ class SimpleCleanUp {
+       : callback_(std::move(callback)) {}
+ 
+   ~SimpleCleanUp() {
+-    if (callback_ != nullptr) callback_();
++    if (callback_ != nullptr)
++      callback_();
+   }
+ 
+   // Use `std::move(simple_cleanup).Cancel()` to prevent the callback from ever
+@@ -63,7 +64,8 @@ class SimpleCleanUp {
+ // Util to get item from src_vector specified by index.
+ template <typename T>
+ const T* GetItemFromVector(
+-    const flatbuffers::Vector<flatbuffers::Offset<T>>* src_vector, int index) {
++    const flatbuffers::Vector<flatbuffers::Offset<T>>* src_vector,
++    int index) {
+   if (src_vector == nullptr || index < 0 || index >= src_vector->size()) {
+     return nullptr;
+   }
+@@ -111,7 +113,8 @@ ModelMetadataExtractor::FindFirstProcessUnit(
+ /* static */
+ std::string ModelMetadataExtractor::FindFirstAssociatedFileName(
+     const tflite::TensorMetadata& tensor_metadata,
+-    tflite::AssociatedFileType type, absl::string_view locale) {
++    tflite::AssociatedFileType type,
++    absl::string_view locale) {
+   if (tensor_metadata.associated_files() == nullptr) {
+     return std::string();
+   }
+@@ -128,7 +131,8 @@ std::string ModelMetadataExtractor::FindFirstAssociatedFileName(
+ }
+ 
+ absl::Status ModelMetadataExtractor::InitFromModelBuffer(
+-    const char* buffer_data, size_t buffer_size) {
++    const char* buffer_data,
++    size_t buffer_size) {
+   // Rely on the simplest, base flatbuffers verifier. Here is not the place to
+   // e.g. use an OpResolver: we just want to make sure the buffer is valid to
+   // access the metadata.
+@@ -187,7 +191,8 @@ absl::Status ModelMetadataExtractor::InitFromModelBuffer(
+ }
+ 
+ absl::Status ModelMetadataExtractor::ExtractAssociatedFiles(
+-    const char* buffer_data, size_t buffer_size) {
++    const char* buffer_data,
++    size_t buffer_size) {
+   // Setup libzip error reporting.
+   zip_error_t error;
+   zip_error_init(&error);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h
+index bff8cdf5ef43e..dc9a992aee2be 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h
+@@ -16,8 +16,8 @@ limitations under the License.
+ #define TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_EXTRACTOR_H_
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "absl/strings/string_view.h"  // from @com_google_absl
++#include "absl/status/status.h"            // from @com_google_absl
++#include "absl/strings/string_view.h"      // from @com_google_absl
+ #include "tensorflow/lite/schema/schema_generated.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h
+index a18e19bdb7973..9037f5853744b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h
+@@ -17,8 +17,8 @@ limitations under the License.
+ #define TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_POPULATOR_H_
+ 
+ #include "absl/container/flat_hash_map.h"  // from @com_google_absl
+-#include "absl/status/status.h"  // from @com_google_absl
+-#include "flatbuffers/flatbuffers.h"  // from @flatbuffers
++#include "absl/status/status.h"            // from @com_google_absl
++#include "flatbuffers/flatbuffers.h"       // from @flatbuffers
+ #include "tensorflow/lite/schema/schema_generated.h"
+ #include "tensorflow_lite_support/cc/port/statusor.h"
+ #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+@@ -77,7 +77,8 @@ class ModelMetadataPopulator {
+   // Zips and appends associated files to the provided model buffer. Called
+   // internally by `Populate()`.
+   tflite::support::StatusOr<std::string> AppendAssociatedFiles(
+-      const char* model_buffer_data, size_t model_buffer_size);
++      const char* model_buffer_data,
++      size_t model_buffer_size);
+ 
+   // The unpacked model FlatBuffer.
+   tflite::ModelT model_t_;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc
+index fb3e01e00b76d..ed75b656e70a2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc
+@@ -22,7 +22,7 @@ limitations under the License.
+ #include <string>
+ #include <vector>
+ 
+-#include "absl/strings/str_join.h"  // from @com_google_absl
++#include "absl/strings/str_join.h"   // from @com_google_absl
+ #include "absl/strings/str_split.h"  // from @com_google_absl
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+ #include "tensorflow/lite/c/common.h"
+@@ -134,7 +134,8 @@ template <typename T>
+ void UpdateMinimumVersionForArray(
+     const flatbuffers::Vector<flatbuffers::Offset<T>>* array,
+     Version* min_version) {
+-  if (array == nullptr) return;
++  if (array == nullptr)
++    return;
+ 
+   for (int i = 0; i < array->size(); ++i) {
+     UpdateMinimumVersionForTable<T>(array->Get(i), min_version);
+@@ -143,8 +144,10 @@ void UpdateMinimumVersionForArray(
+ 
+ template <>
+ void UpdateMinimumVersionForTable<tflite::AssociatedFile>(
+-    const tflite::AssociatedFile* table, Version* min_version) {
+-  if (table == nullptr) return;
++    const tflite::AssociatedFile* table,
++    Version* min_version) {
++  if (table == nullptr)
++    return;
+ 
+   if (table->type() == AssociatedFileType_VOCABULARY) {
+     UpdateMinimumVersion(
+@@ -155,8 +158,10 @@ void UpdateMinimumVersionForTable<tflite::AssociatedFile>(
+ 
+ template <>
+ void UpdateMinimumVersionForTable<tflite::ProcessUnit>(
+-    const tflite::ProcessUnit* table, Version* min_version) {
+-  if (table == nullptr) return;
++    const tflite::ProcessUnit* table,
++    Version* min_version) {
++  if (table == nullptr)
++    return;
+ 
+   tflite::ProcessUnitOptions process_unit_type = table->options_type();
+   if (process_unit_type == ProcessUnitOptions_BertTokenizerOptions) {
+@@ -182,7 +187,8 @@ void UpdateMinimumVersionForTable<tflite::ProcessUnit>(
+ template <>
+ void UpdateMinimumVersionForTable<tflite::Content>(const tflite::Content* table,
+                                                    Version* min_version) {
+-  if (table == nullptr) return;
++  if (table == nullptr)
++    return;
+ 
+   // Checks the ContenProperties field.
+   if (table->content_properties_type() == ContentProperties_AudioProperties) {
+@@ -194,8 +200,10 @@ void UpdateMinimumVersionForTable<tflite::Content>(const tflite::Content* table,
+ 
+ template <>
+ void UpdateMinimumVersionForTable<tflite::TensorMetadata>(
+-    const tflite::TensorMetadata* table, Version* min_version) {
+-  if (table == nullptr) return;
++    const tflite::TensorMetadata* table,
++    Version* min_version) {
++  if (table == nullptr)
++    return;
+ 
+   // Checks the associated_files field.
+   UpdateMinimumVersionForArray<tflite::AssociatedFile>(
+@@ -211,8 +219,10 @@ void UpdateMinimumVersionForTable<tflite::TensorMetadata>(
+ 
+ template <>
+ void UpdateMinimumVersionForTable<tflite::SubGraphMetadata>(
+-    const tflite::SubGraphMetadata* table, Version* min_version) {
+-  if (table == nullptr) return;
++    const tflite::SubGraphMetadata* table,
++    Version* min_version) {
++  if (table == nullptr)
++    return;
+ 
+   // Checks in the input/output metadata arrays.
+   UpdateMinimumVersionForArray<tflite::TensorMetadata>(
+@@ -259,7 +269,8 @@ void UpdateMinimumVersionForTable<tflite::SubGraphMetadata>(
+ 
+ template <>
+ void UpdateMinimumVersionForTable<tflite::ModelMetadata>(
+-    const tflite::ModelMetadata* table, Version* min_version) {
++    const tflite::ModelMetadata* table,
++    Version* min_version) {
+   if (table == nullptr) {
+     // Should never happen, because VerifyModelMetadataBuffer has verified it.
+     TFLITE_LOG(FATAL) << "The ModelMetadata object is null.";
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/flatbuffers_lib.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/flatbuffers_lib.cc
+index 6185722504f69..8e00452bea983 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/flatbuffers_lib.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/flatbuffers_lib.cc
+@@ -14,7 +14,7 @@ limitations under the License.
+ ==============================================================================*/
+ 
+ #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+-#include "flatbuffers/idl.h"  // from @flatbuffers
++#include "flatbuffers/idl.h"          // from @flatbuffers
+ #include "pybind11/pybind11.h"
+ #include "pybind11/pytypes.h"
+ #include "pybind11/stl.h"
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/BoundedInputStream.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/BoundedInputStream.java
+index 6c3d23270f3f0..15bcb45c1a4b1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/BoundedInputStream.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/BoundedInputStream.java
+@@ -33,84 +33,84 @@ import java.nio.ByteBuffer;
+  * synchronized as well.
+  */
+ final class BoundedInputStream extends InputStream {
+-  private final ByteBuffer singleByteBuffer = ByteBuffer.allocate(1);
+-  private final long end; // The valid data for the stream is between [start, end).
+-  private long position;
+-  private final SeekableByteChannelCompat channel;
+-
+-  /**
+-   * Creates a {@link BoundedInputStream} with a {@link SeekableByteChannelCompat}.
+-   *
+-   * @param channel the {@link SeekableByteChannelCompat} that backs up this {@link
+-   *     BoundedInputStream}
+-   * @param start the starting position of this {@link BoundedInputStream} in the given {@link
+-   *     SeekableByteChannelCompat}
+-   * @param remaining the length of this {@link BoundedInputStream}
+-   * @throws IllegalArgumentException if {@code start} or {@code remaining} is negative
+-   */
+-  BoundedInputStream(SeekableByteChannelCompat channel, long start, long remaining) {
+-    checkArgument(
+-        remaining >= 0 && start >= 0,
+-        String.format("Invalid length of stream at offset=%d, length=%d", start, remaining));
+-
+-    end = start + remaining;
+-    this.channel = channel;
+-    position = start;
+-  }
+-
+-  @Override
+-  public int available() throws IOException {
+-    return (int) (Math.min(end, channel.size()) - position);
+-  }
+-
+-  @Override
+-  public int read() throws IOException {
+-    if (position >= end) {
+-      return -1;
++    private final ByteBuffer singleByteBuffer = ByteBuffer.allocate(1);
++    private final long end; // The valid data for the stream is between [start, end).
++    private long position;
++    private final SeekableByteChannelCompat channel;
++
++    /**
++     * Creates a {@link BoundedInputStream} with a {@link SeekableByteChannelCompat}.
++     *
++     * @param channel the {@link SeekableByteChannelCompat} that backs up this {@link
++     *     BoundedInputStream}
++     * @param start the starting position of this {@link BoundedInputStream} in the given {@link
++     *     SeekableByteChannelCompat}
++     * @param remaining the length of this {@link BoundedInputStream}
++     * @throws IllegalArgumentException if {@code start} or {@code remaining} is negative
++     */
++    BoundedInputStream(SeekableByteChannelCompat channel, long start, long remaining) {
++        checkArgument(remaining >= 0 && start >= 0,
++                String.format(
++                        "Invalid length of stream at offset=%d, length=%d", start, remaining));
++
++        end = start + remaining;
++        this.channel = channel;
++        position = start;
+     }
+ 
+-    singleByteBuffer.rewind();
+-    int count = read(position, singleByteBuffer);
+-    if (count < 0) {
+-      return count;
++    @Override
++    public int available() throws IOException {
++        return (int) (Math.min(end, channel.size()) - position);
+     }
+ 
+-    position++;
+-    return singleByteBuffer.get() & 0xff;
+-  }
++    @Override
++    public int read() throws IOException {
++        if (position >= end) {
++            return -1;
++        }
+ 
+-  @Override
+-  public int read(byte[] b, int off, int len) throws IOException {
+-    checkNotNull(b);
+-    checkElementIndex(off, b.length, "The start offset");
+-    checkElementIndex(len, b.length - off + 1, "The maximumn number of bytes to read");
++        singleByteBuffer.rewind();
++        int count = read(position, singleByteBuffer);
++        if (count < 0) {
++            return count;
++        }
+ 
+-    if (len == 0) {
+-      return 0;
++        position++;
++        return singleByteBuffer.get() & 0xff;
+     }
+ 
+-    if (len > end - position) {
+-      if (position >= end) {
+-        return -1;
+-      }
+-      len = (int) (end - position);
++    @Override
++    public int read(byte[] b, int off, int len) throws IOException {
++        checkNotNull(b);
++        checkElementIndex(off, b.length, "The start offset");
++        checkElementIndex(len, b.length - off + 1, "The maximumn number of bytes to read");
++
++        if (len == 0) {
++            return 0;
++        }
++
++        if (len > end - position) {
++            if (position >= end) {
++                return -1;
++            }
++            len = (int) (end - position);
++        }
++
++        ByteBuffer buf = ByteBuffer.wrap(b, off, len);
++        int count = read(position, buf);
++        if (count > 0) {
++            position += count;
++        }
++        return count;
+     }
+ 
+-    ByteBuffer buf = ByteBuffer.wrap(b, off, len);
+-    int count = read(position, buf);
+-    if (count > 0) {
+-      position += count;
++    private int read(long position, ByteBuffer buf) throws IOException {
++        int count;
++        synchronized (channel) {
++            channel.position(position);
++            count = channel.read(buf);
++        }
++        buf.flip();
++        return count;
+     }
+-    return count;
+-  }
+-
+-  private int read(long position, ByteBuffer buf) throws IOException {
+-    int count;
+-    synchronized (channel) {
+-      channel.position(position);
+-      count = channel.read(buf);
+-    }
+-    buf.flip();
+-    return count;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ByteBufferChannel.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ByteBufferChannel.java
+index e5d54a415edc4..354119b02822e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ByteBufferChannel.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ByteBufferChannel.java
+@@ -15,116 +15,114 @@ limitations under the License.
+ 
+ package org.tensorflow.lite.support.metadata;
+ 
+-import static java.lang.Math.min;
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkArgument;
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkNotNull;
+ 
++import static java.lang.Math.min;
++
+ import java.nio.ByteBuffer;
+ import java.nio.channels.NonWritableChannelException;
+ 
+ /** Implements the {@link SeekableByteChannelCompat} on top of {@link ByteBuffer}. */
+ final class ByteBufferChannel implements SeekableByteChannelCompat {
++    /** The ByteBuffer that holds the data. */
++    private final ByteBuffer buffer;
++
++    /**
++     * Creates a {@link ByteBufferChannel} that wraps a {@link ByteBuffer}.
++     *
++     * @param buffer the {@link ByteBuffer} that backs this {@link ByteBufferChannel}
++     * @throws NullPointerException if {@code buffer} is null
++     */
++    public ByteBufferChannel(ByteBuffer buffer) {
++        checkNotNull(buffer, "The ByteBuffer cannot be null.");
++        this.buffer = buffer;
++    }
++
++    @Override
++    public void close() {}
+ 
+-  /** The ByteBuffer that holds the data. */
+-  private final ByteBuffer buffer;
+-
+-  /**
+-   * Creates a {@link ByteBufferChannel} that wraps a {@link ByteBuffer}.
+-   *
+-   * @param buffer the {@link ByteBuffer} that backs this {@link ByteBufferChannel}
+-   * @throws NullPointerException if {@code buffer} is null
+-   */
+-  public ByteBufferChannel(ByteBuffer buffer) {
+-    checkNotNull(buffer, "The ByteBuffer cannot be null.");
+-    this.buffer = buffer;
+-  }
+-
+-  @Override
+-  public void close() {}
+-
+-  @Override
+-  public boolean isOpen() {
+-    return true;
+-  }
+-
+-  @Override
+-  public long position() {
+-    return buffer.position();
+-  }
+-
+-  /**
+-   * Sets this channel's position.
+-   *
+-   * @param newPosition the new position, a non-negative integer counting the number of bytes from
+-   *     the beginning of the entity
+-   * @return this channel
+-   * @throws IllegalArgumentException if the new position is negative, or greater than the size of
+-   *     the underlying {@link ByteBuffer}, or greater than Integer.MAX_VALUE
+-   */
+-  @Override
+-  public synchronized ByteBufferChannel position(long newPosition) {
+-    checkArgument(
+-        (newPosition >= 0 && newPosition <= Integer.MAX_VALUE),
+-        "The new position should be non-negative and be less than Integer.MAX_VALUE.");
+-    buffer.position((int) newPosition);
+-    return this;
+-  }
+-
+-  /**
+-   * {@inheritDoc}
+-   *
+-   * <p>Bytes are read starting at this channel's current position, and then the position is updated
+-   * with the number of bytes actually read. Otherwise this method behaves exactly as specified in
+-   * the {@link ReadableByteChannel} interface.
+-   */
+-  @Override
+-  public synchronized int read(ByteBuffer dst) {
+-    if (buffer.remaining() == 0) {
+-      return -1;
++    @Override
++    public boolean isOpen() {
++        return true;
+     }
+ 
+-    int count = min(dst.remaining(), buffer.remaining());
+-    if (count > 0) {
+-      ByteBuffer tempBuffer = buffer.slice();
+-      tempBuffer.order(buffer.order()).limit(count);
+-      dst.put(tempBuffer);
+-      buffer.position(buffer.position() + count);
++    @Override
++    public long position() {
++        return buffer.position();
+     }
+-    return count;
+-  }
+-
+-  @Override
+-  public long size() {
+-    return buffer.limit();
+-  }
+-
+-  @Override
+-  public synchronized ByteBufferChannel truncate(long size) {
+-    checkArgument(
+-        (size >= 0 && size <= Integer.MAX_VALUE),
+-        "The new size should be non-negative and be less than Integer.MAX_VALUE.");
+-
+-    if (size < buffer.limit()) {
+-      buffer.limit((int) size);
+-      if (buffer.position() > size) {
+-        buffer.position((int) size);
+-      }
++
++    /**
++     * Sets this channel's position.
++     *
++     * @param newPosition the new position, a non-negative integer counting the number of bytes from
++     *     the beginning of the entity
++     * @return this channel
++     * @throws IllegalArgumentException if the new position is negative, or greater than the size of
++     *     the underlying {@link ByteBuffer}, or greater than Integer.MAX_VALUE
++     */
++    @Override
++    public synchronized ByteBufferChannel position(long newPosition) {
++        checkArgument((newPosition >= 0 && newPosition <= Integer.MAX_VALUE),
++                "The new position should be non-negative and be less than Integer.MAX_VALUE.");
++        buffer.position((int) newPosition);
++        return this;
++    }
++
++    /**
++     * {@inheritDoc}
++     *
++     * <p>Bytes are read starting at this channel's current position, and then the position is
++     * updated with the number of bytes actually read. Otherwise this method behaves exactly as
++     * specified in the {@link ReadableByteChannel} interface.
++     */
++    @Override
++    public synchronized int read(ByteBuffer dst) {
++        if (buffer.remaining() == 0) {
++            return -1;
++        }
++
++        int count = min(dst.remaining(), buffer.remaining());
++        if (count > 0) {
++            ByteBuffer tempBuffer = buffer.slice();
++            tempBuffer.order(buffer.order()).limit(count);
++            dst.put(tempBuffer);
++            buffer.position(buffer.position() + count);
++        }
++        return count;
++    }
++
++    @Override
++    public long size() {
++        return buffer.limit();
+     }
+-    return this;
+-  }
+ 
+-  @Override
+-  public synchronized int write(ByteBuffer src) {
+-    if (buffer.isReadOnly()) {
+-      throw new NonWritableChannelException();
++    @Override
++    public synchronized ByteBufferChannel truncate(long size) {
++        checkArgument((size >= 0 && size <= Integer.MAX_VALUE),
++                "The new size should be non-negative and be less than Integer.MAX_VALUE.");
++
++        if (size < buffer.limit()) {
++            buffer.limit((int) size);
++            if (buffer.position() > size) {
++                buffer.position((int) size);
++            }
++        }
++        return this;
+     }
+ 
+-    int count = min(src.remaining(), buffer.remaining());
+-    if (count > 0) {
+-      ByteBuffer tempBuffer = src.slice();
+-      tempBuffer.order(buffer.order()).limit(count);
+-      buffer.put(tempBuffer);
++    @Override
++    public synchronized int write(ByteBuffer src) {
++        if (buffer.isReadOnly()) {
++            throw new NonWritableChannelException();
++        }
++
++        int count = min(src.remaining(), buffer.remaining());
++        if (count > 0) {
++            ByteBuffer tempBuffer = src.slice();
++            tempBuffer.order(buffer.order()).limit(count);
++            buffer.put(tempBuffer);
++        }
++        return count;
+     }
+-    return count;
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataExtractor.java
+index 183d416481156..3fb3c48118748 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataExtractor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataExtractor.java
+@@ -17,15 +17,16 @@ package org.tensorflow.lite.support.metadata;
+ 
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkArgument;
+ 
++import org.checkerframework.checker.nullness.qual.Nullable;
++import org.tensorflow.lite.schema.Tensor;
++import org.tensorflow.lite.support.metadata.schema.ModelMetadata;
++import org.tensorflow.lite.support.metadata.schema.TensorMetadata;
++
+ import java.io.IOException;
+ import java.io.InputStream;
+ import java.nio.ByteBuffer;
+ import java.util.Set;
+ import java.util.zip.ZipException;
+-import org.checkerframework.checker.nullness.qual.Nullable;
+-import org.tensorflow.lite.schema.Tensor;
+-import org.tensorflow.lite.support.metadata.schema.ModelMetadata;
+-import org.tensorflow.lite.support.metadata.schema.TensorMetadata;
+ 
+ /**
+  * Loads metadata from TFLite Model FlatBuffer.
+@@ -53,328 +54,329 @@ import org.tensorflow.lite.support.metadata.schema.TensorMetadata;
+  * MetadataExtractor} omits subgraph index as an input in its methods.
+  */
+ public class MetadataExtractor {
++    /** The helper class to load metadata from TFLite model FlatBuffer. */
++    private final ModelInfo modelInfo;
++
++    /** The helper class to load metadata from TFLite metadata FlatBuffer. */
++    @Nullable
++    private final ModelMetadataInfo metadataInfo;
++
++    /** The handler to load associated files through zip. */
++    @Nullable
++    private final ZipFile zipFile;
++
++    /**
++     * Creates a {@link MetadataExtractor} with TFLite model FlatBuffer.
++     *
++     * @param buffer the TFLite model FlatBuffer
++     * @throws IllegalArgumentException if the number of input or output tensors in the model does
++     *         not
++     *     match that in the metadata
++     * @throws IOException if an error occurs while reading the model as a Zip file
++     */
++    public MetadataExtractor(ByteBuffer buffer) throws IOException {
++        modelInfo = new ModelInfo(buffer);
++        ByteBuffer metadataBuffer = modelInfo.getMetadataBuffer();
++        if (metadataBuffer != null) {
++            metadataInfo = new ModelMetadataInfo(metadataBuffer);
++
++            // Prints warning message if the minimum parser version is not satisfied.
++            if (!isMinimumParserVersionSatisfied()) {
++                System.err.printf(
++                        "<Warning> Some fields in the metadata belong to a future schema. The minimum parser"
++                                + " version required is %s, but the version of the current metadata parser is %s",
++                        metadataInfo.getMininumParserVersion(), MetadataParser.VERSION);
++            }
++
++            checkArgument(modelInfo.getInputTensorCount() == metadataInfo.getInputTensorCount(),
++                    String.format(
++                            "The number of input tensors in the model is %d. The number of input tensors that"
++                                    + " recorded in the metadata is %d. These two values does not match.",
++                            modelInfo.getInputTensorCount(), metadataInfo.getInputTensorCount()));
++            checkArgument(modelInfo.getOutputTensorCount() == metadataInfo.getOutputTensorCount(),
++                    String.format(
++                            "The number of output tensors in the model is %d. The number of output tensors that"
++                                    + " recorded in the metadata is %d. These two values does not match.",
++                            modelInfo.getOutputTensorCount(), metadataInfo.getOutputTensorCount()));
++        } else {
++            // It is allowed to pass in a model FlatBuffer without TFLite metadata. However,
++            // invoking methods that read from TFLite metadata will cause runtime errors.
++            metadataInfo = null;
++        }
++
++        zipFile = createZipFile(buffer);
++    }
+ 
+-  /** The helper class to load metadata from TFLite model FlatBuffer. */
+-  private final ModelInfo modelInfo;
+-
+-  /** The helper class to load metadata from TFLite metadata FlatBuffer. */
+-  @Nullable private final ModelMetadataInfo metadataInfo;
+-
+-  /** The handler to load associated files through zip. */
+-  @Nullable private final ZipFile zipFile;
+-
+-  /**
+-   * Creates a {@link MetadataExtractor} with TFLite model FlatBuffer.
+-   *
+-   * @param buffer the TFLite model FlatBuffer
+-   * @throws IllegalArgumentException if the number of input or output tensors in the model does not
+-   *     match that in the metadata
+-   * @throws IOException if an error occurs while reading the model as a Zip file
+-   */
+-  public MetadataExtractor(ByteBuffer buffer) throws IOException {
+-    modelInfo = new ModelInfo(buffer);
+-    ByteBuffer metadataBuffer = modelInfo.getMetadataBuffer();
+-    if (metadataBuffer != null) {
+-      metadataInfo = new ModelMetadataInfo(metadataBuffer);
+-
+-      // Prints warning message if the minimum parser version is not satisfied.
+-      if (!isMinimumParserVersionSatisfied()) {
+-        System.err.printf(
+-            "<Warning> Some fields in the metadata belong to a future schema. The minimum parser"
+-                + " version required is %s, but the version of the current metadata parser is %s",
+-            metadataInfo.getMininumParserVersion(), MetadataParser.VERSION);
+-      }
+-
+-      checkArgument(
+-          modelInfo.getInputTensorCount() == metadataInfo.getInputTensorCount(),
+-          String.format(
+-              "The number of input tensors in the model is %d. The number of input tensors that"
+-                  + " recorded in the metadata is %d. These two values does not match.",
+-              modelInfo.getInputTensorCount(), metadataInfo.getInputTensorCount()));
+-      checkArgument(
+-          modelInfo.getOutputTensorCount() == metadataInfo.getOutputTensorCount(),
+-          String.format(
+-              "The number of output tensors in the model is %d. The number of output tensors that"
+-                  + " recorded in the metadata is %d. These two values does not match.",
+-              modelInfo.getOutputTensorCount(), metadataInfo.getOutputTensorCount()));
+-    } else {
+-      // It is allowed to pass in a model FlatBuffer without TFLite metadata. However, invoking
+-      // methods that read from TFLite metadata will cause runtime errors.
+-      metadataInfo = null;
++    /**
++     * Quantization parameters that corresponds to the table, {@code QuantizationParameters}, in the
++     * <a
++     * href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/schema/schema.fbs">TFLite
++     * Model schema file.</a>
++     *
++     * <p>Since per-channel quantization does not apply to input and output tensors, {@code scale}
++     * and
++     * {@code zero_point} are both single values instead of arrays.
++     *
++     * <p>For tensor that are not quantized, the values of scale and zero_point are both 0.
++     *
++     * <p>Given a quantized value q, the corresponding float value f should be: <br>
++     * f = scale * (q - zero_point) <br>
++     */
++    public static class QuantizationParams {
++        /** The scale value used in quantization. */
++        private final float scale;
++        /** The zero point value used in quantization. */
++        private final int zeroPoint;
++
++        /**
++         * Creates a {@link QuantizationParams} with {@code scale} and {@code zero_point}.
++         *
++         * @param scale The scale value used in quantization.
++         * @param zeroPoint The zero point value used in quantization.
++         */
++        public QuantizationParams(final float scale, final int zeroPoint) {
++            this.scale = scale;
++            this.zeroPoint = zeroPoint;
++        }
++
++        /** Returns the scale value. */
++        public float getScale() {
++            return scale;
++        }
++
++        /** Returns the zero point value. */
++        public int getZeroPoint() {
++            return zeroPoint;
++        }
+     }
+ 
+-    zipFile = createZipFile(buffer);
+-  }
+-
+-  /**
+-   * Quantization parameters that corresponds to the table, {@code QuantizationParameters}, in the
+-   * <a
+-   * href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/schema/schema.fbs">TFLite
+-   * Model schema file.</a>
+-   *
+-   * <p>Since per-channel quantization does not apply to input and output tensors, {@code scale} and
+-   * {@code zero_point} are both single values instead of arrays.
+-   *
+-   * <p>For tensor that are not quantized, the values of scale and zero_point are both 0.
+-   *
+-   * <p>Given a quantized value q, the corresponding float value f should be: <br>
+-   * f = scale * (q - zero_point) <br>
+-   */
+-  public static class QuantizationParams {
+-    /** The scale value used in quantization. */
+-    private final float scale;
+-    /** The zero point value used in quantization. */
+-    private final int zeroPoint;
++    /** Returns {@code true} if the model has metadata. Otherwise, returns {@code false}. */
++    public boolean hasMetadata() {
++        return metadataInfo != null;
++    }
+ 
+     /**
+-     * Creates a {@link QuantizationParams} with {@code scale} and {@code zero_point}.
++     * Gets the packed associated file with the specified {@code fileName}.
+      *
+-     * @param scale The scale value used in quantization.
+-     * @param zeroPoint The zero point value used in quantization.
++     * @param fileName the name of the associated file
++     * @return the raw input stream containing specified file
++     * @throws IllegalStateException if the model is not a zip file
++     * @throws IllegalArgumentException if the specified file does not exist in the model
+      */
+-    public QuantizationParams(final float scale, final int zeroPoint) {
+-      this.scale = scale;
+-      this.zeroPoint = zeroPoint;
++    public InputStream getAssociatedFile(String fileName) {
++        assertZipFile();
++        return zipFile.getRawInputStream(fileName);
+     }
+ 
+-    /** Returns the scale value. */
+-    public float getScale() {
+-      return scale;
++    /**
++     * Gets the file names of the associated files.
++     *
++     * @return the file names of the associated files
++     * @throws IllegalStateException if the model is not a zip file
++     */
++    public Set<String> getAssociatedFileNames() {
++        assertZipFile();
++        return zipFile.getFileNames();
+     }
+ 
+-    /** Returns the zero point value. */
+-    public int getZeroPoint() {
+-      return zeroPoint;
++    /** Gets the count of input tensors in the model. */
++    public int getInputTensorCount() {
++        return modelInfo.getInputTensorCount();
+     }
+-  }
+-
+-  /** Returns {@code true} if the model has metadata. Otherwise, returns {@code false}. */
+-  public boolean hasMetadata() {
+-    return metadataInfo != null;
+-  }
+-
+-  /**
+-   * Gets the packed associated file with the specified {@code fileName}.
+-   *
+-   * @param fileName the name of the associated file
+-   * @return the raw input stream containing specified file
+-   * @throws IllegalStateException if the model is not a zip file
+-   * @throws IllegalArgumentException if the specified file does not exist in the model
+-   */
+-  public InputStream getAssociatedFile(String fileName) {
+-    assertZipFile();
+-    return zipFile.getRawInputStream(fileName);
+-  }
+-
+-  /**
+-   * Gets the file names of the associated files.
+-   *
+-   * @return the file names of the associated files
+-   * @throws IllegalStateException if the model is not a zip file
+-   */
+-  public Set<String> getAssociatedFileNames() {
+-    assertZipFile();
+-    return zipFile.getFileNames();
+-  }
+-
+-  /** Gets the count of input tensors in the model. */
+-  public int getInputTensorCount() {
+-    return modelInfo.getInputTensorCount();
+-  }
+-
+-  /**
+-   * Gets the metadata for the input tensor specified by {@code inputIndex}.
+-   *
+-   * @param inputIndex the index of the desired input tensor
+-   * @throws IllegalStateException if this model does not contain model metadata
+-   */
+-  @Nullable
+-  public TensorMetadata getInputTensorMetadata(int inputIndex) {
+-    assertMetadataInfo();
+-    return metadataInfo.getInputTensorMetadata(inputIndex);
+-  }
+-
+-  /**
+-   * Gets the quantization parameters for the input tensor specified by {@code inputIndex}.
+-   *
+-   * @param inputIndex the index of the desired input tensor
+-   */
+-  public QuantizationParams getInputTensorQuantizationParams(int inputIndex) {
+-    Tensor tensor = modelInfo.getInputTensor(inputIndex);
+-    return modelInfo.getQuantizationParams(tensor);
+-  }
+-
+-  /**
+-   * Gets the shape of the input tensor with {@code inputIndex}.
+-   *
+-   * @param inputIndex the index of the desired input tensor
+-   */
+-  public int[] getInputTensorShape(int inputIndex) {
+-    return modelInfo.getInputTensorShape(inputIndex);
+-  }
+-
+-  /**
+-   * Gets the {@link TensorType} of the input tensor with {@code inputIndex}.
+-   *
+-   * @param inputIndex the index of the desired input tensor
+-   */
+-  public byte getInputTensorType(int inputIndex) {
+-    return modelInfo.getInputTensorType(inputIndex);
+-  }
+-
+-  /**
+-   * Gets the root handler for the model metadata.
+-   *
+-   * @throws IllegalStateException if this model does not contain model metadata
+-   */
+-  public ModelMetadata getModelMetadata() {
+-    assertMetadataInfo();
+-    return metadataInfo.getModelMetadata();
+-  }
+-
+-  /** Gets the count of output tensors in the model. */
+-  public int getOutputTensorCount() {
+-    return modelInfo.getOutputTensorCount();
+-  }
+-
+-  /**
+-   * Gets the metadata for the output tensor specified by {@code outputIndex}.
+-   *
+-   * @param outputIndex the index of the desired output tensor
+-   * @throws IllegalStateException if this model does not contain model metadata
+-   */
+-  @Nullable
+-  public TensorMetadata getOutputTensorMetadata(int outputIndex) {
+-    assertMetadataInfo();
+-    return metadataInfo.getOutputTensorMetadata(outputIndex);
+-  }
+-
+-  /**
+-   * Gets the quantization parameters for the output tensor specified by {@code outputIndex}.
+-   *
+-   * @param outputIndex the index of the desired output tensor
+-   */
+-  public QuantizationParams getOutputTensorQuantizationParams(int outputIndex) {
+-    Tensor tensor = modelInfo.getOutputTensor(outputIndex);
+-    return modelInfo.getQuantizationParams(tensor);
+-  }
+-
+-  /**
+-   * Gets the shape of the output tensor with {@code outputIndex}.
+-   *
+-   * @param outputIndex the index of the desired output tensor
+-   */
+-  public int[] getOutputTensorShape(int outputIndex) {
+-    return modelInfo.getOutputTensorShape(outputIndex);
+-  }
+-
+-  /**
+-   * Gets the {@link TensorType} of the output tensor with {@code outputIndex}.
+-   *
+-   * @param outputIndex the index of the desired output tensor
+-   */
+-  public byte getOutputTensorType(int outputIndex) {
+-    return modelInfo.getOutputTensorType(outputIndex);
+-  }
+-
+-  /**
+-   * Returns {@code true} if the minimum parser version required by the given metadata flatbuffer
+-   * precedes or equals to the version of the metadata parser that this MetadataExtractor library is
+-   * relying on. All fields in the metadata can be parsed correctly with this metadata extractor
+-   * library in this case. Otherwise, it returns {@code false}.
+-   *
+-   * <p>For example, assume the underlying metadata parser version is {@code 1.14.1},
+-   *
+-   * <ul>
+-   *   <li>it returns {@code true}, if the required minimum parser version is the same or older,
+-   *       such as {@code 1.14.1} or {@code 1.14.0}. Null version precedes all numeric versions,
+-   *       because some metadata flatbuffers are generated before the first versioned release; <br>
+-   *   <li>it returns {@code false}, if the required minimum parser version is newer, such as {@code
+-   *       1.14.2}.
+-   * </ul>
+-   */
+-  public final boolean isMinimumParserVersionSatisfied() {
+-    String minVersion = metadataInfo.getMininumParserVersion();
+-    if (minVersion == null) {
+-      return true;
++
++    /**
++     * Gets the metadata for the input tensor specified by {@code inputIndex}.
++     *
++     * @param inputIndex the index of the desired input tensor
++     * @throws IllegalStateException if this model does not contain model metadata
++     */
++    @Nullable
++    public TensorMetadata getInputTensorMetadata(int inputIndex) {
++        assertMetadataInfo();
++        return metadataInfo.getInputTensorMetadata(inputIndex);
+     }
+-    return compareVersions(minVersion, MetadataParser.VERSION) <= 0;
+-  }
+-
+-  /**
+-   * Asserts if {@link #metadataInfo} is not initialized. Some models may not have metadata and this
+-   * is allowed. However, invoking methods that reads the metadata is not allowed.
+-   *
+-   * @throws IllegalStateException if this model does not contain model metadata
+-   */
+-  private void assertMetadataInfo() {
+-    if (metadataInfo == null) {
+-      throw new IllegalStateException("This model does not contain model metadata.");
++
++    /**
++     * Gets the quantization parameters for the input tensor specified by {@code inputIndex}.
++     *
++     * @param inputIndex the index of the desired input tensor
++     */
++    public QuantizationParams getInputTensorQuantizationParams(int inputIndex) {
++        Tensor tensor = modelInfo.getInputTensor(inputIndex);
++        return modelInfo.getQuantizationParams(tensor);
+     }
+-  }
+-
+-  /**
+-   * Asserts if {@link #zipFile} is not initialized. Some models may not have associated files, thus
+-   * are not Zip files. This is allowed. However, invoking methods that reads those associated files
+-   * is not allowed.
+-   *
+-   * @throws IllegalStateException if this model is not a Zip file
+-   */
+-  private void assertZipFile() {
+-    if (zipFile == null) {
+-      throw new IllegalStateException(
+-          "This model does not contain associated files, and is not a Zip file.");
++
++    /**
++     * Gets the shape of the input tensor with {@code inputIndex}.
++     *
++     * @param inputIndex the index of the desired input tensor
++     */
++    public int[] getInputTensorShape(int inputIndex) {
++        return modelInfo.getInputTensorShape(inputIndex);
+     }
+-  }
+-
+-  /**
+-   * Creates a Zip file handler to read the associated files. If the model is not a zip file, i.e.
+-   * it does not have associated files, return a null handler.
+-   *
+-   * @param buffer the TFLite model FlatBuffer
+-   * @throws IOException if an error occurs while reading the model as a Zip file
+-   */
+-  @Nullable
+-  private static ZipFile createZipFile(ByteBuffer buffer) throws IOException {
+-    try {
+-      // Creates the handler to hold the associated files through the Zip.
+-      ByteBufferChannel byteBufferChannel = new ByteBufferChannel(buffer);
+-      return ZipFile.createFrom(byteBufferChannel);
+-    } catch (ZipException e) {
+-      // Some models may not have associate files. Therefore, Those models are not zip files.
+-      // However, invoking methods that read associated files later will lead into errors.
+-      return null;
++
++    /**
++     * Gets the {@link TensorType} of the input tensor with {@code inputIndex}.
++     *
++     * @param inputIndex the index of the desired input tensor
++     */
++    public byte getInputTensorType(int inputIndex) {
++        return modelInfo.getInputTensorType(inputIndex);
+     }
+-  }
+-
+-  /**
+-   * Compares two semantic version numbers.
+-   *
+-   * <p>Examples of comparing two versions: <br>
+-   * {@code 1.9} precedes {@code 1.14}; <br>
+-   * {@code 1.14} precedes {@code 1.14.1}; <br>
+-   * {@code 1.14} and {@code 1.14.0} are euqal;
+-   *
+-   * @return the value {@code 0} if the two versions are equal; a value less than {@code 0} if
+-   *     {@code version1} precedes {@code version2}; a value greater than {@code 0} if {@code
+-   *     version2} precedes {@code version1}.
+-   */
+-  private static int compareVersions(String version1, String version2) {
+-    // Using String.split instead of the recommanded Guava Splitter because we've been avoiding
+-    // depending on other third party libraries in this project.
+-    String[] levels1 = version1.split("\\.", 0);
+-    String[] levels2 = version2.split("\\.", 0);
+-
+-    int length = Math.max(levels1.length, levels2.length);
+-    for (int i = 0; i < length; i++) {
+-      Integer v1 = i < levels1.length ? Integer.parseInt(levels1[i]) : 0;
+-      Integer v2 = i < levels2.length ? Integer.parseInt(levels2[i]) : 0;
+-      int compare = v1.compareTo(v2);
+-      if (compare != 0) {
+-        return compare;
+-      }
++
++    /**
++     * Gets the root handler for the model metadata.
++     *
++     * @throws IllegalStateException if this model does not contain model metadata
++     */
++    public ModelMetadata getModelMetadata() {
++        assertMetadataInfo();
++        return metadataInfo.getModelMetadata();
++    }
++
++    /** Gets the count of output tensors in the model. */
++    public int getOutputTensorCount() {
++        return modelInfo.getOutputTensorCount();
+     }
+ 
+-    return 0;
+-  }
++    /**
++     * Gets the metadata for the output tensor specified by {@code outputIndex}.
++     *
++     * @param outputIndex the index of the desired output tensor
++     * @throws IllegalStateException if this model does not contain model metadata
++     */
++    @Nullable
++    public TensorMetadata getOutputTensorMetadata(int outputIndex) {
++        assertMetadataInfo();
++        return metadataInfo.getOutputTensorMetadata(outputIndex);
++    }
++
++    /**
++     * Gets the quantization parameters for the output tensor specified by {@code outputIndex}.
++     *
++     * @param outputIndex the index of the desired output tensor
++     */
++    public QuantizationParams getOutputTensorQuantizationParams(int outputIndex) {
++        Tensor tensor = modelInfo.getOutputTensor(outputIndex);
++        return modelInfo.getQuantizationParams(tensor);
++    }
++
++    /**
++     * Gets the shape of the output tensor with {@code outputIndex}.
++     *
++     * @param outputIndex the index of the desired output tensor
++     */
++    public int[] getOutputTensorShape(int outputIndex) {
++        return modelInfo.getOutputTensorShape(outputIndex);
++    }
++
++    /**
++     * Gets the {@link TensorType} of the output tensor with {@code outputIndex}.
++     *
++     * @param outputIndex the index of the desired output tensor
++     */
++    public byte getOutputTensorType(int outputIndex) {
++        return modelInfo.getOutputTensorType(outputIndex);
++    }
++
++    /**
++     * Returns {@code true} if the minimum parser version required by the given metadata flatbuffer
++     * precedes or equals to the version of the metadata parser that this MetadataExtractor library
++     * is relying on. All fields in the metadata can be parsed correctly with this metadata
++     * extractor library in this case. Otherwise, it returns {@code false}.
++     *
++     * <p>For example, assume the underlying metadata parser version is {@code 1.14.1},
++     *
++     * <ul>
++     *   <li>it returns {@code true}, if the required minimum parser version is the same or older,
++     *       such as {@code 1.14.1} or {@code 1.14.0}. Null version precedes all numeric versions,
++     *       because some metadata flatbuffers are generated before the first versioned release;
++     * <br> <li>it returns {@code false}, if the required minimum parser version is newer, such as
++     * {@code 1.14.2}.
++     * </ul>
++     */
++    public final boolean isMinimumParserVersionSatisfied() {
++        String minVersion = metadataInfo.getMininumParserVersion();
++        if (minVersion == null) {
++            return true;
++        }
++        return compareVersions(minVersion, MetadataParser.VERSION) <= 0;
++    }
++
++    /**
++     * Asserts if {@link #metadataInfo} is not initialized. Some models may not have metadata and
++     * this is allowed. However, invoking methods that reads the metadata is not allowed.
++     *
++     * @throws IllegalStateException if this model does not contain model metadata
++     */
++    private void assertMetadataInfo() {
++        if (metadataInfo == null) {
++            throw new IllegalStateException("This model does not contain model metadata.");
++        }
++    }
++
++    /**
++     * Asserts if {@link #zipFile} is not initialized. Some models may not have associated files,
++     * thus are not Zip files. This is allowed. However, invoking methods that reads those
++     * associated files is not allowed.
++     *
++     * @throws IllegalStateException if this model is not a Zip file
++     */
++    private void assertZipFile() {
++        if (zipFile == null) {
++            throw new IllegalStateException(
++                    "This model does not contain associated files, and is not a Zip file.");
++        }
++    }
++
++    /**
++     * Creates a Zip file handler to read the associated files. If the model is not a zip file, i.e.
++     * it does not have associated files, return a null handler.
++     *
++     * @param buffer the TFLite model FlatBuffer
++     * @throws IOException if an error occurs while reading the model as a Zip file
++     */
++    @Nullable
++    private static ZipFile createZipFile(ByteBuffer buffer) throws IOException {
++        try {
++            // Creates the handler to hold the associated files through the Zip.
++            ByteBufferChannel byteBufferChannel = new ByteBufferChannel(buffer);
++            return ZipFile.createFrom(byteBufferChannel);
++        } catch (ZipException e) {
++            // Some models may not have associate files. Therefore, Those models are not zip files.
++            // However, invoking methods that read associated files later will lead into errors.
++            return null;
++        }
++    }
++
++    /**
++     * Compares two semantic version numbers.
++     *
++     * <p>Examples of comparing two versions: <br>
++     * {@code 1.9} precedes {@code 1.14}; <br>
++     * {@code 1.14} precedes {@code 1.14.1}; <br>
++     * {@code 1.14} and {@code 1.14.0} are euqal;
++     *
++     * @return the value {@code 0} if the two versions are equal; a value less than {@code 0} if
++     *     {@code version1} precedes {@code version2}; a value greater than {@code 0} if {@code
++     *     version2} precedes {@code version1}.
++     */
++    private static int compareVersions(String version1, String version2) {
++        // Using String.split instead of the recommanded Guava Splitter because we've been avoiding
++        // depending on other third party libraries in this project.
++        String[] levels1 = version1.split("\\.", 0);
++        String[] levels2 = version2.split("\\.", 0);
++
++        int length = Math.max(levels1.length, levels2.length);
++        for (int i = 0; i < length; i++) {
++            Integer v1 = i < levels1.length ? Integer.parseInt(levels1[i]) : 0;
++            Integer v2 = i < levels2.length ? Integer.parseInt(levels2[i]) : 0;
++            int compare = v1.compareTo(v2);
++            if (compare != 0) {
++                return compare;
++            }
++        }
++
++        return 0;
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java
+index b6dd4a6216f11..20f556692f8f0 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java
+@@ -17,11 +17,11 @@ package org.tensorflow.lite.support.metadata;
+ 
+ /** Information about the metadata parser that this metadata extractor library is depending on. */
+ public final class MetadataParser {
+-  /**
+-   * The version of the metadata parser that this metadata extractor library is depending on. The
+-   * value should match the value of "Schema Semantic version" in metadata_schema.fbs.
+-   */
+-  public static final String VERSION = "1.3.0";
++    /**
++     * The version of the metadata parser that this metadata extractor library is depending on. The
++     * value should match the value of "Schema Semantic version" in metadata_schema.fbs.
++     */
++    public static final String VERSION = "1.3.0";
+ 
+-  private MetadataParser() {}
++    private MetadataParser() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelInfo.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelInfo.java
+index 309a3dbe77470..863ab83e306fb 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelInfo.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelInfo.java
+@@ -18,10 +18,6 @@ package org.tensorflow.lite.support.metadata;
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkArgument;
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkNotNull;
+ 
+-import java.nio.ByteBuffer;
+-import java.util.ArrayList;
+-import java.util.Collections;
+-import java.util.List;
+ import org.checkerframework.checker.nullness.qual.Nullable;
+ import org.tensorflow.lite.schema.Buffer;
+ import org.tensorflow.lite.schema.Metadata;
+@@ -32,235 +28,237 @@ import org.tensorflow.lite.schema.Tensor;
+ import org.tensorflow.lite.schema.TensorType;
+ import org.tensorflow.lite.support.metadata.MetadataExtractor.QuantizationParams;
+ 
++import java.nio.ByteBuffer;
++import java.util.ArrayList;
++import java.util.Collections;
++import java.util.List;
++
+ /** Extracts model information out of TFLite model FLatBuffer. */
+ final class ModelInfo {
+-  /** The model that is loaded from TFLite model FlatBuffer. */
+-  private final Model model;
+-
+-  /** A list of input tensors. */
+-  private final List</* @Nullable */ Tensor> inputTensors;
+-
+-  /** A list of output tensors. */
+-  private final List</* @Nullable */ Tensor> outputTensors;
+-
+-  /** Identifier of the TFLite model metadata in the Metadata array. */
+-  static final String METADATA_FIELD_NAME = "TFLITE_METADATA";
+-
+-  /**
+-   * Creates a {@link ModelInfo} with the model FlatBuffer, {@code buffer}.
+-   *
+-   * <p>Though TFLite model FlatBuffer supports multiple subgraphs, TFLite Interpreter only supports
+-   * single subgraph so far. See the <a
+-   * href="https://www.tensorflow.org/lite/convert/cmdline_examples#specifying_subgraphs">instruction
+-   * of how to specify subgraph during convertion for more information.</a> Therefore, all methods
+-   * in {@link ModelInfo} retrieves metadata of the first subgrpah as default.
+-   *
+-   * @param buffer the TFLite model FlatBuffer
+-   * @throws NullPointerException if {@code buffer} is null
+-   * @throws IllegalArgumentException if the model does not contain any subgraph, or the model does
+-   *     not contain the expected identifier
+-   */
+-  ModelInfo(ByteBuffer buffer) {
+-    assertTFLiteModel(buffer);
+-
+-    model = Model.getRootAsModel(buffer);
+-    checkArgument(model.subgraphsLength() > 0, "The model does not contain any subgraph.");
+-
+-    inputTensors = getInputTensors(model);
+-    outputTensors = getOutputTensors(model);
+-  }
+-
+-  /**
+-   * Gets the input tensor with {@code inputIndex}.
+-   *
+-   * @param inputIndex The index of the desired input tensor.
+-   * @throws IllegalArgumentException if the inputIndex specified is invalid.
+-   */
+-  @Nullable
+-  Tensor getInputTensor(int inputIndex) {
+-    checkArgument(
+-        inputIndex >= 0 && inputIndex < inputTensors.size(),
+-        "The inputIndex specified is invalid.");
+-    return inputTensors.get(inputIndex);
+-  }
+-
+-  int getInputTensorCount() {
+-    return inputTensors.size();
+-  }
+-
+-  /**
+-   * Gets shape of the input tensor with {@code inputIndex}.
+-   *
+-   * @param inputIndex The index of the desired intput tensor.
+-   */
+-  int[] getInputTensorShape(int inputIndex) {
+-    Tensor tensor = getInputTensor(inputIndex);
+-    return getShape(tensor);
+-  }
+-
+-  /**
+-   * Gets the {@link TensorType} in byte of the input tensor with {@code inputIndex}.
+-   *
+-   * @param inputIndex The index of the desired intput tensor.
+-   */
+-  byte getInputTensorType(int inputIndex) {
+-    return getInputTensor(inputIndex).type();
+-  }
+-
+-  /** Gets the metadata FlatBuffer from the model FlatBuffer. */
+-  @Nullable
+-  ByteBuffer getMetadataBuffer() {
+-    // Some models may not have metadata, and this is allowed.
+-    if (model.metadataLength() == 0) {
+-      return null;
++    /** The model that is loaded from TFLite model FlatBuffer. */
++    private final Model model;
++
++    /** A list of input tensors. */
++    private final List</* @Nullable */ Tensor> inputTensors;
++
++    /** A list of output tensors. */
++    private final List</* @Nullable */ Tensor> outputTensors;
++
++    /** Identifier of the TFLite model metadata in the Metadata array. */
++    static final String METADATA_FIELD_NAME = "TFLITE_METADATA";
++
++    /**
++     * Creates a {@link ModelInfo} with the model FlatBuffer, {@code buffer}.
++     *
++     * <p>Though TFLite model FlatBuffer supports multiple subgraphs, TFLite Interpreter only
++     * supports single subgraph so far. See the <a
++     * href="https://www.tensorflow.org/lite/convert/cmdline_examples#specifying_subgraphs">instruction
++     * of how to specify subgraph during convertion for more information.</a> Therefore, all methods
++     * in {@link ModelInfo} retrieves metadata of the first subgrpah as default.
++     *
++     * @param buffer the TFLite model FlatBuffer
++     * @throws NullPointerException if {@code buffer} is null
++     * @throws IllegalArgumentException if the model does not contain any subgraph, or the model
++     *         does
++     *     not contain the expected identifier
++     */
++    ModelInfo(ByteBuffer buffer) {
++        assertTFLiteModel(buffer);
++
++        model = Model.getRootAsModel(buffer);
++        checkArgument(model.subgraphsLength() > 0, "The model does not contain any subgraph.");
++
++        inputTensors = getInputTensors(model);
++        outputTensors = getOutputTensors(model);
++    }
++
++    /**
++     * Gets the input tensor with {@code inputIndex}.
++     *
++     * @param inputIndex The index of the desired input tensor.
++     * @throws IllegalArgumentException if the inputIndex specified is invalid.
++     */
++    @Nullable
++    Tensor getInputTensor(int inputIndex) {
++        checkArgument(inputIndex >= 0 && inputIndex < inputTensors.size(),
++                "The inputIndex specified is invalid.");
++        return inputTensors.get(inputIndex);
++    }
++
++    int getInputTensorCount() {
++        return inputTensors.size();
++    }
++
++    /**
++     * Gets shape of the input tensor with {@code inputIndex}.
++     *
++     * @param inputIndex The index of the desired intput tensor.
++     */
++    int[] getInputTensorShape(int inputIndex) {
++        Tensor tensor = getInputTensor(inputIndex);
++        return getShape(tensor);
+     }
+ 
+-    for (int i = 0; i < model.metadataLength(); i++) {
+-      Metadata meta = model.metadata(i);
+-      if (METADATA_FIELD_NAME.equals(meta.name())) {
+-        long bufferIndex = meta.buffer();
+-        Buffer metadataBuf = model.buffers((int) bufferIndex);
+-        return metadataBuf.dataAsByteBuffer();
+-      }
++    /**
++     * Gets the {@link TensorType} in byte of the input tensor with {@code inputIndex}.
++     *
++     * @param inputIndex The index of the desired intput tensor.
++     */
++    byte getInputTensorType(int inputIndex) {
++        return getInputTensor(inputIndex).type();
+     }
+-    return null;
+-  }
+-
+-  /**
+-   * Gets the output tensor with {@code outputIndex}.
+-   *
+-   * @param outputIndex The index of the desired outtput tensor.
+-   * @throws IllegalArgumentException if the outputIndex specified is invalid.
+-   */
+-  @Nullable
+-  Tensor getOutputTensor(int outputIndex) {
+-    checkArgument(
+-        outputIndex >= 0 && outputIndex < outputTensors.size(),
+-        "The outputIndex specified is invalid.");
+-    return outputTensors.get(outputIndex);
+-  }
+-
+-  int getOutputTensorCount() {
+-    return outputTensors.size();
+-  }
+-
+-  /**
+-   * Gets shape of the output tensor with {@code outputIndex}.
+-   *
+-   * @param outputIndex The index of the desired outtput tensor.
+-   */
+-  int[] getOutputTensorShape(int outputIndex) {
+-    Tensor tensor = getOutputTensor(outputIndex);
+-    return getShape(tensor);
+-  }
+-
+-  /**
+-   * Gets the {@link TensorType} in byte of the output tensor {@code outputIndex}.
+-   *
+-   * @param outputIndex The index of the desired outtput tensor.
+-   */
+-  byte getOutputTensorType(int outputIndex) {
+-    return getOutputTensor(outputIndex).type();
+-  }
+-
+-  /**
+-   * Gets the quantization parameters of a tensor.
+-   *
+-   * <p>Only quantized tensors have valid {@code QuantizationParameters}. For tensor that are not
+-   * quantized, the values of scale and zero_point are both 0.
+-   *
+-   * @param tensor The tensor whoes quantization parameters is desired.
+-   * @throws NullPointerException if the tensor is null.
+-   * @throws IllegalArgumentException if {@code scale} and {@code zeroPoint} of the tensor's {@link
+-   *     QuantizationParameters} are not single values.
+-   */
+-  QuantizationParams getQuantizationParams(Tensor tensor) {
+-    checkNotNull(tensor, "Tensor cannot be null.");
+-
+-    float scale;
+-    int zeroPoint;
+-    QuantizationParameters quantization = tensor.quantization();
+-
+-    // Tensors that are not quantized do not have quantization parameters, which can be null when
+-    // being extracted from the flatbuffer.
+-    if (quantization == null) {
+-      scale = 0.0f;
+-      zeroPoint = 0;
+-      return new QuantizationParams(scale, zeroPoint);
++
++    /** Gets the metadata FlatBuffer from the model FlatBuffer. */
++    @Nullable
++    ByteBuffer getMetadataBuffer() {
++        // Some models may not have metadata, and this is allowed.
++        if (model.metadataLength() == 0) {
++            return null;
++        }
++
++        for (int i = 0; i < model.metadataLength(); i++) {
++            Metadata meta = model.metadata(i);
++            if (METADATA_FIELD_NAME.equals(meta.name())) {
++                long bufferIndex = meta.buffer();
++                Buffer metadataBuf = model.buffers((int) bufferIndex);
++                return metadataBuf.dataAsByteBuffer();
++            }
++        }
++        return null;
++    }
++
++    /**
++     * Gets the output tensor with {@code outputIndex}.
++     *
++     * @param outputIndex The index of the desired outtput tensor.
++     * @throws IllegalArgumentException if the outputIndex specified is invalid.
++     */
++    @Nullable
++    Tensor getOutputTensor(int outputIndex) {
++        checkArgument(outputIndex >= 0 && outputIndex < outputTensors.size(),
++                "The outputIndex specified is invalid.");
++        return outputTensors.get(outputIndex);
++    }
++
++    int getOutputTensorCount() {
++        return outputTensors.size();
++    }
++
++    /**
++     * Gets shape of the output tensor with {@code outputIndex}.
++     *
++     * @param outputIndex The index of the desired outtput tensor.
++     */
++    int[] getOutputTensorShape(int outputIndex) {
++        Tensor tensor = getOutputTensor(outputIndex);
++        return getShape(tensor);
+     }
+ 
+-    // Tensors that are not quantized do not have quantization parameters.
+-    // quantization.scaleLength() and quantization.zeroPointLength() may both return 0.
+-    checkArgument(
+-        quantization.scaleLength() <= 1,
+-        "Input and output tensors do not support per-channel quantization.");
+-    checkArgument(
+-        quantization.zeroPointLength() <= 1,
+-        "Input and output tensors do not support per-channel quantization.");
+-
+-    // For tensors that are not quantized, quantization.scale(0) and quantization.zeroPoint(0) will
+-    // both be the default value in flatbuffer, 0. This behavior is consistent with the TFlite C++
+-    // runtime.
+-    scale = quantization.scale(0);
+-    // zeroPoint is a long value in the schema, but an integer in the C++ runtime. Here we keep it
+-    // consistent with the C++ runtime.
+-    zeroPoint = (int) quantization.zeroPoint(0);
+-
+-    return new QuantizationParams(scale, zeroPoint);
+-  }
+-
+-  /**
+-   * Verifies if the buffer is a valid TFLite model.
+-   *
+-   * @param buffer the TFLite model flatbuffer
+-   * @throws NullPointerException if {@code buffer} is null.
+-   * @throws IllegalArgumentException if {@code buffer} does not contain the expected identifier
+-   */
+-  private static void assertTFLiteModel(ByteBuffer buffer) {
+-    checkNotNull(buffer, "Model flatbuffer cannot be null.");
+-    checkArgument(
+-        Model.ModelBufferHasIdentifier(buffer),
+-        "The identifier of the model is invalid. The buffer may not be a valid TFLite model"
+-            + " flatbuffer.");
+-  }
+-
+-  /**
+-   * Gets the shape of a tensor.
+-   *
+-   * @param tensor The tensor whoes shape is desired.
+-   * @throws NullPointerException if the tensor is null.
+-   */
+-  private static int[] getShape(Tensor tensor) {
+-    checkNotNull(tensor, "Tensor cannot be null.");
+-    int shapeDim = tensor.shapeLength();
+-    int[] tensorShape = new int[shapeDim];
+-    for (int i = 0; i < shapeDim; i++) {
+-      tensorShape[i] = tensor.shape(i);
++    /**
++     * Gets the {@link TensorType} in byte of the output tensor {@code outputIndex}.
++     *
++     * @param outputIndex The index of the desired outtput tensor.
++     */
++    byte getOutputTensorType(int outputIndex) {
++        return getOutputTensor(outputIndex).type();
+     }
+-    return tensorShape;
+-  }
+-
+-  /** Gets input tensors from a model. */
+-  private static List<Tensor> getInputTensors(Model model) {
+-    // TFLite only support one subgraph currently.
+-    SubGraph subgraph = model.subgraphs(0);
+-    int tensorNum = subgraph.inputsLength();
+-    ArrayList<Tensor> inputTensors = new ArrayList<>(tensorNum);
+-    for (int i = 0; i < tensorNum; i++) {
+-      inputTensors.add(subgraph.tensors(subgraph.inputs(i)));
++
++    /**
++     * Gets the quantization parameters of a tensor.
++     *
++     * <p>Only quantized tensors have valid {@code QuantizationParameters}. For tensor that are not
++     * quantized, the values of scale and zero_point are both 0.
++     *
++     * @param tensor The tensor whoes quantization parameters is desired.
++     * @throws NullPointerException if the tensor is null.
++     * @throws IllegalArgumentException if {@code scale} and {@code zeroPoint} of the tensor's
++     *         {@link
++     *     QuantizationParameters} are not single values.
++     */
++    QuantizationParams getQuantizationParams(Tensor tensor) {
++        checkNotNull(tensor, "Tensor cannot be null.");
++
++        float scale;
++        int zeroPoint;
++        QuantizationParameters quantization = tensor.quantization();
++
++        // Tensors that are not quantized do not have quantization parameters, which can be null
++        // when being extracted from the flatbuffer.
++        if (quantization == null) {
++            scale = 0.0f;
++            zeroPoint = 0;
++            return new QuantizationParams(scale, zeroPoint);
++        }
++
++        // Tensors that are not quantized do not have quantization parameters.
++        // quantization.scaleLength() and quantization.zeroPointLength() may both return 0.
++        checkArgument(quantization.scaleLength() <= 1,
++                "Input and output tensors do not support per-channel quantization.");
++        checkArgument(quantization.zeroPointLength() <= 1,
++                "Input and output tensors do not support per-channel quantization.");
++
++        // For tensors that are not quantized, quantization.scale(0) and quantization.zeroPoint(0)
++        // will both be the default value in flatbuffer, 0. This behavior is consistent with the
++        // TFlite C++ runtime.
++        scale = quantization.scale(0);
++        // zeroPoint is a long value in the schema, but an integer in the C++ runtime. Here we keep
++        // it consistent with the C++ runtime.
++        zeroPoint = (int) quantization.zeroPoint(0);
++
++        return new QuantizationParams(scale, zeroPoint);
+     }
+-    return Collections.unmodifiableList(inputTensors);
+-  }
+-
+-  /** Gets output tensors from a model. */
+-  private static List<Tensor> getOutputTensors(Model model) {
+-    // TFLite only support one subgraph currently.
+-    SubGraph subgraph = model.subgraphs(0);
+-    int tensorNum = subgraph.outputsLength();
+-    ArrayList<Tensor> outputTensors = new ArrayList<>(tensorNum);
+-    for (int i = 0; i < tensorNum; i++) {
+-      outputTensors.add(subgraph.tensors(subgraph.outputs(i)));
++
++    /**
++     * Verifies if the buffer is a valid TFLite model.
++     *
++     * @param buffer the TFLite model flatbuffer
++     * @throws NullPointerException if {@code buffer} is null.
++     * @throws IllegalArgumentException if {@code buffer} does not contain the expected identifier
++     */
++    private static void assertTFLiteModel(ByteBuffer buffer) {
++        checkNotNull(buffer, "Model flatbuffer cannot be null.");
++        checkArgument(Model.ModelBufferHasIdentifier(buffer),
++                "The identifier of the model is invalid. The buffer may not be a valid TFLite model"
++                        + " flatbuffer.");
++    }
++
++    /**
++     * Gets the shape of a tensor.
++     *
++     * @param tensor The tensor whoes shape is desired.
++     * @throws NullPointerException if the tensor is null.
++     */
++    private static int[] getShape(Tensor tensor) {
++        checkNotNull(tensor, "Tensor cannot be null.");
++        int shapeDim = tensor.shapeLength();
++        int[] tensorShape = new int[shapeDim];
++        for (int i = 0; i < shapeDim; i++) {
++            tensorShape[i] = tensor.shape(i);
++        }
++        return tensorShape;
++    }
++
++    /** Gets input tensors from a model. */
++    private static List<Tensor> getInputTensors(Model model) {
++        // TFLite only support one subgraph currently.
++        SubGraph subgraph = model.subgraphs(0);
++        int tensorNum = subgraph.inputsLength();
++        ArrayList<Tensor> inputTensors = new ArrayList<>(tensorNum);
++        for (int i = 0; i < tensorNum; i++) {
++            inputTensors.add(subgraph.tensors(subgraph.inputs(i)));
++        }
++        return Collections.unmodifiableList(inputTensors);
++    }
++
++    /** Gets output tensors from a model. */
++    private static List<Tensor> getOutputTensors(Model model) {
++        // TFLite only support one subgraph currently.
++        SubGraph subgraph = model.subgraphs(0);
++        int tensorNum = subgraph.outputsLength();
++        ArrayList<Tensor> outputTensors = new ArrayList<>(tensorNum);
++        for (int i = 0; i < tensorNum; i++) {
++            outputTensors.add(subgraph.tensors(subgraph.outputs(i)));
++        }
++        return Collections.unmodifiableList(outputTensors);
+     }
+-    return Collections.unmodifiableList(outputTensors);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelMetadataInfo.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelMetadataInfo.java
+index 751ed500dc2fc..7ee01df094283 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelMetadataInfo.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ModelMetadataInfo.java
+@@ -18,136 +18,133 @@ package org.tensorflow.lite.support.metadata;
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkArgument;
+ import static org.tensorflow.lite.support.metadata.Preconditions.checkNotNull;
+ 
+-import java.nio.ByteBuffer;
+-import java.util.ArrayList;
+-import java.util.Collections;
+-import java.util.List;
+ import org.checkerframework.checker.nullness.qual.Nullable;
+ import org.tensorflow.lite.support.metadata.schema.ModelMetadata;
+ import org.tensorflow.lite.support.metadata.schema.SubGraphMetadata;
+ import org.tensorflow.lite.support.metadata.schema.TensorMetadata;
+ 
++import java.nio.ByteBuffer;
++import java.util.ArrayList;
++import java.util.Collections;
++import java.util.List;
++
+ /** Extracts model metadata information out of TFLite metadata FlatBuffer. */
+ final class ModelMetadataInfo {
+-  /** The root handler for the model metadata. */
+-  private final ModelMetadata modelMetadata;
+-
+-  /** Metadata array of input tensors. */
+-  private final List</* @Nullable */ TensorMetadata> inputsMetadata;
+-
+-  /** Metadata array of output tensors. */
+-  private final List</* @Nullable */ TensorMetadata> outputsMetadata;
+-
+-  /** The minimum parser version required to fully understand the metadata flatbuffer. */
+-  private final String /* @Nullable */ minVersion;
+-
+-  /**
+-   * Creates a {@link ModelMetadataInfo} with the metadata FlatBuffer, {@code buffer}.
+-   *
+-   * @param buffer the TFLite metadata FlatBuffer
+-   * @throws NullPointerException if {@code buffer} is null
+-   * @throws IllegalArgumentException if {@code buffer} does not contain any subgraph metadata, or
+-   *     it does not contain the expected identifier
+-   */
+-  ModelMetadataInfo(ByteBuffer buffer) {
+-    assertTFLiteMetadata(buffer);
+-
+-    modelMetadata = ModelMetadata.getRootAsModelMetadata(buffer);
+-    checkArgument(
+-        modelMetadata.subgraphMetadataLength() > 0,
+-        "The metadata flatbuffer does not contain any subgraph metadata.");
+-
+-    inputsMetadata = getInputsMetadata(modelMetadata);
+-    outputsMetadata = getOutputsMetadata(modelMetadata);
+-    minVersion = modelMetadata.minParserVersion();
+-  }
+-
+-  /** Gets the count of input tensors with metadata in the metadata FlatBuffer. */
+-  int getInputTensorCount() {
+-    return inputsMetadata.size();
+-  }
+-
+-  /**
+-   * Gets the metadata for the input tensor specified by {@code inputIndex}.
+-   *
+-   * @param inputIndex The index of the desired intput tensor.
+-   * @throws IllegalArgumentException if the inputIndex specified is invalid.
+-   */
+-  @Nullable
+-  TensorMetadata getInputTensorMetadata(int inputIndex) {
+-    checkArgument(
+-        inputIndex >= 0 && inputIndex < inputsMetadata.size(),
+-        "The inputIndex specified is invalid.");
+-    return inputsMetadata.get(inputIndex);
+-  }
+-
+-  /**
+-   * Gets the minimum parser version of the metadata. It can be {@code null} if the version is not
+-   * populated.
+-   */
+-  @Nullable
+-  String getMininumParserVersion() {
+-    return minVersion;
+-  }
+-
+-  /** Gets the root handler for the model metadata. */
+-  ModelMetadata getModelMetadata() {
+-    return modelMetadata;
+-  }
+-
+-  /** Gets the count of output tensors with metadata in the metadata FlatBuffer. */
+-  int getOutputTensorCount() {
+-    return outputsMetadata.size();
+-  }
+-
+-  /**
+-   * Gets the metadata for the output tensor specified by {@code outputIndex}.
+-   *
+-   * @param outputIndex The index of the desired output tensor.
+-   * @throws IllegalArgumentException if the outputIndex specified is invalid.
+-   */
+-  @Nullable
+-  TensorMetadata getOutputTensorMetadata(int outputIndex) {
+-    checkArgument(
+-        outputIndex >= 0 && outputIndex < outputsMetadata.size(),
+-        "The outputIndex specified is invalid.");
+-    return outputsMetadata.get(outputIndex);
+-  }
+-
+-  /**
+-   * Verifies if the buffer is a valid TFLite metadata flatbuffer.
+-   *
+-   * @param buffer the TFLite metadata flatbuffer
+-   * @throws NullPointerException if {@code buffer} is null.
+-   * @throws IllegalArgumentException if {@code buffer} does not contain the expected identifier
+-   */
+-  private static void assertTFLiteMetadata(ByteBuffer buffer) {
+-    checkNotNull(buffer, "Metadata flatbuffer cannot be null.");
+-    checkArgument(
+-        ModelMetadata.ModelMetadataBufferHasIdentifier(buffer),
+-        "The identifier of the metadata is invalid. The buffer may not be a valid TFLite metadata"
+-            + " flatbuffer.");
+-  }
+-
+-  /** Gets metadata for all input tensors. */
+-  private static List<TensorMetadata> getInputsMetadata(ModelMetadata modelMetadata) {
+-    SubGraphMetadata subgraphMetadata = modelMetadata.subgraphMetadata(0);
+-    int tensorNum = subgraphMetadata.inputTensorMetadataLength();
+-    ArrayList<TensorMetadata> inputsMetadata = new ArrayList<>(tensorNum);
+-    for (int i = 0; i < tensorNum; i++) {
+-      inputsMetadata.add(subgraphMetadata.inputTensorMetadata(i));
++    /** The root handler for the model metadata. */
++    private final ModelMetadata modelMetadata;
++
++    /** Metadata array of input tensors. */
++    private final List</* @Nullable */ TensorMetadata> inputsMetadata;
++
++    /** Metadata array of output tensors. */
++    private final List</* @Nullable */ TensorMetadata> outputsMetadata;
++
++    /** The minimum parser version required to fully understand the metadata flatbuffer. */
++    private final String /* @Nullable */ minVersion;
++
++    /**
++     * Creates a {@link ModelMetadataInfo} with the metadata FlatBuffer, {@code buffer}.
++     *
++     * @param buffer the TFLite metadata FlatBuffer
++     * @throws NullPointerException if {@code buffer} is null
++     * @throws IllegalArgumentException if {@code buffer} does not contain any subgraph metadata, or
++     *     it does not contain the expected identifier
++     */
++    ModelMetadataInfo(ByteBuffer buffer) {
++        assertTFLiteMetadata(buffer);
++
++        modelMetadata = ModelMetadata.getRootAsModelMetadata(buffer);
++        checkArgument(modelMetadata.subgraphMetadataLength() > 0,
++                "The metadata flatbuffer does not contain any subgraph metadata.");
++
++        inputsMetadata = getInputsMetadata(modelMetadata);
++        outputsMetadata = getOutputsMetadata(modelMetadata);
++        minVersion = modelMetadata.minParserVersion();
++    }
++
++    /** Gets the count of input tensors with metadata in the metadata FlatBuffer. */
++    int getInputTensorCount() {
++        return inputsMetadata.size();
++    }
++
++    /**
++     * Gets the metadata for the input tensor specified by {@code inputIndex}.
++     *
++     * @param inputIndex The index of the desired intput tensor.
++     * @throws IllegalArgumentException if the inputIndex specified is invalid.
++     */
++    @Nullable
++    TensorMetadata getInputTensorMetadata(int inputIndex) {
++        checkArgument(inputIndex >= 0 && inputIndex < inputsMetadata.size(),
++                "The inputIndex specified is invalid.");
++        return inputsMetadata.get(inputIndex);
+     }
+-    return Collections.unmodifiableList(inputsMetadata);
+-  }
+-
+-  /** Gets metadata for all output tensors. */
+-  private static List<TensorMetadata> getOutputsMetadata(ModelMetadata modelMetadata) {
+-    SubGraphMetadata subgraphMetadata = modelMetadata.subgraphMetadata(0);
+-    int tensorNum = subgraphMetadata.outputTensorMetadataLength();
+-    ArrayList<TensorMetadata> outputsMetadata = new ArrayList<>(tensorNum);
+-    for (int i = 0; i < tensorNum; i++) {
+-      outputsMetadata.add(subgraphMetadata.outputTensorMetadata(i));
++
++    /**
++     * Gets the minimum parser version of the metadata. It can be {@code null} if the version is not
++     * populated.
++     */
++    @Nullable
++    String getMininumParserVersion() {
++        return minVersion;
++    }
++
++    /** Gets the root handler for the model metadata. */
++    ModelMetadata getModelMetadata() {
++        return modelMetadata;
++    }
++
++    /** Gets the count of output tensors with metadata in the metadata FlatBuffer. */
++    int getOutputTensorCount() {
++        return outputsMetadata.size();
++    }
++
++    /**
++     * Gets the metadata for the output tensor specified by {@code outputIndex}.
++     *
++     * @param outputIndex The index of the desired output tensor.
++     * @throws IllegalArgumentException if the outputIndex specified is invalid.
++     */
++    @Nullable
++    TensorMetadata getOutputTensorMetadata(int outputIndex) {
++        checkArgument(outputIndex >= 0 && outputIndex < outputsMetadata.size(),
++                "The outputIndex specified is invalid.");
++        return outputsMetadata.get(outputIndex);
++    }
++
++    /**
++     * Verifies if the buffer is a valid TFLite metadata flatbuffer.
++     *
++     * @param buffer the TFLite metadata flatbuffer
++     * @throws NullPointerException if {@code buffer} is null.
++     * @throws IllegalArgumentException if {@code buffer} does not contain the expected identifier
++     */
++    private static void assertTFLiteMetadata(ByteBuffer buffer) {
++        checkNotNull(buffer, "Metadata flatbuffer cannot be null.");
++        checkArgument(ModelMetadata.ModelMetadataBufferHasIdentifier(buffer),
++                "The identifier of the metadata is invalid. The buffer may not be a valid TFLite metadata"
++                        + " flatbuffer.");
++    }
++
++    /** Gets metadata for all input tensors. */
++    private static List<TensorMetadata> getInputsMetadata(ModelMetadata modelMetadata) {
++        SubGraphMetadata subgraphMetadata = modelMetadata.subgraphMetadata(0);
++        int tensorNum = subgraphMetadata.inputTensorMetadataLength();
++        ArrayList<TensorMetadata> inputsMetadata = new ArrayList<>(tensorNum);
++        for (int i = 0; i < tensorNum; i++) {
++            inputsMetadata.add(subgraphMetadata.inputTensorMetadata(i));
++        }
++        return Collections.unmodifiableList(inputsMetadata);
++    }
++
++    /** Gets metadata for all output tensors. */
++    private static List<TensorMetadata> getOutputsMetadata(ModelMetadata modelMetadata) {
++        SubGraphMetadata subgraphMetadata = modelMetadata.subgraphMetadata(0);
++        int tensorNum = subgraphMetadata.outputTensorMetadataLength();
++        ArrayList<TensorMetadata> outputsMetadata = new ArrayList<>(tensorNum);
++        for (int i = 0; i < tensorNum; i++) {
++            outputsMetadata.add(subgraphMetadata.outputTensorMetadata(i));
++        }
++        return Collections.unmodifiableList(outputsMetadata);
+     }
+-    return Collections.unmodifiableList(outputsMetadata);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/Preconditions.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/Preconditions.java
+index c2f20fbaacd76..ca3eed3490644 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/Preconditions.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/Preconditions.java
+@@ -19,166 +19,170 @@ import org.checkerframework.checker.nullness.qual.Nullable;
+ 
+ /** Static error checking util methods. */
+ final class Preconditions {
+-  /**
+-   * Ensures that an object reference passed as a parameter to the calling method is not null.
+-   *
+-   * @param reference an object reference
+-   * @return the non-null reference that was validated
+-   * @throws NullPointerException if {@code reference} is null
+-   */
+-  public static <T extends Object> T checkNotNull(T reference) {
+-    if (reference == null) {
+-      throw new NullPointerException("The object reference is null.");
++    /**
++     * Ensures that an object reference passed as a parameter to the calling method is not null.
++     *
++     * @param reference an object reference
++     * @return the non-null reference that was validated
++     * @throws NullPointerException if {@code reference} is null
++     */
++    public static <T extends Object> T checkNotNull(T reference) {
++        if (reference == null) {
++            throw new NullPointerException("The object reference is null.");
++        }
++        return reference;
+     }
+-    return reference;
+-  }
+-
+-  /**
+-   * Ensures that an object reference passed as a parameter to the calling method is not null.
+-   *
+-   * @param reference an object reference
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}
+-   * @return the non-null reference that was validated
+-   * @throws NullPointerException if {@code reference} is null
+-   */
+-  public static <T extends Object> T checkNotNull(T reference, @Nullable Object errorMessage) {
+-    if (reference == null) {
+-      throw new NullPointerException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures that an object reference passed as a parameter to the calling method is not null.
++     *
++     * @param reference an object reference
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}
++     * @return the non-null reference that was validated
++     * @throws NullPointerException if {@code reference} is null
++     */
++    public static <T extends Object> T checkNotNull(T reference, @Nullable Object errorMessage) {
++        if (reference == null) {
++            throw new NullPointerException(String.valueOf(errorMessage));
++        }
++        return reference;
++    }
++
++    /**
++     * Ensures that the given String is not empty and not null.
++     *
++     * @param string the String to test
++     * @return the non-null non-empty String that was validated
++     * @throws IllegalArgumentException if {@code string} is null or empty
++     */
++    public static String checkNotEmpty(String string) {
++        if (string == null || string.length() == 0) {
++            throw new IllegalArgumentException("Given String is empty or null.");
++        }
++        return string;
+     }
+-    return reference;
+-  }
+-
+-  /**
+-   * Ensures that the given String is not empty and not null.
+-   *
+-   * @param string the String to test
+-   * @return the non-null non-empty String that was validated
+-   * @throws IllegalArgumentException if {@code string} is null or empty
+-   */
+-  public static String checkNotEmpty(String string) {
+-    if (string == null || string.length() == 0) {
+-      throw new IllegalArgumentException("Given String is empty or null.");
++
++    /**
++     * Ensures that the given String is not empty and not null.
++     *
++     * @param string the String to test
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}
++     * @return the non-null non-empty String that was validated
++     * @throws IllegalArgumentException if {@code string} is null or empty
++     */
++    public static String checkNotEmpty(String string, Object errorMessage) {
++        if (string == null || string.length() == 0) {
++            throw new IllegalArgumentException(String.valueOf(errorMessage));
++        }
++        return string;
+     }
+-    return string;
+-  }
+-
+-  /**
+-   * Ensures that the given String is not empty and not null.
+-   *
+-   * @param string the String to test
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}
+-   * @return the non-null non-empty String that was validated
+-   * @throws IllegalArgumentException if {@code string} is null or empty
+-   */
+-  public static String checkNotEmpty(String string, Object errorMessage) {
+-    if (string == null || string.length() == 0) {
+-      throw new IllegalArgumentException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures the truth of an expression involving one or more parameters to the calling method.
++     *
++     * @param expression a boolean expression.
++     * @throws IllegalArgumentException if {@code expression} is false.
++     */
++    public static void checkArgument(boolean expression) {
++        if (!expression) {
++            throw new IllegalArgumentException();
++        }
+     }
+-    return string;
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving one or more parameters to the calling method.
+-   *
+-   * @param expression a boolean expression.
+-   * @throws IllegalArgumentException if {@code expression} is false.
+-   */
+-  public static void checkArgument(boolean expression) {
+-    if (!expression) {
+-      throw new IllegalArgumentException();
++
++    /**
++     * Ensures the truth of an expression involving one or more parameters to the calling method.
++     *
++     * @param expression a boolean expression.
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}.
++     * @throws IllegalArgumentException if {@code expression} is false.
++     */
++    public static void checkArgument(boolean expression, @Nullable Object errorMessage) {
++        if (!expression) {
++            throw new IllegalArgumentException(String.valueOf(errorMessage));
++        }
+     }
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving one or more parameters to the calling method.
+-   *
+-   * @param expression a boolean expression.
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}.
+-   * @throws IllegalArgumentException if {@code expression} is false.
+-   */
+-  public static void checkArgument(boolean expression, @Nullable Object errorMessage) {
+-    if (!expression) {
+-      throw new IllegalArgumentException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
++     * size
++     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
++     *
++     * @param index a user-supplied index identifying an element of an array, list or string
++     * @param size the size of that array, list or string
++     * @return the value of {@code index}
++     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
++     *         size}
++     * @throws IllegalArgumentException if {@code size} is negative
++     */
++    public static int checkElementIndex(int index, int size) {
++        return checkElementIndex(index, size, "index");
+     }
+-  }
+-
+-  /**
+-   * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of size
+-   * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
+-   *
+-   * @param index a user-supplied index identifying an element of an array, list or string
+-   * @param size the size of that array, list or string
+-   * @return the value of {@code index}
+-   * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code size}
+-   * @throws IllegalArgumentException if {@code size} is negative
+-   */
+-  public static int checkElementIndex(int index, int size) {
+-    return checkElementIndex(index, size, "index");
+-  }
+-
+-  /**
+-   * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of size
+-   * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
+-   *
+-   * @param index a user-supplied index identifying an element of an array, list or string
+-   * @param size the size of that array, list or string
+-   * @param desc the text to use to describe this index in an error message
+-   * @return the value of {@code index}
+-   * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code size}
+-   * @throws IllegalArgumentException if {@code size} is negative
+-   */
+-  public static int checkElementIndex(int index, int size, @Nullable String desc) {
+-    // Carefully optimized for execution by hotspot (explanatory comment above)
+-    if (index < 0 || index >= size) {
+-      throw new IndexOutOfBoundsException(badElementIndex(index, size, desc));
++
++    /**
++     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
++     * size
++     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
++     *
++     * @param index a user-supplied index identifying an element of an array, list or string
++     * @param size the size of that array, list or string
++     * @param desc the text to use to describe this index in an error message
++     * @return the value of {@code index}
++     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
++     *         size}
++     * @throws IllegalArgumentException if {@code size} is negative
++     */
++    public static int checkElementIndex(int index, int size, @Nullable String desc) {
++        // Carefully optimized for execution by hotspot (explanatory comment above)
++        if (index < 0 || index >= size) {
++            throw new IndexOutOfBoundsException(badElementIndex(index, size, desc));
++        }
++        return index;
+     }
+-    return index;
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving the state of the calling instance, but not
+-   * involving any parameters to the calling method.
+-   *
+-   * @param expression a boolean expression
+-   * @throws IllegalStateException if {@code expression} is false
+-   * @see Verify#verify Verify.verify()
+-   */
+-  public static void checkState(boolean expression) {
+-    if (!expression) {
+-      throw new IllegalStateException();
++
++    /**
++     * Ensures the truth of an expression involving the state of the calling instance, but not
++     * involving any parameters to the calling method.
++     *
++     * @param expression a boolean expression
++     * @throws IllegalStateException if {@code expression} is false
++     * @see Verify#verify Verify.verify()
++     */
++    public static void checkState(boolean expression) {
++        if (!expression) {
++            throw new IllegalStateException();
++        }
+     }
+-  }
+-
+-  /**
+-   * Ensures the truth of an expression involving the state of the calling instance, but not
+-   * involving any parameters to the calling method.
+-   *
+-   * @param expression a boolean expression
+-   * @param errorMessage the exception message to use if the check fails; will be converted to a
+-   *     string using {@link String#valueOf(Object)}
+-   * @throws IllegalStateException if {@code expression} is false
+-   * @see Verify#verify Verify.verify()
+-   */
+-  public static void checkState(boolean expression, @Nullable Object errorMessage) {
+-    if (!expression) {
+-      throw new IllegalStateException(String.valueOf(errorMessage));
++
++    /**
++     * Ensures the truth of an expression involving the state of the calling instance, but not
++     * involving any parameters to the calling method.
++     *
++     * @param expression a boolean expression
++     * @param errorMessage the exception message to use if the check fails; will be converted to a
++     *     string using {@link String#valueOf(Object)}
++     * @throws IllegalStateException if {@code expression} is false
++     * @see Verify#verify Verify.verify()
++     */
++    public static void checkState(boolean expression, @Nullable Object errorMessage) {
++        if (!expression) {
++            throw new IllegalStateException(String.valueOf(errorMessage));
++        }
+     }
+-  }
+-
+-  private static String badElementIndex(int index, int size, @Nullable String desc) {
+-    if (index < 0) {
+-      return String.format("%s (%s) must not be negative", desc, index);
+-    } else if (size < 0) {
+-      throw new IllegalArgumentException("negative size: " + size);
+-    } else { // index >= size
+-      return String.format("%s (%s) must be less than size (%s)", desc, index, size);
++
++    private static String badElementIndex(int index, int size, @Nullable String desc) {
++        if (index < 0) {
++            return String.format("%s (%s) must not be negative", desc, index);
++        } else if (size < 0) {
++            throw new IllegalArgumentException("negative size: " + size);
++        } else { // index >= size
++            return String.format("%s (%s) must be less than size (%s)", desc, index, size);
++        }
+     }
+-  }
+ 
+-  private Preconditions() {
+-    throw new AssertionError("Preconditions is Uninstantiable.");
+-  }
++    private Preconditions() {
++        throw new AssertionError("Preconditions is Uninstantiable.");
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/SeekableByteChannelCompat.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/SeekableByteChannelCompat.java
+index c655786755baa..1408a3a73d86b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/SeekableByteChannelCompat.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/SeekableByteChannelCompat.java
+@@ -29,79 +29,79 @@ import java.nio.channels.Channel;
+  * the MetadtaExtractor library consistent with the common used Java libraries.
+  */
+ interface SeekableByteChannelCompat extends Channel {
+-  /**
+-   * Reads a sequence of bytes from this channel into the given buffer.
+-   *
+-   * @param dst The buffer into which bytes are to be transferred
+-   * @return The number of bytes read, possibly zero, or <tt>-1</tt> if the channel has reached
+-   *     end-of-stream
+-   * @throws NonReadableChannelException If this channel was not opened for reading
+-   * @throws ClosedChannelException If this channel is closed
+-   * @throws AsynchronousCloseException If another thread closes this channel while the read
+-   *     operation is in progress
+-   * @throws ClosedByInterruptException If another thread interrupts the current thread while the
+-   *     read operation is in progress, thereby closing the channel and setting the current thread's
+-   *     interrupt status
+-   * @throws IOException If some other I/O error occurs
+-   */
+-  int read(ByteBuffer dst) throws IOException;
++    /**
++     * Reads a sequence of bytes from this channel into the given buffer.
++     *
++     * @param dst The buffer into which bytes are to be transferred
++     * @return The number of bytes read, possibly zero, or <tt>-1</tt> if the channel has reached
++     *     end-of-stream
++     * @throws NonReadableChannelException If this channel was not opened for reading
++     * @throws ClosedChannelException If this channel is closed
++     * @throws AsynchronousCloseException If another thread closes this channel while the read
++     *     operation is in progress
++     * @throws ClosedByInterruptException If another thread interrupts the current thread while the
++     *     read operation is in progress, thereby closing the channel and setting the current
++     * thread's interrupt status
++     * @throws IOException If some other I/O error occurs
++     */
++    int read(ByteBuffer dst) throws IOException;
+ 
+-  /**
+-   * Writes a sequence of bytes to this channel from the given buffer.
+-   *
+-   * @param src The buffer from which bytes are to be retrieved
+-   * @return The number of bytes written, possibly zero
+-   * @throws NonWritableChannelException If this channel was not opened for writing
+-   * @throws ClosedChannelException If this channel is closed
+-   * @throws AsynchronousCloseException If another thread closes this channel while the write
+-   *     operation is in progress
+-   * @throws ClosedByInterruptException If another thread interrupts the current thread while the
+-   *     write operation is in progress, thereby closing the channel and setting the current
+-   *     thread's interrupt status
+-   * @throws IOException If some other I/O error occurs
+-   */
+-  int write(ByteBuffer src) throws IOException;
++    /**
++     * Writes a sequence of bytes to this channel from the given buffer.
++     *
++     * @param src The buffer from which bytes are to be retrieved
++     * @return The number of bytes written, possibly zero
++     * @throws NonWritableChannelException If this channel was not opened for writing
++     * @throws ClosedChannelException If this channel is closed
++     * @throws AsynchronousCloseException If another thread closes this channel while the write
++     *     operation is in progress
++     * @throws ClosedByInterruptException If another thread interrupts the current thread while the
++     *     write operation is in progress, thereby closing the channel and setting the current
++     *     thread's interrupt status
++     * @throws IOException If some other I/O error occurs
++     */
++    int write(ByteBuffer src) throws IOException;
+ 
+-  /**
+-   * Returns this channel's position.
+-   *
+-   * @return This channel's position, a non-negative integer counting the number of bytes from the
+-   *     beginning of the entity to the current position
+-   * @throws ClosedChannelException If this channel is closed
+-   * @throws IOException If some other I/O error occurs
+-   */
+-  long position() throws IOException;
++    /**
++     * Returns this channel's position.
++     *
++     * @return This channel's position, a non-negative integer counting the number of bytes from the
++     *     beginning of the entity to the current position
++     * @throws ClosedChannelException If this channel is closed
++     * @throws IOException If some other I/O error occurs
++     */
++    long position() throws IOException;
+ 
+-  /**
+-   * Sets this channel's position.
+-   *
+-   * @param newPosition The new position, a non-negative integer counting the number of bytes from
+-   *     the beginning of the entity
+-   * @return This channel
+-   * @throws ClosedChannelException If this channel is closed
+-   * @throws IllegalArgumentException If the new position is negative
+-   * @throws IOException If some other I/O error occurs
+-   */
+-  SeekableByteChannelCompat position(long newPosition) throws IOException;
++    /**
++     * Sets this channel's position.
++     *
++     * @param newPosition The new position, a non-negative integer counting the number of bytes from
++     *     the beginning of the entity
++     * @return This channel
++     * @throws ClosedChannelException If this channel is closed
++     * @throws IllegalArgumentException If the new position is negative
++     * @throws IOException If some other I/O error occurs
++     */
++    SeekableByteChannelCompat position(long newPosition) throws IOException;
+ 
+-  /**
+-   * Returns the current size of entity to which this channel is connected.
+-   *
+-   * @return The current size, measured in bytes
+-   * @throws ClosedChannelException If this channel is closed
+-   * @throws IOException If some other I/O error occurs
+-   */
+-  long size() throws IOException;
++    /**
++     * Returns the current size of entity to which this channel is connected.
++     *
++     * @return The current size, measured in bytes
++     * @throws ClosedChannelException If this channel is closed
++     * @throws IOException If some other I/O error occurs
++     */
++    long size() throws IOException;
+ 
+-  /**
+-   * Truncates the entity, to which this channel is connected, to the given size.
+-   *
+-   * @param size The new size, a non-negative byte count
+-   * @return This channel
+-   * @throws NonWritableChannelException If this channel was not opened for writing
+-   * @throws ClosedChannelException If this channel is closed
+-   * @throws IllegalArgumentException If the new size is negative
+-   * @throws IOException If some other I/O error occurs
+-   */
+-  SeekableByteChannelCompat truncate(long size) throws IOException;
++    /**
++     * Truncates the entity, to which this channel is connected, to the given size.
++     *
++     * @param size The new size, a non-negative byte count
++     * @return This channel
++     * @throws NonWritableChannelException If this channel was not opened for writing
++     * @throws ClosedChannelException If this channel is closed
++     * @throws IllegalArgumentException If the new size is negative
++     * @throws IOException If some other I/O error occurs
++     */
++    SeekableByteChannelCompat truncate(long size) throws IOException;
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ZipFile.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ZipFile.java
+index 6b43e724fd814..c8a3fb806d920 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ZipFile.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/ZipFile.java
+@@ -45,393 +45,389 @@ import java.util.zip.ZipException;
+  * size limit for Zip64, which is 4GB.
+  */
+ final class ZipFile implements Closeable {
+-  /** Maps String to list of ZipEntrys, name -> actual entries. */
+-  private final Map<String, List<ZipEntry>> nameMap;
+-
+-  /** The actual data source. */
+-  private final ByteBufferChannel archive;
+-
+-  /**
+-   * Opens the given {@link ByteBufferChannel} for reading, assuming "UTF8" for file names. {@link
+-   * ZipFile} does not synchronized over the buffer that is passed into it.
+-   *
+-   * @param channel the archive
+-   * @throws IOException if an error occurs while creating this {@link ZipFile}
+-   * @throws ZipException if the channel is not a zip archive
+-   * @throws NullPointerException if the archive is null
+-   */
+-  public static ZipFile createFrom(ByteBufferChannel channel) throws IOException {
+-    checkNotNull(channel);
+-    ZipParser zipParser = new ZipParser(channel);
+-    Map<String, List<ZipEntry>> nameMap = zipParser.parseEntries();
+-    return new ZipFile(channel, nameMap);
+-  }
+-
+-  @Override
+-  public void close() {
+-    archive.close();
+-  }
+-
+-  /**
+-   * Exposes the raw stream of the archive entry.
+-   *
+-   * <p>Since the associated files will not be compressed when being packed to the zip file, the raw
+-   * stream represents the non-compressed files.
+-   *
+-   * <p><b>WARNING:</b> The returned {@link InputStream}, is <b>not</b> thread-safe. If multiple
+-   * threads concurrently reading from the returned {@link InputStream}, it must be synchronized
+-   * externally.
+-   *
+-   * @param name name of the entry to get the stream for
+-   * @return the raw input stream containing data
+-   * @throws IllegalArgumentException if the specified file does not exist in the zip file
+-   */
+-  public InputStream getRawInputStream(String name) {
+-    checkArgument(
+-        nameMap.containsKey(name),
+-        String.format("The file, %s, does not exist in the zip file.", name));
+-
+-    List<ZipEntry> entriesWithTheSameName = nameMap.get(name);
+-    ZipEntry entry = entriesWithTheSameName.get(0);
+-    long start = entry.getDataOffset();
+-    long remaining = entry.getSize();
+-    return new BoundedInputStream(archive, start, remaining);
+-  }
+-
+-  /**
+-   * Exposes the file names of the included files.
+-   *
+-   * @return the file names of the included files
+-   */
+-  public Set<String> getFileNames() {
+-    return nameMap.keySet();
+-  }
+-
+-  private ZipFile(ByteBufferChannel channel, Map<String, List<ZipEntry>> nameMap) {
+-    archive = channel;
+-    this.nameMap = nameMap;
+-  }
+-
+-  /* Parses a Zip archive and gets the information for each {@link ZipEntry}. */
+-  private static class ZipParser {
+-    private final ByteBufferChannel archive;
+-
+-    // Cached buffers that will only be used locally in the class to reduce garbage collection.
+-    private final ByteBuffer longBuffer =
+-        ByteBuffer.allocate(ZipConstants.LONG_BYTE_SIZE).order(ByteOrder.LITTLE_ENDIAN);
+-    private final ByteBuffer intBuffer =
+-        ByteBuffer.allocate(ZipConstants.INT_BYTE_SIZE).order(ByteOrder.LITTLE_ENDIAN);
+-    private final ByteBuffer shortBuffer =
+-        ByteBuffer.allocate(ZipConstants.SHORT_BYTE_SIZE).order(ByteOrder.LITTLE_ENDIAN);
++    /** Maps String to list of ZipEntrys, name -> actual entries. */
++    private final Map<String, List<ZipEntry>> nameMap;
+ 
+-    private ZipParser(ByteBufferChannel archive) {
+-      this.archive = archive;
+-    }
+-
+-    /**
+-     * Parses the underlying {@code archive} and returns the information as a list of {@link
+-     * ZipEntry}.
+-     */
+-    private Map<String, List<ZipEntry>> parseEntries() throws IOException {
+-      List<ZipEntry> entries = parseCentralDirectory();
+-      return parseLocalFileHeaderData(entries);
+-    }
+-
+-    /**
+-     * Checks if the current position contains a central file header signature, {@link
+-     * ZipConstants#CENSIG}.
+-     */
+-    private boolean foundCentralFileheaderSignature() {
+-      long signature = (long) getInt();
+-      return signature == ZipConstants.CENSIG;
+-    }
+-
+-    /**
+-     * Gets the value as a Java int from two bytes starting at the current position of the archive.
+-     */
+-    private int getShort() {
+-      shortBuffer.rewind();
+-      archive.read(shortBuffer);
+-      shortBuffer.flip();
+-      return (int) shortBuffer.getShort();
+-    }
++    /** The actual data source. */
++    private final ByteBufferChannel archive;
+ 
+     /**
+-     * Gets the value as a Java long from four bytes starting at the current position of the
+-     * archive.
++     * Opens the given {@link ByteBufferChannel} for reading, assuming "UTF8" for file names. {@link
++     * ZipFile} does not synchronized over the buffer that is passed into it.
++     *
++     * @param channel the archive
++     * @throws IOException if an error occurs while creating this {@link ZipFile}
++     * @throws ZipException if the channel is not a zip archive
++     * @throws NullPointerException if the archive is null
+      */
+-    private int getInt() {
+-      intBuffer.rewind();
+-      archive.read(intBuffer);
+-      intBuffer.flip();
+-      return intBuffer.getInt();
++    public static ZipFile createFrom(ByteBufferChannel channel) throws IOException {
++        checkNotNull(channel);
++        ZipParser zipParser = new ZipParser(channel);
++        Map<String, List<ZipEntry>> nameMap = zipParser.parseEntries();
++        return new ZipFile(channel, nameMap);
+     }
+ 
+-    /**
+-     * Gets the value as a Java long from four bytes starting at the current position of the
+-     * archive.
+-     */
+-    private long getLong() {
+-      longBuffer.rewind();
+-      archive.read(longBuffer);
+-      longBuffer.flip();
+-      return longBuffer.getLong();
++    @Override
++    public void close() {
++        archive.close();
+     }
+ 
+     /**
+-     * Positions the archive at the start of the central directory.
++     * Exposes the raw stream of the archive entry.
++     *
++     * <p>Since the associated files will not be compressed when being packed to the zip file, the
++     * raw stream represents the non-compressed files.
+      *
+-     * <p>First, it searches for the signature of the "end of central directory record", {@link
+-     * ZipConstants#ENDSIG}. Position the stream at the start of the "end of central directory
+-     * record". The zip file are created without archive comments, thus {@link ZipConstants#ENDSIG}
+-     * should appear exactly at {@link ZipConstants#ENDHDR} from the end of the zip file.
++     * <p><b>WARNING:</b> The returned {@link InputStream}, is <b>not</b> thread-safe. If multiple
++     * threads concurrently reading from the returned {@link InputStream}, it must be synchronized
++     * externally.
+      *
+-     * <p>Then, parse the "end of central dir record" and position the archive at the start of the
+-     * central directory.
++     * @param name name of the entry to get the stream for
++     * @return the raw input stream containing data
++     * @throws IllegalArgumentException if the specified file does not exist in the zip file
+      */
+-    private void locateCentralDirectory() throws IOException {
+-      if (archive.size() < ZipConstants.ENDHDR) {
+-        throw new ZipException("The archive is not a ZIP archive.");
+-      }
+-
+-      // Positions the archive at the start of the "end of central directory record".
+-      long offsetRecord = archive.size() - ZipConstants.ENDHDR;
+-      archive.position(offsetRecord);
+-
+-      // Checks for the signature, {@link ZipConstants#ENDSIG}.
+-      long endSig = getLong();
+-      if (endSig != ZipConstants.ENDSIG) {
+-        throw new ZipException("The archive is not a ZIP archive.");
+-      }
+-
+-      // Positions the archive at the “offset of central directory”.
+-      skipBytes(ZipConstants.ENDOFF - ZipConstants.ENDSUB);
+-      // Gets the offset to central directory
+-      long offsetDirectory = getInt();
+-      // Goes to the central directory.
+-      archive.position(offsetDirectory);
++    public InputStream getRawInputStream(String name) {
++        checkArgument(nameMap.containsKey(name),
++                String.format("The file, %s, does not exist in the zip file.", name));
++
++        List<ZipEntry> entriesWithTheSameName = nameMap.get(name);
++        ZipEntry entry = entriesWithTheSameName.get(0);
++        long start = entry.getDataOffset();
++        long remaining = entry.getSize();
++        return new BoundedInputStream(archive, start, remaining);
+     }
+ 
+     /**
+-     * Reads the central directory of the given archive and populates the internal tables with
+-     * {@link ZipEntry} instances.
++     * Exposes the file names of the included files.
++     *
++     * @return the file names of the included files
+      */
+-    private List<ZipEntry> parseCentralDirectory() throws IOException {
+-      /** List of entries in the order they appear inside the central directory. */
+-      List<ZipEntry> entries = new ArrayList<>();
+-      locateCentralDirectory();
+-
+-      while (foundCentralFileheaderSignature()) {
+-        ZipEntry entry = parseCentralDirectoryEntry();
+-        entries.add(entry);
+-      }
+-
+-      return entries;
++    public Set<String> getFileNames() {
++        return nameMap.keySet();
+     }
+ 
+-    /**
+-     * Reads an individual entry of the central directory, creats an ZipEntry from it and adds it to
+-     * the global maps.
+-     */
+-    private ZipEntry parseCentralDirectoryEntry() throws IOException {
+-      // Positions the archive at the "compressed size" and read the value.
+-      skipBytes(ZipConstants.CENSIZ - ZipConstants.CENVEM);
+-      long compressSize = getInt();
+-
+-      // Positions the archive at the "filename length" and read the value.
+-      skipBytes(ZipConstants.CENNAM - ZipConstants.CENLEN);
+-      int fileNameLen = getShort();
+-
+-      // Reads the extra field length and the comment length.
+-      int extraLen = getShort();
+-      int commentLen = getShort();
+-
+-      // Positions the archive at the "local file header offset" and read the value.
+-      skipBytes(ZipConstants.CENOFF - ZipConstants.CENDSK);
+-      long localHeaderOffset = getInt();
+-
+-      // Reads the file name.
+-      byte[] fileNameBuf = new byte[fileNameLen];
+-      archive.read(ByteBuffer.wrap(fileNameBuf));
+-      String fileName = new String(fileNameBuf, Charset.forName("UTF-8"));
++    private ZipFile(ByteBufferChannel channel, Map<String, List<ZipEntry>> nameMap) {
++        archive = channel;
++        this.nameMap = nameMap;
++    }
+ 
+-      // Skips the extra field and the comment.
+-      skipBytes(extraLen + commentLen);
++    /* Parses a Zip archive and gets the information for each {@link ZipEntry}. */
++    private static class ZipParser {
++        private final ByteBufferChannel archive;
+ 
+-      ZipEntry entry = new ZipEntry();
+-      entry.setSize(compressSize);
+-      entry.setLocalHeaderOffset(localHeaderOffset);
+-      entry.setName(fileName);
++        // Cached buffers that will only be used locally in the class to reduce garbage collection.
++        private final ByteBuffer longBuffer =
++                ByteBuffer.allocate(ZipConstants.LONG_BYTE_SIZE).order(ByteOrder.LITTLE_ENDIAN);
++        private final ByteBuffer intBuffer =
++                ByteBuffer.allocate(ZipConstants.INT_BYTE_SIZE).order(ByteOrder.LITTLE_ENDIAN);
++        private final ByteBuffer shortBuffer =
++                ByteBuffer.allocate(ZipConstants.SHORT_BYTE_SIZE).order(ByteOrder.LITTLE_ENDIAN);
+ 
+-      return entry;
+-    }
++        private ZipParser(ByteBufferChannel archive) {
++            this.archive = archive;
++        }
+ 
+-    /** Walks through all recorded entries and records the offsets for the entry data. */
+-    private Map<String, List<ZipEntry>> parseLocalFileHeaderData(List<ZipEntry> entries) {
+-      /** Maps String to list of ZipEntrys, name -> actual entries. */
+-      Map<String, List<ZipEntry>> nameMap = new LinkedHashMap<>();
+-
+-      for (ZipEntry entry : entries) {
+-        long offset = entry.getLocalHeaderOffset();
+-        archive.position(offset + ZipConstants.LOCNAM);
+-
+-        // Gets the data offset of this entry.
+-        int fileNameLen = getShort();
+-        int extraFieldLen = getShort();
+-        long dataOffset =
+-            offset
+-                + ZipConstants.LOCEXT
+-                + ZipConstants.SHORT_BYTE_SIZE
+-                + fileNameLen
+-                + extraFieldLen;
+-        entry.setDataOffset(dataOffset);
+-
+-        // Puts the entry into the nameMap.
+-        String name = entry.getName();
+-        List<ZipEntry> entriesWithTheSameName;
+-        if (nameMap.containsKey(name)) {
+-          entriesWithTheSameName = nameMap.get(name);
+-        } else {
+-          entriesWithTheSameName = new ArrayList<>();
+-          nameMap.put(name, entriesWithTheSameName);
++        /**
++         * Parses the underlying {@code archive} and returns the information as a list of {@link
++         * ZipEntry}.
++         */
++        private Map<String, List<ZipEntry>> parseEntries() throws IOException {
++            List<ZipEntry> entries = parseCentralDirectory();
++            return parseLocalFileHeaderData(entries);
+         }
+-        entriesWithTheSameName.add(entry);
+-      }
+ 
+-      return nameMap;
+-    }
++        /**
++         * Checks if the current position contains a central file header signature, {@link
++         * ZipConstants#CENSIG}.
++         */
++        private boolean foundCentralFileheaderSignature() {
++            long signature = (long) getInt();
++            return signature == ZipConstants.CENSIG;
++        }
+ 
+-    /** Skips the given number of bytes or throws an EOFException if skipping failed. */
+-    private void skipBytes(int count) throws IOException {
+-      long currentPosition = archive.position();
+-      long newPosition = currentPosition + count;
+-      if (newPosition > archive.size()) {
+-        throw new EOFException();
+-      }
+-      archive.position(newPosition);
+-    }
+-  }
++        /**
++         * Gets the value as a Java int from two bytes starting at the current position of the
++         * archive.
++         */
++        private int getShort() {
++            shortBuffer.rewind();
++            archive.read(shortBuffer);
++            shortBuffer.flip();
++            return (int) shortBuffer.getShort();
++        }
+ 
+-  /** Stores the data offset and the size of an entry in the archive. */
+-  private static class ZipEntry {
++        /**
++         * Gets the value as a Java long from four bytes starting at the current position of the
++         * archive.
++         */
++        private int getInt() {
++            intBuffer.rewind();
++            archive.read(intBuffer);
++            intBuffer.flip();
++            return intBuffer.getInt();
++        }
+ 
+-    private String name;
+-    private long dataOffset = -1;
+-    private long size = -1;
+-    private long localHeaderOffset = -1;
++        /**
++         * Gets the value as a Java long from four bytes starting at the current position of the
++         * archive.
++         */
++        private long getLong() {
++            longBuffer.rewind();
++            archive.read(longBuffer);
++            longBuffer.flip();
++            return longBuffer.getLong();
++        }
+ 
+-    public long getSize() {
+-      return size;
+-    }
++        /**
++         * Positions the archive at the start of the central directory.
++         *
++         * <p>First, it searches for the signature of the "end of central directory record", {@link
++         * ZipConstants#ENDSIG}. Position the stream at the start of the "end of central directory
++         * record". The zip file are created without archive comments, thus {@link
++         * ZipConstants#ENDSIG} should appear exactly at {@link ZipConstants#ENDHDR} from the end of
++         * the zip file.
++         *
++         * <p>Then, parse the "end of central dir record" and position the archive at the start of
++         * the central directory.
++         */
++        private void locateCentralDirectory() throws IOException {
++            if (archive.size() < ZipConstants.ENDHDR) {
++                throw new ZipException("The archive is not a ZIP archive.");
++            }
++
++            // Positions the archive at the start of the "end of central directory record".
++            long offsetRecord = archive.size() - ZipConstants.ENDHDR;
++            archive.position(offsetRecord);
++
++            // Checks for the signature, {@link ZipConstants#ENDSIG}.
++            long endSig = getLong();
++            if (endSig != ZipConstants.ENDSIG) {
++                throw new ZipException("The archive is not a ZIP archive.");
++            }
++
++            // Positions the archive at the “offset of central directory”.
++            skipBytes(ZipConstants.ENDOFF - ZipConstants.ENDSUB);
++            // Gets the offset to central directory
++            long offsetDirectory = getInt();
++            // Goes to the central directory.
++            archive.position(offsetDirectory);
++        }
+ 
+-    public long getDataOffset() {
+-      return dataOffset;
+-    }
++        /**
++         * Reads the central directory of the given archive and populates the internal tables with
++         * {@link ZipEntry} instances.
++         */
++        private List<ZipEntry> parseCentralDirectory() throws IOException {
++            /** List of entries in the order they appear inside the central directory. */
++            List<ZipEntry> entries = new ArrayList<>();
++            locateCentralDirectory();
++
++            while (foundCentralFileheaderSignature()) {
++                ZipEntry entry = parseCentralDirectoryEntry();
++                entries.add(entry);
++            }
++
++            return entries;
++        }
+ 
+-    public String getName() {
+-      return name;
+-    }
++        /**
++         * Reads an individual entry of the central directory, creats an ZipEntry from it and adds
++         * it to the global maps.
++         */
++        private ZipEntry parseCentralDirectoryEntry() throws IOException {
++            // Positions the archive at the "compressed size" and read the value.
++            skipBytes(ZipConstants.CENSIZ - ZipConstants.CENVEM);
++            long compressSize = getInt();
++
++            // Positions the archive at the "filename length" and read the value.
++            skipBytes(ZipConstants.CENNAM - ZipConstants.CENLEN);
++            int fileNameLen = getShort();
++
++            // Reads the extra field length and the comment length.
++            int extraLen = getShort();
++            int commentLen = getShort();
++
++            // Positions the archive at the "local file header offset" and read the value.
++            skipBytes(ZipConstants.CENOFF - ZipConstants.CENDSK);
++            long localHeaderOffset = getInt();
++
++            // Reads the file name.
++            byte[] fileNameBuf = new byte[fileNameLen];
++            archive.read(ByteBuffer.wrap(fileNameBuf));
++            String fileName = new String(fileNameBuf, Charset.forName("UTF-8"));
++
++            // Skips the extra field and the comment.
++            skipBytes(extraLen + commentLen);
++
++            ZipEntry entry = new ZipEntry();
++            entry.setSize(compressSize);
++            entry.setLocalHeaderOffset(localHeaderOffset);
++            entry.setName(fileName);
++
++            return entry;
++        }
+ 
+-    public long getLocalHeaderOffset() {
+-      return localHeaderOffset;
+-    }
++        /** Walks through all recorded entries and records the offsets for the entry data. */
++        private Map<String, List<ZipEntry>> parseLocalFileHeaderData(List<ZipEntry> entries) {
++            /** Maps String to list of ZipEntrys, name -> actual entries. */
++            Map<String, List<ZipEntry>> nameMap = new LinkedHashMap<>();
++
++            for (ZipEntry entry : entries) {
++                long offset = entry.getLocalHeaderOffset();
++                archive.position(offset + ZipConstants.LOCNAM);
++
++                // Gets the data offset of this entry.
++                int fileNameLen = getShort();
++                int extraFieldLen = getShort();
++                long dataOffset = offset + ZipConstants.LOCEXT + ZipConstants.SHORT_BYTE_SIZE
++                        + fileNameLen + extraFieldLen;
++                entry.setDataOffset(dataOffset);
++
++                // Puts the entry into the nameMap.
++                String name = entry.getName();
++                List<ZipEntry> entriesWithTheSameName;
++                if (nameMap.containsKey(name)) {
++                    entriesWithTheSameName = nameMap.get(name);
++                } else {
++                    entriesWithTheSameName = new ArrayList<>();
++                    nameMap.put(name, entriesWithTheSameName);
++                }
++                entriesWithTheSameName.add(entry);
++            }
++
++            return nameMap;
++        }
+ 
+-    public void setSize(long size) {
+-      this.size = size;
++        /** Skips the given number of bytes or throws an EOFException if skipping failed. */
++        private void skipBytes(int count) throws IOException {
++            long currentPosition = archive.position();
++            long newPosition = currentPosition + count;
++            if (newPosition > archive.size()) {
++                throw new EOFException();
++            }
++            archive.position(newPosition);
++        }
+     }
+ 
+-    public void setDataOffset(long dataOffset) {
+-      this.dataOffset = dataOffset;
+-    }
++    /** Stores the data offset and the size of an entry in the archive. */
++    private static class ZipEntry {
++        private String name;
++        private long dataOffset = -1;
++        private long size = -1;
++        private long localHeaderOffset = -1;
+ 
+-    public void setName(String name) {
+-      this.name = name;
+-    }
++        public long getSize() {
++            return size;
++        }
+ 
+-    public void setLocalHeaderOffset(long localHeaderOffset) {
+-      this.localHeaderOffset = localHeaderOffset;
+-    }
+-  }
++        public long getDataOffset() {
++            return dataOffset;
++        }
+ 
+-  /**
+-   * Various constants for this {@link ZipFile}.
+-   *
+-   * <p>Referenced from {@link java.util.zip.ZipConstants}.
+-   */
+-  private static class ZipConstants {
+-    /** length of Java short in bytes. */
+-    static final int SHORT_BYTE_SIZE = Short.SIZE / 8;
++        public String getName() {
++            return name;
++        }
+ 
+-    /** length of Java int in bytes. */
+-    static final int INT_BYTE_SIZE = Integer.SIZE / 8;
++        public long getLocalHeaderOffset() {
++            return localHeaderOffset;
++        }
+ 
+-    /** length of Java long in bytes. */
+-    static final int LONG_BYTE_SIZE = Long.SIZE / 8;
++        public void setSize(long size) {
++            this.size = size;
++        }
+ 
+-    /*
+-     * Header signatures
+-     */
+-    static final long LOCSIG = 0x04034b50L; // "PK\003\004"
+-    static final long EXTSIG = 0x08074b50L; // "PK\007\008"
+-    static final long CENSIG = 0x02014b50L; // "PK\001\002"
+-    static final long ENDSIG = 0x06054b50L; // "PK\005\006"
++        public void setDataOffset(long dataOffset) {
++            this.dataOffset = dataOffset;
++        }
+ 
+-    /*
+-     * Header sizes in bytes (including signatures)
+-     */
+-    static final int LOCHDR = 30; // LOC header size
+-    static final int EXTHDR = 16; // EXT header size
+-    static final int CENHDR = 46; // CEN header size
+-    static final int ENDHDR = 22; // END header size
++        public void setName(String name) {
++            this.name = name;
++        }
+ 
+-    /*
+-     * Local file (LOC) header field offsets
+-     */
+-    static final int LOCVER = 4; // version needed to extract
+-    static final int LOCFLG = 6; // general purpose bit flag
+-    static final int LOCHOW = 8; // compression method
+-    static final int LOCTIM = 10; // modification time
+-    static final int LOCCRC = 14; // uncompressed file crc-32 value
+-    static final int LOCSIZ = 18; // compressed size
+-    static final int LOCLEN = 22; // uncompressed size
+-    static final int LOCNAM = 26; // filename length
+-    static final int LOCEXT = 28; // extra field length
+-
+-    /*
+-     * Extra local (EXT) header field offsets
+-     */
+-    static final int EXTCRC = 4; // uncompressed file crc-32 value
+-    static final int EXTSIZ = 8; // compressed size
+-    static final int EXTLEN = 12; // uncompressed size
++        public void setLocalHeaderOffset(long localHeaderOffset) {
++            this.localHeaderOffset = localHeaderOffset;
++        }
++    }
+ 
+-    /*
+-     * Central directory (CEN) header field offsets
+-     */
+-    static final int CENVEM = 4; // version made by
+-    static final int CENVER = 6; // version needed to extract
+-    static final int CENFLG = 8; // encrypt, decrypt flags
+-    static final int CENHOW = 10; // compression method
+-    static final int CENTIM = 12; // modification time
+-    static final int CENCRC = 16; // uncompressed file crc-32 value
+-    static final int CENSIZ = 20; // compressed size
+-    static final int CENLEN = 24; // uncompressed size
+-    static final int CENNAM = 28; // filename length
+-    static final int CENEXT = 30; // extra field length
+-    static final int CENCOM = 32; // comment length
+-    static final int CENDSK = 34; // disk number start
+-    static final int CENATT = 36; // internal file attributes
+-    static final int CENATX = 38; // external file attributes
+-    static final int CENOFF = 42; // LOC header offset
+-
+-    /*
+-     * End of central directory (END) header field offsets
++    /**
++     * Various constants for this {@link ZipFile}.
++     *
++     * <p>Referenced from {@link java.util.zip.ZipConstants}.
+      */
+-    static final int ENDSUB = 8; // number of entries on this disk
+-    static final int ENDTOT = 10; // total number of entries
+-    static final int ENDSIZ = 12; // central directory size in bytes
+-    static final int ENDOFF = 16; // offset of first CEN header
+-    static final int ENDCOM = 20; // zip file comment length
+-
+-    private ZipConstants() {}
+-  }
++    private static class ZipConstants {
++        /** length of Java short in bytes. */
++        static final int SHORT_BYTE_SIZE = Short.SIZE / 8;
++
++        /** length of Java int in bytes. */
++        static final int INT_BYTE_SIZE = Integer.SIZE / 8;
++
++        /** length of Java long in bytes. */
++        static final int LONG_BYTE_SIZE = Long.SIZE / 8;
++
++        /*
++         * Header signatures
++         */
++        static final long LOCSIG = 0x04034b50L; // "PK\003\004"
++        static final long EXTSIG = 0x08074b50L; // "PK\007\008"
++        static final long CENSIG = 0x02014b50L; // "PK\001\002"
++        static final long ENDSIG = 0x06054b50L; // "PK\005\006"
++
++        /*
++         * Header sizes in bytes (including signatures)
++         */
++        static final int LOCHDR = 30; // LOC header size
++        static final int EXTHDR = 16; // EXT header size
++        static final int CENHDR = 46; // CEN header size
++        static final int ENDHDR = 22; // END header size
++
++        /*
++         * Local file (LOC) header field offsets
++         */
++        static final int LOCVER = 4; // version needed to extract
++        static final int LOCFLG = 6; // general purpose bit flag
++        static final int LOCHOW = 8; // compression method
++        static final int LOCTIM = 10; // modification time
++        static final int LOCCRC = 14; // uncompressed file crc-32 value
++        static final int LOCSIZ = 18; // compressed size
++        static final int LOCLEN = 22; // uncompressed size
++        static final int LOCNAM = 26; // filename length
++        static final int LOCEXT = 28; // extra field length
++
++        /*
++         * Extra local (EXT) header field offsets
++         */
++        static final int EXTCRC = 4; // uncompressed file crc-32 value
++        static final int EXTSIZ = 8; // compressed size
++        static final int EXTLEN = 12; // uncompressed size
++
++        /*
++         * Central directory (CEN) header field offsets
++         */
++        static final int CENVEM = 4; // version made by
++        static final int CENVER = 6; // version needed to extract
++        static final int CENFLG = 8; // encrypt, decrypt flags
++        static final int CENHOW = 10; // compression method
++        static final int CENTIM = 12; // modification time
++        static final int CENCRC = 16; // uncompressed file crc-32 value
++        static final int CENSIZ = 20; // compressed size
++        static final int CENLEN = 24; // uncompressed size
++        static final int CENNAM = 28; // filename length
++        static final int CENEXT = 30; // extra field length
++        static final int CENCOM = 32; // comment length
++        static final int CENDSK = 34; // disk number start
++        static final int CENATT = 36; // internal file attributes
++        static final int CENATX = 38; // external file attributes
++        static final int CENOFF = 42; // LOC header offset
++
++        /*
++         * End of central directory (END) header field offsets
++         */
++        static final int ENDSUB = 8; // number of entries on this disk
++        static final int ENDTOT = 10; // total number of entries
++        static final int ENDSIZ = 12; // central directory size in bytes
++        static final int ENDOFF = 16; // offset of first CEN header
++        static final int ENDCOM = 20; // zip file comment length
++
++        private ZipConstants() {}
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/BoundedInputStreamTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/BoundedInputStreamTest.java
+index 3847bc1d2ce01..e0825a1fe7862 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/BoundedInputStreamTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/BoundedInputStreamTest.java
+@@ -16,244 +16,223 @@ limitations under the License.
+ package org.tensorflow.lite.support.metadata;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertArrayEquals;
+ import static org.junit.Assert.assertThrows;
+ 
+-import java.nio.ByteBuffer;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ 
++import java.nio.ByteBuffer;
++
+ /** Tests of {@link BoundedInputStream}. */
+ @RunWith(RobolectricTestRunner.class)
+ public class BoundedInputStreamTest {
++    private static final byte[] testBytes = new byte[] {10, 20, 30, 40, 50};
++    private static final int[] testInts = new int[] {10, 20, 30, 40, 50};
++    private static final int TEST_BYTES_LENGTH = testBytes.length;
++
++    @Test
++    public void boundedInputStream_negtiveStart_throwsException() throws Exception {
++        long start = -1;
++        long remaining = 2;
++        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                () -> createBoundedInputStream(testBytes, start, remaining));
++        assertThat(exception).hasMessageThat().isEqualTo(String.format(
++                "Invalid length of stream at offset=%d, length=%d", start, remaining));
++    }
++
++    @Test
++    public void boundedInputStream_negtiveRemaining_throwsException() throws Exception {
++        long start = 1;
++        long remaining = -2;
++        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                () -> createBoundedInputStream(testBytes, start, remaining));
++        assertThat(exception).hasMessageThat().isEqualTo(String.format(
++                "Invalid length of stream at offset=%d, length=%d", start, remaining));
++    }
++
++    @Test
++    public void available_atStart() throws Exception {
++        int start = 3;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, start, TEST_BYTES_LENGTH);
++
++        int available = boundedInputStream.available();
++        assertThat(available).isEqualTo(TEST_BYTES_LENGTH - start);
++    }
++
++    @Test
++    public void available_afterRead() throws Exception {
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++        // Read a byte out of boundedInputStream. The number of remaining bytes is TEST_BYTES_LENGTH
++        // -1.
++        boundedInputStream.read();
++
++        int available = boundedInputStream.available();
++        assertThat(available).isEqualTo(TEST_BYTES_LENGTH - 1);
++    }
++
++    @Test
++    public void read_repeatedRead() throws Exception {
++        int[] values = new int[TEST_BYTES_LENGTH];
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        for (int i = 0; i < TEST_BYTES_LENGTH; i++) {
++            values[i] = boundedInputStream.read();
++        }
++
++        assertArrayEquals(testInts, values);
++    }
++
++    @Test
++    public void read_reachTheEnd() throws Exception {
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++        boundedInputStream.skip(TEST_BYTES_LENGTH);
++        int value = boundedInputStream.read();
++
++        assertThat(value).isEqualTo(-1);
++    }
++
++    @Test
++    public void read_channelSizeisSmallerThanTheStreamSpecified() throws Exception {
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH + 1);
++        boundedInputStream.skip(TEST_BYTES_LENGTH);
++
++        int value = boundedInputStream.read();
++
++        assertThat(value).isEqualTo(-1);
++    }
+ 
+-  private static final byte[] testBytes = new byte[] {10, 20, 30, 40, 50};
+-  private static final int[] testInts = new int[] {10, 20, 30, 40, 50};
+-  private static final int TEST_BYTES_LENGTH = testBytes.length;
+-
+-  @Test
+-  public void boundedInputStream_negtiveStart_throwsException() throws Exception {
+-    long start = -1;
+-    long remaining = 2;
+-    IllegalArgumentException exception =
+-        assertThrows(
+-            IllegalArgumentException.class,
+-            () -> createBoundedInputStream(testBytes, start, remaining));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(
+-            String.format("Invalid length of stream at offset=%d, length=%d", start, remaining));
+-  }
+-
+-  @Test
+-  public void boundedInputStream_negtiveRemaining_throwsException() throws Exception {
+-    long start = 1;
+-    long remaining = -2;
+-    IllegalArgumentException exception =
+-        assertThrows(
+-            IllegalArgumentException.class,
+-            () -> createBoundedInputStream(testBytes, start, remaining));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(
+-            String.format("Invalid length of stream at offset=%d, length=%d", start, remaining));
+-  }
+-
+-  @Test
+-  public void available_atStart() throws Exception {
+-    int start = 3;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, start, TEST_BYTES_LENGTH);
+-
+-    int available = boundedInputStream.available();
+-    assertThat(available).isEqualTo(TEST_BYTES_LENGTH - start);
+-  }
+-
+-  @Test
+-  public void available_afterRead() throws Exception {
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-    // Read a byte out of boundedInputStream. The number of remaining bytes is TEST_BYTES_LENGTH -1.
+-    boundedInputStream.read();
+-
+-    int available = boundedInputStream.available();
+-    assertThat(available).isEqualTo(TEST_BYTES_LENGTH - 1);
+-  }
+-
+-  @Test
+-  public void read_repeatedRead() throws Exception {
+-    int[] values = new int[TEST_BYTES_LENGTH];
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    for (int i = 0; i < TEST_BYTES_LENGTH; i++) {
+-      values[i] = boundedInputStream.read();
++    @Test
++    public void readArray_nullArray_throwsException() throws Exception {
++        byte[] array = null;
++        int offset = 0;
++        int length = 1;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        NullPointerException exception = assertThrows(
++                NullPointerException.class, () -> boundedInputStream.read(array, offset, length));
++        assertThat(exception).hasMessageThat().isEqualTo("The object reference is null.");
+     }
+ 
+-    assertArrayEquals(testInts, values);
+-  }
+-
+-  @Test
+-  public void read_reachTheEnd() throws Exception {
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-    boundedInputStream.skip(TEST_BYTES_LENGTH);
+-    int value = boundedInputStream.read();
+-
+-    assertThat(value).isEqualTo(-1);
+-  }
+-
+-  @Test
+-  public void read_channelSizeisSmallerThanTheStreamSpecified() throws Exception {
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH + 1);
+-    boundedInputStream.skip(TEST_BYTES_LENGTH);
+-
+-    int value = boundedInputStream.read();
+-
+-    assertThat(value).isEqualTo(-1);
+-  }
+-
+-  @Test
+-  public void readArray_nullArray_throwsException() throws Exception {
+-    byte[] array = null;
+-    int offset = 0;
+-    int length = 1;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    NullPointerException exception =
+-        assertThrows(
+-            NullPointerException.class, () -> boundedInputStream.read(array, offset, length));
+-    assertThat(exception).hasMessageThat().isEqualTo("The object reference is null.");
+-  }
+-
+-  @Test
+-  public void readArray_negativeOffset_throwsException() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = -1;
+-    int length = array.length;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    IndexOutOfBoundsException exception =
+-        assertThrows(
+-            IndexOutOfBoundsException.class, () -> boundedInputStream.read(array, offset, length));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(String.format("The start offset (%s) must not be negative", offset));
+-  }
+-
+-  @Test
+-  public void readArray_OffsetEqualsArrayLength_throwsException() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = array.length;
+-    int length = 0;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    IndexOutOfBoundsException exception =
+-        assertThrows(
+-            IndexOutOfBoundsException.class, () -> boundedInputStream.read(array, offset, length));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(
+-            String.format(
++    @Test
++    public void readArray_negativeOffset_throwsException() throws Exception {
++        byte[] array = new byte[5];
++        int offset = -1;
++        int length = array.length;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
++                () -> boundedInputStream.read(array, offset, length));
++        assertThat(exception).hasMessageThat().isEqualTo(
++                String.format("The start offset (%s) must not be negative", offset));
++    }
++
++    @Test
++    public void readArray_OffsetEqualsArrayLength_throwsException() throws Exception {
++        byte[] array = new byte[5];
++        int offset = array.length;
++        int length = 0;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
++                () -> boundedInputStream.read(array, offset, length));
++        assertThat(exception).hasMessageThat().isEqualTo(String.format(
+                 "The start offset (%s) must be less than size (%s)", offset, array.length));
+-  }
+-
+-  @Test
+-  public void readArray_negativeLength_throwsException() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = 0;
+-    int length = -1;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    IndexOutOfBoundsException exception =
+-        assertThrows(
+-            IndexOutOfBoundsException.class, () -> boundedInputStream.read(array, offset, length));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(
+-            String.format(
++    }
++
++    @Test
++    public void readArray_negativeLength_throwsException() throws Exception {
++        byte[] array = new byte[5];
++        int offset = 0;
++        int length = -1;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
++                () -> boundedInputStream.read(array, offset, length));
++        assertThat(exception).hasMessageThat().isEqualTo(String.format(
+                 "The maximumn number of bytes to read (%s) must not be negative", length));
+-  }
+-
+-  @Test
+-  public void readArray_exceedEndOfArray_throwsException() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = 0;
+-    int length = array.length + 1;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    IndexOutOfBoundsException exception =
+-        assertThrows(
+-            IndexOutOfBoundsException.class, () -> boundedInputStream.read(array, offset, length));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(
+-            String.format(
+-                "The maximumn number of bytes to read (%s) must be less than size (%s)",
+-                length, array.length - offset + 1));
+-  }
+-
+-  @Test
+-  public void readArray_zeroLength() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = 0;
+-    int length = 0;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    int value = boundedInputStream.read(array, offset, length);
+-    assertThat(value).isEqualTo(0);
+-  }
+-
+-  @Test
+-  public void readArray_exceedEndOfStream() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = 0;
+-    int length = 1;
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    // Move the position of the stream to the end.
+-    boundedInputStream.skip(TEST_BYTES_LENGTH);
+-
+-    int value = boundedInputStream.read(array, offset, length);
+-
+-    assertThat(value).isEqualTo(-1);
+-  }
+-
+-  @Test
+-  public void readArray_lengthGreaterThanStreamRemaining() throws Exception {
+-    byte[] array = new byte[5];
+-    int offset = 1;
+-    int length = array.length - 1; // 4
+-    BoundedInputStream boundedInputStream =
+-        createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
+-
+-    // Moves the position of the stream to end-2.
+-    boundedInputStream.skip(TEST_BYTES_LENGTH - 2);
+-
+-    // Reads the last two bytes of the stream to the array, and put the data at offset 1.
+-    int value = boundedInputStream.read(array, offset, length);
+-
+-    byte[] expectedArray = new byte[] {0, 40, 50, 0, 0};
+-    assertArrayEquals(expectedArray, array);
+-    assertThat(value).isEqualTo(2);
+-
+-    // Reachs the end of the stream, thus cannot read anymore.
+-    assertThat(boundedInputStream.read()).isEqualTo(-1);
+-  }
+-
+-  private static BoundedInputStream createBoundedInputStream(
+-      final byte[] testBytes, long start, long remaining) {
+-    ByteBuffer buffer = ByteBuffer.wrap(testBytes);
+-    SeekableByteChannelCompat channel = new ByteBufferChannel(buffer);
+-    return new BoundedInputStream(channel, start, remaining);
+-  }
++    }
++
++    @Test
++    public void readArray_exceedEndOfArray_throwsException() throws Exception {
++        byte[] array = new byte[5];
++        int offset = 0;
++        int length = array.length + 1;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
++                () -> boundedInputStream.read(array, offset, length));
++        assertThat(exception).hasMessageThat().isEqualTo(String.format(
++                "The maximumn number of bytes to read (%s) must be less than size (%s)", length,
++                array.length - offset + 1));
++    }
++
++    @Test
++    public void readArray_zeroLength() throws Exception {
++        byte[] array = new byte[5];
++        int offset = 0;
++        int length = 0;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        int value = boundedInputStream.read(array, offset, length);
++        assertThat(value).isEqualTo(0);
++    }
++
++    @Test
++    public void readArray_exceedEndOfStream() throws Exception {
++        byte[] array = new byte[5];
++        int offset = 0;
++        int length = 1;
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        // Move the position of the stream to the end.
++        boundedInputStream.skip(TEST_BYTES_LENGTH);
++
++        int value = boundedInputStream.read(array, offset, length);
++
++        assertThat(value).isEqualTo(-1);
++    }
++
++    @Test
++    public void readArray_lengthGreaterThanStreamRemaining() throws Exception {
++        byte[] array = new byte[5];
++        int offset = 1;
++        int length = array.length - 1; // 4
++        BoundedInputStream boundedInputStream =
++                createBoundedInputStream(testBytes, 0, TEST_BYTES_LENGTH);
++
++        // Moves the position of the stream to end-2.
++        boundedInputStream.skip(TEST_BYTES_LENGTH - 2);
++
++        // Reads the last two bytes of the stream to the array, and put the data at offset 1.
++        int value = boundedInputStream.read(array, offset, length);
++
++        byte[] expectedArray = new byte[] {0, 40, 50, 0, 0};
++        assertArrayEquals(expectedArray, array);
++        assertThat(value).isEqualTo(2);
++
++        // Reachs the end of the stream, thus cannot read anymore.
++        assertThat(boundedInputStream.read()).isEqualTo(-1);
++    }
++
++    private static BoundedInputStream createBoundedInputStream(
++            final byte[] testBytes, long start, long remaining) {
++        ByteBuffer buffer = ByteBuffer.wrap(testBytes);
++        SeekableByteChannelCompat channel = new ByteBufferChannel(buffer);
++        return new BoundedInputStream(channel, start, remaining);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ByteBufferChannelTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ByteBufferChannelTest.java
+index abda43058aa90..ce625de8034b7 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ByteBufferChannelTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ByteBufferChannelTest.java
+@@ -16,254 +16,252 @@ limitations under the License.
+ package org.tensorflow.lite.support.metadata;
+ 
+ import static com.google.common.truth.Truth.assertThat;
+-import static java.nio.charset.StandardCharsets.UTF_8;
++
+ import static org.junit.Assert.assertThrows;
+ 
+-import java.nio.ByteBuffer;
++import static java.nio.charset.StandardCharsets.UTF_8;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ 
++import java.nio.ByteBuffer;
++
+ /** Tests of {@link ByteBufferChannel}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class ByteBufferChannelTest {
+-  private static final String VALID_STRING = "1234567890";
+-  private final ByteBuffer validByteBuffer = ByteBuffer.wrap(VALID_STRING.getBytes(UTF_8));
+-  private final int validByteBufferLength = validByteBuffer.limit();
+-
+-  @Test
+-  public void byteBufferChannel_validByteBuffer() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    assertThat(byteBufferChannel).isNotNull();
+-  }
+-
+-  @Test
+-  public void byteBufferChannel_nullByteBuffer_throwsException() {
+-    NullPointerException exception =
+-        assertThrows(NullPointerException.class, () -> new ByteBufferChannel(/*buffer=*/ null));
+-    assertThat(exception).hasMessageThat().isEqualTo("The ByteBuffer cannot be null.");
+-  }
+-
+-  @Test
+-  public void isOpen_openedByteBufferChannel() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    assertThat(byteBufferChannel.isOpen()).isTrue();
+-  }
+-
+-  @Test
+-  public void position_newByteBufferChannelWithInitialPosition0() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long position = byteBufferChannel.position();
+-
+-    long expectedPosition = 0;
+-    assertThat(position).isEqualTo(expectedPosition);
+-  }
+-
+-  @Test
+-  public void position_validNewPosition() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long validNewPosition = 6;
+-
+-    byteBufferChannel.position(validNewPosition);
+-    long position = byteBufferChannel.position();
+-
+-    assertThat(position).isEqualTo(validNewPosition);
+-  }
+-
+-  @Test
+-  public void position_negtiveNewPosition_throwsException() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long invalidNewPosition = -1;
+-
+-    IllegalArgumentException exception =
+-        assertThrows(
+-            IllegalArgumentException.class, () -> byteBufferChannel.position(invalidNewPosition));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo("The new position should be non-negative and be less than Integer.MAX_VALUE.");
+-  }
+-
+-  @Test
+-  public void position_newPositionGreaterThanMaxIntegerValue_throwsException() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long invalidNewPosition = Integer.MAX_VALUE + 1;
+-
+-    IllegalArgumentException exception =
+-        assertThrows(
+-            IllegalArgumentException.class, () -> byteBufferChannel.position(invalidNewPosition));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo("The new position should be non-negative and be less than Integer.MAX_VALUE.");
+-  }
+-
+-  @Test
+-  public void position_newPositionGreaterThanByfferLength_throwsException() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long invalidNewPosition = (long) validByteBufferLength + 1;
+-
+-    IllegalArgumentException exception =
+-        assertThrows(
+-            IllegalArgumentException.class, () -> byteBufferChannel.position(invalidNewPosition));
+-    assertThat(exception).hasMessageThat().isEqualTo("newPosition > limit: (11 > 10)");
+-  }
+-
+-  @Test
+-  public void read_fromPosition0() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long validNewPosition = 0;
+-
+-    byteBufferChannel.position(validNewPosition);
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
+-    int numBytes = byteBufferChannel.read(dstBuffer);
+-
+-    assertThat(numBytes).isEqualTo(validByteBufferLength);
+-    assertThat(dstBuffer).isEqualTo(validByteBuffer);
+-  }
+-
+-  @Test
+-  public void read_fromPosition5() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long validNewPosition = 5;
+-
+-    byteBufferChannel.position(validNewPosition);
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
+-    int numBytes = byteBufferChannel.read(dstBuffer);
+-
+-    assertThat(numBytes).isEqualTo(validByteBufferLength - (int) validNewPosition);
+-    String dstString = convertByteByfferToString(dstBuffer, numBytes);
+-    String expectedString = "67890";
+-    assertThat(dstString).isEqualTo(expectedString);
+-  }
+-
+-  @Test
+-  public void read_fromPositionValidByteBufferLength() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long validNewPosition = validByteBufferLength;
+-
+-    byteBufferChannel.position(validNewPosition);
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
+-    int numBytes = byteBufferChannel.read(dstBuffer);
+-
+-    assertThat(numBytes).isEqualTo(-1);
+-  }
+-
+-  @Test
+-  public void read_dstBufferRemaining0() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long validNewPosition = 0;
+-
+-    byteBufferChannel.position(validNewPosition);
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
+-    dstBuffer.position(validByteBufferLength);
+-    int numBytes = byteBufferChannel.read(dstBuffer);
+-
+-    assertThat(numBytes).isEqualTo(0);
+-    String dstString = convertByteByfferToString(dstBuffer, numBytes);
+-    String expectedString = "";
+-    assertThat(dstString).isEqualTo(expectedString);
+-  }
+-
+-  @Test
+-  public void read_dstBufferIsSmallerThanTheBufferChannel() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    int dstBufferLength = 3;
+-
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(dstBufferLength);
+-    int numBytes = byteBufferChannel.read(dstBuffer);
+-
+-    assertThat(numBytes).isEqualTo(dstBufferLength);
+-    assertThat(validByteBuffer.position()).isEqualTo(dstBufferLength);
+-
+-    String dstString = convertByteByfferToString(dstBuffer, dstBufferLength);
+-    String expectedString = "123";
+-    assertThat(dstString).isEqualTo(expectedString);
+-  }
+-
+-  @Test
+-  public void size_validBuffer() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    assertThat(byteBufferChannel.size()).isEqualTo(validByteBufferLength);
+-  }
+-
+-  @Test
+-  public void truncate_validSizeAndPosition0() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long truncateSize = 3;
+-
+-    byteBufferChannel.truncate(truncateSize);
+-
+-    assertThat(byteBufferChannel.size()).isEqualTo(truncateSize);
+-    assertThat(byteBufferChannel.position()).isEqualTo(0);
+-  }
+-
+-  @Test
+-  public void truncate_validSizeAndPosition5() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long validNewPosition = 5;
+-
+-    byteBufferChannel.position(validNewPosition);
+-    long truncateSize = 3;
+-    byteBufferChannel.truncate(truncateSize);
+-
+-    assertThat(byteBufferChannel.position()).isEqualTo(truncateSize);
+-  }
+-
+-  @Test
+-  public void truncate_sizeNotSmallerThanBufferSize() {
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    long truncateSize = (long) validByteBufferLength;
+-
+-    byteBufferChannel.truncate(truncateSize);
+-
+-    assertThat(byteBufferChannel.position()).isEqualTo(0);
+-  }
+-
+-  @Test
+-  public void write_srcBufferSmallerThanBufferChannel() {
+-    String srcString = "5555";
+-    long newPosition = 3;
+-    String expectedString = "1235555890";
+-    ByteBuffer srcBuffer = ByteBuffer.wrap(srcString.getBytes(UTF_8));
+-
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    byteBufferChannel.position(newPosition);
+-    byteBufferChannel.write(srcBuffer);
+-
+-    assertThat(byteBufferChannel.position()).isEqualTo(newPosition + srcString.length());
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
+-    byteBufferChannel.position(0);
+-    byteBufferChannel.read(dstBuffer);
+-    ByteBuffer expectedBuffer = ByteBuffer.wrap(expectedString.getBytes(UTF_8));
+-    dstBuffer.rewind();
+-    expectedBuffer.rewind();
+-    assertThat(dstBuffer).isEqualTo(expectedBuffer);
+-  }
+-
+-  @Test
+-  public void write_srcBufferGreaterThanBufferChannel() {
+-    String srcString = "5555";
+-    long newPosition = 8;
+-    String expectedString = "1234567855";
+-    ByteBuffer srcBuffer = ByteBuffer.wrap(srcString.getBytes(UTF_8));
+-
+-    ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
+-    byteBufferChannel.position(newPosition);
+-    byteBufferChannel.write(srcBuffer);
+-    assertThat(byteBufferChannel.position()).isEqualTo(validByteBufferLength);
+-
+-    ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
+-    byteBufferChannel.position(0);
+-    byteBufferChannel.read(dstBuffer);
+-    ByteBuffer expectedBuffer = ByteBuffer.wrap(expectedString.getBytes(UTF_8));
+-    dstBuffer.rewind();
+-    expectedBuffer.rewind();
+-    assertThat(dstBuffer).isEqualTo(expectedBuffer);
+-  }
+-
+-  private static String convertByteByfferToString(ByteBuffer buffer, int arrLength) {
+-    byte[] bytes = new byte[arrLength];
+-    buffer.rewind();
+-    buffer.get(bytes);
+-    return new String(bytes, UTF_8);
+-  }
++    private static final String VALID_STRING = "1234567890";
++    private final ByteBuffer validByteBuffer = ByteBuffer.wrap(VALID_STRING.getBytes(UTF_8));
++    private final int validByteBufferLength = validByteBuffer.limit();
++
++    @Test
++    public void byteBufferChannel_validByteBuffer() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        assertThat(byteBufferChannel).isNotNull();
++    }
++
++    @Test
++    public void byteBufferChannel_nullByteBuffer_throwsException() {
++        NullPointerException exception = assertThrows(
++                NullPointerException.class, () -> new ByteBufferChannel(/*buffer=*/null));
++        assertThat(exception).hasMessageThat().isEqualTo("The ByteBuffer cannot be null.");
++    }
++
++    @Test
++    public void isOpen_openedByteBufferChannel() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        assertThat(byteBufferChannel.isOpen()).isTrue();
++    }
++
++    @Test
++    public void position_newByteBufferChannelWithInitialPosition0() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long position = byteBufferChannel.position();
++
++        long expectedPosition = 0;
++        assertThat(position).isEqualTo(expectedPosition);
++    }
++
++    @Test
++    public void position_validNewPosition() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long validNewPosition = 6;
++
++        byteBufferChannel.position(validNewPosition);
++        long position = byteBufferChannel.position();
++
++        assertThat(position).isEqualTo(validNewPosition);
++    }
++
++    @Test
++    public void position_negtiveNewPosition_throwsException() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long invalidNewPosition = -1;
++
++        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                () -> byteBufferChannel.position(invalidNewPosition));
++        assertThat(exception).hasMessageThat().isEqualTo(
++                "The new position should be non-negative and be less than Integer.MAX_VALUE.");
++    }
++
++    @Test
++    public void position_newPositionGreaterThanMaxIntegerValue_throwsException() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long invalidNewPosition = Integer.MAX_VALUE + 1;
++
++        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                () -> byteBufferChannel.position(invalidNewPosition));
++        assertThat(exception).hasMessageThat().isEqualTo(
++                "The new position should be non-negative and be less than Integer.MAX_VALUE.");
++    }
++
++    @Test
++    public void position_newPositionGreaterThanByfferLength_throwsException() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long invalidNewPosition = (long) validByteBufferLength + 1;
++
++        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                () -> byteBufferChannel.position(invalidNewPosition));
++        assertThat(exception).hasMessageThat().isEqualTo("newPosition > limit: (11 > 10)");
++    }
++
++    @Test
++    public void read_fromPosition0() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long validNewPosition = 0;
++
++        byteBufferChannel.position(validNewPosition);
++        ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
++        int numBytes = byteBufferChannel.read(dstBuffer);
++
++        assertThat(numBytes).isEqualTo(validByteBufferLength);
++        assertThat(dstBuffer).isEqualTo(validByteBuffer);
++    }
++
++    @Test
++    public void read_fromPosition5() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long validNewPosition = 5;
++
++        byteBufferChannel.position(validNewPosition);
++        ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
++        int numBytes = byteBufferChannel.read(dstBuffer);
++
++        assertThat(numBytes).isEqualTo(validByteBufferLength - (int) validNewPosition);
++        String dstString = convertByteByfferToString(dstBuffer, numBytes);
++        String expectedString = "67890";
++        assertThat(dstString).isEqualTo(expectedString);
++    }
++
++    @Test
++    public void read_fromPositionValidByteBufferLength() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long validNewPosition = validByteBufferLength;
++
++        byteBufferChannel.position(validNewPosition);
++        ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
++        int numBytes = byteBufferChannel.read(dstBuffer);
++
++        assertThat(numBytes).isEqualTo(-1);
++    }
++
++    @Test
++    public void read_dstBufferRemaining0() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long validNewPosition = 0;
++
++        byteBufferChannel.position(validNewPosition);
++        ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
++        dstBuffer.position(validByteBufferLength);
++        int numBytes = byteBufferChannel.read(dstBuffer);
++
++        assertThat(numBytes).isEqualTo(0);
++        String dstString = convertByteByfferToString(dstBuffer, numBytes);
++        String expectedString = "";
++        assertThat(dstString).isEqualTo(expectedString);
++    }
++
++    @Test
++    public void read_dstBufferIsSmallerThanTheBufferChannel() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        int dstBufferLength = 3;
++
++        ByteBuffer dstBuffer = ByteBuffer.allocate(dstBufferLength);
++        int numBytes = byteBufferChannel.read(dstBuffer);
++
++        assertThat(numBytes).isEqualTo(dstBufferLength);
++        assertThat(validByteBuffer.position()).isEqualTo(dstBufferLength);
++
++        String dstString = convertByteByfferToString(dstBuffer, dstBufferLength);
++        String expectedString = "123";
++        assertThat(dstString).isEqualTo(expectedString);
++    }
++
++    @Test
++    public void size_validBuffer() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        assertThat(byteBufferChannel.size()).isEqualTo(validByteBufferLength);
++    }
++
++    @Test
++    public void truncate_validSizeAndPosition0() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long truncateSize = 3;
++
++        byteBufferChannel.truncate(truncateSize);
++
++        assertThat(byteBufferChannel.size()).isEqualTo(truncateSize);
++        assertThat(byteBufferChannel.position()).isEqualTo(0);
++    }
++
++    @Test
++    public void truncate_validSizeAndPosition5() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long validNewPosition = 5;
++
++        byteBufferChannel.position(validNewPosition);
++        long truncateSize = 3;
++        byteBufferChannel.truncate(truncateSize);
++
++        assertThat(byteBufferChannel.position()).isEqualTo(truncateSize);
++    }
++
++    @Test
++    public void truncate_sizeNotSmallerThanBufferSize() {
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        long truncateSize = (long) validByteBufferLength;
++
++        byteBufferChannel.truncate(truncateSize);
++
++        assertThat(byteBufferChannel.position()).isEqualTo(0);
++    }
++
++    @Test
++    public void write_srcBufferSmallerThanBufferChannel() {
++        String srcString = "5555";
++        long newPosition = 3;
++        String expectedString = "1235555890";
++        ByteBuffer srcBuffer = ByteBuffer.wrap(srcString.getBytes(UTF_8));
++
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        byteBufferChannel.position(newPosition);
++        byteBufferChannel.write(srcBuffer);
++
++        assertThat(byteBufferChannel.position()).isEqualTo(newPosition + srcString.length());
++        ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
++        byteBufferChannel.position(0);
++        byteBufferChannel.read(dstBuffer);
++        ByteBuffer expectedBuffer = ByteBuffer.wrap(expectedString.getBytes(UTF_8));
++        dstBuffer.rewind();
++        expectedBuffer.rewind();
++        assertThat(dstBuffer).isEqualTo(expectedBuffer);
++    }
++
++    @Test
++    public void write_srcBufferGreaterThanBufferChannel() {
++        String srcString = "5555";
++        long newPosition = 8;
++        String expectedString = "1234567855";
++        ByteBuffer srcBuffer = ByteBuffer.wrap(srcString.getBytes(UTF_8));
++
++        ByteBufferChannel byteBufferChannel = new ByteBufferChannel(validByteBuffer);
++        byteBufferChannel.position(newPosition);
++        byteBufferChannel.write(srcBuffer);
++        assertThat(byteBufferChannel.position()).isEqualTo(validByteBufferLength);
++
++        ByteBuffer dstBuffer = ByteBuffer.allocate(validByteBufferLength);
++        byteBufferChannel.position(0);
++        byteBufferChannel.read(dstBuffer);
++        ByteBuffer expectedBuffer = ByteBuffer.wrap(expectedString.getBytes(UTF_8));
++        dstBuffer.rewind();
++        expectedBuffer.rewind();
++        assertThat(dstBuffer).isEqualTo(expectedBuffer);
++    }
++
++    private static String convertByteByfferToString(ByteBuffer buffer, int arrLength) {
++        byte[] bytes = new byte[arrLength];
++        buffer.rewind();
++        buffer.get(bytes);
++        return new String(bytes, UTF_8);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java
+index 67fc50d9f57b1..9f1173a1ea19b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java
+@@ -16,24 +16,20 @@ limitations under the License.
+ package org.tensorflow.lite.support.metadata;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertArrayEquals;
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.content.Context;
+ import android.content.res.AssetFileDescriptor;
++
+ import androidx.test.core.app.ApplicationProvider;
++
+ import com.google.flatbuffers.FlatBufferBuilder;
+-import java.io.FileInputStream;
+-import java.io.InputStream;
+-import java.nio.ByteBuffer;
+-import java.nio.channels.FileChannel;
+-import java.util.Arrays;
+-import java.util.Collection;
+-import java.util.HashSet;
+-import java.util.Random;
+-import java.util.Set;
++
+ import org.apache.commons.io.IOUtils;
+ import org.checkerframework.checker.nullness.qual.Nullable;
++import org.junit.Ignore;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.junit.runners.Suite;
+@@ -56,931 +52,903 @@ import org.tensorflow.lite.support.metadata.schema.ModelMetadata;
+ import org.tensorflow.lite.support.metadata.schema.SubGraphMetadata;
+ import org.tensorflow.lite.support.metadata.schema.TensorMetadata;
+ 
+-import org.junit.Ignore;
++import java.io.FileInputStream;
++import java.io.InputStream;
++import java.nio.ByteBuffer;
++import java.nio.channels.FileChannel;
++import java.util.Arrays;
++import java.util.Collection;
++import java.util.HashSet;
++import java.util.Random;
++import java.util.Set;
+ 
+ /** Tests of {@link MetadataExtractor}. */
+ @RunWith(Suite.class)
+ @SuiteClasses({MetadataExtractorTest.General.class, MetadataExtractorTest.InputTensorType.class})
+ public class MetadataExtractorTest {
+-  private static final int[] validShape = new int[] {4, 10, 10, 3};
+-  private static final byte DATA_TYPE = TensorType.UINT8;
+-  private static final byte CONTENT_PROPERTIES_TYPE = ContentProperties.ImageProperties;
+-  private static final float VALID_SCALE = 3.3f;
+-  private static final long VALID_ZERO_POINT = 2;
+-  private static final float DEFAULT_SCALE = 0.0f;
+-  private static final long DEFAULT_ZERO_POINT = 0;
+-  private static final String MODEL_NAME = "model.tflite";
+-  // Scale and zero point should both be a single value, not an array.
+-  private static final float[] invalidScale = new float[] {0.0f, 1.2f};
+-  private static final long[] invalidZeroPoint = new long[] {1, 2};
+-  private static final String MODEL_PATH = "mobilenet_v1_1.0_224_quant.tflite";
+-  // labels.txt is packed in mobilenet_v1_1.0_224_quant.tflite as an associated file.
+-  private static final String VALID_LABEL_FILE_NAME = "labels.txt";
+-  // invalid.txt is not packed in mobilenet_v1_1.0_224_quant.tflite.
+-  private static final String INVALID_LABEL_FILE_NAME = "invalid.txt";
+-  private static final int EMPTY_FLATBUFFER_VECTOR = -1;
+-  private static final String TFLITE_MODEL_IDENTIFIER = "TFL3";
+-  private static final String TFLITE_METADATA_IDENTIFIER = "M001";
+-
+-  /** General tests of MetadataExtractor. */
+-  @RunWith(RobolectricTestRunner.class)
+-  public static final class General extends MetadataExtractorTest {
+-
+-    @Test
+-    public void hasMetadata_modelWithMetadata() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      assertThat(metadataExtractor.hasMetadata()).isTrue();
+-    }
+-
+-    @Test
+-    public void hasMetadata_modelWithoutMetadata() throws Exception {
+-      // Creates a model flatbuffer without metadata.
+-      ByteBuffer modelWithoutMetadata = createModelByteBuffer(/*metadataBuffer=*/ null, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithoutMetadata);
+-      assertThat(metadataExtractor.hasMetadata()).isFalse();
+-    }
+-
+-    @Ignore
+-    @Test
+-    public void getAssociatedFile_validAssociateFile() throws Exception {
+-      ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
+-      MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
+-      InputStream associateFileStream =
+-          mobileNetMetadataExtractor.getAssociatedFile(VALID_LABEL_FILE_NAME);
+-
+-      // Reads the golden file from context.
+-      Context context = ApplicationProvider.getApplicationContext();
+-      InputStream goldenAssociateFileStream = context.getAssets().open(VALID_LABEL_FILE_NAME);
+-      assertThat(IOUtils.contentEquals(goldenAssociateFileStream, associateFileStream)).isTrue();
+-    }
+-
+-    @Ignore
+-    @Test
+-    public void getAssociatedFile_invalidAssociateFile() throws Exception {
+-      ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
+-      MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> mobileNetMetadataExtractor.getAssociatedFile(INVALID_LABEL_FILE_NAME));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .isEqualTo(
+-              String.format(
+-                  "The file, %s, does not exist in the zip file.", INVALID_LABEL_FILE_NAME));
+-    }
+-
+-    @Ignore
+-    @Test
+-    public void getAssociatedFile_nullFileName() throws Exception {
+-      ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
+-      MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> mobileNetMetadataExtractor.getAssociatedFile(/*fileName=*/ null));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("The file, null, does not exist in the zip file.");
+-    }
+-
+-    @Test
+-    public void getAssociatedFile_nonZipModel_throwsException() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalStateException exception =
+-          assertThrows(
+-              IllegalStateException.class,
+-              () -> metadataExtractor.getAssociatedFile(VALID_LABEL_FILE_NAME));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("This model does not contain associated files, and is not a Zip file.");
+-    }
+-
+-    @Test
+-    public void getAssociatedFileNames_nonZipModel_throwsException() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalStateException exception =
+-          assertThrows(IllegalStateException.class, metadataExtractor::getAssociatedFileNames);
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("This model does not contain associated files, and is not a Zip file.");
+-    }
+-
+-    @Ignore
+-    @Test
+-    public void getAssociatedFileNames_validFileNames() throws Exception {
+-      ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
+-      MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
+-      Set<String> expectedSet = new HashSet<>();
+-      expectedSet.add(VALID_LABEL_FILE_NAME);
+-      assertThat(mobileNetMetadataExtractor.getAssociatedFileNames()).isEqualTo(expectedSet);
+-    }
+-
+-    @Test
+-    public void metadataExtractor_loadNullBuffer_throwsException() {
+-      ByteBuffer nullBuffer = null;
+-      NullPointerException exception =
+-          assertThrows(NullPointerException.class, () -> new MetadataExtractor(nullBuffer));
+-      assertThat(exception).hasMessageThat().contains("Model flatbuffer cannot be null.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_loadRandomBuffer_throwsException() {
+-      ByteBuffer randomBuffer = createRandomByteBuffer();
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> new MetadataExtractor(randomBuffer));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "The identifier of the model is invalid. The buffer may not be a valid TFLite model"
+-                  + " flatbuffer.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_loadModelWithInvalidIdentifier_throwsException() {
+-      // Creates a model with an invalid identifier.
+-      String invalidIdentifier = "INVI";
+-      FlatBufferBuilder builder = new FlatBufferBuilder();
+-      Model.startModel(builder);
+-      int model = Model.endModel(builder);
+-      builder.finish(model, invalidIdentifier);
+-      ByteBuffer modelBuffer = builder.dataBuffer();
+-
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> new MetadataExtractor(modelBuffer));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "The identifier of the model is invalid. The buffer may not be a valid TFLite model"
+-                  + " flatbuffer.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_loadMetadataWithInvalidIdentifier_throwsException() {
+-      // Creates a model with metadata which contains an invalid identifier.
+-      String invalidIdentifier = "INVI";
+-      ByteBuffer metadata = createMetadataByteBuffer(invalidIdentifier, null);
+-      ByteBuffer modelBuffer = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(IllegalArgumentException.class, () -> new MetadataExtractor(modelBuffer));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains(
+-              "The identifier of the metadata is invalid. The buffer may not be a valid TFLite"
+-                  + " metadata flatbuffer.");
+-    }
+-
+-    @Test
+-    public void getInputTensorCount_validModelFile() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      int count = metadataExtractor.getInputTensorCount();
+-      assertThat(count).isEqualTo(3);
+-    }
+-
+-    @Test
+-    public void getOutputTensorCount_validModelFile() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      int count = metadataExtractor.getOutputTensorCount();
+-      assertThat(count).isEqualTo(3);
+-    }
+-
+-    @Test
+-    public void getInputTensorShape_validTensorShape() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      int[] shape = metadataExtractor.getInputTensorShape(0);
+-      assertArrayEquals(validShape, shape);
+-    }
+-
+-    @Test
+-    public void getInputTensorShape_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      int[] shape = metadataExtractor.getInputTensorShape(1);
+-      assertThat(shape).isEmpty();
+-    }
+-
+-    @Test
+-    public void getInputTensorType_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      byte type = metadataExtractor.getInputTensorType(1);
+-      assertThat(type).isEqualTo(TensorType.FLOAT32);
+-    }
+-
+-    @Test
+-    public void getOutputTensorShape_validTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      int[] shape = metadataExtractor.getOutputTensorShape(0);
+-      assertArrayEquals(validShape, shape);
+-    }
+-
+-    @Test
+-    public void getOutputTensorShape_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      int[] shape = metadataExtractor.getOutputTensorShape(1);
+-      assertThat(shape).isEmpty();
+-    }
+-
+-    @Test
+-    public void getOutputTensorType_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      byte type = metadataExtractor.getOutputTensorType(1);
+-      assertThat(type).isEqualTo(TensorType.FLOAT32);
+-    }
+-
+-    @Test
+-    public void getInputTensorShape_indexGreaterThanTensorNumber_throwsException()
+-        throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getInputTensorShape(3));
+-      assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getInputTensorShape_negtiveIndex_throwsException() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getInputTensorShape(-1));
+-      assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getOutputTensorShape_indexGreaterThanTensorNumber_throwsException()
+-        throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getOutputTensorShape(3));
+-      assertThat(exception).hasMessageThat().contains("The outputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getOutputTensorShape_negtiveIndex_throwsException() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getOutputTensorShape(-1));
+-      assertThat(exception).hasMessageThat().contains("The outputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getModelMetadata_modelWithMetadata() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      ModelMetadata modelMetadata = metadataExtractor.getModelMetadata();
+-      assertThat(modelMetadata.name()).isEqualTo(MODEL_NAME);
+-    }
+-
+-    @Test
+-    public void getModelMetadata_modelWithoutMetadata_throwsException() throws Exception {
+-      // Creates a model flatbuffer without metadata.
+-      ByteBuffer modelWithoutMetadata = createModelByteBuffer(/*metadataBuffer=*/ null, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithoutMetadata);
+-
+-      IllegalStateException exception =
+-          assertThrows(IllegalStateException.class, () -> metadataExtractor.getModelMetadata());
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("This model does not contain model metadata.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_modelWithEmptySubgraphMetadata_throwsException() {
+-      // Creates a metadata FlatBuffer without empty subgraph metadata.
+-      FlatBufferBuilder builder = new FlatBufferBuilder();
+-      SubGraphMetadata.startSubGraphMetadata(builder);
+-      int subgraph1Metadata = SubGraphMetadata.endSubGraphMetadata(builder);
+-      int subgraphsMetadata =
+-          ModelMetadata.createSubgraphMetadataVector(builder, new int[] {subgraph1Metadata});
+-
+-      ModelMetadata.startModelMetadata(builder);
+-      ModelMetadata.addSubgraphMetadata(builder, subgraphsMetadata);
+-      int modelMetadata = ModelMetadata.endModelMetadata(builder);
+-      builder.finish(modelMetadata, TFLITE_METADATA_IDENTIFIER);
+-      ByteBuffer emptyMetadata = builder.dataBuffer();
+-      ByteBuffer modelWithEmptyMetadata = createModelByteBuffer(emptyMetadata, DATA_TYPE);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> new MetadataExtractor(modelWithEmptyMetadata));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .isEqualTo(
+-              "The number of input tensors in the model is 3. The number of input tensors that"
+-                  + " recorded in the metadata is 0. These two values does not match.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_modelWithEmptyMetadata_throwsException() {
+-      // Creates a empty metadata FlatBuffer.
+-      FlatBufferBuilder builder = new FlatBufferBuilder();
+-      ModelMetadata.startModelMetadata(builder);
+-      int modelMetadata = ModelMetadata.endModelMetadata(builder);
+-      builder.finish(modelMetadata, TFLITE_METADATA_IDENTIFIER);
+-
+-      ByteBuffer emptyMetadata = builder.dataBuffer();
+-      ByteBuffer modelWithEmptyMetadata = createModelByteBuffer(emptyMetadata, DATA_TYPE);
+-
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> new MetadataExtractor(modelWithEmptyMetadata));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("The metadata flatbuffer does not contain any subgraph metadata.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_modelWithNoMetadata_throwsException() throws Exception {
+-      // Creates a model flatbuffer without metadata.
+-      ByteBuffer modelWithoutMetadata = createModelByteBuffer(/*metadataBuffer=*/ null, DATA_TYPE);
+-
+-      // It is allowed to create a model without metadata, but invoking methods that reads metadata
+-      // is not allowed.
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithoutMetadata);
+-
+-      IllegalStateException exception =
+-          assertThrows(
+-              IllegalStateException.class, () -> metadataExtractor.getInputTensorMetadata(0));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("This model does not contain model metadata.");
+-    }
+-
+-    @Test
+-    public void metadataExtractor_modelWithIrrelevantMetadata_throwsException() throws Exception {
+-      // Creates a model with irrelevant metadata.
+-      FlatBufferBuilder builder = new FlatBufferBuilder();
+-      SubGraph.startSubGraph(builder);
+-      int subgraph = SubGraph.endSubGraph(builder);
+-
+-      int metadataName = builder.createString("Irrelevant metadata");
+-      Metadata.startMetadata(builder);
+-      Metadata.addName(builder, metadataName);
+-      int metadata = Metadata.endMetadata(builder);
+-      int metadataArray = Model.createMetadataVector(builder, new int[] {metadata});
+-
+-      // Creates Model.
+-      int[] subgraphs = new int[1];
+-      subgraphs[0] = subgraph;
+-      int modelSubgraphs = Model.createSubgraphsVector(builder, subgraphs);
+-      Model.startModel(builder);
+-      Model.addSubgraphs(builder, modelSubgraphs);
+-      Model.addMetadata(builder, metadataArray);
+-      int model = Model.endModel(builder);
+-      builder.finish(model, TFLITE_MODEL_IDENTIFIER);
+-      ByteBuffer modelBuffer = builder.dataBuffer();
+-
+-      // It is allowed to create a model without metadata, but invoking methods that reads metadata
+-      // is not allowed.
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelBuffer);
+-
+-      IllegalStateException exception =
+-          assertThrows(
+-              IllegalStateException.class, () -> metadataExtractor.getInputTensorMetadata(0));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("This model does not contain model metadata.");
+-    }
+-
+-    @Test
+-    public void getInputTensorMetadata_validTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      TensorMetadata inputMetadata = metadataExtractor.getInputTensorMetadata(0);
+-      assertThat(inputMetadata.content().contentPropertiesType())
+-          .isEqualTo(CONTENT_PROPERTIES_TYPE);
+-    }
+-
+-    @Test
+-    public void getInputTensorMetadata_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      TensorMetadata inputMetadata = metadataExtractor.getInputTensorMetadata(1);
+-      assertThat(inputMetadata.content()).isNull();
+-    }
+-
+-    @Test
+-    public void getInputTensorMetadata_invalidTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      TensorMetadata inputMetadata = metadataExtractor.getInputTensorMetadata(2);
+-      assertThat(inputMetadata.content().contentPropertiesType())
+-          .isEqualTo(CONTENT_PROPERTIES_TYPE);
+-    }
+-
+-    @Test
+-    public void getOutputTensorMetadata_validTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      TensorMetadata outputMetadata = metadataExtractor.getOutputTensorMetadata(0);
+-      assertThat(outputMetadata.content().contentPropertiesType())
+-          .isEqualTo(CONTENT_PROPERTIES_TYPE);
+-    }
+-
+-    @Test
+-    public void getOutputTensorMetadata_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      TensorMetadata outputMetadata = metadataExtractor.getOutputTensorMetadata(1);
+-      assertThat(outputMetadata.content()).isNull();
+-    }
+-
+-    @Test
+-    public void getOutputTensorMetadata_invalidTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      TensorMetadata outputMetadata = metadataExtractor.getOutputTensorMetadata(2);
+-      assertThat(outputMetadata.content().contentPropertiesType())
+-          .isEqualTo(CONTENT_PROPERTIES_TYPE);
+-    }
+-
+-    @Test
+-    public void getInputTensorMetadata_indexGreaterThanTensorNumber_throwsException()
+-        throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getInputTensorMetadata(3));
+-      assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getInputTensorMetadata_negtiveIndex_throwsException() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getInputTensorMetadata(-1));
+-      assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getOutputTensorMetadata_indexGreaterThanTensorNumber_throwsException()
+-        throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getOutputTensorMetadata(3));
+-      assertThat(exception).hasMessageThat().contains("The outputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getOutputTensorMetadata_negtiveIndex_throwsException() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class, () -> metadataExtractor.getOutputTensorMetadata(-1));
+-      assertThat(exception).hasMessageThat().contains("The outputIndex specified is invalid.");
+-    }
+-
+-    @Test
+-    public void getInputTensorQuantizationParams_validScaleAndZeroPoint() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      QuantizationParams quantizationParams = metadataExtractor.getInputTensorQuantizationParams(0);
+-      assertThat(quantizationParams.getScale()).isEqualTo(VALID_SCALE);
+-      assertThat(quantizationParams.getZeroPoint()).isEqualTo(VALID_ZERO_POINT);
+-    }
+-
+-    @Test
+-    public void getInputTensorQuantizationParams_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      QuantizationParams quantizationParams = metadataExtractor.getInputTensorQuantizationParams(1);
+-      // Scale and zero point are expected to be 1.0f and 0, respectively as default.
+-      assertThat(quantizationParams.getScale()).isEqualTo(DEFAULT_SCALE);
+-      assertThat(quantizationParams.getZeroPoint()).isEqualTo(DEFAULT_ZERO_POINT);
+-    }
+-
+-    @Test
+-    public void getInputTensorQuantizationParams_invalidScale() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> metadataExtractor.getInputTensorQuantizationParams(2));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("Input and output tensors do not support per-channel quantization.");
+-    }
+-
+-    @Test
+-    public void getOutputTensorQuantizationParams_validScaleAndZeroPoint() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      QuantizationParams quantizationParams =
+-          metadataExtractor.getOutputTensorQuantizationParams(0);
+-      assertThat(quantizationParams.getScale()).isEqualTo(VALID_SCALE);
+-      assertThat(quantizationParams.getZeroPoint()).isEqualTo(VALID_ZERO_POINT);
+-    }
+-
+-    @Test
+-    public void getOutputTensorQuantizationParams_emptyTensor() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      QuantizationParams quantizationParams =
+-          metadataExtractor.getOutputTensorQuantizationParams(1);
+-      // Scale and zero point are expected to be 1.0f and 0, respectively as default.
+-      assertThat(quantizationParams.getScale()).isEqualTo(DEFAULT_SCALE);
+-      assertThat(quantizationParams.getZeroPoint()).isEqualTo(DEFAULT_ZERO_POINT);
+-    }
+-
+-    @Test
+-    public void getOutputTensorQuantizationParams_invalidScale() throws Exception {
+-      // Creates a model flatbuffer with metadata.
+-      ByteBuffer modelWithMetadata = createModelByteBuffer();
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      IllegalArgumentException exception =
+-          assertThrows(
+-              IllegalArgumentException.class,
+-              () -> metadataExtractor.getOutputTensorQuantizationParams(2));
+-      assertThat(exception)
+-          .hasMessageThat()
+-          .contains("Input and output tensors do not support per-channel quantization.");
+-    }
+-
+-    @Test
+-    public void isMinimumParserVersionSatisfied_olderVersion() throws Exception {
+-      // A version older than the current one. The version starts from 1.0.0, thus 0.10.0 will
+-      // precede any furture versions.
+-      String minVersion = "0.10";
+-      // Creates a metadata using the above version.
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-
+-      assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
+-    }
+-
+-    @Test
+-    public void isMinimumParserVersionSatisfied_sameVersionSamelength() throws Exception {
+-      // A version the same as the current one.
+-      String minVersion = MetadataParser.VERSION;
+-      // Creates a metadata using the above version.
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-
+-      assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
+-    }
+-
+-    @Test
+-    public void isMinimumParserVersionSatisfied_sameVersionLongerlength() throws Exception {
+-      // A version the same as the current one, but with longer length.
+-      String minVersion = MetadataParser.VERSION + ".0";
+-      // Creates a metadata using the above version.
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-
+-      assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
+-    }
+-
+-    @Test
+-    public void isMinimumParserVersionSatisfied_emptyVersion() throws Exception {
+-      // An empty version, which can be generated before the first versioned release.
+-      String minVersion = null;
+-      // Creates a metadata using the above version.
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-
+-      assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
+-    }
+-
+-    @Test
+-    public void isMinimumParserVersionSatisfied_newerVersion() throws Exception {
+-      // Creates a version newer than the current one by appending "1" to the end of the current
+-      // version for testing purposes. For example, 1.0.0 becomes 1.0.01.
+-      String minVersion = MetadataParser.VERSION + "1";
+-      // Creates a metadata using the above version.
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-
+-      assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isFalse();
+-    }
+-
+-    @Test
+-    public void isMinimumParserVersionSatisfied_newerVersionLongerLength() throws Exception {
+-      // Creates a version newer than the current one by appending ".1" to the end of the current
+-      // version for testing purposes. For example, 1.0.0 becomes 1.0.0.1.
+-      String minVersion = MetadataParser.VERSION + ".1";
+-      // Creates a metadata using the above version.
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
+-
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-
+-      assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isFalse();
+-    }
+-  }
+-
+-  /** Parameterized tests for the input tensor data type. */
+-  @RunWith(ParameterizedRobolectricTestRunner.class)
+-  public static final class InputTensorType extends MetadataExtractorTest {
+-    /** The tensor type that used to create the model buffer. */
+-    @Parameter(0)
+-    public byte tensorType;
+-
+-    /** A list of TensorType that is used in the test. */
+-    @Parameters
+-    public static Collection<Object[]> data() {
+-      return Arrays.asList(
+-          new Object[][] {
+-            {TensorType.FLOAT32}, {TensorType.INT32},
+-            {TensorType.UINT8}, {TensorType.INT64},
+-            {TensorType.STRING}
+-          });
+-    }
+-
+-    @Test
+-    public void getInputTensorType_validTensor() throws Exception {
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, null);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, tensorType);
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      byte type = metadataExtractor.getInputTensorType(0);
+-      assertThat(type).isEqualTo(tensorType);
+-    }
+-
+-    @Test
+-    public void getOutputTensorType_validTensor() throws Exception {
+-      ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, null);
+-      ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, tensorType);
+-      MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
+-      byte type = metadataExtractor.getOutputTensorType(0);
+-      assertThat(type).isEqualTo(tensorType);
+-    }
+-  }
+-
+-  /**
+-   * Creates an example metadata flatbuffer, which contains one subgraph with three inputs and three
+-   * outputs.
+-   */
+-  private static ByteBuffer createMetadataByteBuffer(
+-      String identifier, @Nullable String minVersionStr) {
+-    FlatBufferBuilder builder = new FlatBufferBuilder();
+-
+-    Content.startContent(builder);
+-    Content.addContentPropertiesType(builder, CONTENT_PROPERTIES_TYPE);
+-    int content = Content.endContent(builder);
+-
+-    TensorMetadata.startTensorMetadata(builder);
+-    TensorMetadata.addContent(builder, content);
+-    int metadataForValidTensor = TensorMetadata.endTensorMetadata(builder);
+-
+-    TensorMetadata.startTensorMetadata(builder);
+-    int metadataForEmptyTensor = TensorMetadata.endTensorMetadata(builder);
+-
+-    TensorMetadata.startTensorMetadata(builder);
+-    TensorMetadata.addContent(builder, content);
+-    int metadataForInvalidTensor = TensorMetadata.endTensorMetadata(builder);
+-
+-    int[] tensorMetadataArray =
+-        new int[] {metadataForValidTensor, metadataForEmptyTensor, metadataForInvalidTensor};
+-    int inputTensorMetadata =
+-        SubGraphMetadata.createInputTensorMetadataVector(builder, tensorMetadataArray);
+-    int outputTensorMetadata =
+-        SubGraphMetadata.createOutputTensorMetadataVector(builder, tensorMetadataArray);
+-
+-    SubGraphMetadata.startSubGraphMetadata(builder);
+-    SubGraphMetadata.addInputTensorMetadata(builder, inputTensorMetadata);
+-    SubGraphMetadata.addOutputTensorMetadata(builder, outputTensorMetadata);
+-    int subgraph1Metadata = SubGraphMetadata.endSubGraphMetadata(builder);
+-
+-    int[] subgraphMetadataArray = new int[] {subgraph1Metadata};
+-    int subgraphsMetadata =
+-        ModelMetadata.createSubgraphMetadataVector(builder, subgraphMetadataArray);
+-
+-    int modelName = builder.createString(MODEL_NAME);
+-    if (minVersionStr != null) {
+-      int minVersion = builder.createString(minVersionStr);
+-      ModelMetadata.startModelMetadata(builder);
+-      ModelMetadata.addMinParserVersion(builder, minVersion);
+-    } else {
+-      // If minVersionStr is null, skip generating the field in the metadata.
+-      ModelMetadata.startModelMetadata(builder);
+-    }
+-    ModelMetadata.addName(builder, modelName);
+-    ModelMetadata.addSubgraphMetadata(builder, subgraphsMetadata);
+-    int modelMetadata = ModelMetadata.endModelMetadata(builder);
+-
+-    builder.finish(modelMetadata, identifier);
+-    return builder.dataBuffer();
+-  }
+-
+-  private static int createQuantizationParameters(
+-      FlatBufferBuilder builder, float[] scale, long[] zeroPoint) {
+-    int inputScale = QuantizationParameters.createScaleVector(builder, scale);
+-    int inputZeroPoint = QuantizationParameters.createZeroPointVector(builder, zeroPoint);
+-    QuantizationParameters.startQuantizationParameters(builder);
+-    QuantizationParameters.addScale(builder, inputScale);
+-    QuantizationParameters.addZeroPoint(builder, inputZeroPoint);
+-    return QuantizationParameters.endQuantizationParameters(builder);
+-  }
+-
+-  private static int createTensor(
+-      FlatBufferBuilder builder, int[] inputShape, byte inputType, int inputQuantization) {
+-    int inputShapeVector1 = Tensor.createShapeVector(builder, inputShape);
+-    Tensor.startTensor(builder);
+-    Tensor.addShape(builder, inputShapeVector1);
+-    Tensor.addType(builder, inputType);
+-    Tensor.addQuantization(builder, inputQuantization);
+-    return Tensor.endTensor(builder);
+-  }
+-
+-  /**
+-   * Creates an example model flatbuffer, which contains one subgraph with three inputs and three
+-   * output.
+-   */
+-  private static ByteBuffer createModelByteBuffer(ByteBuffer metadataBuffer, byte dataType) {
+-    FlatBufferBuilder builder = new FlatBufferBuilder();
+-
+-    // Creates a valid set of quantization parameters.
+-    int validQuantization =
+-        createQuantizationParameters(
+-            builder, new float[] {VALID_SCALE}, new long[] {VALID_ZERO_POINT});
+-
+-    // Creates an invalid set of quantization parameters.
+-    int inValidQuantization = createQuantizationParameters(builder, invalidScale, invalidZeroPoint);
+-
+-    // Creates an input Tensor with valid quantization parameters.
+-    int validTensor = createTensor(builder, validShape, dataType, validQuantization);
+-
+-    // Creates an empty input Tensor.
+-    Tensor.startTensor(builder);
+-    int emptyTensor = Tensor.endTensor(builder);
+-
+-    // Creates an input Tensor with invalid quantization parameters.
+-    int invalidTensor = createTensor(builder, validShape, dataType, inValidQuantization);
+-
+-    // Creates the SubGraph.
+-    int[] tensors = new int[6];
+-    tensors[0] = validTensor;
+-    tensors[1] = emptyTensor;
+-    tensors[2] = invalidTensor;
+-    tensors[3] = validTensor;
+-    tensors[4] = emptyTensor;
+-    tensors[5] = invalidTensor;
+-    int subgraphTensors = SubGraph.createTensorsVector(builder, tensors);
+-
+-    int subgraphInputs = SubGraph.createInputsVector(builder, new int[] {0, 1, 2});
+-    int subgraphOutputs = SubGraph.createOutputsVector(builder, new int[] {3, 4, 5});
+-
+-    SubGraph.startSubGraph(builder);
+-    SubGraph.addTensors(builder, subgraphTensors);
+-    SubGraph.addInputs(builder, subgraphInputs);
+-    SubGraph.addOutputs(builder, subgraphOutputs);
+-    int subgraph = SubGraph.endSubGraph(builder);
+-
+-    // Creates the Model.
+-    int[] subgraphs = new int[1];
+-    subgraphs[0] = subgraph;
+-    int modelSubgraphs = Model.createSubgraphsVector(builder, subgraphs);
+-
+-    // Inserts metadataBuffer into the model if it's not null.
+-    int modelBuffers = EMPTY_FLATBUFFER_VECTOR;
+-    int metadataArray = EMPTY_FLATBUFFER_VECTOR;
+-    if (metadataBuffer != null) {
+-      int data = Buffer.createDataVector(builder, metadataBuffer);
+-      Buffer.startBuffer(builder);
+-      Buffer.addData(builder, data);
+-      int buffer = Buffer.endBuffer(builder);
+-      modelBuffers = Model.createBuffersVector(builder, new int[] {buffer});
+-
+-      int metadataName = builder.createString(ModelInfo.METADATA_FIELD_NAME);
+-      Metadata.startMetadata(builder);
+-      Metadata.addName(builder, metadataName);
+-      Metadata.addBuffer(builder, 0);
+-      int metadata = Metadata.endMetadata(builder);
+-      metadataArray = Model.createMetadataVector(builder, new int[] {metadata});
+-    }
+-
+-    Model.startModel(builder);
+-    Model.addSubgraphs(builder, modelSubgraphs);
+-    if (modelBuffers != EMPTY_FLATBUFFER_VECTOR && metadataArray != EMPTY_FLATBUFFER_VECTOR) {
+-      Model.addBuffers(builder, modelBuffers);
+-      Model.addMetadata(builder, metadataArray);
++    private static final int[] validShape = new int[] {4, 10, 10, 3};
++    private static final byte DATA_TYPE = TensorType.UINT8;
++    private static final byte CONTENT_PROPERTIES_TYPE = ContentProperties.ImageProperties;
++    private static final float VALID_SCALE = 3.3f;
++    private static final long VALID_ZERO_POINT = 2;
++    private static final float DEFAULT_SCALE = 0.0f;
++    private static final long DEFAULT_ZERO_POINT = 0;
++    private static final String MODEL_NAME = "model.tflite";
++    // Scale and zero point should both be a single value, not an array.
++    private static final float[] invalidScale = new float[] {0.0f, 1.2f};
++    private static final long[] invalidZeroPoint = new long[] {1, 2};
++    private static final String MODEL_PATH = "mobilenet_v1_1.0_224_quant.tflite";
++    // labels.txt is packed in mobilenet_v1_1.0_224_quant.tflite as an associated file.
++    private static final String VALID_LABEL_FILE_NAME = "labels.txt";
++    // invalid.txt is not packed in mobilenet_v1_1.0_224_quant.tflite.
++    private static final String INVALID_LABEL_FILE_NAME = "invalid.txt";
++    private static final int EMPTY_FLATBUFFER_VECTOR = -1;
++    private static final String TFLITE_MODEL_IDENTIFIER = "TFL3";
++    private static final String TFLITE_METADATA_IDENTIFIER = "M001";
++
++    /** General tests of MetadataExtractor. */
++    @RunWith(RobolectricTestRunner.class)
++    public static final class General extends MetadataExtractorTest {
++        @Test
++        public void hasMetadata_modelWithMetadata() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            assertThat(metadataExtractor.hasMetadata()).isTrue();
++        }
++
++        @Test
++        public void hasMetadata_modelWithoutMetadata() throws Exception {
++            // Creates a model flatbuffer without metadata.
++            ByteBuffer modelWithoutMetadata =
++                    createModelByteBuffer(/*metadataBuffer=*/null, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithoutMetadata);
++            assertThat(metadataExtractor.hasMetadata()).isFalse();
++        }
++
++        @Ignore
++        @Test
++        public void getAssociatedFile_validAssociateFile() throws Exception {
++            ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
++            MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
++            InputStream associateFileStream =
++                    mobileNetMetadataExtractor.getAssociatedFile(VALID_LABEL_FILE_NAME);
++
++            // Reads the golden file from context.
++            Context context = ApplicationProvider.getApplicationContext();
++            InputStream goldenAssociateFileStream = context.getAssets().open(VALID_LABEL_FILE_NAME);
++            assertThat(IOUtils.contentEquals(goldenAssociateFileStream, associateFileStream))
++                    .isTrue();
++        }
++
++        @Ignore
++        @Test
++        public void getAssociatedFile_invalidAssociateFile() throws Exception {
++            ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
++            MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> mobileNetMetadataExtractor.getAssociatedFile(INVALID_LABEL_FILE_NAME));
++            assertThat(exception).hasMessageThat().isEqualTo(String.format(
++                    "The file, %s, does not exist in the zip file.", INVALID_LABEL_FILE_NAME));
++        }
++
++        @Ignore
++        @Test
++        public void getAssociatedFile_nullFileName() throws Exception {
++            ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
++            MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> mobileNetMetadataExtractor.getAssociatedFile(/*fileName=*/null));
++            assertThat(exception).hasMessageThat().contains(
++                    "The file, null, does not exist in the zip file.");
++        }
++
++        @Test
++        public void getAssociatedFile_nonZipModel_throwsException() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalStateException exception = assertThrows(IllegalStateException.class,
++                    () -> metadataExtractor.getAssociatedFile(VALID_LABEL_FILE_NAME));
++            assertThat(exception).hasMessageThat().contains(
++                    "This model does not contain associated files, and is not a Zip file.");
++        }
++
++        @Test
++        public void getAssociatedFileNames_nonZipModel_throwsException() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalStateException exception = assertThrows(
++                    IllegalStateException.class, metadataExtractor::getAssociatedFileNames);
++            assertThat(exception).hasMessageThat().contains(
++                    "This model does not contain associated files, and is not a Zip file.");
++        }
++
++        @Ignore
++        @Test
++        public void getAssociatedFileNames_validFileNames() throws Exception {
++            ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
++            MetadataExtractor mobileNetMetadataExtractor = new MetadataExtractor(mobileNetBuffer);
++            Set<String> expectedSet = new HashSet<>();
++            expectedSet.add(VALID_LABEL_FILE_NAME);
++            assertThat(mobileNetMetadataExtractor.getAssociatedFileNames()).isEqualTo(expectedSet);
++        }
++
++        @Test
++        public void metadataExtractor_loadNullBuffer_throwsException() {
++            ByteBuffer nullBuffer = null;
++            NullPointerException exception = assertThrows(
++                    NullPointerException.class, () -> new MetadataExtractor(nullBuffer));
++            assertThat(exception).hasMessageThat().contains("Model flatbuffer cannot be null.");
++        }
++
++        @Test
++        public void metadataExtractor_loadRandomBuffer_throwsException() {
++            ByteBuffer randomBuffer = createRandomByteBuffer();
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> new MetadataExtractor(randomBuffer));
++            assertThat(exception).hasMessageThat().contains(
++                    "The identifier of the model is invalid. The buffer may not be a valid TFLite model"
++                    + " flatbuffer.");
++        }
++
++        @Test
++        public void metadataExtractor_loadModelWithInvalidIdentifier_throwsException() {
++            // Creates a model with an invalid identifier.
++            String invalidIdentifier = "INVI";
++            FlatBufferBuilder builder = new FlatBufferBuilder();
++            Model.startModel(builder);
++            int model = Model.endModel(builder);
++            builder.finish(model, invalidIdentifier);
++            ByteBuffer modelBuffer = builder.dataBuffer();
++
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> new MetadataExtractor(modelBuffer));
++            assertThat(exception).hasMessageThat().contains(
++                    "The identifier of the model is invalid. The buffer may not be a valid TFLite model"
++                    + " flatbuffer.");
++        }
++
++        @Test
++        public void metadataExtractor_loadMetadataWithInvalidIdentifier_throwsException() {
++            // Creates a model with metadata which contains an invalid identifier.
++            String invalidIdentifier = "INVI";
++            ByteBuffer metadata = createMetadataByteBuffer(invalidIdentifier, null);
++            ByteBuffer modelBuffer = createModelByteBuffer(metadata, DATA_TYPE);
++
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> new MetadataExtractor(modelBuffer));
++            assertThat(exception).hasMessageThat().contains(
++                    "The identifier of the metadata is invalid. The buffer may not be a valid TFLite"
++                    + " metadata flatbuffer.");
++        }
++
++        @Test
++        public void getInputTensorCount_validModelFile() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            int count = metadataExtractor.getInputTensorCount();
++            assertThat(count).isEqualTo(3);
++        }
++
++        @Test
++        public void getOutputTensorCount_validModelFile() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            int count = metadataExtractor.getOutputTensorCount();
++            assertThat(count).isEqualTo(3);
++        }
++
++        @Test
++        public void getInputTensorShape_validTensorShape() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            int[] shape = metadataExtractor.getInputTensorShape(0);
++            assertArrayEquals(validShape, shape);
++        }
++
++        @Test
++        public void getInputTensorShape_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            int[] shape = metadataExtractor.getInputTensorShape(1);
++            assertThat(shape).isEmpty();
++        }
++
++        @Test
++        public void getInputTensorType_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            byte type = metadataExtractor.getInputTensorType(1);
++            assertThat(type).isEqualTo(TensorType.FLOAT32);
++        }
++
++        @Test
++        public void getOutputTensorShape_validTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            int[] shape = metadataExtractor.getOutputTensorShape(0);
++            assertArrayEquals(validShape, shape);
++        }
++
++        @Test
++        public void getOutputTensorShape_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            int[] shape = metadataExtractor.getOutputTensorShape(1);
++            assertThat(shape).isEmpty();
++        }
++
++        @Test
++        public void getOutputTensorType_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            byte type = metadataExtractor.getOutputTensorType(1);
++            assertThat(type).isEqualTo(TensorType.FLOAT32);
++        }
++
++        @Test
++        public void getInputTensorShape_indexGreaterThanTensorNumber_throwsException()
++                throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(
++                    IllegalArgumentException.class, () -> metadataExtractor.getInputTensorShape(3));
++            assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getInputTensorShape_negtiveIndex_throwsException() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getInputTensorShape(-1));
++            assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getOutputTensorShape_indexGreaterThanTensorNumber_throwsException()
++                throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getOutputTensorShape(3));
++            assertThat(exception).hasMessageThat().contains(
++                    "The outputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getOutputTensorShape_negtiveIndex_throwsException() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getOutputTensorShape(-1));
++            assertThat(exception).hasMessageThat().contains(
++                    "The outputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getModelMetadata_modelWithMetadata() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            ModelMetadata modelMetadata = metadataExtractor.getModelMetadata();
++            assertThat(modelMetadata.name()).isEqualTo(MODEL_NAME);
++        }
++
++        @Test
++        public void getModelMetadata_modelWithoutMetadata_throwsException() throws Exception {
++            // Creates a model flatbuffer without metadata.
++            ByteBuffer modelWithoutMetadata =
++                    createModelByteBuffer(/*metadataBuffer=*/null, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithoutMetadata);
++
++            IllegalStateException exception = assertThrows(
++                    IllegalStateException.class, () -> metadataExtractor.getModelMetadata());
++            assertThat(exception).hasMessageThat().contains(
++                    "This model does not contain model metadata.");
++        }
++
++        @Test
++        public void metadataExtractor_modelWithEmptySubgraphMetadata_throwsException() {
++            // Creates a metadata FlatBuffer without empty subgraph metadata.
++            FlatBufferBuilder builder = new FlatBufferBuilder();
++            SubGraphMetadata.startSubGraphMetadata(builder);
++            int subgraph1Metadata = SubGraphMetadata.endSubGraphMetadata(builder);
++            int subgraphsMetadata = ModelMetadata.createSubgraphMetadataVector(
++                    builder, new int[] {subgraph1Metadata});
++
++            ModelMetadata.startModelMetadata(builder);
++            ModelMetadata.addSubgraphMetadata(builder, subgraphsMetadata);
++            int modelMetadata = ModelMetadata.endModelMetadata(builder);
++            builder.finish(modelMetadata, TFLITE_METADATA_IDENTIFIER);
++            ByteBuffer emptyMetadata = builder.dataBuffer();
++            ByteBuffer modelWithEmptyMetadata = createModelByteBuffer(emptyMetadata, DATA_TYPE);
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> new MetadataExtractor(modelWithEmptyMetadata));
++            assertThat(exception).hasMessageThat().isEqualTo(
++                    "The number of input tensors in the model is 3. The number of input tensors that"
++                    + " recorded in the metadata is 0. These two values does not match.");
++        }
++
++        @Test
++        public void metadataExtractor_modelWithEmptyMetadata_throwsException() {
++            // Creates a empty metadata FlatBuffer.
++            FlatBufferBuilder builder = new FlatBufferBuilder();
++            ModelMetadata.startModelMetadata(builder);
++            int modelMetadata = ModelMetadata.endModelMetadata(builder);
++            builder.finish(modelMetadata, TFLITE_METADATA_IDENTIFIER);
++
++            ByteBuffer emptyMetadata = builder.dataBuffer();
++            ByteBuffer modelWithEmptyMetadata = createModelByteBuffer(emptyMetadata, DATA_TYPE);
++
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> new MetadataExtractor(modelWithEmptyMetadata));
++            assertThat(exception).hasMessageThat().contains(
++                    "The metadata flatbuffer does not contain any subgraph metadata.");
++        }
++
++        @Test
++        public void metadataExtractor_modelWithNoMetadata_throwsException() throws Exception {
++            // Creates a model flatbuffer without metadata.
++            ByteBuffer modelWithoutMetadata =
++                    createModelByteBuffer(/*metadataBuffer=*/null, DATA_TYPE);
++
++            // It is allowed to create a model without metadata, but invoking methods that reads
++            // metadata is not allowed.
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithoutMetadata);
++
++            IllegalStateException exception = assertThrows(
++                    IllegalStateException.class, () -> metadataExtractor.getInputTensorMetadata(0));
++            assertThat(exception).hasMessageThat().contains(
++                    "This model does not contain model metadata.");
++        }
++
++        @Test
++        public void metadataExtractor_modelWithIrrelevantMetadata_throwsException()
++                throws Exception {
++            // Creates a model with irrelevant metadata.
++            FlatBufferBuilder builder = new FlatBufferBuilder();
++            SubGraph.startSubGraph(builder);
++            int subgraph = SubGraph.endSubGraph(builder);
++
++            int metadataName = builder.createString("Irrelevant metadata");
++            Metadata.startMetadata(builder);
++            Metadata.addName(builder, metadataName);
++            int metadata = Metadata.endMetadata(builder);
++            int metadataArray = Model.createMetadataVector(builder, new int[] {metadata});
++
++            // Creates Model.
++            int[] subgraphs = new int[1];
++            subgraphs[0] = subgraph;
++            int modelSubgraphs = Model.createSubgraphsVector(builder, subgraphs);
++            Model.startModel(builder);
++            Model.addSubgraphs(builder, modelSubgraphs);
++            Model.addMetadata(builder, metadataArray);
++            int model = Model.endModel(builder);
++            builder.finish(model, TFLITE_MODEL_IDENTIFIER);
++            ByteBuffer modelBuffer = builder.dataBuffer();
++
++            // It is allowed to create a model without metadata, but invoking methods that reads
++            // metadata is not allowed.
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelBuffer);
++
++            IllegalStateException exception = assertThrows(
++                    IllegalStateException.class, () -> metadataExtractor.getInputTensorMetadata(0));
++            assertThat(exception).hasMessageThat().contains(
++                    "This model does not contain model metadata.");
++        }
++
++        @Test
++        public void getInputTensorMetadata_validTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            TensorMetadata inputMetadata = metadataExtractor.getInputTensorMetadata(0);
++            assertThat(inputMetadata.content().contentPropertiesType())
++                    .isEqualTo(CONTENT_PROPERTIES_TYPE);
++        }
++
++        @Test
++        public void getInputTensorMetadata_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            TensorMetadata inputMetadata = metadataExtractor.getInputTensorMetadata(1);
++            assertThat(inputMetadata.content()).isNull();
++        }
++
++        @Test
++        public void getInputTensorMetadata_invalidTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            TensorMetadata inputMetadata = metadataExtractor.getInputTensorMetadata(2);
++            assertThat(inputMetadata.content().contentPropertiesType())
++                    .isEqualTo(CONTENT_PROPERTIES_TYPE);
++        }
++
++        @Test
++        public void getOutputTensorMetadata_validTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            TensorMetadata outputMetadata = metadataExtractor.getOutputTensorMetadata(0);
++            assertThat(outputMetadata.content().contentPropertiesType())
++                    .isEqualTo(CONTENT_PROPERTIES_TYPE);
++        }
++
++        @Test
++        public void getOutputTensorMetadata_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            TensorMetadata outputMetadata = metadataExtractor.getOutputTensorMetadata(1);
++            assertThat(outputMetadata.content()).isNull();
++        }
++
++        @Test
++        public void getOutputTensorMetadata_invalidTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            TensorMetadata outputMetadata = metadataExtractor.getOutputTensorMetadata(2);
++            assertThat(outputMetadata.content().contentPropertiesType())
++                    .isEqualTo(CONTENT_PROPERTIES_TYPE);
++        }
++
++        @Test
++        public void getInputTensorMetadata_indexGreaterThanTensorNumber_throwsException()
++                throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getInputTensorMetadata(3));
++            assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getInputTensorMetadata_negtiveIndex_throwsException() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getInputTensorMetadata(-1));
++            assertThat(exception).hasMessageThat().contains("The inputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getOutputTensorMetadata_indexGreaterThanTensorNumber_throwsException()
++                throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getOutputTensorMetadata(3));
++            assertThat(exception).hasMessageThat().contains(
++                    "The outputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getOutputTensorMetadata_negtiveIndex_throwsException() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getOutputTensorMetadata(-1));
++            assertThat(exception).hasMessageThat().contains(
++                    "The outputIndex specified is invalid.");
++        }
++
++        @Test
++        public void getInputTensorQuantizationParams_validScaleAndZeroPoint() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            QuantizationParams quantizationParams =
++                    metadataExtractor.getInputTensorQuantizationParams(0);
++            assertThat(quantizationParams.getScale()).isEqualTo(VALID_SCALE);
++            assertThat(quantizationParams.getZeroPoint()).isEqualTo(VALID_ZERO_POINT);
++        }
++
++        @Test
++        public void getInputTensorQuantizationParams_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            QuantizationParams quantizationParams =
++                    metadataExtractor.getInputTensorQuantizationParams(1);
++            // Scale and zero point are expected to be 1.0f and 0, respectively as default.
++            assertThat(quantizationParams.getScale()).isEqualTo(DEFAULT_SCALE);
++            assertThat(quantizationParams.getZeroPoint()).isEqualTo(DEFAULT_ZERO_POINT);
++        }
++
++        @Test
++        public void getInputTensorQuantizationParams_invalidScale() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getInputTensorQuantizationParams(2));
++            assertThat(exception).hasMessageThat().contains(
++                    "Input and output tensors do not support per-channel quantization.");
++        }
++
++        @Test
++        public void getOutputTensorQuantizationParams_validScaleAndZeroPoint() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            QuantizationParams quantizationParams =
++                    metadataExtractor.getOutputTensorQuantizationParams(0);
++            assertThat(quantizationParams.getScale()).isEqualTo(VALID_SCALE);
++            assertThat(quantizationParams.getZeroPoint()).isEqualTo(VALID_ZERO_POINT);
++        }
++
++        @Test
++        public void getOutputTensorQuantizationParams_emptyTensor() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            QuantizationParams quantizationParams =
++                    metadataExtractor.getOutputTensorQuantizationParams(1);
++            // Scale and zero point are expected to be 1.0f and 0, respectively as default.
++            assertThat(quantizationParams.getScale()).isEqualTo(DEFAULT_SCALE);
++            assertThat(quantizationParams.getZeroPoint()).isEqualTo(DEFAULT_ZERO_POINT);
++        }
++
++        @Test
++        public void getOutputTensorQuantizationParams_invalidScale() throws Exception {
++            // Creates a model flatbuffer with metadata.
++            ByteBuffer modelWithMetadata = createModelByteBuffer();
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                    () -> metadataExtractor.getOutputTensorQuantizationParams(2));
++            assertThat(exception).hasMessageThat().contains(
++                    "Input and output tensors do not support per-channel quantization.");
++        }
++
++        @Test
++        public void isMinimumParserVersionSatisfied_olderVersion() throws Exception {
++            // A version older than the current one. The version starts from 1.0.0, thus 0.10.0 will
++            // precede any furture versions.
++            String minVersion = "0.10";
++            // Creates a metadata using the above version.
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++
++            assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
++        }
++
++        @Test
++        public void isMinimumParserVersionSatisfied_sameVersionSamelength() throws Exception {
++            // A version the same as the current one.
++            String minVersion = MetadataParser.VERSION;
++            // Creates a metadata using the above version.
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++
++            assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
++        }
++
++        @Test
++        public void isMinimumParserVersionSatisfied_sameVersionLongerlength() throws Exception {
++            // A version the same as the current one, but with longer length.
++            String minVersion = MetadataParser.VERSION + ".0";
++            // Creates a metadata using the above version.
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++
++            assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
++        }
++
++        @Test
++        public void isMinimumParserVersionSatisfied_emptyVersion() throws Exception {
++            // An empty version, which can be generated before the first versioned release.
++            String minVersion = null;
++            // Creates a metadata using the above version.
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++
++            assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isTrue();
++        }
++
++        @Test
++        public void isMinimumParserVersionSatisfied_newerVersion() throws Exception {
++            // Creates a version newer than the current one by appending "1" to the end of the
++            // current version for testing purposes. For example, 1.0.0 becomes 1.0.01.
++            String minVersion = MetadataParser.VERSION + "1";
++            // Creates a metadata using the above version.
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++
++            assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isFalse();
++        }
++
++        @Test
++        public void isMinimumParserVersionSatisfied_newerVersionLongerLength() throws Exception {
++            // Creates a version newer than the current one by appending ".1" to the end of the
++            // current version for testing purposes. For example, 1.0.0 becomes 1.0.0.1.
++            String minVersion = MetadataParser.VERSION + ".1";
++            // Creates a metadata using the above version.
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, minVersion);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, DATA_TYPE);
++
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++
++            assertThat(metadataExtractor.isMinimumParserVersionSatisfied()).isFalse();
++        }
++    }
++
++    /** Parameterized tests for the input tensor data type. */
++    @RunWith(ParameterizedRobolectricTestRunner.class)
++    public static final class InputTensorType extends MetadataExtractorTest {
++        /** The tensor type that used to create the model buffer. */
++        @Parameter(0)
++        public byte tensorType;
++
++        /** A list of TensorType that is used in the test. */
++        @Parameters
++        public static Collection<Object[]> data() {
++            return Arrays.asList(new Object[][] {{TensorType.FLOAT32}, {TensorType.INT32},
++                    {TensorType.UINT8}, {TensorType.INT64}, {TensorType.STRING}});
++        }
++
++        @Test
++        public void getInputTensorType_validTensor() throws Exception {
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, null);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, tensorType);
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            byte type = metadataExtractor.getInputTensorType(0);
++            assertThat(type).isEqualTo(tensorType);
++        }
++
++        @Test
++        public void getOutputTensorType_validTensor() throws Exception {
++            ByteBuffer metadata = createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, null);
++            ByteBuffer modelWithMetadata = createModelByteBuffer(metadata, tensorType);
++            MetadataExtractor metadataExtractor = new MetadataExtractor(modelWithMetadata);
++            byte type = metadataExtractor.getOutputTensorType(0);
++            assertThat(type).isEqualTo(tensorType);
++        }
++    }
++
++    /**
++     * Creates an example metadata flatbuffer, which contains one subgraph with three inputs and
++     * three outputs.
++     */
++    private static ByteBuffer createMetadataByteBuffer(
++            String identifier, @Nullable String minVersionStr) {
++        FlatBufferBuilder builder = new FlatBufferBuilder();
++
++        Content.startContent(builder);
++        Content.addContentPropertiesType(builder, CONTENT_PROPERTIES_TYPE);
++        int content = Content.endContent(builder);
++
++        TensorMetadata.startTensorMetadata(builder);
++        TensorMetadata.addContent(builder, content);
++        int metadataForValidTensor = TensorMetadata.endTensorMetadata(builder);
++
++        TensorMetadata.startTensorMetadata(builder);
++        int metadataForEmptyTensor = TensorMetadata.endTensorMetadata(builder);
++
++        TensorMetadata.startTensorMetadata(builder);
++        TensorMetadata.addContent(builder, content);
++        int metadataForInvalidTensor = TensorMetadata.endTensorMetadata(builder);
++
++        int[] tensorMetadataArray = new int[] {
++                metadataForValidTensor, metadataForEmptyTensor, metadataForInvalidTensor};
++        int inputTensorMetadata =
++                SubGraphMetadata.createInputTensorMetadataVector(builder, tensorMetadataArray);
++        int outputTensorMetadata =
++                SubGraphMetadata.createOutputTensorMetadataVector(builder, tensorMetadataArray);
++
++        SubGraphMetadata.startSubGraphMetadata(builder);
++        SubGraphMetadata.addInputTensorMetadata(builder, inputTensorMetadata);
++        SubGraphMetadata.addOutputTensorMetadata(builder, outputTensorMetadata);
++        int subgraph1Metadata = SubGraphMetadata.endSubGraphMetadata(builder);
++
++        int[] subgraphMetadataArray = new int[] {subgraph1Metadata};
++        int subgraphsMetadata =
++                ModelMetadata.createSubgraphMetadataVector(builder, subgraphMetadataArray);
++
++        int modelName = builder.createString(MODEL_NAME);
++        if (minVersionStr != null) {
++            int minVersion = builder.createString(minVersionStr);
++            ModelMetadata.startModelMetadata(builder);
++            ModelMetadata.addMinParserVersion(builder, minVersion);
++        } else {
++            // If minVersionStr is null, skip generating the field in the metadata.
++            ModelMetadata.startModelMetadata(builder);
++        }
++        ModelMetadata.addName(builder, modelName);
++        ModelMetadata.addSubgraphMetadata(builder, subgraphsMetadata);
++        int modelMetadata = ModelMetadata.endModelMetadata(builder);
++
++        builder.finish(modelMetadata, identifier);
++        return builder.dataBuffer();
++    }
++
++    private static int createQuantizationParameters(
++            FlatBufferBuilder builder, float[] scale, long[] zeroPoint) {
++        int inputScale = QuantizationParameters.createScaleVector(builder, scale);
++        int inputZeroPoint = QuantizationParameters.createZeroPointVector(builder, zeroPoint);
++        QuantizationParameters.startQuantizationParameters(builder);
++        QuantizationParameters.addScale(builder, inputScale);
++        QuantizationParameters.addZeroPoint(builder, inputZeroPoint);
++        return QuantizationParameters.endQuantizationParameters(builder);
++    }
++
++    private static int createTensor(
++            FlatBufferBuilder builder, int[] inputShape, byte inputType, int inputQuantization) {
++        int inputShapeVector1 = Tensor.createShapeVector(builder, inputShape);
++        Tensor.startTensor(builder);
++        Tensor.addShape(builder, inputShapeVector1);
++        Tensor.addType(builder, inputType);
++        Tensor.addQuantization(builder, inputQuantization);
++        return Tensor.endTensor(builder);
++    }
++
++    /**
++     * Creates an example model flatbuffer, which contains one subgraph with three inputs and three
++     * output.
++     */
++    private static ByteBuffer createModelByteBuffer(ByteBuffer metadataBuffer, byte dataType) {
++        FlatBufferBuilder builder = new FlatBufferBuilder();
++
++        // Creates a valid set of quantization parameters.
++        int validQuantization = createQuantizationParameters(
++                builder, new float[] {VALID_SCALE}, new long[] {VALID_ZERO_POINT});
++
++        // Creates an invalid set of quantization parameters.
++        int inValidQuantization =
++                createQuantizationParameters(builder, invalidScale, invalidZeroPoint);
++
++        // Creates an input Tensor with valid quantization parameters.
++        int validTensor = createTensor(builder, validShape, dataType, validQuantization);
++
++        // Creates an empty input Tensor.
++        Tensor.startTensor(builder);
++        int emptyTensor = Tensor.endTensor(builder);
++
++        // Creates an input Tensor with invalid quantization parameters.
++        int invalidTensor = createTensor(builder, validShape, dataType, inValidQuantization);
++
++        // Creates the SubGraph.
++        int[] tensors = new int[6];
++        tensors[0] = validTensor;
++        tensors[1] = emptyTensor;
++        tensors[2] = invalidTensor;
++        tensors[3] = validTensor;
++        tensors[4] = emptyTensor;
++        tensors[5] = invalidTensor;
++        int subgraphTensors = SubGraph.createTensorsVector(builder, tensors);
++
++        int subgraphInputs = SubGraph.createInputsVector(builder, new int[] {0, 1, 2});
++        int subgraphOutputs = SubGraph.createOutputsVector(builder, new int[] {3, 4, 5});
++
++        SubGraph.startSubGraph(builder);
++        SubGraph.addTensors(builder, subgraphTensors);
++        SubGraph.addInputs(builder, subgraphInputs);
++        SubGraph.addOutputs(builder, subgraphOutputs);
++        int subgraph = SubGraph.endSubGraph(builder);
++
++        // Creates the Model.
++        int[] subgraphs = new int[1];
++        subgraphs[0] = subgraph;
++        int modelSubgraphs = Model.createSubgraphsVector(builder, subgraphs);
++
++        // Inserts metadataBuffer into the model if it's not null.
++        int modelBuffers = EMPTY_FLATBUFFER_VECTOR;
++        int metadataArray = EMPTY_FLATBUFFER_VECTOR;
++        if (metadataBuffer != null) {
++            int data = Buffer.createDataVector(builder, metadataBuffer);
++            Buffer.startBuffer(builder);
++            Buffer.addData(builder, data);
++            int buffer = Buffer.endBuffer(builder);
++            modelBuffers = Model.createBuffersVector(builder, new int[] {buffer});
++
++            int metadataName = builder.createString(ModelInfo.METADATA_FIELD_NAME);
++            Metadata.startMetadata(builder);
++            Metadata.addName(builder, metadataName);
++            Metadata.addBuffer(builder, 0);
++            int metadata = Metadata.endMetadata(builder);
++            metadataArray = Model.createMetadataVector(builder, new int[] {metadata});
++        }
++
++        Model.startModel(builder);
++        Model.addSubgraphs(builder, modelSubgraphs);
++        if (modelBuffers != EMPTY_FLATBUFFER_VECTOR && metadataArray != EMPTY_FLATBUFFER_VECTOR) {
++            Model.addBuffers(builder, modelBuffers);
++            Model.addMetadata(builder, metadataArray);
++        }
++        int model = Model.endModel(builder);
++        builder.finish(model, TFLITE_MODEL_IDENTIFIER);
++
++        return builder.dataBuffer();
++    }
++
++    /** Creates an example model flatbuffer with the default metadata and data type. */
++    private static ByteBuffer createModelByteBuffer() {
++        ByteBuffer metadata =
++                createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, /*minVersionStr=*/null);
++        return createModelByteBuffer(metadata, DATA_TYPE);
++    }
++
++    private static ByteBuffer loadMobileNetBuffer() throws Exception {
++        Context context = ApplicationProvider.getApplicationContext();
++        // Loads a MobileNet model flatbuffer with metadata. The MobileNet model is a zip file that
++        // contains a label file as the associated file.
++        AssetFileDescriptor fileDescriptor = context.getAssets().openFd(MODEL_PATH);
++        FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor());
++        FileChannel fileChannel = inputStream.getChannel();
++        long startOffset = fileDescriptor.getStartOffset();
++        long declaredLength = fileDescriptor.getDeclaredLength();
++        return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
++    }
++
++    private static ByteBuffer createRandomByteBuffer() {
++        byte[] buffer = new byte[20];
++        new Random().nextBytes(buffer);
++        return ByteBuffer.wrap(buffer);
+     }
+-    int model = Model.endModel(builder);
+-    builder.finish(model, TFLITE_MODEL_IDENTIFIER);
+-
+-    return builder.dataBuffer();
+-  }
+-
+-  /** Creates an example model flatbuffer with the default metadata and data type. */
+-  private static ByteBuffer createModelByteBuffer() {
+-    ByteBuffer metadata =
+-        createMetadataByteBuffer(TFLITE_METADATA_IDENTIFIER, /*minVersionStr=*/ null);
+-    return createModelByteBuffer(metadata, DATA_TYPE);
+-  }
+-
+-  private static ByteBuffer loadMobileNetBuffer() throws Exception {
+-    Context context = ApplicationProvider.getApplicationContext();
+-    // Loads a MobileNet model flatbuffer with metadata. The MobileNet model is a zip file that
+-    // contains a label file as the associated file.
+-    AssetFileDescriptor fileDescriptor = context.getAssets().openFd(MODEL_PATH);
+-    FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor());
+-    FileChannel fileChannel = inputStream.getChannel();
+-    long startOffset = fileDescriptor.getStartOffset();
+-    long declaredLength = fileDescriptor.getDeclaredLength();
+-    return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
+-  }
+-
+-  private static ByteBuffer createRandomByteBuffer() {
+-    byte[] buffer = new byte[20];
+-    new Random().nextBytes(buffer);
+-    return ByteBuffer.wrap(buffer);
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataParserTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataParserTest.java
+index a47566fec06e9..eede6750ea479 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataParserTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataParserTest.java
+@@ -17,20 +17,20 @@ package org.tensorflow.lite.support.metadata;
+ 
+ import static com.google.common.truth.Truth.assertThat;
+ 
+-import java.util.regex.Pattern;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.junit.runners.JUnit4;
+ 
++import java.util.regex.Pattern;
++
+ /** Tests of {@link MetadataParser}. */
+ @RunWith(JUnit4.class)
+ public final class MetadataParserTest {
+-
+-  @Test
+-  public void version_wellFormedAsSemanticVersion() throws Exception {
+-    // Validates that the version is well-formed (x.y.z).
+-    String pattern = "[0-9]+\\.[0-9]+\\.[0-9]+";
+-    Pattern r = Pattern.compile(pattern);
+-    assertThat(MetadataParser.VERSION).matches(r);
+-  }
++    @Test
++    public void version_wellFormedAsSemanticVersion() throws Exception {
++        // Validates that the version is well-formed (x.y.z).
++        String pattern = "[0-9]+\\.[0-9]+\\.[0-9]+";
++        Pattern r = Pattern.compile(pattern);
++        assertThat(MetadataParser.VERSION).matches(r);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java
+index 61231e902e03e..80d2ddc6fd34e 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java
+@@ -16,11 +16,20 @@ limitations under the License.
+ package org.tensorflow.lite.support.metadata;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.content.Context;
+ import android.content.res.AssetFileDescriptor;
++
+ import androidx.test.core.app.ApplicationProvider;
++
++import org.apache.commons.io.IOUtils;
++import org.junit.Ignore;
++import org.junit.Test;
++import org.junit.runner.RunWith;
++import org.robolectric.RobolectricTestRunner;
++
+ import java.io.FileInputStream;
+ import java.io.InputStream;
+ import java.nio.ByteBuffer;
+@@ -28,113 +37,102 @@ import java.nio.channels.FileChannel;
+ import java.util.HashSet;
+ import java.util.Set;
+ import java.util.zip.ZipException;
+-import org.apache.commons.io.IOUtils;
+-import org.junit.Test;
+-import org.junit.runner.RunWith;
+-import org.robolectric.RobolectricTestRunner;
+-
+-import org.junit.Ignore;
+ 
+ /** Tests of {@link ZipFile}. */
+ @RunWith(RobolectricTestRunner.class)
+ public final class ZipFileTest {
+-
+-  // The TFLite model file is a zip file.
+-  private static final String MODEL_PATH = "mobilenet_v1_1.0_224_quant.tflite";
+-  // labels.txt is packed in mobilenet_v1_1.0_224_quant.tflite as an associated file.
+-  private static final String VALID_LABEL_FILE_NAME = "labels.txt";
+-  // invalid.txt is not packed in mobilenet_v1_1.0_224_quant.tflite.
+-  private static final String INVALID_LABEL_FILE_NAME = "invalid.txt";
+-  private final Context context = ApplicationProvider.getApplicationContext();
+-
+-  @Test
+-  public void zipFile_nullChannel_throwsException() throws Exception {
+-    NullPointerException exception =
+-        assertThrows(NullPointerException.class, () -> ZipFile.createFrom(null));
+-    assertThat(exception).hasMessageThat().isEqualTo("The object reference is null.");
+-  }
+-
+-  @Test
+-  public void zipFile_invalidFileWithExtremeSmallSize_throwsException() throws Exception {
+-    // The size limit for a zip file is the End head size, ZipConstant.ENDHDR, which is 22.
+-    ByteBuffer modelBuffer = ByteBuffer.allocate(21);
+-    ByteBufferChannel modelChannel = new ByteBufferChannel(modelBuffer);
+-
+-    ZipException exception =
+-        assertThrows(ZipException.class, () -> ZipFile.createFrom(modelChannel));
+-    assertThat(exception).hasMessageThat().isEqualTo("The archive is not a ZIP archive.");
+-  }
+-
+-  @Test
+-  public void zipFile_invalidFileWithNoSignature_throwsException() throws Exception {
+-    // An invalid zip file that meets the size requirement but does not contain the zip signature.
+-    ByteBuffer modelBuffer = ByteBuffer.allocate(22);
+-    ByteBufferChannel modelChannel = new ByteBufferChannel(modelBuffer);
+-
+-    ZipException exception =
+-        assertThrows(ZipException.class, () -> ZipFile.createFrom(modelChannel));
+-    assertThat(exception).hasMessageThat().isEqualTo("The archive is not a ZIP archive.");
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void getFileNames_correctFileName() throws Exception {
+-    ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
+-    ZipFile zipFile = ZipFile.createFrom(modelChannel);
+-    Set<String> expectedSet = new HashSet<>();
+-    expectedSet.add(VALID_LABEL_FILE_NAME);
+-    assertThat(zipFile.getFileNames()).isEqualTo(expectedSet);
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void getRawInputStream_existentFile() throws Exception {
+-    ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
+-    ZipFile zipFile = ZipFile.createFrom(modelChannel);
+-    InputStream fileStream = zipFile.getRawInputStream(VALID_LABEL_FILE_NAME);
+-
+-    // Reads the golden file from context.
+-    InputStream goldenFileStream = context.getAssets().open(VALID_LABEL_FILE_NAME);
+-    assertThat(IOUtils.contentEquals(goldenFileStream, fileStream)).isTrue();
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void getRawInputStream_nonExistentFile() throws Exception {
+-    ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
+-    ZipFile zipFile = ZipFile.createFrom(modelChannel);
+-
+-    IllegalArgumentException exception =
+-        assertThrows(
+-            IllegalArgumentException.class,
+-            () -> zipFile.getRawInputStream(INVALID_LABEL_FILE_NAME));
+-    assertThat(exception)
+-        .hasMessageThat()
+-        .isEqualTo(
+-            String.format(
++    // The TFLite model file is a zip file.
++    private static final String MODEL_PATH = "mobilenet_v1_1.0_224_quant.tflite";
++    // labels.txt is packed in mobilenet_v1_1.0_224_quant.tflite as an associated file.
++    private static final String VALID_LABEL_FILE_NAME = "labels.txt";
++    // invalid.txt is not packed in mobilenet_v1_1.0_224_quant.tflite.
++    private static final String INVALID_LABEL_FILE_NAME = "invalid.txt";
++    private final Context context = ApplicationProvider.getApplicationContext();
++
++    @Test
++    public void zipFile_nullChannel_throwsException() throws Exception {
++        NullPointerException exception =
++                assertThrows(NullPointerException.class, () -> ZipFile.createFrom(null));
++        assertThat(exception).hasMessageThat().isEqualTo("The object reference is null.");
++    }
++
++    @Test
++    public void zipFile_invalidFileWithExtremeSmallSize_throwsException() throws Exception {
++        // The size limit for a zip file is the End head size, ZipConstant.ENDHDR, which is 22.
++        ByteBuffer modelBuffer = ByteBuffer.allocate(21);
++        ByteBufferChannel modelChannel = new ByteBufferChannel(modelBuffer);
++
++        ZipException exception =
++                assertThrows(ZipException.class, () -> ZipFile.createFrom(modelChannel));
++        assertThat(exception).hasMessageThat().isEqualTo("The archive is not a ZIP archive.");
++    }
++
++    @Test
++    public void zipFile_invalidFileWithNoSignature_throwsException() throws Exception {
++        // An invalid zip file that meets the size requirement but does not contain the zip
++        // signature.
++        ByteBuffer modelBuffer = ByteBuffer.allocate(22);
++        ByteBufferChannel modelChannel = new ByteBufferChannel(modelBuffer);
++
++        ZipException exception =
++                assertThrows(ZipException.class, () -> ZipFile.createFrom(modelChannel));
++        assertThat(exception).hasMessageThat().isEqualTo("The archive is not a ZIP archive.");
++    }
++
++    @Ignore
++    @Test
++    public void getFileNames_correctFileName() throws Exception {
++        ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
++        ZipFile zipFile = ZipFile.createFrom(modelChannel);
++        Set<String> expectedSet = new HashSet<>();
++        expectedSet.add(VALID_LABEL_FILE_NAME);
++        assertThat(zipFile.getFileNames()).isEqualTo(expectedSet);
++    }
++
++    @Ignore
++    @Test
++    public void getRawInputStream_existentFile() throws Exception {
++        ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
++        ZipFile zipFile = ZipFile.createFrom(modelChannel);
++        InputStream fileStream = zipFile.getRawInputStream(VALID_LABEL_FILE_NAME);
++
++        // Reads the golden file from context.
++        InputStream goldenFileStream = context.getAssets().open(VALID_LABEL_FILE_NAME);
++        assertThat(IOUtils.contentEquals(goldenFileStream, fileStream)).isTrue();
++    }
++
++    @Ignore
++    @Test
++    public void getRawInputStream_nonExistentFile() throws Exception {
++        ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
++        ZipFile zipFile = ZipFile.createFrom(modelChannel);
++
++        IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
++                () -> zipFile.getRawInputStream(INVALID_LABEL_FILE_NAME));
++        assertThat(exception).hasMessageThat().isEqualTo(String.format(
+                 "The file, %s, does not exist in the zip file.", INVALID_LABEL_FILE_NAME));
+-  }
+-
+-  @Ignore
+-  @Test
+-  public void close_validStatus() throws Exception {
+-    ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
+-    ZipFile zipFile = ZipFile.createFrom(modelChannel);
+-    // Should do nothing (including not throwing an exception).
+-    zipFile.close();
+-  }
+-
+-  private static ByteBufferChannel loadModel(String modelPath) throws Exception {
+-    // Creates a ZipFile with a TFLite model flatbuffer with metadata. The MobileNet
+-    // model is a zip file that contains a label file as the associated file.
+-    Context context = ApplicationProvider.getApplicationContext();
+-    AssetFileDescriptor fileDescriptor = context.getAssets().openFd(modelPath);
+-    FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor());
+-    FileChannel fileChannel = inputStream.getChannel();
+-    long startOffset = fileDescriptor.getStartOffset();
+-    long declaredLength = fileDescriptor.getDeclaredLength();
+-    ByteBuffer modelBuffer =
+-        fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
+-    return new ByteBufferChannel(modelBuffer);
+-  }
++    }
++
++    @Ignore
++    @Test
++    public void close_validStatus() throws Exception {
++        ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
++        ZipFile zipFile = ZipFile.createFrom(modelChannel);
++        // Should do nothing (including not throwing an exception).
++        zipFile.close();
++    }
++
++    private static ByteBufferChannel loadModel(String modelPath) throws Exception {
++        // Creates a ZipFile with a TFLite model flatbuffer with metadata. The MobileNet
++        // model is a zip file that contains a label file as the associated file.
++        Context context = ApplicationProvider.getApplicationContext();
++        AssetFileDescriptor fileDescriptor = context.getAssets().openFd(modelPath);
++        FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor());
++        FileChannel fileChannel = inputStream.getChannel();
++        long startOffset = fileDescriptor.getStartOffset();
++        long declaredLength = fileDescriptor.getDeclaredLength();
++        ByteBuffer modelBuffer =
++                fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
++        return new ByteBufferChannel(modelBuffer);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h
+index 110186bb63a1b..0c494915e7357 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h
+@@ -19,7 +19,8 @@
+ NS_ASSUME_NONNULL_BEGIN
+ 
+ /** Types of image sources. */
+-typedef NSInteger GMLImageSourceType NS_TYPED_ENUM NS_SWIFT_NAME(MLImageSourceType);
++typedef NSInteger GMLImageSourceType NS_TYPED_ENUM
++    NS_SWIFT_NAME(MLImageSourceType);
+ /** Image source is a `UIImage`. */
+ static const GMLImageSourceType GMLImageSourceTypeImage = 0;
+ /** Image source is a `CVPixelBuffer`. */
+@@ -38,8 +39,9 @@ NS_SWIFT_NAME(MLImage)
+ @property(nonatomic, readonly) CGFloat height;
+ 
+ /**
+- * The display orientation of the image. If `imageSourceType` is `.image`, the default value is
+- * `image.imageOrientation`; otherwise the default value is `.up`.
++ * The display orientation of the image. If `imageSourceType` is `.image`, the
++ * default value is `image.imageOrientation`; otherwise the default value is
++ * `.up`.
+  */
+ @property(nonatomic) UIImageOrientation orientation;
+ 
+@@ -47,30 +49,34 @@ NS_SWIFT_NAME(MLImage)
+ @property(nonatomic, readonly) GMLImageSourceType imageSourceType;
+ 
+ /** The source image. `nil` if `imageSourceType` is not `.image`. */
+-@property(nonatomic, readonly, nullable) UIImage *image;
++@property(nonatomic, readonly, nullable) UIImage* image;
+ 
+-/** The source pixel buffer. `nil` if `imageSourceType` is not `.pixelBuffer`. */
++/** The source pixel buffer. `nil` if `imageSourceType` is not `.pixelBuffer`.
++ */
+ @property(nonatomic, readonly, nullable) CVPixelBufferRef pixelBuffer;
+ 
+-/** The source sample buffer. `nil` if `imageSourceType` is not `.sampleBuffer`. */
++/** The source sample buffer. `nil` if `imageSourceType` is not `.sampleBuffer`.
++ */
+ @property(nonatomic, readonly, nullable) CMSampleBufferRef sampleBuffer;
+ 
+ /**
+  * Initializes an `MLImage` object with the given image.
+  *
+- * @param image The image to use as the source. Its `CGImage` property must not be `NULL`.
+- * @return A new `MLImage` instance with the given image as the source. `nil` if the given `image`
+- *     is `nil` or invalid.
++ * @param image The image to use as the source. Its `CGImage` property must not
++ * be `NULL`.
++ * @return A new `MLImage` instance with the given image as the source. `nil` if
++ * the given `image` is `nil` or invalid.
+  */
+-- (nullable instancetype)initWithImage:(UIImage *)image NS_DESIGNATED_INITIALIZER;
++- (nullable instancetype)initWithImage:(UIImage*)image
++    NS_DESIGNATED_INITIALIZER;
+ 
+ /**
+  * Initializes an `MLImage` object with the given pixel buffer.
+  *
+- * @param pixelBuffer The pixel buffer to use as the source. It will be retained by the new
+- *     `MLImage` instance for the duration of its lifecycle.
+- * @return A new `MLImage` instance with the given pixel buffer as the source. `nil` if the given
+- *     pixel buffer is `nil` or invalid.
++ * @param pixelBuffer The pixel buffer to use as the source. It will be retained
++ * by the new `MLImage` instance for the duration of its lifecycle.
++ * @return A new `MLImage` instance with the given pixel buffer as the source.
++ * `nil` if the given pixel buffer is `nil` or invalid.
+  */
+ - (nullable instancetype)initWithPixelBuffer:(CVPixelBufferRef)pixelBuffer
+     NS_DESIGNATED_INITIALIZER;
+@@ -78,12 +84,13 @@ NS_SWIFT_NAME(MLImage)
+ /**
+  * Initializes an `MLImage` object with the given sample buffer.
+  *
+- * @param sampleBuffer The sample buffer to use as the source. It will be retained by the new
+- *     `MLImage` instance for the duration of its lifecycle. The sample buffer must be based on a
+- *     pixel buffer (not compressed data). In practice, it should be the video output of the camera
+- *     on an iOS device, not other arbitrary types of `CMSampleBuffer`s.
+- * @return A new `MLImage` instance with the given sample buffer as the source. `nil` if the given
+- *     sample buffer is `nil` or invalid.
++ * @param sampleBuffer The sample buffer to use as the source. It will be
++ * retained by the new `MLImage` instance for the duration of its lifecycle. The
++ * sample buffer must be based on a pixel buffer (not compressed data). In
++ * practice, it should be the video output of the camera on an iOS device, not
++ * other arbitrary types of `CMSampleBuffer`s.
++ * @return A new `MLImage` instance with the given sample buffer as the source.
++ * `nil` if the given sample buffer is `nil` or invalid.
+  */
+ - (nullable instancetype)initWithSampleBuffer:(CMSampleBufferRef)sampleBuffer
+     NS_DESIGNATED_INITIALIZER;
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m
+index 094d4e01377d2..38ca74268acc1 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m
+@@ -20,7 +20,7 @@ NS_ASSUME_NONNULL_BEGIN
+ 
+ #pragma mark - Public
+ 
+-- (nullable instancetype)initWithImage:(UIImage *)image {
++- (nullable instancetype)initWithImage:(UIImage*)image {
+   if (image.CGImage == NULL) {
+     return nil;
+   }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m
+index 59205747e416a..8abee1ab2f171 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m
+@@ -22,8 +22,8 @@
+ 
+ NS_ASSUME_NONNULL_BEGIN
+ 
+-static NSString *const kTestImageName = @"grace_hopper";
+-static NSString *const kTestImageType = @"jpg";
++static NSString* const kTestImageName = @"grace_hopper";
++static NSString* const kTestImageType = @"jpg";
+ static CGFloat kTestImageWidthInPixels = 517.0f;
+ static CGFloat kTestImageHeightInPixels = 606.0f;
+ 
+@@ -31,7 +31,7 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+ @interface GMLImageTests : XCTestCase
+ 
+ /** Test image. */
+-@property(nonatomic, nullable) UIImage *image;
++@property(nonatomic, nullable) UIImage* image;
+ 
+ @end
+ 
+@@ -41,8 +41,9 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+ 
+ - (void)setUp {
+   [super setUp];
+-  NSString *imageName = [[NSBundle bundleForClass:[self class]] pathForResource:kTestImageName
+-                                                                         ofType:kTestImageType];
++  NSString* imageName =
++      [[NSBundle bundleForClass:[self class]] pathForResource:kTestImageName
++                                                       ofType:kTestImageType];
+   self.image = [[UIImage alloc] initWithContentsOfFile:imageName];
+ }
+ 
+@@ -52,53 +53,59 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+ }
+ 
+ - (void)testInitWithImage {
+-  GMLImage *mlImage = [[GMLImage alloc] initWithImage:self.image];
++  GMLImage* mlImage = [[GMLImage alloc] initWithImage:self.image];
+   XCTAssertNotNil(mlImage);
+   XCTAssertEqual(mlImage.imageSourceType, GMLImageSourceTypeImage);
+   XCTAssertEqual(mlImage.orientation, self.image.imageOrientation);
+   mlImage.orientation = UIImageOrientationDown;
+   XCTAssertEqual(mlImage.orientation, UIImageOrientationDown);
+-  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels, FLT_EPSILON);
+-  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels, FLT_EPSILON);
++  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels,
++                             FLT_EPSILON);
++  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels,
++                             FLT_EPSILON);
+ }
+ 
+ - (void)testInitWithImage_nilImage {
+-  GMLImage *mlImage = [[GMLImage alloc] initWithImage:nil];
++  GMLImage* mlImage = [[GMLImage alloc] initWithImage:nil];
+   XCTAssertNil(mlImage);
+ }
+ 
+ - (void)testInitWithSampleBuffer {
+   CMSampleBufferRef sampleBuffer = [self sampleBuffer];
+-  GMLImage *mlImage = [[GMLImage alloc] initWithSampleBuffer:sampleBuffer];
++  GMLImage* mlImage = [[GMLImage alloc] initWithSampleBuffer:sampleBuffer];
+   XCTAssertNotNil(mlImage);
+   XCTAssertEqual(mlImage.imageSourceType, GMLImageSourceTypeSampleBuffer);
+   XCTAssertEqual(mlImage.orientation, UIImageOrientationUp);
+   mlImage.orientation = UIImageOrientationDown;
+   XCTAssertEqual(mlImage.orientation, UIImageOrientationDown);
+-  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels, FLT_EPSILON);
+-  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels, FLT_EPSILON);
++  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels,
++                             FLT_EPSILON);
++  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels,
++                             FLT_EPSILON);
+ }
+ 
+ - (void)testInitWithSampleBuffer_nilImage {
+-  GMLImage *mlImage = [[GMLImage alloc] initWithSampleBuffer:nil];
++  GMLImage* mlImage = [[GMLImage alloc] initWithSampleBuffer:nil];
+   XCTAssertNil(mlImage);
+ }
+ 
+ - (void)testInitWithPixelBuffer {
+   CMSampleBufferRef sampleBuffer = [self sampleBuffer];
+   CVPixelBufferRef pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer);
+-  GMLImage *mlImage = [[GMLImage alloc] initWithPixelBuffer:pixelBuffer];
++  GMLImage* mlImage = [[GMLImage alloc] initWithPixelBuffer:pixelBuffer];
+   XCTAssertNotNil(mlImage);
+   XCTAssertEqual(mlImage.imageSourceType, GMLImageSourceTypePixelBuffer);
+   XCTAssertEqual(mlImage.orientation, UIImageOrientationUp);
+   mlImage.orientation = UIImageOrientationDown;
+   XCTAssertEqual(mlImage.orientation, UIImageOrientationDown);
+-  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels, FLT_EPSILON);
+-  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels, FLT_EPSILON);
++  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels,
++                             FLT_EPSILON);
++  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels,
++                             FLT_EPSILON);
+ }
+ 
+ - (void)testInitWithPixelBuffer_nilImage {
+-  GMLImage *mlImage = [[GMLImage alloc] initWithPixelBuffer:nil];
++  GMLImage* mlImage = [[GMLImage alloc] initWithPixelBuffer:nil];
+   XCTAssertNil(mlImage);
+ }
+ 
+@@ -117,17 +124,18 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+   size_t bpr = CGImageGetBytesPerRow(CGImage);
+ 
+   CGDataProviderRef provider = CGImageGetDataProvider(CGImage);
+-  NSData *imageRGBAData = (id)CFBridgingRelease(CGDataProviderCopyData(provider));
++  NSData* imageRGBAData =
++      (id)CFBridgingRelease(CGDataProviderCopyData(provider));
+   const uint8_t order[4] = {2, 1, 0, 3};
+ 
+-  NSData *imageBGRAData = nil;
+-  unsigned char *bgraPixel = (unsigned char *)malloc([imageRGBAData length]);
++  NSData* imageBGRAData = nil;
++  unsigned char* bgraPixel = (unsigned char*)malloc([imageRGBAData length]);
+   if (bgraPixel) {
+     vImage_Buffer src;
+     src.height = height;
+     src.width = width;
+     src.rowBytes = bpr;
+-    src.data = (void *)[imageRGBAData bytes];
++    src.data = (void*)[imageRGBAData bytes];
+ 
+     vImage_Buffer dest;
+     dest.height = height;
+@@ -136,11 +144,13 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+     dest.data = bgraPixel;
+ 
+     // Specify ordering changes in map.
+-    vImage_Error error = vImagePermuteChannels_ARGB8888(&src, &dest, order, kvImageNoFlags);
++    vImage_Error error =
++        vImagePermuteChannels_ARGB8888(&src, &dest, order, kvImageNoFlags);
+ 
+     // Package the result.
+     if (error == kvImageNoError) {
+-      imageBGRAData = [NSData dataWithBytes:bgraPixel length:[imageRGBAData length]];
++      imageBGRAData = [NSData dataWithBytes:bgraPixel
++                                     length:[imageRGBAData length]];
+     }
+ 
+     // Memory cleanup.
+@@ -152,14 +162,15 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+   }
+ 
+   // Write data to `CMSampleBuffer`.
+-  NSDictionary *options = @{
+-    (__bridge NSString *)kCVPixelBufferCGImageCompatibilityKey : @(YES),
+-    (__bridge NSString *)kCVPixelBufferCGBitmapContextCompatibilityKey : @(YES)
++  NSDictionary* options = @{
++    (__bridge NSString*)kCVPixelBufferCGImageCompatibilityKey : @(YES),
++    (__bridge NSString*)kCVPixelBufferCGBitmapContextCompatibilityKey : @(YES)
+   };
+   CVPixelBufferRef pixelBuffer;
+   CVReturn status = CVPixelBufferCreateWithBytes(
+-      kCFAllocatorDefault, width, height, kCVPixelFormatType_32BGRA, (void *)[imageBGRAData bytes],
+-      bpr, NULL, nil, (__bridge CFDictionaryRef)options, &pixelBuffer);
++      kCFAllocatorDefault, width, height, kCVPixelFormatType_32BGRA,
++      (void*)[imageBGRAData bytes], bpr, NULL, nil,
++      (__bridge CFDictionaryRef)options, &pixelBuffer);
+ 
+   if (status != kCVReturnSuccess) {
+     XCTFail(@"Failed to create pixel buffer.");
+@@ -167,10 +178,12 @@ static CGFloat kTestImageHeightInPixels = 606.0f;
+ 
+   CVPixelBufferLockBaseAddress(pixelBuffer, 0);
+   CMVideoFormatDescriptionRef videoInfo = NULL;
+-  CMVideoFormatDescriptionCreateForImageBuffer(kCFAllocatorDefault, pixelBuffer, &videoInfo);
++  CMVideoFormatDescriptionCreateForImageBuffer(kCFAllocatorDefault, pixelBuffer,
++                                               &videoInfo);
+ 
+   CMSampleBufferRef buffer;
+-  CMSampleBufferCreateForImageBuffer(kCFAllocatorDefault, pixelBuffer, true, NULL, NULL, videoInfo,
++  CMSampleBufferCreateForImageBuffer(kCFAllocatorDefault, pixelBuffer, true,
++                                     NULL, NULL, videoInfo,
+                                      &kCMTimingInfoInvalid, &buffer);
+ 
+   CVPixelBufferUnlockBaseAddress(pixelBuffer, 0);
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java
+index a32fc24749e0c..59116a72a0533 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java
+@@ -24,28 +24,27 @@ import android.graphics.Bitmap;
+  * {@link IllegalArgumentException} will be thrown.
+  */
+ public final class BitmapExtractor {
+-
+-  /**
+-   * Extracts a {@link android.graphics.Bitmap} from an {@link MlImage}.
+-   *
+-   * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+-   *
+-   * @param image the image to extract {@link android.graphics.Bitmap} from.
+-   * @return the {@link android.graphics.Bitmap} stored in {@link MlImage}
+-   * @throws IllegalArgumentException when the extraction requires unsupported format or data type
+-   *     conversions.
+-   */
+-  public static Bitmap extract(MlImage image) {
+-    ImageContainer imageContainer = image.getContainer(MlImage.STORAGE_TYPE_BITMAP);
+-    if (imageContainer != null) {
+-      return ((BitmapImageContainer) imageContainer).getBitmap();
+-    } else {
+-      // TODO(b/180504869): Support ByteBuffer -> Bitmap conversion.
+-      throw new IllegalArgumentException(
+-          "Extracting Bitmap from an MlImage created by objects other than Bitmap is not"
+-              + " supported");
++    /**
++     * Extracts a {@link android.graphics.Bitmap} from an {@link MlImage}.
++     *
++     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
++     *
++     * @param image the image to extract {@link android.graphics.Bitmap} from.
++     * @return the {@link android.graphics.Bitmap} stored in {@link MlImage}
++     * @throws IllegalArgumentException when the extraction requires unsupported format or data type
++     *     conversions.
++     */
++    public static Bitmap extract(MlImage image) {
++        ImageContainer imageContainer = image.getContainer(MlImage.STORAGE_TYPE_BITMAP);
++        if (imageContainer != null) {
++            return ((BitmapImageContainer) imageContainer).getBitmap();
++        } else {
++            // TODO(b/180504869): Support ByteBuffer -> Bitmap conversion.
++            throw new IllegalArgumentException(
++                    "Extracting Bitmap from an MlImage created by objects other than Bitmap is not"
++                    + " supported");
++        }
+     }
+-  }
+ 
+-  private BitmapExtractor() {}
++    private BitmapExtractor() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java
+index 77e63f0351449..b1b02f8e369ec 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java
+@@ -16,44 +16,44 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import android.graphics.Bitmap;
++
+ import com.google.android.odml.image.MlImage.ImageFormat;
+ 
+ class BitmapImageContainer implements ImageContainer {
++    private final Bitmap bitmap;
++    private final ImageProperties properties;
++
++    public BitmapImageContainer(Bitmap bitmap) {
++        this.bitmap = bitmap;
++        this.properties = ImageProperties.builder()
++                                  .setImageFormat(convertFormatCode(bitmap.getConfig()))
++                                  .setStorageType(MlImage.STORAGE_TYPE_BITMAP)
++                                  .build();
++    }
++
++    public Bitmap getBitmap() {
++        return bitmap;
++    }
++
++    @Override
++    public ImageProperties getImageProperties() {
++        return properties;
++    }
++
++    @Override
++    public void close() {
++        bitmap.recycle();
++    }
+ 
+-  private final Bitmap bitmap;
+-  private final ImageProperties properties;
+-
+-  public BitmapImageContainer(Bitmap bitmap) {
+-    this.bitmap = bitmap;
+-    this.properties = ImageProperties.builder()
+-        .setImageFormat(convertFormatCode(bitmap.getConfig()))
+-        .setStorageType(MlImage.STORAGE_TYPE_BITMAP)
+-        .build();
+-  }
+-
+-  public Bitmap getBitmap() {
+-    return bitmap;
+-  }
+-
+-  @Override
+-  public ImageProperties getImageProperties() {
+-    return properties;
+-  }
+-
+-  @Override
+-  public void close() {
+-    bitmap.recycle();
+-  }
+-
+-  @ImageFormat
+-  static int convertFormatCode(Bitmap.Config config) {
+-    switch (config) {
+-      case ALPHA_8:
+-        return MlImage.IMAGE_FORMAT_ALPHA;
+-      case ARGB_8888:
+-        return MlImage.IMAGE_FORMAT_RGBA;
+-      default:
+-        return MlImage.IMAGE_FORMAT_UNKNOWN;
++    @ImageFormat
++    static int convertFormatCode(Bitmap.Config config) {
++        switch (config) {
++            case ALPHA_8:
++                return MlImage.IMAGE_FORMAT_ALPHA;
++            case ARGB_8888:
++                return MlImage.IMAGE_FORMAT_RGBA;
++            default:
++                return MlImage.IMAGE_FORMAT_UNKNOWN;
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java
+index fe9c35a8a6ede..6c4552bfdac3a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java
+@@ -20,6 +20,7 @@ import android.graphics.Bitmap;
+ import android.graphics.Rect;
+ import android.net.Uri;
+ import android.provider.MediaStore;
++
+ import java.io.IOException;
+ 
+ /**
+@@ -32,82 +33,76 @@ import java.io.IOException;
+  * <p>Use {@link BitmapExtractor} to get {@link android.graphics.Bitmap} you passed in.
+  */
+ public class BitmapMlImageBuilder {
++    // Mandatory fields.
++    private final Bitmap bitmap;
+ 
+-  // Mandatory fields.
+-  private final Bitmap bitmap;
+-
+-  // Optional fields.
+-  private int rotation;
+-  private Rect roi;
+-  private long timestamp;
++    // Optional fields.
++    private int rotation;
++    private Rect roi;
++    private long timestamp;
+ 
+-  /**
+-   * Creates the builder with a mandatory {@link android.graphics.Bitmap}.
+-   *
+-   * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the values
+-   * will be set with default:
+-   *
+-   * <ul>
+-   *   <li>rotation: 0
+-   * </ul>
+-   *
+-   * @param bitmap image data object.
+-   */
+-  public BitmapMlImageBuilder(Bitmap bitmap) {
+-    this.bitmap = bitmap;
+-    rotation = 0;
+-    roi = new Rect(0, 0, bitmap.getWidth(), bitmap.getHeight());
+-    timestamp = 0;
+-  }
++    /**
++     * Creates the builder with a mandatory {@link android.graphics.Bitmap}.
++     *
++     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
++     * values will be set with default:
++     *
++     * <ul>
++     *   <li>rotation: 0
++     * </ul>
++     *
++     * @param bitmap image data object.
++     */
++    public BitmapMlImageBuilder(Bitmap bitmap) {
++        this.bitmap = bitmap;
++        rotation = 0;
++        roi = new Rect(0, 0, bitmap.getWidth(), bitmap.getHeight());
++        timestamp = 0;
++    }
+ 
+-  /**
+-   * Creates the builder to build {@link MlImage} from a file.
+-   *
+-   * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the values
+-   * will be set with default:
+-   *
+-   * <ul>
+-   *   <li>rotation: 0
+-   * </ul>
+-   *
+-   * @param context the application context.
+-   * @param uri the path to the resource file.
+-   */
+-  public BitmapMlImageBuilder(Context context, Uri uri) throws IOException {
+-    this(MediaStore.Images.Media.getBitmap(context.getContentResolver(), uri));
+-  }
++    /**
++     * Creates the builder to build {@link MlImage} from a file.
++     *
++     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
++     * values will be set with default:
++     *
++     * <ul>
++     *   <li>rotation: 0
++     * </ul>
++     *
++     * @param context the application context.
++     * @param uri the path to the resource file.
++     */
++    public BitmapMlImageBuilder(Context context, Uri uri) throws IOException {
++        this(MediaStore.Images.Media.getBitmap(context.getContentResolver(), uri));
++    }
+ 
+-  /**
+-   * Sets value for {@link MlImage#getRotation()}.
+-   *
+-   * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
+-   */
+-  public BitmapMlImageBuilder setRotation(int rotation) {
+-    MlImage.validateRotation(rotation);
+-    this.rotation = rotation;
+-    return this;
+-  }
++    /**
++     * Sets value for {@link MlImage#getRotation()}.
++     *
++     * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
++     */
++    public BitmapMlImageBuilder setRotation(int rotation) {
++        MlImage.validateRotation(rotation);
++        this.rotation = rotation;
++        return this;
++    }
+ 
+-  /** Sets value for {@link MlImage#getRoi()}. */
+-  BitmapMlImageBuilder setRoi(Rect roi) {
+-    this.roi = roi;
+-    return this;
+-  }
++    /** Sets value for {@link MlImage#getRoi()}. */
++    BitmapMlImageBuilder setRoi(Rect roi) {
++        this.roi = roi;
++        return this;
++    }
+ 
+-  /** Sets value for {@link MlImage#getTimestamp()}. */
+-  BitmapMlImageBuilder setTimestamp(long timestamp) {
+-    this.timestamp = timestamp;
+-    return this;
+-  }
++    /** Sets value for {@link MlImage#getTimestamp()}. */
++    BitmapMlImageBuilder setTimestamp(long timestamp) {
++        this.timestamp = timestamp;
++        return this;
++    }
+ 
+-  /** Builds an {@link MlImage} instance. */
+-  public MlImage build() {
+-    return new MlImage(
+-        new BitmapImageContainer(bitmap),
+-        rotation,
+-        roi,
+-        timestamp,
+-        bitmap.getWidth(),
+-        bitmap.getHeight());
+-  }
++    /** Builds an {@link MlImage} instance. */
++    public MlImage build() {
++        return new MlImage(new BitmapImageContainer(bitmap), rotation, roi, timestamp,
++                bitmap.getWidth(), bitmap.getHeight());
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java
+index 7b86be6d1b533..d5861c8ca94ac 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java
+@@ -19,8 +19,10 @@ import android.graphics.Bitmap;
+ import android.graphics.Bitmap.Config;
+ import android.os.Build.VERSION;
+ import android.os.Build.VERSION_CODES;
++
+ import com.google.android.odml.image.MlImage.ImageFormat;
+ import com.google.auto.value.AutoValue;
++
+ import java.nio.ByteBuffer;
+ import java.nio.ByteOrder;
+ import java.util.Locale;
+@@ -32,229 +34,234 @@ import java.util.Locale;
+  * otherwise {@link IllegalArgumentException} will be thrown.
+  */
+ public class ByteBufferExtractor {
+-
+-  /**
+-   * Extracts a {@link ByteBuffer} from an {@link MlImage}.
+-   *
+-   * <p>The returned {@link ByteBuffer} is a read-only view, with the first available {@link
+-   * ImageProperties} whose storage type is {@code MlImage.STORAGE_TYPE_BYTEBUFFER}.
+-   *
+-   * @see MlImage#getContainedImageProperties()
+-   * @return A read-only {@link ByteBuffer}.
+-   * @throws IllegalArgumentException when the image doesn't contain a {@link ByteBuffer} storage.
+-   */
+-  public static ByteBuffer extract(MlImage image) {
+-    ImageContainer container = image.getContainer();
+-    switch (container.getImageProperties().getStorageType()) {
+-      case MlImage.STORAGE_TYPE_BYTEBUFFER:
+-        ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container;
+-        return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer();
+-      default:
+-        throw new IllegalArgumentException(
+-            "Extract ByteBuffer from an MlImage created by objects other than Bytebuffer is not"
+-                + " supported");
+-    }
+-  }
+-
+-  /**
+-   * Extracts a readonly {@link ByteBuffer} in given {@code targetFormat} from an {@link MlImage}.
+-   *
+-   * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+-   *
+-   * <p>Format conversion spec:
+-   *
+-   * <ul>
+-   *   <li>When extracting RGB images to RGBA format, A channel will always set to 255.
+-   *   <li>When extracting RGBA images to RGB format, A channel will be dropped.
+-   * </ul>
+-   *
+-   * @param image the image to extract buffer from.
+-   * @param targetFormat the image format of the result bytebuffer.
+-   * @return the readonly {@link ByteBuffer} stored in {@link MlImage}
+-   * @throws IllegalArgumentException when the extraction requires unsupported format or data type
+-   *     conversions.
+-   */
+-  static ByteBuffer extract(MlImage image, @ImageFormat int targetFormat) {
+-    ImageContainer container;
+-    ImageProperties byteBufferProperties =
+-        ImageProperties.builder()
+-            .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
+-            .setImageFormat(targetFormat)
+-            .build();
+-    if ((container = image.getContainer(byteBufferProperties)) != null) {
+-      ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container;
+-      return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer();
+-    } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER)) != null) {
+-      ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container;
+-      @ImageFormat int sourceFormat = byteBufferImageContainer.getImageFormat();
+-      return convertByteBuffer(byteBufferImageContainer.getByteBuffer(), sourceFormat, targetFormat)
+-          .asReadOnlyBuffer();
+-    } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP)) != null) {
+-      BitmapImageContainer bitmapImageContainer = (BitmapImageContainer) container;
+-      ByteBuffer byteBuffer =
+-          extractByteBufferFromBitmap(bitmapImageContainer.getBitmap(), targetFormat)
+-              .asReadOnlyBuffer();
+-      image.addContainer(new ByteBufferImageContainer(byteBuffer, targetFormat));
+-      return byteBuffer;
+-    } else {
+-      throw new IllegalArgumentException(
+-          "Extracting ByteBuffer from an MlImage created by objects other than Bitmap or"
+-              + " Bytebuffer is not supported");
+-    }
+-  }
+-
+-  /** A wrapper for a {@link ByteBuffer} and its {@link ImageFormat}. */
+-  @AutoValue
+-  abstract static class Result {
+     /**
+-     * Gets the {@link ByteBuffer} in the result of {@link ByteBufferExtractor#extract(MlImage)}.
++     * Extracts a {@link ByteBuffer} from an {@link MlImage}.
++     *
++     * <p>The returned {@link ByteBuffer} is a read-only view, with the first available {@link
++     * ImageProperties} whose storage type is {@code MlImage.STORAGE_TYPE_BYTEBUFFER}.
++     *
++     * @see MlImage#getContainedImageProperties()
++     * @return A read-only {@link ByteBuffer}.
++     * @throws IllegalArgumentException when the image doesn't contain a {@link ByteBuffer} storage.
+      */
+-    public abstract ByteBuffer buffer();
++    public static ByteBuffer extract(MlImage image) {
++        ImageContainer container = image.getContainer();
++        switch (container.getImageProperties().getStorageType()) {
++            case MlImage.STORAGE_TYPE_BYTEBUFFER:
++                ByteBufferImageContainer byteBufferImageContainer =
++                        (ByteBufferImageContainer) container;
++                return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer();
++            default:
++                throw new IllegalArgumentException(
++                        "Extract ByteBuffer from an MlImage created by objects other than Bytebuffer is not"
++                        + " supported");
++        }
++    }
+ 
+     /**
+-     * Gets the {@link ImageFormat} in the result of {@link ByteBufferExtractor#extract(MlImage)}.
++     * Extracts a readonly {@link ByteBuffer} in given {@code targetFormat} from an {@link MlImage}.
++     *
++     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
++     *
++     * <p>Format conversion spec:
++     *
++     * <ul>
++     *   <li>When extracting RGB images to RGBA format, A channel will always set to 255.
++     *   <li>When extracting RGBA images to RGB format, A channel will be dropped.
++     * </ul>
++     *
++     * @param image the image to extract buffer from.
++     * @param targetFormat the image format of the result bytebuffer.
++     * @return the readonly {@link ByteBuffer} stored in {@link MlImage}
++     * @throws IllegalArgumentException when the extraction requires unsupported format or data type
++     *     conversions.
+      */
+-    @ImageFormat
+-    public abstract int format();
+-
+-    static Result create(ByteBuffer buffer, @ImageFormat int imageFormat) {
+-      return new AutoValue_ByteBufferExtractor_Result(buffer, imageFormat);
++    static ByteBuffer extract(MlImage image, @ImageFormat int targetFormat) {
++        ImageContainer container;
++        ImageProperties byteBufferProperties =
++                ImageProperties.builder()
++                        .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
++                        .setImageFormat(targetFormat)
++                        .build();
++        if ((container = image.getContainer(byteBufferProperties)) != null) {
++            ByteBufferImageContainer byteBufferImageContainer =
++                    (ByteBufferImageContainer) container;
++            return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer();
++        } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER)) != null) {
++            ByteBufferImageContainer byteBufferImageContainer =
++                    (ByteBufferImageContainer) container;
++            @ImageFormat
++            int sourceFormat = byteBufferImageContainer.getImageFormat();
++            return convertByteBuffer(
++                    byteBufferImageContainer.getByteBuffer(), sourceFormat, targetFormat)
++                    .asReadOnlyBuffer();
++        } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP)) != null) {
++            BitmapImageContainer bitmapImageContainer = (BitmapImageContainer) container;
++            ByteBuffer byteBuffer =
++                    extractByteBufferFromBitmap(bitmapImageContainer.getBitmap(), targetFormat)
++                            .asReadOnlyBuffer();
++            image.addContainer(new ByteBufferImageContainer(byteBuffer, targetFormat));
++            return byteBuffer;
++        } else {
++            throw new IllegalArgumentException(
++                    "Extracting ByteBuffer from an MlImage created by objects other than Bitmap or"
++                    + " Bytebuffer is not supported");
++        }
+     }
+-  }
+ 
+-  /**
+-   * Extracts a {@link ByteBuffer} in any available {@code imageFormat} from an {@link MlImage}.
+-   *
+-   * <p>It will make the best effort to return an already existed {@link ByteBuffer} to avoid copy.
+-   *
+-   * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+-   *
+-   * @return the readonly {@link ByteBuffer} stored in {@link MlImage}
+-   * @throws IllegalArgumentException when {@code image} doesn't contain {@link ByteBuffer} with
+-   *     given {@code imageFormat}
+-   */
+-  static Result extractInRecommendedFormat(MlImage image) {
+-    ImageContainer container;
+-    if ((container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP)) != null) {
+-      Bitmap bitmap = ((BitmapImageContainer) container).getBitmap();
+-      @ImageFormat int format = adviseImageFormat(bitmap);
+-      Result result =
+-          Result.create(extractByteBufferFromBitmap(bitmap, format).asReadOnlyBuffer(), format);
++    /** A wrapper for a {@link ByteBuffer} and its {@link ImageFormat}. */
++    @AutoValue
++    abstract static class Result {
++        /**
++         * Gets the {@link ByteBuffer} in the result of {@link
++         * ByteBufferExtractor#extract(MlImage)}.
++         */
++        public abstract ByteBuffer buffer();
+ 
+-      image.addContainer(new ByteBufferImageContainer(result.buffer(), result.format()));
+-      return result;
+-    } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER)) != null) {
+-      ByteBufferImageContainer byteBufferImageContainer = (ByteBufferImageContainer) container;
+-      return Result.create(
+-          byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer(),
+-          byteBufferImageContainer.getImageFormat());
+-    } else {
+-      throw new IllegalArgumentException(
+-          "Extract ByteBuffer from an MlImage created by objects other than Bitmap or Bytebuffer"
+-              + " is not supported");
++        /**
++         * Gets the {@link ImageFormat} in the result of {@link
++         * ByteBufferExtractor#extract(MlImage)}.
++         */
++        @ImageFormat
++        public abstract int format();
++
++        static Result create(ByteBuffer buffer, @ImageFormat int imageFormat) {
++            return new AutoValue_ByteBufferExtractor_Result(buffer, imageFormat);
++        }
+     }
+-  }
+ 
+-  @ImageFormat
+-  private static int adviseImageFormat(Bitmap bitmap) {
+-    if (bitmap.getConfig() == Config.ARGB_8888) {
+-      return MlImage.IMAGE_FORMAT_RGBA;
+-    } else {
+-      throw new IllegalArgumentException(
+-          String.format(
+-              "Extracting ByteBuffer from an MlImage created by a Bitmap in config %s is not"
+-                  + " supported",
+-              bitmap.getConfig()));
++    /**
++     * Extracts a {@link ByteBuffer} in any available {@code imageFormat} from an {@link MlImage}.
++     *
++     * <p>It will make the best effort to return an already existed {@link ByteBuffer} to avoid
++     * copy.
++     *
++     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
++     *
++     * @return the readonly {@link ByteBuffer} stored in {@link MlImage}
++     * @throws IllegalArgumentException when {@code image} doesn't contain {@link ByteBuffer} with
++     *     given {@code imageFormat}
++     */
++    static Result extractInRecommendedFormat(MlImage image) {
++        ImageContainer container;
++        if ((container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP)) != null) {
++            Bitmap bitmap = ((BitmapImageContainer) container).getBitmap();
++            @ImageFormat
++            int format = adviseImageFormat(bitmap);
++            Result result = Result.create(
++                    extractByteBufferFromBitmap(bitmap, format).asReadOnlyBuffer(), format);
++
++            image.addContainer(new ByteBufferImageContainer(result.buffer(), result.format()));
++            return result;
++        } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER)) != null) {
++            ByteBufferImageContainer byteBufferImageContainer =
++                    (ByteBufferImageContainer) container;
++            return Result.create(byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer(),
++                    byteBufferImageContainer.getImageFormat());
++        } else {
++            throw new IllegalArgumentException(
++                    "Extract ByteBuffer from an MlImage created by objects other than Bitmap or Bytebuffer"
++                    + " is not supported");
++        }
+     }
+-  }
+ 
+-  private static ByteBuffer extractByteBufferFromBitmap(
+-      Bitmap bitmap, @ImageFormat int imageFormat) {
+-    if (VERSION.SDK_INT >= VERSION_CODES.JELLY_BEAN_MR1 && bitmap.isPremultiplied()) {
+-      throw new IllegalArgumentException(
+-          "Extracting ByteBuffer from an MlImage created by a premultiplied Bitmap is not"
+-              + " supported");
++    @ImageFormat
++    private static int adviseImageFormat(Bitmap bitmap) {
++        if (bitmap.getConfig() == Config.ARGB_8888) {
++            return MlImage.IMAGE_FORMAT_RGBA;
++        } else {
++            throw new IllegalArgumentException(String.format(
++                    "Extracting ByteBuffer from an MlImage created by a Bitmap in config %s is not"
++                            + " supported",
++                    bitmap.getConfig()));
++        }
+     }
+-    if (bitmap.getConfig() == Config.ARGB_8888) {
+-      if (imageFormat == MlImage.IMAGE_FORMAT_RGBA) {
+-        ByteBuffer buffer = ByteBuffer.allocateDirect(bitmap.getByteCount());
+-        bitmap.copyPixelsToBuffer(buffer);
+-        buffer.rewind();
+-        return buffer;
+-      } else if (imageFormat == MlImage.IMAGE_FORMAT_RGB) {
+-        // TODO(b/180504869): Try Use RGBA buffer to create RGB buffer which might be faster.
+-        int w = bitmap.getWidth();
+-        int h = bitmap.getHeight();
+-        int[] pixels = new int[w * h];
+-        bitmap.getPixels(pixels, 0, w, 0, 0, w, h);
+-        ByteBuffer buffer = ByteBuffer.allocateDirect(w * h * 3);
+-        buffer.order(ByteOrder.nativeOrder());
+-        for (int pixel : pixels) {
+-          // getPixels returns Color in ARGB rather than copyPixelsToBuffer which returns RGBA
+-          buffer.put((byte) ((pixel >> 16) & 0xff));
+-          buffer.put((byte) ((pixel >> 8) & 0xff));
+-          buffer.put((byte) (pixel & 0xff));
++
++    private static ByteBuffer extractByteBufferFromBitmap(
++            Bitmap bitmap, @ImageFormat int imageFormat) {
++        if (VERSION.SDK_INT >= VERSION_CODES.JELLY_BEAN_MR1 && bitmap.isPremultiplied()) {
++            throw new IllegalArgumentException(
++                    "Extracting ByteBuffer from an MlImage created by a premultiplied Bitmap is not"
++                    + " supported");
+         }
+-        buffer.rewind();
+-        return buffer;
+-      }
++        if (bitmap.getConfig() == Config.ARGB_8888) {
++            if (imageFormat == MlImage.IMAGE_FORMAT_RGBA) {
++                ByteBuffer buffer = ByteBuffer.allocateDirect(bitmap.getByteCount());
++                bitmap.copyPixelsToBuffer(buffer);
++                buffer.rewind();
++                return buffer;
++            } else if (imageFormat == MlImage.IMAGE_FORMAT_RGB) {
++                // TODO(b/180504869): Try Use RGBA buffer to create RGB buffer which might be
++                // faster.
++                int w = bitmap.getWidth();
++                int h = bitmap.getHeight();
++                int[] pixels = new int[w * h];
++                bitmap.getPixels(pixels, 0, w, 0, 0, w, h);
++                ByteBuffer buffer = ByteBuffer.allocateDirect(w * h * 3);
++                buffer.order(ByteOrder.nativeOrder());
++                for (int pixel : pixels) {
++                    // getPixels returns Color in ARGB rather than copyPixelsToBuffer which returns
++                    // RGBA
++                    buffer.put((byte) ((pixel >> 16) & 0xff));
++                    buffer.put((byte) ((pixel >> 8) & 0xff));
++                    buffer.put((byte) (pixel & 0xff));
++                }
++                buffer.rewind();
++                return buffer;
++            }
++        }
++        throw new IllegalArgumentException(String.format(
++                "Extracting ByteBuffer from an MlImage created by Bitmap and convert from %s to format"
++                        + " %d is not supported",
++                bitmap.getConfig(), imageFormat));
+     }
+-    throw new IllegalArgumentException(
+-        String.format(
+-            "Extracting ByteBuffer from an MlImage created by Bitmap and convert from %s to format"
+-                + " %d is not supported",
+-            bitmap.getConfig(), imageFormat));
+-  }
+ 
+-  private static ByteBuffer convertByteBuffer(
+-      ByteBuffer source, @ImageFormat int sourceFormat, @ImageFormat int targetFormat) {
+-    if (sourceFormat == MlImage.IMAGE_FORMAT_RGB && targetFormat == MlImage.IMAGE_FORMAT_RGBA) {
+-      ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 3 * 4);
+-      // Extend the buffer when the target is longer than the source. Use two cursors and sweep the
+-      // array reversely to convert in-place.
+-      byte[] array = new byte[target.capacity()];
+-      source.get(array, 0, source.capacity());
+-      source.rewind();
+-      int rgbCursor = source.capacity();
+-      int rgbaCursor = target.capacity();
+-      while (rgbCursor != rgbaCursor) {
+-        array[--rgbaCursor] = (byte) 0xff; // A
+-        array[--rgbaCursor] = array[--rgbCursor]; // B
+-        array[--rgbaCursor] = array[--rgbCursor]; // G
+-        array[--rgbaCursor] = array[--rgbCursor]; // R
+-      }
+-      target.put(array, 0, target.capacity());
+-      target.rewind();
+-      return target;
+-    } else if (sourceFormat == MlImage.IMAGE_FORMAT_RGBA
+-        && targetFormat == MlImage.IMAGE_FORMAT_RGB) {
+-      ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 4 * 3);
+-      // Shrink the buffer when the target is shorter than the source. Use two cursors and sweep the
+-      // array to convert in-place.
+-      byte[] array = new byte[source.capacity()];
+-      source.get(array, 0, source.capacity());
+-      source.rewind();
+-      int rgbaCursor = 0;
+-      int rgbCursor = 0;
+-      while (rgbaCursor < array.length) {
+-        array[rgbCursor++] = array[rgbaCursor++]; // R
+-        array[rgbCursor++] = array[rgbaCursor++]; // G
+-        array[rgbCursor++] = array[rgbaCursor++]; // B
+-        rgbaCursor++;
+-      }
+-      target.put(array, 0, target.capacity());
+-      target.rewind();
+-      return target;
+-    } else {
+-      throw new IllegalArgumentException(
+-          String.format(
+-              Locale.ENGLISH,
+-              "Convert bytebuffer image format from %d to %d is not supported",
+-              sourceFormat,
+-              targetFormat));
++    private static ByteBuffer convertByteBuffer(
++            ByteBuffer source, @ImageFormat int sourceFormat, @ImageFormat int targetFormat) {
++        if (sourceFormat == MlImage.IMAGE_FORMAT_RGB && targetFormat == MlImage.IMAGE_FORMAT_RGBA) {
++            ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 3 * 4);
++            // Extend the buffer when the target is longer than the source. Use two cursors and
++            // sweep the array reversely to convert in-place.
++            byte[] array = new byte[target.capacity()];
++            source.get(array, 0, source.capacity());
++            source.rewind();
++            int rgbCursor = source.capacity();
++            int rgbaCursor = target.capacity();
++            while (rgbCursor != rgbaCursor) {
++                array[--rgbaCursor] = (byte) 0xff; // A
++                array[--rgbaCursor] = array[--rgbCursor]; // B
++                array[--rgbaCursor] = array[--rgbCursor]; // G
++                array[--rgbaCursor] = array[--rgbCursor]; // R
++            }
++            target.put(array, 0, target.capacity());
++            target.rewind();
++            return target;
++        } else if (sourceFormat == MlImage.IMAGE_FORMAT_RGBA
++                && targetFormat == MlImage.IMAGE_FORMAT_RGB) {
++            ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 4 * 3);
++            // Shrink the buffer when the target is shorter than the source. Use two cursors and
++            // sweep the array to convert in-place.
++            byte[] array = new byte[source.capacity()];
++            source.get(array, 0, source.capacity());
++            source.rewind();
++            int rgbaCursor = 0;
++            int rgbCursor = 0;
++            while (rgbaCursor < array.length) {
++                array[rgbCursor++] = array[rgbaCursor++]; // R
++                array[rgbCursor++] = array[rgbaCursor++]; // G
++                array[rgbCursor++] = array[rgbaCursor++]; // B
++                rgbaCursor++;
++            }
++            target.put(array, 0, target.capacity());
++            target.rewind();
++            return target;
++        } else {
++            throw new IllegalArgumentException(String.format(Locale.ENGLISH,
++                    "Convert bytebuffer image format from %d to %d is not supported", sourceFormat,
++                    targetFormat));
++        }
+     }
+-  }
+ 
+-  // ByteBuffer is not able to be instantiated.
+-  private ByteBufferExtractor() {}
++    // ByteBuffer is not able to be instantiated.
++    private ByteBufferExtractor() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java
+index 9fbc3cbb94994..f872db485a8a2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java
+@@ -16,42 +16,40 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import com.google.android.odml.image.MlImage.ImageFormat;
++
+ import java.nio.ByteBuffer;
+ 
+ class ByteBufferImageContainer implements ImageContainer {
+-
+-  private final ByteBuffer buffer;
+-  private final ImageProperties properties;
+-
+-  public ByteBufferImageContainer(
+-      ByteBuffer buffer,
+-      @ImageFormat int imageFormat) {
+-    this.buffer = buffer;
+-    this.properties = ImageProperties.builder()
+-        .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
+-        .setImageFormat(imageFormat)
+-        .build();
+-  }
+-
+-  public ByteBuffer getByteBuffer() {
+-    return buffer;
+-  }
+-
+-  @Override
+-  public ImageProperties getImageProperties() {
+-    return properties;
+-  }
+-
+-  /**
+-   * Returns the image format.
+-   */
+-  @ImageFormat
+-  public int getImageFormat() {
+-    return properties.getImageFormat();
+-  }
+-
+-  @Override
+-  public void close() {
+-    // No op for ByteBuffer.
+-  }
++    private final ByteBuffer buffer;
++    private final ImageProperties properties;
++
++    public ByteBufferImageContainer(ByteBuffer buffer, @ImageFormat int imageFormat) {
++        this.buffer = buffer;
++        this.properties = ImageProperties.builder()
++                                  .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
++                                  .setImageFormat(imageFormat)
++                                  .build();
++    }
++
++    public ByteBuffer getByteBuffer() {
++        return buffer;
++    }
++
++    @Override
++    public ImageProperties getImageProperties() {
++        return properties;
++    }
++
++    /**
++     * Returns the image format.
++     */
++    @ImageFormat
++    public int getImageFormat() {
++        return properties.getImageFormat();
++    }
++
++    @Override
++    public void close() {
++        // No op for ByteBuffer.
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java
+index 421e2b8f0de31..f4b0b31dd5e3b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java
+@@ -16,7 +16,9 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import android.graphics.Rect;
++
+ import com.google.android.odml.image.MlImage.ImageFormat;
++
+ import java.nio.ByteBuffer;
+ 
+ /**
+@@ -28,79 +30,74 @@ import java.nio.ByteBuffer;
+  * <p>Use {@link ByteBufferExtractor} to get {@link ByteBuffer} you passed in.
+  */
+ public class ByteBufferMlImageBuilder {
++    // Mandatory fields.
++    private final ByteBuffer buffer;
++    private final int width;
++    private final int height;
++    @ImageFormat
++    private final int imageFormat;
+ 
+-  // Mandatory fields.
+-  private final ByteBuffer buffer;
+-  private final int width;
+-  private final int height;
+-  @ImageFormat private final int imageFormat;
+-
+-  // Optional fields.
+-  private int rotation;
+-  private Rect roi;
+-  private long timestamp;
++    // Optional fields.
++    private int rotation;
++    private Rect roi;
++    private long timestamp;
+ 
+-  /**
+-   * Creates the builder with mandatory {@link ByteBuffer} and the represented image.
+-   *
+-   * <p>We will validate the size of the {@code byteBuffer} with given {@code width}, {@code height}
+-   * and {@code imageFormat}.
+-   *
+-   * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the values
+-   * will be set with default:
+-   *
+-   * <ul>
+-   *   <li>rotation: 0
+-   * </ul>
+-   *
+-   * @param byteBuffer image data object.
+-   * @param width the width of the represented image.
+-   * @param height the height of the represented image.
+-   * @param imageFormat how the data encode the image.
+-   */
+-  public ByteBufferMlImageBuilder(
+-      ByteBuffer byteBuffer, int width, int height, @ImageFormat int imageFormat) {
+-    this.buffer = byteBuffer;
+-    this.width = width;
+-    this.height = height;
+-    this.imageFormat = imageFormat;
+-    // TODO(b/180504869): Validate bytebuffer size with width, height and image format
+-    this.rotation = 0;
+-    this.roi = new Rect(0, 0, width, height);
+-    this.timestamp = 0;
+-  }
++    /**
++     * Creates the builder with mandatory {@link ByteBuffer} and the represented image.
++     *
++     * <p>We will validate the size of the {@code byteBuffer} with given {@code width}, {@code
++     * height} and {@code imageFormat}.
++     *
++     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
++     * values will be set with default:
++     *
++     * <ul>
++     *   <li>rotation: 0
++     * </ul>
++     *
++     * @param byteBuffer image data object.
++     * @param width the width of the represented image.
++     * @param height the height of the represented image.
++     * @param imageFormat how the data encode the image.
++     */
++    public ByteBufferMlImageBuilder(
++            ByteBuffer byteBuffer, int width, int height, @ImageFormat int imageFormat) {
++        this.buffer = byteBuffer;
++        this.width = width;
++        this.height = height;
++        this.imageFormat = imageFormat;
++        // TODO(b/180504869): Validate bytebuffer size with width, height and image format
++        this.rotation = 0;
++        this.roi = new Rect(0, 0, width, height);
++        this.timestamp = 0;
++    }
+ 
+-  /**
+-   * Sets value for {@link MlImage#getRotation()}.
+-   *
+-   * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
+-   */
+-  public ByteBufferMlImageBuilder setRotation(int rotation) {
+-    MlImage.validateRotation(rotation);
+-    this.rotation = rotation;
+-    return this;
+-  }
++    /**
++     * Sets value for {@link MlImage#getRotation()}.
++     *
++     * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
++     */
++    public ByteBufferMlImageBuilder setRotation(int rotation) {
++        MlImage.validateRotation(rotation);
++        this.rotation = rotation;
++        return this;
++    }
+ 
+-  /** Sets value for {@link MlImage#getRoi()}. */
+-  ByteBufferMlImageBuilder setRoi(Rect roi) {
+-    this.roi = roi;
+-    return this;
+-  }
++    /** Sets value for {@link MlImage#getRoi()}. */
++    ByteBufferMlImageBuilder setRoi(Rect roi) {
++        this.roi = roi;
++        return this;
++    }
+ 
+-  /** Sets value for {@link MlImage#getTimestamp()}. */
+-  ByteBufferMlImageBuilder setTimestamp(long timestamp) {
+-    this.timestamp = timestamp;
+-    return this;
+-  }
++    /** Sets value for {@link MlImage#getTimestamp()}. */
++    ByteBufferMlImageBuilder setTimestamp(long timestamp) {
++        this.timestamp = timestamp;
++        return this;
++    }
+ 
+-  /** Builds an {@link MlImage} instance. */
+-  public MlImage build() {
+-    return new MlImage(
+-        new ByteBufferImageContainer(buffer, imageFormat),
+-        rotation,
+-        roi,
+-        timestamp,
+-        width,
+-        height);
+-  }
++    /** Builds an {@link MlImage} instance. */
++    public MlImage build() {
++        return new MlImage(new ByteBufferImageContainer(buffer, imageFormat), rotation, roi,
++                timestamp, width, height);
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java
+index 25ed2312ce580..bfa7c0a292f4f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java
+@@ -20,11 +20,11 @@ import com.google.android.odml.image.annotation.KeepForSdk;
+ /** Manages internal image data storage. The interface is package-private. */
+ @KeepForSdk
+ interface ImageContainer {
+-  /** Returns the properties of the contained image. */
+-  @KeepForSdk
+-  ImageProperties getImageProperties();
++    /** Returns the properties of the contained image. */
++    @KeepForSdk
++    ImageProperties getImageProperties();
+ 
+-  /** Close the image container and releases the image resource inside. */
+-  @KeepForSdk
+-  void close();
++    /** Close the image container and releases the image resource inside. */
++    @KeepForSdk
++    void close();
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java
+index 717bc5f9935ed..a61e97b81b872 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java
+@@ -24,63 +24,61 @@ import com.google.auto.value.extension.memoized.Memoized;
+ /** Groups a set of properties to describe how an image is stored. */
+ @AutoValue
+ public abstract class ImageProperties {
+-
+-  /**
+-   * Gets the pixel format of the image.
+-   *
+-   * @see MlImage.ImageFormat
+-   */
+-  @ImageFormat
+-  public abstract int getImageFormat();
+-
+-  /**
+-   * Gets the storage type of the image.
+-   *
+-   * @see MlImage.StorageType
+-   */
+-  @StorageType
+-  public abstract int getStorageType();
+-
+-  @Memoized
+-  @Override
+-  public abstract int hashCode();
+-
+-  /**
+-   * Creates a builder of {@link ImageProperties}.
+-   *
+-   * @see ImageProperties.Builder
+-   */
+-  @KeepForSdk
+-  static Builder builder() {
+-    return new AutoValue_ImageProperties.Builder();
+-  }
+-
+-  /** Builds a {@link ImageProperties}. */
+-  @AutoValue.Builder
+-  @KeepForSdk
+-  abstract static class Builder {
++    /**
++     * Gets the pixel format of the image.
++     *
++     * @see MlImage.ImageFormat
++     */
++    @ImageFormat
++    public abstract int getImageFormat();
+ 
+     /**
+-     * Sets the {@link MlImage.ImageFormat}.
++     * Gets the storage type of the image.
+      *
+-     * @see ImageProperties#getImageFormat
++     * @see MlImage.StorageType
+      */
+-    @KeepForSdk
+-    abstract Builder setImageFormat(@ImageFormat int value);
++    @StorageType
++    public abstract int getStorageType();
++
++    @Memoized
++    @Override
++    public abstract int hashCode();
+ 
+     /**
+-     * Sets the {@link MlImage.StorageType}.
++     * Creates a builder of {@link ImageProperties}.
+      *
+-     * @see ImageProperties#getStorageType
++     * @see ImageProperties.Builder
+      */
+     @KeepForSdk
+-    abstract Builder setStorageType(@StorageType int value);
++    static Builder builder() {
++        return new AutoValue_ImageProperties.Builder();
++    }
+ 
+-    /** Builds the {@link ImageProperties}. */
++    /** Builds a {@link ImageProperties}. */
++    @AutoValue.Builder
+     @KeepForSdk
+-    abstract ImageProperties build();
+-  }
++    abstract static class Builder {
++        /**
++         * Sets the {@link MlImage.ImageFormat}.
++         *
++         * @see ImageProperties#getImageFormat
++         */
++        @KeepForSdk
++        abstract Builder setImageFormat(@ImageFormat int value);
++
++        /**
++         * Sets the {@link MlImage.StorageType}.
++         *
++         * @see ImageProperties#getStorageType
++         */
++        @KeepForSdk
++        abstract Builder setStorageType(@StorageType int value);
++
++        /** Builds the {@link ImageProperties}. */
++        @KeepForSdk
++        abstract ImageProperties build();
++    }
+ 
+-  // Hide the constructor.
+-  ImageProperties() {}
++    // Hide the constructor.
++    ImageProperties() {}
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java
+index 9365d0b2a422e..9ed88ee30c62f 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java
+@@ -19,55 +19,56 @@ import android.media.Image;
+ import android.os.Build;
+ import android.os.Build.VERSION;
+ import android.os.Build.VERSION_CODES;
++
+ import androidx.annotation.RequiresApi;
++
+ import com.google.android.odml.image.MlImage.ImageFormat;
+ 
+ @RequiresApi(VERSION_CODES.KITKAT)
+ class MediaImageContainer implements ImageContainer {
++    private final Image mediaImage;
++    private final ImageProperties properties;
+ 
+-  private final Image mediaImage;
+-  private final ImageProperties properties;
+-
+-  public MediaImageContainer(Image mediaImage) {
+-    this.mediaImage = mediaImage;
+-    this.properties = ImageProperties.builder()
+-        .setStorageType(MlImage.STORAGE_TYPE_MEDIA_IMAGE)
+-        .setImageFormat(convertFormatCode(mediaImage.getFormat()))
+-        .build();
+-  }
+-
+-  public Image getImage() {
+-    return mediaImage;
+-  }
++    public MediaImageContainer(Image mediaImage) {
++        this.mediaImage = mediaImage;
++        this.properties = ImageProperties.builder()
++                                  .setStorageType(MlImage.STORAGE_TYPE_MEDIA_IMAGE)
++                                  .setImageFormat(convertFormatCode(mediaImage.getFormat()))
++                                  .build();
++    }
+ 
+-  @Override
+-  public ImageProperties getImageProperties() {
+-    return properties;
+-  }
++    public Image getImage() {
++        return mediaImage;
++    }
+ 
+-  @Override
+-  public void close() {
+-    mediaImage.close();
+-  }
++    @Override
++    public ImageProperties getImageProperties() {
++        return properties;
++    }
+ 
+-  @ImageFormat
+-  static int convertFormatCode(int graphicsFormat) {
+-    // We only cover the format mentioned in
+-    // https://developer.android.com/reference/android/media/Image#getFormat()
+-    if (VERSION.SDK_INT >= Build.VERSION_CODES.M) {
+-      if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGBA_8888) {
+-        return MlImage.IMAGE_FORMAT_RGBA;
+-      } else if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGB_888) {
+-        return MlImage.IMAGE_FORMAT_RGB;
+-      }
++    @Override
++    public void close() {
++        mediaImage.close();
+     }
+-    switch (graphicsFormat) {
+-      case android.graphics.ImageFormat.JPEG:
+-        return MlImage.IMAGE_FORMAT_JPEG;
+-      case android.graphics.ImageFormat.YUV_420_888:
+-        return MlImage.IMAGE_FORMAT_YUV_420_888;
+-      default:
+-        return MlImage.IMAGE_FORMAT_UNKNOWN;
++
++    @ImageFormat
++    static int convertFormatCode(int graphicsFormat) {
++        // We only cover the format mentioned in
++        // https://developer.android.com/reference/android/media/Image#getFormat()
++        if (VERSION.SDK_INT >= Build.VERSION_CODES.M) {
++            if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGBA_8888) {
++                return MlImage.IMAGE_FORMAT_RGBA;
++            } else if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGB_888) {
++                return MlImage.IMAGE_FORMAT_RGB;
++            }
++        }
++        switch (graphicsFormat) {
++            case android.graphics.ImageFormat.JPEG:
++                return MlImage.IMAGE_FORMAT_JPEG;
++            case android.graphics.ImageFormat.YUV_420_888:
++                return MlImage.IMAGE_FORMAT_YUV_420_888;
++            default:
++                return MlImage.IMAGE_FORMAT_UNKNOWN;
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java
+index 73aadabb38789..59ed98b569fa2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java
+@@ -17,6 +17,7 @@ package com.google.android.odml.image;
+ 
+ import android.media.Image;
+ import android.os.Build.VERSION_CODES;
++
+ import androidx.annotation.RequiresApi;
+ 
+ /**
+@@ -27,26 +28,25 @@ import androidx.annotation.RequiresApi;
+  */
+ @RequiresApi(VERSION_CODES.KITKAT)
+ public class MediaImageExtractor {
+-
+-  private MediaImageExtractor() {}
+-
+-  /**
+-   * Extracts a {@link android.media.Image} from an {@link MlImage}. Currently it only works for
+-   * {@link MlImage} that built from {@link MediaMlImageBuilder}.
+-   *
+-   * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+-   *
+-   * @param image the image to extract {@link android.media.Image} from.
+-   * @return {@link android.media.Image} that stored in {@link MlImage}.
+-   * @throws IllegalArgumentException if the extraction failed.
+-   */
+-  public static Image extract(MlImage image) {
+-    ImageContainer container;
+-    if ((container = image.getContainer(MlImage.STORAGE_TYPE_MEDIA_IMAGE)) != null) {
+-      return ((MediaImageContainer) container).getImage();
++    private MediaImageExtractor() {}
++
++    /**
++     * Extracts a {@link android.media.Image} from an {@link MlImage}. Currently it only works for
++     * {@link MlImage} that built from {@link MediaMlImageBuilder}.
++     *
++     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
++     *
++     * @param image the image to extract {@link android.media.Image} from.
++     * @return {@link android.media.Image} that stored in {@link MlImage}.
++     * @throws IllegalArgumentException if the extraction failed.
++     */
++    public static Image extract(MlImage image) {
++        ImageContainer container;
++        if ((container = image.getContainer(MlImage.STORAGE_TYPE_MEDIA_IMAGE)) != null) {
++            return ((MediaImageContainer) container).getImage();
++        }
++        throw new IllegalArgumentException(
++                "Extract Media Image from an MlImage created by objects other than Media Image"
++                + " is not supported");
+     }
+-    throw new IllegalArgumentException(
+-        "Extract Media Image from an MlImage created by objects other than Media Image"
+-            + " is not supported");
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java
+index e96ab38317bac..80771bdb91890 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java
+@@ -18,6 +18,7 @@ package com.google.android.odml.image;
+ import android.graphics.Rect;
+ import android.media.Image;
+ import android.os.Build.VERSION_CODES;
++
+ import androidx.annotation.RequiresApi;
+ 
+ /**
+@@ -30,65 +31,59 @@ import androidx.annotation.RequiresApi;
+  */
+ @RequiresApi(VERSION_CODES.KITKAT)
+ public class MediaMlImageBuilder {
++    // Mandatory fields.
++    private final Image mediaImage;
+ 
+-  // Mandatory fields.
+-  private final Image mediaImage;
+-
+-  // Optional fields.
+-  private int rotation;
+-  private Rect roi;
+-  private long timestamp;
++    // Optional fields.
++    private int rotation;
++    private Rect roi;
++    private long timestamp;
+ 
+-  /**
+-   * Creates the builder with a mandatory {@link android.media.Image}.
+-   *
+-   * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the values
+-   * will be set with default:
+-   *
+-   * <ul>
+-   *   <li>rotation: 0
+-   * </ul>
+-   *
+-   * @param mediaImage image data object.
+-   */
+-  public MediaMlImageBuilder(Image mediaImage) {
+-    this.mediaImage = mediaImage;
+-    this.rotation = 0;
+-    this.roi = new Rect(0, 0, mediaImage.getWidth(), mediaImage.getHeight());
+-    this.timestamp = 0;
+-  }
++    /**
++     * Creates the builder with a mandatory {@link android.media.Image}.
++     *
++     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
++     * values will be set with default:
++     *
++     * <ul>
++     *   <li>rotation: 0
++     * </ul>
++     *
++     * @param mediaImage image data object.
++     */
++    public MediaMlImageBuilder(Image mediaImage) {
++        this.mediaImage = mediaImage;
++        this.rotation = 0;
++        this.roi = new Rect(0, 0, mediaImage.getWidth(), mediaImage.getHeight());
++        this.timestamp = 0;
++    }
+ 
+-  /**
+-   * Sets value for {@link MlImage#getRotation()}.
+-   *
+-   * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
+-   */
+-  public MediaMlImageBuilder setRotation(int rotation) {
+-    MlImage.validateRotation(rotation);
+-    this.rotation = rotation;
+-    return this;
+-  }
++    /**
++     * Sets value for {@link MlImage#getRotation()}.
++     *
++     * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
++     */
++    public MediaMlImageBuilder setRotation(int rotation) {
++        MlImage.validateRotation(rotation);
++        this.rotation = rotation;
++        return this;
++    }
+ 
+-  /** Sets value for {@link MlImage#getRoi()}. */
+-  MediaMlImageBuilder setRoi(Rect roi) {
+-    this.roi = roi;
+-    return this;
+-  }
++    /** Sets value for {@link MlImage#getRoi()}. */
++    MediaMlImageBuilder setRoi(Rect roi) {
++        this.roi = roi;
++        return this;
++    }
+ 
+-  /** Sets value for {@link MlImage#getTimestamp()}. */
+-  MediaMlImageBuilder setTimestamp(long timestamp) {
+-    this.timestamp = timestamp;
+-    return this;
+-  }
++    /** Sets value for {@link MlImage#getTimestamp()}. */
++    MediaMlImageBuilder setTimestamp(long timestamp) {
++        this.timestamp = timestamp;
++        return this;
++    }
+ 
+-  /** Builds an {@link MlImage} instance. */
+-  public MlImage build() {
+-    return new MlImage(
+-        new MediaImageContainer(mediaImage),
+-        rotation,
+-        roi,
+-        timestamp,
+-        mediaImage.getWidth(),
+-        mediaImage.getHeight());
+-  }
++    /** Builds an {@link MlImage} instance. */
++    public MlImage build() {
++        return new MlImage(new MediaImageContainer(mediaImage), rotation, roi, timestamp,
++                mediaImage.getWidth(), mediaImage.getHeight());
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java
+index 975ff7c0908c7..7e21e6ad428f2 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java
+@@ -16,9 +16,12 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import android.graphics.Rect;
++
+ import androidx.annotation.IntDef;
+ import androidx.annotation.Nullable;
++
+ import com.google.android.odml.image.annotation.KeepForSdk;
++
+ import java.io.Closeable;
+ import java.lang.annotation.Retention;
+ import java.lang.annotation.RetentionPolicy;
+@@ -62,228 +65,232 @@ import java.util.Map.Entry;
+  * and multiple storages.
+  */
+ public class MlImage implements Closeable {
++    /** Specifies the image format of an image. */
++    @IntDef({
++            IMAGE_FORMAT_UNKNOWN,
++            IMAGE_FORMAT_RGBA,
++            IMAGE_FORMAT_RGB,
++            IMAGE_FORMAT_NV12,
++            IMAGE_FORMAT_NV21,
++            IMAGE_FORMAT_YV12,
++            IMAGE_FORMAT_YV21,
++            IMAGE_FORMAT_YUV_420_888,
++            IMAGE_FORMAT_ALPHA,
++            IMAGE_FORMAT_JPEG,
++    })
++    @Retention(RetentionPolicy.SOURCE)
++    public @interface ImageFormat {}
++
++    public static final int IMAGE_FORMAT_UNKNOWN = 0;
++    public static final int IMAGE_FORMAT_RGBA = 1;
++    public static final int IMAGE_FORMAT_RGB = 2;
++    public static final int IMAGE_FORMAT_NV12 = 3;
++    public static final int IMAGE_FORMAT_NV21 = 4;
++    public static final int IMAGE_FORMAT_YV12 = 5;
++    public static final int IMAGE_FORMAT_YV21 = 6;
++    public static final int IMAGE_FORMAT_YUV_420_888 = 7;
++    public static final int IMAGE_FORMAT_ALPHA = 8;
++    public static final int IMAGE_FORMAT_JPEG = 9;
++
++    /** Specifies the image container type. Would be useful for choosing extractors. */
++    @IntDef({
++            STORAGE_TYPE_BITMAP,
++            STORAGE_TYPE_BYTEBUFFER,
++            STORAGE_TYPE_MEDIA_IMAGE,
++            STORAGE_TYPE_IMAGE_PROXY,
++    })
++    @Retention(RetentionPolicy.SOURCE)
++    public @interface StorageType {}
++
++    public static final int STORAGE_TYPE_BITMAP = 1;
++    public static final int STORAGE_TYPE_BYTEBUFFER = 2;
++    public static final int STORAGE_TYPE_MEDIA_IMAGE = 3;
++    public static final int STORAGE_TYPE_IMAGE_PROXY = 4;
++
++    /**
++     * Returns a list of supported image properties for this {@link MlImage}.
++     *
++     * <p>Currently {@link MlImage} only support single storage type so the size of return list will
++     * always be 1.
++     *
++     * @see ImageProperties
++     */
++    public List<ImageProperties> getContainedImageProperties() {
++        return Collections.singletonList(getContainer().getImageProperties());
++    }
++
++    /** Returns the rotation value attached to the image. Rotation value will be 0, 90, 180, 270. */
++    public int getRotation() {
++        return rotation;
++    }
++
++    /** Returns the timestamp attached to the image. */
++    long getTimestamp() {
++        return timestamp;
++    }
++
++    /** Returns the width of the image. */
++    public int getWidth() {
++        return width;
++    }
++
++    /** Returns the height of the image. */
++    public int getHeight() {
++        return height;
++    }
+ 
+-  /** Specifies the image format of an image. */
+-  @IntDef({
+-    IMAGE_FORMAT_UNKNOWN,
+-    IMAGE_FORMAT_RGBA,
+-    IMAGE_FORMAT_RGB,
+-    IMAGE_FORMAT_NV12,
+-    IMAGE_FORMAT_NV21,
+-    IMAGE_FORMAT_YV12,
+-    IMAGE_FORMAT_YV21,
+-    IMAGE_FORMAT_YUV_420_888,
+-    IMAGE_FORMAT_ALPHA,
+-    IMAGE_FORMAT_JPEG,
+-  })
+-  @Retention(RetentionPolicy.SOURCE)
+-  public @interface ImageFormat {}
+-
+-  public static final int IMAGE_FORMAT_UNKNOWN = 0;
+-  public static final int IMAGE_FORMAT_RGBA = 1;
+-  public static final int IMAGE_FORMAT_RGB = 2;
+-  public static final int IMAGE_FORMAT_NV12 = 3;
+-  public static final int IMAGE_FORMAT_NV21 = 4;
+-  public static final int IMAGE_FORMAT_YV12 = 5;
+-  public static final int IMAGE_FORMAT_YV21 = 6;
+-  public static final int IMAGE_FORMAT_YUV_420_888 = 7;
+-  public static final int IMAGE_FORMAT_ALPHA = 8;
+-  public static final int IMAGE_FORMAT_JPEG = 9;
+-
+-  /** Specifies the image container type. Would be useful for choosing extractors. */
+-  @IntDef({
+-    STORAGE_TYPE_BITMAP,
+-    STORAGE_TYPE_BYTEBUFFER,
+-    STORAGE_TYPE_MEDIA_IMAGE,
+-    STORAGE_TYPE_IMAGE_PROXY,
+-  })
+-  @Retention(RetentionPolicy.SOURCE)
+-  public @interface StorageType {}
+-
+-  public static final int STORAGE_TYPE_BITMAP = 1;
+-  public static final int STORAGE_TYPE_BYTEBUFFER = 2;
+-  public static final int STORAGE_TYPE_MEDIA_IMAGE = 3;
+-  public static final int STORAGE_TYPE_IMAGE_PROXY = 4;
+-
+-  /**
+-   * Returns a list of supported image properties for this {@link MlImage}.
+-   *
+-   * <p>Currently {@link MlImage} only support single storage type so the size of return list will
+-   * always be 1.
+-   *
+-   * @see ImageProperties
+-   */
+-  public List<ImageProperties> getContainedImageProperties() {
+-    return Collections.singletonList(getContainer().getImageProperties());
+-  }
+-
+-  /** Returns the rotation value attached to the image. Rotation value will be 0, 90, 180, 270. */
+-  public int getRotation() {
+-    return rotation;
+-  }
+-
+-  /** Returns the timestamp attached to the image. */
+-  long getTimestamp() {
+-    return timestamp;
+-  }
+-
+-  /** Returns the width of the image. */
+-  public int getWidth() {
+-    return width;
+-  }
+-
+-  /** Returns the height of the image. */
+-  public int getHeight() {
+-    return height;
+-  }
+-
+-  /** Returns the region-of-interest rectangle attached to the image. */
+-  Rect getRoi() {
+-    Rect result = new Rect();
+-    result.set(roi);
+-    return result;
+-  }
+-
+-  /** Acquires a reference on this {@link MlImage}. This will increase the reference count by 1. */
+-  private synchronized void acquire() {
+-    referenceCount += 1;
+-  }
+-
+-  /**
+-   * Removes a reference that was previously acquired or init.
+-   *
+-   * <p>When {@link MlImage} is created, it has 1 reference count.
+-   *
+-   * <p>When the reference count becomes 0, it will release the resource under the hood.
+-   */
+-  @Override
+-  // TODO(b/189767728): Create an internal flag to indicate image is closed, or use referenceCount
+-  public synchronized void close() {
+-    referenceCount -= 1;
+-    if (referenceCount == 0) {
+-      for (ImageContainer imageContainer : containerMap.values()) {
+-        imageContainer.close();
+-      }
++    /** Returns the region-of-interest rectangle attached to the image. */
++    Rect getRoi() {
++        Rect result = new Rect();
++        result.set(roi);
++        return result;
+     }
+-  }
+-
+-  /**
+-   * Advanced API access for {@link MlImage}.
+-   *
+-   * <p>These APIs are useful for other infrastructures, for example, acquiring extra reference
+-   * count for {@link MlImage}. However, an App developer should avoid using the following APIs.
+-   *
+-   * <p>APIs inside are treated as internal APIs which are subject to change.
+-   */
+-  public static final class Internal {
+ 
+     /**
+      * Acquires a reference on this {@link MlImage}. This will increase the reference count by 1.
++     */
++    private synchronized void acquire() {
++        referenceCount += 1;
++    }
++
++    /**
++     * Removes a reference that was previously acquired or init.
++     *
++     * <p>When {@link MlImage} is created, it has 1 reference count.
+      *
+-     * <p>This method is more useful for image consumer to acquire a reference so image resource
+-     * will not be closed accidentally. As image creator, normal developer doesn't need to call this
+-     * method.
++     * <p>When the reference count becomes 0, it will release the resource under the hood.
++     */
++    @Override
++    // TODO(b/189767728): Create an internal flag to indicate image is closed, or use referenceCount
++    public synchronized void close() {
++        referenceCount -= 1;
++        if (referenceCount == 0) {
++            for (ImageContainer imageContainer : containerMap.values()) {
++                imageContainer.close();
++            }
++        }
++    }
++
++    /**
++     * Advanced API access for {@link MlImage}.
+      *
+-     * <p>The reference count is 1 when {@link MlImage} is created. Developer can call {@link
+-     * #close()} to indicate it doesn't need this {@link MlImage} anymore.
++     * <p>These APIs are useful for other infrastructures, for example, acquiring extra reference
++     * count for {@link MlImage}. However, an App developer should avoid using the following APIs.
+      *
+-     * @see #close()
++     * <p>APIs inside are treated as internal APIs which are subject to change.
+      */
+-    public void acquire() {
+-      image.acquire();
++    public static final class Internal {
++        /**
++         * Acquires a reference on this {@link MlImage}. This will increase the reference count
++         * by 1.
++         *
++         * <p>This method is more useful for image consumer to acquire a reference so image resource
++         * will not be closed accidentally. As image creator, normal developer doesn't need to call
++         * this method.
++         *
++         * <p>The reference count is 1 when {@link MlImage} is created. Developer can call {@link
++         * #close()} to indicate it doesn't need this {@link MlImage} anymore.
++         *
++         * @see #close()
++         */
++        public void acquire() {
++            image.acquire();
++        }
++
++        private final MlImage image;
++
++        // Only MlImage creates the internal helper.
++        private Internal(MlImage image) {
++            this.image = image;
++        }
++    }
++
++    /** Gets {@link Internal} object which contains internal APIs. */
++    public Internal getInternal() {
++        return new Internal(this);
+     }
+ 
+-    private final MlImage image;
++    private final Map<ImageProperties, ImageContainer> containerMap;
++    private final int rotation;
++    private final Rect roi;
++    private final long timestamp;
++    private final int width;
++    private final int height;
++
++    private int referenceCount;
++
++    /** Constructs an {@link MlImage} with a built container. */
++    @KeepForSdk
++    MlImage(ImageContainer container, int rotation, Rect roi, long timestamp, int width,
++            int height) {
++        this.containerMap = new HashMap<>();
++        containerMap.put(container.getImageProperties(), container);
++        this.rotation = rotation;
++        this.roi = new Rect();
++        this.roi.set(roi);
++        this.timestamp = timestamp;
++        this.width = width;
++        this.height = height;
++        this.referenceCount = 1;
++    }
++
++    /**
++     * Gets one available container.
++     *
++     * @return the current container.
++     */
++    @KeepForSdk
++    ImageContainer getContainer() {
++        // According to the design, in the future we will support multiple containers in one image.
++        // Currently just return the original container.
++        // TODO(b/182443927): Cache multiple containers in MlImage.
++        return containerMap.values().iterator().next();
++    }
+ 
+-    // Only MlImage creates the internal helper.
+-    private Internal(MlImage image) {
+-      this.image = image;
++    /**
++     * Gets container from required {@code storageType}. Returns {@code null} if not existed.
++     *
++     * <p>If there are multiple containers with required {@code storageType}, returns the first one.
++     */
++    @Nullable
++    @KeepForSdk
++    ImageContainer getContainer(@StorageType int storageType) {
++        for (Entry<ImageProperties, ImageContainer> entry : containerMap.entrySet()) {
++            if (entry.getKey().getStorageType() == storageType) {
++                return entry.getValue();
++            }
++        }
++        return null;
+     }
+-  }
+-
+-  /** Gets {@link Internal} object which contains internal APIs. */
+-  public Internal getInternal() {
+-    return new Internal(this);
+-  }
+-
+-  private final Map<ImageProperties, ImageContainer> containerMap;
+-  private final int rotation;
+-  private final Rect roi;
+-  private final long timestamp;
+-  private final int width;
+-  private final int height;
+-
+-  private int referenceCount;
+-
+-  /** Constructs an {@link MlImage} with a built container. */
+-  @KeepForSdk
+-  MlImage(ImageContainer container, int rotation, Rect roi, long timestamp, int width, int height) {
+-    this.containerMap = new HashMap<>();
+-    containerMap.put(container.getImageProperties(), container);
+-    this.rotation = rotation;
+-    this.roi = new Rect();
+-    this.roi.set(roi);
+-    this.timestamp = timestamp;
+-    this.width = width;
+-    this.height = height;
+-    this.referenceCount = 1;
+-  }
+-
+-  /**
+-   * Gets one available container.
+-   *
+-   * @return the current container.
+-   */
+-  @KeepForSdk
+-  ImageContainer getContainer() {
+-    // According to the design, in the future we will support multiple containers in one image.
+-    // Currently just return the original container.
+-    // TODO(b/182443927): Cache multiple containers in MlImage.
+-    return containerMap.values().iterator().next();
+-  }
+-
+-  /**
+-   * Gets container from required {@code storageType}. Returns {@code null} if not existed.
+-   *
+-   * <p>If there are multiple containers with required {@code storageType}, returns the first one.
+-   */
+-  @Nullable
+-  @KeepForSdk
+-  ImageContainer getContainer(@StorageType int storageType) {
+-    for (Entry<ImageProperties, ImageContainer> entry : containerMap.entrySet()) {
+-      if (entry.getKey().getStorageType() == storageType) {
+-        return entry.getValue();
+-      }
++
++    /**
++     * Gets container from required {@code imageProperties}. Returns {@code null} if non existed.
++     */
++    @Nullable
++    @KeepForSdk
++    ImageContainer getContainer(ImageProperties imageProperties) {
++        return containerMap.get(imageProperties);
+     }
+-    return null;
+-  }
+-
+-  /** Gets container from required {@code imageProperties}. Returns {@code null} if non existed. */
+-  @Nullable
+-  @KeepForSdk
+-  ImageContainer getContainer(ImageProperties imageProperties) {
+-    return containerMap.get(imageProperties);
+-  }
+-
+-  /** Adds a new container if it doesn't exist. Returns {@code true} if it succeeds. */
+-  boolean addContainer(ImageContainer container) {
+-    ImageProperties imageProperties = container.getImageProperties();
+-    if (containerMap.containsKey(imageProperties)) {
+-      return false;
++
++    /** Adds a new container if it doesn't exist. Returns {@code true} if it succeeds. */
++    boolean addContainer(ImageContainer container) {
++        ImageProperties imageProperties = container.getImageProperties();
++        if (containerMap.containsKey(imageProperties)) {
++            return false;
++        }
++        containerMap.put(imageProperties, container);
++        return true;
+     }
+-    containerMap.put(imageProperties, container);
+-    return true;
+-  }
+-
+-  /**
+-   * Validates rotation values for builders. Only supports 0, 90, 180, 270.
+-   *
+-   * @throws IllegalArgumentException if the rotation value is invalid.
+-   */
+-  static void validateRotation(int rotation) {
+-    if (rotation != 0 && rotation != 90 && rotation != 180 && rotation != 270) {
+-      throw new IllegalArgumentException(
+-          "Rotation value " + rotation + " is not valid. Use only 0, 90, 180 or 270.");
++
++    /**
++     * Validates rotation values for builders. Only supports 0, 90, 180, 270.
++     *
++     * @throws IllegalArgumentException if the rotation value is invalid.
++     */
++    static void validateRotation(int rotation) {
++        if (rotation != 0 && rotation != 90 && rotation != 180 && rotation != 270) {
++            throw new IllegalArgumentException(
++                    "Rotation value " + rotation + " is not valid. Use only 0, 90, 180 or 270.");
++        }
+     }
+-  }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java
+index 44eb1198884fa..8408a0e424a9b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java
+@@ -16,39 +16,37 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.graphics.Bitmap;
+-import java.nio.ByteBuffer;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ 
++import java.nio.ByteBuffer;
++
+ /** Unit test for {@link BitmapExtractor}. */
+ @RunWith(RobolectricTestRunner.class)
+ public class BitmapExtractorTest {
++    @Test
++    public void extract_fromBitmap_succeeds() {
++        Bitmap bitmap = TestImageCreator.createRgbaBitmap();
++        MlImage image = new BitmapMlImageBuilder(bitmap).build();
++
++        Bitmap result = BitmapExtractor.extract(image);
++
++        assertThat(result).isSameInstanceAs(bitmap);
++    }
++
++    @Test
++    public void extract_fromByteBuffer_throwsException() {
++        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
++                                .build();
+ 
+-  @Test
+-  public void extract_fromBitmap_succeeds() {
+-    Bitmap bitmap = TestImageCreator.createRgbaBitmap();
+-    MlImage image = new BitmapMlImageBuilder(bitmap).build();
+-
+-    Bitmap result = BitmapExtractor.extract(image);
+-
+-    assertThat(result).isSameInstanceAs(bitmap);
+-  }
+-
+-  @Test
+-  public void extract_fromByteBuffer_throwsException() {
+-    ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                buffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGB)
+-            .build();
+-
+-    assertThrows(IllegalArgumentException.class, () -> BitmapExtractor.extract(image));
+-  }
++        assertThrows(IllegalArgumentException.class, () -> BitmapExtractor.extract(image));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java
+index f9908210f2970..9a4051cdf8f6a 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java
+@@ -16,11 +16,13 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.Bitmap.Config;
+ import android.graphics.Rect;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+@@ -28,63 +30,59 @@ import org.robolectric.RobolectricTestRunner;
+ /** Tests for {@link BitmapMlImageBuilder} */
+ @RunWith(RobolectricTestRunner.class)
+ public final class BitmapMlImageBuilderTest {
+-
+-  @Test
+-  public void build_fromBitmap_succeeds() {
+-    Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+-
+-    MlImage image = new BitmapMlImageBuilder(bitmap).build();
+-    ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP);
+-
+-    assertThat(image.getWidth()).isEqualTo(20);
+-    assertThat(image.getHeight()).isEqualTo(25);
+-    assertThat(image.getContainedImageProperties())
+-        .containsExactly(
+-            ImageProperties.builder()
+-                .setImageFormat(MlImage.IMAGE_FORMAT_RGBA)
+-                .setStorageType(MlImage.STORAGE_TYPE_BITMAP)
+-                .build());
+-    assertThat(((BitmapImageContainer) container).getBitmap().getConfig())
+-        .isEqualTo(Config.ARGB_8888);
+-  }
+-
+-  @Test
+-  public void build_withOptionalProperties_succeeds() {
+-    Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+-
+-    MlImage image =
+-        new BitmapMlImageBuilder(bitmap)
+-            .setRoi(new Rect(0, 5, 10, 15))
+-            .setRotation(90)
+-            .setTimestamp(12345)
+-            .build();
+-
+-    assertThat(image.getTimestamp()).isEqualTo(12345);
+-    assertThat(image.getRotation()).isEqualTo(90);
+-    assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
+-  }
+-
+-  @Test
+-  public void build_withInvalidRotation_throwsException() {
+-    Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+-    BitmapMlImageBuilder builder = new BitmapMlImageBuilder(bitmap);
+-
+-    assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
+-  }
+-
+-  @Test
+-  public void release_recyclesBitmap() {
+-    Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+-
+-    MlImage image =
+-        new BitmapMlImageBuilder(bitmap)
+-            .setRoi(new Rect(0, 5, 10, 15))
+-            .setRotation(90)
+-            .setTimestamp(12345)
+-            .build();
+-    assertThat(bitmap.isRecycled()).isFalse();
+-    image.close();
+-
+-    assertThat(bitmap.isRecycled()).isTrue();
+-  }
++    @Test
++    public void build_fromBitmap_succeeds() {
++        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
++
++        MlImage image = new BitmapMlImageBuilder(bitmap).build();
++        ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP);
++
++        assertThat(image.getWidth()).isEqualTo(20);
++        assertThat(image.getHeight()).isEqualTo(25);
++        assertThat(image.getContainedImageProperties())
++                .containsExactly(ImageProperties.builder()
++                                         .setImageFormat(MlImage.IMAGE_FORMAT_RGBA)
++                                         .setStorageType(MlImage.STORAGE_TYPE_BITMAP)
++                                         .build());
++        assertThat(((BitmapImageContainer) container).getBitmap().getConfig())
++                .isEqualTo(Config.ARGB_8888);
++    }
++
++    @Test
++    public void build_withOptionalProperties_succeeds() {
++        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
++
++        MlImage image = new BitmapMlImageBuilder(bitmap)
++                                .setRoi(new Rect(0, 5, 10, 15))
++                                .setRotation(90)
++                                .setTimestamp(12345)
++                                .build();
++
++        assertThat(image.getTimestamp()).isEqualTo(12345);
++        assertThat(image.getRotation()).isEqualTo(90);
++        assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
++    }
++
++    @Test
++    public void build_withInvalidRotation_throwsException() {
++        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
++        BitmapMlImageBuilder builder = new BitmapMlImageBuilder(bitmap);
++
++        assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
++    }
++
++    @Test
++    public void release_recyclesBitmap() {
++        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
++
++        MlImage image = new BitmapMlImageBuilder(bitmap)
++                                .setRoi(new Rect(0, 5, 10, 15))
++                                .setRotation(90)
++                                .setTimestamp(12345)
++                                .build();
++        assertThat(bitmap.isRecycled()).isFalse();
++        image.close();
++
++        assertThat(bitmap.isRecycled()).isTrue();
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java
+index 2ff49010443a5..e675ba9abd479 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java
+@@ -16,15 +16,18 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.graphics.Bitmap;
+-import java.nio.Buffer;
+-import java.nio.ByteBuffer;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ 
++import java.nio.Buffer;
++import java.nio.ByteBuffer;
++
+ /**
+  * Tests for {@link ByteBufferExtractor}.
+  *
+@@ -35,145 +38,120 @@ import org.robolectric.RobolectricTestRunner;
+  */
+ @RunWith(RobolectricTestRunner.class)
+ public final class ByteBufferExtractorTest {
+-
+-  @Test
+-  public void extract_fromByteBuffer_succeeds() {
+-    ByteBuffer byteBuffer = TestImageCreator.createRgbBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                byteBuffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGB)
+-            .build();
+-
+-    ByteBuffer result = ByteBufferExtractor.extract(image);
+-
+-    assertThat(result).isEquivalentAccordingToCompareTo(byteBuffer);
+-    assertThat(result.isReadOnly()).isTrue();
+-  }
+-
+-  @Test
+-  public void extract_fromBitmap_throws() {
+-    Bitmap rgbaBitmap = TestImageCreator.createRgbaBitmap();
+-    MlImage image = new BitmapMlImageBuilder(rgbaBitmap).build();
+-
+-    assertThrows(IllegalArgumentException.class, () -> ByteBufferExtractor.extract(image));
+-  }
+-
+-  @Test
+-  public void extract_rgbFromRgbByteBuffer_succeeds() {
+-    ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                buffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGB)
+-            .build();
+-
+-    ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+-
+-    assertThat(result.isReadOnly()).isTrue();
+-    assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
+-  }
+-
+-  @Test
+-  public void extract_rgbFromRgbaByteBuffer_succeeds() {
+-    ByteBuffer buffer = TestImageCreator.createRgbaBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                buffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGBA)
+-            .build();
+-
+-    ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+-
+-    assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
+-    assertThat(buffer.position()).isEqualTo(0);
+-  }
+-
+-  @Test
+-  public void extract_rgbaFromRgbByteBuffer_succeeds() {
+-    ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                buffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGB)
+-            .build();
+-
+-    ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGBA);
+-
+-    assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createOpaqueRgbaBuffer());
+-    assertThat(buffer.position()).isEqualTo(0);
+-  }
+-
+-  @Test
+-  public void extract_rgbFromRgbaBitmap_succeeds() {
+-    Bitmap rgbaBitmap = TestImageCreator.createRgbaBitmap();
+-    MlImage image = new BitmapMlImageBuilder(rgbaBitmap).build();
+-
+-    ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+-
+-    assertThat(result.isReadOnly()).isTrue();
+-    assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
+-
+-    // Verifies ByteBuffer is cached inside MlImage.
+-    ByteBufferImageContainer byteBufferImageContainer =
+-        (ByteBufferImageContainer) image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
+-    assertThat(byteBufferImageContainer.getByteBuffer()).isEqualTo(result);
+-    assertThat(byteBufferImageContainer.getImageFormat()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+-
+-    // Verifies that extracted ByteBuffer is the cached one.
+-    ByteBuffer result2 = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+-    assertThat(result2).isEqualTo(result);
+-  }
+-
+-  @Test
+-  public void extract_unsupportedFormatFromByteBuffer_throws() {
+-    ByteBuffer buffer = TestImageCreator.createRgbaBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                buffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGBA)
+-            .build();
+-
+-    assertThrows(
+-        IllegalArgumentException.class,
+-        () -> ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_YUV_420_888));
+-  }
+-
+-  @Test
+-  public void extractInRecommendedFormat_anyFormatFromRgbByteBuffer_succeeds() {
+-    ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(
+-                buffer,
+-                TestImageCreator.getWidth(),
+-                TestImageCreator.getHeight(),
+-                MlImage.IMAGE_FORMAT_RGB)
+-            .build();
+-
+-    ByteBufferExtractor.Result result = ByteBufferExtractor.extractInRecommendedFormat(image);
+-
+-    assertThat(result.buffer().isReadOnly()).isTrue();
+-    assertThat(result.format()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+-
+-    // Verifies ByteBuffer is cached inside MlImage.
+-    ByteBufferImageContainer byteBufferImageContainer =
+-        (ByteBufferImageContainer) image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
+-    assertThat(byteBufferImageContainer.getByteBuffer()).isEqualTo(result.buffer());
+-    assertThat(byteBufferImageContainer.getImageFormat()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+-
+-    // Verifies that extracted ByteBuffer is the cached one.
+-    ByteBufferExtractor.Result result2 = ByteBufferExtractor.extractInRecommendedFormat(image);
+-    assertThat(result2.buffer()).isEqualTo(result.buffer());
+-    assertThat(result2.format()).isEqualTo(result.format());
+-  }
++    @Test
++    public void extract_fromByteBuffer_succeeds() {
++        ByteBuffer byteBuffer = TestImageCreator.createRgbBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(byteBuffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
++                                .build();
++
++        ByteBuffer result = ByteBufferExtractor.extract(image);
++
++        assertThat(result).isEquivalentAccordingToCompareTo(byteBuffer);
++        assertThat(result.isReadOnly()).isTrue();
++    }
++
++    @Test
++    public void extract_fromBitmap_throws() {
++        Bitmap rgbaBitmap = TestImageCreator.createRgbaBitmap();
++        MlImage image = new BitmapMlImageBuilder(rgbaBitmap).build();
++
++        assertThrows(IllegalArgumentException.class, () -> ByteBufferExtractor.extract(image));
++    }
++
++    @Test
++    public void extract_rgbFromRgbByteBuffer_succeeds() {
++        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
++                                .build();
++
++        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
++
++        assertThat(result.isReadOnly()).isTrue();
++        assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
++    }
++
++    @Test
++    public void extract_rgbFromRgbaByteBuffer_succeeds() {
++        ByteBuffer buffer = TestImageCreator.createRgbaBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGBA)
++                                .build();
++
++        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
++
++        assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
++        assertThat(buffer.position()).isEqualTo(0);
++    }
++
++    @Test
++    public void extract_rgbaFromRgbByteBuffer_succeeds() {
++        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
++                                .build();
++
++        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGBA);
++
++        assertThat(result).isEquivalentAccordingToCompareTo(
++                TestImageCreator.createOpaqueRgbaBuffer());
++        assertThat(buffer.position()).isEqualTo(0);
++    }
++
++    @Test
++    public void extract_rgbFromRgbaBitmap_succeeds() {
++        Bitmap rgbaBitmap = TestImageCreator.createRgbaBitmap();
++        MlImage image = new BitmapMlImageBuilder(rgbaBitmap).build();
++
++        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
++
++        assertThat(result.isReadOnly()).isTrue();
++        assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
++
++        // Verifies ByteBuffer is cached inside MlImage.
++        ByteBufferImageContainer byteBufferImageContainer =
++                (ByteBufferImageContainer) image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
++        assertThat(byteBufferImageContainer.getByteBuffer()).isEqualTo(result);
++        assertThat(byteBufferImageContainer.getImageFormat()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
++
++        // Verifies that extracted ByteBuffer is the cached one.
++        ByteBuffer result2 = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
++        assertThat(result2).isEqualTo(result);
++    }
++
++    @Test
++    public void extract_unsupportedFormatFromByteBuffer_throws() {
++        ByteBuffer buffer = TestImageCreator.createRgbaBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGBA)
++                                .build();
++
++        assertThrows(IllegalArgumentException.class,
++                () -> ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_YUV_420_888));
++    }
++
++    @Test
++    public void extractInRecommendedFormat_anyFormatFromRgbByteBuffer_succeeds() {
++        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
++        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
++                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
++                                .build();
++
++        ByteBufferExtractor.Result result = ByteBufferExtractor.extractInRecommendedFormat(image);
++
++        assertThat(result.buffer().isReadOnly()).isTrue();
++        assertThat(result.format()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
++
++        // Verifies ByteBuffer is cached inside MlImage.
++        ByteBufferImageContainer byteBufferImageContainer =
++                (ByteBufferImageContainer) image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
++        assertThat(byteBufferImageContainer.getByteBuffer()).isEqualTo(result.buffer());
++        assertThat(byteBufferImageContainer.getImageFormat()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
++
++        // Verifies that extracted ByteBuffer is the cached one.
++        ByteBufferExtractor.Result result2 = ByteBufferExtractor.extractInRecommendedFormat(image);
++        assertThat(result2.buffer()).isEqualTo(result.buffer());
++        assertThat(result2.format()).isEqualTo(result.format());
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java
+index 45ba77934a61f..374c82b3f4e8d 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java
+@@ -16,61 +16,62 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ 
+ import android.graphics.Rect;
+-import java.nio.ByteBuffer;
++
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+ import org.robolectric.RobolectricTestRunner;
+ 
++import java.nio.ByteBuffer;
++
+ /** Tests for {@link ByteBufferMlImageBuilder} */
+ @RunWith(RobolectricTestRunner.class)
+ public final class ByteBufferMlImageBuilderTest {
++    @Test
++    public void build_fromByteBuffer_succeeds() {
++        ByteBuffer buffer = ByteBuffer.allocate(500);
++
++        MlImage image =
++                new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB).build();
++        ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
++
++        assertThat(image.getWidth()).isEqualTo(20);
++        assertThat(image.getHeight()).isEqualTo(25);
++        assertThat(image.getRoi()).isEqualTo(new Rect(0, 0, 20, 25));
++        assertThat(image.getRotation()).isEqualTo(0);
++        assertThat(image.getContainedImageProperties())
++                .containsExactly(ImageProperties.builder()
++                                         .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
++                                         .setImageFormat(MlImage.IMAGE_FORMAT_RGB)
++                                         .build());
++        assertThat(((ByteBufferImageContainer) container).getImageFormat())
++                .isEqualTo(MlImage.IMAGE_FORMAT_RGB);
++    }
++
++    @Test
++    public void build_withOptionalProperties_succeeds() {
++        ByteBuffer buffer = ByteBuffer.allocate(500);
++
++        MlImage image = new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB)
++                                .setRoi(new Rect(0, 5, 10, 15))
++                                .setRotation(90)
++                                .setTimestamp(12345)
++                                .build();
++
++        assertThat(image.getTimestamp()).isEqualTo(12345);
++        assertThat(image.getRotation()).isEqualTo(90);
++        assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
++    }
++
++    @Test
++    public void build_withInvalidRotation_throwsException() {
++        ByteBuffer buffer = ByteBuffer.allocate(500);
++        ByteBufferMlImageBuilder builder =
++                new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB);
+ 
+-  @Test
+-  public void build_fromByteBuffer_succeeds() {
+-    ByteBuffer buffer = ByteBuffer.allocate(500);
+-
+-    MlImage image = new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB).build();
+-    ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
+-
+-    assertThat(image.getWidth()).isEqualTo(20);
+-    assertThat(image.getHeight()).isEqualTo(25);
+-    assertThat(image.getRoi()).isEqualTo(new Rect(0, 0, 20, 25));
+-    assertThat(image.getRotation()).isEqualTo(0);
+-    assertThat(image.getContainedImageProperties())
+-        .containsExactly(
+-            ImageProperties.builder()
+-                .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
+-                .setImageFormat(MlImage.IMAGE_FORMAT_RGB)
+-                .build());
+-    assertThat(((ByteBufferImageContainer) container).getImageFormat())
+-        .isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+-  }
+-
+-  @Test
+-  public void build_withOptionalProperties_succeeds() {
+-    ByteBuffer buffer = ByteBuffer.allocate(500);
+-
+-    MlImage image =
+-        new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB)
+-            .setRoi(new Rect(0, 5, 10, 15))
+-            .setRotation(90)
+-            .setTimestamp(12345)
+-            .build();
+-
+-    assertThat(image.getTimestamp()).isEqualTo(12345);
+-    assertThat(image.getRotation()).isEqualTo(90);
+-    assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
+-  }
+-
+-  @Test
+-  public void build_withInvalidRotation_throwsException() {
+-    ByteBuffer buffer = ByteBuffer.allocate(500);
+-    ByteBufferMlImageBuilder builder =
+-        new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB);
+-
+-    assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
+-  }
++        assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java
+index 67ed4a7f6e2c4..fa832671e4458 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java
+@@ -16,6 +16,7 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.mockito.Mockito.when;
+ 
+@@ -23,6 +24,7 @@ import android.graphics.Bitmap;
+ import android.graphics.Bitmap.Config;
+ import android.graphics.ImageFormat;
+ import android.media.Image;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -33,34 +35,34 @@ import org.robolectric.RobolectricTestRunner;
+ /** Tests for {@link MediaImageExtractor} */
+ @RunWith(RobolectricTestRunner.class)
+ public final class MediaImageExtractorTest {
+-  private static final int HEIGHT = 100;
+-  private static final int WIDTH = 50;
++    private static final int HEIGHT = 100;
++    private static final int WIDTH = 50;
+ 
+-  @Mock private Image mediaImage;
++    @Mock
++    private Image mediaImage;
+ 
+-  @Before
+-  public void setUp() {
+-    MockitoAnnotations.initMocks(this);
++    @Before
++    public void setUp() {
++        MockitoAnnotations.initMocks(this);
+ 
+-    when(mediaImage.getHeight()).thenReturn(HEIGHT);
+-    when(mediaImage.getWidth()).thenReturn(WIDTH);
+-    when(mediaImage.getFormat()).thenReturn(ImageFormat.YUV_420_888);
+-  }
++        when(mediaImage.getHeight()).thenReturn(HEIGHT);
++        when(mediaImage.getWidth()).thenReturn(WIDTH);
++        when(mediaImage.getFormat()).thenReturn(ImageFormat.YUV_420_888);
++    }
+ 
+-  @Test
+-  public void extract_fromMediaMlImage_succeeds() {
+-    MlImage image = new MediaMlImageBuilder(mediaImage).build();
+-    Image extractedMediaImage = MediaImageExtractor.extract(image);
++    @Test
++    public void extract_fromMediaMlImage_succeeds() {
++        MlImage image = new MediaMlImageBuilder(mediaImage).build();
++        Image extractedMediaImage = MediaImageExtractor.extract(image);
+ 
+-    assertThat(extractedMediaImage).isSameInstanceAs(image);
+-  }
++        assertThat(extractedMediaImage).isSameInstanceAs(image);
++    }
+ 
+-  @Test
+-  public void extract_fromBitmapMlImage_throwsException() {
+-    MlImage image =
+-        new BitmapMlImageBuilder(
++    @Test
++    public void extract_fromBitmapMlImage_throwsException() {
++        MlImage image = new BitmapMlImageBuilder(
+                 Bitmap.createBitmap(/* width= */ 20, /* height= */ 25, Config.ARGB_8888))
+-            .build();
+-    assertThrows(IllegalArgumentException.class, () -> MediaImageExtractor.extract(image));
+-  }
++                                .build();
++        assertThrows(IllegalArgumentException.class, () -> MediaImageExtractor.extract(image));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java
+index 4f589874bfaf8..60397feceb067 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java
+@@ -16,12 +16,14 @@ limitations under the License.
+ package com.google.android.odml.image;
+ 
+ import static com.google.common.truth.Truth.assertThat;
++
+ import static org.junit.Assert.assertThrows;
+ import static org.mockito.Mockito.when;
+ 
+ import android.graphics.ImageFormat;
+ import android.graphics.Rect;
+ import android.media.Image;
++
+ import org.junit.Before;
+ import org.junit.Test;
+ import org.junit.runner.RunWith;
+@@ -32,58 +34,57 @@ import org.robolectric.RobolectricTestRunner;
+ /** Tests for {@link MediaMlImageBuilder} */
+ @RunWith(RobolectricTestRunner.class)
+ public final class MediaMlImageBuilderTest {
+-  private static final int HEIGHT = 100;
+-  private static final int WIDTH = 50;
+-
+-  @Mock private Image mediaImage;
+-
+-  @Before
+-  public void setUp() {
+-    MockitoAnnotations.initMocks(this);
+-
+-    when(mediaImage.getHeight()).thenReturn(HEIGHT);
+-    when(mediaImage.getWidth()).thenReturn(WIDTH);
+-    when(mediaImage.getFormat()).thenReturn(ImageFormat.YUV_420_888);
+-  }
+-
+-  @Test
+-  public void build_fromMediaImage_succeeds() {
+-    MlImage image = new MediaMlImageBuilder(mediaImage).build();
+-    ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_MEDIA_IMAGE);
+-
+-    assertThat(image.getWidth()).isEqualTo(WIDTH);
+-    assertThat(image.getHeight()).isEqualTo(HEIGHT);
+-    assertThat(image.getRoi()).isEqualTo(new Rect(0, 0, WIDTH, HEIGHT));
+-    assertThat(image.getRotation()).isEqualTo(0);
+-    assertThat(image.getTimestamp()).isAtLeast(0);
+-    assertThat(image.getContainedImageProperties())
+-        .containsExactly(
+-            ImageProperties.builder()
+-                .setStorageType(MlImage.STORAGE_TYPE_MEDIA_IMAGE)
+-                .setImageFormat(MlImage.IMAGE_FORMAT_YUV_420_888)
+-                .build());
+-    assertThat(((MediaImageContainer) container).getImage().getFormat())
+-        .isEqualTo(ImageFormat.YUV_420_888);
+-  }
+-
+-  @Test
+-  public void build_withOptionalProperties_succeeds() {
+-    MlImage image =
+-        new MediaMlImageBuilder(mediaImage)
+-            .setTimestamp(12345)
+-            .setRoi(new Rect(0, 5, 10, 15))
+-            .setRotation(90)
+-            .build();
+-
+-    assertThat(image.getTimestamp()).isEqualTo(12345);
+-    assertThat(image.getRotation()).isEqualTo(90);
+-    assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
+-  }
+-
+-  @Test
+-  public void build_withInvalidRotation_throwsException() {
+-    MediaMlImageBuilder builder = new MediaMlImageBuilder(mediaImage);
+-
+-    assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
+-  }
++    private static final int HEIGHT = 100;
++    private static final int WIDTH = 50;
++
++    @Mock
++    private Image mediaImage;
++
++    @Before
++    public void setUp() {
++        MockitoAnnotations.initMocks(this);
++
++        when(mediaImage.getHeight()).thenReturn(HEIGHT);
++        when(mediaImage.getWidth()).thenReturn(WIDTH);
++        when(mediaImage.getFormat()).thenReturn(ImageFormat.YUV_420_888);
++    }
++
++    @Test
++    public void build_fromMediaImage_succeeds() {
++        MlImage image = new MediaMlImageBuilder(mediaImage).build();
++        ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_MEDIA_IMAGE);
++
++        assertThat(image.getWidth()).isEqualTo(WIDTH);
++        assertThat(image.getHeight()).isEqualTo(HEIGHT);
++        assertThat(image.getRoi()).isEqualTo(new Rect(0, 0, WIDTH, HEIGHT));
++        assertThat(image.getRotation()).isEqualTo(0);
++        assertThat(image.getTimestamp()).isAtLeast(0);
++        assertThat(image.getContainedImageProperties())
++                .containsExactly(ImageProperties.builder()
++                                         .setStorageType(MlImage.STORAGE_TYPE_MEDIA_IMAGE)
++                                         .setImageFormat(MlImage.IMAGE_FORMAT_YUV_420_888)
++                                         .build());
++        assertThat(((MediaImageContainer) container).getImage().getFormat())
++                .isEqualTo(ImageFormat.YUV_420_888);
++    }
++
++    @Test
++    public void build_withOptionalProperties_succeeds() {
++        MlImage image = new MediaMlImageBuilder(mediaImage)
++                                .setTimestamp(12345)
++                                .setRoi(new Rect(0, 5, 10, 15))
++                                .setRotation(90)
++                                .build();
++
++        assertThat(image.getTimestamp()).isEqualTo(12345);
++        assertThat(image.getRotation()).isEqualTo(90);
++        assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
++    }
++
++    @Test
++    public void build_withInvalidRotation_throwsException() {
++        MediaMlImageBuilder builder = new MediaMlImageBuilder(mediaImage);
++
++        assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
++    }
+ }
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java
+index c9e7134bedd93..28f54be2c70a3 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java
++++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java
+@@ -17,6 +17,7 @@ package com.google.android.odml.image;
+ 
+ import android.graphics.Bitmap;
+ import android.graphics.Color;
++
+ import java.nio.ByteBuffer;
+ 
+ /**
+@@ -35,113 +36,113 @@ import java.nio.ByteBuffer;
+  * <p>The created {@link Bitmap} is not pre-multiplied.
+  */
+ final class TestImageCreator {
++    private static final int RED = 0x73;
++    private static final int GREEN = 0x85;
++    private static final int BLUE = 0x96;
++    private static final int ALPHA = 0x70;
++
++    static int getWidth() {
++        return 10;
++    }
++
++    static int getHeight() {
++        return 2;
++    }
++
++    /**
++     * Creates an example non-pre-multiplied bitmap which is 100% opaque.
++     *
++     * @see TestImageCreator for details.
++     */
++    static Bitmap createOpaqueRgbaBitmap() {
++        return createRgbaBitmap(0xff);
++    }
++
++    /**
++     * Creates an example non-pre-multiplied bitmap which has non-trivial alpha channel.
++     *
++     * @see TestImageCreator for details.
++     */
++    static Bitmap createRgbaBitmap() {
++        return createRgbaBitmap(ALPHA);
++    }
+ 
+-  private static final int RED = 0x73;
+-  private static final int GREEN = 0x85;
+-  private static final int BLUE = 0x96;
+-  private static final int ALPHA = 0x70;
+-
+-  static int getWidth() {
+-    return 10;
+-  }
+-
+-  static int getHeight() {
+-    return 2;
+-  }
+-
+-  /**
+-   * Creates an example non-pre-multiplied bitmap which is 100% opaque.
+-   *
+-   * @see TestImageCreator for details.
+-   */
+-  static Bitmap createOpaqueRgbaBitmap() {
+-    return createRgbaBitmap(0xff);
+-  }
+-
+-  /**
+-   * Creates an example non-pre-multiplied bitmap which has non-trivial alpha channel.
+-   *
+-   * @see TestImageCreator for details.
+-   */
+-  static Bitmap createRgbaBitmap() {
+-    return createRgbaBitmap(ALPHA);
+-  }
+-
+-  /**
+-   * Creates an example 10x2 bitmap demonstrated in the class doc. A channel sets to {@code alpha}.
+-   */
+-  static Bitmap createRgbaBitmap(int alpha) {
+-    int[] colors = new int[20];
+-    for (int i = 0; i < 5; i++) {
+-      colors[i] = Color.argb(alpha, 0, 0, BLUE);
+-      colors[i + 5] = Color.argb(alpha, 0xff, 0xff, 0xff);
+-      colors[i + 10] = Color.argb(alpha, 0, GREEN, 0);
+-      colors[i + 15] = Color.argb(alpha, RED, 0, 0);
++    /**
++     * Creates an example 10x2 bitmap demonstrated in the class doc. A channel sets to {@code
++     * alpha}.
++     */
++    static Bitmap createRgbaBitmap(int alpha) {
++        int[] colors = new int[20];
++        for (int i = 0; i < 5; i++) {
++            colors[i] = Color.argb(alpha, 0, 0, BLUE);
++            colors[i + 5] = Color.argb(alpha, 0xff, 0xff, 0xff);
++            colors[i + 10] = Color.argb(alpha, 0, GREEN, 0);
++            colors[i + 15] = Color.argb(alpha, RED, 0, 0);
++        }
++        // We don't use Bitmap#createBitmap(int[] ...) here, because that method creates
++        // pre-multiplied bitmaps.
++        Bitmap bitmap = Bitmap.createBitmap(10, 2, Bitmap.Config.ARGB_8888);
++        bitmap.setPremultiplied(false);
++        bitmap.setPixels(colors, 0, 10, 0, 0, 10, 2);
++        return bitmap;
+     }
+-    // We don't use Bitmap#createBitmap(int[] ...) here, because that method creates pre-multiplied
+-    // bitmaps.
+-    Bitmap bitmap = Bitmap.createBitmap(10, 2, Bitmap.Config.ARGB_8888);
+-    bitmap.setPremultiplied(false);
+-    bitmap.setPixels(colors, 0, 10, 0, 0, 10, 2);
+-    return bitmap;
+-  }
+-
+-  /**
+-   * Creates an example 10*10*3 bytebuffer in R-G-B format.
+-   *
+-   * @see TestImageCreator for details.
+-   */
+-  static ByteBuffer createRgbBuffer() {
+-    return createRgbOrRgbaBuffer(false, 0xff);
+-  }
+-
+-  /**
+-   * Creates an example 10*10*4 bytebuffer in R-G-B-A format.
+-   *
+-   * @see TestImageCreator for details.
+-   */
+-  static ByteBuffer createRgbaBuffer() {
+-    return createRgbOrRgbaBuffer(true, ALPHA);
+-  }
+-
+-  /**
+-   * Creates an example 10*10*4 bytebuffer in R-G-B-A format, but the A channel is 0xFF.
+-   *
+-   * @see TestImageCreator for details.
+-   */
+-  static ByteBuffer createOpaqueRgbaBuffer() {
+-    return createRgbOrRgbaBuffer(true, 0xff);
+-  }
+-
+-  /**
+-   * Creates an example 10x2x4 (or 10x2x3 if no alpha) bytebuffer demonstrated in the class doc.
+-   *
+-   * @param withAlpha if true, set A to {@code alpha}, otherwise A channel is ignored.
+-   * @param alpha alpha channel value. Only effective when {@code withAlpha} is {@code true}.
+-   */
+-  static ByteBuffer createRgbOrRgbaBuffer(boolean withAlpha, int alpha) {
+-    int capacity = withAlpha ? 80 : 60;
+-    ByteBuffer buffer = ByteBuffer.allocateDirect(capacity);
+-    putColorInByteBuffer(buffer, 0, 0, BLUE, withAlpha, alpha, 5);
+-    putColorInByteBuffer(buffer, 0xff, 0xff, 0xff, withAlpha, alpha, 5);
+-    putColorInByteBuffer(buffer, 0, GREEN, 0, withAlpha, alpha, 5);
+-    putColorInByteBuffer(buffer, RED, 0, 0, withAlpha, alpha, 5);
+-    buffer.rewind();
+-    return buffer;
+-  }
+-
+-  private static void putColorInByteBuffer(
+-      ByteBuffer buffer, int r, int g, int b, boolean withAlpha, int alpha, int num) {
+-    for (int i = 0; i < num; i++) {
+-      buffer.put((byte) r);
+-      buffer.put((byte) g);
+-      buffer.put((byte) b);
+-      if (withAlpha) {
+-        buffer.put((byte) alpha);
+-      }
++
++    /**
++     * Creates an example 10*10*3 bytebuffer in R-G-B format.
++     *
++     * @see TestImageCreator for details.
++     */
++    static ByteBuffer createRgbBuffer() {
++        return createRgbOrRgbaBuffer(false, 0xff);
++    }
++
++    /**
++     * Creates an example 10*10*4 bytebuffer in R-G-B-A format.
++     *
++     * @see TestImageCreator for details.
++     */
++    static ByteBuffer createRgbaBuffer() {
++        return createRgbOrRgbaBuffer(true, ALPHA);
++    }
++
++    /**
++     * Creates an example 10*10*4 bytebuffer in R-G-B-A format, but the A channel is 0xFF.
++     *
++     * @see TestImageCreator for details.
++     */
++    static ByteBuffer createOpaqueRgbaBuffer() {
++        return createRgbOrRgbaBuffer(true, 0xff);
++    }
++
++    /**
++     * Creates an example 10x2x4 (or 10x2x3 if no alpha) bytebuffer demonstrated in the class doc.
++     *
++     * @param withAlpha if true, set A to {@code alpha}, otherwise A channel is ignored.
++     * @param alpha alpha channel value. Only effective when {@code withAlpha} is {@code true}.
++     */
++    static ByteBuffer createRgbOrRgbaBuffer(boolean withAlpha, int alpha) {
++        int capacity = withAlpha ? 80 : 60;
++        ByteBuffer buffer = ByteBuffer.allocateDirect(capacity);
++        putColorInByteBuffer(buffer, 0, 0, BLUE, withAlpha, alpha, 5);
++        putColorInByteBuffer(buffer, 0xff, 0xff, 0xff, withAlpha, alpha, 5);
++        putColorInByteBuffer(buffer, 0, GREEN, 0, withAlpha, alpha, 5);
++        putColorInByteBuffer(buffer, RED, 0, 0, withAlpha, alpha, 5);
++        buffer.rewind();
++        return buffer;
++    }
++
++    private static void putColorInByteBuffer(
++            ByteBuffer buffer, int r, int g, int b, boolean withAlpha, int alpha, int num) {
++        for (int i = 0; i < num; i++) {
++            buffer.put((byte) r);
++            buffer.put((byte) g);
++            buffer.put((byte) b);
++            if (withAlpha) {
++                buffer.put((byte) alpha);
++            }
++        }
+     }
+-  }
+ 
+-  // Should not be instantiated.
+-  private TestImageCreator() {}
++    // Should not be instantiated.
++    private TestImageCreator() {}
+ }
+diff --git a/third_party/tflite_support/src/third_party/fft2d/fft.h b/third_party/tflite_support/src/third_party/fft2d/fft.h
+index 36d838b7f6280..35dbcc766c169 100644
+--- a/third_party/tflite_support/src/third_party/fft2d/fft.h
++++ b/third_party/tflite_support/src/third_party/fft2d/fft.h
+@@ -22,12 +22,12 @@ limitations under the License.
+ extern "C" {
+ #endif
+ 
+-extern void cdft(int, int, double *, int *, double *);
+-extern void rdft(int, int, double *, int *, double *);
+-extern void ddct(int, int, double *, int *, double *);
+-extern void ddst(int, int, double *, int *, double *);
+-extern void dfct(int, double *, double *, int *, double *);
+-extern void dfst(int, double *, double *, int *, double *);
++extern void cdft(int, int, double*, int*, double*);
++extern void rdft(int, int, double*, int*, double*);
++extern void ddct(int, int, double*, int*, double*);
++extern void ddst(int, int, double*, int*, double*);
++extern void dfct(int, double*, double*, int*, double*);
++extern void dfst(int, double*, double*, int*, double*);
+ 
+ #ifdef __cplusplus
+ }
+diff --git a/third_party/tflite_support/src/third_party/fft2d/fft2d.h b/third_party/tflite_support/src/third_party/fft2d/fft2d.h
+index d587b3b441ce2..d79441827d54c 100644
+--- a/third_party/tflite_support/src/third_party/fft2d/fft2d.h
++++ b/third_party/tflite_support/src/third_party/fft2d/fft2d.h
+@@ -22,12 +22,12 @@ limitations under the License.
+ extern "C" {
+ #endif
+ 
+-extern void cdft2d(int, int, int, double **, double *, int *, double *);
+-extern void rdft2d(int, int, int, double **, double *, int *, double *);
+-extern void ddct2d(int, int, int, double **, double *, int *, double *);
+-extern void ddst2d(int, int, int, double **, double *, int *, double *);
+-extern void ddct8x8s(int isgn, double **a);
+-extern void ddct16x16s(int isgn, double **a);
++extern void cdft2d(int, int, int, double**, double*, int*, double*);
++extern void rdft2d(int, int, int, double**, double*, int*, double*);
++extern void ddct2d(int, int, int, double**, double*, int*, double*);
++extern void ddst2d(int, int, int, double**, double*, int*, double*);
++extern void ddct8x8s(int isgn, double** a);
++extern void ddct16x16s(int isgn, double** a);
+ 
+ #ifdef __cplusplus
+ }
+-- 
+2.34.1.307.g9b7440fafd-goog
+
diff --git a/third_party/tflite_support/patches/0012-rm-stdio-static-init.patch b/third_party/tflite_support/patches/0012-rm-stdio-static-init.patch
new file mode 100644
index 0000000..4562b6d
--- /dev/null
+++ b/third_party/tflite_support/patches/0012-rm-stdio-static-init.patch
@@ -0,0 +1,38 @@
+From f3ab1569fa4dfd69f74d1bb9c6d1c2c26e9215ce Mon Sep 17 00:00:00 2001
+From: Robert Ogden <robertogden@chromium.org>
+Date: Fri, 7 Jan 2022 09:30:06 -0800
+Subject: [PATCH] rm stdio static init
+
+---
+ .../cc/task/core/tflite_engine.cc                 | 15 ---------------
+ 1 file changed, 15 deletions(-)
+
+diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+index 0b34bad4f18f7..41e06389af80b 100644
+--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
++++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+@@ -32,21 +32,6 @@ namespace tflite {
+ namespace task {
+ namespace core {
+ 
+-#ifdef __ANDROID__
+-// https://github.com/opencv/opencv/issues/14906
+-// "ios_base::Init" object is not a part of Android's "iostream" header (in case
+-// of clang toolchain, NDK 20).
+-//
+-// Ref1:
+-// https://en.cppreference.com/w/cpp/io/ios_base/Init
+-//       The header <iostream> behaves as if it defines (directly or indirectly)
+-//       an instance of std::ios_base::Init with static storage duration
+-//
+-// Ref2:
+-// https://github.com/gcc-mirror/gcc/blob/gcc-8-branch/libstdc%2B%2B-v3/include/std/iostream#L73-L74
+-static std::ios_base::Init s_iostream_initializer;
+-#endif
+-
+ using ::absl::StatusCode;
+ using ::tflite::proto::ComputeSettings;
+ using ::tflite::support::CreateStatusWithPayload;
+-- 
+2.34.1.575.g55b058a8bb-goog
+
diff --git a/third_party/tflite_support/src/.bazelrc b/third_party/tflite_support/src/.bazelrc
new file mode 100644
index 0000000..02ba9da
--- /dev/null
+++ b/third_party/tflite_support/src/.bazelrc
@@ -0,0 +1,170 @@
+# This file is based on tensorflow's (v2.2.0) .bazelrc found here:
+# https://github.com/tensorflow/tensorflow/blob/v2.2.0/.bazelrc
+
+# Sets the default Apple platform to macOS.
+build:macos --apple_platform_type=macos
+
+# Flag to enable remote config. Required starting from TF 2.2.
+common --experimental_repo_remote_exec
+
+# For workaround https://github.com/bazelbuild/bazel/issues/8772 with Bazel >= 0.29.1
+build --java_toolchain=//third_party/toolchains/java:tf_java_toolchain
+build --host_java_toolchain=//third_party/toolchains/java:tf_java_toolchain
+
+# Suppress C++ compiler warnings, otherwise build logs become 10s of MBs.
+build:android --copt=-w
+build:linux --copt=-w
+build:macos --copt=-w
+build:windows --copt=/w
+
+# Android workspace configurations. Should be replaced by an interative configure in the future.
+build --action_env ANDROID_NDK_HOME
+build --action_env ANDROID_NDK_API_LEVEL
+build --action_env ANDROID_BUILD_TOOLS_VERSION
+build --action_env ANDROID_SDK_API_LEVEL
+build --action_env ANDROID_SDK_HOME
+
+# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
+# target CPU to build transient dependencies correctly. See
+# https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu
+
+build:android --crosstool_top=//external:android/crosstool
+build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
+build:android_arm --config=android
+build:android_arm --cpu=armeabi-v7a
+build:android_arm --fat_apk_cpu=armeabi-v7a
+build:android_arm64 --config=android
+build:android_arm64 --cpu=arm64-v8a
+build:android_arm64 --fat_apk_cpu=arm64-v8a
+build:android_x86 --config=android
+build:android_x86 --cpu=x86
+build:android_x86 --fat_apk_cpu=x86
+build:android_x86_64 --config=android
+build:android_x86_64 --cpu=x86_64
+build:android_x86_64 --fat_apk_cpu=x86_64
+
+# iOS configs for each architecture and the fat binary builds.
+build:ios --apple_platform_type=ios
+build:ios --apple_bitcode=embedded --copt=-fembed-bitcode
+build:ios --copt=-Wno-c++11-narrowing
+build:ios_armv7 --config=ios
+build:ios_armv7 --cpu=ios_armv7
+build:ios_arm64 --config=ios
+build:ios_arm64 --cpu=ios_arm64
+build:ios_x86_64 --config=ios
+build:ios_x86_64 --cpu=ios_x86_64
+build:ios_fat --config=ios
+build:ios_fat --ios_multi_cpus=armv7,arm64,x86_64
+
+# TFLite build configs for generic embedded Linux
+build:elinux --crosstool_top=@local_config_embedded_arm//:toolchain
+build:elinux --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
+build:elinux_aarch64 --config=elinux
+build:elinux_aarch64 --cpu=aarch64
+build:elinux_aarch64 --distinct_host_configuration=true
+build:elinux_armhf --config=elinux
+build:elinux_armhf --cpu=armhf
+build:elinux_armhf --distinct_host_configuration=true
+
+# By default, build TF in C++ 14 mode.
+build:android --cxxopt=-std=c++14
+build:android --host_cxxopt=-std=c++14
+build:ios --cxxopt=-std=c++14
+build:ios --host_cxxopt=-std=c++14
+build:linux --cxxopt=-std=c++14
+build:linux --host_cxxopt=-std=c++14
+build:macos --cxxopt=-std=c++14
+build:macos --host_cxxopt=-std=c++14
+build:windows --cxxopt=/std:c++14
+build:windows --host_cxxopt=/std:c++14
+
+# Config to use a mostly-static build and disable modular op registration
+# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
+# By default, TensorFlow will build with a dependence on
+# //tensorflow:libtensorflow_framework.so.
+build:monolithic --define framework_shared_object=false
+
+# For projects which use TensorFlow as part of a Bazel build process, putting
+# nothing in a bazelrc will default to a monolithic build. The following line
+# opts in to modular op registration support by default.
+build --define framework_shared_object=true
+
+# ASAN build
+build:asan --strip=never
+build:asan --copt -fsanitize=address
+build:asan --copt -DADDRESS_SANITIZER
+build:asan --copt -O1
+build:asan --copt -g
+build:asan --copt -fno-omit-frame-pointer
+build:asan --linkopt -fsanitize=address
+
+# dbg config, as a shorthand for '--config=opt -c dbg'
+build:dbg --config=opt -c dbg
+# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360
+build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON
+# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
+build:dbg --copt -DDEBUG_BUILD
+
+build --define=use_fast_cpp_protos=true
+build --define=allow_oversize_protos=true
+
+# TF uses `standalone`, which is deprecated.
+build --spawn_strategy=local
+build -c opt
+
+# Adding "--cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0" creates parity with TF
+# compilation options. It also addresses memory use due to
+# copy-on-write semantics of std::strings of the older ABI.
+build --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0
+
+# Make Bazel print out all options from rc files.
+build --announce_rc
+
+# Other build flags.
+build --define=grpc_no_ares=true
+
+# See https://github.com/bazelbuild/bazel/issues/7362 for information on what
+# --incompatible_remove_legacy_whole_archive flag does.
+# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
+# Tensorflow to the default, however test coverage wasn't enough to catch the
+# errors.
+# There is ongoing work on Bazel team's side to provide support for transitive
+# shared libraries. As part of migrating to transitive shared libraries, we
+# hope to provide a better mechanism for control over symbol exporting, and
+# then tackle this issue again.
+#
+# TODO: Remove this line once TF doesn't depend on Bazel wrapping all library
+# archives in -whole_archive -no_whole_archive.
+build --noincompatible_remove_legacy_whole_archive
+
+# These are bazel 2.0's incompatible flags. Tensorflow needs to use bazel 2.0.0
+# to use cc_shared_library, as part of the Tensorflow Build Improvements RFC:
+# https://github.com/tensorflow/community/pull/179
+build --noincompatible_prohibit_aapt1
+
+# Build TF with C++ 17 features.
+build:c++17 --cxxopt=-std=c++1z
+build:c++17 --cxxopt=-stdlib=libc++
+build:c++1z --config=c++17
+
+# Enable using platform specific build settings, except when cross-compiling for
+# mobile platforms.
+build --enable_platform_specific_config
+build:android --noenable_platform_specific_config
+build:ios --noenable_platform_specific_config
+
+# Suppress all warning messages.
+build:short_logs --output_filter=DONT_MATCH_ANYTHING
+build:verbose_logs --output_filter=
+build --config=short_logs
+
+# Options to build TensorFlow 1.x or 2.x.
+build:v1 --define=tf_api_version=1
+build:v2 --define=tf_api_version=2
+build:v1 --action_env=TF2_BEHAVIOR=0
+build:v2 --action_env=TF2_BEHAVIOR=1
+build --config=v2
+test --config=v2
+
+# Put user-specific options in .bazelrc.user
+try-import %workspace%/.bazelrc.user
diff --git a/third_party/tflite_support/src/.bazelversion b/third_party/tflite_support/src/.bazelversion
new file mode 100644
index 0000000..47b6be3f
--- /dev/null
+++ b/third_party/tflite_support/src/.bazelversion
@@ -0,0 +1 @@
+3.7.2
\ No newline at end of file
diff --git a/third_party/tflite_support/src/README.md b/third_party/tflite_support/src/README.md
index 67d4a8f..bab0201 100644
--- a/third_party/tflite_support/src/README.md
+++ b/third_party/tflite_support/src/README.md
@@ -5,8 +5,8 @@
 C++ (WIP), and Swift (WIP). The TFLite Support project consists of the following
 major components:
 
-*   **TFLite Support Library**: a cross-platform library that helps to
-    deploy TFLite models onto mobile devices.
+*   **TFLite Support Library**: a cross-platform library that helps to deploy
+    TFLite models onto mobile devices.
 *   **TFLite Model Metadata**: (metadata populator and metadata extractor
     library): includes both human and machine readable information about what a
     model does and how to use the model.
@@ -55,6 +55,11 @@
 *   `ANDROID_SDK_API_LEVEL`
 *   `ANDROID_BUILD_TOOLS_VERSION`
 
+## How to contribute
+
+Please issue a pull request and assign @xunkai55 or @lu-wang-g for a code
+review.
+
 ## Contact us
 
 Let us know what you think about TFLite Support by creating a
diff --git a/third_party/tflite_support/src/WORKSPACE b/third_party/tflite_support/src/WORKSPACE
index 33e44e8..c7834d3 100644
--- a/third_party/tflite_support/src/WORKSPACE
+++ b/third_party/tflite_support/src/WORKSPACE
@@ -1,9 +1,58 @@
 workspace(name = "org_tensorflow_lite_support")
 
 load("@bazel_tools//tools/build_defs/repo:java.bzl", "java_import_external")
-load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
+load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive", "http_file")
 load("@//third_party/py:python_configure.bzl", "python_configure")
 
+http_file(
+    name = "mobilebert_float",
+    sha256 = "883bf5d40f0b0ae435326bb21ed0f4c9004b22c3fd1539383fd16d68623696dd",
+    urls = ["https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1?lite-format=tflite"],
+)
+
+http_file(
+    name = "mobilebert_with_metadata",
+    sha256 = "e79d3c70108bbdee02da657b679349cab46dbb859a05b599c76b53d98e82f272",
+    urls = ["https://tfhub.dev/tensorflow/lite-model/mobilebert/1/metadata/1?lite-format=tflite"],
+)
+
+http_file(
+    name = "30k-clean",
+    sha256 = "fefb02b667a6c5c2fe27602d28e5fb3428f66ab89c7d6f388e7c8d44a02d0336",
+    urls = ["https://storage.googleapis.com/download.tensorflow.org/models/tflite_support/bert_qa/30k-clean.model"],
+)
+
+http_file(
+    name = "mobilebert_vocab",
+    sha256 = "07eced375cec144d27c900241f3e339478dec958f92fddbc551f295c992038a3",
+    urls = ["https://storage.googleapis.com/download.tensorflow.org/models/tflite_support/bert_qa/mobilebert_vocab.txt"],
+)
+
+
+http_file(
+    name = "albert",
+    sha256 = "4a29c7063c518925960229f49dd03e8da5d6682001cf73037815dcd98afd728a",
+    urls = ["https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1?lite-format=tflite"],
+)
+
+http_file(
+    name = "albert_with_metadata",
+    sha256 = "8a8a91856b94b945e4a9f22f0332bbf105c3b6b878bb23abfc97eb89d3e8436a",
+    urls = ["https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/metadata/1?lite-format=tflite"],
+)
+
+http_file(
+    name = "bert_nl_classifier",
+    sha256 = "1e5a550c09bff0a13e61858bcfac7654d7fcc6d42106b4f15e11117695069600",
+    urls = ["https://storage.googleapis.com/download.tensorflow.org/models/tflite_support/bert_nl_classifier/bert_nl_classifier.tflite"],
+)
+
+http_file(
+    name = "bert_nl_classifier_no_metadata",
+    sha256 = "9b4554f6e28a72a3f40511964eed1ccf4e74cc074f81543cacca4faf169a173e",
+    urls = ["https://storage.googleapis.com/download.tensorflow.org/models/tflite_support/bert_nl_classifier/bert_nl_classifier_no_metadata.tflite"],
+)
+
 http_archive(
     name = "io_bazel_rules_closure",
     sha256 = "5b00383d08dd71f28503736db0500b6fb4dda47489ff5fc6bed42557c07c6ba9",
@@ -14,6 +63,14 @@
     ],
 )
 
+# GoogleTest/GoogleMock framework. Used by most unit-tests.
+http_archive(
+    name = "com_google_googletest",
+    urls = ["https://github.com/google/googletest/archive/4ec4cd23f486bf70efcc5d2caa40f24368f752e3.zip"],
+    strip_prefix = "googletest-4ec4cd23f486bf70efcc5d2caa40f24368f752e3",
+    sha256 = "de682ea824bfffba05b4e33b67431c247397d6175962534305136aa06f92e049",
+)
+
 # Apple and Swift rules.
 # https://github.com/bazelbuild/rules_apple/releases
 http_archive(
@@ -37,15 +94,21 @@
     ],
 )
 
-# tf-nightly-20200810
+# TF on 2021-11-09.
+TENSORFLOW_COMMIT = "6a144e7763914d3f6141a7cdc9cb116cc23425f9"
+TENSORFLOW_SHA256 = "cec9a514c09d2b171ad447f3413151b25a6c3d88d048148cced1e85db81f3617"
 http_archive(
     name = "org_tensorflow",
-    sha256 = "fc6d7c57cd9427e695a38ad00fb6ecc3f623bac792dd44ad73a3f85b338b68be",
-    strip_prefix = "tensorflow-8a4ffe2e1ae722cff5306778df0cfca8b7f503fe",
+    sha256 = TENSORFLOW_SHA256,
+    strip_prefix = "tensorflow-" + TENSORFLOW_COMMIT,
     urls = [
-        "https://github.com/tensorflow/tensorflow/archive/8a4ffe2e1ae722cff5306778df0cfca8b7f503fe.tar.gz",
+        "https://github.com/tensorflow/tensorflow/archive/" + TENSORFLOW_COMMIT
+        + ".tar.gz",
     ],
-    patches = ["@//third_party:tensorflow_lite_ios_build.patch"],
+    patches = [
+        # We need to rename lite/ios/BUILD.apple to lite/ios/BUILD.
+        "@//third_party:tensorflow_lite_ios_build.patch",
+    ],
     patch_args = ["-p1"],
 )
 
@@ -60,11 +123,11 @@
 third_party_http_archive(
     name = "pybind11",
     urls = [
-        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/pybind/pybind11/archive/v2.4.3.tar.gz",
-        "https://github.com/pybind/pybind11/archive/v2.4.3.tar.gz",
+        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/pybind/pybind11/archive/v2.6.0.tar.gz",
+        "https://github.com/pybind/pybind11/archive/v2.6.0.tar.gz",
     ],
-    sha256 = "1eed57bc6863190e35637290f97a20c81cfe4d9090ac0a24f3bbf08f265eb71d",
-    strip_prefix = "pybind11-2.4.3",
+    sha256 = "90b705137b69ee3b5fc655eaca66d0dc9862ea1759226f7ccd3098425ae69571",
+    strip_prefix = "pybind11-2.6.0",
     build_file = "//third_party:pybind11.BUILD",
 )
 
@@ -119,13 +182,14 @@
     ],
 )
 
-# ABSL cpp library lts_2020_02_25
-# Needed for absl/status
+# ABSL cpp library lts_2021_03_24 Patch2
+# See https://github.com/abseil/abseil-cpp/releases for details.
+# Needed for absl/status and absl/status:statusor
 http_archive(
     name = "com_google_absl",
     build_file = "//third_party:com_google_absl.BUILD",
     urls = [
-        "https://github.com/abseil/abseil-cpp/archive/20200225.tar.gz",
+        "https://github.com/abseil/abseil-cpp/archive/20210324.2.tar.gz",
     ],
     # Remove after https://github.com/abseil/abseil-cpp/issues/326 is solved.
     patches = [
@@ -134,8 +198,8 @@
     patch_args = [
         "-p1",
     ],
-    strip_prefix = "abseil-cpp-20200225",
-    sha256 = "728a813291bdec2aa46eab8356ace9f75ac2ed9dfe2df5ab603c4e6c09f1c353"
+    strip_prefix = "abseil-cpp-20210324.2",
+    sha256 = "59b862f50e710277f8ede96f083a5bb8d7c9595376146838b9580be90374ee1f"
 )
 
 http_archive(
@@ -175,12 +239,12 @@
 
 http_archive(
     name = "libyuv",
-    urls = ["https://chromium.googlesource.com/libyuv/libyuv/+archive/6d603ec3f57dafddc424ef895e5d903915e94ba6.tar.gz"],
-    # Adding the constrain of sha256 and strip_prefix will cause failure.
-    # It seems that the downloaded libyuv was different every time, so that
-    # the specified sha256 and strip_prefix cannot match.
-    # sha256 = "ce196c72858456baa8022fa4a0dc18b77d619265dbc0e3d58e25ad15ca402522",
-    # strip_prefix = "libyuv-6d603ec3f57dafddc424ef895e5d903915e94ba6",
+    urls = ["https://chromium.googlesource.com/libyuv/libyuv/+archive/39240f7149cffde62e3620344d222c8ab2c21178.tar.gz"],
+    # Adding the constrain of sha256 and strip_prefix will cause failure as of
+    # Jan 2021. It seems that the downloaded libyuv was different every time,
+    # so that the specified sha256 and strip_prefix cannot match.
+    # sha256 = "01c2e30eb8e83880f9ba382f6bece9c38cd5b07f9cadae46ef1d5a69e07fafaf",
+    # strip_prefix = "libyuv-39240f7149cffde62e3620344d222c8ab2c21178",
     build_file = "//third_party:libyuv.BUILD",
 )
 
@@ -243,18 +307,18 @@
 )
 
 http_archive(
-    name = "com_google_protobuf",
-    sha256 = "a79d19dcdf9139fa4b81206e318e33d245c4c9da1ffed21c87288ed4380426f9",
-    strip_prefix = "protobuf-3.11.4",
-    urls = ["https://github.com/protocolbuffers/protobuf/archive/v3.11.4.tar.gz"],
-    patches = [
-        "@//third_party:com_google_protobuf_fixes.diff"
-    ],
-    patch_args = [
-        "-p1",
-    ],
+  name = "libedgetpu",
+  sha256 = "a179016a5874c58db969a5edd3fecf57610604e751b5c4d6d82ad58c383ffd64",
+  strip_prefix = "libedgetpu-ea1eaddbddece0c9ca1166e868f8fd03f4a3199e",
+  urls = [
+    "https://github.com/google-coral/libedgetpu/archive/ea1eaddbddece0c9ca1166e868f8fd03f4a3199e.tar.gz"
+  ],
 )
 
+# Set up TensorFlow version for Coral.
+load("@libedgetpu//:workspace.bzl", "libedgetpu_dependencies")
+libedgetpu_dependencies(TENSORFLOW_COMMIT, TENSORFLOW_SHA256)
+
 # AutoValue 1.6+ shades Guava, Auto Common, and JavaPoet. That's OK
 # because none of these jars become runtime dependencies.
 java_import_external(
@@ -317,12 +381,38 @@
     default_visibility = ["@com_google_auto_value//:__pkg__"],
 )
 
+http_archive(
+    name = "robolectric",
+    urls = ["https://github.com/robolectric/robolectric-bazel/archive/4.4.tar.gz"],
+    strip_prefix = "robolectric-bazel-4.4",
+)
+load("@robolectric//bazel:robolectric.bzl", "robolectric_repositories")
+robolectric_repositories()
+
 load("//third_party/flatbuffers:workspace.bzl", flatbuffers = "repo")
 
 flatbuffers()
+
+RULES_JVM_EXTERNAL_TAG = "3.2"
+
+http_archive(
+    name = "rules_jvm_external",
+    strip_prefix = "rules_jvm_external-%s" % RULES_JVM_EXTERNAL_TAG,
+    sha256 = "82262ff4223c5fda6fb7ff8bd63db8131b51b413d26eb49e3131037e79e324af",
+    url = "https://github.com/bazelbuild/rules_jvm_external/archive/%s.zip" % RULES_JVM_EXTERNAL_TAG,
+)
+
+load("@rules_jvm_external//:defs.bzl", "maven_install")
+
 # Set up TF.
-load("@org_tensorflow//tensorflow:workspace.bzl", "tf_workspace")
-tf_workspace(tf_repo_name="@org_tensorflow")
+load("@org_tensorflow//tensorflow:workspace3.bzl", "workspace")
+workspace()
+load("@org_tensorflow//tensorflow:workspace2.bzl", "workspace")  # buildifier: disable=load
+workspace()
+load("@org_tensorflow//tensorflow:workspace1.bzl", "workspace")  # buildifier: disable=load
+workspace()
+load("@org_tensorflow//tensorflow:workspace0.bzl", "workspace")  # buildifier: disable=load
+workspace()
 
 load("//third_party/tensorflow:tf_configure.bzl", "tf_configure")
 tf_configure(name = "local_config_tf")
@@ -346,35 +436,38 @@
 load("@upb//bazel:repository_defs.bzl", "bazel_version_repository")
 bazel_version_repository(name = "bazel_version")
 
-
-# Set up Android.
-load("//third_party/android:android_configure.bzl", "android_configure")
-android_configure(name="local_config_android")
-load("@local_config_android//:android.bzl", "android_workspace")
-android_workspace()
-
 python_configure(name = "local_config_python")
 
+ATS_TAG = "androidx-test-1.3.0"
+http_archive(
+    name = "android_test_support",
+    strip_prefix = "android-test-%s" % ATS_TAG,
+    urls = ["https://github.com/android/android-test/archive/%s.tar.gz" % ATS_TAG],
+)
+load("@android_test_support//:repo.bzl", "android_test_repositories")
+android_test_repositories()
 
 # Maven dependencies.
 
-RULES_JVM_EXTERNAL_TAG = "3.2"
-
-http_archive(
-    name = "rules_jvm_external",
-    strip_prefix = "rules_jvm_external-%s" % RULES_JVM_EXTERNAL_TAG,
-    sha256 = "82262ff4223c5fda6fb7ff8bd63db8131b51b413d26eb49e3131037e79e324af",
-    url = "https://github.com/bazelbuild/rules_jvm_external/archive/%s.zip" % RULES_JVM_EXTERNAL_TAG,
-)
-
-load("@rules_jvm_external//:defs.bzl", "maven_install")
-
 maven_install(
     artifacts = [
         "androidx.annotation:annotation:aar:1.1.0",
+        "androidx.annotation:annotation-experimental:1.1.0",
+        "androidx.multidex:multidex:jar:2.0.1",
+        "androidx.test:core:jar:1.3.0",
+        "androidx.test.ext:junit:jar:1.1.2",
+        "androidx.test:runner:jar:1.3.0",
+        "com.google.android.odml:image:aar:1.0.0-beta1",
+        "com.google.truth:truth:jar:1.1",
+        "commons-io:commons-io:jar:2.8.0",
+        # Mockito >= 3.4.6 cannot pass bazel desugar.
+        "org.mockito:mockito-android:jar:3.0.0",
+        "org.mockito:mockito-core:jar:3.0.0",
+        "org.mockito:mockito-inline:jar:3.0.0",
+        "org.robolectric:robolectric:jar:4.4",
+        "junit:junit:jar:4.13",
     ],
     repositories = [
-        "https://jcenter.bintray.com",
         "https://maven.google.com",
         "https://dl.google.com/dl/android/maven2",
         "https://repo1.maven.org/maven2",
@@ -382,3 +475,23 @@
     fetch_sources = True,
     version_conflict_policy = "pinned",
 )
+
+http_archive(
+    name = "tf_toolchains",
+    sha256 = "d72b2e52baf0592f5b94347b128ef75422fc22f63dfcf2d5fd46bc732cab052b",
+    strip_prefix = "toolchains-1.3.0",
+    urls = [
+        "http://mirror.tensorflow.org/github.com/tensorflow/toolchains/archive/v1.3.0.tar.gz",
+        "https://github.com/tensorflow/toolchains/archive/v1.3.0.tar.gz",
+    ],
+)
+
+load("@tf_toolchains//toolchains/embedded/arm-linux:arm_linux_toolchain_configure.bzl", "arm_linux_toolchain_configure")
+
+# TFLite crossbuild toolchain for embeddeds Linux
+arm_linux_toolchain_configure(
+    name = "local_config_embedded_arm",
+    build_file = "@tf_toolchains//toolchains/embedded/arm-linux:BUILD",
+    aarch64_repo = "../aarch64_linux_toolchain",
+    armhf_repo = "../armhf_linux_toolchain",
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/BUILD
index 258f29bc..0830d48 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/BUILD
@@ -8,17 +8,21 @@
 
 exports_files(["LICENSE"])
 
-# LINT.IfChange
 package_group(
     name = "users",
+    includes = [
+        ":internal",
+    ],
     packages = [
-        "//tensorflow_lite_support/...",
-        "//third_party/py/tensorflow_examples/...",
-        "//third_party/tensorflow_models/...",
     ],
 )
-# Remove internal path from tensorflow_lite_support:users in the copybara file.
-# LINT.ThenChange(//tensorflow_lite_support/copy.bara.sky)
+
+package_group(
+    name = "internal",
+    packages = [
+        "//tensorflow_lite_support/...",
+    ],
+)
 
 # Config setting for determining if we are building for Android.
 config_setting(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/README.md b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/README.md
new file mode 100644
index 0000000..6221f02
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/README.md
@@ -0,0 +1,18 @@
+# Acceleration allowlisting
+
+A complementary directory for the work of
+[accelerator allowlisting](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/experimental/acceleration)
+in TensorFlow Lite.
+
+## Coral Edge TPU plugin
+
+The Coral Edge TPU delegate plugin used in the
+[acceleration library](https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/cc/port/default/tflite_wrapper.h).
+See
+[CoralSettings](https://github.com/tensorflow/tensorflow/blob/896fecee319ffeb4af2a3c0b5436f3a55ab058fa/tensorflow/lite/experimental/acceleration/configuration/configuration.proto#L323)
+about how to configure the Coral Edge TPU plugin. You can use the acceleration
+library together with
+[Task Library](https://github.com/tensorflow/tflite-support/tree/master/tensorflow_lite_support/cc/task).
+Configure your desired accelerator, including the Coral plugin through the
+options of each task, i.e.
+[image_classifier_options](https://github.com/tensorflow/tflite-support/blob/43f1267b99f1dbc27c7c5b2e1111e1ff6b9121ea/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.proto#L79).
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/BUILD
new file mode 100644
index 0000000..d6da77e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/BUILD
@@ -0,0 +1,136 @@
+load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
+load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "gpu_plugin",
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:gpu_plugin",
+    ],
+    alwayslink = 1,  # For registration to always run.
+)
+
+cc_library(
+    name = "nnapi_plugin",
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:nnapi_plugin",
+    ],
+    alwayslink = 1,  # For registration to always run.
+)
+
+cc_library(
+    name = "hexagon_plugin",
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:hexagon_plugin",
+    ],
+    alwayslink = 1,  # For registration to always run.
+)
+
+cc_library(
+    name = "xnnpack_plugin",
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:xnnpack_plugin",
+    ],
+    alwayslink = 1,  # For registration to always run.
+)
+
+# To use the edgetpu_coral_plugin externally, add the following flags to the bazel command:
+# --define darwinn_portable=1
+cc_library(
+    name = "edgetpu_coral_plugin",
+    srcs = ["edgetpu_coral_plugin.cc"],
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "@com_google_absl//absl/container:node_hash_map",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/strings",
+        "@com_google_glog//:glog",
+        "@libedgetpu//tflite/public:edgetpu_c",
+        "@libedgetpu//tflite/public:oss_edgetpu_direct_all",  # buildcleaner: keep
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_fbs",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:delegate_registry",
+    ],
+    alwayslink = 1,  # For registration to always run.
+)
+
+# To test it externally, plugin a Coral device, and run the following command:
+# bazel test tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin_test \
+# --define darwinn_portable=1
+cc_test(
+    name = "edgetpu_coral_plugin_test",
+    srcs = ["edgetpu_coral_plugin_test.cc"],
+    data = [
+        "//tensorflow_lite_support/acceleration/configuration/testdata:test_files",
+    ],
+    tags = [
+        "manual",
+        "notap",  # Requires edge TPU device.
+    ],
+    deps = [
+        ":edgetpu_coral_plugin",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_googletest//:gtest_main",
+        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_fbs",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:delegate_registry",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+    ],
+)
+
+# Targets for delegate plugin library Maven release.
+
+# GPU delegate plugin library.
+tflite_jni_binary(
+    name = "libgpu_delegate_plugin.so",
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    visibility = ["//visibility:private"],
+    deps = [
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration/c:gpu_plugin",
+    ],
+)
+
+cc_library(
+    name = "gpu_delegate_plugin_native",
+    srcs = [
+        ":libgpu_delegate_plugin.so",
+    ],
+    visibility = ["//visibility:private"],
+)
+
+# Android target of Acceleration@Scale GPU plugin.
+# Use this target when GPU delegate is selected in the Task Library Java API.
+android_library(
+    name = "gpu_delegate_plugin_android",
+    visibility = [
+        "//visibility:public",
+    ],
+    exports = [":gpu_delegate_plugin_native"],
+)
+
+# AAR target of Acceleration@Scale GPU acceleration for OSS release.
+aar_with_jni(
+    name = "gpu-delegate-plugin",
+    android_library = ":gpu_delegate_plugin_android",
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc
new file mode 100644
index 0000000..6a16d12
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin.cc
@@ -0,0 +1,170 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include <memory>
+#include <unordered_map>
+
+#include <glog/logging.h>
+#include "absl/container/node_hash_map.h"  // from @com_google_absl
+#include "absl/memory/memory.h"            // from @com_google_absl
+#include "absl/strings/match.h"            // from @com_google_absl
+#include "absl/strings/numbers.h"          // from @com_google_absl
+#include "tensorflow/lite/experimental/acceleration/configuration/configuration_generated.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/delegate_registry.h"
+#include "tflite/public/edgetpu_c.h"
+
+namespace tflite {
+namespace delegates {
+namespace {
+
+constexpr int kDEFAULT_USB_MAX_BULK_IN_QUEUE_LENGTH = 32;
+constexpr char kUsb[] = "usb";
+constexpr char kPci[] = "pci";
+
+inline std::string ConvertPerformance(
+    const CoralSettings_::Performance& from_performance) {
+  switch (from_performance) {
+    case CoralSettings_::Performance_LOW:
+      return "Low";
+    case CoralSettings_::Performance_MEDIUM:
+      return "Medium";
+    case CoralSettings_::Performance_HIGH:
+      return "High";
+    default:
+      return "Max";
+  }
+}
+
+inline std::string ConvertBool(bool from_bool) {
+  return from_bool ? "True" : "False";
+}
+
+bool MatchDevice(const std::string& device,
+                 const std::string& type,
+                 int* index) {
+  const auto prefix(type + ":");
+  if (!absl::StartsWith(device, prefix))
+    return false;
+  if (!absl::SimpleAtoi(device.substr(prefix.size()), index))
+    return false;
+  if (*index < 0)
+    return false;
+  return true;
+}
+
+// device_index corresponds to specific device type, e.g. "usb:0" means the
+// first USB device or "pci:0" means the first PCIe device.
+TfLiteDelegate* CreateEdgeTpuDelegate(
+    absl::optional<edgetpu_device_type> device_type,
+    absl::optional<int> device_index,
+    const absl::node_hash_map<std::string, std::string>& device_options) {
+  std::vector<edgetpu_option> options(device_options.size());
+  size_t i = 0;
+  for (auto& device_option : device_options) {
+    options[i++] = {device_option.first.c_str(), device_option.second.c_str()};
+  }
+
+  size_t num_devices;
+  std::unique_ptr<edgetpu_device, decltype(&edgetpu_free_devices)> devices(
+      edgetpu_list_devices(&num_devices), &edgetpu_free_devices);
+
+  if (!device_index.has_value()) {
+    return CreateEdgeTpuDelegate(device_type, 0, device_options);
+  } else {
+    const int index = device_index.value();
+    if (device_type.has_value()) {
+      int type_index = 0;
+      for (size_t i = 0; i < num_devices; i++) {
+        const auto& device = devices.get()[i];
+        if (device.type == device_type.value() && type_index++ == index)
+          return edgetpu_create_delegate(device.type, device.path,
+                                         options.data(), options.size());
+      }
+    } else {
+      if (index < num_devices)
+        return edgetpu_create_delegate(devices.get()[index].type,
+                                       devices.get()[index].path,
+                                       options.data(), options.size());
+    }
+    return nullptr;
+  }
+}
+
+TfLiteDelegate* CreateEdgeTpuDelegate(
+    const std::string& device,
+    const absl::node_hash_map<std::string, std::string>& options) {
+  if (device.empty()) {
+    return CreateEdgeTpuDelegate(absl::nullopt, absl::nullopt, options);
+  } else if (device == kUsb) {
+    return CreateEdgeTpuDelegate(EDGETPU_APEX_USB, absl::nullopt, options);
+  } else if (device == kPci) {
+    return CreateEdgeTpuDelegate(EDGETPU_APEX_PCI, absl::nullopt, options);
+  } else {
+    int index;
+    if (MatchDevice(device, "", &index)) {
+      return CreateEdgeTpuDelegate(absl::nullopt, index, options);
+    } else if (MatchDevice(device, kUsb, &index)) {
+      return CreateEdgeTpuDelegate(EDGETPU_APEX_USB, index, options);
+    } else if (MatchDevice(device, kPci, &index)) {
+      return CreateEdgeTpuDelegate(EDGETPU_APEX_PCI, index, options);
+    } else {
+      LOG(ERROR) << "Cannot match the given device string (" << device
+                 << ") with a Coral device.";
+      return nullptr;
+    }
+  }
+}
+
+class EdgeTpuCoralPlugin : public DelegatePluginInterface {
+ public:
+  TfLiteDelegatePtr Create() override {
+    return TfLiteDelegatePtr(CreateEdgeTpuDelegate(device_, options_),
+                             edgetpu_free_delegate);
+  }
+
+  int GetDelegateErrno(TfLiteDelegate* from_delegate) override { return 0; }
+
+  static std::unique_ptr<DelegatePluginInterface> New(
+      const TFLiteSettings& acceleration) {
+    return absl::make_unique<EdgeTpuCoralPlugin>(acceleration);
+  }
+
+  explicit EdgeTpuCoralPlugin(const TFLiteSettings& tflite_settings) {
+    const auto* coral_settings = tflite_settings.coral_settings();
+    if (!coral_settings) {
+      return;
+    }
+
+    device_ = coral_settings->device()->str();
+    options_.insert(
+        {"Performance", ConvertPerformance(coral_settings->performance())});
+    options_.insert(
+        {"Usb.AlwaysDfu", ConvertBool(coral_settings->usb_always_dfu())});
+    options_.insert(
+        {"Usb.MaxBulkInQueueLength",
+         std::to_string(coral_settings->usb_max_bulk_in_queue_length() == 0
+                            ? kDEFAULT_USB_MAX_BULK_IN_QUEUE_LENGTH
+                            : coral_settings->usb_max_bulk_in_queue_length())});
+  }
+
+ private:
+  std::string device_;
+  absl::node_hash_map<std::string, std::string> options_;
+};
+}  // namespace
+
+TFLITE_REGISTER_DELEGATE_FACTORY_FUNCTION(EdgeTpuCoralPlugin,
+                                          EdgeTpuCoralPlugin::New);
+}  // namespace delegates
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc
new file mode 100644
index 0000000..cc183a6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/edgetpu_coral_plugin_test.cc
@@ -0,0 +1,100 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <gmock/gmock.h>
+#include <gtest/gtest.h>
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/configuration_generated.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/delegate_registry.h"
+#include "tensorflow/lite/interpreter.h"
+#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/model.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace delegates {
+namespace {
+
+constexpr char kEdgeTpuModelFilePath[] =
+    "tensorflow_lite_support/acceleration/configuration/testdata/"
+    "mobilenet_v1_1.0_224_quant_edgetpu.tflite";
+constexpr char kRegularModelFilePath[] =
+    "tensorflow_lite_support/acceleration/configuration/testdata/"
+    "mobilenet_v1_1.0_224_quant.tflite";
+constexpr char kImagePath[] =
+    "tensorflow_lite_support/acceleration/configuration/testdata/"
+    "burger.jpg";
+
+using ::tflite::task::vision::DecodeImageFromFile;
+using ::tflite::task::vision::ImageData;
+using ::tflite::task::vision::ImageDataFree;
+
+using EdgeTpuCoralPluginTest = testing::TestWithParam<std::string>;
+
+INSTANTIATE_TEST_SUITE_P(CoralPluginTests,
+                         EdgeTpuCoralPluginTest,
+                         testing::Values(kRegularModelFilePath,
+                                         kEdgeTpuModelFilePath));
+
+TEST_P(EdgeTpuCoralPluginTest, CreateEdgeTpuCoralPlugin) {
+  // Create the Coral delegate from the Coral plugin.
+  flatbuffers::FlatBufferBuilder flatbuffer_builder;
+  auto settings = flatbuffers::GetTemporaryPointer(
+      flatbuffer_builder,
+      CreateTFLiteSettings(flatbuffer_builder, tflite::Delegate_EDGETPU_CORAL));
+  auto plugin = ::tflite::delegates::DelegatePluginRegistry::CreateByName(
+      "EdgeTpuCoralPlugin", *settings);
+  auto coral_delegate = plugin->Create();
+
+  // Load the tflite model file.
+  std::unique_ptr<::tflite::FlatBufferModel> tflite_model =
+      ::tflite::FlatBufferModel::BuildFromFile(GetParam().c_str());
+  ASSERT_NE(tflite_model, nullptr);
+
+  // Create the tflite interpreter.
+  tflite::ops::builtin::BuiltinOpResolver resolver;
+  std::unique_ptr<::tflite::Interpreter> interpreter;
+  ASSERT_EQ(::tflite::InterpreterBuilder(*tflite_model, resolver)(&interpreter),
+            kTfLiteOk);
+  ASSERT_NE(interpreter, nullptr);
+  interpreter->ModifyGraphWithDelegate(coral_delegate.get());
+
+  // Verifies that interpreter runs correctly.
+  // To open source the code under tensorflow/lite, the following code needs to
+  // be stript from the Task library dependency, meaning forking or rewriting
+  // `LoadImage` and `ImageData`.
+  // `ASSERT_OK_AND_ASSIGN` is not available externally.
+  auto rgb_image_or = DecodeImageFromFile(kImagePath);
+  ASSERT_TRUE(rgb_image_or.ok());
+
+  ImageData rgb_image = rgb_image_or.value();
+  const uint8_t* input_data = rgb_image.pixel_data;
+  size_t input_data_byte_size =
+      rgb_image.width * rgb_image.height * rgb_image.channels * sizeof(uint8_t);
+
+  ASSERT_EQ(interpreter->AllocateTensors(), kTfLiteOk);
+  uint8_t* input_tensor = interpreter->typed_input_tensor<uint8_t>(0);
+  memcpy(input_tensor, input_data, input_data_byte_size);
+  ASSERT_EQ(interpreter->Invoke(), kTfLiteOk);
+  uint8_t* output_tensor = interpreter->typed_output_tensor<uint8_t>(0);
+  // `cheeseburger` is the 935th item in the label file of
+  // "mobilenet_v1_1.0_224_quant_edgetpu.tflite". See labels.txt.
+  EXPECT_EQ(output_tensor[934], 255);
+  ImageDataFree(&rgb_image);
+}
+
+}  // namespace
+}  // namespace delegates
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/BUILD
new file mode 100644
index 0000000..d3dcbaf
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/BUILD
@@ -0,0 +1,12 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.tflite",
+        "*.jpg",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/burger.jpg b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/burger.jpg
new file mode 100644
index 0000000..58ec72b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/burger.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/mobilenet_v1_1.0_224_quant.tflite b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/mobilenet_v1_1.0_224_quant.tflite
new file mode 100644
index 0000000..437640b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/mobilenet_v1_1.0_224_quant.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/mobilenet_v1_1.0_224_quant_edgetpu.tflite b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/mobilenet_v1_1.0_224_quant_edgetpu.tflite
new file mode 100644
index 0000000..416152a1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/acceleration/configuration/testdata/mobilenet_v1_1.0_224_quant_edgetpu.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/BUILD
new file mode 100644
index 0000000..ecee826
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/BUILD
@@ -0,0 +1,23 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "common",
+    srcs = ["common.cc"],
+    hdrs = ["common.h"],
+)
+
+cc_library(
+    name = "common_utils",
+    srcs = ["common_utils.cc"],
+    hdrs = ["common_utils.h"],
+    deps = [
+        ":common",
+        "//tensorflow_lite_support/cc:common",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:cord",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc
new file mode 100644
index 0000000..f0974ed2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common.cc
@@ -0,0 +1,25 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/common.h"
+
+#include <cstdlib>
+
+void TfLiteSupportErrorDelete(TfLiteSupportError* error) {
+  // `strdup` obtains memory using `malloc` and the memory needs to be
+  // released using `free`.
+  free(error->message);
+  delete error;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common.h b/third_party/tflite_support/src/tensorflow_lite_support/c/common.h
new file mode 100644
index 0000000..3ced6422
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common.h
@@ -0,0 +1,202 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_COMMON_H_
+#define TENSORFLOW_LITE_SUPPORT_C_COMMON_H_
+
+// Defines C struct and error codes for describing any error returned from the C
+// Task Library.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Error codes for TensorFlow Lite Task Library C APIs.
+//
+// Holds one to one mapping with `TfLiteSupportStatus` code starting from kError
+// = 1. Omits `kOk` since `TfLiteErrorCode` is only to be used in the event of
+// an error and does not account for success unlike `TfLiteSupportStatus`. In
+// case of success, TensorFlow Lite Task Library C APIs return the appropriate
+// return value and a null error. One to one mapping makes it easier to convert
+// between `TfLiteSupportStatus` and `TfLiteSupportErrorCode` without long
+// switch statements.
+//
+// Also holds error codes mapping to absl::Status::code() starting from
+// kNotFound = 900 in cases where the absl::Status payload can't
+// be mapped to a `TfLiteSupportStatus` code. kErrorCodeFirst and kErrorCodeLast
+// are also provided for safety checks during conversion between
+// `TfLiteSupportStatus` and `TfLiteSupportErrorCode`. In case of modifications
+// in error codes, ensure that kErrorCodeFirst and kErrorCodeLast is
+// respectively, set to the least and greatest enum value amongst the error
+// codes mapping to TfLiteSupportStatus.
+enum TfLiteSupportErrorCode {
+  // Unspecified error.
+  kError = 1,
+  // Invalid argument specified.
+  kInvalidArgumentError = 2,
+  // Invalid FlatBuffer file or buffer specified.
+  kInvalidFlatBufferError = 3,
+  // Model contains a builtin op that isn't supported by the OpResolver or
+  // delegates.
+  kUnsupportedBuiltinOpError = 4,
+  // Model contains a custom op that isn't supported by the OpResolver or
+  // delegates.
+  kUnsupportedCustomOpError = 5,
+
+  // File I/O error codes.
+
+  // No such file.
+  kFileNotFoundError = 100,
+  // Permission issue.
+  kFilePermissionDeniedError,
+  // I/O error when reading file.
+  kFileReadError,
+  // I/O error when mmap-ing file.
+  kFileMmapError,
+
+  // TensorFlow Lite metadata error codes.
+
+  // Unexpected schema version (aka file_identifier) in the Metadata FlatBuffer.
+  kMetadataInvalidSchemaVersionError = 200,
+  // No such associated file within metadata, or file has not been packed.
+  kMetadataAssociatedFileNotFoundError,
+  // ZIP I/O error when unpacking an associated file.
+  kMetadataAssociatedFileZipError,
+  // Inconsistency error between the metadata and actual TF Lite model.
+  // E.g.: number of labels and output tensor values differ.
+  kMetadataInconsistencyError,
+  // Invalid process units specified.
+  // E.g.: multiple ProcessUnits with the same type for a given tensor.
+  kMetadataInvalidProcessUnitsError,
+  // Inconsistency error with the number of labels.
+  // E.g.: label files for different locales have a different number of labels.
+  kMetadataNumLabelsMismatchError,
+  // Score calibration parameters parsing error.
+  // E.g.: too many parameters provided in the corresponding associated file.
+  kMetadataMalformedScoreCalibrationError,
+  // Unexpected number of subgraphs for the current task.
+  // E.g.: image classification expects a single subgraph.
+  kMetadataInvalidNumSubgraphsError,
+  // A given tensor requires NormalizationOptions but none were found.
+  // E.g.: float input tensor requires normalization to preprocess input images.
+  kMetadataMissingNormalizationOptionsError,
+  // Invalid ContentProperties specified.
+  // E.g. expected ImageProperties, got BoundingBoxProperties.
+  kMetadataInvalidContentPropertiesError,
+  // Metadata is mandatory but was not found.
+  // E.g. current task requires TFLite Model Metadata but none was found.
+  kMetadataNotFoundError,
+  // Associated TENSOR_AXIS_LABELS or TENSOR_VALUE_LABELS file is mandatory but
+  // none was found or it was empty.
+  // E.g. current task requires labels but none were found.
+  kMetadataMissingLabelsError,
+  // The ProcessingUnit for tokenizer is not correctly configured.
+  // E.g BertTokenizer doesn't have a valid vocab file associated.
+  kMetadataInvalidTokenizerError,
+
+  // Input tensor(s) error codes.
+
+  // Unexpected number of input tensors for the current task.
+  // E.g. current task expects a single input tensor.
+  kInvalidNumInputTensorsError = 300,
+  // Unexpected input tensor dimensions for the current task.
+  // E.g.: only 4D input tensors supported.
+  kInvalidInputTensorDimensionsError,
+  // Unexpected input tensor type for the current task.
+  // E.g.: current task expects a uint8 pixel image as input.
+  kInvalidInputTensorTypeError,
+  // Unexpected input tensor bytes size.
+  // E.g.: size in bytes does not correspond to the expected number of pixels.
+  kInvalidInputTensorSizeError,
+  // No correct input tensor found for the model.
+  // E.g.: input tensor name is not part of the text model's input tensors.
+  kInputTensorNotFoundError,
+
+  // Output tensor(s) error codes.
+
+  // Unexpected output tensor dimensions for the current task.
+  // E.g.: only a batch size of 1 is supported.
+  kInvalidOutputTensorDimensionsError = 400,
+  // Unexpected input tensor type for the current task.
+  // E.g.: multi-head model with different output tensor types.
+  kInvalidOutputTensorTypeError,
+  // No correct output tensor found for the model.
+  // E.g.: output tensor name is not part of the text model's output tensors.
+  kOutputTensorNotFoundError,
+  // Unexpected number of output tensors for the current task.
+  // E.g.: current task expects a single output tensor.
+  kInvalidNumOutputTensorsError,
+
+  // Image processing error codes.
+
+  // Unspecified image processing failures.
+  kImageProcessingError = 500,
+  // Unexpected input or output buffer metadata.
+  // E.g.: rotate RGBA buffer to Grayscale buffer by 90 degrees.
+  kImageProcessingInvalidArgumentError,
+  // Image processing operation failures.
+  // E.g. libyuv rotation failed for an unknown reason.
+  kImageProcessingBackendError,
+
+  // Convenience error codes for condition checks during type casting.
+  //
+  // Codes mapping to absl status codes should not be considered for these
+  // ranges.
+  // They must be used exclsively for checking if error codes fall in valid
+  // ranges when converting between TfLiteSupportStatus and
+  // TfLiteSupportErrorCodee.
+
+  // Ensure it holds the least enum value amongst error codes mapping to
+  // TfLiteSupportStatus.
+  kErrorCodeFirst = kError,
+  // Ensure it holds the greatest enum value amongst error codes mapping to
+  // TfLiteSupportStatus.
+  kErrorCodeLast = kImageProcessingBackendError,
+
+  // Absl Status Codes Mapping
+  //
+  // Codes starting from 900 will be used to map absl::Status created by TfLite
+  // and are used as is by TfLite Support C++ layer. Such absl status objects
+  // don't have a TfLiteSupportStatus in the payload that can be mapped to other
+  // error codes in this struct. You must use the absl::Status::code() and map
+  // them to the following error codes in such cases.
+  // For more info on respective absl status codes, please see:
+  // https://github.com/abseil/abseil-cpp/blob/master/absl/status/status.h#L91
+
+  // kNotFound indicates some requested entity (such as a file or directory)
+  // was not found.
+  kNotFoundError = 900,
+  // kInternal indicates an internal error has occurred
+  // and some invariants expected by the underlying system have not been
+  // satisfied. This error code is reserved for serious errors.
+  kInternalError,
+};
+
+// A `TfLiteSupportError` encapsulates an error code and a descriptive message
+// to return in the event of an error being encountered in any TensorFlow Lite
+// Task Library C API.
+typedef struct TfLiteSupportError {
+  // Holds the error code.
+  enum TfLiteSupportErrorCode code;
+  // Detailed description of the error.
+  char* message;
+} TfLiteSupportError;
+
+void TfLiteSupportErrorDelete(TfLiteSupportError* error);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_COMMON_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc
new file mode 100644
index 0000000..39afb9c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.cc
@@ -0,0 +1,111 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/common_utils.h"
+
+#include <string>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/strings/cord.h"   // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+
+namespace tflite {
+namespace support {
+
+void CreateTfLiteSupportError(enum TfLiteSupportErrorCode code,
+                              const char* message,
+                              TfLiteSupportError** error) {
+  if (error == nullptr)
+    return;
+
+  *error = new TfLiteSupportError;
+  (*error)->code = code;
+  (*error)->message = strdup(message);
+}
+
+void CreateTfLiteSupportErrorWithStatus(const absl::Status& status,
+                                        TfLiteSupportError** error) {
+  if (status.ok() || error == nullptr)
+    return;
+
+  // Payload of absl::Status created by the tflite task library stores an
+  // appropriate value of the enum TfLiteSupportStatus. The integer value
+  // corresponding to the TfLiteSupportStatus enum stored in the payload is
+  // extracted here to later map to the appropriate error code to be returned.
+  // In cases where the enum is not stored in (payload is NULL or the payload
+  // string cannot be converted to an integer), we set the error code value to
+  // be 1 (kError of TfLiteErrorCode used in the C library to signify any errors
+  // not falling into other categories.) Since payload is of type absl::Cord
+  // that can be type cast into an absl::optional<std::string>, we use the
+  // std::stoi function to convert it into an integer code if possible.
+  int generic_error_code = static_cast<int>(kError);
+  int error_code;
+  try {
+    // Try converting payload to integer if payload is not empty. Otherwise
+    // convert a string signifying generic error code kError to integer.
+    error_code = std::stoi(static_cast<absl::optional<std::string>>(
+                               status.GetPayload(kTfLiteSupportPayload))
+                               .value_or(std::to_string(generic_error_code)));
+  } catch (std::invalid_argument& e) {
+    // If non empty payload string cannot be converted to an integer. Set error
+    // code to 1(kError).
+    error_code = generic_error_code;
+  }
+
+  // If error_code is outside the range of enum values possible or is kError, we
+  // try to map the absl::Status::code() to assign appropriate
+  // TfLiteSupportErrorCode or kError in default cases. Note: The mapping to
+  // absl::Status::code() is done to generate a more specific error code than
+  // kError in cases when the payload can't be mapped to TfLiteSupportStatus.
+  // This can happen when absl::Status returned by TfLite are in turn returned
+  // without moodification by TfLite Support Methods.
+  if (error_code > static_cast<int>(kErrorCodeLast) ||
+      error_code <= static_cast<int>(kErrorCodeFirst)) {
+    switch (status.code()) {
+      case absl::StatusCode::kInternal:
+        error_code = kInternalError;
+        break;
+      case absl::StatusCode::kInvalidArgument:
+        error_code = kInvalidArgumentError;
+        break;
+      case absl::StatusCode::kNotFound:
+        error_code = kNotFoundError;
+        break;
+      default:
+        error_code = kError;
+        break;
+    }
+  }
+
+  // Creates the TfLiteSupportError with the appropriate error
+  // TfLiteSupportErrorCode and message. TfLiteErrorCode has a one to one
+  // mapping with TfLiteSupportStatus starting from the value 1(kError) and
+  // hence will be correctly initialized if directly cast from the integer code
+  // derived from TfLiteSupportStatus stored in payload. TfLiteErrorCode omits
+  // kOk = 0 of TfLiteSupportStatus.
+  //
+  // Stores a string including absl status code and message(if non empty) as the
+  // error message See
+  // https://github.com/abseil/abseil-cpp/blob/master/absl/status/status.h#L514
+  // for explanation. absl::Status::message() can also be used but not always
+  // guaranteed to be non empty.
+  CreateTfLiteSupportError(
+      static_cast<TfLiteSupportErrorCode>(error_code),
+      status.ToString(absl::StatusToStringMode::kWithNoExtraData).c_str(),
+      error);
+}
+
+}  // namespace support
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h
new file mode 100644
index 0000000..551f64a5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/common_utils.h
@@ -0,0 +1,57 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_COMMON_UTILS_H_
+#define TENSORFLOW_LITE_SUPPORT_C_COMMON_UTILS_H_
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/c/common.h"
+
+// Utils for Conversion of absl::Status to TfLiteError
+// -----------------------------------------------------------------
+// Meant to be used with task C apis.
+
+namespace tflite {
+namespace support {
+
+// Creates a TfLiteSupportError with a TfLiteSupportErrorCode and message.
+void CreateTfLiteSupportError(enum TfLiteSupportErrorCode code,
+                              const char* message,
+                              TfLiteSupportError** error);
+
+// Creates a TfLiteSupportError from absl::Status and passes it back as a
+// parameter which is a pointer to the error pointer.
+//
+// Example Usage With Image Classifier
+//
+// APIs: TfLiteImageClassifier* TfLiteImageClassifierFromOptions(
+//     const TfLiteImageClassifierOptions* options,
+//     TfLiteSupportError **error) {
+// // Necessary checks
+// tflite::support::StatusOr<std::unique_ptr<ImageClassifier>> classifier_status
+// = // Call to create Cpp Image Classifier.
+// if (classifier_status.ok()) {
+//     Code to return classifier
+// } else {
+//     ::tflite::support::CreateTfLiteSupportErrorWithStatus(classifier_status.status(),
+//     error);
+//     return nullptr;
+//  }
+//}
+void CreateTfLiteSupportErrorWithStatus(const absl::Status& status,
+                                        TfLiteSupportError** error);
+
+}  // namespace support
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_SUPPORT_C_COMMON_UTILS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/task/core/BUILD
new file mode 100644
index 0000000..659f165
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/core/BUILD
@@ -0,0 +1,9 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "base_options",
+    hdrs = ["base_options.h"],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/core/base_options.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/core/base_options.h
new file mode 100644
index 0000000..1093b63
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/core/base_options.h
@@ -0,0 +1,73 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_CORE_BASE_OPTIONS_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_CORE_BASE_OPTIONS_H_
+
+#include <stdint.h>
+
+// Defines C Structs for Base Options Shared by all tasks.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Holds cpu settings.
+typedef struct TfLiteCpuSettings {
+  // Specifies the number of threads to be used for TFLite
+  // ops that support multi-threading when running inference with CPU.
+  // num_threads should be greater than 0 or equal to -1. Setting num_threads to
+  // -1 has the effect to let TFLite runtime set the value.
+  int num_threads;
+} TfLiteCpuSettings;
+
+// Holds settings for one possible acceleration configuration.
+typedef struct TfLiteComputeSettings {
+  // Holds cpu settings
+  TfLiteCpuSettings cpu_settings;
+} TfLiteComputeSettings;
+
+// Represents external files used by the Task APIs (e.g. TF Lite Model File).
+// For now you can only specify the path of the file using file_path:
+// In future other sources may be supported.
+typedef struct TfLiteExternalFile {
+  // The path to the file to open.
+  const char* file_path;
+  // Additional option for byte data when it's supported.
+} TfLiteExternalFile;
+
+// Holds the base options that is used for creation of any type of task. It has
+// fields withh important information acceleration configuration, tflite model
+// source etc.
+// This struct must be zero initialized before setting any options as this
+// will result in seg faults.
+typedef struct TfLiteBaseOptions {
+  // The external model file, as a single standalone TFLite file. It could be
+  // packed with TFLite Model Metadata[1] and associated files if exist. Fail to
+  // provide the necessary metadata and associated files might result in errors.
+  // Check the documentation for each task about the specific requirement.
+  // [1]: https://www.tensorflow.org/lite/convert/metadata
+  TfLiteExternalFile model_file;
+
+  // Holds settings for one possible acceleration configuration
+  // including.cpu/gpu settings. Please see documentation of
+  // TfLiteComputeSettings and its members for more details.
+  TfLiteComputeSettings compute_settings;
+} TfLiteBaseOptions;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_CORE_BASE_OPTIONS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/BUILD
new file mode 100644
index 0000000..2d0cef6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/BUILD
@@ -0,0 +1,42 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "category",
+    hdrs = ["category.h"],
+)
+
+cc_library(
+    name = "classification_result",
+    srcs = [
+        "classification_result.cc",
+    ],
+    hdrs = ["classification_result.h"],
+    deps = [
+        ":category",
+    ],
+)
+
+cc_library(
+    name = "bounding_box",
+    hdrs = ["bounding_box.h"],
+)
+
+cc_library(
+    name = "classification_options",
+    hdrs = ["classification_options.h"],
+)
+
+cc_library(
+    name = "detection_result",
+    srcs = [
+        "detection_result.cc",
+    ],
+    hdrs = ["detection_result.h"],
+    deps = [
+        ":bounding_box",
+        ":category",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/bounding_box.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/bounding_box.h
new file mode 100644
index 0000000..4a28f77
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/bounding_box.h
@@ -0,0 +1,45 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_BOUNDING_BOX_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_BOUNDING_BOX_H_
+
+#include <stdint.h>
+
+// Defines C Struct for Bounding Box Shared by Vision Tasks.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Holds the region of interest used for image classification.
+typedef struct TfLiteBoundingBox {
+  // The X coordinate of the top-left corner, in pixels.
+  int origin_x;
+
+  // The Y coordinate of the top-left corner, in pixels.
+  int origin_y;
+
+  // The width of the bounding box, in pixels.
+  int width;
+
+  // The height of the bounding box, in pixels.
+  int height;
+} TfLiteBoundingBox;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_BOUNDING_BOX_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/category.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/category.h
new file mode 100644
index 0000000..5c049ec
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/category.h
@@ -0,0 +1,49 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CATEGORY_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CATEGORY_H_
+
+// Defines C structure for a Category which encapsulates a single predicted
+// class.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// A single predicted class.
+typedef struct TfLiteCategory {
+  // The index of the class in the corresponding label map, usually packed in
+  // the TFLite Model Metadata [1].
+  //
+  // [1]: https://www.tensorflow.org/lite/convert/metadata
+  int index;
+
+  // The score for this class e.g. (but not necessarily) a probability in [0,1].
+  float score;
+
+  // A human readable name of the class filled from the label map.
+  char* display_name;
+  // An ID for the class, not necessarily human-readable (e.g. a Google
+  // Knowledge Graph ID [1]), filled from the label map.
+  //
+  // [1]: https://developers.google.com/knowledge-graph
+  char* label;
+} TfLiteCategory;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_CATEGORY_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_options.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_options.h
new file mode 100644
index 0000000..829e9e97
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_options.h
@@ -0,0 +1,66 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CLASSIFICATION_OPTIONS_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CLASSIFICATION_OPTIONS_H_
+
+#include <stdint.h>
+
+// Defines C Struct for Classification Options Shared by All Classification
+// Tasks.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Holds pointer to array of C strings and length for looping through the array.
+typedef struct TfLiteStringArrayOption {
+  // Length of list. length can be used to loop through list.
+  int length;
+
+  // Array of C strings.
+  char** list;
+} TfLiteStringArrayOption;
+
+// Holds settings for any single classification task.
+typedef struct TfLiteClassificationOptions {
+  // Optional denylist of class labels. If non NULL, classifications whose
+  // class label is in this set will be filtered out. Duplicate or unknown
+  // class labels are ignored. Mutually exclusive with label_allowlist.
+  TfLiteStringArrayOption label_denylist;
+
+  // Optional allowlist of class labels. If non-empty, classifications whose
+  // class label is not in this set will be filtered out. Duplicate or unknown
+  // class labels are ignored. Mutually exclusive with label_denylist.
+  TfLiteStringArrayOption label_allowlist;
+
+  // The locale to use for display names specified through the TFLite Model
+  // Metadata, if any. Defaults to English.
+  char* display_names_local;
+
+  // The maximum number of top-scored classification results to return. If < 0,
+  // all available results will be returned. If 0, an invalid argument error is
+  // returned. Defaults to -1.
+  int max_results;
+
+  // Score threshold, overrides the ones provided in the model metadata
+  // (if any). Results below this value are rejected.
+  float score_threshold;
+} TfLiteClassificationOptions;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CLASSIFICATION_OPTIONS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_result.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_result.cc
new file mode 100644
index 0000000..c277df0
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_result.cc
@@ -0,0 +1,46 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/processor/classification_result.h"
+
+#include <cstdlib>
+#include <memory>
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+void TfLiteClassificationResultDelete(
+    TfLiteClassificationResult* classification_result) {
+  for (int head = 0; head < classification_result->size; ++head) {
+    TfLiteClassifications classifications =
+        classification_result->classifications[head];
+    for (int rank = 0; rank < classifications.size; ++rank) {
+      // `strdup` obtains memory using `malloc` and the memory needs to be
+      // released using `free`.
+      free(classifications.categories[rank].display_name);
+      free(classifications.categories[rank].label);
+    }
+
+    delete[] classifications.categories;
+  }
+
+  delete[] classification_result->classifications;
+  delete classification_result;
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_result.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_result.h
new file mode 100644
index 0000000..1b73365a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/classification_result.h
@@ -0,0 +1,63 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CLASSIFICATION_RESULT_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_CLASSIFICATION_RESULT_H_
+
+#include "tensorflow_lite_support/c/task/processor/category.h"
+
+// Defines C structure for Classification Results and associated helper methods.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// List of predicted classes (aka labels) for a given image classifier head.
+typedef struct TfLiteClassifications {
+  // The index of the image classifier head these classes refer to. This is
+  // useful for multi-head models.
+  int head_index;
+
+  // Number of predicted classes which can be used to traverse the array of
+  // predicted classes.
+  int size;
+
+  // The array of predicted classes, usually sorted by descending scores (e.g.
+  // from high to low probability). Since this array is dynamically allocated,
+  // use size to traverse through the array.
+  TfLiteCategory* categories;
+} TfLiteClassifications;
+
+// Holds Image Classification results.
+// Contains one set of results per image classifier head.
+typedef struct TfLiteClassificationResult {
+  // Number of predicted classes which can be used to traverse the array of
+  // predicted classes.
+  int size;
+
+  // Array of image classifier results per image classifier head. This array can
+  // have any number of results. size holds the size of this array. size should
+  // be used to traverse this array.
+  TfLiteClassifications* classifications;
+} TfLiteClassificationResult;
+
+// Frees up the ClassificationResult Structure.
+void TfLiteClassificationResultDelete(
+    TfLiteClassificationResult* classification_result);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_CLASSIFICATION_RESULT_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/detection_result.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/detection_result.h
new file mode 100644
index 0000000..2f4c701
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/processor/detection_result.h
@@ -0,0 +1,65 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_DETECTION_RESULT_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_PROCESSOR_DETECTION_RESULT_H_
+
+#include "tensorflow_lite_support/c/task/processor/bounding_box.h"
+#include "tensorflow_lite_support/c/task/processor/category.h"
+
+// Defines C structure for Object Detection Results and associated helper
+// methods.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Bounding box and list of predicted classes (aka labels) for a detected
+// object.
+typedef struct TfLiteDetection {
+  // The bounding box of the detected object.
+  TfLiteBoundingBox bounding_box;
+
+  // The array of predicted classes for the object detection represented by an
+  // instance of TfLiteDetection, usually sorted by descending scores (e.g. from
+  // high to low probability). Since this array is dynamically allocated, use
+  // size to traverse through the array.
+  TfLiteCategory* categories;
+
+  // Number of detectd objects be used to traverse the array of the detected
+  // objects.
+  int size;
+} TfLiteDetection;
+
+// Holds Object Detection results.
+// Contains one set of results per detected object.
+typedef struct TfLiteDetectionResult {
+  // Number of detectd objects be used to traverse the array of the detected
+  // objects.
+  int size;
+
+  // Array of results per detected object. This array can
+  // have any number of results. size holds the size of this array. size should
+  // be used to traverse this array.
+  TfLiteDetection* detections;
+} TfLiteDetectionResult;
+
+// Frees up the DetectionResult Structure.
+void TfLiteDetectionResultDelete(TfLiteDetectionResult* detection_result);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_DETECTION_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/BUILD
new file mode 100644
index 0000000..fd2e9740
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/BUILD
@@ -0,0 +1,79 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_library_with_tflite",
+)
+
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files([
+    "bert_nl_classifier.h",
+    "nl_classifier.h",
+    "nl_classifier_common.h",
+    "bert_question_answerer.h",
+])
+
+cc_library_with_tflite(
+    name = "nl_classifier",
+    srcs = [
+        "nl_classifier.cc",
+    ],
+    hdrs = [
+        "nl_classifier.h",
+        "nl_classifier_common.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
+    ],
+    deps = [
+        ":nl_classifier_common",
+        "//tensorflow_lite_support/cc/task/core:category",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "bert_nl_classifier",
+    srcs = [
+        "bert_nl_classifier.cc",
+    ],
+    hdrs = [
+        "bert_nl_classifier.h",
+        "nl_classifier_common.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/text:bert_nl_classifier",
+    ],
+    deps = [
+        ":nl_classifier_common",
+        "//tensorflow_lite_support/cc/task/core:category",
+        "//tensorflow_lite_support/cc/task/text/proto:bert_nl_classifier_options_proto_inc",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
+cc_library(
+    name = "nl_classifier_common",
+    srcs = [
+        "nl_classifier_common.cc",
+    ],
+    hdrs = [
+        "nl_classifier_common.h",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "bert_question_answerer",
+    srcs = [
+        "bert_question_answerer.cc",
+    ],
+    hdrs = [
+        "bert_question_answerer.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/text:bert_question_answerer",
+        "//tensorflow_lite_support/cc/task/text:question_answerer",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc
new file mode 100644
index 0000000..52907f4f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.cc
@@ -0,0 +1,93 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/text/bert_nl_classifier.h"
+
+#include <memory>
+
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/task/core/category.h"
+#include "tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
+#include "tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options_proto_inc.h"
+
+namespace {
+using CategoryCpp = ::tflite::task::core::Category;
+using BertNLClassifierCpp = ::tflite::task::text::BertNLClassifier;
+using BertNLClassifierOptionsCpp =
+    ::tflite::task::text::BertNLClassifierOptions;
+
+const TfLiteBertNLClassifierOptions kBertNLClassifierOptionsDefault = {128};
+}  // namespace
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+struct TfLiteBertNLClassifier {
+  std::unique_ptr<BertNLClassifierCpp> impl;
+};
+
+TfLiteBertNLClassifier* TfLiteBertNLClassifierCreateFromOptions(
+    const char* model_path,
+    const TfLiteBertNLClassifierOptions* options) {
+  BertNLClassifierOptionsCpp cc_options;
+
+  cc_options.mutable_base_options()->mutable_model_file()->set_file_name(
+      model_path);
+  auto classifier_status = BertNLClassifierCpp::CreateFromOptions(cc_options);
+
+  if (classifier_status.ok()) {
+    return new TfLiteBertNLClassifier{
+        .impl = std::unique_ptr<BertNLClassifierCpp>(
+            dynamic_cast<BertNLClassifierCpp*>(
+                classifier_status.value().release()))};
+
+  } else {
+    return nullptr;
+  }
+}
+
+TfLiteBertNLClassifier* TfLiteBertNLClassifierCreate(const char* model_path) {
+  return TfLiteBertNLClassifierCreateFromOptions(
+      model_path, &kBertNLClassifierOptionsDefault);
+}
+
+Categories* TfLiteBertNLClassifierClassify(
+    const TfLiteBertNLClassifier* classifier,
+    const char* text) {
+  std::vector<CategoryCpp> results =
+
+      classifier->impl->Classify(absl::string_view(text).data());
+  size_t size = results.size();
+  auto* categories = new Category[size];
+
+  for (size_t i = 0; i < size; ++i) {
+    categories[i].text = strdup(results[i].class_name.c_str());
+    categories[i].score = results[i].score;
+  }
+
+  auto* c_categories = new Categories;
+  c_categories->size = size;
+  c_categories->categories = categories;
+  return c_categories;
+}
+
+void TfLiteBertNLClassifierDelete(TfLiteBertNLClassifier* classifier) {
+  delete classifier;
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h
new file mode 100644
index 0000000..94138a2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_nl_classifier.h
@@ -0,0 +1,70 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_BERT_NL_CLASSIFIER_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_BERT_NL_CLASSIFIER_H_
+
+#include "tensorflow_lite_support/c/task/text/nl_classifier_common.h"
+// --------------------------------------------------------------------------
+// C API for BertNLClassifier.
+//
+// Usage:
+// // Create the model and interpreter options.
+// TfLiteBertNLClassifier* classifier =
+//     TfLiteBertNLClassifierCreate("/path/to/model.tflite");
+//
+// // Classification.
+// Categories* categories = TfLiteBertNLClassifierClassify(classifier,
+//     question);
+//
+// // Dispose of the API object.
+// TfLiteBertNLClassifierDelete(classifier);
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef struct TfLiteBertNLClassifier TfLiteBertNLClassifier;
+
+typedef struct TfLiteBertNLClassifierOptions {
+  // Max number of tokens to pass to the model.
+  //
+  // Deprecated: max_seq_len is now read from the model (i.e. input tensor size)
+  // automatically.
+  int max_seq_len;
+} TfLiteBertNLClassifierOptions;
+
+// Creates TfLiteBertNLClassifier from model path and options, returns nullptr
+// if the file doesn't exist or is not a well formatted TFLite model path.
+TfLiteBertNLClassifier* TfLiteBertNLClassifierCreateFromOptions(
+    const char* model_path,
+    const TfLiteBertNLClassifierOptions* options);
+
+// Creates TfLiteBertNLClassifier from model path and default options, returns
+// nullptr if the file doesn't exist or is not a well formatted TFLite model
+// path.
+TfLiteBertNLClassifier* TfLiteBertNLClassifierCreate(const char* model_path);
+
+// Invokes the encapsulated TFLite model and classifies the input text.
+Categories* TfLiteBertNLClassifierClassify(
+    const TfLiteBertNLClassifier* classifier,
+    const char* text);
+
+void TfLiteBertNLClassifierDelete(TfLiteBertNLClassifier* classifier);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_BERT_NL_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc
new file mode 100644
index 0000000..1887d52
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.cc
@@ -0,0 +1,89 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/text/bert_question_answerer.h"
+
+#include <memory>
+
+#include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
+#include "tensorflow_lite_support/cc/task/text/question_answerer.h"
+
+namespace {
+using BertQuestionAnswererCpp = ::tflite::task::text::BertQuestionAnswerer;
+using QaAnswerCpp = ::tflite::task::text::QaAnswer;
+}  // namespace
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+struct TfLiteBertQuestionAnswerer {
+  std::unique_ptr<BertQuestionAnswererCpp> impl;
+};
+
+TfLiteBertQuestionAnswerer* TfLiteBertQuestionAnswererCreate(
+    const char* model_path) {
+  auto bert_qa_status =
+      BertQuestionAnswererCpp::CreateFromFile(std::string(model_path));
+  if (bert_qa_status.ok()) {
+    return new TfLiteBertQuestionAnswerer{
+        .impl = std::unique_ptr<BertQuestionAnswererCpp>(
+            dynamic_cast<BertQuestionAnswererCpp*>(
+                bert_qa_status.value().release()))};
+  } else {
+    return nullptr;
+  }
+}
+
+TfLiteQaAnswers* TfLiteBertQuestionAnswererAnswer(
+    const TfLiteBertQuestionAnswerer* question_answerer,
+    const char* context,
+    const char* question) {
+  std::vector<QaAnswerCpp> answers = question_answerer->impl->Answer(
+      absl::string_view(context).data(), absl::string_view(question).data());
+  size_t size = answers.size();
+  auto* qa_answers = new TfLiteQaAnswer[size];
+
+  for (size_t i = 0; i < size; ++i) {
+    qa_answers[i].start = answers[i].pos.start;
+    qa_answers[i].end = answers[i].pos.end;
+    qa_answers[i].logit = answers[i].pos.logit;
+    qa_answers[i].text = strdup(answers[i].text.c_str());
+  }
+
+  auto* c_answers = new TfLiteQaAnswers;
+  c_answers->size = size;
+  c_answers->answers = qa_answers;
+  return c_answers;
+}
+
+void TfLiteBertQuestionAnswererDelete(
+    TfLiteBertQuestionAnswerer* bert_question_answerer) {
+  delete bert_question_answerer;
+}
+
+void TfLiteQaAnswersDelete(TfLiteQaAnswers* qa_answers) {
+  for (int i = 0; i < qa_answers->size; i++) {
+    // `strdup` obtains memory using `malloc` and the memory needs to be
+    // released using `free`.
+    free(qa_answers->answers[i].text);
+  }
+  delete[] qa_answers->answers;
+  delete qa_answers;
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h
new file mode 100644
index 0000000..e9a1190
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/bert_question_answerer.h
@@ -0,0 +1,74 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_BERT_QUESTION_ANSWERER_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_BERT_QUESTION_ANSWERER_H_
+
+// --------------------------------------------------------------------------
+// C API for BertQuestionAnswerer.
+//
+// Usage:
+// <pre><code>
+// // Create the model and interpreter options.
+// TfLiteBertQuestionAnswerer* qa_answerer =
+//     TfLiteBertQuestionAnswererCreate("/path/to/model.tflite");
+//
+// // Answer a question.
+// TfLiteQaAnswers* answers = TfLiteBertQuestionAnswererAnswer(qa_answerer,
+//     question);
+//
+// // Dispose of the API and QaAnswers objects.
+// TfLiteBertQuestionAnswererDelete(qa_answerer);
+// TfLiteQaAnswersDelete(answers);
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef struct TfLiteBertQuestionAnswerer TfLiteBertQuestionAnswerer;
+
+typedef struct TfLiteQaAnswer {
+  int start;
+  int end;
+  float logit;
+  char* text;
+} TfLiteQaAnswer;
+
+typedef struct TfLiteQaAnswers {
+  int size;
+  TfLiteQaAnswer* answers;
+} TfLiteQaAnswers;
+
+// Creates TfLiteBertQuestionAnswerer from model path, returns nullptr if the
+// file doesn't exist or is not a well formatted TFLite model path.
+TfLiteBertQuestionAnswerer* TfLiteBertQuestionAnswererCreate(
+    const char* model_path);
+
+// Invokes the encapsulated TFLite model and answers a question based on
+// context.
+TfLiteQaAnswers* TfLiteBertQuestionAnswererAnswer(
+    const TfLiteBertQuestionAnswerer* question_answerer,
+    const char* context,
+    const char* question);
+
+void TfLiteBertQuestionAnswererDelete(
+    TfLiteBertQuestionAnswerer* bert_question_answerer);
+
+void TfLiteQaAnswersDelete(TfLiteQaAnswers* qa_answers);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_BERT_QUESTION_ANSWERER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc
new file mode 100644
index 0000000..1e6805c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.cc
@@ -0,0 +1,94 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/text/nl_classifier.h"
+
+#include <memory>
+
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/task/core/category.h"
+#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
+
+namespace {
+using CategoryCpp = ::tflite::task::core::Category;
+using NLClassifierCpp = ::tflite::task::text::nlclassifier::NLClassifier;
+using NLClassifierOptionsCpp =
+    ::tflite::task::text::nlclassifier::NLClassifierOptions;
+}  // namespace
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+struct TfLiteNLClassifier {
+  std::unique_ptr<NLClassifierCpp> impl;
+};
+
+TfLiteNLClassifier* TfLiteNLClassifierCreateFromOptions(
+    const char* model_path,
+    const TfLiteNLClassifierOptions* options) {
+  auto classifier_status = NLClassifierCpp::CreateFromFileAndOptions(
+      std::string(model_path),
+      {
+          .input_tensor_index = options->input_tensor_index,
+          .output_score_tensor_index = options->output_score_tensor_index,
+          .output_label_tensor_index = options->output_label_tensor_index,
+          .input_tensor_name = !options->input_tensor_name
+                                   ? ""
+                                   : std::string(options->input_tensor_name),
+          .output_score_tensor_name =
+              !options->output_score_tensor_name
+                  ? ""
+                  : std::string(options->output_score_tensor_name),
+          .output_label_tensor_name =
+              !options->output_label_tensor_name
+                  ? ""
+                  : std::string(options->output_label_tensor_name),
+      });
+
+  if (classifier_status.ok()) {
+    return new TfLiteNLClassifier{
+        .impl = std::unique_ptr<NLClassifierCpp>(dynamic_cast<NLClassifierCpp*>(
+            classifier_status.value().release()))};
+  } else {
+    return nullptr;
+  }
+}
+
+Categories* TfLiteNLClassifierClassify(const TfLiteNLClassifier* classifier,
+                                       const char* text) {
+  std::vector<CategoryCpp> results =
+      classifier->impl->Classify(absl::string_view(text).data());
+  size_t size = results.size();
+  auto* categories = new Category[size];
+
+  for (size_t i = 0; i < size; ++i) {
+    categories[i].text = strdup(results[i].class_name.c_str());
+    categories[i].score = results[i].score;
+  }
+
+  auto* c_categories = new Categories;
+  c_categories->size = size;
+  c_categories->categories = categories;
+  return c_categories;
+}
+
+void TfLiteNLClassifierDelete(TfLiteNLClassifier* classifier) {
+  delete classifier;
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h
new file mode 100644
index 0000000..389ca5d6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier.h
@@ -0,0 +1,64 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_NL_CLASSIFIER_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_NL_CLASSIFIER_H_
+
+#include "tensorflow_lite_support/c/task/text/nl_classifier_common.h"
+// --------------------------------------------------------------------------
+// C API for NLClassifier.
+//
+// Usage:
+// // Create the model and interpreter options.
+// TfLiteNLClassifier* classifier = TfLiteNLClassifierCreate(
+//     "/path/to/model.tflite");
+//
+// // Classification.
+// Categories* categories = TfLiteNLClassifierClassify(classifier, question);
+//
+// // Dispose of the API object.
+// TfLiteNLClassifierDelete(classifier);
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef struct TfLiteNLClassifier TfLiteNLClassifier;
+
+typedef struct TfLiteNLClassifierOptions {
+  int input_tensor_index;
+  int output_score_tensor_index;
+  int output_label_tensor_index;
+  const char* input_tensor_name;
+  const char* output_score_tensor_name;
+  const char* output_label_tensor_name;
+} TfLiteNLClassifierOptions;
+
+// Creates TfLiteNLClassifier from model path and options, returns nullptr if
+// the file doesn't exist or is not a well formatted TFLite model path.
+TfLiteNLClassifier* TfLiteNLClassifierCreateFromOptions(
+    const char* model_path,
+    const TfLiteNLClassifierOptions* options);
+
+// Invokes the encapsulated TFLite model and classifies the input text.
+Categories* TfLiteNLClassifierClassify(const TfLiteNLClassifier* classifier,
+                                       const char* text);
+
+void TfLiteNLClassifierDelete(TfLiteNLClassifier* classifier);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_NL_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier_common.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier_common.cc
new file mode 100644
index 0000000..c26ce05
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier_common.cc
@@ -0,0 +1,36 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/text/nl_classifier_common.h"
+
+#include <memory>
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+void NLClassifierCategoriesDelete(Categories* categories) {
+  for (int i = 0; i < categories->size; i++) {
+    // `strdup` obtains memory using `malloc` and the memory needs to be
+    // released using `free`.
+    free(categories->categories[i].text);
+  }
+  delete[] categories->categories;
+  delete categories;
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier_common.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier_common.h
new file mode 100644
index 0000000..ed4d1c8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/text/nl_classifier_common.h
@@ -0,0 +1,43 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_NL_CLASSIFIER_COMMON_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_NL_CLASSIFIER_COMMON_H_
+
+// C API for the NLClassifier results, Catergory.
+
+// TODO(b/197355311): deprecate this class and use the unified one with image
+// and audio.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef struct Category {
+  char* text;
+  double score;
+} Category;
+
+typedef struct Categories {
+  int size;
+  Category* categories;
+} Categories;
+
+void NLClassifierCategoriesDelete(Categories* categories);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_TEXT_NL_CLASSIFIER_COMMON_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/BUILD
new file mode 100644
index 0000000..5bd132a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/BUILD
@@ -0,0 +1,50 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library_with_tflite(
+    name = "image_classifier",
+    srcs = [
+        "image_classifier.cc",
+    ],
+    hdrs = [
+        "image_classifier.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/vision:image_classifier",
+    ],
+    deps = [
+        "//tensorflow_lite_support/c:common",
+        "//tensorflow_lite_support/c:common_utils",
+        "//tensorflow_lite_support/c/task/core:base_options",
+        "//tensorflow_lite_support/c/task/processor:bounding_box",
+        "//tensorflow_lite_support/c/task/processor:classification_options",
+        "//tensorflow_lite_support/c/task/processor:classification_result",
+        "//tensorflow_lite_support/c/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/c/task/vision/utils:frame_buffer_cpp_c_utils",
+        "//tensorflow_lite_support/cc/task/vision/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_classifier_options_proto_inc",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "object_detector",
+    hdrs = [
+        "object_detector.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/vision:object_detector",
+    ],
+    deps = [
+        "//tensorflow_lite_support/c:common",
+        "//tensorflow_lite_support/c/task/core:base_options",
+        "//tensorflow_lite_support/c/task/processor:classification_options",
+        "//tensorflow_lite_support/c/task/processor:detection_result",
+        "//tensorflow_lite_support/c/task/vision/core:frame_buffer",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/core/BUILD
new file mode 100644
index 0000000..75c97b4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/core/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "frame_buffer",
+    hdrs = [
+        "frame_buffer.h",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/core/frame_buffer.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/core/frame_buffer.h
new file mode 100644
index 0000000..8cab2676
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/core/frame_buffer.h
@@ -0,0 +1,81 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_FRAME_BUFFER_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_FRAME_BUFFER_H_
+
+#include <stdint.h>
+
+// Defines C structs for holding the frame buffer.
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// Colorspace formats.
+enum TfLiteFrameBufferFormat {
+  kRGBA,
+  kRGB,
+  kNV12,
+  kNV21,
+  kYV12,
+  kYV21,
+  kGRAY,
+  kUNKNOWN
+};
+
+// FrameBuffer content orientation follows EXIF specification. The name of
+// each enum value defines the position of the 0th row and the 0th column of
+// the image content. See http://jpegclub.org/exif_orientation.html for
+// details.
+enum TfLiteFrameBufferOrientation {
+  kTopLeft = 1,
+  kTopRight = 2,
+  kBottomRight = 3,
+  kBottomLeft = 4,
+  kLeftTop = 5,
+  kRightTop = 6,
+  kRightBottom = 7,
+  kLeftBottom = 8
+};
+
+// Dimension information for the whole frame.
+struct TfLiteFrameBufferDimension {
+  // The width dimension in pixel unit.
+  int width;
+  // The height dimension in pixel unit.
+  int height;
+};
+
+// A `FrameBuffer` provides a view into the provided backing buffer (e.g. camera
+// frame or still image) with buffer format information. FrameBuffer doesn't
+// take ownership of the provided backing buffer. The caller is responsible to
+// manage the backing buffer lifecycle for the lifetime of the FrameBuffer.
+typedef struct TfLiteFrameBuffer {
+  // Colorspace format of the frame buffer.
+  enum TfLiteFrameBufferFormat format;
+  // Orientation of the frame buffer.
+  enum TfLiteFrameBufferOrientation orientation;
+  // Dimension information for the whole frame.
+  struct TfLiteFrameBufferDimension dimension;
+  // Holds the backing buffer for the frame buffer. Only single planar images
+  // are supported as of now.
+  uint8_t* buffer;
+} TfLiteFrameBuffer;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_FRAME_BUFFER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc
new file mode 100644
index 0000000..8981e66
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.cc
@@ -0,0 +1,236 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/vision/image_classifier.h"
+
+#include <memory>
+
+#include "tensorflow_lite_support/c/common_utils.h"
+#include "tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/image_classifier.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h"
+
+namespace {
+using ::tflite::support::StatusOr;
+using ClassificationResultCpp = ::tflite::task::vision::ClassificationResult;
+using ClassificationsCpp = ::tflite::task::vision::Classifications;
+using ClassCpp = ::tflite::task::vision::Class;
+using BoundingBoxCpp = ::tflite::task::vision::BoundingBox;
+using ImageClassifierCpp = ::tflite::task::vision::ImageClassifier;
+using ImageClassifierOptionsCpp =
+    ::tflite::task::vision::ImageClassifierOptions;
+using FrameBufferCpp = ::tflite::task::vision::FrameBuffer;
+using ::tflite::support::TfLiteSupportStatus;
+
+StatusOr<ImageClassifierOptionsCpp> CreateImageClassifierCppOptionsFromCOptions(
+    const TfLiteImageClassifierOptions* c_options) {
+  if (c_options == nullptr) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("Expected non null options."),
+        TfLiteSupportStatus::kInvalidArgumentError);
+  }
+
+  ImageClassifierOptionsCpp cpp_options = {};
+
+  // More file sources can be added in else ifs
+  if (c_options->base_options.model_file.file_path)
+    cpp_options.mutable_base_options()->mutable_model_file()->set_file_name(
+        c_options->base_options.model_file.file_path);
+
+  // c_options->base_options.compute_settings.num_threads is expected to be
+  // set to value > 0 or -1. Otherwise invoking
+  // ImageClassifierCpp::CreateFromOptions() results in a not ok status.
+  cpp_options.mutable_base_options()
+      ->mutable_compute_settings()
+      ->mutable_tflite_settings()
+      ->mutable_cpu_settings()
+      ->set_num_threads(
+          c_options->base_options.compute_settings.cpu_settings.num_threads);
+
+  for (int i = 0; i < c_options->classification_options.label_denylist.length;
+       i++)
+    cpp_options.add_class_name_blacklist(
+        c_options->classification_options.label_denylist.list[i]);
+
+  for (int i = 0; i < c_options->classification_options.label_allowlist.length;
+       i++)
+    cpp_options.add_class_name_whitelist(
+        c_options->classification_options.label_allowlist.list[i]);
+
+  // Check needed since setting a nullptr for this field results in a segfault
+  // on invocation of ImageClassifierCpp::CreateFromOptions().
+  if (c_options->classification_options.display_names_local) {
+    cpp_options.set_display_names_locale(
+        c_options->classification_options.display_names_local);
+  }
+
+  // c_options->classification_options.max_results is expected to be set to -1
+  // or any value > 0. Otherwise invoking
+  // ImageClassifierCpp::CreateFromOptions() results in a not ok status.
+  cpp_options.set_max_results(c_options->classification_options.max_results);
+
+  cpp_options.set_score_threshold(
+      c_options->classification_options.score_threshold);
+
+  return cpp_options;
+}
+}  // namespace
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+struct TfLiteImageClassifier {
+  std::unique_ptr<ImageClassifierCpp> impl;
+};
+
+TfLiteImageClassifierOptions TfLiteImageClassifierOptionsCreate() {
+  // Use brace-enclosed initializer list will break the Kokoro test.
+  TfLiteImageClassifierOptions options = {{{0}}};
+  options.classification_options.max_results = -1;
+  options.classification_options.score_threshold = 0.0;
+  options.base_options.compute_settings.cpu_settings.num_threads = -1;
+  return options;
+}
+
+TfLiteImageClassifier* TfLiteImageClassifierFromOptions(
+    const TfLiteImageClassifierOptions* options,
+    TfLiteSupportError** error) {
+  StatusOr<ImageClassifierOptionsCpp> cpp_option_status =
+      CreateImageClassifierCppOptionsFromCOptions(options);
+
+  if (!cpp_option_status.ok()) {
+    ::tflite::support::CreateTfLiteSupportErrorWithStatus(
+        cpp_option_status.status(), error);
+    return nullptr;
+  }
+
+  StatusOr<std::unique_ptr<ImageClassifierCpp>> classifier_status =
+      ImageClassifierCpp::CreateFromOptions(cpp_option_status.value());
+
+  if (classifier_status.ok()) {
+    return new TfLiteImageClassifier{.impl =
+                                         std::move(classifier_status.value())};
+  } else {
+    ::tflite::support::CreateTfLiteSupportErrorWithStatus(
+        classifier_status.status(), error);
+    return nullptr;
+  }
+}
+
+TfLiteClassificationResult* GetClassificationResultCStruct(
+    const ClassificationResultCpp& classification_result_cpp) {
+  auto c_classifications =
+      new TfLiteClassifications[classification_result_cpp
+                                    .classifications_size()];
+
+  for (int head = 0; head < classification_result_cpp.classifications_size();
+       ++head) {
+    const ClassificationsCpp& classifications =
+        classification_result_cpp.classifications(head);
+    c_classifications[head].head_index = head;
+
+    auto c_categories = new TfLiteCategory[classifications.classes_size()];
+    c_classifications->size = classifications.classes_size();
+
+    for (int rank = 0; rank < classifications.classes_size(); ++rank) {
+      const ClassCpp& classification = classifications.classes(rank);
+      c_categories[rank].index = classification.index();
+      c_categories[rank].score = classification.score();
+
+      if (classification.has_class_name())
+        c_categories[rank].label = strdup(classification.class_name().c_str());
+      else
+        c_categories[rank].label = nullptr;
+
+      if (classification.has_display_name())
+        c_categories[rank].display_name =
+            strdup(classification.display_name().c_str());
+      else
+        c_categories[rank].display_name = nullptr;
+    }
+    c_classifications[head].categories = c_categories;
+  }
+
+  auto c_classification_result = new TfLiteClassificationResult;
+  c_classification_result->classifications = c_classifications;
+  c_classification_result->size =
+      classification_result_cpp.classifications_size();
+
+  return c_classification_result;
+}
+
+TfLiteClassificationResult* TfLiteImageClassifierClassifyWithRoi(
+    const TfLiteImageClassifier* classifier,
+    const TfLiteFrameBuffer* frame_buffer,
+    const TfLiteBoundingBox* roi,
+    TfLiteSupportError** error) {
+  if (classifier == nullptr) {
+    tflite::support::CreateTfLiteSupportError(
+        kInvalidArgumentError, "Expected non null image classifier.", error);
+    return nullptr;
+  }
+
+  StatusOr<std::unique_ptr<FrameBufferCpp>> cpp_frame_buffer_status =
+      ::tflite::task::vision::CreateCppFrameBuffer(frame_buffer);
+  if (!cpp_frame_buffer_status.ok()) {
+    tflite::support::CreateTfLiteSupportErrorWithStatus(
+        cpp_frame_buffer_status.status(), error);
+    return nullptr;
+  }
+
+  BoundingBoxCpp cc_roi;
+  if (roi == nullptr) {
+    cc_roi.set_width(frame_buffer->dimension.width);
+    cc_roi.set_height(frame_buffer->dimension.height);
+  } else {
+    cc_roi.set_origin_x(roi->origin_x);
+    cc_roi.set_origin_y(roi->origin_y);
+    cc_roi.set_width(roi->width);
+    cc_roi.set_height(roi->height);
+  }
+
+  // fnc_sample(cpp_frame_buffer_status);
+  StatusOr<ClassificationResultCpp> cpp_classification_result_status =
+      classifier->impl->Classify(*std::move(cpp_frame_buffer_status.value()),
+                                 cc_roi);
+
+  if (!cpp_classification_result_status.ok()) {
+    tflite::support::CreateTfLiteSupportErrorWithStatus(
+        cpp_classification_result_status.status(), error);
+    return nullptr;
+  }
+
+  return GetClassificationResultCStruct(
+      cpp_classification_result_status.value());
+}
+
+TfLiteClassificationResult* TfLiteImageClassifierClassify(
+    const TfLiteImageClassifier* classifier,
+    const TfLiteFrameBuffer* frame_buffer,
+    TfLiteSupportError** error) {
+  return TfLiteImageClassifierClassifyWithRoi(classifier, frame_buffer, nullptr,
+                                              error);
+}
+
+void TfLiteImageClassifierDelete(TfLiteImageClassifier* classifier) {
+  delete classifier;
+}
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h
new file mode 100644
index 0000000..8a53e5e2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/image_classifier.h
@@ -0,0 +1,214 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_IMAGE_CLASSIFIER_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_IMAGE_CLASSIFIER_H_
+
+#include <stdint.h>
+
+#include "tensorflow_lite_support/c/common.h"
+#include "tensorflow_lite_support/c/task/core/base_options.h"
+#include "tensorflow_lite_support/c/task/processor/bounding_box.h"
+#include "tensorflow_lite_support/c/task/processor/classification_options.h"
+#include "tensorflow_lite_support/c/task/processor/classification_result.h"
+#include "tensorflow_lite_support/c/task/vision/core/frame_buffer.h"
+
+// --------------------------------------------------------------------------
+/// C API for ImageClassifiier.
+///
+/// The API leans towards simplicity and uniformity instead of convenience, as
+/// most usage will be by language-specific wrappers. It provides largely the
+/// same set of functionality as that of the C++ TensorFlow Lite
+/// `ImageClassifier` API, but is useful for shared libraries where having
+/// a stable ABI boundary is important.
+///
+/// Usage:
+/// <pre><code>
+/// // Create the model
+/// Using the options initialized with default values returned by
+/// TfLiteImageClassifierOptionsCreate() makes sure that there will be no
+/// undefined behaviour due to garbage values in unitialized members.
+/// TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+///
+/// Set the model file path in options
+///   options.base_options.model_file.file_path = "/path/to/model.tflite";
+///
+/// If need be, set values for any options to customize behaviour.
+/// options.base_options.compute_settings.cpu_settings.num_threads = 3
+///
+/// Create TfLiteImageClassifier using the options:
+/// If error information is not nedded in case of failure:
+/// TfLiteImageClassifier* image_classifier =
+///       TfLiteImageClassifierFromOptions(&options, NULL);
+///
+/// If error information is nedded in case of failure:
+/// TfLiteSupportError* create_error = NULL;
+/// TfLiteImageClassifier* image_classifier =
+///       TfLiteImageClassifierFromOptions(&options, &create_error);
+///
+/// if (!image_classifier) {
+///   Handle failure.
+///   Do something with `create_error`, if requested as illustrated above.
+/// }
+///
+/// Dispose of the create_error object.
+/// TfLiteSupportErrorDelete(create_error);
+///
+/// Classify an image
+/// TfLiteFrameBuffer frame_buffer = { Initialize with image data }
+///
+/// If error information is not nedded in case of failure:
+/// TfLiteClassificationResult* classification_result =
+///       TfLiteImageClassifierClassify(image_classifier, &frame_buffer, NULL);
+///
+/// If error information is nedded in case of failure:
+/// TfLiteSupportError* classify_error = NULL;
+/// TfLiteClassificationResult* classification_result =
+///       TfLiteImageClassifierClassify(image_classifier, &frame_buffer,
+///       &classify_error);
+///
+/// if (!classification_result) {
+///   Handle failure.
+///   Do something with `classify_error`, if requested as illustrated above.
+/// }
+///
+/// Dispose of the classify_error object.
+/// TfLiteSupportErrorDelete(classify_error);
+///
+/// Dispose of the API object.
+/// TfLiteImageClassifierDelete(image_classifier);
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef struct TfLiteImageClassifier TfLiteImageClassifier;
+
+typedef struct TfLiteImageClassifierOptions {
+  TfLiteClassificationOptions classification_options;
+  TfLiteBaseOptions base_options;
+} TfLiteImageClassifierOptions;
+
+// Creates and returns TfLiteImageClassifierOptions initialized with default
+// values. Default values are as follows:
+// 1. .classification_options.max_results = -1, which returns all classification
+// categories by default.
+// 2. .base_options.compute_settings.tflite_settings.cpu_settings.num_threads =
+// -1, which makes the TFLite runtime choose the value.
+// 3. .classification_options.score_threshold = 0
+// 4. All pointers like .base_options.model_file.file_path,
+// .base_options.classification_options.display_names_local,
+// .classification_options.label_allowlist.list,
+// options.classification_options.label_denylist.list are NULL.
+// 5. All other integer values are initialized to 0.
+TfLiteImageClassifierOptions TfLiteImageClassifierOptionsCreate();
+
+// Creates TfLiteImageClassifier from options.
+// .base_options.model_file.file_path in TfLiteImageClassifierOptions should be
+// set to the path of the tflite model you wish to create the
+// TfLiteImageClassifier with.
+// Create TfLiteImageClassifierOptions using
+// TfLiteImageClassifierOptionsCreate(). If need be, you can change the default
+// values of options for customizing classification, If options are not created
+// in the aforementioned way, you have to make sure that all members are
+// initialized to respective default values and all pointer members are zero
+// initialized to avoid any undefined behaviour.
+//
+// Returns the created image classifier in case of success.
+// Returns nullptr on failure which happens commonly due to one of the following
+// issues:
+// 1. file doesn't exist or is not a well formatted.
+// 2. options is nullptr.
+// 3. Both options.classification_options.label_denylist and
+// options.classification_options.label_allowlist are non empty. These
+// fields are mutually exclusive.
+//
+// The caller can check if an error was encountered by testing if the returned
+// value of the function is null. If the caller doesn't want the reason for
+// failure, they can simply pass a NULL for the address of the error pointer as
+// shown below:
+//
+// TfLiteImageClassifier* classifier = TfLiteImageClassifierFromOptions(options,
+// NULL);
+//
+// If the caller wants to be informed of the reason for failure, they must pass
+// the adress of a pointer of type TfLiteSupportError to the `error` param as
+// shown below:
+//
+// TfLiteSupport *error = NULL:
+// TfLiteImageClassifier* classifier = TfLiteImageClassifierFromOptions(options,
+// &error);
+//
+// In case of unsuccessful execution, Once the function returns, the error
+// pointer will point to a struct containing the error information. If error
+// info is passed back to the caller, it is the responsibility of the caller to
+// free the error struct by calling the following method defined in common.h:
+//
+// TfLiteSupportErrorDelete(error)
+//
+TfLiteImageClassifier* TfLiteImageClassifierFromOptions(
+    const TfLiteImageClassifierOptions* options,
+    TfLiteSupportError** error);
+
+// Invokes the encapsulated TFLite model and classifies the frame_buffer.
+// Returns a pointer to the created classification result in case of success or
+// NULL in case of failure. The caller must test the return value to identify
+// success or failure. If the caller doesn't want the reason for failure, they
+// can simply pass a NULL for the address of the error pointer as shown below:
+//
+// TfLiteClassificationResult* classification_result =
+// TfLiteImageClassifierClassify(&options, NULL);
+//
+// If the caller wants to be informed of the reason for failure, they must pass
+// the adress of a pointer of type TfLiteSupportError to the `error` param as
+// shown below:
+//
+// TfLiteSupport *error = NULL:
+// TfLiteImageClassifier* classifier = TfLiteImageClassifierFromOptions(options,
+// &error);
+//
+// In case of unsuccessful execution, Once the function returns, the error
+// pointer will point to a struct containing the error information. If error
+// info is passed back to the caller, it is the responsibility of the caller to
+// free the error struct by calling the following method defined in common.h:
+//
+// TfLiteSupportErrorDelete(error)
+//
+TfLiteClassificationResult* TfLiteImageClassifierClassify(
+    const TfLiteImageClassifier* classifier,
+    const TfLiteFrameBuffer* frame_buffer,
+    TfLiteSupportError** error);
+
+// Invokes the encapsulated TFLite model and classifies the region of the
+// frame_buffer specified by the bounding box. Same as TfLiteImageClassifier*
+// TfLiteImageClassifierFromOptions(
+//    const TfLiteImageClassifierOptions* options, TfLiteSupportError** error),
+//    except that the
+// classification is performed based on the input region of interest. Cropping
+// according to this region of interest is prepended to the pre-processing
+// operations.
+TfLiteClassificationResult* TfLiteImageClassifierClassifyWithRoi(
+    const TfLiteImageClassifier* classifier,
+    const TfLiteFrameBuffer* frame_buffer,
+    const TfLiteBoundingBox* roi,
+    TfLiteSupportError** error);
+
+// Disposes off the image classifier.
+void TfLiteImageClassifierDelete(TfLiteImageClassifier* classifier);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_IMAGE_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h
new file mode 100644
index 0000000..5a2d3e1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/object_detector.h
@@ -0,0 +1,200 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_IMAGE_CLASSIFIER_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_IMAGE_CLASSIFIER_H_
+
+#include <stdint.h>
+
+#include "tensorflow_lite_support/c/common.h"
+#include "tensorflow_lite_support/c/task/core/base_options.h"
+#include "tensorflow_lite_support/c/task/processor/classification_options.h"
+#include "tensorflow_lite_support/c/task/processor/detection_result.h"
+#include "tensorflow_lite_support/c/task/vision/core/frame_buffer.h"
+
+// --------------------------------------------------------------------------
+/// C API for Object Detector.
+///
+/// The API leans towards simplicity and uniformity instead of convenience, as
+/// most usage will be by language-specific wrappers. It provides largely the
+/// same set of functionality as that of the C++ TensorFlow Lite
+/// `ObjectDetector` API, but is useful for shared libraries where having
+/// a stable ABI boundary is important.
+///
+/// Usage:
+/// <pre><code>
+/// // Create the model
+/// Using the options initialized with default values returned by
+/// TfLiteObjectDetectorOptionsCreate() makes sure that there will be no
+/// undefined behaviour due to garbage values in unitialized members.
+/// TfLiteObjectDetectorOptions options = TfLiteObjectDetectorOptionsCreate();
+///
+/// Set the model file path in options
+///   options.base_options.model_file.file_path = "/path/to/model.tflite";
+///
+/// If need be, set values for any options to customize behaviour.
+/// options.base_options.compute_settings.cpu_settings.num_threads = 3
+///
+/// Create TfLiteObjectDetector using the options:
+/// If error information is not nedded in case of failure:
+/// TfLiteObjectDetector* object_detector =
+///       TfLiteObjectDetectorFromOptions(&options, NULL);
+///
+/// If error information is nedded in case of failure:
+/// TfLiteSupportError* create_error = NULL;
+/// TfLiteObjectDetector* object_detector =
+///       TfLiteObjectDetectorFromOptions(&options, &create_error);
+///
+/// if (!object_detector) {
+///   Handle failure.
+///   Do something with `create_error`, if requested as illustrated above.
+/// }
+///
+/// Dispose of the create_error object.
+/// TfLiteSupportErrorDelete(create_error);
+///
+/// Classify an image
+/// TfLiteFrameBuffer frame_buffer = { Initialize with image data }
+///
+/// If error information is not nedded in case of failure:
+/// TfLiteDetectionResult* detection_result =
+///       TfLiteObjectDetectorClassify(object_detector, &frame_buffer, NULL);
+///
+/// If error information is needed in case of failure:
+/// TfLiteSupportError* detect_error = NULL;
+/// TfLiteDetectionResult* detection_result =
+///       TfLiteObjectDetectorDetect(object_detector, &frame_buffer,
+///       &detect_error);
+///
+/// if (!detection_result) {
+///   Handle failure.
+///   Do something with `detection_error`, if requested as illustrated above.
+/// }
+///
+/// Dispose of the detection_error object.
+/// TfLiteSupportErrorDelete(detection_error);
+///
+/// Dispose of the API object.
+/// TfLiteObjectDetectorOptionsDelete(object_detector);
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef struct TfLiteObjectDetector TfLiteObjectDetector;
+
+typedef struct TfLiteObjectDetectorOptions {
+  TfLiteClassificationOptions classification_options;
+  TfLiteBaseOptions base_options;
+} TfLiteObjectDetectorOptions;
+
+// Creates and returns TfLiteObjectDetectorOptions initialized with default
+// values. Default values are as follows:
+// 1. .classification_options.max_results = -1, which returns all classification
+// categories by default.
+// 2. .base_options.compute_settings.tflite_settings.cpu_settings.num_threads =
+// -1, which makes the TFLite runtime choose the value.
+// 3. .classification_options.score_threshold = 0
+// 4. All pointers like .base_options.model_file.file_path,
+// .base_options.classification_options.display_names_local,
+// .classification_options.label_allowlist.list,
+// options.classification_options.label_denylist.list are NULL.
+// 5. All other integer values are initialized to 0.
+TfLiteObjectDetectorOptions TfLiteObjectDetectorOptionsCreate();
+
+// Creates TfLiteObjectDetector from options.
+// .base_options.model_file.file_path in TfLiteObjectDetectorOptions should be
+// set to the path of the tflite model you wish to create the
+// TfLiteObjectDetector with.
+// Create TfLiteObjectDetectorOptions using
+// TfLiteObjectDetectorOptionsCreate(). If need be, you can change the default
+// values of options for customizing classification, If options are not created
+// in the aforementioned way, you have to make sure that all members are
+// initialized to respective default values and all pointer members are zero
+// initialized to avoid any undefined behaviour.
+//
+// Returns the created object detector in case of success.
+// Returns nullptr on failure which happens commonly due to one of the following
+// issues:
+// 1. file doesn't exist or is not a well formatted.
+// 2. options is nullptr.
+// 3. Both options.classification_options.label_denylist and
+// options.classification_options.label_allowlist are non empty. These
+// fields are mutually exclusive.
+//
+// The caller can check if an error was encountered by testing if the returned
+// value of the function is null. If the caller doesn't want the reason for
+// failure, they can simply pass a NULL for the address of the error pointer as
+// shown below:
+//
+// TfLiteObjectDetector* detector = TfLiteObjectDetectorFromOptions(options,
+// NULL);
+//
+// If the caller wants to be informed of the reason for failure, they must pass
+// the adress of a pointer of type TfLiteSupportError to the `error` param as
+// shown below:
+//
+// TfLiteSupport *error = NULL:
+// TfLiteObjectDetector* classifier = TfLiteObjectDetectorFromOptions(options,
+// &error);
+//
+// In case of unsuccessful execution, Once the function returns, the error
+// pointer will point to a struct containing the error information. If error
+// info is passed back to the caller, it is the responsibility of the caller to
+// free the error struct by calling the following method defined in common.h:
+//
+// TfLiteSupportErrorDelete(error)
+//
+TfLiteObjectDetector* TfLiteObjectDetectorFromOptions(
+    const TfLiteObjectDetectorOptions* options,
+    TfLiteSupportError** error);
+
+// Invokes the encapsulated TFLite model and performs object detection on the
+// frame_buffer. Returns a pointer to the created object detection result result
+// in case of success or NULL in case of failure. The caller must test the
+// return value to identify success or failure. If the caller doesn't want the
+// reason for failure, they can simply pass a NULL for the address of the error
+// pointer as shown below:
+//
+// TfLiteDetectionResult* detection_result =
+// TfLiteObjectDetectorDetect(&options, NULL);
+//
+// If the caller wants to be informed of the reason for failure, they must pass
+// the adress of a pointer of type TfLiteSupportError to the `error` param as
+// shown below:
+//
+// TfLiteSupport *error = NULL:
+// TfLiteObjectDetector* detector = TfLiteObjectDetectorFromOptions(options,
+// &error);
+//
+// In case of unsuccessful execution, Once the function returns, the error
+// pointer will point to a struct containing the error information. If error
+// info is passed back to the caller, it is the responsibility of the caller to
+// free the error struct by calling the following method defined in common.h:
+//
+// TfLiteSupportErrorDelete(error)
+//
+TfLiteDetectionResult* TfLiteObjectDetectorDetect(
+    const TfLiteObjectDetector* detector,
+    const TfLiteFrameBuffer* frame_buffer,
+    TfLiteSupportError** error);
+
+// Disposes off the object detector.
+void TfLiteObjectDetectorDelete(TfLiteObjectDetector* detector);
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_IMAGE_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/BUILD
new file mode 100644
index 0000000..9b395b3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/BUILD
@@ -0,0 +1,22 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "frame_buffer_cpp_c_utils",
+    srcs = [
+        "frame_buffer_cpp_c_utils.cc",
+    ],
+    hdrs = [
+        "frame_buffer_cpp_c_utils.h",
+    ],
+    deps = [
+        "//tensorflow_lite_support/c/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.cc
new file mode 100644
index 0000000..a084789
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.cc
@@ -0,0 +1,50 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.h"
+
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+
+namespace {
+using FrameBufferCpp = ::tflite::task::vision::FrameBuffer;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+}  // namespace
+
+StatusOr<std::unique_ptr<FrameBufferCpp>> CreateCppFrameBuffer(
+    const TfLiteFrameBuffer* frame_buffer) {
+  if (frame_buffer == nullptr)
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("Expected non null frame buffer."),
+        TfLiteSupportStatus::kInvalidArgumentError);
+
+  FrameBufferCpp::Format frame_buffer_format =
+      FrameBufferCpp::Format(frame_buffer->format);
+
+  return CreateFromRawBuffer(
+      frame_buffer->buffer,
+      {frame_buffer->dimension.width, frame_buffer->dimension.height},
+      frame_buffer_format);
+}
+
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.h
new file mode 100644
index 0000000..6d062da
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/task/vision/utils/frame_buffer_cpp_c_utils.h
@@ -0,0 +1,36 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_FRAME_BUFFER_CPP_C_UTILS_H_
+#define TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_FRAME_BUFFER_CPP_C_UTILS_H_
+
+#include "tensorflow_lite_support/c/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+
+// Utils for Conversions between C and C++ FrameBuffer
+// -----------------------------------------------------------------
+// Meant to be used with vision C apis.
+
+// Creates the C++ FrameBuffer from the C FrameBuffer
+namespace tflite {
+namespace task {
+namespace vision {
+
+tflite::support::StatusOr<std::unique_ptr<tflite::task::vision::FrameBuffer>>
+CreateCppFrameBuffer(const TfLiteFrameBuffer* frame_buffer);
+
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_SUPPORT_C_TASK_VISION_FRAME_BUFFER_CPP_C_UTILS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/BUILD
new file mode 100644
index 0000000..788dce4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/BUILD
@@ -0,0 +1,34 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_test_with_tflite",
+)
+
+package(
+    default_visibility = [
+        "//visibility:private",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+# To test it with Bazel, run the following command from the terminal of your desktop:
+# bazel test tensorflow_lite_support/c/test/task/vision:image_classifier_test
+cc_test_with_tflite(
+    name = "image_classifier_test",
+    srcs = ["image_classifier_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/c/task/vision:image_classifier",
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+    ],
+    deps = [
+        "//tensorflow_lite_support/c:common",
+        "//tensorflow_lite_support/c/task/processor:classification_result",
+        "//tensorflow_lite_support/c/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc
new file mode 100644
index 0000000..b398b7ad
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/c/test/task/vision/image_classifier_test.cc
@@ -0,0 +1,432 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/c/task/vision/image_classifier.h"
+
+#include <string.h>
+
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow_lite_support/c/common.h"
+#include "tensorflow_lite_support/c/task/processor/classification_result.h"
+#include "tensorflow_lite_support/c/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+namespace {
+
+using ::testing::HasSubstr;
+using ::tflite::support::StatusOr;
+using ::tflite::task::JoinPath;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "vision/";
+// Quantized model.
+constexpr char kMobileNetQuantizedWithMetadata[] =
+    "mobilenet_v1_0.25_224_quant.tflite";
+
+StatusOr<ImageData> LoadImage(const char* image_name) {
+  return DecodeImageFromFile(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+}
+
+class ImageClassifierFromOptionsTest : public tflite_shims::testing::Test {};
+
+TEST_F(ImageClassifierFromOptionsTest, FailsWithNullOptionsAndError) {
+  TfLiteSupportError* error = nullptr;
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(nullptr, &error);
+
+  EXPECT_EQ(image_classifier, nullptr);
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("Expected non null options"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+TEST_F(ImageClassifierFromOptionsTest, FailsWithMissingModelPath) {
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, nullptr);
+  EXPECT_EQ(image_classifier, nullptr);
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+}
+
+TEST_F(ImageClassifierFromOptionsTest, FailsWithMissingModelPathAndError) {
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+
+  TfLiteSupportError* error = nullptr;
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, &error);
+
+  EXPECT_EQ(image_classifier, nullptr);
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("`base_options.model_file`"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+TEST_F(ImageClassifierFromOptionsTest, SucceedsWithModelPath) {
+  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                                    kMobileNetQuantizedWithMetadata);
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+  options.base_options.model_file.file_path = model_path.data();
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, nullptr);
+
+  EXPECT_NE(image_classifier, nullptr);
+  TfLiteImageClassifierDelete(image_classifier);
+}
+
+TEST_F(ImageClassifierFromOptionsTest, SucceedsWithNumberOfThreadsAndError) {
+  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                                    kMobileNetQuantizedWithMetadata);
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+  options.base_options.model_file.file_path = model_path.data();
+  options.base_options.compute_settings.cpu_settings.num_threads = 3;
+
+  TfLiteSupportError* error = nullptr;
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, &error);
+
+  EXPECT_NE(image_classifier, nullptr);
+  EXPECT_EQ(error, nullptr);
+
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+  if (error)
+    TfLiteSupportErrorDelete(error);
+}
+
+TEST_F(ImageClassifierFromOptionsTest,
+       FailsWithClassNameDenyListAndClassNameAllowListAndError) {
+  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                                    kMobileNetQuantizedWithMetadata);
+
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+  options.base_options.model_file.file_path = model_path.data();
+
+  char* label_denylist[9] = {(char*)"brambling"};
+  options.classification_options.label_denylist.list = label_denylist;
+  options.classification_options.label_denylist.length = 1;
+
+  char* label_allowlist[12] = {(char*)"cheeseburger"};
+  options.classification_options.label_allowlist.list = label_allowlist;
+  options.classification_options.label_allowlist.length = 1;
+
+  TfLiteSupportError* error = nullptr;
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, &error);
+
+  EXPECT_EQ(image_classifier, nullptr);
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("mutually exclusive options"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+TEST(ImageClassifierNullClassifierClassifyTest,
+     FailsWithNullImageClassifierAndError) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteSupportError* error = nullptr;
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassify(nullptr, nullptr, &error);
+
+  ImageDataFree(&image_data);
+
+  EXPECT_EQ(classification_result, nullptr);
+  if (classification_result)
+    TfLiteClassificationResultDelete(classification_result);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("Expected non null image classifier"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+class ImageClassifierClassifyTest : public tflite_shims::testing::Test {
+ protected:
+  void SetUp() override {
+    std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                                      kMobileNetQuantizedWithMetadata);
+
+    TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+    options.base_options.model_file.file_path = model_path.data();
+    image_classifier = TfLiteImageClassifierFromOptions(&options, nullptr);
+    ASSERT_NE(image_classifier, nullptr);
+  }
+
+  void TearDown() override { TfLiteImageClassifierDelete(image_classifier); }
+  TfLiteImageClassifier* image_classifier;
+};
+
+TEST_F(ImageClassifierClassifyTest, SucceedsWithImageData) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteFrameBuffer frame_buffer = {
+      .format = kRGB,
+      .orientation = kTopLeft,
+      .dimension = {.width = image_data.width, .height = image_data.height},
+      .buffer = image_data.pixel_data};
+
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassify(image_classifier, &frame_buffer, nullptr);
+
+  ImageDataFree(&image_data);
+
+  ASSERT_NE(classification_result, nullptr);
+  EXPECT_GE(classification_result->size, 1);
+  EXPECT_NE(classification_result->classifications, nullptr);
+  EXPECT_GE(classification_result->classifications->size, 1);
+  EXPECT_NE(classification_result->classifications->categories, nullptr);
+  EXPECT_EQ(strcmp(classification_result->classifications->categories[0].label,
+                   "cheeseburger"),
+            0);
+  EXPECT_GE(classification_result->classifications->categories[0].score, 0.90);
+
+  TfLiteClassificationResultDelete(classification_result);
+}
+
+TEST_F(ImageClassifierClassifyTest, FailsWithNullFrameBufferAndError) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteSupportError* error = nullptr;
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassify(image_classifier, nullptr, &error);
+
+  ImageDataFree(&image_data);
+
+  EXPECT_EQ(classification_result, nullptr);
+  if (classification_result)
+    TfLiteClassificationResultDelete(classification_result);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("Expected non null frame buffer"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+TEST_F(ImageClassifierClassifyTest, FailsWithNullImageDataAndError) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteFrameBuffer frame_buffer = {.format = kRGB, .orientation = kTopLeft};
+
+  TfLiteSupportError* error = nullptr;
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassify(image_classifier, &frame_buffer, &error);
+
+  ImageDataFree(&image_data);
+
+  EXPECT_EQ(classification_result, nullptr);
+  if (classification_result)
+    TfLiteClassificationResultDelete(classification_result);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("Invalid stride information"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+TEST_F(ImageClassifierClassifyTest, SucceedsWithRoiWithinImageBounds) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteFrameBuffer frame_buffer = {
+      .format = kRGB,
+      .orientation = kTopLeft,
+      .dimension = {.width = image_data.width, .height = image_data.height},
+      .buffer = image_data.pixel_data};
+
+  TfLiteBoundingBox bounding_box = {
+      .origin_x = 0, .origin_y = 0, .width = 100, .height = 100};
+  TfLiteSupportError* error = nullptr;
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassifyWithRoi(image_classifier, &frame_buffer,
+                                           &bounding_box, &error);
+
+  ImageDataFree(&image_data);
+
+  ASSERT_NE(classification_result, nullptr);
+  EXPECT_GE(classification_result->size, 1);
+  EXPECT_NE(classification_result->classifications, nullptr);
+  EXPECT_GE(classification_result->classifications->size, 1);
+  EXPECT_NE(classification_result->classifications->categories, nullptr);
+  EXPECT_EQ(strcmp(classification_result->classifications->categories[0].label,
+                   "bagel"),
+            0);
+  EXPECT_GE(classification_result->classifications->categories[0].score, 0.30);
+
+  TfLiteClassificationResultDelete(classification_result);
+}
+
+TEST_F(ImageClassifierClassifyTest, FailsWithRoiOutsideImageBoundsAndError) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteFrameBuffer frame_buffer = {
+      .format = kRGB,
+      .orientation = kTopLeft,
+      .dimension = {.width = image_data.width, .height = image_data.height},
+      .buffer = image_data.pixel_data};
+
+  TfLiteBoundingBox bounding_box = {
+      .origin_x = 0, .origin_y = 0, .width = 250, .height = 250};
+  TfLiteSupportError* error = nullptr;
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassifyWithRoi(image_classifier, &frame_buffer,
+                                           &bounding_box, &error);
+
+  ImageDataFree(&image_data);
+
+  EXPECT_EQ(classification_result, nullptr);
+  if (classification_result)
+    TfLiteClassificationResultDelete(classification_result);
+
+  ASSERT_NE(error, nullptr);
+  EXPECT_EQ(error->code, kInvalidArgumentError);
+  EXPECT_NE(error->message, nullptr);
+  EXPECT_THAT(error->message, HasSubstr("Invalid crop coordinates"));
+
+  TfLiteSupportErrorDelete(error);
+}
+
+TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+     SucceedsWithClassNameDenyList) {
+  char* denylisted_label_name = (char*)"cheeseburger";
+  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                                    kMobileNetQuantizedWithMetadata);
+
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+  options.base_options.model_file.file_path = model_path.data();
+
+  char* label_denylist[12] = {denylisted_label_name};
+  options.classification_options.label_denylist.list = label_denylist;
+  options.classification_options.label_denylist.length = 1;
+
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, nullptr);
+  ASSERT_NE(image_classifier, nullptr);
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteFrameBuffer frame_buffer = {
+      .format = kRGB,
+      .orientation = kTopLeft,
+      .dimension = {.width = image_data.width, .height = image_data.height},
+      .buffer = image_data.pixel_data};
+
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassify(image_classifier, &frame_buffer, nullptr);
+
+  ImageDataFree(&image_data);
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+
+  ASSERT_NE(classification_result, nullptr);
+  EXPECT_GE(classification_result->size, 1);
+  EXPECT_NE(classification_result->classifications, nullptr);
+  EXPECT_GE(classification_result->classifications->size, 1);
+  EXPECT_NE(classification_result->classifications->categories, nullptr);
+  EXPECT_NE(strcmp(classification_result->classifications->categories[0].label,
+                   denylisted_label_name),
+            0);
+
+  TfLiteClassificationResultDelete(classification_result);
+}
+
+TEST(ImageClassifierWithUserDefinedOptionsClassifyTest,
+     SucceedsWithClassNameAllowList) {
+  char* allowlisted_label_name = (char*)"cheeseburger";
+  std::string model_path = JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                                    kMobileNetQuantizedWithMetadata)
+                               .data();
+
+  TfLiteImageClassifierOptions options = TfLiteImageClassifierOptionsCreate();
+  options.base_options.model_file.file_path = model_path.data();
+
+  char* label_allowlist[12] = {allowlisted_label_name};
+  options.classification_options.label_allowlist.list = label_allowlist;
+  options.classification_options.label_allowlist.length = 1;
+
+  TfLiteImageClassifier* image_classifier =
+      TfLiteImageClassifierFromOptions(&options, nullptr);
+  ASSERT_NE(image_classifier, nullptr);
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image_data,
+                               LoadImage("burger-224.png"));
+
+  TfLiteFrameBuffer frame_buffer = {
+      .format = kRGB,
+      .orientation = kTopLeft,
+      .dimension = {.width = image_data.width, .height = image_data.height},
+      .buffer = image_data.pixel_data};
+
+  TfLiteClassificationResult* classification_result =
+      TfLiteImageClassifierClassify(image_classifier, &frame_buffer, nullptr);
+
+  ImageDataFree(&image_data);
+  if (image_classifier)
+    TfLiteImageClassifierDelete(image_classifier);
+
+  ASSERT_NE(classification_result, nullptr);
+  EXPECT_GE(classification_result->size, 1);
+  EXPECT_NE(classification_result->classifications, nullptr);
+  EXPECT_GE(classification_result->classifications->size, 1);
+  EXPECT_NE(classification_result->classifications->categories, nullptr);
+  EXPECT_EQ(strcmp(classification_result->classifications->categories[0].label,
+                   allowlisted_label_name),
+            0);
+
+  TfLiteClassificationResultDelete(classification_result);
+}
+
+}  // namespace
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/BUILD
index b19bfde..3fe09242 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/BUILD
@@ -1,5 +1,5 @@
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -9,17 +9,12 @@
         "common.cc",
     ],
     hdrs = ["common.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
         "@com_google_absl//absl/strings:cord",
     ],
 )
-
-config_setting(
-    name = "tflite_use_c_api",
-    values = {
-        "copt": "-DTFLITE_USE_C_API",
-    },
-    visibility = ["//tensorflow_lite_support:__subpackages__"],
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc
index ed373e9..09e9a83 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.cc
@@ -15,7 +15,8 @@
 
 #include "tensorflow_lite_support/cc/common.h"
 
-#include "absl/strings/str_cat.h"
+#include "absl/strings/cord.h"     // from @com_google_absl
+#include "absl/strings/str_cat.h"  // from @com_google_absl
 
 namespace tflite {
 namespace support {
@@ -25,6 +26,8 @@
                                      TfLiteSupportStatus tfls_code) {
   // NOTE: Ignores `message` if the canonical code is ok.
   absl::Status status = absl::Status(canonical_code, message);
+  // NOTE: Does nothing if the canonical code is ok.
+  status.SetPayload(kTfLiteSupportPayload, absl::Cord(absl::StrCat(tfls_code)));
   return status;
 }
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h
index 15a9224..71dd920 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/common.h
@@ -16,8 +16,8 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_COMMON_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_COMMON_H_
 
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 
 namespace tflite {
 namespace support {
@@ -53,6 +53,12 @@
   kInvalidArgumentError = 2,
   // Invalid FlatBuffer file or buffer specified.
   kInvalidFlatBufferError = 3,
+  // Model contains a builtin op that isn't supported by the OpResolver or
+  // delegates.
+  kUnsupportedBuiltinOp = 4,
+  // Model contains a custom op that isn't supported by the OpResolver or
+  // delegates.
+  kUnsupportedCustomOp = 5,
 
   // File I/O error codes.
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/BUILD
index 4a413617..39f4a45 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/BUILD
@@ -1,5 +1,7 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -8,8 +10,9 @@
     hdrs = [
         "statusor.h",
     ],
+    visibility = ["//visibility:public"],
     deps = [
-        "//tensorflow_lite_support/cc/port/default:statusor",
+        "@com_google_absl//absl/status:statusor",
     ],
 )
 
@@ -18,31 +21,54 @@
     hdrs = [
         "status_macros.h",
     ],
+    visibility = ["//visibility:public"],
     deps = [
         "//tensorflow_lite_support/cc/port/default:status_macros",
     ],
 )
 
 cc_library(
+    name = "configuration_proto_inc",
+    hdrs = ["configuration_proto_inc.h"],
+    deps = ["@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_cc_proto"],
+)
+
+cc_library_with_tflite(
     name = "tflite_wrapper",
     hdrs = ["tflite_wrapper.h"],
     deps = ["//tensorflow_lite_support/cc/port/default:tflite_wrapper"],
 )
 
-# This is identical to the rule above, except that it gets built with
-# '-DTFLITE_USE_C_API'. This rule is used for unit tests that verify things
-# work correctly when built with TFLITE_USE_C_API defined.
 cc_library(
-    name = "tflite_wrapper_with_c_api_for_test",
+    name = "integral_types",
+    hdrs = ["integral_types.h"],
+    visibility = ["//tensorflow_lite_support:users"],
+)
+
+cc_library(
+    name = "gtest_main",
     testonly = 1,
-    hdrs = ["tflite_wrapper.h"],
+    hdrs = [
+        "benchmark.h",
+        "gmock.h",
+        "gtest.h",
+        "status_matchers.h",
+    ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
-        "//intelligence/mobile_acceleration/proto:allowlist_portable_proto",
-        "//intelligence/mobile_acceleration/support_library:tflite_wrapper_with_c_api_for_test",
+        "//tensorflow_lite_support/cc/port/default:status_matchers",
+        "@com_google_googletest//:gtest_main",
     ],
 )
 
 cc_library(
-    name = "integral_types",
-    hdrs = ["integral_types.h"],
+    name = "proto2",
+    hdrs = [
+        "proto2.h",
+    ],
+    deps = [
+        "@com_google_protobuf//:protobuf",
+    ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/build_defs.bzl b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/build_defs.bzl
index a8053db..73fbb5f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/build_defs.bzl
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/build_defs.bzl
@@ -1,30 +1,22 @@
 """.bzl file for TFLite Support open source build configs."""
 
-load("@com_google_protobuf//:protobuf.bzl", "cc_proto_library")
-
 def provided_args(**kwargs):
     """Returns the keyword arguments omitting None arguments."""
     return {k: v for k, v in kwargs.items() if v != None}
 
-def support_cc_proto_library(name, srcs, visibility = None, deps = [], cc_deps = [], testonly = 0):
-    """Generate cc_proto_library for TFLite Support open source version.
+def support_cc_proto_library(name, deps = [], visibility = None):
+    """Generates cc_proto_library for TFLite Support open source version.
 
       Args:
         name: the name of the cc_proto_library.
-        srcs: the .proto files of the cc_proto_library for Bazel use.
+        deps: a list of dependency labels for Bazel use; must be proto_library.
         visibility: visibility of this target.
-        deps: a list of dependency labels for Bazel use; must be cc_proto_library.
-        testonly: test only proto or not.
     """
-    _ignore = [deps]
-    cc_proto_library(**provided_args(
+
+    # Verified in the external path.
+    # buildifier: disable=native-cc-proto
+    native.cc_proto_library(**provided_args(
         name = name,
-        srcs = srcs,
         visibility = visibility,
-        deps = cc_deps,
-        testonly = testonly,
-        cc_libs = ["@com_google_protobuf//:protobuf"],
-        protoc = "@com_google_protobuf//:protoc",
-        default_runtime = "@com_google_protobuf//:protobuf",
-        alwayslink = 1,
+        deps = deps,
     ))
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/configuration_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/configuration_proto_inc.h
new file mode 100644
index 0000000..d014973
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/configuration_proto_inc.h
@@ -0,0 +1,21 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_PORT_CONFIGURATION_PROTO_INC_H_
+#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_PORT_CONFIGURATION_PROTO_INC_H_
+
+#include "tensorflow/lite/experimental/acceleration/configuration/configuration.pb.h"
+
+#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_PORT_CONFIGURATION_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/BUILD
index 3f6e9e9..f506a7c3 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/BUILD
@@ -1,30 +1,12 @@
 package(
     default_visibility = [
-        "//tensorflow_lite_support/cc/port:__pkg__",
-        "//tensorflow_lite_support/cc/test:__pkg__",
+        "//tensorflow_lite_support/cc/port:__subpackages__",
+        "//tensorflow_lite_support/cc/test:__subpackages__",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
 
 cc_library(
-    name = "statusor",
-    srcs = ["statusor.cc"],
-    hdrs = [
-        "statusor.h",
-        "statusor_internals.h",
-    ],
-    deps = [
-        "@com_google_absl//absl/base:core_headers",
-        "@com_google_absl//absl/meta:type_traits",
-        "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings",
-        "@com_google_absl//absl/types:variant",
-        "@com_google_absl//absl/utility",
-        "@com_google_glog//:glog",
-    ],
-)
-
-cc_library(
     name = "status_macros",
     hdrs = [
         "status_macros.h",
@@ -36,15 +18,47 @@
 )
 
 cc_library(
+    name = "status_matchers",
+    testonly = 1,
+    hdrs = ["status_matchers.h"],
+    deps = [
+        "@com_google_googletest//:gtest_main",
+    ],
+)
+
+cc_library(
     name = "tflite_wrapper",
     srcs = ["tflite_wrapper.cc"],
     hdrs = [
         "tflite_wrapper.h",
     ],
     deps = [
-        "//tensorflow_lite_support/cc/port:status_macros",
         "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+        "@com_google_absl//absl/synchronization",
+        "@flatbuffers",
         "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite:minimal_logging",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:nnapi_plugin",
+        "@org_tensorflow//tensorflow/lite/delegates:interpreter_utils",
         "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_cc_proto",
-    ],
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:delegate_registry",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:flatbuffer_to_proto",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:proto_to_flatbuffer",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/mini_benchmark",
+        "//tensorflow_lite_support/cc/port:status_macros",
+    ] + select({
+        # We only intend to use TFLite mini-benchmark on arm-based Andorid and x86_64 Linux.
+        "@org_tensorflow//tensorflow:android_arm": [
+            "@org_tensorflow//tensorflow/lite/experimental/acceleration/mini_benchmark:mini_benchmark_implementation",
+        ],
+        "@org_tensorflow//tensorflow:android_arm64": [
+            "@org_tensorflow//tensorflow/lite/experimental/acceleration/mini_benchmark:mini_benchmark_implementation",
+        ],
+        "@org_tensorflow//tensorflow:linux_x86_64": [
+            "@org_tensorflow//tensorflow/lite/experimental/acceleration/mini_benchmark:mini_benchmark_implementation",
+        ],
+        "//conditions:default": [],
+    }),
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h
index 47476c9..cb145db 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/status_macros.h
@@ -17,8 +17,8 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUS_MACROS_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUS_MACROS_H_
 
-#include "absl/base/optimization.h"
-#include "absl/status/status.h"
+#include "absl/base/optimization.h"  // from @com_google_absl
+#include "absl/status/status.h"      // from @com_google_absl
 
 // Evaluates an expression that produces a `absl::Status`. If the status is not
 // ok, returns it from the current function.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor.cc
deleted file mode 100644
index 058c0070..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor.cc
+++ /dev/null
@@ -1,67 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-// This file is forked from absl.
-
-#include "tensorflow_lite_support/cc/port/default/statusor.h"
-
-#include <utility>
-
-#include "absl/strings/str_cat.h"
-#include "base/logging.h"
-
-namespace tflite {
-namespace support {
-
-BadStatusOrAccess::BadStatusOrAccess(absl::Status status)
-    : status_(std::move(status)) {}
-
-BadStatusOrAccess::~BadStatusOrAccess() = default;
-
-const char* BadStatusOrAccess::what() const noexcept {
-  return "Bad StatusOr access";
-}
-
-const absl::Status& BadStatusOrAccess::status() const {
-  return status_;
-}
-
-namespace internal_statusor {
-
-void Helper::HandleInvalidStatusCtorArg(absl::Status* status) {
-  const char* kMessage =
-      "An OK status is not a valid constructor argument to StatusOr<T>";
-  LOG(DFATAL) << kMessage;
-  // In optimized builds, we will fall back to ::util::error::INTERNAL.
-  *status = absl::InternalError(kMessage);
-}
-
-void Helper::Crash(const absl::Status& status) {
-  LOG(FATAL) << "Attempting to fetch value instead of handling error "
-             << status;
-  _Exit(1);
-}
-
-void ThrowBadStatusOrAccess(absl::Status status) {
-#ifdef ABSL_HAVE_EXCEPTIONS
-  throw BadStatusOrAccess(std::move(status));
-#else
-  LOG(FATAL) << "Attempting to fetch value instead of handling error "
-             << status;
-#endif
-}
-
-}  // namespace internal_statusor
-}  // namespace support
-}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor.h
deleted file mode 100644
index b8d41c79..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor.h
+++ /dev/null
@@ -1,584 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-// This file is forked from absl.
-
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUSOR_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUSOR_H_
-
-#include <exception>
-#include <initializer_list>
-#include <new>
-#include <string>
-#include <type_traits>
-#include <utility>
-
-#include "absl/base/optimization.h"
-#include "absl/meta/type_traits.h"
-#include "absl/status/status.h"
-#include "absl/types/variant.h"
-#include "absl/utility/utility.h"
-#include "tensorflow_lite_support/cc/port/default/statusor_internals.h"
-
-namespace tflite {
-namespace support {
-
-#ifndef SWIG
-class BadStatusOrAccess : public std::exception {
- public:
-  explicit BadStatusOrAccess(absl::Status status);
-  ~BadStatusOrAccess() override;
-  const char* what() const noexcept override;
-  const absl::Status& status() const;
-
- private:
-  absl::Status status_;
-};
-#endif  // !SWIG
-
-// Returned StatusOr objects may not be ignored.
-// Note: Disabled for SWIG as it doesn't parse attributes correctly.  Codesearch
-// doesn't handle ifdefs as part of a class definitions (b/6995610), so we use a
-// forward declaration.
-#ifndef SWIG
-template <typename T>
-class ABSL_MUST_USE_RESULT StatusOr;
-#endif
-
-template <typename T>
-class StatusOr : private internal_statusor::StatusOrData<T>,
-                 private internal_statusor::CopyCtorBase<T>,
-                 private internal_statusor::MoveCtorBase<T>,
-                 private internal_statusor::CopyAssignBase<T>,
-                 private internal_statusor::MoveAssignBase<T> {
-  template <typename U>
-  friend class StatusOr;
-
-  typedef internal_statusor::StatusOrData<T> Base;
-
- public:
-  typedef T value_type;
-
-  // Constructs a new StatusOr with Status::UNKNOWN status.  This is marked
-  // 'explicit' to try to catch cases like 'return {};', where people think
-  // tflite::support::StatusOr<std::vector<int>> will be initialized with an
-  // empty vector, instead of a Status::UNKNOWN status.
-  explicit StatusOr();
-
-  // StatusOr<T> is copy constructible if T is copy constructible.
-  StatusOr(const StatusOr&) = default;
-  // StatusOr<T> is copy assignable if T is copy constructible and copy
-  // assignable.
-  StatusOr& operator=(const StatusOr&) = default;
-
-#ifndef SWIG
-
-  // StatusOr<T> is move constructible if T is move constructible.
-  StatusOr(StatusOr&&) = default;
-  // StatusOr<T> is moveAssignable if T is move constructible and move
-  // assignable.
-  StatusOr& operator=(StatusOr&&) = default;
-
-  // Converting constructors from StatusOr<U>, when T is constructible from U.
-  // To avoid ambiguity, they are disabled if T is also constructible from
-  // StatusOr<U>. Explicit iff the corresponding construction of T from U is
-  // explicit.
-  template <
-      typename U,
-      absl::enable_if_t<
-          absl::conjunction<
-              absl::negation<std::is_same<T, U>>,
-              std::is_constructible<T, const U&>,
-              std::is_convertible<const U&, T>,
-              absl::negation<
-                  internal_statusor::
-                      IsConstructibleOrConvertibleFromStatusOr<T, U>>>::value,
-          int> = 0>
-  StatusOr(const StatusOr<U>& other)  // NOLINT
-      : Base(static_cast<const typename StatusOr<U>::Base&>(other)) {}
-  template <
-      typename U,
-      absl::enable_if_t<
-          absl::conjunction<
-              absl::negation<std::is_same<T, U>>,
-              std::is_constructible<T, const U&>,
-              absl::negation<std::is_convertible<const U&, T>>,
-              absl::negation<
-                  internal_statusor::
-                      IsConstructibleOrConvertibleFromStatusOr<T, U>>>::value,
-          int> = 0>
-  explicit StatusOr(const StatusOr<U>& other)
-      : Base(static_cast<const typename StatusOr<U>::Base&>(other)) {}
-
-  template <
-      typename U,
-      absl::enable_if_t<
-          absl::conjunction<
-              absl::negation<std::is_same<T, U>>,
-              std::is_constructible<T, U&&>,
-              std::is_convertible<U&&, T>,
-              absl::negation<
-                  internal_statusor::
-                      IsConstructibleOrConvertibleFromStatusOr<T, U>>>::value,
-          int> = 0>
-  StatusOr(StatusOr<U>&& other)  // NOLINT
-      : Base(static_cast<typename StatusOr<U>::Base&&>(other)) {}
-  template <
-      typename U,
-      absl::enable_if_t<
-          absl::conjunction<
-              absl::negation<std::is_same<T, U>>,
-              std::is_constructible<T, U&&>,
-              absl::negation<std::is_convertible<U&&, T>>,
-              absl::negation<
-                  internal_statusor::
-                      IsConstructibleOrConvertibleFromStatusOr<T, U>>>::value,
-          int> = 0>
-  explicit StatusOr(StatusOr<U>&& other)
-      : Base(static_cast<typename StatusOr<U>::Base&&>(other)) {}
-
-  // Conversion copy/move assignment operator, T must be constructible and
-  // assignable from U. Only enable if T cannot be directly assigned from
-  // StatusOr<U>.
-  template <
-      typename U,
-      absl::enable_if_t<
-          absl::conjunction<
-              absl::negation<std::is_same<T, U>>,
-              std::is_constructible<T, const U&>,
-              std::is_assignable<T, const U&>,
-              absl::negation<
-                  internal_statusor::
-                      IsConstructibleOrConvertibleOrAssignableFromStatusOr<
-                          T,
-                          U>>>::value,
-          int> = 0>
-  StatusOr& operator=(const StatusOr<U>& other) {
-    this->Assign(other);
-    return *this;
-  }
-  template <
-      typename U,
-      absl::enable_if_t<
-          absl::conjunction<
-              absl::negation<std::is_same<T, U>>,
-              std::is_constructible<T, U&&>,
-              std::is_assignable<T, U&&>,
-              absl::negation<
-                  internal_statusor::
-                      IsConstructibleOrConvertibleOrAssignableFromStatusOr<
-                          T,
-                          U>>>::value,
-          int> = 0>
-  StatusOr& operator=(StatusOr<U>&& other) {
-    this->Assign(std::move(other));
-    return *this;
-  }
-
-#endif  // SWIG
-
-  // Constructs a new StatusOr with the given value. After calling this
-  // constructor, this->ok() will be true and the contained value may be
-  // retrieved with value(), operator*(), or operator->().
-  //
-  // NOTE: Not explicit - we want to use StatusOr<T> as a return type
-  // so it is convenient and sensible to be able to do 'return T()'
-  // when the return type is StatusOr<T>.
-  //
-  // REQUIRES: T is copy constructible.
-  // TODO(b/113125838): Replace this constructor with a direct-initialization
-  // constructor.
-  StatusOr(const T& value);
-
-  // Constructs a new StatusOr with the given non-ok status. After calling this
-  // constructor, this->ok() will be false and calls to value() will CHECK-fail.
-  //
-  // NOTE: Not explicit - we want to use StatusOr<T> as a return
-  // value, so it is convenient and sensible to be able to do 'return
-  // Status()' when the return type is StatusOr<T>.
-  //
-  // REQUIRES: !status.ok(). This requirement is DCHECKed.
-  // In optimized builds, passing util::OkStatus() here will have the effect
-  // of passing util::error::INTERNAL as a fallback.
-  StatusOr(const absl::Status& status);
-  StatusOr& operator=(const absl::Status& status);
-
-#ifndef SWIG
-  // Perfect-forwarding value assignment operator.
-  // If `*this` contains a `T` value before the call, the contained value is
-  // assigned from `std::forward<U>(v)`; Otherwise, it is directly-initialized
-  // from `std::forward<U>(v)`.
-  // This function does not participate in overload unless:
-  // 1. `std::is_constructible_v<T, U>` is true,
-  // 2. `std::is_assignable_v<T&, U>` is true.
-  // 3. `std::is_same_v<StatusOr<T>, std::remove_cvref_t<U>>` is false.
-  // 4. Assigning `U` to `T` is not ambiguous:
-  //  If `U` is `StatusOr<V>` and `T` is constructible and assignable from
-  //  both `StatusOr<V>` and `V`, the assignment is considered bug-prone and
-  //  ambiguous thus will fail to compile. For example:
-  //    StatusOr<bool> s1 = true;  // s1.ok() && *s1 == true
-  //    StatusOr<bool> s2 = false;  // s2.ok() && *s2 == false
-  //    s1 = s2;  // ambiguous, `s1 = *s2` or `s1 = bool(s2)`?
-  template <
-      typename U = T,
-      typename = typename std::enable_if<absl::conjunction<
-          std::is_constructible<T, U&&>,
-          std::is_assignable<T&, U&&>,
-          internal_statusor::IsForwardingAssignmentValid<T, U&&>>::value>::type>
-  StatusOr& operator=(U&& v) {
-    this->Assign(std::forward<U>(v));
-    return *this;
-  }
-
-  // Similar to the `const T&` overload.
-  //
-  // REQUIRES: T is move constructible.
-  StatusOr(T&& value);
-
-  // RValue versions of the operations declared above.
-  StatusOr(absl::Status&& status);
-  StatusOr& operator=(absl::Status&& status);
-
-  // Constructs the inner value T in-place using the provided args, using the
-  // T(args...) constructor.
-  template <typename... Args>
-  explicit StatusOr(absl::in_place_t, Args&&... args);
-  template <typename U, typename... Args>
-  explicit StatusOr(absl::in_place_t,
-                    std::initializer_list<U> ilist,
-                    Args&&... args);
-
-  // Constructs the inner value T in-place using the provided args, using the
-  // T(U) (direct-initialization) constructor. Only valid if T can be
-  // constructed from a U. Can accept move or copy constructors. Explicit if
-  // U is not convertible to T. To avoid ambiguity, this is disabled if U is
-  // a StatusOr<J>, where J is convertible to T.
-  // Style waiver for implicit conversion granted in cl/209187539.
-  template <typename U = T,
-            absl::enable_if_t<
-                absl::conjunction<
-                    internal_statusor::IsDirectInitializationValid<T, U&&>,
-                    std::is_constructible<T, U&&>,
-                    std::is_convertible<U&&, T>>::value,
-                int> = 0>
-  StatusOr(U&& u)  // NOLINT
-      : StatusOr(absl::in_place, std::forward<U>(u)) {}
-
-  template <typename U = T,
-            absl::enable_if_t<
-                absl::conjunction<
-                    internal_statusor::IsDirectInitializationValid<T, U&&>,
-                    std::is_constructible<T, U&&>,
-                    absl::negation<std::is_convertible<U&&, T>>>::value,
-                int> = 0>
-  explicit StatusOr(U&& u)  // NOLINT
-      : StatusOr(absl::in_place, std::forward<U>(u)) {}
-
-#endif  // SWIG
-
-  // Returns this->status().ok()
-  ABSL_MUST_USE_RESULT bool ok() const { return this->status_.ok(); }
-
-  // Returns a reference to our status. If this contains a T, then
-  // returns util::OkStatus().
-#ifdef SWIG
-  const ::util::Status& status() const;
-#else   // SWIG
-  const absl::Status& status() const&;
-  absl::Status status() &&;
-#endif  // SWIG
-
-  // Returns a reference to the held value if `this->ok()`. Otherwise, throws
-  // `absl::BadStatusOrAccess` if exception is enabled, or `LOG(FATAL)` if
-  // exception is disabled.
-  // If you have already checked the status using `this->ok()` or
-  // `operator bool()`, you probably want to use `operator*()` or `operator->()`
-  // to access the value instead of `value`.
-  // Note: for value types that are cheap to copy, prefer simple code:
-  //
-  //   T value = statusor.value();
-  //
-  // Otherwise, if the value type is expensive to copy, but can be left
-  // in the StatusOr, simply assign to a reference:
-  //
-  //   T& value = statusor.value();  // or `const T&`
-  //
-  // Otherwise, if the value type supports an efficient move, it can be
-  // used as follows:
-  //
-  //   T value = std::move(statusor).value();
-  //
-  // The `std::move` on statusor instead of on the whole expression enables
-  // warnings about possible uses of the statusor object after the move.
-#ifdef SWIG
-  const T& value() const;
-#else   // SWIG
-  const T& value() const&;
-  T& value() &;
-  const T&& value() const&&;
-  T&& value() &&;
-#endif  // SWIG
-
-#ifndef SWIG
-  // Returns a reference to the current value.
-  //
-  // REQUIRES: this->ok() == true, otherwise the behavior is undefined.
-  //
-  // Use this->ok() or `operator bool()` to verify that there is a current
-  // value. Alternatively, see value() for a similar API that guarantees
-  // CHECK-failing if there is no current value.
-  const T& operator*() const&;
-  T& operator*() &;
-  const T&& operator*() const&&;
-  T&& operator*() &&;
-#endif  // SWIG
-
-#ifndef SWIG
-  // Returns a pointer to the current value.
-  //
-  // REQUIRES: this->ok() == true, otherwise the behavior is undefined.
-  //
-  // Use this->ok() or `operator bool()` to verify that there is a current
-  // value.
-  const T* operator->() const;
-  T* operator->();
-#endif  // SWIG
-
-#ifndef SWIG
-  // Returns a copy of the current value if this->ok() == true. Otherwise
-  // returns a default value.
-  template <typename U>
-  T value_or(U&& default_value) const&;
-  template <typename U>
-  T value_or(U&& default_value) &&;
-#endif  // SWIG
-
-  // Ignores any errors. This method does nothing except potentially suppress
-  // complaints from any tools that are checking that errors are not dropped on
-  // the floor.
-  void IgnoreError() const;
-
-#ifndef SWIG
-  // Reconstructs the inner value T in-place using the provided args, using the
-  // T(args...) constructor. Returns reference to the reconstructed `T`.
-  template <typename... Args>
-  T& emplace(Args&&... args) {
-    if (ok()) {
-      this->Clear();
-      this->MakeValue(std::forward<Args>(args)...);
-    } else {
-      this->MakeValue(std::forward<Args>(args)...);
-      this->status_ = absl::OkStatus();
-    }
-    return this->data_;
-  }
-
-  template <
-      typename U,
-      typename... Args,
-      absl::enable_if_t<
-          std::is_constructible<T, std::initializer_list<U>&, Args&&...>::value,
-          int> = 0>
-  T& emplace(std::initializer_list<U> ilist, Args&&... args) {
-    if (ok()) {
-      this->Clear();
-      this->MakeValue(ilist, std::forward<Args>(args)...);
-    } else {
-      this->MakeValue(ilist, std::forward<Args>(args)...);
-      this->status_ = absl::OkStatus();
-    }
-    return this->data_;
-  }
-#endif  // SWIG
-
- private:
-#ifndef SWIG
-  using internal_statusor::StatusOrData<T>::Assign;
-  template <typename U>
-  void Assign(const StatusOr<U>& other);
-  template <typename U>
-  void Assign(StatusOr<U>&& other);
-#endif  // SWIG
-};
-
-#ifndef SWIG
-////////////////////////////////////////////////////////////////////////////////
-// Implementation details for StatusOr<T>
-
-template <typename T>
-tflite::support::StatusOr<T>::StatusOr()
-    : Base(absl::Status(absl::StatusCode::kUnknown, "")) {}
-
-template <typename T>
-tflite::support::StatusOr<T>::StatusOr(const T& value) : Base(value) {}
-
-template <typename T>
-tflite::support::StatusOr<T>::StatusOr(const absl::Status& status)
-    : Base(status) {}
-
-template <typename T>
-tflite::support::StatusOr<T>& StatusOr<T>::operator=(
-    const absl::Status& status) {
-  this->Assign(status);
-  return *this;
-}
-
-template <typename T>
-tflite::support::StatusOr<T>::StatusOr(T&& value) : Base(std::move(value)) {}
-
-template <typename T>
-tflite::support::StatusOr<T>::StatusOr(absl::Status&& status)
-    : Base(std::move(status)) {}
-
-template <typename T>
-tflite::support::StatusOr<T>& StatusOr<T>::operator=(absl::Status&& status) {
-  this->Assign(std::move(status));
-  return *this;
-}
-
-template <typename T>
-template <typename U>
-inline void StatusOr<T>::Assign(const StatusOr<U>& other) {
-  if (other.ok()) {
-    this->Assign(other.value());
-  } else {
-    this->Assign(other.status());
-  }
-}
-
-template <typename T>
-template <typename U>
-inline void StatusOr<T>::Assign(StatusOr<U>&& other) {
-  if (other.ok()) {
-    this->Assign(std::move(other).value());
-  } else {
-    this->Assign(std::move(other).status());
-  }
-}
-template <typename T>
-template <typename... Args>
-tflite::support::StatusOr<T>::StatusOr(absl::in_place_t, Args&&... args)
-    : Base(absl::in_place, std::forward<Args>(args)...) {}
-
-template <typename T>
-template <typename U, typename... Args>
-tflite::support::StatusOr<T>::StatusOr(absl::in_place_t,
-                                       std::initializer_list<U> ilist,
-                                       Args&&... args)
-    : Base(absl::in_place, ilist, std::forward<Args>(args)...) {}
-
-template <typename T>
-const absl::Status& StatusOr<T>::status() const& {
-  return this->status_;
-}
-template <typename T>
-absl::Status StatusOr<T>::status() && {
-  return ok() ? absl::OkStatus() : std::move(this->status_);
-}
-
-template <typename T>
-const T& StatusOr<T>::value() const& {
-  if (!this->ok())
-    internal_statusor::ThrowBadStatusOrAccess(this->status_);
-  return this->data_;
-}
-
-template <typename T>
-T& StatusOr<T>::value() & {
-  if (!this->ok())
-    internal_statusor::ThrowBadStatusOrAccess(this->status_);
-  return this->data_;
-}
-
-template <typename T>
-const T&& StatusOr<T>::value() const&& {
-  if (!this->ok()) {
-    internal_statusor::ThrowBadStatusOrAccess(std::move(this->status_));
-  }
-  return std::move(this->data_);
-}
-
-template <typename T>
-T&& StatusOr<T>::value() && {
-  if (!this->ok()) {
-    internal_statusor::ThrowBadStatusOrAccess(std::move(this->status_));
-  }
-  return std::move(this->data_);
-}
-
-template <typename T>
-const T& StatusOr<T>::operator*() const& {
-  this->EnsureOk();
-  return this->data_;
-}
-
-template <typename T>
-T& StatusOr<T>::operator*() & {
-  this->EnsureOk();
-  return this->data_;
-}
-
-template <typename T>
-const T&& StatusOr<T>::operator*() const&& {
-  this->EnsureOk();
-  return std::move(this->data_);
-}
-
-template <typename T>
-T&& StatusOr<T>::operator*() && {
-  this->EnsureOk();
-  return std::move(this->data_);
-}
-
-template <typename T>
-const T* StatusOr<T>::operator->() const {
-  this->EnsureOk();
-  return &this->data_;
-}
-
-template <typename T>
-T* StatusOr<T>::operator->() {
-  this->EnsureOk();
-  return &this->data_;
-}
-
-template <typename T>
-template <typename U>
-T StatusOr<T>::value_or(U&& default_value) const& {
-  if (ok()) {
-    return this->data_;
-  }
-  return std::forward<U>(default_value);
-}
-
-template <typename T>
-template <typename U>
-T StatusOr<T>::value_or(U&& default_value) && {
-  if (ok()) {
-    return std::move(this->data_);
-  }
-  return std::forward<U>(default_value);
-}
-
-template <typename T>
-void StatusOr<T>::IgnoreError() const {
-  // no-op
-}
-
-#endif  // SWIG
-
-}  // namespace support
-}  // namespace tflite
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_STATUSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h
index 30b7e3f..81ec3c1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/statusor_internals.h
@@ -20,9 +20,9 @@
 #include <type_traits>
 #include <utility>
 
-#include "absl/meta/type_traits.h"
-#include "absl/status/status.h"
-#include "absl/utility/utility.h"
+#include "absl/meta/type_traits.h"  // from @com_google_absl
+#include "absl/status/status.h"     // from @com_google_absl
+#include "absl/utility/utility.h"   // from @com_google_absl
 
 namespace tflite {
 namespace support {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc
index 548e679..0b3e5d6 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.cc
@@ -15,45 +15,332 @@
 
 #include "tensorflow_lite_support/cc/port/default/tflite_wrapper.h"
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/delegates/interpreter_utils.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/flatbuffer_to_proto.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/proto_to_flatbuffer.h"
+#include "tensorflow/lite/minimal_logging.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 
 namespace tflite {
 namespace support {
 
+namespace {
+using tflite::delegates::DelegatePluginRegistry;
+using tflite::delegates::InterpreterUtils;
+using tflite::proto::ComputeSettings;
+using tflite::proto::Delegate;
+}  // namespace
+
+/* static */
+absl::Status TfLiteInterpreterWrapper::SanityCheckComputeSettings(
+    const ComputeSettings& compute_settings) {
+  Delegate delegate = compute_settings.tflite_settings().delegate();
+  if (delegate != Delegate::NONE && delegate != Delegate::GPU &&
+      delegate != Delegate::HEXAGON && delegate != Delegate::NNAPI &&
+      delegate != Delegate::XNNPACK && delegate != Delegate::EDGETPU_CORAL) {
+    return absl::UnimplementedError(absl::StrFormat(
+        "Using delegate '%s' is not supported.", Delegate_Name(delegate)));
+  }
+  return absl::OkStatus();
+}
+
+TfLiteInterpreterWrapper::TfLiteInterpreterWrapper(
+    const std::string& default_model_namespace,
+    const std::string& default_model_id)
+    : delegate_(nullptr, nullptr),
+      got_error_do_not_delegate_anymore_(false),
+      default_model_namespace_(default_model_namespace),
+      default_model_id_(default_model_id),
+      mini_benchmark_(nullptr) {}
+
+std::string TfLiteInterpreterWrapper::ModelNamespace() {
+  const auto& ns_from_acceleration =
+      compute_settings_.model_namespace_for_statistics();
+  return ns_from_acceleration.empty() ? default_model_namespace_
+                                      : ns_from_acceleration;
+}
+
+std::string TfLiteInterpreterWrapper::ModelID() {
+  const auto& id_from_acceleration =
+      compute_settings_.model_identifier_for_statistics();
+  return id_from_acceleration.empty() ? default_model_id_
+                                      : id_from_acceleration;
+}
+
+// This is the deprecated overload that doesn't take an
+// InterpreterCreationResources parameter.
 absl::Status TfLiteInterpreterWrapper::InitializeWithFallback(
     std::function<absl::Status(std::unique_ptr<tflite::Interpreter>*)>
         interpreter_initializer,
-    const tflite::proto::ComputeSettings& compute_settings) {
-  if (compute_settings.has_preference() ||
-      compute_settings.has_tflite_settings()) {
-    return absl::UnimplementedError(
-        "Acceleration via ComputeSettings is not supported yet.");
+    const ComputeSettings& compute_settings) {
+  return InitializeWithFallback(
+      [interpreter_initializer](
+          const InterpreterCreationResources& resources,
+          std::unique_ptr<tflite::Interpreter>* interpreter_out)
+          -> absl::Status {
+        RETURN_IF_ERROR(interpreter_initializer(interpreter_out));
+        if (*interpreter_out != nullptr &&
+            resources.optional_delegate != nullptr) {
+          TfLiteStatus status =
+              (*interpreter_out)
+                  ->ModifyGraphWithDelegate(resources.optional_delegate);
+          if (status != kTfLiteOk) {
+            *interpreter_out = nullptr;
+            RETURN_IF_ERROR(
+                absl::InvalidArgumentError("Applying delegate failed"));
+          }
+        }
+        return absl::OkStatus();
+      },
+      compute_settings);
+}
+
+absl::Status TfLiteInterpreterWrapper::InitializeWithFallback(
+    std::function<absl::Status(const InterpreterCreationResources&,
+                               std::unique_ptr<tflite::Interpreter>*)>
+        interpreter_initializer,
+    const ComputeSettings& compute_settings) {
+  // Store interpreter initializer if not already here.
+  if (interpreter_initializer_) {
+    return absl::FailedPreconditionError(
+        "InitializeWithFallback already called.");
   }
-  RETURN_IF_ERROR(interpreter_initializer(&interpreter_));
-  return interpreter_->AllocateTensors() != kTfLiteOk
-             ? absl::InternalError(
-                   "TFLite interpreter: AllocateTensors() failed.")
-             : absl::OkStatus();
+  interpreter_initializer_ = std::move(interpreter_initializer);
+
+  // Sanity check and copy ComputeSettings.
+  RETURN_IF_ERROR(SanityCheckComputeSettings(compute_settings));
+  compute_settings_ = compute_settings;
+  if (compute_settings_.has_settings_to_test_locally()) {
+    flatbuffers::FlatBufferBuilder mini_benchmark_settings_fbb;
+    const auto* mini_benchmark_settings =
+        tflite::ConvertFromProto(compute_settings_.settings_to_test_locally(),
+                                 &mini_benchmark_settings_fbb);
+    mini_benchmark_ = tflite::acceleration::CreateMiniBenchmark(
+        *mini_benchmark_settings, ModelNamespace(), ModelID());
+    const tflite::ComputeSettingsT from_minibenchmark =
+        mini_benchmark_->GetBestAcceleration();
+    if (from_minibenchmark.tflite_settings != nullptr) {
+      TFLITE_LOG_PROD_ONCE(TFLITE_LOG_INFO, "Using mini benchmark results\n");
+      compute_settings_ = tflite::ConvertFromFlatbuffer(
+          from_minibenchmark, /*skip_mini_benchmark_settings=*/true);
+    }
+    // Trigger mini benchmark if it hasn't already run. Vast majority of cases
+    // should not actually do anything, since first runs are rare.
+    mini_benchmark_->TriggerMiniBenchmark();
+    mini_benchmark_->MarkAndGetEventsToLog();
+  }
+
+  // Initialize fallback behavior.
+  fallback_on_compilation_error_ =
+      compute_settings_.tflite_settings()
+          .fallback_settings()
+          .allow_automatic_fallback_on_compilation_error() ||
+      // Deprecated, keep supporting for backward compatibility.
+      compute_settings_.tflite_settings()
+          .nnapi_settings()
+          .fallback_settings()
+          .allow_automatic_fallback_on_compilation_error();
+  fallback_on_execution_error_ =
+      compute_settings_.tflite_settings()
+          .fallback_settings()
+          .allow_automatic_fallback_on_execution_error() ||
+      // Deprecated, keep supporting for backward compatibility.
+      compute_settings_.tflite_settings()
+          .nnapi_settings()
+          .fallback_settings()
+          .allow_automatic_fallback_on_execution_error();
+
+  return InitializeWithFallbackAndResize();
+}
+
+absl::Status TfLiteInterpreterWrapper::AllocateTensors() {
+  if (interpreter_->AllocateTensors() != kTfLiteOk) {
+    return absl::InternalError("AllocateTensors() failed.");
+  }
+  return absl::OkStatus();
+}
+
+// TODO(b/173406463): the `resize` parameter is going to be used by
+// ResizeAndAllocateTensors functions, coming soon.
+absl::Status TfLiteInterpreterWrapper::InitializeWithFallbackAndResize(
+    std::function<absl::Status(Interpreter*)> resize) {
+  InterpreterCreationResources resources{};
+  if (got_error_do_not_delegate_anymore_ ||
+      compute_settings_.tflite_settings().delegate() == Delegate::NONE) {
+    delegate_.reset(nullptr);
+  } else {
+    // Initialize delegate and add it to 'resources'.
+    RETURN_IF_ERROR(InitializeDelegate());
+    resources.optional_delegate = delegate_.get();
+  }
+
+  absl::Status status = interpreter_initializer_(resources, &interpreter_);
+  if (resources.optional_delegate == nullptr) {
+    RETURN_IF_ERROR(status);
+  }
+  if (resources.optional_delegate != nullptr && !status.ok()) {
+    // Any error when constructing the interpreter is assumed to be a delegate
+    // compilation error.  If a delegate compilation error occurs, stop
+    // delegation from happening in the future.
+    got_error_do_not_delegate_anymore_ = true;
+    delegate_.reset(nullptr);
+    if (fallback_on_compilation_error_) {
+      InterpreterCreationResources fallback_resources{};
+      fallback_resources.optional_delegate = nullptr;
+      RETURN_IF_ERROR(
+          interpreter_initializer_(fallback_resources, &interpreter_));
+    } else {
+      // If instructed not to fallback, return error.
+      return absl::InternalError(absl::StrFormat(
+          "ModifyGraphWithDelegate() failed for delegate '%s'.",
+          Delegate_Name(compute_settings_.tflite_settings().delegate())));
+    }
+  }
+
+  RETURN_IF_ERROR(resize(interpreter_.get()));
+  if (compute_settings_.tflite_settings().cpu_settings().num_threads() != -1) {
+    if (interpreter_->SetNumThreads(
+            compute_settings_.tflite_settings().cpu_settings().num_threads()) !=
+        kTfLiteOk) {
+      return absl::InternalError("Failed setting number of CPU threads");
+    }
+  }
+  SetTfLiteCancellation();
+
+  if (!delegate_) {
+    // Just allocate tensors and return.
+    return AllocateTensors();
+  }
+
+  // The call to ModifyGraphWithDelegate() leaves the interpreter in a usable
+  // state in case of failure: calling AllocateTensors() will silently fallback
+  // on CPU in such a situation.
+  return AllocateTensors();
+}
+
+absl::Status TfLiteInterpreterWrapper::InitializeDelegate() {
+  if (delegate_ == nullptr) {
+    Delegate which_delegate = compute_settings_.tflite_settings().delegate();
+    const tflite::ComputeSettings* compute_settings =
+        tflite::ConvertFromProto(compute_settings_, &flatbuffers_builder_);
+
+    if (which_delegate == Delegate::NNAPI) {
+      RETURN_IF_ERROR(
+          LoadDelegatePlugin("Nnapi", *compute_settings->tflite_settings()));
+    } else if (which_delegate == Delegate::HEXAGON) {
+      RETURN_IF_ERROR(
+          LoadDelegatePlugin("Hexagon", *compute_settings->tflite_settings()));
+    } else if (which_delegate == Delegate::GPU) {
+      RETURN_IF_ERROR(
+          LoadDelegatePlugin("Gpu", *compute_settings->tflite_settings()));
+    } else if (which_delegate == Delegate::EDGETPU) {
+      RETURN_IF_ERROR(
+          LoadDelegatePlugin("EdgeTpu", *compute_settings->tflite_settings()));
+    } else if (which_delegate == Delegate::EDGETPU_CORAL) {
+      RETURN_IF_ERROR(LoadDelegatePlugin("EdgeTpuCoral",
+                                         *compute_settings->tflite_settings()));
+    } else if (which_delegate == Delegate::XNNPACK) {
+      RETURN_IF_ERROR(
+          LoadDelegatePlugin("XNNPack", *compute_settings->tflite_settings()));
+    }
+  }
+  return absl::OkStatus();
 }
 
 absl::Status TfLiteInterpreterWrapper::InvokeWithFallback(
     const std::function<absl::Status(tflite::Interpreter* interpreter)>&
         set_inputs) {
   RETURN_IF_ERROR(set_inputs(interpreter_.get()));
-  return interpreter_->Invoke() != kTfLiteOk
-             ? absl::InternalError("TFLite interpreter: Invoke() failed.")
-             : absl::OkStatus();
+  // Reset cancel flag before calling `Invoke()`.
+  cancel_flag_.Set(false);
+  TfLiteStatus status = kTfLiteError;
+  if (fallback_on_execution_error_) {
+    status = InterpreterUtils::InvokeWithCPUFallback(interpreter_.get());
+  } else {
+    status = interpreter_->Invoke();
+  }
+  if (status == kTfLiteOk) {
+    return absl::OkStatus();
+  }
+  // Assume InvokeWithoutFallback() is guarded under caller's synchronization.
+  // Assume the inference is cancelled successfully if Invoke() returns
+  // kTfLiteError and the cancel flag is `true`.
+  if (status == kTfLiteError && cancel_flag_.Get()) {
+    return absl::CancelledError("Invoke() cancelled.");
+  }
+  if (delegate_) {
+    // Mark that an error occurred so that later invocations immediately
+    // fallback to CPU.
+    got_error_do_not_delegate_anymore_ = true;
+    // InvokeWithCPUFallback returns `kTfLiteDelegateError` in case of
+    // *successful* fallback: convert it to an OK status.
+    if (status == kTfLiteDelegateError) {
+      return absl::OkStatus();
+    }
+  }
+  return absl::InternalError("Invoke() failed.");
 }
 
 absl::Status TfLiteInterpreterWrapper::InvokeWithoutFallback() {
-  return interpreter_->Invoke() != kTfLiteOk
-             ? absl::InternalError("TFLite interpreter: Invoke() failed.")
-             : absl::OkStatus();
+  // Reset cancel flag before calling `Invoke()`.
+  cancel_flag_.Set(false);
+  TfLiteStatus status = interpreter_->Invoke();
+  if (status != kTfLiteOk) {
+    // Assume InvokeWithoutFallback() is guarded under caller's synchronization.
+    // Assume the inference is cancelled successfully if Invoke() returns
+    // kTfLiteError and the cancel flag is `true`.
+    if (status == kTfLiteError && cancel_flag_.Get()) {
+      return absl::CancelledError("Invoke() cancelled.");
+    }
+    return absl::InternalError("Invoke() failed.");
+  }
+  return absl::OkStatus();
 }
 
 void TfLiteInterpreterWrapper::Cancel() {
-  // NOP
+  cancel_flag_.Set(true);
+}
+
+void TfLiteInterpreterWrapper::SetTfLiteCancellation() {
+  // Create a cancellation check function and set to the TFLite interpreter.
+  auto check_cancel_flag = [](void* data) {
+    auto* cancel_flag = reinterpret_cast<CancelFlag*>(data);
+    return cancel_flag->Get();
+  };
+  interpreter_->SetCancellationFunction(reinterpret_cast<void*>(&cancel_flag_),
+                                        check_cancel_flag);
+}
+
+absl::Status TfLiteInterpreterWrapper::LoadDelegatePlugin(
+    const std::string& name,
+    const tflite::TFLiteSettings& tflite_settings) {
+  delegate_plugin_ = DelegatePluginRegistry::CreateByName(
+      absl::StrFormat("%sPlugin", name), tflite_settings);
+
+  if (delegate_plugin_ == nullptr) {
+    return absl::InternalError(absl::StrFormat(
+        "Could not create %s plugin. Have you linked in the %s_plugin target?",
+        name, name));
+  }
+
+  delegate_ = delegate_plugin_->Create();
+  if (delegate_ == nullptr) {
+    return absl::InternalError(
+        absl::StrFormat("Plugin did not create %s delegate.", name));
+  }
+
+  return absl::OkStatus();
+}
+
+bool TfLiteInterpreterWrapper::HasMiniBenchmarkCompleted() {
+  if (mini_benchmark_ != nullptr &&
+      mini_benchmark_->NumRemainingAccelerationTests() == 0) {
+    return true;
+  }
+  return false;
 }
 
 }  // namespace support
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h
index 3fd489f7..9f32fa8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/default/tflite_wrapper.h
@@ -16,40 +16,123 @@
 #define TENSORFLOW_LITE_SUPPORT_CC_PORT_DEFAULT_TFLITE_WRAPPER_H_
 
 #include <memory>
+#include <string>
 #include <utility>
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"       // from @com_google_absl
+#include "flatbuffers/flatbuffers.h"  // from @flatbuffers
+#include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/experimental/acceleration/configuration/configuration.pb.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/delegate_registry.h"
+#include "tensorflow/lite/experimental/acceleration/mini_benchmark/mini_benchmark.h"
 #include "tensorflow/lite/interpreter.h"
+#include "tensorflow/lite/interpreter_builder.h"
 
 namespace tflite {
 namespace support {
 
-// Wrapper for a TfLiteInterpreter that may be accelerated[1]. This is NOT yet
-// implemented: this class only provides a first, minimal interface in the
-// meanwhile.
+// Options that are created by `TFLiteInterpreterWrapper` and will help to
+// initialize Interpreter in the callback function. `TFLiteInterpreterWrapper`
+// retains ownership of the included options, and will ensure that they remain
+// valid for the duration of the created interpreter's lifetime.
+struct InterpreterCreationResources {
+  // The delegate created, based on the parameters in `ComputeSettings`.
+  // `TfLiteInterpreterWrapper` exclusively owns the `TfLiteDelegate` object,
+  // and maintains it through out the lifetime of `TfLiteInterpreterWrapper`.
+  TfLiteDelegate* optional_delegate;
+
+  // Number of threads to use, or -1 to use the default number of threads.
+  int num_threads = -1;
+
+  // Apply the InterpreterCreationResources to the InterpreterBuilder.
+  // Note: caller is responsible for ensuring that arguments are valid,
+  // e.g. that num_threads >= -1.
+  void ApplyTo(tflite::InterpreterBuilder* interpreter_builder) const {
+    if (optional_delegate != nullptr) {
+      interpreter_builder->AddDelegate(optional_delegate);
+    }
+    if (num_threads != -1) {
+      // We ignore the TfLiteStatus return value here; caller is responsible
+      // for checking that num_threads is valid.
+      (void)interpreter_builder->SetNumThreads(num_threads);
+    }
+  }
+};
+
+// Wrapper for a TfLiteInterpreter that may be accelerated [1]. Meant to be
+// substituted for `unique_ptr<tflite::Interpreter>` class members.
 //
-// [1] See tensorflow/lite/experimental/acceleration for more details.
+// This class is in charge of:
+// * Picking, instantiating and configuring the right delegate for the provided
+//   ComputeSettings [2],
+// * Providing methods to initialize and invoke the Interpreter with optional
+//   (controlled through the ComputeSettings) automatic fallback to CPU if any
+//   acceleration-related error occurs at compilation or runtime.
+// * TODO(b/169474250) Cache interpreters for multiple input sizes to enable
+//   performant acceleration for the case where input size changes frequently.
+//
+// IMPORTANT: The only supported delegates are (as defined in [1]) NONE, GPU,
+// HEXAGON and NNAPI. Trying to use this class with EDGETPU or XNNPACK delegates
+// will cause an UnimplementedError to be thrown at initialization time.
+//
+// Like TfLiteInterpreter, this class is thread-compatible. Use from multiple
+// threads must be guarded by synchronization outside this class.
+//
+// [1]:
+// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/configuration.proto
 class TfLiteInterpreterWrapper {
  public:
-  TfLiteInterpreterWrapper() = default;
+  // Creates an instance to be associated with a TfLite model that could be
+  // identified by (`default_model_namespace`, `default_model_id`). Note the
+  // model identifier is generally used for the sake of logging.
+  TfLiteInterpreterWrapper(const std::string& default_model_namespace,
+                           const std::string& default_model_id);
+  TfLiteInterpreterWrapper()
+      : TfLiteInterpreterWrapper("org.tensorflow.lite.support",
+                                 "unknown_model_id") {}
 
   virtual ~TfLiteInterpreterWrapper() = default;
 
-  // Calls `interpreter_initializer` and then `AllocateTensors`. Future
-  // implementation of this method will attempt to apply the provided
-  // `compute_settings` with a graceful fallback in case a failure occurs.
-  // Note: before this gets implemented, do NOT call this method with non-empty
-  // `compute_settings` otherwise an unimplemented error occurs.
+  // Calls `interpreter_initializer` to construct the Interpreter, then
+  // initializes it with the appropriate delegate (if any) specified through
+  // `compute_settings` and finally calls AllocateTensors() on it.
+  //
+  // Whether or not this function automatically falls back to using CPU in case
+  // initialization with a delegate fails depends on the FallbackSettings
+  // specified in the TFLiteSettings of the provided ComputeSettings: if the
+  // `allow_automatic_fallback_on_compilation_error` field is set to true,
+  // fallback will automatically happen; otherwise an InternalError will be
+  // thrown.
+  // This flag allows callers to rely on this function whether or not they
+  // actually want fallback to happen; if they don't, it will ensure that the
+  // configuration doesn't accidentally trigger fallback.
+  //
+  // IMPORTANT: Supported delegate type includes: NONE, NNAPI, GPU, HEXAGON,
+  // XNNPACK, EDGETPU (Google internal), and EDGETPU_CORAL. Specifying another
+  // delegate type may cause an UnimplementedError to be thrown.
+  absl::Status InitializeWithFallback(
+      std::function<absl::Status(const InterpreterCreationResources&,
+                                 std::unique_ptr<tflite::Interpreter>*)>
+          interpreter_initializer,
+      const tflite::proto::ComputeSettings& compute_settings);
+
+  // Deprecated: Use the one above with `InterpreterCreationResources` instead.
   absl::Status InitializeWithFallback(
       std::function<absl::Status(std::unique_ptr<tflite::Interpreter>*)>
           interpreter_initializer,
       const tflite::proto::ComputeSettings& compute_settings);
 
-  // Calls `set_inputs` and then Invoke() on the interpreter. Future
-  // implementation of this method will perform a graceful fallback in case a
-  // failure occur due to the `compute_settings` provided at initialization
-  // time.
+  // Calls `set_inputs` and then Invoke() on the interpreter.
+  //
+  // Whether or not this function automatically falls back to using CPU in case
+  // invocation with a delegate fails depends on the FallbackSettings
+  // specified in the TFLiteSettings of the ComputeSettings provided at
+  // initialization: if the `allow_automatic_fallback_on_execution_error`
+  // field is set to true, fallback will automatically happen; otherwise an
+  // InternalError will be thrown.
+  // This flag allows callers to rely on this function whether or not they
+  // actually want fallback to happen; if they don't, it will ensure that the
+  // configuration doesn't accidentally trigger fallback.
   absl::Status InvokeWithFallback(
       const std::function<absl::Status(tflite::Interpreter* interpreter)>&
           set_inputs);
@@ -58,8 +141,23 @@
   // before-hand.
   absl::Status InvokeWithoutFallback();
 
-  // Cancels the current running TFLite invocation on CPU. This method is not
-  // yet implemented though it is safe to use it as it acts as a NOP.
+  // Cancels the current TFLite **CPU** inference.
+  //
+  // IMPORTANT: If inference is entirely running on a delegate, this has no
+  // effect; if inference is partially delegated, only the CPU part is
+  // cancelled.
+  //
+  // Usually called on a different thread than the one Invoke() is running
+  // on. Calling Cancel() while InvokeWithFallback() or InvokeWithoutFallback()
+  // is running may cause these methods to return a `CancelledError` with empty
+  // results. Calling Cancel() at any other time doesn't have any effect.
+  //
+  // InvokeWithFallback() and InvokeWithoutFallback() reset the cancel flag
+  // right before the underlying Invoke() is called, so these two methods can be
+  // called again on the same instance after a call to Cancel().
+  //
+  // Note that this is the only method that can be called from another thread
+  // without locking.
   void Cancel();
 
   // Accesses the underlying interpreter for other methods.
@@ -72,8 +170,109 @@
   TfLiteInterpreterWrapper(const TfLiteInterpreterWrapper&) = delete;
   TfLiteInterpreterWrapper& operator=(const TfLiteInterpreterWrapper&) = delete;
 
+  // Whether an error has occurred with the delegate.
+  bool HasDelegateError() { return got_error_do_not_delegate_anymore_; }
+
+  // Whether the on-device mini-benchmark has completed for those TfLite
+  // acceleration configurations that are specified in passed-in
+  // ComputeSettings. If it finishes, the next time this same InterpreterWrapper
+  // object is created (i.e. w/ the same model and the same
+  // mini-benchmark-related configurations), the best acceleration configuration
+  // will be picked up and used.
+  bool HasMiniBenchmarkCompleted();
+
+  const tflite::proto::ComputeSettings& compute_settings() const {
+    return compute_settings_;
+  }
+
+ protected:
+  // The delegate used to accelerate inference.
+  Interpreter::TfLiteDelegatePtr delegate_;
+  // The corresponding delegate plugin.
+  std::unique_ptr<tflite::delegates::DelegatePluginInterface> delegate_plugin_;
+
  private:
+  // Performs sanity checks on the provided ComputeSettings.
+  static absl::Status SanityCheckComputeSettings(
+      const tflite::proto::ComputeSettings& compute_settings);
+
+  // Inner function for initializing an interpreter with fallback, optionally
+  // resizing input tensors by calling `resize` on the newly initialized
+  // interpreter.
+  absl::Status InitializeWithFallbackAndResize(
+      std::function<absl::Status(Interpreter* interpreter)> resize =
+          [](Interpreter* interpreter) { return absl::OkStatus(); });
+
+  // Initializes the delegate plugin and creates the delegate.
+  absl::Status InitializeDelegate();
+
+  // Wrapper around the interpreter's `AllocateTensors()` method converting the
+  // returned `TfLiteStatus` to an `absl::Status`.
+  absl::Status AllocateTensors();
+
+  absl::Status LoadDelegatePlugin(const std::string&,
+                                  const tflite::TFLiteSettings&);
+
+  std::string ModelNamespace();
+  std::string ModelID();
+
+  // The interpreter instance being used.
   std::unique_ptr<tflite::Interpreter> interpreter_;
+  // The function used to initialize the interpreter and store it into the
+  // provided `std::unique_ptr`.
+  // This is typically a wrapper function around `tflite::InterpreterBuilder`,
+  // giving the caller the opportunity to hook-up a custom `tflite::OpResolver`
+  // and / or `tflite::ErrorReporter`.
+  std::function<absl::Status(const InterpreterCreationResources&,
+                             std::unique_ptr<Interpreter>*)>
+      interpreter_initializer_;
+
+  // The ComputeSettings provided at initialization time.
+  // Note when TfLite mini-benchmark is enabled, it could be changed to the
+  // best TfLite acceleration setting selected.
+  tflite::proto::ComputeSettings compute_settings_;
+
+  // Set to true if an occurs with the specified delegate (if any), causing
+  // future calls to fallback on CPU.
+  bool got_error_do_not_delegate_anymore_;
+
+  // Fallback behavior as specified through the ComputeSettings.
+  bool fallback_on_compilation_error_;
+  bool fallback_on_execution_error_;
+
+  std::string default_model_namespace_;
+  std::string default_model_id_;
+
+  // Used to convert the ComputeSettings proto to FlatBuffer format.
+  flatbuffers::FlatBufferBuilder flatbuffers_builder_;
+
+  // Cancellation flag definition.
+  struct CancelFlag {
+    // Mutex to guard the `cancel_flag`.
+    mutable absl::Mutex cancel_mutex;
+
+    // A flag indicates if the caller cancels the TFLite interpreter invocation.
+    bool cancel_flag ABSL_GUARDED_BY(cancel_mutex) = false;
+
+    // Returns `cancel_flag`.
+    bool Get() const ABSL_LOCKS_EXCLUDED(cancel_mutex) {
+      absl::MutexLock cancel_lock(&cancel_mutex);
+      return cancel_flag;
+    }
+
+    // Sets `cancel_flag` to `value`.
+    void Set(bool value) ABSL_LOCKS_EXCLUDED(cancel_mutex) {
+      absl::MutexLock cancel_lock(&cancel_mutex);
+      cancel_flag = value;
+    }
+  };
+  CancelFlag cancel_flag_;
+
+  std::unique_ptr<tflite::acceleration::MiniBenchmark> mini_benchmark_;
+
+  // Sets up the TFLite invocation cancellation by
+  // tflite::Interpreter::SetCancellationFunction().
+  void SetTfLiteCancellation();
 };
 
 }  // namespace support
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h
index 76d9d50..dc6183be 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/integral_types.h
@@ -37,6 +37,19 @@
 #define GG_LL_FORMAT "ll"  // As in "%lld". Note that "q" is poor form also.
 #define GG_LL_FORMAT_W L"ll"
 
+const uint8 kuint8max{0xFF};
+const uint16 kuint16max{0xFFFF};
+const uint32 kuint32max{0xFFFFFFFF};
+const uint64 kuint64max{GG_ULONGLONG(0xFFFFFFFFFFFFFFFF)};
+const int8 kint8min{~0x7F};
+const int8 kint8max{0x7F};
+const int16 kint16min{~0x7FFF};
+const int16 kint16max{0x7FFF};
+const int32 kint32min{~0x7FFFFFFF};
+const int32 kint32max{0x7FFFFFFF};
+const int64 kint64min{GG_LONGLONG(~0x7FFFFFFFFFFFFFFF)};
+const int64 kint64max{GG_LONGLONG(0x7FFFFFFFFFFFFFFF)};
+
 typedef uint64 Fprint;
 static const Fprint kIllegalFprint = 0;
 static const Fprint kMaxFprint = GG_ULONGLONG(0xFFFFFFFFFFFFFFFF);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/status_matchers.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/status_matchers.h
new file mode 100644
index 0000000..3794c0b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/status_matchers.h
@@ -0,0 +1,21 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_STATUS_MATCHERS_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_PORT_STATUS_MATCHERS_H_
+
+#include "tensorflow_lite_support/cc/port/default/status_matchers.h"
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_STATUS_MATCHERS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/statusor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/statusor.h
index f84c756..a80394d41 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/port/statusor.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/port/statusor.h
@@ -16,5 +16,17 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_PORT_STATUSOR_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_PORT_STATUSOR_H_
 
-#include "tensorflow_lite_support/cc/port/default/statusor.h"
+// This header file is used to manage the depended StatusOr library. It creates
+// an extra layer that makes it easier to switch between the desired version of
+// StatusOr.
+#include "absl/status/statusor.h"  // from @com_google_absl
+
+namespace tflite {
+namespace support {
+
+template <typename T>
+using StatusOr = absl::StatusOr<T>;
+
+}  // namespace support
+}  // namespace tflite
 #endif  // TENSORFLOW_LITE_SUPPORT_CC_PORT_STATUSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/README.md b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/README.md
index bd756a2..b91c264 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/README.md
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/README.md
@@ -15,8 +15,8 @@
 Use the C++ API to answer questions as follows:
 
 ```cc
-using tflite::task::text::qa::BertQuestionAnswerer;
-using tflite::task::text::qa::QaAnswer;
+using tflite::task::text::BertQuestionAnswerer;
+using tflite::task::text::QaAnswer;
 // Create API handler with Mobile Bert model.
 auto qa_client = BertQuestionAnswerer::CreateBertQuestionAnswererFromFile("/path/to/mobileBertModel", "/path/to/vocab");
 // Or create API handler with Albert model.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/BUILD
new file mode 100644
index 0000000..d50d3e98
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/BUILD
@@ -0,0 +1,65 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_library_with_tflite",
+)
+
+package(
+    default_visibility = [
+        "//visibility:public",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library_with_tflite(
+    name = "audio_classifier",
+    srcs = ["audio_classifier.cc"],
+    hdrs = ["audio_classifier.h"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/processor:classification_postprocessor",
+        "//tensorflow_lite_support/cc/task/processor:audio_preprocessor",
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:integral_types",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/audio/core:audio_buffer",
+        "//tensorflow_lite_support/cc/task/audio/proto:audio_classifier_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/audio/proto:class_proto_inc",
+        "//tensorflow_lite_support/cc/task/audio/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/core:classification_head",
+        "//tensorflow_lite_support/cc/task/core:label_map_item",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/processor/proto:classification_options_cc_proto",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+        "@org_tensorflow//tensorflow/lite/c:c_api_types",
+        "@org_tensorflow//tensorflow/lite/core/api:op_resolver",
+    ],
+    alwayslink = 1,
+)
+
+cc_library_with_tflite(
+    name = "audio_embedder",
+    srcs = ["audio_embedder.cc"],
+    hdrs = ["audio_embedder.h"],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/processor:embedding_postprocessor",
+        "//tensorflow_lite_support/cc/task/processor:audio_preprocessor",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/audio/proto:audio_embedder_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/processor/proto:embedding_cc_proto",
+        "//tensorflow_lite_support/cc/task/processor/proto:embedding_options_cc_proto",
+        "@com_google_absl//absl/status",
+        "@org_tensorflow//tensorflow/lite/c:common",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc
new file mode 100644
index 0000000..4be3e53
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.cc
@@ -0,0 +1,151 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/audio/audio_classifier.h"
+
+#include <initializer_list>
+
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow/lite/c/c_api_types.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/integral_types.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/audio_classifier_options.pb.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/class_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/core/classification_head.h"
+#include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/processor/audio_preprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/classification_postprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/classification_options.pb.h"
+#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+namespace {
+
+using ::absl::StatusCode;
+using ::tflite::AudioProperties;
+using ::tflite::ContentProperties;
+using ::tflite::ContentProperties_AudioProperties;
+using ::tflite::metadata::ModelMetadataExtractor;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::audio::Class;
+using ::tflite::task::audio::ClassificationResult;
+using ::tflite::task::core::AssertAndReturnTypedTensor;
+using ::tflite::task::core::LabelMapItem;
+using ::tflite::task::core::TaskAPIFactory;
+using ::tflite::task::core::TfLiteEngine;
+
+}  // namespace
+
+StatusOr<std::unique_ptr<processor::ClassificationPostprocessor>>
+CreatePostprocessor(TfLiteEngine* engine,
+                    const std::initializer_list<int> output_indices,
+                    AudioClassifierOptions* options) {
+  auto new_options = std::make_unique<processor::ClassificationOptions>();
+  new_options->set_display_names_locale(options->display_names_locale());
+  new_options->set_max_results(options->max_results());
+  new_options->set_score_threshold(options->score_threshold());
+  new_options->mutable_class_name_allowlist()->Swap(
+      options->mutable_class_name_allowlist());
+  new_options->mutable_class_name_denylist()->Swap(
+      options->mutable_class_name_denylist());
+  return processor::ClassificationPostprocessor::Create(engine, output_indices,
+                                                        std::move(new_options));
+}
+
+/* static */
+StatusOr<std::unique_ptr<AudioClassifier>> AudioClassifier::CreateFromOptions(
+    const AudioClassifierOptions& options,
+    std::unique_ptr<tflite::OpResolver> resolver) {
+  RETURN_IF_ERROR(SanityCheckOptions(options));
+
+  // Copy options to ensure the ExternalFile outlives the constructed object.
+  auto options_copy = absl::make_unique<AudioClassifierOptions>(options);
+
+  ASSIGN_OR_RETURN(auto audio_classifier,
+                   TaskAPIFactory::CreateFromBaseOptions<AudioClassifier>(
+                       &options_copy->base_options(), std::move(resolver)));
+
+  RETURN_IF_ERROR(audio_classifier->Init(std::move(options_copy)));
+
+  return audio_classifier;
+}
+
+/* static */
+absl::Status AudioClassifier::SanityCheckOptions(
+    const AudioClassifierOptions& options) {
+  if (!options.has_base_options()) {
+    return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                   "Missing mandatory `base_options` field",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+
+absl::Status AudioClassifier::Init(
+    std::unique_ptr<AudioClassifierOptions> options) {
+  // Set options.
+  options_ = std::move(options);
+
+  // Create preprocessor, assuming having only 1 input tensor.
+  ASSIGN_OR_RETURN(preprocessor_, processor::AudioPreprocessor::Create(
+                                      GetTfLiteEngine(), {0}));
+
+  // Assuming all output tensors share the same option. This is an limitation in
+  // the current API design.
+  int output_count =
+      GetTfLiteEngine()->OutputCount(GetTfLiteEngine()->interpreter());
+  postprocessors_.reserve(output_count);
+  for (int i = 0; i < output_count; i++) {
+    ASSIGN_OR_RETURN(auto processor, CreatePostprocessor(GetTfLiteEngine(), {i},
+                                                         options_.get()));
+    postprocessors_.emplace_back(std::move(processor));
+  }
+
+  return absl::OkStatus();
+}
+
+tflite::support::StatusOr<ClassificationResult> AudioClassifier::Classify(
+    const AudioBuffer& audio_buffer) {
+  return InferWithFallback(audio_buffer);
+}
+
+tflite::support::StatusOr<audio::ClassificationResult>
+AudioClassifier::Postprocess(
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const AudioBuffer& audio_buffer) {
+  audio::ClassificationResult result;
+  for (auto& processor : postprocessors_) {
+    auto* classification = result.add_classifications();
+    // ClassificationPostprocessor doesn't set head name for backward
+    // compatibility, so we set it here manually.
+    classification->set_head_name(processor->GetHeadName());
+    RETURN_IF_ERROR(processor->Postprocess(classification));
+  }
+
+  return result;
+}
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.h
new file mode 100644
index 0000000..cef48d8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_classifier.h
@@ -0,0 +1,133 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_AUDIO_CLASSIFIER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_AUDIO_CLASSIFIER_H_
+
+#include <memory>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/core/audio_buffer.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/audio_classifier_options.pb.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/classification_head.h"
+#include "tensorflow_lite_support/cc/task/processor/audio_preprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/classification_postprocessor.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+// Performs classification on audio clips.
+//
+// This API expects a TFLite model with metadata.
+//
+// Input tensor:
+//   (kTfLiteFloat32)
+//    - input audio buffer of size `[batch * samples]`.
+//    - batch inference is not supported (`batch` is required to be 1).
+//    - for multi-channel models, the channels need be interleaved.
+// At least one output tensor with:
+//   (kTfLiteFloat32)
+//    - `[1 x N]` array with `N` represents the class number.
+//    - optional (but recommended) label map(s) as AssociatedFile-s with type
+//      TENSOR_AXIS_LABELS, containing one label per line. The first such
+//      AssociatedFile (if any) is used to fill the `class_name` field of the
+//      results. The `display_name` field is filled from the AssociatedFile (if
+//      any) whose locale matches the `display_names_locale` field of the
+//      `ImageClassifierOptions` used at creation time ("en" by default, i.e.
+//      English). If none of these are available, only the `index` field of the
+//      results will be filled.
+//
+// An example of such model can be found at:
+// https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1
+
+// A CLI demo tool is available for easily trying out this API, and provides
+// example usage. See:
+// https://github.com/tensorflow/tflite-support/tree/master/tensorflow_lite_support/examples/task/audio/desktop
+class AudioClassifier
+    : public tflite::task::core::BaseTaskApi<ClassificationResult,
+                                             const AudioBuffer&> {
+ public:
+  using BaseTaskApi::BaseTaskApi;
+
+  // Creates an AudioClassifier from the provided options. A non-default
+  // OpResolver can be specified in order to support custom Ops or specify a
+  // subset of built-in Ops.
+  static tflite::support::StatusOr<std::unique_ptr<AudioClassifier>>
+  CreateFromOptions(
+      const AudioClassifierOptions& options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+
+  // Performs classification on the provided audio buffer.
+  //
+  // The input `audio_buffer` are the raw buffer captured by the required format
+  // which can retrieved by GetRequiredAudioFormat().
+  tflite::support::StatusOr<ClassificationResult> Classify(
+      const AudioBuffer& audio_buffer);
+
+  // Returns the required input audio format if it is set. Otherwise, returns
+  // kMetadataNotFoundError.
+  // TODO(b/182625132): Add unit test after the format is populated from model
+  // metadata.
+  tflite::support::StatusOr<AudioBuffer::AudioFormat> GetRequiredAudioFormat() {
+    return preprocessor_->GetRequiredAudioFormat();
+  }
+
+  // Returns the required input buffer size in number of float elements.
+  int GetRequiredInputBufferSize() {
+    return preprocessor_->GetRequiredInputBufferSize();
+  }
+
+ private:
+  // Performs sanity checks on the provided AudioClassifierOptions.
+  static absl::Status SanityCheckOptions(const AudioClassifierOptions& options);
+
+  // Initializes the AudioClassifier from the provided AudioClassifierOptions,
+  // whose ownership is transferred to this object.
+  absl::Status Init(std::unique_ptr<AudioClassifierOptions> options);
+
+  // Passes through the input audio buffer into model's input tensor.
+  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
+                          const AudioBuffer& audio_buffer) override {
+    return preprocessor_->Preprocess(audio_buffer);
+  }
+
+  // Post-processing to transform the raw model outputs into classification
+  // results.
+  tflite::support::StatusOr<ClassificationResult> Postprocess(
+      const std::vector<const TfLiteTensor*>& output_tensors,
+      const AudioBuffer& audio_buffer) override;
+
+  // The options used to build this AudioClassifier.
+  std::unique_ptr<AudioClassifierOptions> options_;
+
+  std::unique_ptr<tflite::task::processor::AudioPreprocessor> preprocessor_ =
+      nullptr;
+
+  std::vector<
+      std::unique_ptr<tflite::task::processor::ClassificationPostprocessor>>
+      postprocessors_;
+};
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_AUDIO_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.cc
new file mode 100644
index 0000000..c67b67dd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.cc
@@ -0,0 +1,119 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/audio/audio_embedder.h"
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/audio_embedder_options.pb.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/processor/audio_preprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/embedding_options.pb.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+/* static */
+tflite::support::StatusOr<std::unique_ptr<AudioEmbedder>>
+AudioEmbedder::CreateFromOptions(const AudioEmbedderOptions& options,
+                                 std::unique_ptr<tflite::OpResolver> resolver) {
+  RETURN_IF_ERROR(SanityCheckOptions(options));
+  auto options_copy = absl::make_unique<AudioEmbedderOptions>(options);
+
+  ASSIGN_OR_RETURN(auto audio_embedder,
+                   core::TaskAPIFactory::CreateFromBaseOptions<AudioEmbedder>(
+                       &options_copy->base_options(), std::move(resolver)));
+
+  RETURN_IF_ERROR(audio_embedder->Init(std::move(options_copy)));
+  return audio_embedder;
+}
+
+/* static */
+absl::Status AudioEmbedder::SanityCheckOptions(
+    const AudioEmbedderOptions& options) {
+  if (!options.has_base_options()) {
+    return support::CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "Missing mandatory `base_options` field",
+        support::TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+
+absl::Status AudioEmbedder::Init(
+    std::unique_ptr<AudioEmbedderOptions> options) {
+  options_ = std::move(options);
+
+  // Create preprocessor, assuming having only 1 input tensor.
+  ASSIGN_OR_RETURN(preprocessor_,
+                   tflite::task::processor::AudioPreprocessor::Create(
+                       GetTfLiteEngine(), {0}));
+
+  // Create postprocessors, assuming that all output tensors are embedding
+  // outputs.
+  int post_processors_count =
+      GetTfLiteEngine()->OutputCount(GetTfLiteEngine()->interpreter());
+  postprocessors_.reserve(post_processors_count);
+
+  for (int i = 0; i < post_processors_count; i++) {
+    std::unique_ptr<processor::EmbeddingOptions> option = nullptr;
+    if (options_->embedding_options_size() == 0) {
+      // Default options.
+      option = std::make_unique<processor::EmbeddingOptions>();
+    } else if (options_->embedding_options_size() == 1) {
+      // Share the first options.
+      option = std::make_unique<processor::EmbeddingOptions>(
+          options_->embedding_options(0));
+    } else if (options_->embedding_options_size() == post_processors_count) {
+      option = std::make_unique<processor::EmbeddingOptions>(
+          // Use the corresponding options for the tensor.
+          options_->embedding_options(i));
+    } else {
+      return support::CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "Invalid embedding_options. It should have size of either 0, 1 or "
+          "number of output tensors.",
+          support::TfLiteSupportStatus::kInvalidArgumentError);
+    }
+    ASSIGN_OR_RETURN(auto processor,
+                     processor::EmbeddingPostprocessor::Create(
+                         GetTfLiteEngine(), {i}, std::move(option)));
+    postprocessors_.emplace_back(std::move(processor));
+  }
+  return absl::OkStatus();
+}
+
+tflite::support::StatusOr<tflite::task::processor::EmbeddingResult>
+AudioEmbedder::Postprocess(
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const AudioBuffer& audio_buffer) {
+  tflite::task::processor::EmbeddingResult result;
+  for (int i = 0; i < postprocessors_.size(); i++) {
+    auto processor = postprocessors_.at(i).get();
+    RETURN_IF_ERROR(processor->Postprocess(result.add_embeddings()));
+  }
+  return result;
+}
+
+tflite::support::StatusOr<tflite::task::processor::EmbeddingResult>
+AudioEmbedder::Embed(const AudioBuffer& audio_buffer) {
+  return InferWithFallback(audio_buffer);
+}
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h
new file mode 100644
index 0000000..a3d4c57
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/audio_embedder.h
@@ -0,0 +1,92 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_AUDIO_EMBEDDER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_AUDIO_EMBEDDER_H_
+
+#include <memory>
+
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/audio_embedder_options.pb.h"
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/processor/audio_preprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/embedding.pb.h"
+namespace tflite {
+namespace task {
+namespace audio {
+class AudioEmbedder : public tflite::task::core::BaseTaskApi<
+                          tflite::task::processor::EmbeddingResult,
+                          const AudioBuffer&> {
+ public:
+  // Use base class constructor.
+  using BaseTaskApi::BaseTaskApi;
+
+  // Creates an AudioEmbedder from the provided options. A non-default
+  // OpResolver can be specified in order to support custom Ops or specify a
+  // subset of built-in Ops.
+  static tflite::support::StatusOr<std::unique_ptr<AudioEmbedder>>
+  CreateFromOptions(
+      const AudioEmbedderOptions& options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+
+  // Performs actual feature vector extraction on the provided AudioBuffer.
+  tflite::support::StatusOr<tflite::task::processor::EmbeddingResult> Embed(
+      const AudioBuffer& audio_buffer);
+
+  // Returns the required input audio format if it is set. Otherwise, returns
+  // kMetadataNotFoundError.
+  // TODO(b/182625132): Add unit test after the format is populated from model
+  // metadata.
+  tflite::support::StatusOr<AudioBuffer::AudioFormat> GetRequiredAudioFormat() {
+    return preprocessor_->GetRequiredAudioFormat();
+  }
+
+  // Returns the required input buffer size in number of float elements.
+  int GetRequiredInputBufferSize() {
+    return preprocessor_->GetRequiredInputBufferSize();
+  }
+
+ private:
+  static absl::Status SanityCheckOptions(const AudioEmbedderOptions& options);
+
+  absl::Status Init(std::unique_ptr<AudioEmbedderOptions> options);
+
+  // Passes through the input audio buffer into model's input tensor.
+  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
+                          const AudioBuffer& audio_buffer) override {
+    return preprocessor_->Preprocess(audio_buffer);
+  }
+
+  // Transforms the raw model outputs into embedding results.
+  tflite::support::StatusOr<tflite::task::processor::EmbeddingResult>
+  Postprocess(const std::vector<const TfLiteTensor*>& output_tensors,
+              const AudioBuffer& audio_buffer) override;
+
+  std::unique_ptr<AudioEmbedderOptions> options_ = nullptr;
+
+  // Processors
+  std::unique_ptr<tflite::task::processor::AudioPreprocessor> preprocessor_ =
+      nullptr;
+  std::vector<std::unique_ptr<tflite::task::processor::EmbeddingPostprocessor>>
+      postprocessors_;
+};
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_AUDIO_EMBEDDER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/BUILD
new file mode 100644
index 0000000..1b785da
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/BUILD
@@ -0,0 +1,23 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "audio_buffer",
+    hdrs = [
+        "audio_buffer.h",
+    ],
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h
new file mode 100644
index 0000000..d922e48
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/core/audio_buffer.h
@@ -0,0 +1,76 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_CORE_AUDIO_BUFFER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_CORE_AUDIO_BUFFER_H_
+
+#include <memory>
+
+#include "absl/memory/memory.h"       // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+// Provides a view into the provided backing buffer and the audio format
+// metadata.
+// TODO(b/182675479): Support quantized input format.
+class AudioBuffer {
+ public:
+  // Audio format metadata.
+  struct AudioFormat {
+    int channels;
+    int sample_rate;
+  };
+
+  // Factory method for creating an AudioBuffer object. The internal buffer does
+  // not take the ownership of the input backing buffer.
+  static tflite::support::StatusOr<std::unique_ptr<AudioBuffer>> Create(
+      const float* audio_buffer,
+      int buffer_size,
+      const AudioFormat& audio_format) {
+    return absl::make_unique<AudioBuffer>(audio_buffer, buffer_size,
+                                          audio_format);
+  }
+
+  // AudioBuffer for internal use only. Uses the factory method to construct
+  // AudioBuffer instance. The internal buffer does not take the ownership of
+  // the input backing buffer.
+  AudioBuffer(const float* audio_buffer,
+              int buffer_size,
+              const AudioFormat& audio_format)
+      : audio_buffer_(audio_buffer),
+        buffer_size_(buffer_size),
+        audio_format_(audio_format) {}
+
+  // Accessors
+  AudioFormat GetAudioFormat() const { return audio_format_; }
+  int GetBufferSize() const { return buffer_size_; }
+  const float* GetFloatBuffer() const { return audio_buffer_; }
+
+ private:
+  const float* audio_buffer_;
+  int buffer_size_;
+  AudioFormat audio_format_;
+};
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_CORE_AUDIO_BUFFER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/BUILD
new file mode 100644
index 0000000..63d78fb4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/BUILD
@@ -0,0 +1,53 @@
+package(
+    default_visibility = [
+        "//visibility:public",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+# AudioClassifier protos.
+
+proto_library(
+    name = "audio_classifier_options_proto",
+    srcs = ["audio_classifier_options.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "audio_classifier_options_cc_proto",
+    deps = [
+        ":audio_classifier_options_proto",
+    ],
+)
+
+cc_library(
+    name = "classifications_proto_inc",
+    hdrs = ["classifications_proto_inc.h"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:classifications_cc_proto",
+    ],
+)
+
+cc_library(
+    name = "class_proto_inc",
+    hdrs = ["class_proto_inc.h"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:class_cc_proto",
+    ],
+)
+
+proto_library(
+    name = "audio_embedder_options_proto",
+    srcs = ["audio_embedder_options.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
+        "//tensorflow_lite_support/cc/task/processor/proto:embedding_options_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "audio_embedder_options_cc_proto",
+    deps = [":audio_embedder_options_proto"],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/audio_classifier_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/audio_classifier_options.proto
new file mode 100644
index 0000000..a17bb15
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/audio_classifier_options.proto
@@ -0,0 +1,50 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.audio;
+
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
+
+// Options for setting up an AudioClassifier.
+// Next Id: 7
+message AudioClassifierOptions {
+  // Base options for configuring the external model file.
+  optional tflite.task.core.BaseOptions base_options = 1;
+
+  // The locale to use for display names specified through the TFLite Model
+  // Metadata, if any. Defaults to English.
+  optional string display_names_locale = 2 [default = "en"];
+
+  // The maximum number of top-scored classification results to return. If < 0,
+  // all available results will be returned. If 0, an invalid argument error is
+  // returned.
+  optional int32 max_results = 3 [default = -1];
+
+  // Score threshold, overrides the ones provided in the model metadata
+  // (if any). Results below this value are rejected.
+  optional float score_threshold = 4;
+
+  // Optional allowlist of class names. If non-empty, classifications whose
+  // class name is not in this set will be filtered out. Duplicate or unknown
+  // class names are ignored. Mutually exclusive with class_name_denylist.
+  repeated string class_name_allowlist = 5;
+
+  // Optional denylist of class names. If non-empty, classifications whose
+  // class name is in this set will be filtered out. Duplicate or unknown
+  // class names are ignored. Mutually exclusive with class_name_allowlist.
+  repeated string class_name_denylist = 6;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/audio_embedder_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/audio_embedder_options.proto
new file mode 100644
index 0000000..0271c2f4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/audio_embedder_options.proto
@@ -0,0 +1,36 @@
+
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.audio;
+
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
+import "tensorflow_lite_support/cc/task/processor/proto/embedding_options.proto";
+
+// Options for setting up an AudioEmbedder.
+// Next Id: 3
+message AudioEmbedderOptions {
+  // Base options for configuring the external model file.
+  optional tflite.task.core.BaseOptions base_options = 1;
+
+  // Options for each embedding head. If the model contains N heads (embedding
+  // output tensor), then the len(embedding_options) needs to either
+  // 0: All output tensors are processed using the *default* EmbeddingOptions.
+  // 1: All output tensors are processed using the *same* EmbeddingOptions.
+  // N: Output tensors are processed using the *corresponding* EmbeddingOptions.
+  repeated tflite.task.processor.EmbeddingOptions embedding_options = 2;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/class_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/class_proto_inc.h
new file mode 100644
index 0000000..f965e5a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/class_proto_inc.h
@@ -0,0 +1,29 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_PROTO_CLASS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_PROTO_CLASS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/class.pb.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+using Class = ::tflite::task::core::Class;
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_PROTO_CLASSIFICATIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h
new file mode 100644
index 0000000..00ac3fd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h
@@ -0,0 +1,30 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_PROTO_CLASSIFICATIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_PROTO_CLASSIFICATIONS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/classifications.pb.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+using Classifications = ::tflite::task::core::Classifications;
+using ClassificationResult = ::tflite::task::core::ClassificationResult;
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_PROTO_CLASSIFICATIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/BUILD
new file mode 100644
index 0000000..9d2b542
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/BUILD
@@ -0,0 +1,27 @@
+# Description: some utilitiy function for audio processing.
+
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "wav_io",
+    srcs = [
+        "wav_io.cc",
+    ],
+    hdrs = ["wav_io.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:integral_types",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "@com_google_absl//absl/base",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc
new file mode 100644
index 0000000..9ae3fbec
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.cc
@@ -0,0 +1,232 @@
+/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Functions to write audio in WAV format.
+// This file is forked from `tensorflow/core/lib/wav/wav_io.cc`.
+
+#include "tensorflow_lite_support/cc/task/audio/utils/wav_io.h"
+
+#include <math.h>
+#include <string.h>
+
+#include <algorithm>
+#include <cinttypes>
+#include <cstdint>
+#include <fstream>
+#include <limits>
+
+#include "absl/base/casts.h"          // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_cat.h"     // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+namespace {
+
+constexpr char kRiffChunkId[] = "RIFF";
+constexpr char kRiffType[] = "WAVE";
+constexpr char kFormatChunkId[] = "fmt ";
+constexpr char kDataChunkId[] = "data";
+
+inline float Int16SampleToFloat(int16_t data) {
+  constexpr float kMultiplier = 1.0f / (1 << 15);
+  return data * kMultiplier;
+}
+
+}  // namespace
+
+std::string ReadFile(const std::string filepath) {
+  std::ifstream fs(filepath);
+  if (!fs.is_open()) {
+    return "";
+  }
+  std::string contents((std::istreambuf_iterator<char>(fs)),
+                       (std::istreambuf_iterator<char>()));
+  return contents;
+}
+
+// Handles moving the data index forward, validating the arguments, and avoiding
+// overflow or underflow.
+absl::Status IncrementOffset(int old_offset,
+                             size_t increment,
+                             size_t max_size,
+                             int* new_offset) {
+  if (old_offset < 0) {
+    return absl::InvalidArgumentError(
+        absl::StrFormat("Negative offsets are not allowed: %d", old_offset));
+  }
+  if (old_offset > max_size) {
+    return absl::InvalidArgumentError(absl::StrFormat(
+        "Initial offset is outside data range: %d", old_offset));
+  }
+  *new_offset = old_offset + increment;
+  if (*new_offset > max_size) {
+    return absl::InvalidArgumentError(
+        "Data too short when trying to read string");
+  }
+  // See above for the check that the input offset is positive. If it's negative
+  // here then it means that there's been an overflow in the arithmetic.
+  if (*new_offset < 0) {
+    return absl::InvalidArgumentError(
+        absl::StrFormat("Offset too large, overflowed: %d", *new_offset));
+  }
+  return absl::OkStatus();
+}
+
+absl::Status ExpectText(const std::string& data,
+                        const std::string& expected_text,
+                        int* offset) {
+  int new_offset;
+  RETURN_IF_ERROR(
+      IncrementOffset(*offset, expected_text.size(), data.size(), &new_offset));
+  const std::string found_text(data.begin() + *offset,
+                               data.begin() + new_offset);
+  if (found_text != expected_text) {
+    return absl::InvalidArgumentError(absl::StrCat(
+        "Header mismatch: Expected", expected_text, " but found ", found_text));
+  }
+  *offset = new_offset;
+  return absl::OkStatus();
+}
+
+absl::Status ReadString(const std::string& data,
+                        int expected_length,
+                        std::string* value,
+                        int* offset) {
+  int new_offset;
+  RETURN_IF_ERROR(
+      IncrementOffset(*offset, expected_length, data.size(), &new_offset));
+  *value = std::string(data.begin() + *offset, data.begin() + new_offset);
+  *offset = new_offset;
+  return absl::OkStatus();
+}
+
+absl::Status DecodeLin16WaveAsFloatVector(const std::string& wav_string,
+                                          std::vector<float>* float_values,
+                                          uint32_t* sample_count,
+                                          uint16_t* channel_count,
+                                          uint32_t* sample_rate) {
+  int offset = 0;
+  RETURN_IF_ERROR(ExpectText(wav_string, kRiffChunkId, &offset));
+  uint32_t total_file_size;
+  RETURN_IF_ERROR(ReadValue<uint32_t>(wav_string, &total_file_size, &offset));
+  RETURN_IF_ERROR(ExpectText(wav_string, kRiffType, &offset));
+  RETURN_IF_ERROR(ExpectText(wav_string, kFormatChunkId, &offset));
+  uint32_t format_chunk_size;
+  RETURN_IF_ERROR(ReadValue<uint32_t>(wav_string, &format_chunk_size, &offset));
+  if ((format_chunk_size != 16) && (format_chunk_size != 18)) {
+    return absl::InvalidArgumentError(absl::StrFormat(
+        "Bad format chunk size for WAV: Expected 16 or 18, but got %" PRIu32,
+        format_chunk_size));
+  }
+  uint16_t audio_format;
+  RETURN_IF_ERROR(ReadValue<uint16_t>(wav_string, &audio_format, &offset));
+  if (audio_format != 1) {
+    return absl::InvalidArgumentError(absl::StrFormat(
+        "Bad audio format for WAV: Expected 1 (PCM), but got %" PRIu16,
+        audio_format));
+  }
+  RETURN_IF_ERROR(ReadValue<uint16_t>(wav_string, channel_count, &offset));
+  if (*channel_count < 1) {
+    return absl::InvalidArgumentError(absl::StrFormat(
+        "Bad number of channels for WAV: Expected at least 1, but got %" PRIu16,
+        *channel_count));
+  }
+  RETURN_IF_ERROR(ReadValue<uint32_t>(wav_string, sample_rate, &offset));
+  uint32_t bytes_per_second;
+  RETURN_IF_ERROR(ReadValue<uint32_t>(wav_string, &bytes_per_second, &offset));
+  uint16_t bytes_per_sample;
+  RETURN_IF_ERROR(ReadValue<uint16_t>(wav_string, &bytes_per_sample, &offset));
+  // Confusingly, bits per sample is defined as holding the number of bits for
+  // one channel, unlike the definition of sample used elsewhere in the WAV
+  // spec. For example, bytes per sample is the memory needed for all channels
+  // for one point in time.
+  uint16_t bits_per_sample;
+  RETURN_IF_ERROR(ReadValue<uint16_t>(wav_string, &bits_per_sample, &offset));
+  if (bits_per_sample != 16) {
+    return absl::InvalidArgumentError(
+        absl::StrFormat("Can only read 16-bit WAV files, but received %" PRIu16,
+                        bits_per_sample));
+  }
+  const uint32_t expected_bytes_per_sample =
+      ((bits_per_sample * *channel_count) + 7) / 8;
+  if (bytes_per_sample != expected_bytes_per_sample) {
+    return absl::InvalidArgumentError(
+        absl::StrFormat("Bad bytes per sample in WAV header: Expected %" PRIu32
+                        " but got %" PRIu16,
+                        expected_bytes_per_sample, bytes_per_sample));
+  }
+  const uint32_t expected_bytes_per_second = bytes_per_sample * *sample_rate;
+  if (bytes_per_second != expected_bytes_per_second) {
+    return absl::InvalidArgumentError(
+        absl::StrFormat("Bad bytes per second in WAV header: Expected %" PRIu32
+                        " but got %" PRIu32 " (sample_rate=%" PRIu32
+                        ", bytes_per_sample=%" PRIu16 ")",
+                        expected_bytes_per_second, bytes_per_second,
+                        *sample_rate, bytes_per_sample));
+  }
+  if (format_chunk_size == 18) {
+    // Skip over this unused section.
+    offset += 2;
+  }
+
+  bool was_data_found = false;
+  while (offset < wav_string.size()) {
+    std::string chunk_id;
+    RETURN_IF_ERROR(ReadString(wav_string, 4, &chunk_id, &offset));
+    uint32_t chunk_size;
+    RETURN_IF_ERROR(ReadValue<uint32_t>(wav_string, &chunk_size, &offset));
+    if (chunk_size > std::numeric_limits<int32_t>::max()) {
+      return absl::InvalidArgumentError(absl::StrFormat(
+          "WAV data chunk '%s' is too large: %" PRIu32
+          " bytes, but the limit is %d",
+          chunk_id.c_str(), chunk_size, std::numeric_limits<int32_t>::max()));
+    }
+    if (chunk_id == kDataChunkId) {
+      if (was_data_found) {
+        return absl::InvalidArgumentError(
+            "More than one data chunk found in WAV");
+      }
+      was_data_found = true;
+      *sample_count = chunk_size / bytes_per_sample;
+      const uint32_t data_count = *sample_count * *channel_count;
+      int unused_new_offset = 0;
+      // Validate that the data exists before allocating space for it
+      // (prevent easy OOM errors).
+      RETURN_IF_ERROR(IncrementOffset(offset, sizeof(int16_t) * data_count,
+                                      wav_string.size(), &unused_new_offset));
+      float_values->resize(data_count);
+      for (int i = 0; i < data_count; ++i) {
+        int16_t single_channel_value = 0;
+        RETURN_IF_ERROR(
+            ReadValue<int16_t>(wav_string, &single_channel_value, &offset));
+        (*float_values)[i] = Int16SampleToFloat(single_channel_value);
+      }
+    } else {
+      offset += chunk_size;
+    }
+  }
+  if (!was_data_found) {
+    return absl::InvalidArgumentError("No data chunk found in WAV");
+  }
+  return absl::OkStatus();
+}
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h
new file mode 100644
index 0000000..9aca5d06
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/audio/utils/wav_io.h
@@ -0,0 +1,102 @@
+/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Functions to write audio in WAV format.
+// This file is forked from `tensorflow/core/lib/wav/wav_io.h`.
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_UTILS_WAV_IO_H_
+
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_UTILS_WAV_IO_H_
+
+#include <cstdint>
+#include <string>
+#include <vector>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+// Byte order definition provided by gcc. MSVC doesn't define those so
+// we define them here.
+// We assume that all windows platform out there are little endian.
+#if defined(_MSC_VER) && !defined(__clang__)
+#define __ORDER_LITTLE_ENDIAN__ 0x4d2
+#define __ORDER_BIG_ENDIAN__ 0x10e1
+#define __BYTE_ORDER__ __ORDER_LITTLE_ENDIAN__
+#endif
+
+namespace port {
+
+// TODO(jeff,sanjay): Make portable
+constexpr bool kLittleEndian = __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__;
+
+}  // namespace port
+
+// Decodes the little-endian signed 16-bit PCM WAV file data (aka LIN16
+// encoding) into a float Tensor. The channels are encoded as the lowest
+// dimension of the tensor, with the number of frames as the second. This means
+// that a four frame stereo signal will have the shape [4, 2]. The sample rate
+// is read from the file header, and an error is returned if the format is not
+// supported.
+// The results are output as floats within the range -1 to 1,
+absl::Status DecodeLin16WaveAsFloatVector(const std::string& wav_string,
+                                          std::vector<float>* float_values,
+                                          uint32_t* sample_count,
+                                          uint16_t* channel_count,
+                                          uint32_t* sample_rate);
+
+// Everything below here is only exposed publicly for testing purposes.
+
+// Handles moving the data index forward, validating the arguments, and avoiding
+// overflow or underflow.
+absl::Status IncrementOffset(int old_offset,
+                             size_t increment,
+                             size_t max_size,
+                             int* new_offset);
+
+// This function is only exposed in the header for testing purposes, as a
+// template that needs to be instantiated. Reads a typed numeric value from a
+// stream of data.
+template <class T>
+absl::Status ReadValue(const std::string& data, T* value, int* offset) {
+  int new_offset;
+  RETURN_IF_ERROR(
+      IncrementOffset(*offset, sizeof(T), data.size(), &new_offset));
+  if (port::kLittleEndian) {
+    memcpy(value, data.data() + *offset, sizeof(T));
+  } else {
+    *value = 0;
+    const uint8_t* data_buf =
+        reinterpret_cast<const uint8_t*>(data.data() + *offset);
+    int shift = 0;
+    for (int i = 0; i < sizeof(T); ++i, shift += 8) {
+      *value = *value | (data_buf[i] << shift);
+    }
+  }
+  *offset = new_offset;
+  return absl::OkStatus();
+}
+
+// Load the content of the file into std::string.
+std::string ReadFile(const std::string filepath);
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_AUDIO_UTILS_WAV_IO_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/BUILD
index 13164ed..46a16bd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/BUILD
@@ -1,19 +1,16 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "tflite_engine",
     srcs = ["tflite_engine.cc"],
     hdrs = ["tflite_engine.h"],
-    deps = [
-        ":external_file_handler",
-        "@com_google_absl//absl/memory",
-        "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings",
-        "@org_tensorflow//tensorflow/lite/c:common",
-        "@org_tensorflow//tensorflow/lite/core/api",
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:common",
         # The dependency on builtin_ops here is only for the default
         # value of the OpResolver parameter:
         #     std::unique_ptr<tflite::IterableOpResolver> resolver =
@@ -21,88 +18,70 @@
         # When linking statically, if the client of this library doesn't use
         # the default argument, this dependency does not cause all the builtin ops
         # to get included in the executable.
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-        "@org_tensorflow//tensorflow/lite/tools:verifier",
-        "@org_tensorflow//tensorflow/lite:kernel_api",
-    ] + select({
-        "//tensorflow_lite_support/cc:tflite_use_c_api": [
-            "@org_tensorflow//tensorflow/lite/c:c_api",
-            "@org_tensorflow//tensorflow/lite/c:c_api_experimental",
-            "@org_tensorflow//tensorflow/lite:stderr_reporter",
-        ],
-        "//conditions:default": ["@org_tensorflow//tensorflow/lite:framework"],
-    }) + [
-        "//tensorflow_lite_support/cc:common",
-        "//tensorflow_lite_support/cc/port:status_macros",
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "@org_tensorflow//tensorflow/lite/core/shims:framework",
+        "@org_tensorflow//tensorflow/lite/core/shims:verifier",
         "//tensorflow_lite_support/cc/port:tflite_wrapper",
-        "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
-        "//tensorflow_lite_support/metadata/cc:metadata_extractor",
     ],
-)
-
-# This is a duplicate of the above 'tflite_engine' target that is used for
-# testing with TFLITE_USE_C_API defined.  It should be the same as the target
-# above, except that it adds
-#    testonly = 1,
-#    defines = ["TFLITE_USE_C_API"],
-# and that it resolves the conditional deps from the 'select' as if
-# "//tensorflow_lite_support/cc:tflite_use_c_api" was enabled.
-# This allows testing the TFLITE_USE_C_API case even when
-# '--copt=-DTFLITE_USE_C_API' wasn't passed on the build command line.
-cc_library(
-    name = "tflite_engine_with_c_api_for_test",
-    testonly = 1,
-    srcs = ["tflite_engine.cc"],
-    hdrs = ["tflite_engine.h"],
-    defines = ["TFLITE_USE_C_API"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
+        ":error_reporter",
         ":external_file_handler",
         "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:configuration_proto_inc",
         "//tensorflow_lite_support/cc/port:status_macros",
-        "//tensorflow_lite_support/cc/port:tflite_wrapper_with_c_api_for_test",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
         "//tensorflow_lite_support/metadata/cc:metadata_extractor",
         "@com_google_absl//absl/memory",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
         "@org_tensorflow//tensorflow/lite:kernel_api",
-        "@org_tensorflow//tensorflow/lite:stderr_reporter",
-        "@org_tensorflow//tensorflow/lite/c:c_api",
-        "@org_tensorflow//tensorflow/lite/c:c_api_experimental",
-        "@org_tensorflow//tensorflow/lite/c:common",
-        "@org_tensorflow//tensorflow/lite/core/api",
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-        "@org_tensorflow//tensorflow/lite/tools:verifier",
+        "@org_tensorflow//tensorflow/lite/core/api:op_resolver",
     ],
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "base_task_api",
     hdrs = ["base_task_api.h"],
-    deps = [
+    tflite_deps = [
         ":tflite_engine",
+        "//tensorflow_lite_support/cc/port:tflite_wrapper",
+    ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/port:tflite_wrapper",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
         "@org_tensorflow//tensorflow/lite/c:common",
     ],
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "task_api_factory",
     hdrs = ["task_api_factory.h"],
-    deps = [
+    tflite_deps = [
         ":base_task_api",
         ":tflite_engine",
+    ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:configuration_proto_inc",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
+        "@com_google_absl//absl/base:core_headers",
         "@com_google_absl//absl/status",
         "@org_tensorflow//tensorflow/lite/c:common",
-        "@org_tensorflow//tensorflow/lite/core/api",
+        "@org_tensorflow//tensorflow/lite/core/api:op_resolver",
         "@org_tensorflow//tensorflow/lite/kernels:op_macros",
     ],
 )
@@ -111,10 +90,18 @@
     name = "task_utils",
     srcs = ["task_utils.cc"],
     hdrs = ["task_utils.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/metadata:metadata_schema_cc",
         "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
         "@flatbuffers",
         "@org_tensorflow//tensorflow/lite:string_util",
         "@org_tensorflow//tensorflow/lite:type_to_tflitetype",
@@ -126,13 +113,18 @@
 cc_library(
     name = "category",
     hdrs = ["category.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
 )
 
 cc_library(
     name = "external_file_handler",
     srcs = ["external_file_handler.cc"],
     hdrs = ["external_file_handler.h"],
-    visibility = ["//visibility:public"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:integral_types",
@@ -146,3 +138,64 @@
         "@com_google_absl//absl/strings:str_format",
     ],
 )
+
+cc_library(
+    name = "error_reporter",
+    srcs = ["error_reporter.cc"],
+    hdrs = ["error_reporter.h"],
+    deps = [
+        "@org_tensorflow//tensorflow/lite:minimal_logging",
+        "@org_tensorflow//tensorflow/lite:stateful_error_reporter",
+    ],
+)
+
+cc_library(
+    name = "label_map_item",
+    srcs = ["label_map_item.cc"],
+    hdrs = ["label_map_item.h"],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "@com_google_absl//absl/container:flat_hash_map",
+        "@com_google_absl//absl/container:flat_hash_set",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
+
+cc_library(
+    name = "classification_head",
+    srcs = ["classification_head.cc"],
+    hdrs = ["classification_head.h"],
+    deps = [
+        ":label_map_item",
+        ":score_calibration",
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
+        "//tensorflow_lite_support/metadata/cc:metadata_extractor",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
+cc_library(
+    name = "score_calibration",
+    srcs = ["score_calibration.cc"],
+    hdrs = ["score_calibration.h"],
+    deps = [
+        ":label_map_item",
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
+        "@com_google_absl//absl/container:flat_hash_map",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
+        "@com_google_absl//absl/types:optional",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h
index a27f785..effd42f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/base_task_api.h
@@ -18,8 +18,8 @@
 
 #include <utility>
 
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
@@ -38,14 +38,19 @@
 
   virtual ~BaseUntypedTaskApi() = default;
 
-  TfLiteEngine* GetTfLiteEngine() { return engine_.get(); }
-  const TfLiteEngine* GetTfLiteEngine() const { return engine_.get(); }
-
   const metadata::ModelMetadataExtractor* GetMetadataExtractor() const {
     return engine_->metadata_extractor();
   }
 
  protected:
+  // TODO(b/200258103): It's a short term solution. In the future we will forbid
+  // Tasks exposing the underlying TfLiteEngine. Please try not rely on this
+  // function.
+  //
+  // Returns a raw pointer to the underlying TfLiteEngine.
+  TfLiteEngine* GetTfLiteEngine() { return engine_.get(); }
+
+ private:
   std::unique_ptr<TfLiteEngine> engine_;
 };
 
@@ -58,6 +63,24 @@
   BaseTaskApi(const BaseTaskApi&) = delete;
   BaseTaskApi& operator=(const BaseTaskApi&) = delete;
 
+  int32_t GetInputCount() {
+    return GetTfLiteEngine()->interpreter()->inputs().size();
+  }
+
+  const TfLiteIntArray* GetInputShape(int index) {
+    auto interpreter = GetTfLiteEngine()->interpreter();
+    return interpreter->tensor(interpreter->inputs()[index])->dims;
+  }
+
+  int32_t GetOutputCount() {
+    return GetTfLiteEngine()->interpreter()->outputs().size();
+  }
+
+  const TfLiteIntArray* GetOutputShape(int index) {
+    auto interpreter = GetTfLiteEngine()->interpreter();
+    return interpreter->tensor(interpreter->outputs()[index])->dims;
+  }
+
   // Cancels the current running TFLite invocation on CPU.
   //
   // Usually called on a different thread than the one inference is running on.
@@ -69,7 +92,7 @@
   // partially delegated on CPU, logs a warning message and only cancels the
   // invocation running on CPU. Other invocation which depends on the output of
   // the CPU invocation will not be executed.
-  void Cancel() { engine_->Cancel(); }
+  void Cancel() { GetTfLiteEngine()->Cancel(); }
 
  protected:
   // Subclasses need to populate input_tensors from api_inputs.
@@ -84,18 +107,20 @@
       InputTypes... api_inputs) = 0;
 
   // Returns (the addresses of) the model's inputs.
-  std::vector<TfLiteTensor*> GetInputTensors() { return engine_->GetInputs(); }
+  std::vector<TfLiteTensor*> GetInputTensors() {
+    return GetTfLiteEngine()->GetInputs();
+  }
 
   // Returns (the addresses of) the model's outputs.
   std::vector<const TfLiteTensor*> GetOutputTensors() {
-    return engine_->GetOutputs();
+    return GetTfLiteEngine()->GetOutputs();
   }
 
   // Performs inference using tflite::support::TfLiteInterpreterWrapper
   // InvokeWithoutFallback().
   tflite::support::StatusOr<OutputType> Infer(InputTypes... args) {
     tflite::task::core::TfLiteEngine::InterpreterWrapper* interpreter_wrapper =
-        engine_->interpreter_wrapper();
+        GetTfLiteEngine()->interpreter_wrapper();
     // Note: AllocateTensors() is already performed by the interpreter wrapper
     // at InitInterpreter time (see TfLiteEngine).
     RETURN_IF_ERROR(Preprocess(GetInputTensors(), args...));
@@ -115,7 +140,7 @@
   // CPU where applicable.
   tflite::support::StatusOr<OutputType> InferWithFallback(InputTypes... args) {
     tflite::task::core::TfLiteEngine::InterpreterWrapper* interpreter_wrapper =
-        engine_->interpreter_wrapper();
+        GetTfLiteEngine()->interpreter_wrapper();
     // Note: AllocateTensors() is already performed by the interpreter wrapper
     // at InitInterpreter time (see TfLiteEngine).
     RETURN_IF_ERROR(Preprocess(GetInputTensors(), args...));
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/category.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/category.h
index a99f994..9fadd6a 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/category.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/category.h
@@ -15,6 +15,8 @@
 
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_CATEGORY_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_CATEGORY_H_
+
+#include <cmath>
 #include <string>
 
 namespace tflite {
@@ -29,7 +31,9 @@
       : class_name(class_name), score(score) {}
 
   friend bool operator==(const Category& lhs, const Category& rhs) {
-    return lhs.score == rhs.score && lhs.class_name == rhs.class_name;
+    constexpr const double kScoreTolerance = 1e-6;
+    return lhs.class_name == rhs.class_name &&
+           abs((double)(lhs.score - rhs.score)) <= kScoreTolerance;
   }
 
   friend bool operator!=(const Category& lhs, const Category& rhs) {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.cc
new file mode 100644
index 0000000..fe22176
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.cc
@@ -0,0 +1,114 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/core/classification_head.h"
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+using ::absl::StatusCode;
+using ::tflite::metadata::ModelMetadataExtractor;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+
+StatusOr<ClassificationHead> BuildClassificationHead(
+    const tflite::metadata::ModelMetadataExtractor& metadata_extractor,
+    const tflite::TensorMetadata& output_tensor_metadata,
+    absl::string_view display_names_locale) {
+  ClassificationHead head;
+  if (output_tensor_metadata.name() != nullptr) {
+    head.name = output_tensor_metadata.name()->str();
+  }
+
+  // Build label map, if present.
+  const std::string labels_filename =
+      ModelMetadataExtractor::FindFirstAssociatedFileName(
+          output_tensor_metadata,
+          tflite::AssociatedFileType_TENSOR_AXIS_LABELS);
+  if (!labels_filename.empty()) {
+    ASSIGN_OR_RETURN(absl::string_view labels_file,
+                     metadata_extractor.GetAssociatedFile(labels_filename));
+    const std::string display_names_filename =
+        ModelMetadataExtractor::FindFirstAssociatedFileName(
+            output_tensor_metadata,
+            tflite::AssociatedFileType_TENSOR_AXIS_LABELS,
+            display_names_locale);
+    absl::string_view display_names_file;
+    if (!display_names_filename.empty()) {
+      ASSIGN_OR_RETURN(display_names_file, metadata_extractor.GetAssociatedFile(
+                                               display_names_filename));
+    }
+    ASSIGN_OR_RETURN(head.label_map_items,
+                     BuildLabelMapFromFiles(labels_file, display_names_file));
+  }
+
+  // Set score threshold, if present.
+  ASSIGN_OR_RETURN(const tflite::ProcessUnit* score_thresholding_process_unit,
+                   ModelMetadataExtractor::FindFirstProcessUnit(
+                       output_tensor_metadata,
+                       tflite::ProcessUnitOptions_ScoreThresholdingOptions));
+  if (score_thresholding_process_unit != nullptr) {
+    head.score_threshold =
+        score_thresholding_process_unit->options_as_ScoreThresholdingOptions()
+            ->global_score_threshold();
+  }
+
+  // Build score calibration parameters, if present.
+  ASSIGN_OR_RETURN(const tflite::ProcessUnit* score_calibration_process_unit,
+                   ModelMetadataExtractor::FindFirstProcessUnit(
+                       output_tensor_metadata,
+                       tflite::ProcessUnitOptions_ScoreCalibrationOptions));
+  if (score_calibration_process_unit != nullptr) {
+    if (labels_filename.empty()) {
+      return CreateStatusWithPayload(
+          StatusCode::kNotFound,
+          "Using ScoreCalibrationOptions requires a label map to be provided "
+          "as TENSOR_AXIS_LABELS associated file.",
+          TfLiteSupportStatus::kMetadataAssociatedFileNotFoundError);
+    }
+    const std::string score_calibration_filename =
+        ModelMetadataExtractor::FindFirstAssociatedFileName(
+            output_tensor_metadata,
+            tflite::AssociatedFileType_TENSOR_AXIS_SCORE_CALIBRATION);
+    if (score_calibration_filename.empty()) {
+      return CreateStatusWithPayload(
+          StatusCode::kNotFound,
+          "Found ScoreCalibrationOptions but missing required associated "
+          "parameters file with type TENSOR_AXIS_SCORE_CALIBRATION.",
+          TfLiteSupportStatus::kMetadataAssociatedFileNotFoundError);
+    }
+    ASSIGN_OR_RETURN(
+        absl::string_view score_calibration_file,
+        metadata_extractor.GetAssociatedFile(score_calibration_filename));
+    ASSIGN_OR_RETURN(SigmoidCalibrationParameters sigmoid_params,
+                     BuildSigmoidCalibrationParams(
+                         *score_calibration_process_unit
+                              ->options_as_ScoreCalibrationOptions(),
+                         score_calibration_file, head.label_map_items));
+    head.calibration_params = sigmoid_params;
+  }
+
+  return head;
+}
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h
new file mode 100644
index 0000000..c91552f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/classification_head.h
@@ -0,0 +1,110 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_CLASSIFICATION_HEAD_ITEM_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_CLASSIFICATION_HEAD_ITEM_H_
+
+#include <string>
+#include <vector>
+
+#include "absl/memory/memory.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+#include "tensorflow_lite_support/cc/task/core/score_calibration.h"
+#include "tensorflow_lite_support/metadata/cc/metadata_extractor.h"
+#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+// A single classifier head for a classifier model, associated with a
+// corresponding output tensor.
+struct ClassificationHead {
+  ClassificationHead() : score_threshold(0) {}
+
+  explicit ClassificationHead(
+      const std::vector<tflite::task::core::LabelMapItem>&& label_map_items)
+      : label_map_items(label_map_items), score_threshold(0) {}
+
+  // An optional name that usually indicates what this set of classes represent,
+  // e.g. "flowers".
+  std::string name;
+  // The label map representing the list of supported classes, aka labels.
+  //
+  // This must be in direct correspondence with the associated output tensor,
+  // i.e.:
+  //
+  // - The number of classes must match with the dimension of the corresponding
+  // output tensor,
+  // - The i-th item in the label map is assumed to correspond to the i-th
+  // output value in the output tensor.
+  //
+  // This requires to put in place dedicated sanity checks before running
+  // inference.
+  std::vector<tflite::task::core::LabelMapItem> label_map_items;
+  // Recommended score threshold typically in [0,1[. Classification results with
+  // a score below this value are considered low-confidence and should be
+  // rejected from returned results.
+  float score_threshold;
+  // Optional score calibration parameters (one set of parameters per class in
+  // the label map). This is primarily meant for multi-label classifiers made of
+  // independent sigmoids.
+  //
+  // Such parameters are usually tuned so that calibrated scores can be compared
+  // to a default threshold common to all classes to achieve a given amount of
+  // precision.
+  //
+  // Example: 60% precision for threshold = 0.5.
+  absl::optional<tflite::task::core::SigmoidCalibrationParameters>
+      calibration_params;
+};
+
+// Builds a classification head using the provided metadata extractor, for the
+// given output tensor metadata. Returns an error in case the head cannot be
+// built (e.g. missing associated file for score calibration parameters).
+//
+// Optionally it is possible to specify which locale should be used (e.g. "en")
+// to fill the label map display names, if any, and provided the corresponding
+// associated file is present in the metadata. If no locale is specified, or if
+// there is no associated file for the provided locale, display names are just
+// left empty and no error is returned.
+//
+// E.g. (metatada displayed in JSON format below):
+//
+// ...
+// "associated_files": [
+//  {
+//    "name": "labels.txt",
+//    "type": "TENSOR_AXIS_LABELS"
+//  },
+//  {
+//    "name": "labels-en.txt",
+//    "type": "TENSOR_AXIS_LABELS",
+//    "locale": "en"
+//  },
+// ...
+//
+// See metadata schema TENSOR_AXIS_LABELS for more details.
+tflite::support::StatusOr<ClassificationHead> BuildClassificationHead(
+    const tflite::metadata::ModelMetadataExtractor& metadata_extractor,
+    const tflite::TensorMetadata& output_tensor_metadata,
+    absl::string_view display_names_locale = absl::string_view());
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_CLASSIFICATION_HEAD_ITEM_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc
new file mode 100644
index 0000000..a626ce6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.cc
@@ -0,0 +1,48 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/core/error_reporter.h"
+
+#include <cstdarg>
+#include <cstdio>
+#include <cstring>
+
+#include "tensorflow/lite/minimal_logging.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+int ErrorReporter::Report(const char* format, va_list args) {
+  std::strcpy(second_last_message_, last_message_);  // NOLINT
+  last_message_[0] = '\0';
+  int num_characters = vsnprintf(last_message_, kBufferSize, format, args);
+  // To mimic tflite::StderrReporter.
+  tflite::logging_internal::MinimalLogger::Log(TFLITE_LOG_ERROR, "%s",
+                                               last_message_);
+  return num_characters;
+}
+
+std::string ErrorReporter::message() {
+  return last_message_;
+}
+
+std::string ErrorReporter::previous_message() {
+  return second_last_message_;
+}
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.h
new file mode 100644
index 0000000..9f05350
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/error_reporter.h
@@ -0,0 +1,56 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_ERROR_REPORTER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_ERROR_REPORTER_H_
+
+#include <cstdarg>
+#include <string>
+
+#include "tensorflow/lite/stateful_error_reporter.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+// An ErrorReporter that logs to stderr and captures the last two messages.
+class ErrorReporter : public tflite::StatefulErrorReporter {
+ public:
+  ErrorReporter() {
+    last_message_[0] = '\0';
+    second_last_message_[0] = '\0';
+  }
+
+  // We declared two functions with name 'Report', so that the variadic Report
+  // function in tflite::ErrorReporter is hidden.
+  // See https://isocpp.org/wiki/faq/strange-inheritance#hiding-rule.
+  using tflite::ErrorReporter::Report;
+
+  int Report(const char* format, std::va_list args) override;
+
+  std::string message() override;
+  std::string previous_message();
+
+ private:
+  static constexpr int kBufferSize = 1024;
+  char last_message_[kBufferSize];
+  char second_last_message_[kBufferSize];
+};
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_ERROR_REPORTER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
index 55b662f..e91a54f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.cc
@@ -15,14 +15,12 @@
 
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 
-#include <errno.h>
-#include <fcntl.h>
 #include <stddef.h>
 #include <memory>
 #include <string>
 
-#include "absl/memory/memory.h"
-#include "absl/strings/str_format.h"
+#include "absl/memory/memory.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
@@ -30,15 +28,12 @@
 namespace tflite {
 namespace task {
 namespace core {
-namespace {
 
 using ::absl::StatusCode;
 using ::tflite::support::CreateStatusWithPayload;
 using ::tflite::support::StatusOr;
 using ::tflite::support::TfLiteSupportStatus;
 
-}  // namespace
-
 /* static */
 StatusOr<std::unique_ptr<ExternalFileHandler>>
 ExternalFileHandler::CreateFromExternalFile(const ExternalFile* external_file) {
@@ -56,21 +51,15 @@
   if (!external_file_.file_content().empty()) {
     return absl::OkStatus();
   }
-  return CreateStatusWithPayload(
-      StatusCode::kInvalidArgument,
-      "ExternalFile must have 'file_content' set, loading from"
-      "'file_name' is not supported.",
-      TfLiteSupportStatus::kInvalidArgumentError);
+
+  return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                 "ExternalFile must specify 'file_content' "
+                                 "to be compatible with Chromium.",
+                                 TfLiteSupportStatus::kInvalidArgumentError);
 }
 
 absl::string_view ExternalFileHandler::GetFileContent() {
-  if (!external_file_.file_content().empty()) {
-    return external_file_.file_content();
-  } else {
-    return absl::string_view(static_cast<const char*>(buffer_) +
-                                 buffer_offset_ - buffer_aligned_offset_,
-                             buffer_size_);
-  }
+  return external_file_.file_content();
 }
 
 ExternalFileHandler::~ExternalFileHandler() = default;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
index ad292dc..48c6281 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/external_file_handler.h
@@ -18,8 +18,8 @@
 
 #include <memory>
 
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
@@ -64,20 +64,6 @@
 
   // Reference to the input ExternalFile.
   const ExternalFile& external_file_;
-
-  // Points to the memory buffer mapped from the file descriptor of the
-  // ExternalFile, if provided by path or file descriptor.
-  void* buffer_{};
-
-  // The mapped memory buffer offset, if any.
-  int64 buffer_offset_{};
-  // The size in bytes of the mapped memory buffer, if any.
-  int64 buffer_size_{};
-
-  // As mmap(2) requires the offset to be a multiple of sysconf(_SC_PAGE_SIZE):
-
-  // The aligned mapped memory buffer offset, if any.
-  int64 buffer_aligned_offset_{};
 };
 
 }  // namespace core
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc
new file mode 100644
index 0000000..72e4b67
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.cc
@@ -0,0 +1,128 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "absl/strings/str_split.h"   // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+using ::absl::StatusCode;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+
+StatusOr<std::vector<LabelMapItem>> BuildLabelMapFromFiles(
+    absl::string_view labels_file,
+    absl::string_view display_names_file) {
+  if (labels_file.empty()) {
+    return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                   "Expected non-empty labels file.",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  std::vector<absl::string_view> labels = absl::StrSplit(labels_file, '\n');
+  // In most cases, there is an empty line (i.e. newline character) at the end
+  // of the file that needs to be ignored. In such a situation, StrSplit() will
+  // produce a vector with an empty string as final element. Also note that in
+  // case `labels_file` is entirely empty, StrSplit() will produce a vector with
+  // one single empty substring, so there's no out-of-range risk here.
+  if (labels[labels.size() - 1].empty()) {
+    labels.pop_back();
+  }
+
+  std::vector<LabelMapItem> label_map_items;
+  label_map_items.reserve(labels.size());
+  for (int i = 0; i < labels.size(); ++i) {
+    label_map_items.emplace_back(LabelMapItem{.name = std::string(labels[i])});
+  }
+
+  if (!display_names_file.empty()) {
+    std::vector<std::string> display_names =
+        absl::StrSplit(display_names_file, '\n');
+    // In most cases, there is an empty line (i.e. newline character) at the end
+    // of the file that needs to be ignored. See above.
+    if (display_names[display_names.size() - 1].empty()) {
+      display_names.pop_back();
+    }
+    if (display_names.size() != labels.size()) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat(
+              "Mismatch between number of labels (%d) and display names (%d).",
+              labels.size(), display_names.size()),
+          TfLiteSupportStatus::kMetadataNumLabelsMismatchError);
+    }
+    for (int i = 0; i < display_names.size(); ++i) {
+      label_map_items[i].display_name = display_names[i];
+    }
+  }
+  return label_map_items;
+}
+
+absl::Status LabelHierarchy::InitializeFromLabelMap(
+    std::vector<LabelMapItem> label_map_items) {
+  parents_map_.clear();
+  for (const LabelMapItem& label : label_map_items) {
+    for (const std::string& child_name : label.child_name) {
+      parents_map_[child_name].insert(label.name);
+    }
+  }
+  if (parents_map_.empty()) {
+    return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                   "Input labelmap is not hierarchical: there "
+                                   "is no parent-child relationship.",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+
+bool LabelHierarchy::HaveAncestorDescendantRelationship(
+    const std::string& ancestor_name,
+    const std::string& descendant_name) const {
+  absl::flat_hash_set<std::string> ancestors;
+  GetAncestors(descendant_name, &ancestors);
+  return ancestors.contains(ancestor_name);
+}
+
+absl::flat_hash_set<std::string> LabelHierarchy::GetParents(
+    const std::string& name) const {
+  absl::flat_hash_set<std::string> parents;
+  auto it = parents_map_.find(name);
+  if (it != parents_map_.end()) {
+    for (const std::string& parent_name : it->second) {
+      parents.insert(parent_name);
+    }
+  }
+  return parents;
+}
+
+void LabelHierarchy::GetAncestors(
+    const std::string& name,
+    absl::flat_hash_set<std::string>* ancestors) const {
+  const absl::flat_hash_set<std::string> parents = GetParents(name);
+  for (const std::string& parent_name : parents) {
+    auto it = ancestors->insert(parent_name);
+    if (it.second) {
+      GetAncestors(parent_name, ancestors);
+    }
+  }
+}
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h
new file mode 100644
index 0000000..d8e1f70d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/label_map_item.h
@@ -0,0 +1,96 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_LABEL_MAP_ITEM_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_LABEL_MAP_ITEM_H_
+
+#include <string>
+#include <vector>
+
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/container/flat_hash_set.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/string_view.h"      // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+// Structure mapping a numerical class index output to a Knowledge Graph entity
+// ID or any other string label representing this class. Optionally it is
+// possible to specify an additional display name (in a given language) which is
+// typically used for display purposes.
+struct LabelMapItem {
+  // E.g. name = "/m/02xwb"
+  std::string name;
+  // E.g. display_name = "Fruit"
+  std::string display_name;
+  // Optional list of children (e.g. subcategories) used to represent a
+  // hierarchy.
+  std::vector<std::string> child_name;
+};
+
+// Builds a label map from labels and (optional) display names file contents,
+// both expected to contain one label per line. Those are typically obtained
+// from TFLite Model Metadata TENSOR_AXIS_LABELS or TENSOR_VALUE_LABELS
+// associated files.
+// Returns an error e.g. if there's a mismatch between the number of labels and
+// display names.
+tflite::support::StatusOr<std::vector<LabelMapItem>> BuildLabelMapFromFiles(
+    absl::string_view labels_file,
+    absl::string_view display_names_file);
+
+// A class that represents a hierarchy of labels as specified in a label map.
+//
+// For example, it is useful to determine if one label is a descendant of
+// another label or not. This can be used to implement labels pruning based on
+// hierarchy, e.g. if both "fruit" and "banana" have been inferred by a given
+// classifier model prune "fruit" from the final results as "banana" is a more
+// fine-grained descendant.
+class LabelHierarchy {
+ public:
+  LabelHierarchy() = default;
+
+  // Initializes the hierarchy of labels from a given label map vector. Returns
+  // an error status in case of failure, typically if the input label map does
+  // not contain any hierarchical relations between labels.
+  absl::Status InitializeFromLabelMap(
+      std::vector<LabelMapItem> label_map_items);
+
+  // Returns true if `descendant_name` is a descendant of `ancestor_name` in the
+  // hierarchy of labels. Invalid names, i.e. names which do not exist in the
+  // label map used at initialization time, are ignored.
+  bool HaveAncestorDescendantRelationship(
+      const std::string& ancestor_name,
+      const std::string& descendant_name) const;
+
+ private:
+  // Retrieve and return all parent names, if any, for the input label name.
+  absl::flat_hash_set<std::string> GetParents(const std::string& name) const;
+
+  // Retrieve all ancestor names, if any, for the input label name.
+  void GetAncestors(const std::string& name,
+                    absl::flat_hash_set<std::string>* ancestors) const;
+
+  // Label name (key) to parent names (value) direct mapping.
+  absl::flat_hash_map<std::string, absl::flat_hash_set<std::string>>
+      parents_map_;
+};
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_LABEL_MAP_ITEM_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/BUILD
index 7418e5b2..6c97e2b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/BUILD
@@ -12,9 +12,8 @@
     srcs = ["external_file.proto"],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "external_file_cc_proto",
-    srcs = ["external_file.proto"],
     deps = [
         ":external_file_proto",
     ],
@@ -25,3 +24,56 @@
     hdrs = ["external_file_proto_inc.h"],
     deps = [":external_file_cc_proto"],
 )
+
+proto_library(
+    name = "base_options_proto",
+    srcs = ["base_options.proto"],
+    deps = [
+        ":external_file_proto",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_proto",
+    ],
+)
+
+support_cc_proto_library(
+    name = "base_options_cc_proto",
+    deps = [
+        ":base_options_proto",
+    ],
+)
+
+cc_library(
+    name = "base_options_proto_inc",
+    hdrs = ["base_options_proto_inc.h"],
+    deps = [
+        ":base_options_cc_proto",
+        ":external_file_proto_inc",
+        "//tensorflow_lite_support/cc/port:configuration_proto_inc",
+    ],
+)
+
+proto_library(
+    name = "classifications_proto",
+    srcs = ["classifications.proto"],
+    deps = [
+        ":class_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "classifications_cc_proto",
+    deps = [
+        ":classifications_proto",
+    ],
+)
+
+proto_library(
+    name = "class_proto",
+    srcs = ["class.proto"],
+)
+
+cc_proto_library(
+    name = "class_cc_proto",
+    deps = [
+        ":class_proto",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/base_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/base_options.proto
new file mode 100644
index 0000000..9d529d6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/base_options.proto
@@ -0,0 +1,51 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.core;
+
+import "tensorflow/lite/experimental/acceleration/configuration/configuration.proto";
+
+import "tensorflow_lite_support/cc/task/core/proto/external_file.proto";
+
+// Base options for task libraries.
+// Next Id: 4
+message BaseOptions {
+  // The external model file, as a single standalone TFLite file. It could be
+  // packed with TFLite Model Metadata[1] and associated files if exist. Fail to
+  // provide the necessary metadata and associated files might result in errors.
+  // Check the documentation for each task about the specific requirement.
+  // [1]: https://www.tensorflow.org/lite/convert/metadata
+
+  optional core.ExternalFile model_file = 1;
+
+  // Advanced settings specifying how to accelerate the model inference using
+  // dedicated delegates. Supported delegate type includes:
+  // NONE, NNAPI, GPU, HEXAGON, XNNPACK, EDGETPU (Google internal),
+  // and EDGETPU_CORAL.
+  //
+  // IMPORTANT: in order to use a delegate, the appropriate delegate plugin
+  // needs to be linked at build time.
+  //
+  // For example, `gpu_plugin` for GPU from:
+  // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/BUILD
+  // To use EDGETPU_CORAL, link to `edgetpu_coral_plugin` from:
+  // https://github.com/tensorflow/tflite-support/blob/a58a4f9225c411fa9ba29f821523e6e283988d23/tensorflow_lite_support/acceleration/configuration/BUILD#L11
+  //
+  // See settings definition at:
+  // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/configuration.proto
+  optional tflite.proto.ComputeSettings compute_settings = 2;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h
new file mode 100644
index 0000000..4c53a2f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h
@@ -0,0 +1,23 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_PROTO_BASE_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_PROTO_BASE_OPTIONS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options.pb.h"
+#include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_PROTO_BASE_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/class.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/class.proto
new file mode 100644
index 0000000..83d381a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/class.proto
@@ -0,0 +1,36 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.core;
+
+// A single classification result.
+message Class {
+  // The index of the class in the corresponding label map, usually packed in
+  // the TFLite Model Metadata [1].
+  //
+  // [1]: https://www.tensorflow.org/lite/convert/metadata
+  optional int32 index = 1;
+  // The score for this class e.g. (but not necessarily) a probability in [0,1].
+  optional float score = 2;
+  // A human readable name of the class filled from the label map.
+  optional string display_name = 3;
+  // An ID for the class, not necessarily human-readable (e.g. a Google
+  // Knowledge Graph ID [1]), filled from the label map.
+  //
+  // [1]: https://developers.google.com/knowledge-graph
+  optional string class_name = 4;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/classifications.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/classifications.proto
new file mode 100644
index 0000000..ee1f099e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/classifications.proto
@@ -0,0 +1,39 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.core;
+
+import "tensorflow_lite_support/cc/task/core/proto/class.proto";
+
+// List of predicted classes (aka labels) for a given classifier head.
+message Classifications {
+  // The array of predicted classes, usually sorted by descending scores (e.g.
+  // from high to low probability).
+  repeated Class classes = 1;
+  // The index of the classifier head these classes refer to. This is useful for
+  // multi-head models.
+  optional int32 head_index = 2;
+  // The name of the classifier head, which is the corresponding tensor metadata
+  // name. See
+  // https://github.com/tensorflow/tflite-support/blob/710e323265bfb71fdbdd72b3516e00cff15c0326/tensorflow_lite_support/metadata/metadata_schema.fbs#L545
+  optional string head_name = 3;
+}
+
+// Contains one set of results per classifier head.
+message ClassificationResult {
+  repeated Classifications classifications = 1;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/proto_config.pbtxt b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/proto_config.pbtxt
deleted file mode 100644
index dafb0fd..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/proto/proto_config.pbtxt
+++ /dev/null
@@ -1,2 +0,0 @@
-allow_all: true
-optimize_mode: LITE_RUNTIME
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc
new file mode 100644
index 0000000..e7faeba
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.cc
@@ -0,0 +1,225 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/core/score_calibration.h"
+
+#include <cmath>
+#include <memory>
+#include <utility>
+#include <vector>
+
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/str_format.h"   // from @com_google_absl
+#include "absl/strings/str_split.h"    // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "absl/types/optional.h"       // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+namespace {
+
+using ::absl::StatusCode;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+
+// Used to prevent log(<=0.0) in ClampedLog() calls.
+constexpr float kLogScoreMinimum = 1e-16;
+
+// Returns the following, depending on x:
+//   x => threshold: log(x)
+//   x < threshold: 2 * log(thresh) - log(2 * thresh - x)
+// This form (a) is anti-symmetric about the threshold and (b) has continuous
+// value and first derivative. This is done to prevent taking the log of values
+// close to 0 which can lead to floating point errors and is better than simple
+// clamping since it preserves order for scores less than the threshold.
+float ClampedLog(float x, float threshold) {
+  if (x < threshold) {
+    return 2.0 * std::log(static_cast<double>(threshold)) -
+           log(2.0 * threshold - x);
+  }
+  return std::log(static_cast<double>(x));
+}
+
+// Applies the specified score transformation to the provided score.
+// Currently supports the following,
+//   IDENTITY         : f(x) = x
+//   LOG              : f(x) = log(x)
+//   INVERSE_LOGISTIC : f(x) = log(x) - log(1-x)
+float ApplyScoreTransformation(float score, const ScoreTransformation& type) {
+  switch (type) {
+    case ScoreTransformation::kIDENTITY:
+      return score;
+    case ScoreTransformation::kINVERSE_LOGISTIC:
+      return (ClampedLog(score, kLogScoreMinimum) -
+              ClampedLog(1.0 - score, kLogScoreMinimum));
+    case ScoreTransformation::kLOG:
+      return ClampedLog(score, kLogScoreMinimum);
+  }
+}
+
+// Builds a single Sigmoid from the label name and associated CSV file line.
+StatusOr<Sigmoid> SigmoidFromLabelAndLine(absl::string_view label,
+                                          absl::string_view line) {
+  std::vector<absl::string_view> str_params = absl::StrSplit(line, ',');
+  if (str_params.size() != 3 && str_params.size() != 4) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Expected 3 or 4 parameters per line in score "
+                        "calibration file, got %d.",
+                        str_params.size()),
+        TfLiteSupportStatus::kMetadataMalformedScoreCalibrationError);
+  }
+  std::vector<float> float_params(4);
+  for (int i = 0; i < str_params.size(); ++i) {
+    if (!absl::SimpleAtof(str_params[i], &float_params[i])) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat(
+              "Could not parse score calibration parameter as float: %s.",
+              str_params[i]),
+          TfLiteSupportStatus::kMetadataMalformedScoreCalibrationError);
+    }
+  }
+  Sigmoid sigmoid;
+  sigmoid.label = std::string(label);
+  sigmoid.scale = float_params[0];
+  sigmoid.slope = float_params[1];
+  sigmoid.offset = float_params[2];
+  if (str_params.size() == 4) {
+    sigmoid.min_uncalibrated_score = float_params[3];
+  }
+  return sigmoid;
+}
+
+// Converts a tflite::ScoreTransformationType to its
+// tflite::task::vision::ScoreTransformation equivalent.
+ScoreTransformation ConvertScoreTransformationType(
+    tflite::ScoreTransformationType type) {
+  switch (type) {
+    case tflite::ScoreTransformationType_IDENTITY:
+      return ScoreTransformation::kIDENTITY;
+    case tflite::ScoreTransformationType_LOG:
+      return ScoreTransformation::kLOG;
+    case tflite::ScoreTransformationType_INVERSE_LOGISTIC:
+      return ScoreTransformation::kINVERSE_LOGISTIC;
+  }
+}
+
+}  // namespace
+
+std::ostream& operator<<(std::ostream& os, const Sigmoid& s) {
+  os << s.label << "," << s.slope << "," << s.offset << "," << s.scale;
+  if (s.min_uncalibrated_score.has_value()) {
+    os << "," << s.min_uncalibrated_score.value();
+  }
+  return os;
+}
+
+ScoreCalibration::ScoreCalibration() {}
+ScoreCalibration::~ScoreCalibration() {}
+
+absl::Status ScoreCalibration::InitializeFromParameters(
+    const SigmoidCalibrationParameters& params) {
+  sigmoid_parameters_ = std::move(params);
+  // Fill in the map from label -> sigmoid.
+  sigmoid_parameters_map_.clear();
+  for (const auto& sigmoid : sigmoid_parameters_.sigmoid) {
+    sigmoid_parameters_map_.insert_or_assign(sigmoid.label, sigmoid);
+  }
+  return absl::OkStatus();
+}
+
+float ScoreCalibration::ComputeCalibratedScore(const std::string& label,
+                                               float uncalibrated_score) const {
+  absl::optional<Sigmoid> sigmoid = FindSigmoidParameters(label);
+  if (!sigmoid.has_value() ||
+      (sigmoid.value().min_uncalibrated_score.has_value() &&
+       uncalibrated_score < sigmoid.value().min_uncalibrated_score.value())) {
+    return sigmoid_parameters_.default_score;
+  }
+
+  float transformed_score = ApplyScoreTransformation(
+      uncalibrated_score, sigmoid_parameters_.score_transformation);
+  float scale_shifted_score =
+      transformed_score * sigmoid.value().slope + sigmoid.value().offset;
+
+  // For numerical stability use 1 / (1+exp(-x)) when scale_shifted_score >= 0
+  // and exp(x) / (1+exp(x)) when scale_shifted_score < 0.
+  if (scale_shifted_score >= 0.0) {
+    return sigmoid.value().scale /
+           (1.0 + std::exp(static_cast<double>(-scale_shifted_score)));
+  } else {
+    float score_exp = std::exp(static_cast<double>(scale_shifted_score));
+    return sigmoid.value().scale * score_exp / (1.0 + score_exp);
+  }
+}
+
+absl::optional<Sigmoid> ScoreCalibration::FindSigmoidParameters(
+    const std::string& label) const {
+  auto it = sigmoid_parameters_map_.find(label);
+  if (it != sigmoid_parameters_map_.end()) {
+    return it->second;
+  } else if (sigmoid_parameters_.default_sigmoid.has_value()) {
+    return sigmoid_parameters_.default_sigmoid.value();
+  }
+  return absl::nullopt;
+}
+
+StatusOr<SigmoidCalibrationParameters> BuildSigmoidCalibrationParams(
+    const tflite::ScoreCalibrationOptions& score_calibration_options,
+    absl::string_view score_calibration_file,
+    const std::vector<LabelMapItem>& label_map_items) {
+  // Split file lines and perform sanity checks.
+  if (score_calibration_file.empty()) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        "Expected non-empty score calibration file.");
+  }
+  std::vector<absl::string_view> lines =
+      absl::StrSplit(score_calibration_file, '\n');
+  if (label_map_items.size() != lines.size()) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Mismatch between number of labels (%d) and score "
+                        "calibration parameters (%d).",
+                        label_map_items.size(), lines.size()),
+        TfLiteSupportStatus::kMetadataNumLabelsMismatchError);
+  }
+  // Initialize SigmoidCalibrationParameters with its class-agnostic parameters.
+  SigmoidCalibrationParameters sigmoid_params = {};
+  sigmoid_params.score_transformation = ConvertScoreTransformationType(
+      score_calibration_options.score_transformation());
+  sigmoid_params.default_score = score_calibration_options.default_score();
+  std::vector<Sigmoid> sigmoid_vector;
+  // Fill sigmoids for each class with parameters in the file.
+  for (int i = 0; i < label_map_items.size(); ++i) {
+    if (lines[i].empty()) {
+      continue;
+    }
+    ASSIGN_OR_RETURN(Sigmoid sigmoid, SigmoidFromLabelAndLine(
+                                          label_map_items[i].name, lines[i]));
+    sigmoid_vector.emplace_back(std::move(sigmoid));
+  }
+  sigmoid_params.sigmoid = std::move(sigmoid_vector);
+
+  return sigmoid_params;
+}
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h
new file mode 100644
index 0000000..6e2b308b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/score_calibration.h
@@ -0,0 +1,149 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_SCORE_CALIBRATION_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_SCORE_CALIBRATION_H_
+
+#include <iostream>
+#include <map>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/string_view.h"      // from @com_google_absl
+#include "absl/types/optional.h"           // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+
+namespace tflite {
+namespace task {
+namespace core {
+
+// Sigmoid structure.
+struct Sigmoid {
+  Sigmoid() : scale(1.0) {}
+  Sigmoid(std::string label,
+          float slope,
+          float offset,
+          float scale = 1.0,
+          absl::optional<float> min_uncalibrated_score = absl::nullopt)
+      : label(label),
+        slope(slope),
+        offset(offset),
+        scale(scale),
+        min_uncalibrated_score(min_uncalibrated_score) {}
+
+  bool operator==(const Sigmoid& other) const {
+    return label == other.label && slope == other.slope &&
+           offset == other.offset && scale == other.scale &&
+           min_uncalibrated_score == other.min_uncalibrated_score;
+  }
+
+  // Unique label corresponding to the sigmoid parameters.
+  std::string label;
+  float slope;
+  float offset;
+  float scale;
+  absl::optional<float> min_uncalibrated_score;
+};
+
+std::ostream& operator<<(std::ostream& os, const Sigmoid& s);
+
+// Transformation function to use for computing transformation scores.
+enum class ScoreTransformation {
+  kIDENTITY,         // f(x) = x
+  kLOG,              // f(x) = log(x)
+  kINVERSE_LOGISTIC  // f(x) = log(x) - log(1 - x)
+};
+
+// Sigmoid calibration parameters.
+struct SigmoidCalibrationParameters {
+  SigmoidCalibrationParameters()
+      : default_score(0.0),
+        score_transformation(ScoreTransformation::kIDENTITY) {}
+  explicit SigmoidCalibrationParameters(
+      std::vector<Sigmoid> sigmoid,
+      ScoreTransformation score_transformation = ScoreTransformation::kIDENTITY,
+      absl::optional<Sigmoid> default_sigmoid = absl::nullopt,
+      float default_score = 0.0)
+      : sigmoid(sigmoid),
+        default_sigmoid(default_sigmoid),
+        default_score(default_score),
+        score_transformation(score_transformation) {}
+  // A vector of Sigmoid associated to the ScoreCalibration instance.
+  std::vector<Sigmoid> sigmoid;
+  // If set, this sigmoid will be applied to any non-matching labels.
+  absl::optional<Sigmoid> default_sigmoid;
+  // The default score for non-matching labels. Only used if default_sigmoid
+  // isn't set.
+  float default_score;
+  // Function for computing a transformation score prior to sigmoid fitting.
+  ScoreTransformation score_transformation;
+};
+
+// This class is used to calibrate predicted scores so that scores are
+// comparable across labels. Depending on the particular calibration parameters
+// being used, the calibrated scores can also be approximately interpreted as a
+// likelihood of being correct. For a given TF Lite model, such parameters are
+// typically obtained from TF Lite Metadata (see ScoreCalibrationOptions).
+class ScoreCalibration {
+ public:
+  ScoreCalibration();
+  ~ScoreCalibration();
+
+  // Transfers input parameters and construct a label to sigmoid map.
+  absl::Status InitializeFromParameters(
+      const SigmoidCalibrationParameters& params);
+
+  // Returns a calibrated score given a label string and uncalibrated score. The
+  // calibrated score will be in the range [0.0, 1.0] and can loosely be
+  // interpreted as a likelihood of the label being correct.
+  float ComputeCalibratedScore(const std::string& label,
+                               float uncalibrated_score) const;
+
+ private:
+  // Finds the sigmoid parameters corresponding to the provided label.
+  absl::optional<Sigmoid> FindSigmoidParameters(const std::string& label) const;
+
+  // Parameters for internal states.
+  SigmoidCalibrationParameters sigmoid_parameters_;
+
+  // Maps label strings to the particular sigmoid stored in sigmoid_parameters_.
+  absl::flat_hash_map<std::string, Sigmoid> sigmoid_parameters_map_;
+};
+
+// Builds SigmoidCalibrationParameters using data obtained from TF Lite Metadata
+// (see ScoreCalibrationOptions in metadata schema).
+//
+// The provided `score_calibration_file` represents the contents of the score
+// calibration associated file (TENSOR_AXIS_SCORE_CALIBRATION), i.e. one set of
+// parameters (scale, slope, etc) per line. Each line must be in 1:1
+// correspondence with `label_map_items`, so as to associate each sigmoid to its
+// corresponding label name. Returns an error if no valid parameters could be
+// built (e.g. malformed parameters).
+tflite::support::StatusOr<SigmoidCalibrationParameters>
+BuildSigmoidCalibrationParams(
+    const tflite::ScoreCalibrationOptions& score_calibration_options,
+    absl::string_view score_calibration_file,
+    const std::vector<LabelMapItem>& label_map_items);
+
+}  // namespace core
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_CORE_SCORE_CALIBRATION_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h
index 76a3440..f42d703 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_api_factory.h
@@ -18,18 +18,22 @@
 
 #include <memory>
 
-#include "absl/status/status.h"
+#include "absl/base/macros.h"    // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow/lite/core/api/op_resolver.h"
 #include "tensorflow/lite/kernels/op_macros.h"
+#include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
 
 namespace tflite {
 namespace task {
 namespace core {
+
 template <typename T>
 using EnableIfBaseUntypedTaskApiSubclass = typename std::enable_if<
     std::is_base_of<BaseUntypedTaskApi, T>::value>::type*;
@@ -40,57 +44,132 @@
   TaskAPIFactory() = delete;
 
   template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
+  ABSL_DEPRECATED(
+      "Use CreateFromBaseOptions and configure model input from "
+      "tensorflow_lite_support/cc/task/core/proto/base_options.proto")
   static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromBuffer(
       const char* buffer_data,
       size_t buffer_size,
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-      int num_threads = 1) {
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+      int num_threads = 1,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings()) {
     auto engine = absl::make_unique<TfLiteEngine>(std::move(resolver));
-    RETURN_IF_ERROR(engine->BuildModelFromFlatBuffer(buffer_data, buffer_size));
-    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads);
+    RETURN_IF_ERROR(engine->BuildModelFromFlatBuffer(buffer_data, buffer_size,
+                                                     compute_settings));
+    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads,
+                                     compute_settings);
   }
 
   template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
+  ABSL_DEPRECATED(
+      "Use CreateFromBaseOptions and configure model input from "
+      "tensorflow_lite_support/cc/task/core/proto/base_options.proto")
   static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromFile(
-      const string& file_name,
+      const std::string& file_name,
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-      int num_threads = 1) {
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+      int num_threads = 1,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings()) {
     auto engine = absl::make_unique<TfLiteEngine>(std::move(resolver));
-    RETURN_IF_ERROR(engine->BuildModelFromFile(file_name));
-    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads);
+    RETURN_IF_ERROR(engine->BuildModelFromFile(file_name, compute_settings));
+    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads,
+                                     compute_settings);
   }
 
   template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
+  ABSL_DEPRECATED(
+      "Use CreateFromBaseOptions and configure model input from "
+      "tensorflow_lite_support/cc/task/core/proto/base_options.proto")
   static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromFileDescriptor(
       int file_descriptor,
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-      int num_threads = 1) {
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+      int num_threads = 1,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings()) {
     auto engine = absl::make_unique<TfLiteEngine>(std::move(resolver));
-    RETURN_IF_ERROR(engine->BuildModelFromFileDescriptor(file_descriptor));
-    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads);
+    RETURN_IF_ERROR(engine->BuildModelFromFileDescriptor(file_descriptor,
+                                                         compute_settings));
+    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads,
+                                     compute_settings);
   }
 
   template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
-  static tflite::support::StatusOr<std::unique_ptr<T>>
-  CreateFromExternalFileProto(
-      const ExternalFile* external_file,
-      std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-      int num_threads = 1) {
+  ABSL_DEPRECATED(
+      "Use CreateFromBaseOptions and configure model input from "
+      "tensorflow_lite_support/cc/task/core/proto/base_options.proto")
+  static tflite::support::
+      StatusOr<std::unique_ptr<T>> CreateFromExternalFileProto(
+          const ExternalFile* external_file,
+          std::unique_ptr<tflite::OpResolver> resolver = absl::make_unique<
+              tflite_shims::ops::builtin::BuiltinOpResolver>(),
+          int num_threads = 1,
+          const tflite::proto::ComputeSettings& compute_settings =
+              tflite::proto::ComputeSettings()) {
     auto engine = absl::make_unique<TfLiteEngine>(std::move(resolver));
-    RETURN_IF_ERROR(engine->BuildModelFromExternalFileProto(external_file));
-    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads);
+    RETURN_IF_ERROR(engine->BuildModelFromExternalFileProto(external_file,
+                                                            compute_settings));
+    return CreateFromTfLiteEngine<T>(std::move(engine), num_threads,
+                                     compute_settings);
+  }
+
+  // Creates a Task API from the provided BaseOptions. A non-default
+  // OpResolver can be specified in order to support custom Ops or specify a
+  // subset of built-in Ops.
+  template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
+  static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromBaseOptions(
+      const BaseOptions* base_options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>()) {
+    if (!base_options->has_model_file()) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "Missing mandatory `model_file` field in `base_options`",
+          tflite::support::TfLiteSupportStatus::kInvalidArgumentError);
+    }
+
+    int num_threads = base_options->compute_settings()
+                          .tflite_settings()
+                          .cpu_settings()
+                          .num_threads();
+    if (num_threads == 0 || num_threads < -1) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "`num_threads` must be greater than 0 or equal to -1.",
+          tflite::support::TfLiteSupportStatus::kInvalidArgumentError);
+    }
+
+    auto engine = absl::make_unique<TfLiteEngine>(std::move(resolver));
+    RETURN_IF_ERROR(engine->BuildModelFromExternalFileProto(
+        &base_options->model_file(), base_options->compute_settings()));
+    return CreateFromTfLiteEngine<T>(std::move(engine),
+                                     base_options->compute_settings());
   }
 
  private:
   template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
   static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromTfLiteEngine(
       std::unique_ptr<TfLiteEngine> engine,
-      int num_threads) {
-    RETURN_IF_ERROR(engine->InitInterpreter(num_threads));
+      int num_threads,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings()) {
+    tflite::proto::ComputeSettings settings_copy =
+        tflite::proto::ComputeSettings(compute_settings);
+    settings_copy.mutable_tflite_settings()
+        ->mutable_cpu_settings()
+        ->set_num_threads(num_threads);
+    return CreateFromTfLiteEngine<T>(std::move(engine), settings_copy);
+  }
+
+  template <typename T, EnableIfBaseUntypedTaskApiSubclass<T> = nullptr>
+  static tflite::support::StatusOr<std::unique_ptr<T>> CreateFromTfLiteEngine(
+      std::unique_ptr<TfLiteEngine> engine,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings()) {
+    RETURN_IF_ERROR(engine->InitInterpreter(compute_settings));
     return absl::make_unique<T>(std::move(engine));
   }
 };
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.cc
index de733ae..e40c2ac 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.cc
@@ -17,7 +17,7 @@
 
 #include <fstream>
 
-#include "absl/strings/str_cat.h"
+#include "absl/strings/str_cat.h"  // from @com_google_absl
 
 namespace tflite {
 namespace task {
@@ -61,6 +61,22 @@
   return buffer;
 }
 
+int FindIndexByMetadataTensorName(
+    const flatbuffers::Vector<flatbuffers::Offset<TensorMetadata>>*
+        tensor_metadatas,
+    const std::string& name) {
+  if (tensor_metadatas == nullptr) {
+    return -1;
+  }
+  for (int i = 0; i < tensor_metadatas->size(); i++) {
+    if (strcmp(name.data(), tensor_metadatas->Get(i)->name()->c_str()) == 0) {
+      return i;
+    }
+  }
+  // Returns -1 if not found.
+  return -1;
+}
+
 }  // namespace core
 }  // namespace task
 }  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
index ced3dbc..7cde474 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/task_utils.h
@@ -21,119 +21,164 @@
 #include <numeric>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/strings/str_cat.h"
+#include "absl/memory/memory.h"       // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_cat.h"     // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
 #include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
 #include "tensorflow/lite/kernels/op_macros.h"
 #include "tensorflow/lite/string_util.h"
 #include "tensorflow/lite/type_to_tflitetype.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
 
 namespace tflite {
 namespace task {
 namespace core {
 
-// Checks if data type of tensor is T and returns the pointer casted to T if
-// applicable, returns nullptr if tensor type is not T.
-// See type_to_tflitetype.h for a mapping from plain C++ type to TfLiteType.
-template <typename T>
-T* TypedTensor(const TfLiteTensor* tensor_ptr) {
-  if (tensor_ptr->type == typeToTfLiteType<T>()) {
-    return reinterpret_cast<T*>(tensor_ptr->data.raw);
-  }
-  return nullptr;
-}
-
 // Checks and returns type of a tensor, fails if tensor type is not T.
 template <typename T>
-T* AssertAndReturnTypedTensor(const TfLiteTensor* tensor) {
-  if (T* v = TypedTensor<T>(tensor))
-    return v;
-  // TODO(b/150903834): throw exceptions instead
-  TF_LITE_ASSERT(tensor->data.raw);
-  TF_LITE_FATAL(absl::StrCat("Type mismatch for tensor ", tensor->name,
-                             ". Requested ",
-                             TfLiteTypeGetName(typeToTfLiteType<T>()), ", got ",
-                             TfLiteTypeGetName(tensor->type), ".")
-                    .c_str());
+tflite::support::StatusOr<T*> AssertAndReturnTypedTensor(
+    const TfLiteTensor* tensor) {
+  if (!tensor->data.raw) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrFormat("Tensor (%s) has no raw data.", tensor->name));
+  }
+
+  // Checks if data type of tensor is T and returns the pointer casted to T if
+  // applicable, returns nullptr if tensor type is not T.
+  // See type_to_tflitetype.h for a mapping from plain C++ type to TfLiteType.
+  if (tensor->type == typeToTfLiteType<T>()) {
+    return reinterpret_cast<T*>(tensor->data.raw);
+  }
+  return tflite::support::CreateStatusWithPayload(
+      absl::StatusCode::kInternal,
+      absl::StrFormat("Type mismatch for tensor %s. Required %d, got %d.",
+                      tensor->name, typeToTfLiteType<T>(), tensor->bytes));
 }
 
 // Populates tensor with array of data, fails if data type doesn't match tensor
 // type or has not the same number of elements.
-template <typename T>
-inline void PopulateTensor(const T* data,
-                           int num_elements,
-                           TfLiteTensor* tensor) {
-  T* v = AssertAndReturnTypedTensor<T>(tensor);
+// Note: std::negation is not used because it is from C++17, where the code will
+// be compiled using C++14 in OSS.
+template <
+    typename T,
+    typename = std::enable_if_t<std::is_same<T, std::string>::value == false>>
+inline absl::Status PopulateTensor(const T* data,
+                                   int num_elements,
+                                   TfLiteTensor* tensor) {
+  T* v;
+  ASSIGN_OR_RETURN(v, AssertAndReturnTypedTensor<T>(tensor));
   size_t bytes = num_elements * sizeof(T);
-  // TODO(b/150903834): throw exceptions instead
-  TF_LITE_ASSERT(tensor->bytes == bytes);
+  if (tensor->bytes != bytes) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrFormat("tensor->bytes (%d) != bytes (%d)", tensor->bytes,
+                        bytes));
+  }
   memcpy(v, data, bytes);
+  return absl::OkStatus();
 }
 
 // Populates tensor with vector of data, fails if data type doesn't match tensor
 // type or has not the same number of elements.
 template <typename T>
-inline void PopulateTensor(const std::vector<T>& data, TfLiteTensor* tensor) {
+inline absl::Status PopulateTensor(const std::vector<T>& data,
+                                   TfLiteTensor* tensor) {
   return PopulateTensor<T>(data.data(), data.size(), tensor);
 }
 
 template <>
-inline void PopulateTensor<std::string>(const std::vector<std::string>& data,
-                                        TfLiteTensor* tensor) {
+inline absl::Status PopulateTensor<std::string>(
+    const std::vector<std::string>& data,
+    TfLiteTensor* tensor) {
   if (tensor->type != kTfLiteString) {
-    TF_LITE_FATAL(absl::StrCat("Type mismatch for tensor ", tensor->name,
-                               ". Requested STRING, got ",
-                               TfLiteTypeGetName(tensor->type), ".")
-                      .c_str());
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrFormat("Type mismatch for tensor %s. Required STRING, got %d.",
+                        tensor->name, tensor->bytes));
   }
   tflite::DynamicBuffer input_buf;
   for (const auto& value : data) {
     input_buf.AddString(value.data(), value.length());
   }
   input_buf.WriteToTensorAsVector(tensor);
+  return absl::OkStatus();
 }
 
 // Populates tensor one data item, fails if data type doesn't match tensor
 // type.
 template <typename T>
-inline void PopulateTensor(const T& data, TfLiteTensor* tensor) {
-  T* v = AssertAndReturnTypedTensor<T>(tensor);
+inline absl::Status PopulateTensor(const T& data, TfLiteTensor* tensor) {
+  T* v;
+  ASSIGN_OR_RETURN(v, AssertAndReturnTypedTensor<T>(tensor));
   *v = data;
+  return absl::OkStatus();
 }
 
 template <>
-inline void PopulateTensor<std::string>(const std::string& data,
-                                        TfLiteTensor* tensor) {
+inline absl::Status PopulateTensor<std::string>(const std::string& data,
+                                                TfLiteTensor* tensor) {
   tflite::DynamicBuffer input_buf;
   input_buf.AddString(data.data(), data.length());
   input_buf.WriteToTensorAsVector(tensor);
+  return absl::OkStatus();
 }
 
 // Populates a vector from the tensor, fails if data type doesn't match tensor
 // type.
 template <typename T>
-inline void PopulateVector(const TfLiteTensor* tensor, std::vector<T>* data) {
-  AssertAndReturnTypedTensor<T>(tensor);
-  const T* results = GetTensorData<T>(tensor);
+inline absl::Status PopulateVector(const TfLiteTensor* tensor,
+                                   std::vector<T>* data) {
+  const T* v;
+  ASSIGN_OR_RETURN(v, AssertAndReturnTypedTensor<T>(tensor));
   size_t num = tensor->bytes / sizeof(tensor->type);
   data->reserve(num);
   for (size_t i = 0; i < num; i++) {
-    data->emplace_back(results[i]);
+    data->emplace_back(v[i]);
   }
+  return absl::OkStatus();
 }
 
 template <>
-inline void PopulateVector<std::string>(const TfLiteTensor* tensor,
-                                        std::vector<std::string>* data) {
-  AssertAndReturnTypedTensor<std::string>(tensor);
+inline absl::Status PopulateVector<std::string>(
+    const TfLiteTensor* tensor,
+    std::vector<std::string>* data) {
+  if (tensor->type != typeToTfLiteType<std::string>()) {
+    return absl::InvalidArgumentError("not of type string");
+  }
+
   int num = GetStringCount(tensor);
   data->reserve(num);
   for (int i = 0; i < num; i++) {
     const auto& strref = tflite::GetString(tensor, i);
     data->emplace_back(strref.str, strref.len);
   }
+  return absl::OkStatus();
+}
+
+// Populates vector to a repeated field.
+// Note: std::negation is not used because it is from C++17, where the code will
+// be compiled using C++14 in OSS.
+template <
+    class TRepeatedField,
+    class T = float,
+    typename = std::enable_if_t<std::is_same<T, std::string>::value == false>>
+inline absl::Status PopulateVectorToRepeated(const TfLiteTensor* tensor,
+                                             TRepeatedField* data) {
+  const T* v;
+  ASSIGN_OR_RETURN(v, AssertAndReturnTypedTensor<T>(tensor));
+  size_t num = tensor->bytes / sizeof(tensor->type);
+  data->Resize(num, T());
+  T* pdata = data->mutable_data();
+  for (size_t i = 0; i < num; i++) {
+    pdata[i] = v[i];
+  }
+  return absl::OkStatus();
 }
 
 // Returns the reversely sorted indices of a vector.
@@ -158,6 +203,14 @@
 // Loads binary content of a file into a string.
 std::string LoadBinaryContent(const char* filename);
 
+// Gets the index from a vector of tensors with name specified inside metadata.
+// The range of the return value should be [0, output_tensor_size). If not
+// found, returns -1.
+int FindIndexByMetadataTensorName(
+    const flatbuffers::Vector<flatbuffers::Offset<TensorMetadata>>*
+        tensor_metadatas,
+    const std::string& name);
+
 // Gets the tensor from a vector of tensors with name specified inside metadata.
 template <typename TensorType>
 static TensorType* FindTensorByName(
@@ -169,12 +222,8 @@
       tensor_metadatas->size() != tensors.size()) {
     return nullptr;
   }
-  for (flatbuffers::uoffset_t i = 0; i < tensor_metadatas->size(); i++) {
-    if (strcmp(name.data(), tensor_metadatas->Get(i)->name()->c_str()) == 0) {
-      return tensors[i];
-    }
-  }
-  return nullptr;
+  int i = FindIndexByMetadataTensorName(tensor_metadatas, name);
+  return i == -1 ? nullptr : tensors[i];
 }
 
 }  // namespace core
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
index 6230e5c..41e06389 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.cc
@@ -15,63 +15,37 @@
 
 #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
 
-#include "absl/strings/match.h"
-#include "absl/strings/str_cat.h"
+#include <memory>
+
+#include "absl/strings/match.h"    // from @com_google_absl
+#include "absl/strings/str_cat.h"  // from @com_google_absl
 #include "tensorflow/lite/builtin_ops.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
+#include "tensorflow/lite/core/shims/cc/tools/verifier.h"
 #include "tensorflow/lite/stderr_reporter.h"
-#include "tensorflow/lite/tools/verifier.h"
 #include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 
-#if TFLITE_USE_C_API
-#include "tensorflow/lite/c/c_api_experimental.h"
-#else
-#include "tensorflow/lite/kernels/register.h"
-#endif
-
 namespace tflite {
 namespace task {
 namespace core {
 
-#ifdef __ANDROID__
-// https://github.com/opencv/opencv/issues/14906
-// "ios_base::Init" object is not a part of Android's "iostream" header (in case
-// of clang toolchain, NDK 20).
-//
-// Ref1:
-// https://en.cppreference.com/w/cpp/io/ios_base/Init
-//       The header <iostream> behaves as if it defines (directly or indirectly)
-//       an instance of std::ios_base::Init with static storage duration
-//
-// Ref2:
-// https://github.com/gcc-mirror/gcc/blob/gcc-8-branch/libstdc%2B%2B-v3/include/std/iostream#L73-L74
-static std::ios_base::Init s_iostream_initializer;
-#endif
-
 using ::absl::StatusCode;
+using ::tflite::proto::ComputeSettings;
 using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::InterpreterCreationResources;
 using ::tflite::support::TfLiteSupportStatus;
 
-int TfLiteEngine::ErrorReporter::Report(const char* format, va_list args) {
-  return std::vsnprintf(error_message, sizeof(error_message), format, args);
-}
-
 bool TfLiteEngine::Verifier::Verify(const char* data,
                                     int length,
                                     tflite::ErrorReporter* reporter) {
-  return tflite::Verify(data, length, *op_resolver_, reporter);
+  return tflite_shims::Verify(data, length, reporter);
 }
 
-#if TFLITE_USE_C_API
 TfLiteEngine::TfLiteEngine(std::unique_ptr<tflite::OpResolver> resolver)
-    : model_(nullptr, TfLiteModelDelete),
-      resolver_(std::move(resolver)),
-      verifier_(resolver_.get()) {}
-#else
-TfLiteEngine::TfLiteEngine(std::unique_ptr<tflite::OpResolver> resolver)
-    : model_(), resolver_(std::move(resolver)), verifier_(resolver_.get()) {}
-#endif
+    : model_(), resolver_(std::move(resolver)), verifier_() {}
 
 std::vector<TfLiteTensor*> TfLiteEngine::GetInputs() {
   Interpreter* interpreter = this->interpreter();
@@ -95,46 +69,33 @@
   return tensors;
 }
 
-// The following function is adapted from the code in
-// tflite::FlatBufferModel::VerifyAndBuildFromBuffer.
-void TfLiteEngine::VerifyAndBuildModelFromBuffer(const char* buffer_data,
-                                                 size_t buffer_size) {
-#if TFLITE_USE_C_API
-  // First verify with the base flatbuffers verifier.
-  // This verifies that the model is a valid flatbuffer model.
-  flatbuffers::Verifier base_verifier(
-      reinterpret_cast<const uint8_t*>(buffer_data), buffer_size);
-  if (!VerifyModelBuffer(base_verifier)) {
-    TF_LITE_REPORT_ERROR(&error_reporter_,
-                         "The model is not a valid Flatbuffer buffer");
-    model_ = nullptr;
-    return;
-  }
-  // Next verify with the extra verifier.  This verifies that the model only
-  // uses operators supported by the OpResolver.
-  if (!verifier_.Verify(buffer_data, buffer_size, &error_reporter_)) {
-    model_ = nullptr;
-    return;
-  }
-  // Build the model.
-  model_.reset(TfLiteModelCreate(buffer_data, buffer_size));
-#else
-  model_ = tflite::FlatBufferModel::VerifyAndBuildFromBuffer(
-      buffer_data, buffer_size, &verifier_, &error_reporter_);
-#endif
+void TfLiteEngine::VerifyAndBuildModelFromBuffer(
+    const char* buffer_data,
+    size_t buffer_size,
+    TfLiteVerifier* extra_verifier) {
+  model_ = tflite_shims::FlatBufferModel::VerifyAndBuildFromBuffer(
+      buffer_data, buffer_size, extra_verifier, &error_reporter_);
 }
 
-absl::Status TfLiteEngine::InitializeFromModelFileHandler() {
+absl::Status TfLiteEngine::InitializeFromModelFileHandler(
+    const tflite::proto::ComputeSettings& compute_settings) {
   const char* buffer_data = model_file_handler_->GetFileContent().data();
   size_t buffer_size = model_file_handler_->GetFileContent().size();
-  VerifyAndBuildModelFromBuffer(buffer_data, buffer_size);
+  VerifyAndBuildModelFromBuffer(buffer_data, buffer_size, &verifier_);
   if (model_ == nullptr) {
+    static constexpr char kInvalidFlatbufferMessage[] =
+        "The model is not a valid Flatbuffer";
     // To be replaced with a proper switch-case when TF Lite model builder
     // returns a `TfLiteStatus` code capturing this type of error.
-    if (absl::StrContains(error_reporter_.error_message,
-                          "The model is not a valid Flatbuffer")) {
+    if (absl::StrContains(error_reporter_.message(),
+                          kInvalidFlatbufferMessage)) {
       return CreateStatusWithPayload(
-          StatusCode::kInvalidArgument, error_reporter_.error_message,
+          StatusCode::kInvalidArgument, error_reporter_.message(),
+          TfLiteSupportStatus::kInvalidFlatBufferError);
+    } else if (absl::StrContains(error_reporter_.message(),
+                                 "Error loading model from buffer")) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument, kInvalidFlatbufferMessage,
           TfLiteSupportStatus::kInvalidFlatBufferError);
     } else {
       // TODO(b/154917059): augment status with another `TfLiteStatus` code when
@@ -144,7 +105,7 @@
           StatusCode::kUnknown,
           absl::StrCat(
               "Could not build model from the provided pre-loaded flatbuffer: ",
-              error_reporter_.error_message));
+              error_reporter_.message()));
     }
   }
 
@@ -156,125 +117,125 @@
   return absl::OkStatus();
 }
 
-absl::Status TfLiteEngine::BuildModelFromFlatBuffer(const char* buffer_data,
-                                                    size_t buffer_size) {
+absl::Status TfLiteEngine::BuildModelFromFlatBuffer(
+    const char* buffer_data,
+    size_t buffer_size,
+    const tflite::proto::ComputeSettings& compute_settings) {
   if (model_) {
     return CreateStatusWithPayload(StatusCode::kInternal,
                                    "Model already built");
   }
-  external_file_.set_file_content(std::string(buffer_data, buffer_size));
+  external_file_ = std::make_unique<ExternalFile>();
+  external_file_->set_file_content(std::string(buffer_data, buffer_size));
   ASSIGN_OR_RETURN(
       model_file_handler_,
-      ExternalFileHandler::CreateFromExternalFile(&external_file_));
-  return InitializeFromModelFileHandler();
+      ExternalFileHandler::CreateFromExternalFile(external_file_.get()));
+  return InitializeFromModelFileHandler(compute_settings);
 }
 
-absl::Status TfLiteEngine::BuildModelFromFile(const std::string& file_name) {
+absl::Status TfLiteEngine::BuildModelFromFile(
+    const std::string& file_name,
+    const tflite::proto::ComputeSettings& compute_settings) {
   if (model_) {
     return CreateStatusWithPayload(StatusCode::kInternal,
                                    "Model already built");
   }
-  external_file_.set_file_name(file_name);
+  if (external_file_ == nullptr) {
+    external_file_ = std::make_unique<ExternalFile>();
+  }
+  external_file_->set_file_name(file_name);
   ASSIGN_OR_RETURN(
       model_file_handler_,
-      ExternalFileHandler::CreateFromExternalFile(&external_file_));
-  return InitializeFromModelFileHandler();
+      ExternalFileHandler::CreateFromExternalFile(external_file_.get()));
+  return InitializeFromModelFileHandler(compute_settings);
 }
 
-absl::Status TfLiteEngine::BuildModelFromFileDescriptor(int file_descriptor) {
+absl::Status TfLiteEngine::BuildModelFromFileDescriptor(
+    int file_descriptor,
+    const tflite::proto::ComputeSettings& compute_settings) {
   if (model_) {
     return CreateStatusWithPayload(StatusCode::kInternal,
                                    "Model already built");
   }
-  external_file_.mutable_file_descriptor_meta()->set_fd(file_descriptor);
+  if (external_file_ == nullptr) {
+    external_file_ = std::make_unique<ExternalFile>();
+  }
+  external_file_->mutable_file_descriptor_meta()->set_fd(file_descriptor);
   ASSIGN_OR_RETURN(
       model_file_handler_,
-      ExternalFileHandler::CreateFromExternalFile(&external_file_));
-  return InitializeFromModelFileHandler();
+      ExternalFileHandler::CreateFromExternalFile(external_file_.get()));
+  return InitializeFromModelFileHandler(compute_settings);
 }
 
 absl::Status TfLiteEngine::BuildModelFromExternalFileProto(
-    const ExternalFile* external_file) {
+    const ExternalFile* external_file,
+    const tflite::proto::ComputeSettings& compute_settings) {
   if (model_) {
     return CreateStatusWithPayload(StatusCode::kInternal,
                                    "Model already built");
   }
   ASSIGN_OR_RETURN(model_file_handler_,
                    ExternalFileHandler::CreateFromExternalFile(external_file));
-  return InitializeFromModelFileHandler();
+  return InitializeFromModelFileHandler(compute_settings);
+}
+
+absl::Status TfLiteEngine::BuildModelFromExternalFileProto(
+    std::unique_ptr<ExternalFile> external_file) {
+  if (model_) {
+    return CreateStatusWithPayload(StatusCode::kInternal,
+                                   "Model already built");
+  }
+  external_file_ = std::move(external_file);
+  ASSIGN_OR_RETURN(
+      model_file_handler_,
+      ExternalFileHandler::CreateFromExternalFile(external_file_.get()));
+  // Dummy proto. InitializeFromModelFileHandler doesn't use this proto.
+  tflite::proto::ComputeSettings compute_settings;
+  return InitializeFromModelFileHandler(compute_settings);
 }
 
 absl::Status TfLiteEngine::InitInterpreter(int num_threads) {
   tflite::proto::ComputeSettings compute_settings;
-  return InitInterpreter(compute_settings, num_threads);
+  compute_settings.mutable_tflite_settings()
+      ->mutable_cpu_settings()
+      ->set_num_threads(num_threads);
+  return InitInterpreter(compute_settings);
 }
 
-#if TFLITE_USE_C_API
-const TfLiteRegistration* FindBuiltinOp(void* user_data,
-                                        TfLiteBuiltinOperator builtin_op,
-                                        int version) {
-  OpResolver* op_resolver = reinterpret_cast<OpResolver*>(user_data);
-  tflite::BuiltinOperator op = static_cast<tflite::BuiltinOperator>(builtin_op);
-  return op_resolver->FindOp(op, version);
-}
-
-const TfLiteRegistration* FindCustomOp(void* user_data,
-                                       const char* custom_op,
-                                       int version) {
-  OpResolver* op_resolver = reinterpret_cast<OpResolver*>(user_data);
-  return op_resolver->FindOp(custom_op, version);
-}
-#endif
-
+// TODO(b/183798104): deprecate num_threads in VK task protos.
+// Deprecated. Use the following method, and configure `num_threads` through
+// `compute_settings`, i.e. in `CPUSettings`:
+// absl::Status TfLiteEngine::InitInterpreter(
+//    const tflite::proto::ComputeSettings& compute_settings)
 absl::Status TfLiteEngine::InitInterpreter(
     const tflite::proto::ComputeSettings& compute_settings,
     int num_threads) {
+  ComputeSettings settings_copy = ComputeSettings(compute_settings);
+  settings_copy.mutable_tflite_settings()
+      ->mutable_cpu_settings()
+      ->set_num_threads(num_threads);
+  return InitInterpreter(settings_copy);
+}
+
+absl::Status TfLiteEngine::InitInterpreter(
+    const tflite::proto::ComputeSettings& compute_settings) {
   if (model_ == nullptr) {
     return CreateStatusWithPayload(
         StatusCode::kInternal,
         "TF Lite FlatBufferModel is null. Please make sure to call one of the "
         "BuildModelFrom methods before calling InitInterpreter.");
   }
-#if TFLITE_USE_C_API
-  std::function<absl::Status(TfLiteDelegate*,
-                             std::unique_ptr<Interpreter, InterpreterDeleter>*)>
-      initializer =
-          [this, num_threads](
-              TfLiteDelegate* optional_delegate,
-              std::unique_ptr<Interpreter, InterpreterDeleter>* interpreter_out)
-      -> absl::Status {
-    std::unique_ptr<TfLiteInterpreterOptions,
-                    void (*)(TfLiteInterpreterOptions*)>
-        options{TfLiteInterpreterOptionsCreate(),
-                TfLiteInterpreterOptionsDelete};
-    TfLiteInterpreterOptionsSetOpResolver(options.get(), FindBuiltinOp,
-                                          FindCustomOp, resolver_.get());
-    TfLiteInterpreterOptionsSetNumThreads(options.get(), num_threads);
-    if (optional_delegate != nullptr) {
-      TfLiteInterpreterOptionsAddDelegate(options.get(), optional_delegate);
-    }
-    interpreter_out->reset(
-        TfLiteInterpreterCreateWithSelectedOps(model_.get(), options.get()));
-    if (*interpreter_out == nullptr) {
-      return CreateStatusWithPayload(
-          StatusCode::kAborted,
-          absl::StrCat("Could not build the TF Lite interpreter: "
-                       "TfLiteInterpreterCreateWithSelectedOps failed: ",
-                       error_reporter_.error_message));
-    }
-    return absl::OkStatus();
-  };
-#else
   auto initializer =
-      [this, num_threads](
-          std::unique_ptr<Interpreter, InterpreterDeleter>* interpreter_out)
+      [this](const InterpreterCreationResources& resources,
+             std::unique_ptr<Interpreter, InterpreterDeleter>* interpreter_out)
       -> absl::Status {
-    if (tflite::InterpreterBuilder(*model_, *resolver_)(
-            interpreter_out, num_threads) != kTfLiteOk) {
+    tflite_shims::InterpreterBuilder interpreter_builder(*model_, *resolver_);
+    resources.ApplyTo(&interpreter_builder);
+    if (interpreter_builder(interpreter_out) != kTfLiteOk) {
       return CreateStatusWithPayload(
           StatusCode::kUnknown,
           absl::StrCat("Could not build the TF Lite interpreter: ",
-                       error_reporter_.error_message));
+                       error_reporter_.message()));
     }
     if (*interpreter_out == nullptr) {
       return CreateStatusWithPayload(StatusCode::kInternal,
@@ -282,14 +243,24 @@
     }
     return absl::OkStatus();
   };
-#endif
 
   absl::Status status =
       interpreter_.InitializeWithFallback(initializer, compute_settings);
-
-  if (!status.ok() &&
-      !status.GetPayload(tflite::support::kTfLiteSupportPayload).has_value()) {
-    status = CreateStatusWithPayload(status.code(), status.message());
+  if (!status.ok()) {
+    if (absl::StrContains(error_reporter_.previous_message(),
+                          "Encountered unresolved custom op")) {
+      return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                     error_reporter_.previous_message(),
+                                     TfLiteSupportStatus::kUnsupportedCustomOp);
+    } else if (absl::StrContains(error_reporter_.previous_message(),
+                                 "Didn't find op for builtin opcode")) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument, error_reporter_.previous_message(),
+          TfLiteSupportStatus::kUnsupportedBuiltinOp);
+    } else if (!status.GetPayload(tflite::support::kTfLiteSupportPayload)
+                    .has_value()) {
+      return CreateStatusWithPayload(status.code(), status.message());
+    }
   }
   return status;
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
index bc55f6b0..0cbaa73 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/core/tflite_engine.h
@@ -18,31 +18,21 @@
 
 #include <memory>
 
-#include "absl/memory/memory.h"
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
-#include "tensorflow/lite/c/common.h"
+#include "absl/memory/memory.h"        // from @com_google_absl
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow/lite/core/api/op_resolver.h"
-#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/core/shims/c/common.h"
+#include "tensorflow/lite/core/shims/cc/interpreter.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
+#include "tensorflow/lite/core/shims/cc/model.h"
+#include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
 #include "tensorflow_lite_support/cc/port/tflite_wrapper.h"
+#include "tensorflow_lite_support/cc/task/core/error_reporter.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
 #include "tensorflow_lite_support/metadata/cc/metadata_extractor.h"
 
-// If compiled with -DTFLITE_USE_C_API, this file will use the TF Lite C API
-// rather than the TF Lite C++ API.
-// TODO(b/168025296): eliminate the '#if TFLITE_USE_C_API' directives here and
-// elsewhere and instead use the C API unconditionally, once we have a suitable
-// replacement for the features of tflite::support::TfLiteInterpreterWrapper.
-#if TFLITE_USE_C_API
-#include "tensorflow/lite/c/c_api.h"
-#include "tensorflow/lite/core/api/verifier.h"
-#include "tensorflow/lite/tools/verifier.h"
-#else
-#include "tensorflow/lite/interpreter.h"
-#include "tensorflow/lite/model.h"
-#endif
-
 namespace tflite {
 namespace task {
 namespace core {
@@ -52,77 +42,42 @@
 class TfLiteEngine {
  public:
   // Types.
-  using InterpreterWrapper = tflite::support::TfLiteInterpreterWrapper;
-#if TFLITE_USE_C_API
-  using Model = struct TfLiteModel;
-  using Interpreter = struct TfLiteInterpreter;
-  using ModelDeleter = void (*)(Model*);
-  using InterpreterDeleter = InterpreterWrapper::InterpreterDeleter;
-#else
-  using Model = tflite::FlatBufferModel;
-  using Interpreter = tflite::Interpreter;
+  using InterpreterWrapper = ::tflite::support::TfLiteInterpreterWrapper;
+  using Model = ::tflite_shims::FlatBufferModel;
+  using Interpreter = ::tflite_shims::Interpreter;
   using ModelDeleter = std::default_delete<Model>;
   using InterpreterDeleter = std::default_delete<Interpreter>;
-#endif
 
   // Constructors.
   explicit TfLiteEngine(
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
   // Model is neither copyable nor movable.
   TfLiteEngine(const TfLiteEngine&) = delete;
   TfLiteEngine& operator=(const TfLiteEngine&) = delete;
 
   // Accessors.
   static int32_t InputCount(const Interpreter* interpreter) {
-#if TFLITE_USE_C_API
-    return TfLiteInterpreterGetInputTensorCount(interpreter);
-#else
     return interpreter->inputs().size();
-#endif
   }
   static int32_t OutputCount(const Interpreter* interpreter) {
-#if TFLITE_USE_C_API
-    return TfLiteInterpreterGetOutputTensorCount(interpreter);
-#else
     return interpreter->outputs().size();
-#endif
   }
   static TfLiteTensor* GetInput(Interpreter* interpreter, int index) {
-#if TFLITE_USE_C_API
-    return TfLiteInterpreterGetInputTensor(interpreter, index);
-#else
     return interpreter->tensor(interpreter->inputs()[index]);
-#endif
   }
   // Same as above, but const.
   static const TfLiteTensor* GetInput(const Interpreter* interpreter,
                                       int index) {
-#if TFLITE_USE_C_API
-    return TfLiteInterpreterGetInputTensor(interpreter, index);
-#else
     return interpreter->tensor(interpreter->inputs()[index]);
-#endif
   }
   static TfLiteTensor* GetOutput(Interpreter* interpreter, int index) {
-#if TFLITE_USE_C_API
-    // We need a const_cast here, because the TF Lite C API only has a non-const
-    // version of GetOutputTensor (in part because C doesn't support overloading
-    // on const).
-    return const_cast<TfLiteTensor*>(
-        TfLiteInterpreterGetOutputTensor(interpreter, index));
-#else
     return interpreter->tensor(interpreter->outputs()[index]);
-#endif
   }
   // Same as above, but const.
   static const TfLiteTensor* GetOutput(const Interpreter* interpreter,
                                        int index) {
-#if TFLITE_USE_C_API
-    return TfLiteInterpreterGetOutputTensor(interpreter, index);
-#else
     return interpreter->tensor(interpreter->outputs()[index]);
-#endif
   }
 
   std::vector<TfLiteTensor*> GetInputs();
@@ -140,51 +95,61 @@
   // whose ownership remains with the caller, and which must outlive the current
   // object. This performs extra verification on the input data using
   // tflite::Verify.
-  absl::Status BuildModelFromFlatBuffer(const char* buffer_data,
-                                        size_t buffer_size);
+  absl::Status BuildModelFromFlatBuffer(
+      const char* buffer_data,
+      size_t buffer_size,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings());
 
   // Builds the TF Lite model from a given file.
-  absl::Status BuildModelFromFile(const std::string& file_name);
+  absl::Status BuildModelFromFile(
+      const std::string& file_name,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings());
 
   // Builds the TF Lite model from a given file descriptor using mmap(2).
-  absl::Status BuildModelFromFileDescriptor(int file_descriptor);
+  absl::Status BuildModelFromFileDescriptor(
+      int file_descriptor,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings());
 
   // Builds the TFLite model from the provided ExternalFile proto, which must
   // outlive the current object.
   absl::Status BuildModelFromExternalFileProto(
-      const ExternalFile* external_file);
+      const ExternalFile* external_file,
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings());
+
+  // Builds the TFLite model from the provided ExternalFile proto, and take
+  // ownership of ExternalFile proto.
+  absl::Status BuildModelFromExternalFileProto(
+      std::unique_ptr<ExternalFile> external_file);
 
   // Initializes interpreter with encapsulated model.
   // Note: setting num_threads to -1 has for effect to let TFLite runtime set
   // the value.
   absl::Status InitInterpreter(int num_threads = 1);
 
-  // Same as above, but allows specifying `compute_settings` for acceleration.
+  // Initializes interpreter with acceleration configurations.
+  absl::Status InitInterpreter(
+      const tflite::proto::ComputeSettings& compute_settings);
+
+  // Deprecated. Use the following method, and configure `num_threads` through
+  // `compute_settings`, i.e. in `CPUSettings`:
+  // absl::Status TfLiteEngine::InitInterpreter(
+  //    const tflite::proto::ComputeSettings& compute_settings)
   absl::Status InitInterpreter(
       const tflite::proto::ComputeSettings& compute_settings,
-      int num_threads = 1);
+      int num_threads);
 
   // Cancels the on-going `Invoke()` call if any and if possible. This method
   // can be called from a different thread than the one where `Invoke()` is
   // running.
-  void Cancel() {
-#if TFLITE_USE_C_API
-    // NOP.
-#else
-    interpreter_.Cancel();
-#endif
-  }
+  void Cancel() { interpreter_.Cancel(); }
 
  protected:
-  // TF Lite's DefaultErrorReporter() outputs to stderr. This one captures the
-  // error into a string so that it can be used to complement tensorflow::Status
+  // Custom error reporter capturing and printing to stderr low-level TF Lite
   // error messages.
-  struct ErrorReporter : public tflite::ErrorReporter {
-    // Last error message captured by this error reporter.
-    char error_message[256];
-    int Report(const char* format, va_list args) override;
-  };
-  // Custom error reporter capturing low-level TF Lite error messages.
   ErrorReporter error_reporter_;
 
  private:
@@ -192,13 +157,9 @@
   // the FlatBuffer data provided as input.
   class Verifier : public tflite::TfLiteVerifier {
    public:
-    explicit Verifier(const tflite::OpResolver* op_resolver)
-        : op_resolver_(op_resolver) {}
     bool Verify(const char* data,
                 int length,
                 tflite::ErrorReporter* reporter) override;
-    // The OpResolver to be used to build the TF Lite interpreter.
-    const tflite::OpResolver* op_resolver_;
   };
 
   // Verifies that the supplied buffer refers to a valid flatbuffer model,
@@ -206,13 +167,23 @@
   // that was passed to the TfLiteEngine constructor, and then builds
   // the model from the buffer and stores it in 'model_'.
   void VerifyAndBuildModelFromBuffer(const char* buffer_data,
-                                     size_t buffer_size);
+                                     size_t buffer_size,
+                                     TfLiteVerifier* extra_verifier = nullptr);
 
   // Gets the buffer from the file handler; verifies and builds the model
   // from the buffer; if successful, sets 'model_metadata_extractor_' to be
   // a TF Lite Metadata extractor for the model; and calculates an appropriate
   // return Status,
-  absl::Status InitializeFromModelFileHandler();
+  // TODO(b/192726981): Remove `compute_settings` as it's not in use.
+  absl::Status InitializeFromModelFileHandler(
+      const tflite::proto::ComputeSettings& compute_settings =
+          tflite::proto::ComputeSettings());
+
+  // ExternalFile and corresponding ExternalFileHandler for models loaded from
+  // disk or file descriptor.
+  // Make sure ExternalFile proto outlives the model and the interpreter.
+  std::unique_ptr<ExternalFile> external_file_;
+  std::unique_ptr<ExternalFileHandler> model_file_handler_;
 
   // TF Lite model and interpreter for actual inference.
   std::unique_ptr<Model, ModelDeleter> model_;
@@ -230,11 +201,6 @@
 
   // Extra verifier for FlatBuffer input data.
   Verifier verifier_;
-
-  // ExternalFile and corresponding ExternalFileHandler for models loaded from
-  // disk or file descriptor.
-  ExternalFile external_file_;
-  std::unique_ptr<ExternalFileHandler> model_file_handler_;
 };
 
 }  // namespace core
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/BUILD
new file mode 100644
index 0000000..c412dee
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/BUILD
@@ -0,0 +1,169 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library_with_tflite(
+    name = "processor",
+    srcs = ["processor.cc"],
+    hdrs = ["processor.h"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:common",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "image_preprocessor",
+    srcs = ["image_preprocessor.cc"],
+    hdrs = ["image_preprocessor.h"],
+    tflite_deps = [
+        ":processor",
+        "//tensorflow_lite_support/cc/task/vision/utils:image_tensor_specs",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "@com_google_absl//absl/memory",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "classification_postprocessor",
+    srcs = ["classification_postprocessor.cc"],
+    hdrs = ["classification_postprocessor.h"],
+    tflite_deps = [
+        ":processor",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:classification_head",
+        "//tensorflow_lite_support/cc/task/core:label_map_item",
+        "//tensorflow_lite_support/cc/task/core:score_calibration",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/processor/proto:class_cc_proto",
+        "//tensorflow_lite_support/cc/task/processor/proto:classification_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/processor/proto:classifications_cc_proto",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+        "@org_tensorflow//tensorflow/lite/c:c_api_types",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "embedding_postprocessor",
+    srcs = ["embedding_postprocessor.cc"],
+    hdrs = ["embedding_postprocessor.h"],
+    tflite_deps = [
+        ":processor",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/processor/proto:embedding_options_cc_proto",
+        "@com_google_absl//absl/status",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "audio_preprocessor",
+    srcs = ["audio_preprocessor.cc"],
+    hdrs = ["audio_preprocessor.h"],
+    tflite_deps = [
+        ":processor",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/audio/core:audio_buffer",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "regex_preprocessor",
+    srcs = ["regex_preprocessor.cc"],
+    hdrs = ["regex_preprocessor.h"],
+    tflite_deps = [
+        ":text_preprocessor_header",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/text/tokenizers:regex_tokenizer",
+        "@com_google_absl//absl/status",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "bert_preprocessor",
+    srcs = ["bert_preprocessor.cc"],
+    hdrs = ["bert_preprocessor.h"],
+    tflite_deps = [
+        ":text_preprocessor_header",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer_utils",
+        "//tensorflow_lite_support/cc/utils:common_utils",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "text_preprocessor_header",
+    hdrs = ["text_preprocessor.h"],
+    tflite_deps = [
+        ":processor",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:statusor",
+        "@com_google_absl//absl/status",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "text_preprocessor",
+    srcs = ["text_preprocessor.cc"],
+    hdrs = ["text_preprocessor.h"],
+    tflite_deps = [
+        ":processor",
+        ":bert_preprocessor",
+        ":regex_preprocessor",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "@com_google_absl//absl/status",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc
new file mode 100644
index 0000000..254d068
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.cc
@@ -0,0 +1,167 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/processor/audio_preprocessor.h"
+
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/core/audio_buffer.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+namespace {
+// Looks up AudioProperty from metadata. If no error occurs, the returned value
+// is guaranteed to be valid (not null).
+tflite::support::StatusOr<const AudioProperties*> GetAudioPropertiesSafe(
+    const TensorMetadata* tensor_metadata,
+    int input_index) {
+  if (tensor_metadata->content() == nullptr ||
+      tensor_metadata->content()->content_properties() == nullptr) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        "Missing audio format metadata in the model metadata.",
+        tflite::support::TfLiteSupportStatus::kMetadataNotFoundError);
+  }
+
+  ContentProperties type =
+      tensor_metadata->content()->content_properties_type();
+
+  if (type != ContentProperties_AudioProperties) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrCat("Expected AudioProperties for tensor ",
+                     tensor_metadata->name()
+                         ? tensor_metadata->name()->str()
+                         : absl::StrFormat("#%d", input_index),
+                     ", got ", EnumNameContentProperties(type), "."),
+        tflite::support::TfLiteSupportStatus::
+            kMetadataInvalidContentPropertiesError);
+  }
+
+  auto props =
+      tensor_metadata->content()->content_properties_as_AudioProperties();
+  if (props == nullptr) {
+    return support::CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrCat("Expected AudioProperties for tensor",
+                     tensor_metadata->name()
+                         ? tensor_metadata->name()->str()
+                         : absl::StrFormat("#%d", input_index),
+                     ", got nullptr"),
+        tflite::support::TfLiteSupportStatus::
+            kMetadataInvalidContentPropertiesError);
+  }
+  return props;
+}
+}  // namespace
+
+/* static */
+tflite::support::StatusOr<std::unique_ptr<AudioPreprocessor>>
+AudioPreprocessor::Create(tflite::task::core::TfLiteEngine* engine,
+                          const std::initializer_list<int> input_indices) {
+  ASSIGN_OR_RETURN(auto processor,
+                   Processor::Create<AudioPreprocessor>(
+                       /* num_expected_tensors = */ 1, engine, input_indices));
+
+  RETURN_IF_ERROR(processor->Init());
+  return processor;
+}
+
+absl::Status AudioPreprocessor::Init() {
+  RETURN_IF_ERROR(SetAudioFormatFromMetadata());
+  RETURN_IF_ERROR(CheckAndSetInputs());
+  return absl::OkStatus();
+}
+
+absl::Status AudioPreprocessor::SetAudioFormatFromMetadata() {
+  ASSIGN_OR_RETURN(
+      const AudioProperties* props,
+      GetAudioPropertiesSafe(GetTensorMetadata(), tensor_indices_.at(0)));
+  audio_format_.channels = props->channels();
+  audio_format_.sample_rate = props->sample_rate();
+  if (audio_format_.channels <= 0 || audio_format_.sample_rate <= 0) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "Missing audio format metadata in the model.",
+        tflite::support::TfLiteSupportStatus::kMetadataNotFoundError);
+  }
+
+  return absl::OkStatus();
+}
+
+absl::Status AudioPreprocessor::CheckAndSetInputs() {
+  input_buffer_size_ = 1;
+  for (int i = 0; i < GetTensor()->dims->size; i++) {
+    if (GetTensor()->dims->data[i] < 1) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          absl::StrFormat("Invalid size: %d for input tensor dimension: %d.",
+                          GetTensor()->dims->data[i], i),
+          tflite::support::TfLiteSupportStatus::
+              kInvalidInputTensorDimensionsError);
+    }
+    input_buffer_size_ *= GetTensor()->dims->data[i];
+  }
+  // Check if the input buffer size is divisible by the required audio channels.
+  // This needs to be done after loading metadata and input.
+  if (input_buffer_size_ % audio_format_.channels != 0) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrFormat("Model input tensor size (%d) should be a "
+                        "multiplier of the number of channels (%d).",
+                        input_buffer_size_, audio_format_.channels),
+        tflite::support::TfLiteSupportStatus::kMetadataInconsistencyError);
+  }
+  return absl::OkStatus();
+}
+
+absl::Status AudioPreprocessor::Preprocess(
+    const ::tflite::task::audio::AudioBuffer& audio_buffer) {
+  if (audio_buffer.GetAudioFormat().channels != audio_format_.channels) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("Input audio buffer channel number %d does not match "
+                        "the model required audio channel number %d.",
+                        audio_buffer.GetAudioFormat().channels,
+                        audio_format_.channels));
+  }
+  if (audio_buffer.GetAudioFormat().sample_rate != audio_format_.sample_rate) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("Input audio sample rate %d does not match "
+                        "the model required audio sample rate %d.",
+                        audio_buffer.GetAudioFormat().sample_rate,
+                        audio_format_.sample_rate));
+  }
+  if (audio_buffer.GetBufferSize() != input_buffer_size_) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat(
+            "Input audio buffer size %d does not match the model required "
+            "input size %d.",
+            audio_buffer.GetBufferSize(), input_buffer_size_),
+        tflite::support::TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return tflite::task::core::PopulateTensor(audio_buffer.GetFloatBuffer(),
+                                            input_buffer_size_, GetTensor());
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.h
new file mode 100644
index 0000000..7cc337b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/audio_preprocessor.h
@@ -0,0 +1,79 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_AUDIO_PREPROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_AUDIO_PREPROCESSOR_H_
+
+#include <initializer_list>
+
+#include "absl/memory/memory.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/core/audio_buffer.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/processor/processor.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// Processes input audio and populates the associate input tensor.
+// Requirement for the input tensor:
+//
+// Input tensor:
+//   (kTfLiteFloat32)
+//    - input audio buffer of size `[batch * samples]`.
+//    - batch inference is not supported (`batch` is required to be 1).
+//    - for multi-channel models, the channels need be interleaved.
+class AudioPreprocessor : public Preprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<AudioPreprocessor>> Create(
+      tflite::task::core::TfLiteEngine* engine,
+      const std::initializer_list<int> input_indices);
+
+  // Processes the provided AudioBuffer and populates tensor values.
+  //
+  // The input `audio_buffer` are the raw buffer captured by the required format
+  // which can retrieved by GetRequiredAudioFormat().
+  ::absl::Status Preprocess(
+      const tflite::task::audio::AudioBuffer& audio_buffer);
+
+  // Returns the required input audio format if it is set. Otherwise, returns
+  // kMetadataNotFoundError.
+  tflite::task::audio::AudioBuffer::AudioFormat GetRequiredAudioFormat() {
+    return audio_format_;
+  }
+
+  // Returns the required input buffer size in number of float elements.
+  int GetRequiredInputBufferSize() { return input_buffer_size_; }
+
+ private:
+  using Preprocessor::Preprocessor;
+
+  ::absl::Status Init();
+  ::absl::Status SetAudioFormatFromMetadata();
+  ::absl::Status CheckAndSetInputs();
+
+  // Expected input audio format by the model.
+  tflite::task::audio::AudioBuffer::AudioFormat audio_format_;
+
+  // Expected input audio buffer size in number of float elements.
+  int input_buffer_size_;
+};
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_AUDIO_PREPROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/bert_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/bert_preprocessor.cc
new file mode 100644
index 0000000..96c5e0d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/bert_preprocessor.cc
@@ -0,0 +1,157 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/processor/bert_preprocessor.h"
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/strings/ascii.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h"
+#include "tensorflow_lite_support/cc/utils/common_utils.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+using ::absl::StatusCode;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::support::text::tokenizer::CreateTokenizerFromProcessUnit;
+using ::tflite::support::text::tokenizer::TokenizerResult;
+using ::tflite::task::core::FindIndexByMetadataTensorName;
+using ::tflite::task::core::PopulateTensor;
+
+constexpr int kTokenizerProcessUnitIndex = 0;
+constexpr char kIdsTensorName[] = "ids";
+constexpr char kMaskTensorName[] = "mask";
+constexpr char kSegmentIdsTensorName[] = "segment_ids";
+constexpr char kClassificationToken[] = "[CLS]";
+constexpr char kSeparator[] = "[SEP]";
+
+/* static */
+StatusOr<std::unique_ptr<BertPreprocessor>> BertPreprocessor::Create(
+    tflite::task::core::TfLiteEngine* engine,
+    const std::initializer_list<int> input_tensor_indices) {
+  ASSIGN_OR_RETURN(auto processor, Processor::Create<BertPreprocessor>(
+                                       /* num_expected_tensors = */ 3, engine,
+                                       input_tensor_indices,
+                                       /* requires_metadata = */ false));
+  RETURN_IF_ERROR(processor->Init());
+  return processor;
+}
+
+absl::Status BertPreprocessor::Init() {
+  // Try if RegexTokenzier can be found.
+  // BertTokenzier is packed in the processing unit of the InputTensors in
+  // SubgraphMetadata.
+  const tflite::ProcessUnit* tokenzier_metadata =
+      GetMetadataExtractor()->GetInputProcessUnit(kTokenizerProcessUnitIndex);
+  // Identify the tensor index for three Bert input tensors.
+  auto tensors_metadata = GetMetadataExtractor()->GetInputTensorMetadata();
+  int ids_tensor_index =
+      FindIndexByMetadataTensorName(tensors_metadata, kIdsTensorName);
+  ids_tensor_index_ =
+      ids_tensor_index == -1 ? tensor_indices_[0] : ids_tensor_index;
+  int mask_tensor_index =
+      FindIndexByMetadataTensorName(tensors_metadata, kMaskTensorName);
+  mask_tensor_index_ =
+      mask_tensor_index == -1 ? tensor_indices_[1] : mask_tensor_index;
+  int segment_ids_tensor_index =
+      FindIndexByMetadataTensorName(tensors_metadata, kSegmentIdsTensorName);
+  segment_ids_tensor_index_ = segment_ids_tensor_index == -1
+                                  ? tensor_indices_[2]
+                                  : segment_ids_tensor_index;
+
+  if (GetLastDimSize(ids_tensor_index_) != GetLastDimSize(mask_tensor_index_) ||
+      GetLastDimSize(ids_tensor_index_) !=
+          GetLastDimSize(segment_ids_tensor_index_)) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrFormat("The three input tensors in Bert models are "
+                        "expected to have same length, but got ids_tensor "
+                        "(%d), mask_tensor (%d), segment_ids_tensor (%d).",
+                        GetLastDimSize(ids_tensor_index_),
+                        GetLastDimSize(mask_tensor_index_),
+                        GetLastDimSize(segment_ids_tensor_index_)),
+        TfLiteSupportStatus::kInvalidNumOutputTensorsError);
+  }
+  bert_max_seq_len_ = GetLastDimSize(ids_tensor_index_);
+
+  ASSIGN_OR_RETURN(tokenizer_, CreateTokenizerFromProcessUnit(
+                                   tokenzier_metadata, GetMetadataExtractor()));
+  return absl::OkStatus();
+}
+
+absl::Status BertPreprocessor::Preprocess(const std::string& input_text) {
+  auto* ids_tensor =
+      engine_->GetInput(engine_->interpreter(), ids_tensor_index_);
+  auto* mask_tensor =
+      engine_->GetInput(engine_->interpreter(), mask_tensor_index_);
+  auto* segment_ids_tensor =
+      engine_->GetInput(engine_->interpreter(), segment_ids_tensor_index_);
+
+  std::string processed_input = input_text;
+  absl::AsciiStrToLower(&processed_input);
+
+  TokenizerResult input_tokenize_results;
+  input_tokenize_results = tokenizer_->Tokenize(processed_input);
+
+  // 2 accounts for [CLS], [SEP]
+  absl::Span<const std::string> query_tokens =
+      absl::MakeSpan(input_tokenize_results.subwords.data(),
+                     input_tokenize_results.subwords.data() +
+                         std::min(static_cast<size_t>(bert_max_seq_len_ - 2),
+                                  input_tokenize_results.subwords.size()));
+
+  std::vector<std::string> tokens;
+  tokens.reserve(2 + query_tokens.size());
+  // Start of generating the features.
+  tokens.push_back(kClassificationToken);
+  // For query input.
+  for (const auto& query_token : query_tokens) {
+    tokens.push_back(query_token);
+  }
+  // For Separation.
+  tokens.push_back(kSeparator);
+
+  std::vector<int> input_ids(bert_max_seq_len_, 0);
+  std::vector<int> input_mask(bert_max_seq_len_, 0);
+  // Convert tokens back into ids and set mask
+  for (int i = 0; i < tokens.size(); ++i) {
+    tokenizer_->LookupId(tokens[i], &input_ids[i]);
+    input_mask[i] = 1;
+  }
+  //                           |<--------bert_max_seq_len_--------->|
+  // input_ids                 [CLS] s1  s2...  sn [SEP]  0  0...  0
+  // input_masks                 1    1   1...  1    1    0  0...  0
+  // segment_ids                 0    0   0...  0    0    0  0...  0
+
+  RETURN_IF_ERROR(PopulateTensor(input_ids, ids_tensor));
+  RETURN_IF_ERROR(PopulateTensor(input_mask, mask_tensor));
+  RETURN_IF_ERROR(PopulateTensor(std::vector<int>(bert_max_seq_len_, 0),
+                                 segment_ids_tensor));
+  return absl::OkStatus();
+}
+
+int BertPreprocessor::GetLastDimSize(int tensor_index) {
+  auto tensor = engine_->GetInput(engine_->interpreter(), tensor_index);
+  return tensor->dims->data[tensor->dims->size - 1];
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/bert_preprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/bert_preprocessor.h
new file mode 100644
index 0000000..85bba20
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/bert_preprocessor.h
@@ -0,0 +1,59 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_BERT_PREPROCESOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_BERT_PREPROCESOR_H_
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/processor/text_preprocessor.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// Processes input text and populates the associated bert input tensors.
+// Requirements for the input tensors:
+//   - The 3 input tensors should be populated with the metadata tensor names,
+//   "ids", "mask", and "segment_ids", respectively.
+//   - The input_process_units metadata should contain WordPiece or
+//   Sentencepiece Tokenizer metadata.
+class BertPreprocessor : public TextPreprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<BertPreprocessor>> Create(
+      tflite::task::core::TfLiteEngine* engine,
+      const std::initializer_list<int> input_tensor_indices);
+
+  absl::Status Preprocess(const std::string& text);
+
+ private:
+  using TextPreprocessor::TextPreprocessor;
+
+  absl::Status Init();
+
+  int GetLastDimSize(int tensor_index);
+
+  std::unique_ptr<tflite::support::text::tokenizer::Tokenizer> tokenizer_;
+  int ids_tensor_index_;
+  int mask_tensor_index_;
+  int segment_ids_tensor_index_;
+  int bert_max_seq_len_;
+};
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_BERT_PREPROCESOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc
new file mode 100644
index 0000000..6396200
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.cc
@@ -0,0 +1,222 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/processor/classification_postprocessor.h"
+
+#include <memory>
+
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow/lite/c/c_api_types.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+namespace {
+
+using ::absl::StatusCode;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::core::BuildClassificationHead;
+using ::tflite::task::core::LabelMapItem;
+using ::tflite::task::core::ScoreCalibration;
+
+}  // namespace
+
+/* static */
+tflite::support::StatusOr<std::unique_ptr<ClassificationPostprocessor>>
+ClassificationPostprocessor::Create(
+    core::TfLiteEngine* engine,
+    const std::initializer_list<int> output_indices,
+    std::unique_ptr<ClassificationOptions> options) {
+  ASSIGN_OR_RETURN(auto processor,
+                   Processor::Create<ClassificationPostprocessor>(
+                       /* num_expected_tensors = */ 1, engine, output_indices));
+
+  RETURN_IF_ERROR(processor->Init(std::move(options)));
+  return processor;
+}
+
+absl::Status ClassificationPostprocessor::Init(
+    std::unique_ptr<ClassificationOptions> options) {
+  // Sanity check options
+  if (options->max_results() == 0) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        "Invalid `max_results` option: value must be != 0",
+        TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  if (options->class_name_allowlist_size() > 0 &&
+      options->class_name_denylist_size() > 0) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        "`class_name_allowlist` and `class_name_denylist` are mutually "
+        "exclusive options.",
+        TfLiteSupportStatus::kInvalidArgumentError);
+  }
+
+  ASSIGN_OR_RETURN(classification_head_,
+                   BuildClassificationHead(*engine_->metadata_extractor(),
+                                           *GetTensorMetadata(),
+                                           options->display_names_locale()));
+
+  // Sanity check output tensors
+  const TfLiteTensor* output_tensor = GetTensor();
+  const int num_dimensions = output_tensor->dims->size;
+  if (num_dimensions == 4) {
+    if (output_tensor->dims->data[1] != 1 ||
+        output_tensor->dims->data[2] != 1) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat("Unexpected WxH sizes for output index %d: got "
+                          "%dx%d, expected 1x1.",
+                          tensor_indices_.at(0), output_tensor->dims->data[2],
+                          output_tensor->dims->data[1]),
+          TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+    }
+  } else if (num_dimensions != 2) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat(
+            "Unexpected number of dimensions for output index %d: got %dD, "
+            "expected either 2D (BxN with B=1) or 4D (BxHxWxN with B=1, W=1, "
+            "H=1).",
+            tensor_indices_.at(0), num_dimensions),
+        TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+  }
+  if (output_tensor->dims->data[0] != 1) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("The output array is expected to have a batch size "
+                        "of 1. Got %d for output index %d.",
+                        output_tensor->dims->data[0], tensor_indices_.at(0)),
+        TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+  }
+  int num_classes = output_tensor->dims->data[num_dimensions - 1];
+  // If label map is not set, build a default one based on model
+  // introspection. This happens if a model with partial or no metadata was
+  // provided through the `model_file_with_metadata` options field.
+  if (classification_head_.label_map_items.empty()) {
+    classification_head_.label_map_items.reserve(num_classes);
+    for (int class_index = 0; class_index < num_classes; ++class_index) {
+      classification_head_.label_map_items.emplace_back(LabelMapItem{});
+    }
+  }
+  int num_label_map_items = classification_head_.label_map_items.size();
+  if (num_classes != num_label_map_items) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Got %d class(es) for output index %d, expected %d "
+                        "according to the label map.",
+                        output_tensor->dims->data[num_dimensions - 1],
+                        tensor_indices_.at(0), num_label_map_items),
+        TfLiteSupportStatus::kMetadataInconsistencyError);
+  }
+  if (output_tensor->type != kTfLiteUInt8 &&
+      output_tensor->type != kTfLiteFloat32) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Type mismatch for output tensor %s. Requested one "
+                        "of these types: "
+                        "kTfLiteUint8/kTfLiteFloat32, got %s.",
+                        output_tensor->name,
+                        TfLiteTypeGetName(output_tensor->type)),
+        TfLiteSupportStatus::kInvalidOutputTensorTypeError);
+  }
+
+  // Set class name set
+  if (options->class_name_denylist_size() != 0 ||
+      options->class_name_allowlist_size() != 0) {
+    // Before processing class names allowlist or denylist from the input
+    // options create a set with _all_ known class names from the label map(s).
+    absl::flat_hash_set<std::string> head_class_names;
+    for (const auto& item : classification_head_.label_map_items) {
+      if (!item.name.empty()) {
+        head_class_names.insert(item.name);
+      }
+    }
+
+    if (head_class_names.empty()) {
+      std::string name = classification_head_.name;
+      if (name.empty()) {
+        name = absl::StrFormat("#%d", tensor_indices_.at(0));
+      }
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat(
+              "Using `class_name_allowlist` or `class_name_denylist` "
+              "requires labels to be present but none was found for "
+              "classification head: %s",
+              name),
+          TfLiteSupportStatus::kMetadataMissingLabelsError);
+    }
+
+    class_name_set_.is_allowlist = options->class_name_allowlist_size() > 0;
+    const auto& class_names = class_name_set_.is_allowlist
+                                  ? options->class_name_allowlist()
+                                  : options->class_name_denylist();
+
+    // Note: duplicate or unknown classes are just ignored.
+    class_name_set_.values.clear();
+    for (const auto& class_name : class_names) {
+      if (!head_class_names.contains(class_name)) {
+        continue;
+      }
+      class_name_set_.values.insert(class_name);
+    }
+
+    if (class_name_set_.values.empty()) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat(
+              "Invalid class names specified via `class_name_%s`: none match "
+              "with model labels.",
+              class_name_set_.is_allowlist ? "allowlsit" : "denylist"),
+          TfLiteSupportStatus::kInvalidArgumentError);
+    }
+  }
+
+  // Set score calibration
+  if (classification_head_.calibration_params.has_value()) {
+    score_calibration_ = absl::make_unique<ScoreCalibration>();
+    if (score_calibration_ == nullptr) {
+      return CreateStatusWithPayload(
+          StatusCode::kInternal, "Could not create score calibration object.");
+    }
+
+    RETURN_IF_ERROR(score_calibration_->InitializeFromParameters(
+        classification_head_.calibration_params.value()));
+  }
+
+  num_results_ =
+      options->max_results() >= 0
+          ? std::min(
+                static_cast<int>(classification_head_.label_map_items.size()),
+                options->max_results())
+          : classification_head_.label_map_items.size();
+  score_threshold_ = options->has_score_threshold()
+                         ? options->score_threshold()
+                         : classification_head_.score_threshold;
+
+  return absl::OkStatus();
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.h
new file mode 100644
index 0000000..517974c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/classification_postprocessor.h
@@ -0,0 +1,230 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_CLASSIFICATION_POSTPROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_CLASSIFICATION_POSTPROCESSOR_H_
+
+#include <initializer_list>
+
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/classification_head.h"
+#include "tensorflow_lite_support/cc/task/core/label_map_item.h"
+#include "tensorflow_lite_support/cc/task/core/score_calibration.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/processor/processor.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/class.pb.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/classification_options.pb.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/classifications.pb.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// This Postprocessor expects one output tensor with:
+//   (kTfLiteUInt8/kTfLiteFloat32)
+//    -  `N `classes and either 2 or 4 dimensions, i.e. `[1 x N]` or
+//       `[1 x 1 x 1 x N]`
+//    - optional (but recommended) label map(s) as AssociatedFile-s with type
+//      TENSOR_AXIS_LABELS, containing one label per line. The first such
+//      AssociatedFile (if any) is used to fill the `class_name` field of the
+//      results. The `display_name` field is filled from the AssociatedFile (if
+//      any) whose locale matches the `display_names_locale` field of the
+//      `ImageClassifierOptions` used at creation time ("en" by default, i.e.
+//      English). If none of these are available, only the `index` field of the
+//      results will be filled.
+class ClassificationPostprocessor : public Postprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<ClassificationPostprocessor>>
+  Create(core::TfLiteEngine* engine,
+         const std::initializer_list<int> output_indices,
+         std::unique_ptr<ClassificationOptions> options);
+
+  // Convert the tensor output to classification class.
+  // Note that this method doesn't add head_name for backward compatibility.
+  // Head name can be retrieved by `GetHeadName` method.
+  template <typename T>
+  absl::Status Postprocess(T* classifications);
+
+  const std::string GetHeadName() const { return classification_head_.name; }
+
+ private:
+  using Postprocessor::Postprocessor;
+
+  absl::Status Init(std::unique_ptr<ClassificationOptions> options);
+  // Given a ClassificationResult object containing class indices, fills the
+  // name and display name from the label map(s).
+  template <typename T>
+  absl::Status FillResultsFromLabelMaps(T* classifications);
+
+  // The list of classification heads associated with the corresponding output
+  // tensors. Built from TFLite Model Metadata.
+  ::tflite::task::core::ClassificationHead classification_head_{};
+
+  // Set of allowlisted or denylisted class names.
+  struct ClassNameSet {
+    absl::flat_hash_set<std::string> values;
+    bool is_allowlist;
+  };
+
+  // Allowlisted or denylisted class names based on provided options at
+  // construction time. These are used to filter out results during
+  // post-processing.
+  ClassNameSet class_name_set_;
+
+  // Score calibration parameters, if any. Built from TFLite Model
+  // Metadata.
+  std::unique_ptr<core::ScoreCalibration> score_calibration_;
+
+  // Number of classes returned by `Postprocess` method.
+  int num_results_;
+
+  // Recommended score threshold typically in [0,1[. Classification results with
+  // a score below this value are considered low-confidence and should be
+  // rejected from returned results.
+  float score_threshold_;
+};
+
+template <typename T>
+absl::Status ClassificationPostprocessor::Postprocess(T* classifications) {
+  const auto& head = classification_head_;
+  classifications->set_head_index(tensor_indices_.at(0));
+
+  std::vector<std::pair<int, float>> score_pairs;
+  score_pairs.reserve(head.label_map_items.size());
+
+  const TfLiteTensor* output_tensor = GetTensor();
+  if (output_tensor->type == kTfLiteUInt8) {
+    ASSIGN_OR_RETURN(const uint8* output_data,
+                     core::AssertAndReturnTypedTensor<uint8>(output_tensor));
+    for (int j = 0; j < head.label_map_items.size(); ++j) {
+      score_pairs.emplace_back(
+          j, output_tensor->params.scale * (static_cast<int>(output_data[j]) -
+                                            output_tensor->params.zero_point));
+    }
+  } else {
+    ASSIGN_OR_RETURN(const float* output_data,
+                     core::AssertAndReturnTypedTensor<float>(output_tensor));
+    for (int j = 0; j < head.label_map_items.size(); ++j) {
+      score_pairs.emplace_back(j, output_data[j]);
+    }
+  }
+
+  // Optional score calibration.
+  if (score_calibration_ != nullptr) {
+    for (auto& score_pair : score_pairs) {
+      const std::string& class_name =
+          head.label_map_items[score_pair.first].name;
+
+      // In ComputeCalibratedScore, score_pair.second is set to the
+      // default_score value from metadata [1] if the category (1) has no
+      // score calibration data or (2) has a very low confident uncalibrated
+      // score, i.e. lower than the `min_uncalibrated_score` threshold.
+      // Otherwise, score_pair.second is calculated based on the selected
+      // score transformation function, and the value is guaranteed to be in
+      // the range of [0, scale], where scale is a label-dependent sigmoid
+      // parameter.
+      //
+      // [1]:
+      // https://github.com/tensorflow/tflite-support/blob/af26cb6952ccdeee0e849df2b93dbe7e57f6bc48/tensorflow_lite_support/metadata/metadata_schema.fbs#L453
+      score_pair.second = score_calibration_->ComputeCalibratedScore(
+          class_name, score_pair.second);
+    }
+  }
+
+  if (class_name_set_.values.empty()) {
+    // Partially sort in descending order (higher score is better).
+    absl::c_partial_sort(
+        score_pairs, score_pairs.begin() + num_results_,
+        [](const std::pair<int, float>& a, const std::pair<int, float>& b) {
+          return a.second > b.second;
+        });
+
+    for (int j = 0; j < num_results_; ++j) {
+      float score = score_pairs[j].second;
+      if (score < score_threshold_) {
+        break;
+      }
+      auto* cl = classifications->add_classes();
+      cl->set_index(score_pairs[j].first);
+      cl->set_score(score);
+    }
+  } else {
+    // Sort in descending order (higher score is better).
+    absl::c_sort(score_pairs, [](const std::pair<int, float>& a,
+                                 const std::pair<int, float>& b) {
+      return a.second > b.second;
+    });
+
+    for (int j = 0; j < head.label_map_items.size(); ++j) {
+      float score = score_pairs[j].second;
+      if (score < score_threshold_ ||
+          classifications->classes_size() >= num_results_) {
+        break;
+      }
+
+      const int class_index = score_pairs[j].first;
+      const std::string& class_name = head.label_map_items[class_index].name;
+
+      bool class_name_found = class_name_set_.values.contains(class_name);
+
+      if ((!class_name_found && class_name_set_.is_allowlist) ||
+          (class_name_found && !class_name_set_.is_allowlist)) {
+        continue;
+      }
+
+      auto* cl = classifications->add_classes();
+      cl->set_index(class_index);
+      cl->set_score(score);
+    }
+  }
+  return FillResultsFromLabelMaps(classifications);
+}
+
+template <typename T>
+absl::Status ClassificationPostprocessor::FillResultsFromLabelMaps(
+    T* classifications) {
+  int head_index = classifications->head_index();
+  const auto& label_map_items = classification_head_.label_map_items;
+  for (int j = 0; j < classifications->classes_size(); ++j) {
+    auto* current_class = classifications->mutable_classes(j);
+    int current_class_index = current_class->index();
+    if (current_class_index < 0 ||
+        current_class_index >= label_map_items.size()) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          absl::StrFormat("Invalid class index (%d) with respect to label "
+                          "map size (%d) for head #%d.",
+                          current_class_index, label_map_items.size(),
+                          head_index),
+          support::TfLiteSupportStatus::kMetadataInconsistencyError);
+    }
+    const std::string& name = label_map_items[current_class_index].name;
+    if (!name.empty()) {
+      current_class->set_class_name(name);
+    }
+    const std::string& display_name =
+        label_map_items[current_class_index].display_name;
+    if (!display_name.empty()) {
+      current_class->set_display_name(display_name);
+    }
+  }
+  return absl::OkStatus();
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_CLASSIFICATION_POSTPROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.cc
new file mode 100644
index 0000000..83b123f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.cc
@@ -0,0 +1,90 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+/* static */
+tflite::support::StatusOr<std::unique_ptr<EmbeddingPostprocessor>>
+EmbeddingPostprocessor::Create(core::TfLiteEngine* engine,
+                               const std::initializer_list<int> output_indices,
+                               std::unique_ptr<EmbeddingOptions> options) {
+  ASSIGN_OR_RETURN(auto processor,
+                   Processor::Create<EmbeddingPostprocessor>(
+                       /* num_expected_tensors = */ 1, engine, output_indices,
+                       /* requires_metadata = */ false));
+
+  RETURN_IF_ERROR(processor->Init(std::move(options)));
+  return processor;
+}
+
+absl::Status EmbeddingPostprocessor::Init(
+    std::unique_ptr<EmbeddingOptions> options) {
+  options_ = std::move(options);
+
+  int output_index = tensor_indices_.at(0);
+  auto* output_tensor = GetTensor();
+  int num_dimensions = output_tensor->dims->size;
+  if (num_dimensions == 4) {
+    if (output_tensor->dims->data[1] != 1 ||
+        output_tensor->dims->data[2] != 1) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          absl::StrFormat("Unexpected WxH sizes for output index %d: got "
+                          "%dx%d, expected 1x1.",
+                          output_index, output_tensor->dims->data[2],
+                          output_tensor->dims->data[1]),
+          support::TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+    }
+  } else if (num_dimensions != 2) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat(
+            "Unexpected number of dimensions for output index %d: got %dD, "
+            "expected either 2D (BxN with B=1) or 4D (BxHxWxN with B=1, "
+            "W=1, "
+            "H=1).",
+            output_index, num_dimensions),
+        support::TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+  }
+  if (output_tensor->dims->data[0] != 1) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("The output array is expected to have a batch size "
+                        "of 1. Got %d for output index %d.",
+                        output_tensor->dims->data[0], output_index),
+        support::TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+  }
+  embedding_dimension_ = output_tensor->dims->data[num_dimensions - 1];
+  if (output_tensor->type != kTfLiteUInt8 &&
+      output_tensor->type != kTfLiteFloat32) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("Type mismatch for output tensor %s. Requested one "
+                        "of these types: "
+                        "kTfLiteUint8/kTfLiteFloat32, got %s.",
+                        output_tensor->name,
+                        TfLiteTypeGetName(output_tensor->type)),
+        support::TfLiteSupportStatus::kInvalidOutputTensorTypeError);
+  }
+  return absl::OkStatus();
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h
new file mode 100644
index 0000000..78cef8ab5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h
@@ -0,0 +1,213 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_EMBEDDING_POSTPROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_EMBEDDING_POSTPROCESSOR_H_
+#include <initializer_list>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/processor/processor.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/embedding_options.pb.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// This postprocessor works with the following output tensor:
+//   (kTfLiteUInt8/kTfLiteFloat32)
+//    - `N` components corresponding to the `N` dimensions of the returned
+//      feature vector for this output layer.
+//    - Either 2 or 4 dimensions, i.e. `[1 x N]` or `[1 x 1 x 1 x N]`.
+class EmbeddingPostprocessor : public Postprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<EmbeddingPostprocessor>>
+  Create(core::TfLiteEngine* engine,
+         const std::initializer_list<int> output_indices,
+         std::unique_ptr<EmbeddingOptions> options);
+
+  template <typename T>
+  absl::Status Postprocess(T* embedding);
+
+  // Utility function to compute cosine similarity [1] between two feature
+  // vectors. May return an InvalidArgumentError if e.g. the feature vectors are
+  // of different types (quantized vs. float), have different sizes, or have a
+  // an L2-norm of 0.
+  //
+  // [1]: https://en.wikipedia.org/wiki/Cosine_similarity
+  template <typename T>
+  static tflite::support::StatusOr<double> CosineSimilarity(const T& u,
+                                                            const T& v);
+
+  int GetEmbeddingDimension() const { return embedding_dimension_; }
+
+ private:
+  using Postprocessor::Postprocessor;
+
+  absl::Status Init(std::unique_ptr<EmbeddingOptions> options);
+
+  std::unique_ptr<EmbeddingOptions> options_;
+
+  int embedding_dimension_ = 0;
+
+  // Performs actual cosine similarity computation.
+  template <typename T>
+  static tflite::support::StatusOr<double>
+  ComputeCosineSimilarity(const T* u, const T* v, int num_elements);
+
+  template <typename T>
+  void NormalizeFeatureVector(T* feature_vector) const;
+
+  template <typename T>
+  void QuantizeFeatureVector(T* feature_vector) const;
+};
+
+template <typename T>
+absl::Status EmbeddingPostprocessor::Postprocess(T* embedding) {
+  embedding->set_output_index(tensor_indices_.at(0));
+  auto* feature_vector = embedding->mutable_feature_vector();
+  if (GetTensor()->type == kTfLiteUInt8) {
+    const uint8* output_data =
+        engine_->interpreter()->typed_output_tensor<uint8>(
+            tensor_indices_.at(0));
+    // Get the zero_point and scale parameters from the tensor metadata.
+    const int output_tensor_index =
+        engine_->interpreter()->outputs()[tensor_indices_.at(0)];
+    const TfLiteTensor* output_tensor =
+        engine_->interpreter()->tensor(output_tensor_index);
+    for (int j = 0; j < embedding_dimension_; ++j) {
+      feature_vector->add_value_float(output_tensor->params.scale *
+                                      (static_cast<int>(output_data[j]) -
+                                       output_tensor->params.zero_point));
+    }
+  } else {
+    // Float
+    const float* output_data =
+        engine_->interpreter()->typed_output_tensor<float>(
+            tensor_indices_.at(0));
+    for (int j = 0; j < embedding_dimension_; ++j) {
+      feature_vector->add_value_float(output_data[j]);
+    }
+  }
+  if (options_->l2_normalize()) {
+    NormalizeFeatureVector(feature_vector);
+  }
+  if (options_->quantize()) {
+    QuantizeFeatureVector(feature_vector);
+  }
+  return absl::OkStatus();
+}
+
+template <typename T>
+void EmbeddingPostprocessor::NormalizeFeatureVector(T* feature_vector) const {
+  float squared_l2_norm = 0.0f;
+  for (const float val : feature_vector->value_float()) {
+    squared_l2_norm += val * val;
+  }
+  if (squared_l2_norm == 0.0f) {
+    return;
+  }
+  const float inv_l2_norm = 1.0f / std::sqrt(squared_l2_norm);
+  for (int i = 0; i < feature_vector->value_float().size(); ++i) {
+    feature_vector->set_value_float(
+        i, feature_vector->value_float(i) * inv_l2_norm);
+  }
+}
+
+template <typename T>
+void EmbeddingPostprocessor::QuantizeFeatureVector(T* feature_vector) const {
+  auto* quantized_values = feature_vector->mutable_value_string();
+  quantized_values->resize(feature_vector->value_float().size());
+  for (int i = 0; i < feature_vector->value_float().size(); ++i) {
+    int value = static_cast<int>(roundf(feature_vector->value_float(i) * 128));
+    (*quantized_values)[i] =
+        static_cast<char>(std::max(-128, std::min(value, 127)));
+  }
+  feature_vector->clear_value_float();
+}
+
+/* static */
+template <typename T>
+tflite::support::StatusOr<double>
+EmbeddingPostprocessor::ComputeCosineSimilarity(const T* u,
+                                                const T* v,
+                                                int num_elements) {
+  if (num_elements <= 0) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "Cannot compute cosine similarity on empty feature vectors",
+        support::TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  double dot_product = 0.0;
+  double norm_u = 0.0;
+  double norm_v = 0.0;
+  for (int i = 0; i < num_elements; ++i) {
+    dot_product += u[i] * v[i];
+    norm_u += u[i] * u[i];
+    norm_v += v[i] * v[i];
+  }
+  if (norm_u <= 0.0 || norm_v <= 0.0) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "Cannot compute cosine similarity on feature vector with 0 norm",
+        support::TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return dot_product / std::sqrt(norm_u * norm_v);
+}
+
+/* static */
+template <typename T>
+tflite::support::StatusOr<double> EmbeddingPostprocessor::CosineSimilarity(
+    const T& u,
+    const T& v) {
+  if (u.has_value_string() && v.has_value_string()) {
+    if (u.value_string().size() != v.value_string().size()) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          absl::StrFormat("Cannot compute cosine similarity on quantized "
+                          "feature vectors of different sizes (%d vs %d)",
+                          u.value_string().size(), v.value_string().size()),
+          support::TfLiteSupportStatus::kInvalidArgumentError);
+    }
+    return ComputeCosineSimilarity(
+        reinterpret_cast<const int8_t*>(&u.value_string()[0]),
+        reinterpret_cast<const int8_t*>(&v.value_string()[0]),
+        u.value_string().size());
+  }
+  if (!u.has_value_string() && !v.has_value_string()) {
+    if (u.value_float_size() != v.value_float_size()) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          absl::StrFormat("Cannot compute cosine similarity on float "
+                          "feature vectors of different sizes (%d vs %d)",
+                          u.value_float_size(), v.value_float_size()),
+          support::TfLiteSupportStatus::kInvalidArgumentError);
+    }
+    return ComputeCosineSimilarity(
+        u.value_float().data(), v.value_float().data(), u.value_float().size());
+  }
+  return CreateStatusWithPayload(
+      absl::StatusCode::kInvalidArgument,
+      "Cannot compute cosine similarity between quantized and float "
+      "feature vectors",
+      support::TfLiteSupportStatus::kInvalidArgumentError);
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_EMBEDDING_POSTPROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc
new file mode 100644
index 0000000..310a1f5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.cc
@@ -0,0 +1,232 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/processor/image_preprocessor.h"
+
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+namespace {
+// Number of bytes required for 8-bit per pixel RGB color space.
+static constexpr int kRgbPixelBytes = 3;
+
+using ::tflite::task::vision::BoundingBox;
+using ::tflite::task::vision::FrameBuffer;
+}  // namespace
+
+/* static */
+tflite::support::StatusOr<std::unique_ptr<ImagePreprocessor>>
+ImagePreprocessor::Create(
+    core::TfLiteEngine* engine,
+    const std::initializer_list<int> input_indices,
+    const vision::FrameBufferUtils::ProcessEngine& process_engine) {
+  ASSIGN_OR_RETURN(auto processor,
+                   Processor::Create<ImagePreprocessor>(
+                       /* num_expected_tensors = */ 1, engine, input_indices,
+                       /* requires_metadata = */ false));
+
+  RETURN_IF_ERROR(processor->Init(process_engine));
+  return processor;
+}
+
+// Returns false if image preprocessing could be skipped, true otherwise.
+bool ImagePreprocessor::IsImagePreprocessingNeeded(
+    const FrameBuffer& frame_buffer,
+    const BoundingBox& roi) {
+  // Is crop required?
+  if (roi.origin_x() != 0 || roi.origin_y() != 0 ||
+      roi.width() != frame_buffer.dimension().width ||
+      roi.height() != frame_buffer.dimension().height) {
+    return true;
+  }
+
+  // Are image transformations required?
+  if (frame_buffer.orientation() != FrameBuffer::Orientation::kTopLeft ||
+      frame_buffer.format() != FrameBuffer::Format::kRGB ||
+      frame_buffer.dimension().width != input_specs_.image_width ||
+      frame_buffer.dimension().height != input_specs_.image_height) {
+    return true;
+  }
+
+  return false;
+}
+
+absl::Status ImagePreprocessor::Init(
+    const vision::FrameBufferUtils::ProcessEngine& process_engine) {
+  frame_buffer_utils_ = vision::FrameBufferUtils::Create(process_engine);
+
+  ASSIGN_OR_RETURN(input_specs_, vision::BuildInputImageTensorSpecs(
+                                     *engine_->interpreter(),
+                                     *engine_->metadata_extractor()));
+
+  if (input_specs_.color_space != tflite::ColorSpaceType_RGB) {
+    return tflite::support::CreateStatusWithPayload(
+        absl::StatusCode::kUnimplemented,
+        "ImagePreprocessor only supports RGB color space for now.");
+  }
+
+  // Determine if the input shape is resizable.
+  const TfLiteIntArray* dims_signature = GetTensor()->dims_signature;
+
+  // Some fixed-shape models do not have dims_signature.
+  if (dims_signature != nullptr && dims_signature->size > 2) {
+    // Only the HxW dimensions support mutability.
+    is_height_mutable_ = dims_signature->data[1] == -1;
+    is_width_mutable_ = dims_signature->data[2] == -1;
+  }
+  return absl::OkStatus();
+}
+
+absl::Status ImagePreprocessor::Preprocess(const FrameBuffer& frame_buffer) {
+  BoundingBox roi;
+  roi.set_width(frame_buffer.dimension().width);
+  roi.set_height(frame_buffer.dimension().height);
+  return Preprocess(frame_buffer, roi);
+}
+
+absl::Status ImagePreprocessor::Preprocess(const FrameBuffer& frame_buffer,
+                                           const BoundingBox& roi) {
+  // Input data to be normalized (if needed) and used for inference. In most
+  // cases, this is the result of image preprocessing. In case no image
+  // preprocessing is needed (see below), this points to the input frame
+  // buffer raw data.
+  const uint8* input_data;
+  size_t input_data_byte_size;
+
+  // Optional buffers in case image preprocessing is needed.
+  std::unique_ptr<FrameBuffer> preprocessed_frame_buffer;
+  std::vector<uint8> preprocessed_data;
+
+  if (IsImagePreprocessingNeeded(frame_buffer, roi)) {
+    // Preprocess input image to fit model requirements.
+    // For now RGB is the only color space supported, which is ensured by
+    // `InitInternal`.
+    input_specs_.image_width =
+        is_width_mutable_ ? roi.width() : input_specs_.image_width;
+    input_specs_.image_height =
+        is_height_mutable_ ? roi.height() : input_specs_.image_height;
+
+    FrameBuffer::Dimension to_buffer_dimension = {input_specs_.image_width,
+                                                  input_specs_.image_height};
+    input_data_byte_size =
+        GetBufferByteSize(to_buffer_dimension, FrameBuffer::Format::kRGB);
+    preprocessed_data.resize(input_data_byte_size / sizeof(uint8), 0);
+    input_data = preprocessed_data.data();
+
+    FrameBuffer::Plane preprocessed_plane = {
+        /*buffer=*/preprocessed_data.data(),
+        /*stride=*/{input_specs_.image_width * kRgbPixelBytes, kRgbPixelBytes}};
+    preprocessed_frame_buffer = FrameBuffer::Create(
+        {preprocessed_plane}, to_buffer_dimension, FrameBuffer::Format::kRGB,
+        FrameBuffer::Orientation::kTopLeft);
+
+    RETURN_IF_ERROR(frame_buffer_utils_->Preprocess(
+        frame_buffer, roi, preprocessed_frame_buffer.get()));
+  } else {
+    // Input frame buffer already targets model requirements: skip image
+    // preprocessing. For RGB, the data is always stored in a single plane.
+    input_data = frame_buffer.plane(0).buffer;
+    input_data_byte_size = frame_buffer.plane(0).stride.row_stride_bytes *
+                           frame_buffer.dimension().height;
+  }
+
+  // If dynamic, it will re-dim the entire graph as per the input.
+  if (is_height_mutable_ || is_width_mutable_) {
+    engine_->interpreter()->ResizeInputTensorStrict(
+        0, {GetTensor()->dims->data[0], input_specs_.image_height,
+            input_specs_.image_width, GetTensor()->dims->data[3]});
+
+    engine_->interpreter()->AllocateTensors();
+  }
+  // Then normalize pixel data (if needed) and populate the input tensor.
+  switch (input_specs_.tensor_type) {
+    case kTfLiteUInt8:
+      if (GetTensor()->bytes != input_data_byte_size) {
+        return tflite::support::CreateStatusWithPayload(
+            absl::StatusCode::kInternal,
+            "Size mismatch or unsupported padding bytes between pixel data "
+            "and input tensor.");
+      }
+      // No normalization required: directly populate data.
+      RETURN_IF_ERROR(tflite::task::core::PopulateTensor(
+          input_data, input_data_byte_size / sizeof(uint8), GetTensor()));
+      break;
+    case kTfLiteFloat32: {
+      if (GetTensor()->bytes / sizeof(float) !=
+          input_data_byte_size / sizeof(uint8)) {
+        return tflite::support::CreateStatusWithPayload(
+            absl::StatusCode::kInternal,
+            "Size mismatch or unsupported padding bytes between pixel data "
+            "and input tensor.");
+      }
+      // Normalize and populate.
+      ASSIGN_OR_RETURN(
+          float* normalized_input_data,
+          tflite::task::core::AssertAndReturnTypedTensor<float>(GetTensor()));
+      const tflite::task::vision::NormalizationOptions& normalization_options =
+          input_specs_.normalization_options.value();
+      for (int i = 0; i < normalization_options.num_values; i++) {
+        if (std::abs(normalization_options.std_values[i]) <
+            std::numeric_limits<float>::epsilon()) {
+          return tflite::support::CreateStatusWithPayload(
+              absl::StatusCode::kInternal,
+              "NormalizationOptions.std_values can't be 0. Please check if the "
+              "tensor metadata has been populated correctly.");
+        }
+      }
+      if (normalization_options.num_values == 1) {
+        float mean_value = normalization_options.mean_values[0];
+        float inv_std_value = (1.0f / normalization_options.std_values[0]);
+        for (size_t i = 0; i < input_data_byte_size / sizeof(uint8);
+             i++, input_data++, normalized_input_data++) {
+          *normalized_input_data =
+              inv_std_value * (static_cast<float>(*input_data) - mean_value);
+        }
+      } else {
+        std::array<float, 3> inv_std_values = {
+            1.0f / normalization_options.std_values[0],
+            1.0f / normalization_options.std_values[1],
+            1.0f / normalization_options.std_values[2]};
+        for (size_t i = 0; i < input_data_byte_size / sizeof(uint8);
+             i++, input_data++, normalized_input_data++) {
+          *normalized_input_data = inv_std_values[i % 3] *
+                                   (static_cast<float>(*input_data) -
+                                    normalization_options.mean_values[i % 3]);
+        }
+      }
+      break;
+    }
+    case kTfLiteInt8:
+      return tflite::support::CreateStatusWithPayload(
+          absl::StatusCode::kUnimplemented,
+          "kTfLiteInt8 input type is not implemented yet.");
+    default:
+      return tflite::support::CreateStatusWithPayload(
+          absl::StatusCode::kInternal, "Unexpected input tensor type.");
+  }
+
+  return absl::OkStatus();
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.h
new file mode 100644
index 0000000..9b7d46f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/image_preprocessor.h
@@ -0,0 +1,103 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_IMAGE_PREPROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_IMAGE_PREPROCESSOR_H_
+
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/processor/processor.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// Process input image and populate the associate input tensor.
+// Requirement for the input tensor:
+//   (kTfLiteUInt8/kTfLiteFloat32)
+//    - image input of size `[batch x height x width x channels]`.
+//    - batch inference is not supported (`batch` is required to be 1).
+//    - only RGB inputs are supported (`channels` is required to be 3).
+//    - if type is kTfLiteFloat32, NormalizationOptions are required to be
+//      attached to the metadata for input normalization.
+class ImagePreprocessor : public Preprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<ImagePreprocessor>> Create(
+      core::TfLiteEngine* engine,
+      const std::initializer_list<int> input_indices,
+      const vision::FrameBufferUtils::ProcessEngine& process_engine =
+          vision::FrameBufferUtils::ProcessEngine::kLibyuv);
+
+  // Processes the provided FrameBuffer and populate tensor values.
+  //
+  // The FrameBuffer can be of any size and any of the supported formats, i.e.
+  // RGBA, RGB, NV12, NV21, YV12, YV21. It is automatically pre-processed before
+  // inference in order to (and in this order):
+  // - resize it (with bilinear interpolation, aspect-ratio *not* preserved) to
+  //   the dimensions of the model input tensor,
+  // - convert it to the colorspace of the input tensor (i.e. RGB, which is the
+  //   only supported colorspace for now),
+  // - rotate it according to its `Orientation` so that inference is performed
+  //   on an "upright" image.
+  //
+  // NOTE: In case the model has dynamic input shape, the method would re-dim
+  // the entire graph based on the dimensions of the image.
+  absl::Status Preprocess(const vision::FrameBuffer& frame_buffer);
+
+  // Same as above, except based on the input region of interest.
+  //
+  // IMPORTANT: as a consequence of cropping occurring first, the provided
+  // region of interest is expressed in the unrotated frame of reference
+  // coordinates system, i.e. in `[0, frame_buffer.width) x [0,
+  // frame_buffer.height)`, which are the dimensions of the underlying
+  // `frame_buffer` data before any `Orientation` flag gets applied. Also, the
+  // region of interest is not clamped, so this method will return a non-ok
+  // status if the region is out of these bounds.
+  absl::Status Preprocess(const vision::FrameBuffer& frame_buffer,
+                          const vision::BoundingBox& roi);
+
+  // Returns the spec of model. Passing in an image with this spec will speed up
+  // the inference as it bypasses image cropping and resizing.
+  const vision::ImageTensorSpecs& GetInputSpecs() const { return input_specs_; }
+
+ private:
+  using Preprocessor::Preprocessor;
+
+  // Returns false if image preprocessing could be skipped, true otherwise.
+  bool IsImagePreprocessingNeeded(const vision::FrameBuffer& frame_buffer,
+                                  const vision::BoundingBox& roi);
+
+  absl::Status Init(
+      const vision::FrameBufferUtils::ProcessEngine& process_engine);
+
+  // Parameters related to the input tensor which represents an image.
+  vision::ImageTensorSpecs input_specs_;
+
+  // Utils for input image preprocessing (resizing, colorspace conversion, etc).
+  std::unique_ptr<vision::FrameBufferUtils> frame_buffer_utils_;
+
+  // Is true if the model expects dynamic image shape, false otherwise.
+  bool is_height_mutable_ = false;
+  bool is_width_mutable_ = false;
+};
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_IMAGE_PREPROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.cc
new file mode 100644
index 0000000..1fc47f7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.cc
@@ -0,0 +1,70 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/processor/processor.h"
+
+#include <iterator>
+#include <sstream>
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+constexpr char Preprocessor::kInputTypeName[];
+constexpr char Postprocessor::kOutputTypeName[];
+
+absl::Status Processor::SanityCheck(int num_expected_tensors,
+                                    bool requires_metadata) {
+  const char* tensor_type_name = GetTensorTypeName();
+  if (tensor_indices_.size() != num_expected_tensors) {
+    return support::CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("Processor can handle %d tensors, "
+                        "got: %d tensors.",
+                        num_expected_tensors, tensor_indices_.size()));
+  }
+
+  int tensor_count = GetModelTensorCount();
+  for (int i = 0; i < tensor_indices_.size(); i++) {
+    int index = tensor_indices_.at(i);
+    if (index < 0 || index >= tensor_count) {
+      return support::CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          absl::StrFormat("Invalid tensor_index: %d. Model has %d %s tensors.",
+                          index, tensor_count, tensor_type_name));
+    }
+    if (requires_metadata) {
+      if (GetTensorMetadata(i) == nullptr) {
+        return CreateStatusWithPayload(
+            absl::StatusCode::kInvalidArgument,
+            absl::StrFormat("%s tensor %d is missing TensorMetadata.",
+                            tensor_type_name, index),
+            support::TfLiteSupportStatus::kMetadataNotFoundError);
+      }
+    }
+  }
+
+  return absl::OkStatus();
+}
+
+std::string Processor::GetTensorIndexString() {
+  std::stringstream stream;
+  std::copy(tensor_indices_.begin(), tensor_indices_.end(),
+            std::ostream_iterator<int>(stream, " "));
+  return stream.str();
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h
new file mode 100644
index 0000000..b3c4360
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/processor.h
@@ -0,0 +1,201 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_PROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_PROCESSOR_H_
+
+#include <initializer_list>
+#include <vector>
+
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow/lite/core/shims/c/common.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// Abstract base class for all Processors.
+// Shares the common logics to handle tflite_engine and metadata.
+class Processor {
+ public:
+  Processor() = default;
+  virtual ~Processor() = default;
+
+  // Processor is neither copyable nor movable.
+  Processor(const Processor&) = delete;
+  Processor& operator=(const Processor&) = delete;
+
+  template <typename T>
+  using EnableIfProcessorSubclass =
+      typename std::enable_if<std::is_base_of<Processor, T>::value>::type*;
+
+  // Factory method to create a subclass of Processor.
+  //
+  // Example usage:
+  // auto processor = Processor::Create<MyPreprocessor>(
+  //   num_expected_tensors, engine, tensor_indices);
+  template <typename T, EnableIfProcessorSubclass<T> = nullptr>
+  static tflite::support::StatusOr<std::unique_ptr<T>> Create(
+      int num_expected_tensors,
+      tflite::task::core::TfLiteEngine* engine,
+      const std::initializer_list<int> tensor_indices,
+      bool requires_metadata = true) {
+    auto processor = absl::make_unique<T>(engine, tensor_indices);
+    RETURN_IF_ERROR(
+        processor->SanityCheck(num_expected_tensors, requires_metadata));
+    return processor;
+  }
+
+  // `tensor_indices` is the indices of the input tensors or output tensors
+  // that the processor should process. For example, a model may have 4 input
+  // tensors, and a preprocessor can process the first and third tensor,
+  // then `tensor_indices` should be {0, 2}.
+  explicit Processor(core::TfLiteEngine* engine,
+                     const std::initializer_list<int> tensor_indices)
+      : engine_(engine), tensor_indices_(tensor_indices) {}
+
+  // Checks if tensor counts and metadata of the model matches what required
+  // by the processor in general.
+  absl::Status SanityCheck(int num_expected_tensors,
+                           bool requires_metadata = true);
+
+ protected:
+  // Gets the associated tensor.
+  // `i` refers to the element index in `tensor_indices`. For example,
+  // assume `tensor_indices` is {3, 6, 8}, to access second tensor in
+  // `tensor_indices`, which is the 6th tensor of the model inputs or ourputs,
+  // `i` should be 1.
+  virtual TfLiteTensor* GetTensor(int i) const = 0;
+
+  // Gets the associated tensor metadata.
+  // `i` refers to the element index in `tensor_indices`. For example,
+  // assume `tensor_indices` is {3, 6, 8}, to access second tensor in
+  // `tensor_indices`, which is the 6th tensor of the model inputs or ourputs,
+  // `i` should be 1.
+  virtual const tflite::TensorMetadata* GetTensorMetadata(int i = 0) const = 0;
+
+  inline const tflite::metadata::ModelMetadataExtractor* GetMetadataExtractor()
+      const {
+    return engine_->metadata_extractor();
+  }
+
+  // Gets the tesnor indices in string format.
+  std::string GetTensorIndexString();
+
+  core::TfLiteEngine* engine_;
+  const std::vector<int> tensor_indices_;
+
+ private:
+  // Gets the number of input or ourput tensors of the TfLiteEngine that this
+  // processor holds.
+  virtual int GetModelTensorCount() const = 0;
+
+  // Either "input" or "output".
+  virtual const char* GetTensorTypeName() const = 0;
+};
+
+// Abstract base class for all Preprocessors.
+// Preprocessor is a helper class that converts input structured data (such as
+// image) to raw bytes and populates the associated tensors in the
+// interpreter.
+//
+// As a convention, child class needs to implement a factory `Create` method
+// to initialize and bind tensors.
+//
+// Example usage:
+// auto processor = MyPreprocessor::Create(
+//   /* input_tensors */ {0}, engine, option);
+// // Populate the associate tensors.
+// processor->Preprocess(...);
+class Preprocessor : public Processor {
+ protected:
+  using Processor::Processor;
+
+  // Get the associated input tensor.
+  // Note: Caller is responsible for passing in a valid `i`.
+  inline TfLiteTensor* GetTensor(int i = 0) const override {
+    return engine_->GetInput(engine_->interpreter(), tensor_indices_.at(i));
+  }
+
+  // Get the associated input metadata.
+  // Note: Caller is responsible for passing in a valid `i`.
+  inline const tflite::TensorMetadata* GetTensorMetadata(
+      int i = 0) const override {
+    return GetMetadataExtractor()->GetInputTensorMetadata(
+        tensor_indices_.at(i));
+  }
+
+ private:
+  static constexpr char kInputTypeName[] = "input";
+
+  inline int GetModelTensorCount() const override {
+    return engine_->InputCount(engine_->interpreter());
+  }
+
+  inline const char* GetTensorTypeName() const override {
+    return kInputTypeName;
+  }
+};
+
+// Abstract base class for all Postprocessors.
+// Postprocessor is a helper class to convert tensor value to structured
+// data.
+// As a convention, child class needs to implement a factory `Create` method
+// to initialize and bind tensors.
+//
+// Example usage:
+// auto processor = MyPostprocessor::Create(
+//   /* output_tensors */ {0}, engine, option);
+// // Populate the associate tensors.
+// auto value = processor->Postprocess();
+class Postprocessor : public Processor {
+ protected:
+  using Processor::Processor;
+
+  // Get the associated output tensor.
+  // Note: Caller is responsible for passing in a valid `i`.
+  inline TfLiteTensor* GetTensor(int i = 0) const override {
+    return engine_->GetOutput(engine_->interpreter(), tensor_indices_.at(i));
+  }
+
+  // Get the associated output metadata.
+  // Note: Caller is responsible for passing in a valid `i`.
+  inline const tflite::TensorMetadata* GetTensorMetadata(
+      int i = 0) const override {
+    return GetMetadataExtractor()->GetOutputTensorMetadata(
+        tensor_indices_.at(i));
+  }
+
+ private:
+  static constexpr char kOutputTypeName[] = "output";
+
+  inline int GetModelTensorCount() const override {
+    return engine_->OutputCount(engine_->interpreter());
+  }
+
+  inline const char* GetTensorTypeName() const override {
+    return kOutputTypeName;
+  }
+};
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_PROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/BUILD
new file mode 100644
index 0000000..7e1e203
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/BUILD
@@ -0,0 +1,67 @@
+package(
+    default_visibility = [
+        "//visibility:public",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+proto_library(
+    name = "classifications_proto",
+    srcs = ["classifications.proto"],
+    deps = [":class_proto"],
+)
+
+cc_proto_library(
+    name = "classifications_cc_proto",
+    deps = [
+        ":classifications_proto",
+    ],
+)
+
+proto_library(
+    name = "class_proto",
+    srcs = ["class.proto"],
+)
+
+cc_proto_library(
+    name = "class_cc_proto",
+    deps = [
+        ":class_proto",
+    ],
+)
+
+proto_library(
+    name = "embedding_proto",
+    srcs = ["embedding.proto"],
+)
+
+cc_proto_library(
+    name = "embedding_cc_proto",
+    deps = [
+        ":embedding_proto",
+    ],
+)
+
+proto_library(
+    name = "embedding_options_proto",
+    srcs = ["embedding_options.proto"],
+)
+
+cc_proto_library(
+    name = "embedding_options_cc_proto",
+    deps = [
+        ":embedding_options_proto",
+    ],
+)
+
+proto_library(
+    name = "classification_options_proto",
+    srcs = ["classification_options.proto"],
+)
+
+cc_proto_library(
+    name = "classification_options_cc_proto",
+    deps = [
+        ":classification_options_proto",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/class.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/class.proto
new file mode 100644
index 0000000..f8b13f6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/class.proto
@@ -0,0 +1,36 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.processor;
+
+// A single classification result.
+message Class {
+  // The index of the class in the corresponding label map, usually packed in
+  // the TFLite Model Metadata [1].
+  //
+  // [1]: https://www.tensorflow.org/lite/convert/metadata
+  optional int32 index = 1;
+  // The score for this class e.g. (but not necessarily) a probability in [0,1].
+  optional float score = 2;
+  // A human readable name of the class filled from the label map.
+  optional string display_name = 3;
+  // An ID for the class, not necessarily human-readable (e.g. a Google
+  // Knowledge Graph ID [1]), filled from the label map.
+  //
+  // [1]: https://developers.google.com/knowledge-graph
+  optional string class_name = 4;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/classification_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/classification_options.proto
new file mode 100644
index 0000000..0546800
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/classification_options.proto
@@ -0,0 +1,45 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.processor;
+
+// Options for classification processor.
+// Next Id: 6
+message ClassificationOptions {
+  // The locale to use for display names specified through the TFLite Model
+  // Metadata, if any. Defaults to English.
+  optional string display_names_locale = 1 [default = "en"];
+
+  // The maximum number of top-scored classification results to return. If < 0,
+  // all available results will be returned. If 0, an invalid argument error is
+  // returned.
+  optional int32 max_results = 2 [default = -1];
+
+  // Score threshold, overrides the ones provided in the model metadata
+  // (if any). Results below this value are rejected.
+  optional float score_threshold = 3;
+
+  // Optional allowlist of class names. If non-empty, classifications whose
+  // class name is not in this set will be filtered out. Duplicate or unknown
+  // class names are ignored. Mutually exclusive with class_name_denylist.
+  repeated string class_name_allowlist = 4;
+
+  // Optional denylist of class names. If non-empty, classifications whose
+  // class name is in this set will be filtered out. Duplicate or unknown
+  // class names are ignored. Mutually exclusive with class_name_allowlist.
+  repeated string class_name_denylist = 5;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/classifications.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/classifications.proto
new file mode 100644
index 0000000..aaa4e7e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/classifications.proto
@@ -0,0 +1,39 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.processor;
+
+import "tensorflow_lite_support/cc/task/processor/proto/class.proto";
+
+// List of predicted classes (aka labels) for a given classifier head.
+message Classifications {
+  // The array of predicted classes, usually sorted by descending scores (e.g.
+  // from high to low probability).
+  repeated Class classes = 1;
+  // The index of the classifier head these classes refer to. This is useful for
+  // multi-head models.
+  optional int32 head_index = 2;
+  // The name of the classifier head, which is the corresponding tensor metadata
+  // name. See
+  // https://github.com/tensorflow/tflite-support/blob/710e323265bfb71fdbdd72b3516e00cff15c0326/tensorflow_lite_support/metadata/metadata_schema.fbs#L545
+  optional string head_name = 3;
+}
+
+// Contains one set of results per classifier head.
+message ClassificationResult {
+  repeated Classifications classifications = 1;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/embedding.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/embedding.proto
new file mode 100644
index 0000000..5c55c88
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/embedding.proto
@@ -0,0 +1,48 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.processor;
+
+// Defines a dense feature vector. Only one of the two fields is ever present.
+// Feature vectors are assumed to be one-dimensional and L2-normalized.
+message FeatureVector {
+  // Raw output of the embedding layer. Only provided if `quantize` is set to
+  // false in the EmbeddingOptions, which is the case by default.
+  repeated float value_float = 1 [packed = true];
+  // Scalar-quantized embedding. Only provided if `quantize` is set to true in
+  // the ImageEmbedderOptions.
+  optional bytes value_string = 2;
+}
+
+// Result produced by one of the embedder model output layers.
+message Embedding {
+  // The output feature vector.
+  optional FeatureVector feature_vector = 1;
+  // The index of the model output layer that produced this feature vector.
+  optional int32 output_index = 2;
+}
+
+// Embeddings produced by the Embedder.
+message EmbeddingResult {
+  // The embeddings produced by each of the model output layers.
+  //
+  // Except in advanced cases, the embedding model has a single output layer,
+  // and this list is thus made of a single element.
+  repeated Embedding embeddings = 1;
+  // Reserved tags.
+  reserved 2;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/embedding_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/embedding_options.proto
new file mode 100644
index 0000000..28bd2e11
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/proto/embedding_options.proto
@@ -0,0 +1,34 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.processor;
+
+// Options for embedding processor.
+// Next Id: 3
+message EmbeddingOptions {
+  // Whether to normalize the returned feature vector with L2 norm. Use this
+  // option only if the model does not already contain a native L2_NORMALIZATION
+  // TF Lite Op. In most cases, this is already the case and L2 norm is thus
+  // achieved through TF Lite inference.
+  optional bool l2_normalize = 1;
+
+  // Whether the returned embedding should be quantized to bytes via scalar
+  // quantization. Embeddings are implicitly assumed to be unit-norm and
+  // therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use
+  // the l2_normalize option if this is not the case.
+  optional bool quantize = 2;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc
new file mode 100644
index 0000000..58b77b6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.cc
@@ -0,0 +1,216 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/processor/regex_preprocessor.h"
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+namespace {
+
+using ::absl::StatusCode;
+using ::tflite::TensorMetadata;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::support::text::tokenizer::RegexTokenizer;
+using ::tflite::support::text::tokenizer::TokenizerResult;
+using ::tflite::task::core::PopulateTensor;
+
+StatusOr<absl::string_view> CheckAndLoadFirstAssociatedFile(
+    const flatbuffers::Vector<flatbuffers::Offset<tflite::AssociatedFile>>*
+        associated_files,
+    const tflite::metadata::ModelMetadataExtractor* metadata_extractor) {
+  if (associated_files == nullptr || associated_files->size() < 1 ||
+      associated_files->Get(0)->name() == nullptr) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "Invalid vocab_file from input process unit.",
+        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+  }
+  ASSIGN_OR_RETURN(absl::string_view vocab_buffer,
+                   metadata_extractor->GetAssociatedFile(
+                       associated_files->Get(0)->name()->str()));
+  return vocab_buffer;
+}
+
+}  // namespace
+
+/* static */
+StatusOr<std::unique_ptr<RegexPreprocessor>> RegexPreprocessor::Create(
+    tflite::task::core::TfLiteEngine* engine,
+    int input_tensor_index) {
+  ASSIGN_OR_RETURN(auto processor, Processor::Create<RegexPreprocessor>(
+                                       /* num_expected_tensors = */ 1, engine,
+                                       {input_tensor_index},
+                                       /* requires_metadata = */ false));
+  RETURN_IF_ERROR(processor->Init());
+  return processor;
+}
+
+absl::Status RegexPreprocessor::Init() {
+  // Check if the input is a STRING. If so, no tokenizer is needed.
+  if (GetTensor()->type == kTfLiteString) {
+    return absl::OkStatus();
+  }
+  // Try if RegexTokenzier metadata can be found.
+  ASSIGN_OR_RETURN(const auto tokenzier_metadata,
+                   TryFindRegexTokenizerMetadata());
+
+  ASSIGN_OR_RETURN(tokenizer_, CreateTokenizerFromMetadata(
+                                   tokenzier_metadata, GetMetadataExtractor()));
+  return absl::OkStatus();
+}
+
+StatusOr<const tflite::ProcessUnit*>
+RegexPreprocessor::TryFindRegexTokenizerMetadata() {
+  // RegexTokenizer is packed in the processing unit of the input tensor.
+  const TensorMetadata* tensor_metadata = GetTensorMetadata();
+  if (tensor_metadata == nullptr) {
+    return nullptr;
+  }
+
+  ASSIGN_OR_RETURN(
+      auto tokenizer_metadata,
+      GetMetadataExtractor()->FindFirstProcessUnit(
+          *tensor_metadata, ProcessUnitOptions_RegexTokenizerOptions));
+
+  if (tokenizer_metadata != nullptr) {
+    // RegexTokenizer is found. Check if the tensor type matches.
+    auto input_tensor = GetTensor();
+    if (input_tensor->type != kTfLiteInt32) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrCat("Type mismatch for input tensor ", input_tensor->name,
+                       ". Requested INT32 for RegexTokenizer, got ",
+                       TfLiteTypeGetName(input_tensor->type), "."),
+          TfLiteSupportStatus::kInvalidInputTensorTypeError);
+    }
+  }
+  return tokenizer_metadata;
+}
+
+StatusOr<std::unique_ptr<RegexTokenizer>>
+RegexPreprocessor::CreateTokenizerFromMetadata(
+    const tflite::ProcessUnit* tokenizer_metadata,
+    const tflite::metadata::ModelMetadataExtractor* metadata_extractor) {
+  if (metadata_extractor == nullptr || tokenizer_metadata == nullptr) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "No metadata or input process unit found.",
+        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+  }
+  if (tokenizer_metadata->options_type() ==
+      ProcessUnitOptions_RegexTokenizerOptions) {
+    const tflite::RegexTokenizerOptions* options =
+        tokenizer_metadata->options_as<RegexTokenizerOptions>();
+    ASSIGN_OR_RETURN(absl::string_view vocab_buffer,
+                     CheckAndLoadFirstAssociatedFile(options->vocab_file(),
+                                                     metadata_extractor));
+    if (options->delim_regex_pattern() == nullptr) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "Invalid delim_regex_pattern from input process unit.",
+          TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+    }
+
+    std::unique_ptr<RegexTokenizer> regex_tokenizer =
+        absl::make_unique<RegexTokenizer>(options->delim_regex_pattern()->str(),
+                                          vocab_buffer.data(),
+                                          vocab_buffer.size());
+
+    int unknown_token_id = 0;
+    if (!regex_tokenizer->GetUnknownToken(&unknown_token_id)) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "RegexTokenizer doesn't have <UNKNOWN> token.",
+          TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+    }
+
+    int pad_token_id = 0;
+    if (!regex_tokenizer->GetPadToken(&pad_token_id)) {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "RegexTokenizer doesn't have <PAD> token.",
+          TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+    }
+
+    return std::move(regex_tokenizer);
+  } else {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kNotFound,
+        absl::StrCat("Incorrect options_type:",
+                     tokenizer_metadata->options_type()),
+        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+  }
+}
+
+absl::Status RegexPreprocessor::Preprocess(const std::string& input_text) {
+  if (tokenizer_ == nullptr) {
+    return PopulateTensor(input_text, GetTensor());
+  } else {
+    return RegexPreprocess(input_text);
+  }
+}
+
+absl::Status RegexPreprocessor::RegexPreprocess(const std::string& input_text) {
+  TfLiteTensor* input_tensor = GetTensor();
+
+  //                              |<-------sentence_length-------->|
+  // input_tensor                 <START>, t1, t2... <PAD>, <PAD>...
+  // <START> is optional, t1, t2... will be replaced by <UNKNOWN> if it's
+  // not found in tokenizer vocab.
+  TokenizerResult result = tokenizer_->Tokenize(input_text);
+
+  size_t max_sentence_length = input_tensor->dims->size == 2
+                                   ? input_tensor->dims->data[1]
+                                   : input_tensor->dims->data[0];
+
+  int unknown_token_id = 0;
+  tokenizer_->GetUnknownToken(&unknown_token_id);
+
+  int pad_token_id = 0;
+  tokenizer_->GetPadToken(&pad_token_id);
+
+  std::vector<int> input_tokens(max_sentence_length, pad_token_id);
+  int start_token_id = 0;
+  size_t input_token_index = 0;
+  if (tokenizer_->GetStartToken(&start_token_id)) {
+    input_tokens[0] = start_token_id;
+    input_token_index = 1;
+  }
+
+  for (size_t i = 0; (i < result.subwords.size()) &&
+                     (input_token_index < max_sentence_length);
+       ++i, ++input_token_index) {
+    const std::string& token = result.subwords[i];
+    int token_id = 0;
+    if (tokenizer_->LookupId(token, &token_id)) {
+      input_tokens[input_token_index] = token_id;
+    } else {
+      input_tokens[input_token_index] = unknown_token_id;
+    }
+  }
+  return PopulateTensor(input_tokens, input_tensor);
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h
new file mode 100644
index 0000000..bdd4e5e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/regex_preprocessor.h
@@ -0,0 +1,65 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_REGEX_PREPROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_REGEX_PREPROCESSOR_H_
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/processor/text_preprocessor.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// Processes input text and populates the associated input tensor.
+// Requirements for the input tensor:
+//   A string tensor of type, kTfLiteString
+//      or
+//   An int32 tensor of type, kTfLiteInt32: contains the tokenized indices of
+//   a string input. A RegexTokenizer needs to be set up in the input tensor's
+//   metadata.
+class RegexPreprocessor : public TextPreprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<RegexPreprocessor>> Create(
+      tflite::task::core::TfLiteEngine* engine,
+      int input_tensor_index);
+
+  absl::Status Preprocess(const std::string& text);
+
+ private:
+  using TextPreprocessor::TextPreprocessor;
+
+  absl::Status Init();
+
+  tflite::support::StatusOr<const tflite::ProcessUnit*>
+  TryFindRegexTokenizerMetadata();
+
+  absl::Status RegexPreprocess(const std::string& input_text);
+
+  tflite::support::StatusOr<
+      std::unique_ptr<tflite::support::text::tokenizer::RegexTokenizer>>
+  CreateTokenizerFromMetadata(
+      const tflite::ProcessUnit* tokenizer_metadata,
+      const tflite::metadata::ModelMetadataExtractor* metadata_extractor);
+
+  std::unique_ptr<tflite::support::text::tokenizer::RegexTokenizer> tokenizer_;
+};
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_REGEX_PREPROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/text_preprocessor.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/text_preprocessor.cc
new file mode 100644
index 0000000..30525229
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/text_preprocessor.cc
@@ -0,0 +1,58 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/processor/text_preprocessor.h"
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/processor/bert_preprocessor.h"
+#include "tensorflow_lite_support/cc/task/processor/regex_preprocessor.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+namespace {
+
+using ::absl::StatusCode;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+
+}  // namespace
+
+/* static */ StatusOr<std::unique_ptr<TextPreprocessor>>
+TextPreprocessor::Create(
+    tflite::task::core::TfLiteEngine* engine,
+    const std::initializer_list<int> input_tensor_indices) {
+  switch (input_tensor_indices.size()) {
+    case 1:
+      return RegexPreprocessor::Create(engine, *input_tensor_indices.begin());
+    case 3:
+      return BertPreprocessor::Create(engine, input_tensor_indices);
+    default:
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat(
+              "TextPrerocessor accepts either 1 input tesnor (for Regex "
+              "tokenizer or String tensor) or 3 input tensors (for Bert "
+              "tokenizer), but got %d tensors.",
+              input_tensor_indices.size()));
+  }
+}
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/text_preprocessor.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/text_preprocessor.h
new file mode 100644
index 0000000..5781bf4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/processor/text_preprocessor.h
@@ -0,0 +1,56 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_TEXT_PREPROCESSOR_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_TEXT_PREPROCESSOR_H_
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/processor/processor.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+
+// Processes input text and populates the associated input tensors.
+// Requirements for the input tensors (either one of the following):
+//   - One input tensor:
+//     A string tensor of type, kTfLiteString
+//        or
+//     An int32 tensor of type, kTfLiteInt32: contains the tokenized indices of
+//     a string input. A RegexTokenizer needs to be set up in the input tensor's
+//     metadata.
+//   - Three input tensors (input tensors of a Bert model):
+//     The 3 input tensors should be populated with metadata tensor names,
+//     "ids", "mask", and "segment_ids", respectively. The input_process_units
+//     metadata should contain WordPiece or Sentencepiece Tokenizer
+//     metadata.
+class TextPreprocessor : public Preprocessor {
+ public:
+  static tflite::support::StatusOr<std::unique_ptr<TextPreprocessor>> Create(
+      tflite::task::core::TfLiteEngine* engine,
+      const std::initializer_list<int> input_tensor_indices);
+
+  absl::Status Preprocess(const std::string& text);
+
+ protected:
+  using Preprocessor::Preprocessor;
+};
+
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_PROCESSOR_TEXT_PREPROCESSOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/BUILD
new file mode 100644
index 0000000..05b7c5e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/BUILD
@@ -0,0 +1,116 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_library_with_tflite",
+)
+
+package(
+    default_visibility = ["//visibility:public"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library_with_tflite(
+    name = "bert_nl_classifier",
+    srcs = [
+        "bert_nl_classifier.cc",
+    ],
+    hdrs = [
+        "bert_nl_classifier.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/core:category",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/text/proto:bert_nl_classifier_options_proto_inc",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer_utils",
+        "//tensorflow_lite_support/metadata/cc:metadata_extractor",
+        "@com_google_absl//absl/base:core_headers",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
+        "@org_tensorflow//tensorflow/lite:string",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/core/api",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "question_answerer",
+    hdrs = [
+        "question_answerer.h",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "bert_question_answerer",
+    srcs = [
+        "bert_question_answerer.cc",
+    ],
+    hdrs = [
+        "bert_question_answerer.h",
+    ],
+    tflite_deps = [
+        ":question_answerer",
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/text/proto:bert_question_answerer_options_proto_inc",
+        "//tensorflow_lite_support/cc/text/tokenizers:bert_tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:sentencepiece_tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
+        "@com_google_absl//absl/base:core_headers",
+        "@com_google_absl//absl/container:flat_hash_map",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
+cc_library_with_tflite(
+    name = "universal_sentence_encoder_qa",
+    srcs = [
+        "universal_sentence_encoder_qa.cc",
+    ],
+    hdrs = [
+        "universal_sentence_encoder_qa.h",
+    ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/processor/proto:embedding_cc_proto",
+        "//tensorflow_lite_support/cc/task/text/proto:retrieval_cc_proto",
+        "//tensorflow_lite_support/cc/text/tokenizers:bert_tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:sentencepiece_tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
+        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
+        "@com_google_absl//absl/container:flat_hash_map",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc
new file mode 100644
index 0000000..ac8fa548
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.cc
@@ -0,0 +1,208 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
+
+#include <limits.h>
+#include <stddef.h>
+
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/ascii.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/string_type.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/core/category.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h"
+#include "tensorflow_lite_support/metadata/cc/metadata_extractor.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::support::text::tokenizer::CreateTokenizerFromProcessUnit;
+using ::tflite::support::text::tokenizer::TokenizerResult;
+using ::tflite::task::core::FindTensorByName;
+using ::tflite::task::core::PopulateTensor;
+
+namespace {
+constexpr char kIdsTensorName[] = "ids";
+constexpr char kMaskTensorName[] = "mask";
+constexpr char kSegmentIdsTensorName[] = "segment_ids";
+constexpr char kScoreTensorName[] = "probability";
+constexpr char kClassificationToken[] = "[CLS]";
+constexpr char kSeparator[] = "[SEP]";
+constexpr int kTokenizerProcessUnitIndex = 0;
+
+absl::Status SanityCheckOptions(const BertNLClassifierOptions& options) {
+  if (!options.has_base_options()) {
+    return CreateStatusWithPayload(absl::StatusCode::kInvalidArgument,
+                                   "Missing mandatory `base_options` field",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+
+int GetLastDimSize(const TfLiteTensor* tensor) {
+  return tensor->dims->data[tensor->dims->size - 1];
+}
+
+}  // namespace
+
+absl::Status BertNLClassifier::Preprocess(
+    const std::vector<TfLiteTensor*>& input_tensors,
+    const std::string& input) {
+  auto* input_tensor_metadatas =
+      GetMetadataExtractor()->GetInputTensorMetadata();
+  auto* ids_tensor =
+      FindTensorByName(input_tensors, input_tensor_metadatas, kIdsTensorName);
+  auto* mask_tensor =
+      FindTensorByName(input_tensors, input_tensor_metadatas, kMaskTensorName);
+  auto* segment_ids_tensor = FindTensorByName(
+      input_tensors, input_tensor_metadatas, kSegmentIdsTensorName);
+
+  if (GetLastDimSize(ids_tensor) != GetLastDimSize(mask_tensor) ||
+      GetLastDimSize(ids_tensor) != GetLastDimSize(segment_ids_tensor)) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInternal,
+        absl::StrFormat("The three input tensors in BertNLClassifier models "
+                        "are expected to have same length, but got ids_tensor "
+                        "(%d), mask_tensor (%d), segment_ids_tensor (%d).",
+                        GetLastDimSize(ids_tensor), GetLastDimSize(mask_tensor),
+                        GetLastDimSize(ids_tensor)),
+        TfLiteSupportStatus::kInvalidNumOutputTensorsError);
+  }
+
+  int max_seq_len = GetLastDimSize(ids_tensor);
+
+  std::string processed_input = input;
+  absl::AsciiStrToLower(&processed_input);
+
+  TokenizerResult input_tokenize_results;
+  input_tokenize_results = tokenizer_->Tokenize(processed_input);
+
+  // 2 accounts for [CLS], [SEP]
+  absl::Span<const std::string> query_tokens =
+      absl::MakeSpan(input_tokenize_results.subwords.data(),
+                     input_tokenize_results.subwords.data() +
+                         std::min(static_cast<size_t>(max_seq_len - 2),
+                                  input_tokenize_results.subwords.size()));
+
+  std::vector<std::string> tokens;
+  tokens.reserve(2 + query_tokens.size());
+  // Start of generating the features.
+  tokens.push_back(kClassificationToken);
+  // For query input.
+  for (const auto& query_token : query_tokens) {
+    tokens.push_back(query_token);
+  }
+  // For Separation.
+  tokens.push_back(kSeparator);
+
+  std::vector<int> input_ids(max_seq_len, 0);
+  std::vector<int> input_mask(max_seq_len, 0);
+  // Convert tokens back into ids and set mask
+  for (int i = 0; i < tokens.size(); ++i) {
+    tokenizer_->LookupId(tokens[i], &input_ids[i]);
+    input_mask[i] = 1;
+  }
+  //                             |<-----------max_seq_len--------->|
+  // input_ids                 [CLS] s1  s2...  sn [SEP]  0  0...  0
+  // input_masks                 1    1   1...  1    1    0  0...  0
+  // segment_ids                 0    0   0...  0    0    0  0...  0
+
+  RETURN_IF_ERROR(PopulateTensor(input_ids, ids_tensor));
+  RETURN_IF_ERROR(PopulateTensor(input_mask, mask_tensor));
+  RETURN_IF_ERROR(
+      PopulateTensor(std::vector<int>(max_seq_len, 0), segment_ids_tensor));
+
+  return absl::OkStatus();
+}
+
+StatusOr<std::vector<core::Category>> BertNLClassifier::Postprocess(
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const std::string& /*input*/) {
+  if (output_tensors.size() != 1) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        absl::StrFormat("BertNLClassifier models are expected to have only 1 "
+                        "output, found %d",
+                        output_tensors.size()),
+        TfLiteSupportStatus::kInvalidNumOutputTensorsError);
+  }
+  const TfLiteTensor* scores = FindTensorByName(
+      output_tensors, GetMetadataExtractor()->GetOutputTensorMetadata(),
+      kScoreTensorName);
+
+  // optional labels extracted from metadata
+  return BuildResults(scores, /*labels=*/nullptr);
+}
+
+StatusOr<std::unique_ptr<BertNLClassifier>> BertNLClassifier::CreateFromOptions(
+    const BertNLClassifierOptions& options,
+    std::unique_ptr<tflite::OpResolver> resolver) {
+  RETURN_IF_ERROR(SanityCheckOptions(options));
+
+  auto options_copy = absl::make_unique<BertNLClassifierOptions>(options);
+
+  ASSIGN_OR_RETURN(
+      auto bert_nl_classifier,
+      core::TaskAPIFactory::CreateFromBaseOptions<BertNLClassifier>(
+          &options_copy->base_options(), std::move(resolver)));
+  RETURN_IF_ERROR(bert_nl_classifier->Initialize(std::move(options_copy)));
+  return std::move(bert_nl_classifier);
+}
+
+absl::Status BertNLClassifier::Initialize(
+    std::unique_ptr<BertNLClassifierOptions> options) {
+  options_ = std::move(options);
+  // Set up mandatory tokenizer from metadata.
+  const ProcessUnit* tokenizer_process_unit =
+      GetMetadataExtractor()->GetInputProcessUnit(kTokenizerProcessUnitIndex);
+  if (tokenizer_process_unit == nullptr) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "No input process unit found from metadata.",
+        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+  }
+  ASSIGN_OR_RETURN(tokenizer_,
+                   CreateTokenizerFromProcessUnit(tokenizer_process_unit,
+                                                  GetMetadataExtractor()));
+
+  // Set up optional label vector from metadata.
+  TrySetLabelFromMetadata(
+      GetMetadataExtractor()->GetOutputTensorMetadata(kOutputTensorIndex))
+      .IgnoreError();
+
+  return absl::OkStatus();
+}
+
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h
new file mode 100644
index 0000000..91bcfe5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h
@@ -0,0 +1,133 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_NLCLASSIFIER_BERT_NL_CLASSIFIER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_NLCLASSIFIER_BERT_NL_CLASSIFIER_H_
+
+#include <stddef.h>
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "absl/base/macros.h"    // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
+#include "tensorflow/lite/string_type.h"
+#include "tensorflow_lite_support/cc/task/core/category.h"
+#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
+#include "tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+// Classifier API for NLClassification tasks with Bert models, categorizes
+// string into different classes.
+//
+// The API expects a Bert based TFLite model with metadata populated.
+// The metadata should contain the following information:
+//   - input_process_units for Wordpiece/Sentencepiece Tokenizer
+//   - 3 input tensors with names "ids", "mask" and "segment_ids"
+//   - 1 output tensor of type float32[1, 2], with a optionally attached label
+//     file. If a label file is attached, the file should be a plain text file
+//     with one label per line, the number of labels should match the number of
+//     categories the model outputs.
+
+class BertNLClassifier : public tflite::task::text::nlclassifier::NLClassifier {
+ public:
+  using tflite::task::text::nlclassifier::NLClassifier::NLClassifier;
+
+  // Factory function to create a BertNLClassifier from BertNLClassifierOptions.
+  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
+  CreateFromOptions(
+      const BertNLClassifierOptions& options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+
+  // Factory function to create a BertNLClassifier from TFLite model with
+  // metadata.
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
+  CreateFromFile(
+      const std::string& path_to_model_with_metadata,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>()) {
+    BertNLClassifierOptions options;
+    options.mutable_base_options()->mutable_model_file()->set_file_name(
+        path_to_model_with_metadata);
+    return CreateFromOptions(options, std::move(resolver));
+  }
+
+  // Factory function to create a BertNLClassifier from in memory buffer of a
+  // TFLite model with metadata.
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
+  CreateFromBuffer(
+      const char* model_with_metadata_buffer_data,
+      size_t model_with_metadata_buffer_size,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>()) {
+    BertNLClassifierOptions options;
+    options.mutable_base_options()->mutable_model_file()->set_file_content(
+        model_with_metadata_buffer_data, model_with_metadata_buffer_size);
+    return CreateFromOptions(options, std::move(resolver));
+  }
+
+  // Factory function to create a BertNLClassifier from the file descriptor of a
+  // TFLite model with metadata.
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
+  CreateFromFd(
+      int fd,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>()) {
+    BertNLClassifierOptions options;
+    options.mutable_base_options()
+        ->mutable_model_file()
+        ->mutable_file_descriptor_meta()
+        ->set_fd(fd);
+    return CreateFromOptions(options, std::move(resolver));
+  }
+
+ protected:
+  // Run tokenization on input text and construct three input tensors ids, mask
+  // and segment_ids for the model input.
+  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
+                          const std::string& input) override;
+
+  // Extract model output and create results with label file attached in
+  // metadata. If no label file is attached, use output score index as labels.
+  tflite::support::StatusOr<std::vector<core::Category>> Postprocess(
+      const std::vector<const TfLiteTensor*>& output_tensors,
+      const std::string& input) override;
+
+ private:
+  // Initialize the API with the tokenizer and label files set in the metadata.
+  absl::Status Initialize(std::unique_ptr<BertNLClassifierOptions> options);
+
+  std::unique_ptr<tflite::support::text::tokenizer::Tokenizer> tokenizer_;
+
+  std::unique_ptr<BertNLClassifierOptions> options_;
+};
+
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_NLCLASSIFIER_BERT_NL_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc
new file mode 100644
index 0000000..591b70e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.cc
@@ -0,0 +1,423 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
+
+#include "absl/status/status.h"      // from @com_google_absl
+#include "absl/strings/str_join.h"   // from @com_google_absl
+#include "absl/strings/str_split.h"  // from @com_google_absl
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h"
+#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+constexpr char kIdsTensorName[] = "ids";
+constexpr char kMaskTensorName[] = "mask";
+constexpr char kSegmentIdsTensorName[] = "segment_ids";
+constexpr char kEndLogitsTensorName[] = "end_logits";
+constexpr char kStartLogitsTensorName[] = "start_logits";
+
+using ::absl::StatusCode;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::support::text::tokenizer::BertTokenizer;
+using ::tflite::support::text::tokenizer::CreateTokenizerFromProcessUnit;
+using ::tflite::support::text::tokenizer::SentencePieceTokenizer;
+using ::tflite::support::text::tokenizer::TokenizerResult;
+using ::tflite::task::core::FindTensorByName;
+using ::tflite::task::core::PopulateTensor;
+using ::tflite::task::core::PopulateVector;
+using ::tflite::task::core::ReverseSortIndices;
+
+namespace {
+constexpr int kTokenizerProcessUnitIndex = 0;
+
+absl::Status SanityCheckOptions(const BertQuestionAnswererOptions& options) {
+  if (!options.has_base_options()) {
+    return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                   "Missing mandatory `base_options` field",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+}  // namespace
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateFromOptions(
+    const BertQuestionAnswererOptions& options,
+    std::unique_ptr<tflite::OpResolver> resolver) {
+  RETURN_IF_ERROR(SanityCheckOptions(options));
+
+  // Copy options to ensure the ExternalFile outlives the duration of this
+  // created BertQuestionAnswerer object.
+  auto options_copy = absl::make_unique<BertQuestionAnswererOptions>(options);
+
+  ASSIGN_OR_RETURN(
+      auto bert_question_answerer,
+      core::TaskAPIFactory::CreateFromBaseOptions<BertQuestionAnswerer>(
+          &options_copy->base_options(), std::move(resolver)));
+  RETURN_IF_ERROR(
+      bert_question_answerer->InitializeFromMetadata(std::move(options_copy)));
+  return std::move(bert_question_answerer);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateFromFile(
+    const std::string& path_to_model_with_metadata) {
+  BertQuestionAnswererOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      path_to_model_with_metadata);
+  return CreateFromOptions(options);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateFromBuffer(
+    const char* model_with_metadata_buffer_data,
+    size_t model_with_metadata_buffer_size) {
+  BertQuestionAnswererOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_content(
+      model_with_metadata_buffer_data, model_with_metadata_buffer_size);
+  return CreateFromOptions(options);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>> BertQuestionAnswerer::CreateFromFd(
+    int fd) {
+  BertQuestionAnswererOptions options;
+  options.mutable_base_options()
+      ->mutable_model_file()
+      ->mutable_file_descriptor_meta()
+      ->set_fd(fd);
+  return CreateFromOptions(options);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
+    const std::string& path_to_model,
+    const std::string& path_to_vocab) {
+  std::unique_ptr<BertQuestionAnswerer> api_to_init;
+  ASSIGN_OR_RETURN(
+      api_to_init,
+      core::TaskAPIFactory::CreateFromFile<BertQuestionAnswerer>(
+          path_to_model,
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+          kNumLiteThreads));
+  api_to_init->InitializeBertTokenizer(path_to_vocab);
+  return std::move(api_to_init);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
+    const char* model_buffer_data,
+    size_t model_buffer_size,
+    const char* vocab_buffer_data,
+    size_t vocab_buffer_size) {
+  std::unique_ptr<BertQuestionAnswerer> api_to_init;
+  ASSIGN_OR_RETURN(
+      api_to_init,
+      core::TaskAPIFactory::CreateFromBuffer<BertQuestionAnswerer>(
+          model_buffer_data, model_buffer_size,
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+          kNumLiteThreads));
+  api_to_init->InitializeBertTokenizerFromBinary(vocab_buffer_data,
+                                                 vocab_buffer_size);
+  return std::move(api_to_init);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateAlbertQuestionAnswererFromFile(
+    const std::string& path_to_model,
+    const std::string& path_to_spmodel) {
+  std::unique_ptr<BertQuestionAnswerer> api_to_init;
+  ASSIGN_OR_RETURN(
+      api_to_init,
+      core::TaskAPIFactory::CreateFromFile<BertQuestionAnswerer>(
+          path_to_model,
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+          kNumLiteThreads));
+  api_to_init->InitializeSentencepieceTokenizer(path_to_spmodel);
+  return std::move(api_to_init);
+}
+
+StatusOr<std::unique_ptr<QuestionAnswerer>>
+BertQuestionAnswerer::CreateAlbertQuestionAnswererFromBuffer(
+    const char* model_buffer_data,
+    size_t model_buffer_size,
+    const char* spmodel_buffer_data,
+    size_t spmodel_buffer_size) {
+  std::unique_ptr<BertQuestionAnswerer> api_to_init;
+  ASSIGN_OR_RETURN(
+      api_to_init,
+      core::TaskAPIFactory::CreateFromBuffer<BertQuestionAnswerer>(
+          model_buffer_data, model_buffer_size,
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>(),
+          kNumLiteThreads));
+  api_to_init->InitializeSentencepieceTokenizerFromBinary(spmodel_buffer_data,
+                                                          spmodel_buffer_size);
+  return std::move(api_to_init);
+}
+
+std::vector<QaAnswer> BertQuestionAnswerer::Answer(
+    const std::string& context,
+    const std::string& question) {
+  // The BertQuestionAnswererer implementation for Preprocess() and
+  // Postprocess() never returns errors: just call value().
+  return Infer(context, question).value();
+}
+
+absl::Status BertQuestionAnswerer::Preprocess(
+    const std::vector<TfLiteTensor*>& input_tensors,
+    const std::string& context,
+    const std::string& query) {
+  auto* input_tensor_metadatas =
+      GetMetadataExtractor()->GetInputTensorMetadata();
+  TfLiteTensor* ids_tensor =
+      input_tensor_metadatas
+          ? FindTensorByName(input_tensors, input_tensor_metadatas,
+                             kIdsTensorName)
+          : input_tensors[0];
+  TfLiteTensor* mask_tensor =
+      input_tensor_metadatas
+          ? FindTensorByName(input_tensors, input_tensor_metadatas,
+                             kMaskTensorName)
+          : input_tensors[1];
+  TfLiteTensor* segment_ids_tensor =
+      input_tensor_metadatas
+          ? FindTensorByName(input_tensors, input_tensor_metadatas,
+                             kSegmentIdsTensorName)
+          : input_tensors[2];
+
+  token_to_orig_map_.clear();
+
+  // The orig_tokens is used for recovering the answer string from the index,
+  // while the processed_tokens is lower-cased and used to generate input of
+  // the model.
+  orig_tokens_ = absl::StrSplit(context, absl::ByChar(' '), absl::SkipEmpty());
+  std::vector<std::string> processed_tokens(orig_tokens_);
+
+  std::string processed_query = query;
+  if (kUseLowerCase) {
+    for (auto& token : processed_tokens) {
+      absl::AsciiStrToLower(&token);
+    }
+    absl::AsciiStrToLower(&processed_query);
+  }
+
+  TokenizerResult query_tokenize_results;
+  query_tokenize_results = tokenizer_->Tokenize(processed_query);
+
+  std::vector<std::string> query_tokens = query_tokenize_results.subwords;
+  if (query_tokens.size() > kMaxQueryLen) {
+    query_tokens.resize(kMaxQueryLen);
+  }
+
+  // Example:
+  // context:             tokenize     me  please
+  // all_doc_tokens:      token ##ize  me  plea ##se
+  // token_to_orig_index: [0,   0,     1,  2,   2]
+
+  std::vector<std::string> all_doc_tokens;
+  std::vector<int> token_to_orig_index;
+  for (size_t i = 0; i < processed_tokens.size(); i++) {
+    const std::string& token = processed_tokens[i];
+    std::vector<std::string> sub_tokens = tokenizer_->Tokenize(token).subwords;
+    for (const std::string& sub_token : sub_tokens) {
+      token_to_orig_index.emplace_back(i);
+      all_doc_tokens.emplace_back(sub_token);
+    }
+  }
+
+  // -3 accounts for [CLS], [SEP] and [SEP].
+  int max_context_len = kMaxSeqLen - query_tokens.size() - 3;
+  if (all_doc_tokens.size() > max_context_len) {
+    all_doc_tokens.resize(max_context_len);
+  }
+
+  std::vector<std::string> tokens;
+  tokens.reserve(3 + query_tokens.size() + all_doc_tokens.size());
+  std::vector<int> segment_ids;
+  segment_ids.reserve(kMaxSeqLen);
+
+  // Start of generating the features.
+  tokens.emplace_back("[CLS]");
+  segment_ids.emplace_back(0);
+
+  // For query input.
+  for (const auto& query_token : query_tokens) {
+    tokens.emplace_back(query_token);
+    segment_ids.emplace_back(0);
+  }
+
+  // For Separation.
+  tokens.emplace_back("[SEP]");
+  segment_ids.emplace_back(0);
+
+  // For Text Input.
+  for (int i = 0; i < all_doc_tokens.size(); i++) {
+    auto& doc_token = all_doc_tokens[i];
+    tokens.emplace_back(doc_token);
+    segment_ids.emplace_back(1);
+    token_to_orig_map_[tokens.size()] = token_to_orig_index[i];
+  }
+
+  // For ending mark.
+  tokens.emplace_back("[SEP]");
+  segment_ids.emplace_back(1);
+
+  std::vector<int> input_ids(tokens.size());
+  input_ids.reserve(kMaxSeqLen);
+  // Convert tokens back into ids
+  for (int i = 0; i < tokens.size(); i++) {
+    auto& token = tokens[i];
+    tokenizer_->LookupId(token, &input_ids[i]);
+  }
+
+  std::vector<int> input_mask;
+  input_mask.reserve(kMaxSeqLen);
+  input_mask.insert(input_mask.end(), tokens.size(), 1);
+
+  int zeros_to_pad = kMaxSeqLen - input_ids.size();
+  input_ids.insert(input_ids.end(), zeros_to_pad, 0);
+  input_mask.insert(input_mask.end(), zeros_to_pad, 0);
+  segment_ids.insert(segment_ids.end(), zeros_to_pad, 0);
+
+  // input_ids INT32[1, 384]
+  RETURN_IF_ERROR(PopulateTensor(input_ids, ids_tensor));
+  // input_mask INT32[1, 384]
+  RETURN_IF_ERROR(PopulateTensor(input_mask, mask_tensor));
+  // segment_ids INT32[1, 384]
+  RETURN_IF_ERROR(PopulateTensor(segment_ids, segment_ids_tensor));
+
+  return absl::OkStatus();
+}
+
+StatusOr<std::vector<QaAnswer>> BertQuestionAnswerer::Postprocess(
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const std::string& /*lowercased_context*/,
+    const std::string& /*lowercased_query*/) {
+  auto* output_tensor_metadatas =
+      GetMetadataExtractor()->GetOutputTensorMetadata();
+
+  const TfLiteTensor* end_logits_tensor =
+      output_tensor_metadatas
+          ? FindTensorByName(output_tensors, output_tensor_metadatas,
+                             kEndLogitsTensorName)
+          : output_tensors[0];
+  const TfLiteTensor* start_logits_tensor =
+      output_tensor_metadatas
+          ? FindTensorByName(output_tensors, output_tensor_metadatas,
+                             kStartLogitsTensorName)
+          : output_tensors[1];
+
+  std::vector<float> end_logits;
+  std::vector<float> start_logits;
+
+  // end_logits FLOAT[1, 384]
+  RETURN_IF_ERROR(PopulateVector(end_logits_tensor, &end_logits));
+  // start_logits FLOAT[1, 384]
+  RETURN_IF_ERROR(PopulateVector(start_logits_tensor, &start_logits));
+
+  auto start_indices = ReverseSortIndices(start_logits);
+  auto end_indices = ReverseSortIndices(end_logits);
+
+  std::vector<QaAnswer::Pos> orig_results;
+  for (int start_index = 0; start_index < kPredictAnsNum; start_index++) {
+    for (int end_index = 0; end_index < kPredictAnsNum; end_index++) {
+      int start = start_indices[start_index];
+      int end = end_indices[end_index];
+
+      if (!token_to_orig_map_.contains(start + kOutputOffset) ||
+          !token_to_orig_map_.contains(end + kOutputOffset) || end < start ||
+          (end - start + 1) > kMaxAnsLen) {
+        continue;
+      }
+      orig_results.emplace_back(
+          QaAnswer::Pos(start, end, start_logits[start] + end_logits[end]));
+    }
+  }
+
+  std::sort(orig_results.begin(), orig_results.end());
+
+  std::vector<QaAnswer> answers;
+  for (int i = 0; i < orig_results.size() && i < kPredictAnsNum; i++) {
+    auto orig_pos = orig_results[i];
+    answers.emplace_back(
+        orig_pos.start > 0 ? ConvertIndexToString(orig_pos.start, orig_pos.end)
+                           : "",
+        orig_pos);
+  }
+
+  return answers;
+}
+
+std::string BertQuestionAnswerer::ConvertIndexToString(int start, int end) {
+  int start_index = token_to_orig_map_[start + kOutputOffset];
+  int end_index = token_to_orig_map_[end + kOutputOffset];
+
+  return absl::StrJoin(orig_tokens_.begin() + start_index,
+                       orig_tokens_.begin() + end_index + 1, " ");
+}
+
+absl::Status BertQuestionAnswerer::InitializeFromMetadata(
+    std::unique_ptr<BertQuestionAnswererOptions> options) {
+  options_ = std::move(options);
+
+  const ProcessUnit* tokenizer_process_unit =
+      GetMetadataExtractor()->GetInputProcessUnit(kTokenizerProcessUnitIndex);
+  if (tokenizer_process_unit == nullptr) {
+    return CreateStatusWithPayload(
+        absl::StatusCode::kInvalidArgument,
+        "No input process unit found from metadata.",
+        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+  }
+  ASSIGN_OR_RETURN(tokenizer_,
+                   CreateTokenizerFromProcessUnit(tokenizer_process_unit,
+                                                  GetMetadataExtractor()));
+  return absl::OkStatus();
+}
+
+void BertQuestionAnswerer::InitializeBertTokenizer(
+    const std::string& path_to_vocab) {
+  tokenizer_ = absl::make_unique<BertTokenizer>(path_to_vocab);
+}
+
+void BertQuestionAnswerer::InitializeBertTokenizerFromBinary(
+    const char* vocab_buffer_data,
+    size_t vocab_buffer_size) {
+  tokenizer_ =
+      absl::make_unique<BertTokenizer>(vocab_buffer_data, vocab_buffer_size);
+}
+
+void BertQuestionAnswerer::InitializeSentencepieceTokenizer(
+    const std::string& path_to_spmodel) {
+  tokenizer_ = absl::make_unique<SentencePieceTokenizer>(path_to_spmodel);
+}
+
+void BertQuestionAnswerer::InitializeSentencepieceTokenizerFromBinary(
+    const char* spmodel_buffer_data,
+    size_t spmodel_buffer_size) {
+  tokenizer_ = absl::make_unique<SentencePieceTokenizer>(spmodel_buffer_data,
+                                                         spmodel_buffer_size);
+}
+
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h
new file mode 100644
index 0000000..52ec835
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_question_answerer.h
@@ -0,0 +1,160 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_BERT_QUESTION_ANSWERER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_BERT_QUESTION_ANSWERER_H_
+
+#include "absl/base/macros.h"              // from @com_google_absl
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/question_answerer.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h"
+#include "tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+// BertQA task API, performs tokenization for models (BERT, Albert, etc.) in
+// preprocess and returns most possible answers.
+//
+// In particular, the branch of BERT models use WordPiece tokenizer, and the
+// branch of Albert models use SentencePiece tokenizer, respectively.
+//
+// The API expects a Bert based TFLite model with metadata populated.
+// The metadata should contain the following information:
+//   - input_process_units for Wordpiece/Sentencepiece Tokenizer. Wordpiece
+//         Tokenizer can be used for a MobileBert[0] model, Sentencepiece
+//         Tokenizer Tokenizer can be used for an Albert[1] model.
+//   - 3 input tensors with names "ids", "mask" and "segment_ids".
+//   - 2 output tensors with names "end_logits" and "start_logits".
+//   [0]: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
+//   [1]: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
+//
+// See the public documentation for more information:
+// https://www.tensorflow.org/lite/inference_with_metadata/task_library/bert_question_answerer
+
+class BertQuestionAnswerer : public QuestionAnswerer {
+ public:
+  // TODO(b/150904655): add support to parameterize.
+  static constexpr int kMaxQueryLen = 64;
+  static constexpr int kMaxSeqLen = 384;
+  static constexpr int kPredictAnsNum = 5;
+  static constexpr int kMaxAnsLen = 32;
+  // TODO(b/151954803): clarify the offset usage
+  static constexpr int kOutputOffset = 1;
+  static constexpr int kNumLiteThreads = 4;
+  static constexpr bool kUseLowerCase = true;
+
+  // Factory function to create a `BertQuestionAnswerer` from
+  // `BertQuestionAnswererOptions`.
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateFromOptions(
+      const BertQuestionAnswererOptions& options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateFromFile(const std::string& path_to_model_with_metadata);
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateFromBuffer(const char* model_with_metadata_buffer_data,
+                   size_t model_with_metadata_buffer_size);
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateFromFd(int fd);
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateBertQuestionAnswererFromFile(const std::string& path_to_model,
+                                     const std::string& path_to_vocab);
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateBertQuestionAnswererFromBuffer(const char* model_buffer_data,
+                                       size_t model_buffer_size,
+                                       const char* vocab_buffer_data,
+                                       size_t vocab_buffer_size);
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateAlbertQuestionAnswererFromFile(const std::string& path_to_model,
+                                       const std::string& path_to_spmodel);
+
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
+  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
+  CreateAlbertQuestionAnswererFromBuffer(const char* model_buffer_data,
+                                         size_t model_buffer_size,
+                                         const char* spmodel_buffer_data,
+                                         size_t spmodel_buffer_size);
+
+  explicit BertQuestionAnswerer(std::unique_ptr<core::TfLiteEngine> engine)
+      : QuestionAnswerer(std::move(engine)) {}
+
+  // Answers question based on the context. Could be empty if no answer was
+  // found from the given context.
+  std::vector<QaAnswer> Answer(const std::string& context,
+                               const std::string& question) override;
+
+ private:
+  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
+                          const std::string& lowercased_context,
+                          const std::string& lowercased_query) override;
+
+  tflite::support::StatusOr<std::vector<QaAnswer>> Postprocess(
+      const std::vector<const TfLiteTensor*>& output_tensors,
+      const std::string& lowercased_context,
+      const std::string& lowercased_query) override;
+
+  // Initialize API with a BertTokenizer from the vocabulary file.
+  void InitializeBertTokenizer(const std::string& path_to_vocab);
+  // Initialize API with a BertTokenizer from the vocabulary buffer.
+  void InitializeBertTokenizerFromBinary(const char* vocab_buffer_data,
+                                         size_t vocab_buffer_size);
+
+  // Initialize API with a SentencepieceTokenizer from the model file.
+  void InitializeSentencepieceTokenizer(const std::string& path_to_spmodel);
+  // Initialize API with a SentencepieceTokenizer from the model buffer.
+  void InitializeSentencepieceTokenizerFromBinary(
+      const char* spmodel_buffer_data,
+      size_t spmodel_buffer_size);
+
+  // Initialize the API with the tokenizer set in the metadata.
+  absl::Status InitializeFromMetadata(
+      std::unique_ptr<BertQuestionAnswererOptions> options);
+
+  std::string ConvertIndexToString(int start, int end);
+
+  std::unique_ptr<tflite::support::text::tokenizer::Tokenizer> tokenizer_;
+  // Maps index of input token to index of untokenized word from original input.
+  absl::flat_hash_map<size_t, size_t> token_to_orig_map_;
+  // Original tokens of context.
+  std::vector<std::string> orig_tokens_;
+  std::unique_ptr<BertQuestionAnswererOptions> options_;
+};
+
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_BERT_QUESTION_ANSWERER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/BUILD
index 33b6f6a..8a5ae2b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/BUILD
@@ -1,15 +1,14 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_library_with_tflite",
+)
+
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
     licenses = ["notice"],  # Apache 2.0
 )
 
-exports_files([
-    "bert_nl_classifier_c_api.h",
-    "nl_classifier_c_api.h",
-    "nl_classifier_c_api_common.h",
-])
-
-cc_library(
+cc_library_with_tflite(
     name = "nl_classifier",
     srcs = [
         "nl_classifier.cc",
@@ -17,102 +16,30 @@
     hdrs = [
         "nl_classifier.h",
     ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/core:base_task_api",
         "//tensorflow_lite_support/cc/task/core:category",
-        "//tensorflow_lite_support/cc/task/core:task_api_factory",
         "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/text/proto:nl_classifier_options_proto_inc",
         "//tensorflow_lite_support/cc/text/tokenizers:regex_tokenizer",
         "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
         "//tensorflow_lite_support/cc/utils:common_utils",
         "//tensorflow_lite_support/metadata/cc:metadata_extractor",
         "@com_google_absl//absl/algorithm:container",
+        "@com_google_absl//absl/base:core_headers",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
         "@flatbuffers",
         "@org_tensorflow//tensorflow/lite:string",
         "@org_tensorflow//tensorflow/lite/c:common",
         "@org_tensorflow//tensorflow/lite/core/api",
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
         "@org_tensorflow//tensorflow/lite/kernels/internal:tensor",
     ],
 )
-
-cc_library(
-    name = "nl_classifier_c_api",
-    srcs = [
-        "nl_classifier_c_api.cc",
-    ],
-    hdrs = [
-        "nl_classifier_c_api.h",
-        "nl_classifier_c_api_common.h",
-    ],
-    visibility = ["//tensorflow_lite_support:__subpackages__"],
-    deps = [
-        ":nl_classifier",
-        ":nl_classifier_c_api_common",
-        "//tensorflow_lite_support/cc/task/core:category",
-        "@com_google_absl//absl/strings",
-    ],
-)
-
-cc_library(
-    name = "bert_nl_classifier",
-    srcs = [
-        "bert_nl_classifier.cc",
-    ],
-    hdrs = [
-        "bert_nl_classifier.h",
-    ],
-    deps = [
-        ":nl_classifier",
-        "//tensorflow_lite_support/cc:common",
-        "//tensorflow_lite_support/cc/port:status_macros",
-        "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/core:category",
-        "//tensorflow_lite_support/cc/task/core:task_api_factory",
-        "//tensorflow_lite_support/cc/task/core:task_utils",
-        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
-        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer_utils",
-        "//tensorflow_lite_support/metadata/cc:metadata_extractor",
-        "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings",
-        "@com_google_absl//absl/strings:str_format",
-        "@org_tensorflow//tensorflow/lite:string",
-        "@org_tensorflow//tensorflow/lite/c:common",
-        "@org_tensorflow//tensorflow/lite/core/api",
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-    ],
-)
-
-cc_library(
-    name = "bert_nl_classifier_c_api",
-    srcs = [
-        "bert_nl_classifier_c_api.cc",
-    ],
-    hdrs = [
-        "bert_nl_classifier_c_api.h",
-        "nl_classifier_c_api_common.h",
-    ],
-    visibility = ["//tensorflow_lite_support:__subpackages__"],
-    deps = [
-        ":bert_nl_classifier",
-        ":nl_classifier_c_api_common",
-        "//tensorflow_lite_support/cc/task/core:category",
-        "@com_google_absl//absl/strings",
-    ],
-)
-
-cc_library(
-    name = "nl_classifier_c_api_common",
-    srcs = [
-        "nl_classifier_c_api_common.cc",
-    ],
-    hdrs = [
-        "nl_classifier_c_api_common.h",
-    ],
-    visibility = ["//tensorflow_lite_support:__subpackages__"],
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.cc
deleted file mode 100644
index e992b1c..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.cc
+++ /dev/null
@@ -1,198 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h"
-
-#include <stddef.h>
-
-#include <memory>
-#include <string>
-#include <utility>
-#include <vector>
-
-#include "absl/status/status.h"
-#include "absl/strings/ascii.h"
-#include "absl/strings/str_format.h"
-#include "tensorflow/lite/c/common.h"
-#include "tensorflow/lite/core/api/op_resolver.h"
-#include "tensorflow/lite/string_type.h"
-#include "tensorflow_lite_support/cc/common.h"
-#include "tensorflow_lite_support/cc/port/status_macros.h"
-#include "tensorflow_lite_support/cc/task/core/category.h"
-#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
-#include "tensorflow_lite_support/cc/task/core/task_utils.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h"
-#include "tensorflow_lite_support/metadata/cc/metadata_extractor.h"
-
-namespace tflite {
-namespace task {
-namespace text {
-namespace nlclassifier {
-
-using ::tflite::support::CreateStatusWithPayload;
-using ::tflite::support::StatusOr;
-using ::tflite::support::TfLiteSupportStatus;
-using ::tflite::support::text::tokenizer::CreateTokenizerFromProcessUnit;
-using ::tflite::support::text::tokenizer::TokenizerResult;
-using ::tflite::task::core::FindTensorByName;
-using ::tflite::task::core::PopulateTensor;
-
-namespace {
-constexpr char kIdsTensorName[] = "ids";
-constexpr char kMaskTensorName[] = "mask";
-constexpr char kSegmentIdsTensorName[] = "segment_ids";
-constexpr char kScoreTensorName[] = "probability";
-constexpr char kClassificationToken[] = "[CLS]";
-constexpr char kSeparator[] = "[SEP]";
-constexpr int kTokenizerProcessUnitIndex = 0;
-}  // namespace
-
-absl::Status BertNLClassifier::Preprocess(
-    const std::vector<TfLiteTensor*>& input_tensors,
-    const std::string& input) {
-  auto* input_tensor_metadatas =
-      GetMetadataExtractor()->GetInputTensorMetadata();
-  auto* ids_tensor =
-      FindTensorByName(input_tensors, input_tensor_metadatas, kIdsTensorName);
-  auto* mask_tensor =
-      FindTensorByName(input_tensors, input_tensor_metadatas, kMaskTensorName);
-  auto* segment_ids_tensor = FindTensorByName(
-      input_tensors, input_tensor_metadatas, kSegmentIdsTensorName);
-
-  std::string processed_input = input;
-  absl::AsciiStrToLower(&processed_input);
-
-  TokenizerResult input_tokenize_results;
-  input_tokenize_results = tokenizer_->Tokenize(processed_input);
-
-  // 2 accounts for [CLS], [SEP]
-  absl::Span<const std::string> query_tokens =
-      absl::MakeSpan(input_tokenize_results.subwords.data(),
-                     input_tokenize_results.subwords.data() +
-                         std::min(static_cast<size_t>(kMaxSeqLen - 2),
-                                  input_tokenize_results.subwords.size()));
-
-  std::vector<std::string> tokens;
-  tokens.reserve(2 + query_tokens.size());
-  // Start of generating the features.
-  tokens.push_back(kClassificationToken);
-  // For query input.
-  for (const auto& query_token : query_tokens) {
-    tokens.push_back(query_token);
-  }
-  // For Separation.
-  tokens.push_back(kSeparator);
-
-  std::vector<int> input_ids(kMaxSeqLen, 0);
-  std::vector<int> input_mask(kMaxSeqLen, 0);
-  // Convert tokens back into ids and set mask
-  for (int i = 0; i < tokens.size(); ++i) {
-    tokenizer_->LookupId(tokens[i], &input_ids[i]);
-    input_mask[i] = 1;
-  }
-  //                             |<-----------kMaxSeqLen---------->|
-  // input_ids                 [CLS] s1  s2...  sn [SEP]  0  0...  0
-  // input_masks                 1    1   1...  1    1    0  0...  0
-  // segment_ids                 0    0   0...  0    0    0  0...  0
-
-  PopulateTensor(input_ids, ids_tensor);
-  PopulateTensor(input_mask, mask_tensor);
-  PopulateTensor(std::vector<int>(kMaxSeqLen, 0), segment_ids_tensor);
-
-  return absl::OkStatus();
-}
-
-StatusOr<std::vector<core::Category>> BertNLClassifier::Postprocess(
-    const std::vector<const TfLiteTensor*>& output_tensors,
-    const std::string& /*input*/) {
-  if (output_tensors.size() != 1) {
-    return CreateStatusWithPayload(
-        absl::StatusCode::kInvalidArgument,
-        absl::StrFormat("BertNLClassifier models are expected to have only 1 "
-                        "output, found %d",
-                        output_tensors.size()),
-        TfLiteSupportStatus::kInvalidNumOutputTensorsError);
-  }
-  const TfLiteTensor* scores = FindTensorByName(
-      output_tensors, GetMetadataExtractor()->GetOutputTensorMetadata(),
-      kScoreTensorName);
-
-  // optional labels extracted from metadata
-  return BuildResults(scores, /*labels=*/nullptr);
-}
-
-StatusOr<std::unique_ptr<BertNLClassifier>> BertNLClassifier::CreateFromFile(
-    const std::string& path_to_model_with_metadata,
-    std::unique_ptr<tflite::OpResolver> resolver) {
-  std::unique_ptr<BertNLClassifier> bert_nl_classifier;
-  ASSIGN_OR_RETURN(bert_nl_classifier,
-                   core::TaskAPIFactory::CreateFromFile<BertNLClassifier>(
-                       path_to_model_with_metadata, std::move(resolver)));
-  RETURN_IF_ERROR(bert_nl_classifier->InitializeFromMetadata());
-  return std::move(bert_nl_classifier);
-}
-
-StatusOr<std::unique_ptr<BertNLClassifier>> BertNLClassifier::CreateFromBuffer(
-    const char* model_with_metadata_buffer_data,
-    size_t model_with_metadata_buffer_size,
-    std::unique_ptr<tflite::OpResolver> resolver) {
-  std::unique_ptr<BertNLClassifier> bert_nl_classifier;
-  ASSIGN_OR_RETURN(bert_nl_classifier,
-                   core::TaskAPIFactory::CreateFromBuffer<BertNLClassifier>(
-                       model_with_metadata_buffer_data,
-                       model_with_metadata_buffer_size, std::move(resolver)));
-  RETURN_IF_ERROR(bert_nl_classifier->InitializeFromMetadata());
-  return std::move(bert_nl_classifier);
-}
-
-StatusOr<std::unique_ptr<BertNLClassifier>> BertNLClassifier::CreateFromFd(
-    int fd,
-    std::unique_ptr<tflite::OpResolver> resolver) {
-  std::unique_ptr<BertNLClassifier> bert_nl_classifier;
-  ASSIGN_OR_RETURN(
-      bert_nl_classifier,
-      core::TaskAPIFactory::CreateFromFileDescriptor<BertNLClassifier>(
-          fd, std::move(resolver)));
-  RETURN_IF_ERROR(bert_nl_classifier->InitializeFromMetadata());
-  return std::move(bert_nl_classifier);
-}
-
-absl::Status BertNLClassifier::InitializeFromMetadata() {
-  // Set up mandatory tokenizer.
-  const ProcessUnit* tokenizer_process_unit =
-      GetMetadataExtractor()->GetInputProcessUnit(kTokenizerProcessUnitIndex);
-  if (tokenizer_process_unit == nullptr) {
-    return CreateStatusWithPayload(
-        absl::StatusCode::kInvalidArgument,
-        "No input process unit found from metadata.",
-        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
-  }
-  ASSIGN_OR_RETURN(tokenizer_,
-                   CreateTokenizerFromProcessUnit(tokenizer_process_unit,
-                                                  GetMetadataExtractor()));
-
-  // Set up optional label vector.
-  TrySetLabelFromMetadata(
-      GetMetadataExtractor()->GetOutputTensorMetadata(kOutputTensorIndex))
-      .IgnoreError();
-  return absl::OkStatus();
-}
-
-}  // namespace nlclassifier
-}  // namespace text
-}  // namespace task
-}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h
deleted file mode 100644
index e78085d..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h
+++ /dev/null
@@ -1,106 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_BERT_NL_CLASSIFIER_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_BERT_NL_CLASSIFIER_H_
-
-#include <stddef.h>
-
-#include <memory>
-#include <string>
-#include <vector>
-
-#include "absl/status/status.h"
-#include "tensorflow/lite/c/common.h"
-#include "tensorflow/lite/core/api/op_resolver.h"
-#include "tensorflow/lite/kernels/register.h"
-#include "tensorflow/lite/string_type.h"
-#include "tensorflow_lite_support/cc/task/core/category.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
-
-namespace tflite {
-namespace task {
-namespace text {
-namespace nlclassifier {
-
-// Classifier API for NLClassification tasks with Bert models, categorizes
-// string into different classes.
-//
-// The API expects a Bert based TFLite model with metadata populated.
-// The metadata should contain the following information:
-//   - input_process_units for Wordpiece/Sentencepiece Tokenizer
-//   - 3 input tensors with names "ids", "mask" and "segment_ids"
-//   - 1 output tensor of type float32[1, 2], with a optionally attached label
-//     file. If a label file is attached, the file should be a plain text file
-//     with one label per line, the number of labels should match the number of
-//     categories the model outputs.
-
-class BertNLClassifier : public NLClassifier {
- public:
-  using NLClassifier::NLClassifier;
-  // Max number of tokens to pass to the model.
-  static constexpr int kMaxSeqLen = 512;
-
-  // Factory function to create a BertNLClassifier from TFLite model with
-  // metadata.
-  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
-  CreateFromFile(
-      const std::string& path_to_model_with_metadata,
-      std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
-
-  // Factory function to create a BertNLClassifier from in memory buffer of a
-  // TFLite model with metadata.
-  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
-  CreateFromBuffer(
-      const char* model_with_metadata_buffer_data,
-      size_t model_with_metadata_buffer_size,
-      std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
-
-  // Factory function to create a BertNLClassifier from the file descriptor of a
-  // TFLite model with metadata.
-  static tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>>
-  CreateFromFd(
-      int fd,
-      std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
-
- protected:
-  // Run tokenization on input text and construct three input tensors ids, mask
-  // and segment_ids for the model input.
-  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
-                          const std::string& input) override;
-
-  // Extract model output and create results with label file attached in
-  // metadata. If no label file is attached, use output score index as labels.
-  tflite::support::StatusOr<std::vector<core::Category>> Postprocess(
-      const std::vector<const TfLiteTensor*>& output_tensors,
-      const std::string& input) override;
-
- private:
-  // Initialize the API with the tokenizer and label files set in the metadata.
-  absl::Status InitializeFromMetadata();
-
-  std::unique_ptr<tflite::support::text::tokenizer::Tokenizer> tokenizer_;
-};
-
-}  // namespace nlclassifier
-}  // namespace text
-}  // namespace task
-}  // namespace tflite
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_BERT_NL_CLASSIFIER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.cc
deleted file mode 100644
index f42e2b5..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.cc
+++ /dev/null
@@ -1,72 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.h"
-
-#include <memory>
-
-#include "absl/strings/string_view.h"
-#include "tensorflow_lite_support/cc/task/core/category.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h"
-
-using CategoryCPP = ::tflite::task::core::Category;
-using BertNLClassifierCPP =
-    ::tflite::task::text::nlclassifier::BertNLClassifier;
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-struct BertNLClassifier {
-  std::unique_ptr<BertNLClassifierCPP> impl;
-};
-
-BertNLClassifier* BertNLClassifierFromFile(const char* model_path) {
-  auto classifier_status =
-      BertNLClassifierCPP::CreateFromFile(std::string(model_path));
-  if (classifier_status.ok()) {
-    return new BertNLClassifier{.impl = std::unique_ptr<BertNLClassifierCPP>(
-                                    dynamic_cast<BertNLClassifierCPP*>(
-                                        classifier_status.value().release()))};
-  } else {
-    return nullptr;
-  }
-}
-
-Categories* BertNLClassifierClassify(const BertNLClassifier* classifier,
-                                     const char* text) {
-  std::vector<CategoryCPP> results =
-      classifier->impl->Classify(absl::string_view(text).data());
-  size_t size = results.size();
-  auto* categories = new Category[size];
-
-  for (size_t i = 0; i < size; ++i) {
-    categories[i].text = strdup(results[i].class_name.c_str());
-    categories[i].score = results[i].score;
-  }
-
-  auto* c_categories = new Categories;
-  c_categories->size = size;
-  c_categories->categories = categories;
-  return c_categories;
-}
-
-void BertNLClassifierDelete(BertNLClassifier* classifier) {
-  delete classifier;
-}
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.h
deleted file mode 100644
index 674521b9..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.h
+++ /dev/null
@@ -1,61 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_BERT_NL_CLASSIFIER_C_API_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_BERT_NL_CLASSIFIER_C_API_H_
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h"
-// --------------------------------------------------------------------------
-/// C API for BertNLClassifier.
-///
-/// The API leans towards simplicity and uniformity instead of convenience, as
-/// most usage will be by language-specific wrappers. It provides largely the
-/// same set of functionality as that of the C++ TensorFlow Lite
-/// `BertNLClassifier` API, but is useful for shared libraries where having
-/// a stable ABI boundary is important.
-///
-/// Usage:
-/// <pre><code>
-/// // Create the model and interpreter options.
-/// BertNLClassifier* classifier =
-///   BertNLClassifierFromFile("/path/to/model.tflite");
-///
-/// // classification.
-/// Categories* categories = Classify(classifier, context, question);
-///
-/// // Dispose of the API object.
-/// BertNLClassifierrDelete(classifier);
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-typedef struct BertNLClassifier BertNLClassifier;
-
-// Creates BertNLClassifier from model path, returns nullptr if the file
-// doesn't exist or is not a well formatted TFLite model path.
-extern BertNLClassifier* BertNLClassifierFromFile(const char* model_path);
-
-// Invokes the encapsulated TFLite model and classifies the input text.
-extern struct Categories* BertNLClassifierClassify(
-    const BertNLClassifier* classifier,
-    const char* text);
-
-extern void BertNLClassifierDelete(BertNLClassifier* classifier);
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_BERT_NL_CLASSIFIER_C_API_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc
index 693ea6f..6986bcc 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.cc
@@ -21,10 +21,10 @@
 #include <utility>
 #include <vector>
 
-#include "absl/algorithm/container.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_cat.h"
-#include "absl/strings/string_view.h"
+#include "absl/algorithm/container.h"  // from @com_google_absl
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/str_cat.h"      // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/core/api/op_resolver.h"
@@ -59,11 +59,24 @@
 using ::tflite::task::core::Dequantize;
 using ::tflite::task::core::GetStringAtIndex;
 using ::tflite::task::core::PopulateTensor;
+using ::tflite::task::core::TaskAPIFactory;
+// To differenciate it with the struct option,
+// tflite::task::text::nl_classifier::NLClassifierOptions.
+using NLClassifierProtoOptions = ::tflite::task::text::NLClassifierOptions;
 
 namespace {
 constexpr int kRegexTokenizerInputTensorIndex = 0;
 constexpr int kRegexTokenizerProcessUnitIndex = 0;
 
+absl::Status SanityCheckOptions(const NLClassifierProtoOptions& options) {
+  if (!options.has_base_options()) {
+    return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                   "Missing mandatory `base_options` field",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+
 StatusOr<absl::string_view> CheckAndLoadFirstAssociatedFile(
     const flatbuffers::Vector<flatbuffers::Offset<tflite::AssociatedFile>>*
         associated_files,
@@ -133,13 +146,13 @@
         "RegexTokenizer doesn't have <PAD> token.",
         TfLiteSupportStatus::kMetadataInvalidTokenizerError);
   }
-  return regex_tokenizer;
+  return std::move(regex_tokenizer);
 }
 
 }  // namespace
 
 const NLClassifierOptions& NLClassifier::GetOptions() const {
-  return options_;
+  return struct_options_;
 }
 
 absl::Status NLClassifier::TrySetLabelFromMetadata(
@@ -191,7 +204,7 @@
     const std::string& input) {
   TfLiteTensor* input_tensor = FindTensorWithNameOrIndex(
       input_tensors, GetMetadataExtractor()->GetInputTensorMetadata(),
-      options_.input_tensor_name, options_.input_tensor_index);
+      struct_options_.input_tensor_name, struct_options_.input_tensor_index);
   if (input_tensor == nullptr) {
     return CreateStatusWithPayload(
         absl::StatusCode::kInvalidArgument,
@@ -236,9 +249,9 @@
       }
     }
 
-    PopulateTensor(input_tokens, input_tensor);
+    RETURN_IF_ERROR(PopulateTensor(input_tokens, input_tensor));
   } else {
-    PopulateTensor(input, input_tensor);
+    RETURN_IF_ERROR(PopulateTensor(input, input_tensor));
   }
   return absl::OkStatus();
 }
@@ -249,12 +262,12 @@
   return BuildResults(
       FindTensorWithNameOrIndex(
           output_tensors, GetMetadataExtractor()->GetOutputTensorMetadata(),
-          options_.output_score_tensor_name,
-          options_.output_score_tensor_index),
+          struct_options_.output_score_tensor_name,
+          struct_options_.output_score_tensor_index),
       FindTensorWithNameOrIndex(
-          output_tensors, GetMetadataExtractor()->GetInputTensorMetadata(),
-          options_.output_label_tensor_name,
-          options_.output_label_tensor_index));
+          output_tensors, GetMetadataExtractor()->GetOutputTensorMetadata(),
+          struct_options_.output_label_tensor_name,
+          struct_options_.output_label_tensor_index));
 }
 
 std::vector<Category> NLClassifier::BuildResults(const TfLiteTensor* scores,
@@ -298,8 +311,23 @@
 
   return predictions;
 }
+
+absl::Status NLClassifier::Initialize(
+    std::unique_ptr<tflite::task::text::NLClassifierOptions> options) {
+  proto_options_ = std::move(options);
+
+  RETURN_IF_ERROR(Initialize(NLClassifierOptions{
+      .input_tensor_index = proto_options_->input_tensor_index(),
+      .output_score_tensor_index = proto_options_->output_score_tensor_index(),
+      .output_label_tensor_index = proto_options_->output_label_tensor_index(),
+      .input_tensor_name = proto_options_->input_tensor_name(),
+      .output_score_tensor_name = proto_options_->output_score_tensor_name(),
+      .output_label_tensor_name = proto_options_->output_label_tensor_name()}));
+  return absl::OkStatus();
+}
+
 absl::Status NLClassifier::Initialize(const NLClassifierOptions& options) {
-  options_ = options;
+  struct_options_ = options;
   // input tensor should be type STRING
   auto input_tensor = FindTensorWithNameOrIndex(
       GetInputTensors(), GetMetadataExtractor()->GetInputTensorMetadata(),
@@ -399,6 +427,24 @@
   return absl::OkStatus();
 }
 
+/* static */
+StatusOr<std::unique_ptr<NLClassifier>> NLClassifier::CreateFromOptions(
+    const NLClassifierProtoOptions& options,
+    std::unique_ptr<tflite::OpResolver> resolver) {
+  RETURN_IF_ERROR(SanityCheckOptions(options));
+
+  // Copy options to ensure the ExternalFile outlives the duration of this
+  // created NLClassifier object.
+  auto options_copy = absl::make_unique<NLClassifierProtoOptions>(options);
+
+  ASSIGN_OR_RETURN(auto nl_classifier,
+                   TaskAPIFactory::CreateFromBaseOptions<NLClassifier>(
+                       &options_copy->base_options(), std::move(resolver)));
+  RETURN_IF_ERROR(nl_classifier->Initialize(std::move(options_copy)));
+
+  return nl_classifier;
+}
+
 StatusOr<std::unique_ptr<NLClassifier>>
 NLClassifier::CreateFromBufferAndOptions(
     const char* model_buffer_data,
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
index 4055a93..331a6e4 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h
@@ -23,16 +23,18 @@
 #include <string>
 #include <vector>
 
-#include "absl/status/status.h"
+#include "absl/base/macros.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
 #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/core/api/op_resolver.h"
-#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
 #include "tensorflow/lite/string_type.h"
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/base_task_api.h"
 #include "tensorflow_lite_support/cc/task/core/category.h"
+#include "tensorflow_lite_support/cc/task/text/proto/nl_classifier_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h"
 
 namespace tflite {
@@ -87,30 +89,49 @@
  public:
   using BaseTaskApi::BaseTaskApi;
 
-  // Creates a NLClassifier from TFLite model buffer.
+  // Creates an NLClassifier from the provided options. A non-default
+  // OpResolver can be specified in order to support custom Ops or specify a
+  // subset of built-in Ops.
+  //
+  // This is a forward compatible method that uses
+  // `tflite::task::text::NLClassifierOptions`. Factory create methods with
+  // `tflite::task::text::nlclassifier::NLClassifierOptions` will be deprecated.
+  //
+  // TODO(b/182537114): unify the classification options (support the common
+  // classification options) and results across vision/text/audio.
+  static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
+  CreateFromOptions(
+      const tflite::task::text::NLClassifierOptions& options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+
+  // Creates an NLClassifier from TFLite model buffer.
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
   static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
   CreateFromBufferAndOptions(
       const char* model_buffer_data,
       size_t model_buffer_size,
       const NLClassifierOptions& options = {},
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
 
-  // Creates a NLClassifier from TFLite model file.
+  // Creates an NLClassifier from TFLite model file.
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
   static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
   CreateFromFileAndOptions(
       const std::string& path_to_model,
       const NLClassifierOptions& options = {},
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
 
-  // Creates a NLClassifier from TFLite model file descriptor.
+  // Creates an NLClassifier from TFLite model file descriptor.
+  ABSL_DEPRECATED("Prefer using `CreateFromOptions`")
   static tflite::support::StatusOr<std::unique_ptr<NLClassifier>>
   CreateFromFdAndOptions(
       int fd,
       const NLClassifierOptions& options = {},
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
 
   // Performs classification on a string input, returns classified results.
   std::vector<core::Category> Classify(const std::string& text);
@@ -119,7 +140,18 @@
   static constexpr int kOutputTensorIndex = 0;
   static constexpr int kOutputTensorLabelFileIndex = 0;
 
-  absl::Status Initialize(const NLClassifierOptions& options);
+  // Initialize NLClassifier with the proto NLClassifierOptions.
+  absl::Status Initialize(
+      std::unique_ptr<tflite::task::text::NLClassifierOptions> options);
+
+  ABSL_DEPRECATED(
+      "Prefer using `tflite::task::text::NLClassifierOptions` and "
+      "`Initialize(std::unique_ptr<tflite::task::text::NLClassifierOptions> "
+      "options)`")
+  absl::Status Initialize(const NLClassifierOptions& options = {});
+  ABSL_DEPRECATED(
+      "Prefer using `tflite::task::text::NLClassifierOptions` and "
+      "`CreateFromOptions`")
   const NLClassifierOptions& GetOptions() const;
 
   // Try to extract attached label file from metadata and initialize
@@ -170,7 +202,12 @@
   bool HasRegexTokenizerMetadata();
   absl::Status SetupRegexTokenizer();
 
-  NLClassifierOptions options_;
+  std::unique_ptr<tflite::task::text::NLClassifierOptions> proto_options_;
+
+  // Deprecated: using the proto_options_
+  // (tflite::task::text::NLClassifierOptions).
+  NLClassifierOptions struct_options_;
+
   // labels vector initialized from output tensor's associated file, if one
   // exists.
   std::unique_ptr<std::vector<std::string>> labels_vector_;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.cc
deleted file mode 100644
index f498ae9e..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.cc
+++ /dev/null
@@ -1,92 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.h"
-
-#include <memory>
-
-#include "absl/strings/string_view.h"
-#include "tensorflow_lite_support/cc/task/core/category.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
-
-using CategoryCPP = ::tflite::task::core::Category;
-using NLClassifierCPP = ::tflite::task::text::nlclassifier::NLClassifier;
-using NLClassifierOptionsCPP =
-    ::tflite::task::text::nlclassifier::NLClassifierOptions;
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-struct NLClassifier {
-  std::unique_ptr<NLClassifierCPP> impl;
-};
-
-NLClassifier* NLClassifierFromFileAndOptions(
-    const char* model_path,
-    const NLClassifierOptions* options) {
-  auto classifier_status = NLClassifierCPP::CreateFromFileAndOptions(
-      std::string(model_path),
-      {
-          .input_tensor_index = options->input_tensor_index,
-          .output_score_tensor_index = options->output_score_tensor_index,
-          .output_label_tensor_index = options->output_label_tensor_index,
-          .input_tensor_name = !options->input_tensor_name
-                                   ? ""
-                                   : std::string(options->input_tensor_name),
-          .output_score_tensor_name =
-              !options->output_score_tensor_name
-                  ? ""
-                  : std::string(options->output_score_tensor_name),
-          .output_label_tensor_name =
-              !options->output_label_tensor_name
-                  ? ""
-                  : std::string(options->output_label_tensor_name),
-      });
-
-  if (classifier_status.ok()) {
-    return new NLClassifier{
-        .impl = std::unique_ptr<NLClassifierCPP>(dynamic_cast<NLClassifierCPP*>(
-            classifier_status.value().release()))};
-  } else {
-    return nullptr;
-  }
-}
-
-Categories* NLClassifierClassify(const NLClassifier* classifier,
-                                 const char* text) {
-  std::vector<CategoryCPP> results =
-      classifier->impl->Classify(absl::string_view(text).data());
-  size_t size = results.size();
-  auto* categories = new Category[size];
-
-  for (size_t i = 0; i < size; ++i) {
-    categories[i].text = strdup(results[i].class_name.c_str());
-    categories[i].score = results[i].score;
-  }
-
-  auto* c_categories = new Categories;
-  c_categories->size = size;
-  c_categories->categories = categories;
-  return c_categories;
-}
-
-void NLClassifierDelete(NLClassifier* classifier) {
-  delete classifier;
-}
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.h
deleted file mode 100644
index 25e2c23..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.h
+++ /dev/null
@@ -1,71 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_C_API_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_C_API_H_
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h"
-// --------------------------------------------------------------------------
-/// C API for NLClassifier.
-///
-/// The API leans towards simplicity and uniformity instead of convenience, as
-/// most usage will be by language-specific wrappers. It provides largely the
-/// same set of functionality as that of the C++ TensorFlow Lite `NLClassifier`
-/// API, but is useful for shared libraries where having a stable ABI boundary
-/// is important.
-///
-/// Usage:
-/// <pre><code>
-/// // Create the model and interpreter options.
-/// NLClassifier* classifier = NLClassifierFromFileAndOptions(
-///   "/path/to/model.tflite");
-///
-/// // classification.
-/// Categories* categories = Classify(classifier, context, question);
-///
-/// // Dispose of the API object.
-/// NLClassifierDelete(classifier);
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-typedef struct NLClassifier NLClassifier;
-
-struct NLClassifierOptions {
-  int input_tensor_index;
-  int output_score_tensor_index;
-  int output_label_tensor_index;
-  const char* input_tensor_name;
-  const char* output_score_tensor_name;
-  const char* output_label_tensor_name;
-};
-
-// Creates NLClassifier from model path and options, returns nullptr if the file
-// doesn't exist or is not a well formatted TFLite model path.
-extern NLClassifier* NLClassifierFromFileAndOptions(
-    const char* model_path,
-    const struct NLClassifierOptions* options);
-
-// Invokes the encapsulated TFLite model and classifies the input text.
-extern struct Categories* NLClassifierClassify(const NLClassifier* classifier,
-                                               const char* text);
-
-extern void NLClassifierDelete(NLClassifier* classifier);
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_C_API_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.cc
deleted file mode 100644
index 817ef3d..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.cc
+++ /dev/null
@@ -1,29 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h"
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-void NLClassifierCategoriesDelete(Categories* categories) {
-  delete[] categories->categories;
-  delete categories;
-}
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h
deleted file mode 100644
index 663c873..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h
+++ /dev/null
@@ -1,43 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_C_API_COMMON_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_C_API_COMMON_H_
-
-// Common structs shared between NLClassifier APIs
-//
-/// // Dispose of the Categories object.
-/// NLClassifierCategoriesDelete(categories);
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-struct Category {
-  char* text;
-  double score;
-};
-
-struct Categories {
-  int size;
-  struct Category* categories;
-};
-
-extern void NLClassifierCategoriesDelete(struct Categories* categories);
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_C_API_COMMON_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/BUILD
new file mode 100644
index 0000000..abc1f24
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/BUILD
@@ -0,0 +1,104 @@
+load("//tensorflow_lite_support/cc/port:build_defs.bzl", "support_cc_proto_library")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+proto_library(
+    name = "nl_classifier_options_proto",
+    srcs = ["nl_classifier_options.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
+    ],
+)
+
+support_cc_proto_library(
+    name = "nl_classifier_options_cc_proto",
+    deps = [
+        ":nl_classifier_options_proto",
+    ],
+)
+
+cc_library(
+    name = "nl_classifier_options_proto_inc",
+    hdrs = ["nl_classifier_options_proto_inc.h"],
+    deps = [
+        ":nl_classifier_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+    ],
+)
+
+proto_library(
+    name = "bert_nl_classifier_options_proto",
+    srcs = ["bert_nl_classifier_options.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "bert_nl_classifier_options_cc_proto",
+    deps = [
+        ":bert_nl_classifier_options_proto",
+    ],
+)
+
+cc_library(
+    name = "bert_nl_classifier_options_proto_inc",
+    hdrs = ["bert_nl_classifier_options_proto_inc.h"],
+    deps = [
+        ":bert_nl_classifier_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+    ],
+)
+
+proto_library(
+    name = "bert_question_answerer_options_proto",
+    srcs = ["bert_question_answerer_options.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "bert_question_answerer_options_cc_proto",
+    deps = [
+        ":bert_question_answerer_options_proto",
+    ],
+)
+
+cc_library(
+    name = "bert_question_answerer_options_proto_inc",
+    hdrs = ["bert_question_answerer_options_proto_inc.h"],
+    deps = [
+        ":bert_question_answerer_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+    ],
+)
+
+proto_library(
+    name = "retrieval_proto",
+    srcs = ["retrieval.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
+        "//tensorflow_lite_support/cc/task/processor/proto:embedding_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "retrieval_cc_proto",
+    deps = [
+        ":retrieval_proto",
+    ],
+)
+
+cc_library(
+    name = "retrieval_proto_inc",
+    hdrs = ["retrieval_proto_inc.h"],
+    deps = [
+        ":retrieval_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:embeddings_proto_inc",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options.proto
new file mode 100644
index 0000000..505ccef
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options.proto
@@ -0,0 +1,34 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.text;
+
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
+
+// Options for setting up a BertNLClassifier.
+// Next Id: 3
+message BertNLClassifierOptions {
+  // Base options for configuring BertNLClassifier, such as specifying the
+  // TfLite model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 1;
+
+  // Max number of tokens to pass to the model.
+  //
+  // Deprecated: max_seq_len is now read from the model (i.e. input tensor size)
+  // automatically.
+  optional int32 max_seq_len = 2 [default = 128];
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options_proto_inc.h
new file mode 100644
index 0000000..59cfddb
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options_proto_inc.h
@@ -0,0 +1,22 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_BERT_NL_CLASSIFIER_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_BERT_NL_CLASSIFIER_OPTIONS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options.pb.h"
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_BERT_NL_CLASSIFIER_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options.proto
new file mode 100644
index 0000000..2b5bcc5f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options.proto
@@ -0,0 +1,28 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.text;
+
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
+
+// Options for setting up a BertQuestionAnswerer.
+// Next Id: 2
+message BertQuestionAnswererOptions {
+  // Base options for configuring BertQuestionAnswerer, such as specifying the
+  // TfLite model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 1;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options_proto_inc.h
new file mode 100644
index 0000000..993d420
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options_proto_inc.h
@@ -0,0 +1,22 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_BERT_QUESTION_ANSWERER_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_BERT_QUESTION_ANSWERER_OPTIONS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/proto/bert_question_answerer_options.pb.h"
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_BERT_QUESTION_ANSWERER_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options.proto
new file mode 100644
index 0000000..6ebb459e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options.proto
@@ -0,0 +1,111 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.text;
+
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
+
+// Options for setting up an NLClassifier.
+// Next Id: 8
+message NLClassifierOptions {
+  // Base options for configuring NLClassifier, such as specifying the
+  // TfLite model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 1;
+
+  // ****************************************************
+  // Configure the input/output tensors for NLClassifier:
+  //
+  // - No special configuration is needed if the model has only one input tensor
+  // and one output tensor.
+  //
+  // - When the model has multiple input or output tensors, use the following
+  // configurations to specifiy the desired tensors:
+  //   -- tensor names: `input_tensor_name`, `output_score_tensor_name`,
+  //   `output_label_tensor_name`
+  //   -- tensor indices: `input_tensor_index`, `output_score_tensor_index`,
+  //   `output_label_tensor_index`
+  // Tensor names has higher priorities than tensor indices in locating the
+  // tensors. It means the tensors will be first located according to tensor
+  // names. If not found, then the tensors will be located according to tensor
+  // indices.
+  //
+  // - Failing to match the input text tensor or output score tensor with
+  // neither tensor names nor tensor indices will trigger a runtime error.
+  // However, failing to locate the output label tensor will not trigger an
+  // error because the label tensor is optional.
+  // ****************************************************
+
+  // Name of the input text tensor, if the model has multiple inputs. Only the
+  // input tensor specified will be used for inference; other input tensors will
+  // be ignored. Default to "INPUT".
+  //
+  // See the "Configure the input/output tensors for NLClassifier" section above
+  // for more details.
+  optional string input_tensor_name = 2 [default = "INPUT"];
+
+  // Name of the output score tensor, if the model has multiple outputs. Default
+  // to "OUTPUT_SCORE".
+  //
+  // See the "Configure the input/output tensors for NLClassifier" section above
+  // for more details.
+  optional string output_score_tensor_name = 3 [default = "OUTPUT_SCORE"];
+
+  // Name of the output label tensor, if the model has multiple outputs. Default
+  // to "OUTPUT_LABEL".
+  //
+  // See the "Configure the input/output tensors for NLClassifier" section above
+  // for more details.
+  //
+  // By default, label file should be packed with
+  // the output score tensor through Model Metadata. See the MetadataWriter for
+  // NLClassifier [1]. NLClassifier reads and parses labels from the label
+  // file automatically. However, some models may output a specific label tensor
+  // instead. In this case, NLClassifier reads labels from the output label
+  // tensor.
+  //
+  // [1]:
+  // https://www.tensorflow.org/lite/convert/metadata_writer_tutorial#natural_language_classifiers
+  optional string output_label_tensor_name = 4 [default = "OUTPUT_LABEL"];
+
+  // Index of the input text tensor among all input tensors, if the model has
+  // multiple inputs. Only the input tensor specified will be used for
+  // inference; other input tensors will be ignored. Default to 0.
+  //
+  // See the "Configure the input/output tensors for NLClassifier" section above
+  // for more details.
+  optional int32 input_tensor_index = 5 [default = 0];
+
+  // Index of the output score tensor among all output tensors, if the model has
+  // multiple outputs. Default to 0.
+  //
+  // See the "Configure the input/output tensors for NLClassifier" section above
+  // for more details.
+  optional int32 output_score_tensor_index = 6 [default = 0];
+
+  // Index of the optional output label tensor among all output tensors, if the
+  // model has multiple outputs.
+  //
+  // See the comment above `output_label_tensor_name` for more information about
+  // what the output label tensor is.
+  //
+  // See the "Configure the input/output tensors for NLClassifier" section above
+  // for more details.
+  //
+  // `output_label_tensor_index` defaults to -1, meaning to disable searching
+  // the output label tensor as it might be optional.
+  optional int32 output_label_tensor_index = 7 [default = -1];
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options_proto_inc.h
new file mode 100644
index 0000000..9c2a2ac
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/nl_classifier_options_proto_inc.h
@@ -0,0 +1,22 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_NL_CLASSIFIER_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_NL_CLASSIFIER_OPTIONS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/proto/nl_classifier_options.pb.h"
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_NL_CLASSIFIER_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/retrieval.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/retrieval.proto
new file mode 100644
index 0000000..21c0fb2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/retrieval.proto
@@ -0,0 +1,89 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+syntax = "proto2";
+
+package tflite.task.text;
+
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
+import "tensorflow_lite_support/cc/task/processor/proto/embedding.proto";
+
+// Input message for retrieval models that encode strings into vectors.
+// The input is a tuple of query text, and one or more response text with their
+// context.
+//
+// Retrieve expects both query_text and responses are not empty.
+message RetrievalInput {
+  // Input text as the user query (e.g. "When is Father's Day?").
+  optional string query_text = 1;
+
+  // A list of response entries.
+  repeated ResponseEntry responses = 2;
+  // Next Id: 3
+}
+
+// Response entry includes raw text or text_encoding.
+message ResponseEntry {
+  // We allow users to pass:
+  // (1) raw_text to encode
+  // Or (2) cached text_encoding (save computation and faster).
+  oneof response_options {
+    RawText raw_text = 1;
+    tflite.task.processor.FeatureVector text_encoding = 2;
+    // Next Id: 3
+  }
+
+  // Raw text contains the text and its context.
+  message RawText {
+    // Text for the response (e.g. "In the US, it falls on the third Sunday in
+    // June.").
+    optional string text = 1;
+
+    // Context for the response, such as the surrounding text or background
+    // information (e.g. "Father's Day is a celebration honoring fathers and
+    // celebrating fatherhood, paternal bonds, and the influence of fathers
+    // in society.").
+    optional string context = 2;
+    // Next Id: 3
+  }
+}
+
+// The result for response entry.
+message ResponseResult {
+  // The encoded vector for the response.
+  optional tflite.task.processor.FeatureVector encoding = 1;
+
+  // The score measured by encodings of query and response.
+  optional float score = 2;
+  // Next Id: 3
+}
+
+// Output message for retrieval. The retrieval model encodes query and response
+// into respective vectors, and calculates their similarity score.
+message RetrievalOutput {
+  // The encoded vector for the query.
+  optional tflite.task.processor.FeatureVector query_encoding = 1;
+
+  // Results corresponding to responses in the same input order.
+  repeated ResponseResult response_results = 2;
+  // Next Id: 3
+}
+
+// Options for setting up retrieval models.
+message RetrievalOptions {
+  // Base options for configuring retrieval models, such as specifying the
+  // TfLite model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 1;
+  // Next Id: 2
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/retrieval_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/retrieval_proto_inc.h
new file mode 100644
index 0000000..7d7bb8f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/proto/retrieval_proto_inc.h
@@ -0,0 +1,22 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_RETRIEVAL_PROTO_INC_H_
+#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_RETRIEVAL_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/proto/retrieval.pb.h"
+
+#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_PROTO_RETRIEVAL_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/BUILD
deleted file mode 100644
index 49ad5a1f..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/BUILD
+++ /dev/null
@@ -1,61 +0,0 @@
-package(
-    default_visibility = ["//tensorflow_lite_support:users"],
-    licenses = ["notice"],  # Apache 2.0
-)
-
-exports_files([
-    "bert_qa_c_api.h",
-])
-
-cc_library(
-    name = "question_answerer",
-    hdrs = [
-        "question_answerer.h",
-    ],
-    deps = [
-        "//tensorflow_lite_support/cc/task/core:base_task_api",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
-    ],
-)
-
-cc_library(
-    name = "bert_question_answerer",
-    srcs = [
-        "bert_question_answerer.cc",
-    ],
-    hdrs = [
-        "bert_question_answerer.h",
-    ],
-    deps = [
-        ":question_answerer",
-        "//tensorflow_lite_support/cc/port:status_macros",
-        "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/core:base_task_api",
-        "//tensorflow_lite_support/cc/task/core:task_api_factory",
-        "//tensorflow_lite_support/cc/task/core:task_utils",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
-        "//tensorflow_lite_support/cc/text/tokenizers:bert_tokenizer",
-        "//tensorflow_lite_support/cc/text/tokenizers:sentencepiece_tokenizer",
-        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer",
-        "//tensorflow_lite_support/cc/text/tokenizers:tokenizer_utils",
-        "//tensorflow_lite_support/metadata:metadata_schema_cc",
-        "@com_google_absl//absl/container:flat_hash_map",
-        "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings",
-    ],
-)
-
-cc_library(
-    name = "bert_qa_c_api",
-    srcs = [
-        "bert_qa_c_api.cc",
-    ],
-    hdrs = [
-        "bert_qa_c_api.h",
-    ],
-    visibility = ["//tensorflow_lite_support:__subpackages__"],
-    deps = [
-        ":bert_question_answerer",
-        ":question_answerer",
-    ],
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.cc
deleted file mode 100644
index 3dc7a28..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.cc
+++ /dev/null
@@ -1,80 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.h"
-
-#include <memory>
-
-#include "tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h"
-#include "tensorflow_lite_support/cc/task/text/qa/question_answerer.h"
-
-using BertQuestionAnswererCPP = ::tflite::task::text::qa::BertQuestionAnswerer;
-using QaAnswerCPP = ::tflite::task::text::qa::QaAnswer;
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-struct BertQuestionAnswerer {
-  std::unique_ptr<BertQuestionAnswererCPP> impl;
-};
-
-BertQuestionAnswerer* BertQuestionAnswererFromFile(const char* model_path) {
-  auto bert_qa_status =
-      BertQuestionAnswererCPP::CreateFromFile(std::string(model_path));
-  if (bert_qa_status.ok()) {
-    return new BertQuestionAnswerer{
-        .impl = std::unique_ptr<BertQuestionAnswererCPP>(
-            dynamic_cast<BertQuestionAnswererCPP*>(
-                bert_qa_status.value().release()))};
-  } else {
-    return nullptr;
-  }
-}
-
-QaAnswers* BertQuestionAnswererAnswer(
-    const BertQuestionAnswerer* question_answerer,
-    const char* context,
-    const char* question) {
-  std::vector<QaAnswerCPP> answers = question_answerer->impl->Answer(
-      absl::string_view(context).data(), absl::string_view(question).data());
-  size_t size = answers.size();
-  auto* qa_answers = new QaAnswer[size];
-
-  for (size_t i = 0; i < size; ++i) {
-    qa_answers[i].start = answers[i].pos.start;
-    qa_answers[i].end = answers[i].pos.end;
-    qa_answers[i].logit = answers[i].pos.logit;
-    qa_answers[i].text = strdup(answers[i].text.c_str());
-  }
-
-  auto* c_answers = new QaAnswers;
-  c_answers->size = size;
-  c_answers->answers = qa_answers;
-  return c_answers;
-}
-
-void BertQuestionAnswererDelete(BertQuestionAnswerer* bert_question_answerer) {
-  delete bert_question_answerer;
-}
-
-void BertQuestionAnswererQaAnswersDelete(QaAnswers* qa_answers) {
-  delete[] qa_answers->answers;
-  delete qa_answers;
-}
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.h
deleted file mode 100644
index 6cd27ee..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.h
+++ /dev/null
@@ -1,79 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_BERT_QA_C_API_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_BERT_QA_C_API_H_
-
-// --------------------------------------------------------------------------
-/// C API for BertQuestionAnswerer.
-///
-/// The API leans towards simplicity and uniformity instead of convenience, as
-/// most usage will be by language-specific wrappers. It provides largely the
-/// same set of functionality as that of the C++ TensorFlow Lite
-/// `BertQuestionAnswerer` API, but is useful for shared libraries where having
-/// a stable ABI boundary is important.
-///
-/// Usage:
-/// <pre><code>
-/// // Create the model and interpreter options.
-/// BertQuestionAnswerer* qa_answerer =
-///   BertQuestionAnswererFromFile("/path/to/model.tflite");
-///
-/// // answer a question.
-/// QaAnswers* answers = Answer(qa_answerer, context, question);
-///
-/// // Dispose of the API and QaAnswers objects.
-/// BertQuestionAnswererDelete(qa_answerer);
-/// BertQuestionAnswererQaAnswersDelete(answers);
-
-#ifdef __cplusplus
-extern "C" {
-#endif  // __cplusplus
-
-typedef struct BertQuestionAnswerer BertQuestionAnswerer;
-
-struct QaAnswer {
-  int start;
-  int end;
-  float logit;
-  char* text;
-};
-
-struct QaAnswers {
-  int size;
-  struct QaAnswer* answers;
-};
-
-// Creates BertQuestionAnswerer from model path, returns nullptr if the file
-// doesn't exist or is not a well formatted TFLite model path.
-extern BertQuestionAnswerer* BertQuestionAnswererFromFile(
-    const char* model_path);
-
-// Invokes the encapsulated TFLite model and answers a question based on
-// context.
-extern struct QaAnswers* BertQuestionAnswererAnswer(
-    const BertQuestionAnswerer* question_answerer,
-    const char* context,
-    const char* question);
-
-extern void BertQuestionAnswererDelete(
-    BertQuestionAnswerer* bert_question_answerer);
-
-extern void BertQuestionAnswererQaAnswersDelete(struct QaAnswers* qa_answers);
-
-#ifdef __cplusplus
-}  // extern "C"
-#endif  // __cplusplus
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_BERT_QA_C_API_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.cc
deleted file mode 100644
index 286f6f6..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.cc
+++ /dev/null
@@ -1,403 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h"
-
-#include "absl/strings/str_join.h"
-#include "absl/strings/str_split.h"
-#include "tensorflow_lite_support/cc/port/status_macros.h"
-#include "tensorflow_lite_support/cc/task/core/task_utils.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h"
-#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
-
-namespace tflite {
-namespace task {
-namespace text {
-namespace qa {
-
-constexpr char kIdsTensorName[] = "ids";
-constexpr char kMaskTensorName[] = "mask";
-constexpr char kSegmentIdsTensorName[] = "segment_ids";
-constexpr char kEndLogitsTensorName[] = "end_logits";
-constexpr char kStartLogitsTensorName[] = "start_logits";
-
-using ::tflite::support::CreateStatusWithPayload;
-using ::tflite::support::StatusOr;
-using ::tflite::support::TfLiteSupportStatus;
-using ::tflite::support::text::tokenizer::BertTokenizer;
-using ::tflite::support::text::tokenizer::CreateTokenizerFromProcessUnit;
-using ::tflite::support::text::tokenizer::SentencePieceTokenizer;
-using ::tflite::support::text::tokenizer::TokenizerResult;
-using ::tflite::task::core::FindTensorByName;
-using ::tflite::task::core::PopulateTensor;
-using ::tflite::task::core::PopulateVector;
-using ::tflite::task::core::ReverseSortIndices;
-
-namespace {
-constexpr int kTokenizerProcessUnitIndex = 0;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>>
-BertQuestionAnswerer::CreateFromFile(
-    const std::string& path_to_model_with_metadata) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromFile<BertQuestionAnswerer>(
-          path_to_model_with_metadata,
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  RETURN_IF_ERROR(api_to_init->InitializeFromMetadata());
-  return api_to_init;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>>
-BertQuestionAnswerer::CreateFromBuffer(
-    const char* model_with_metadata_buffer_data,
-    size_t model_with_metadata_buffer_size) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromBuffer<BertQuestionAnswerer>(
-          model_with_metadata_buffer_data, model_with_metadata_buffer_size,
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  RETURN_IF_ERROR(api_to_init->InitializeFromMetadata());
-  return api_to_init;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>> BertQuestionAnswerer::CreateFromFd(
-    int fd) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromFileDescriptor<BertQuestionAnswerer>(
-          fd, absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  RETURN_IF_ERROR(api_to_init->InitializeFromMetadata());
-  return api_to_init;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>>
-BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
-    const std::string& path_to_model,
-    const std::string& path_to_vocab) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromFile<BertQuestionAnswerer>(
-          path_to_model,
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  api_to_init->InitializeBertTokenizer(path_to_vocab);
-  return api_to_init;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>>
-BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
-    const char* model_buffer_data,
-    size_t model_buffer_size,
-    const char* vocab_buffer_data,
-    size_t vocab_buffer_size) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromBuffer<BertQuestionAnswerer>(
-          model_buffer_data, model_buffer_size,
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  api_to_init->InitializeBertTokenizerFromBinary(vocab_buffer_data,
-                                                 vocab_buffer_size);
-  return api_to_init;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>>
-BertQuestionAnswerer::CreateAlbertQuestionAnswererFromFile(
-    const std::string& path_to_model,
-    const std::string& path_to_spmodel) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromFile<BertQuestionAnswerer>(
-          path_to_model,
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  api_to_init->InitializeSentencepieceTokenizer(path_to_spmodel);
-  return api_to_init;
-}
-
-StatusOr<std::unique_ptr<QuestionAnswerer>>
-BertQuestionAnswerer::CreateAlbertQuestionAnswererFromBuffer(
-    const char* model_buffer_data,
-    size_t model_buffer_size,
-    const char* spmodel_buffer_data,
-    size_t spmodel_buffer_size) {
-  std::unique_ptr<BertQuestionAnswerer> api_to_init;
-  ASSIGN_OR_RETURN(
-      api_to_init,
-      core::TaskAPIFactory::CreateFromBuffer<BertQuestionAnswerer>(
-          model_buffer_data, model_buffer_size,
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>(),
-          kNumLiteThreads));
-  api_to_init->InitializeSentencepieceTokenizerFromBinary(spmodel_buffer_data,
-                                                          spmodel_buffer_size);
-  return api_to_init;
-}
-
-std::vector<QaAnswer> BertQuestionAnswerer::Answer(
-    const std::string& context,
-    const std::string& question) {
-  // The BertQuestionAnswererer implementation for Preprocess() and
-  // Postprocess() never returns errors: just call value().
-  return Infer(context, question).value();
-}
-
-absl::Status BertQuestionAnswerer::Preprocess(
-    const std::vector<TfLiteTensor*>& input_tensors,
-    const std::string& context,
-    const std::string& query) {
-  auto* input_tensor_metadatas =
-      GetMetadataExtractor()->GetInputTensorMetadata();
-  TfLiteTensor* ids_tensor =
-      input_tensor_metadatas
-          ? FindTensorByName(input_tensors, input_tensor_metadatas,
-                             kIdsTensorName)
-          : input_tensors[0];
-  TfLiteTensor* mask_tensor =
-      input_tensor_metadatas
-          ? FindTensorByName(input_tensors, input_tensor_metadatas,
-                             kMaskTensorName)
-          : input_tensors[1];
-  TfLiteTensor* segment_ids_tensor =
-      input_tensor_metadatas
-          ? FindTensorByName(input_tensors, input_tensor_metadatas,
-                             kSegmentIdsTensorName)
-          : input_tensors[2];
-
-  token_to_orig_map_.clear();
-
-  // The orig_tokens is used for recovering the answer string from the index,
-  // while the processed_tokens is lower-cased and used to generate input of
-  // the model.
-  orig_tokens_ = absl::StrSplit(context, absl::ByChar(' '), absl::SkipEmpty());
-  std::vector<std::string> processed_tokens(orig_tokens_);
-
-  std::string processed_query = query;
-  if (kUseLowerCase) {
-    for (auto& token : processed_tokens) {
-      absl::AsciiStrToLower(&token);
-    }
-    absl::AsciiStrToLower(&processed_query);
-  }
-
-  TokenizerResult query_tokenize_results;
-  query_tokenize_results = tokenizer_->Tokenize(processed_query);
-
-  std::vector<std::string> query_tokens = query_tokenize_results.subwords;
-  if (query_tokens.size() > kMaxQueryLen) {
-    query_tokens.resize(kMaxQueryLen);
-  }
-
-  // Example:
-  // context:             tokenize     me  please
-  // all_doc_tokens:      token ##ize  me  plea ##se
-  // token_to_orig_index: [0,   0,     1,  2,   2]
-
-  std::vector<std::string> all_doc_tokens;
-  std::vector<int> token_to_orig_index;
-  for (size_t i = 0; i < processed_tokens.size(); i++) {
-    const std::string& token = processed_tokens[i];
-    std::vector<std::string> sub_tokens = tokenizer_->Tokenize(token).subwords;
-    for (const std::string& sub_token : sub_tokens) {
-      token_to_orig_index.emplace_back(i);
-      all_doc_tokens.emplace_back(sub_token);
-    }
-  }
-
-  // -3 accounts for [CLS], [SEP] and [SEP].
-  int max_context_len = kMaxSeqLen - query_tokens.size() - 3;
-  if (all_doc_tokens.size() > max_context_len) {
-    all_doc_tokens.resize(max_context_len);
-  }
-
-  std::vector<std::string> tokens;
-  tokens.reserve(3 + query_tokens.size() + all_doc_tokens.size());
-  std::vector<int> segment_ids;
-  segment_ids.reserve(kMaxSeqLen);
-
-  // Start of generating the features.
-  tokens.emplace_back("[CLS]");
-  segment_ids.emplace_back(0);
-
-  // For query input.
-  for (const auto& query_token : query_tokens) {
-    tokens.emplace_back(query_token);
-    segment_ids.emplace_back(0);
-  }
-
-  // For Separation.
-  tokens.emplace_back("[SEP]");
-  segment_ids.emplace_back(0);
-
-  // For Text Input.
-  for (int i = 0; i < all_doc_tokens.size(); i++) {
-    auto& doc_token = all_doc_tokens[i];
-    tokens.emplace_back(doc_token);
-    segment_ids.emplace_back(1);
-    token_to_orig_map_[tokens.size()] = token_to_orig_index[i];
-  }
-
-  // For ending mark.
-  tokens.emplace_back("[SEP]");
-  segment_ids.emplace_back(1);
-
-  std::vector<int> input_ids(tokens.size());
-  input_ids.reserve(kMaxSeqLen);
-  // Convert tokens back into ids
-  for (int i = 0; i < tokens.size(); i++) {
-    auto& token = tokens[i];
-    tokenizer_->LookupId(token, &input_ids[i]);
-  }
-
-  std::vector<int> input_mask;
-  input_mask.reserve(kMaxSeqLen);
-  input_mask.insert(input_mask.end(), tokens.size(), 1);
-
-  int zeros_to_pad = kMaxSeqLen - input_ids.size();
-  input_ids.insert(input_ids.end(), zeros_to_pad, 0);
-  input_mask.insert(input_mask.end(), zeros_to_pad, 0);
-  segment_ids.insert(segment_ids.end(), zeros_to_pad, 0);
-
-  // input_ids INT32[1, 384]
-  PopulateTensor(input_ids, ids_tensor);
-  // input_mask INT32[1, 384]
-  PopulateTensor(input_mask, mask_tensor);
-  // segment_ids INT32[1, 384]
-  PopulateTensor(segment_ids, segment_ids_tensor);
-
-  return absl::OkStatus();
-}
-
-StatusOr<std::vector<QaAnswer>> BertQuestionAnswerer::Postprocess(
-    const std::vector<const TfLiteTensor*>& output_tensors,
-    const std::string& /*lowercased_context*/,
-    const std::string& /*lowercased_query*/) {
-  auto* output_tensor_metadatas =
-      GetMetadataExtractor()->GetOutputTensorMetadata();
-
-  const TfLiteTensor* end_logits_tensor =
-      output_tensor_metadatas
-          ? FindTensorByName(output_tensors, output_tensor_metadatas,
-                             kEndLogitsTensorName)
-          : output_tensors[0];
-  const TfLiteTensor* start_logits_tensor =
-      output_tensor_metadatas
-          ? FindTensorByName(output_tensors, output_tensor_metadatas,
-                             kStartLogitsTensorName)
-          : output_tensors[1];
-
-  std::vector<float> end_logits;
-  std::vector<float> start_logits;
-
-  // end_logits FLOAT[1, 384]
-  PopulateVector(end_logits_tensor, &end_logits);
-  // start_logits FLOAT[1, 384]
-  PopulateVector(start_logits_tensor, &start_logits);
-
-  auto start_indices = ReverseSortIndices(start_logits);
-  auto end_indices = ReverseSortIndices(end_logits);
-
-  std::vector<QaAnswer::Pos> orig_results;
-  for (int start_index = 0; start_index < kPredictAnsNum; start_index++) {
-    for (int end_index = 0; end_index < kPredictAnsNum; end_index++) {
-      int start = start_indices[start_index];
-      int end = end_indices[end_index];
-
-      if (!token_to_orig_map_.contains(start + kOutputOffset) ||
-          !token_to_orig_map_.contains(end + kOutputOffset) || end < start ||
-          (end - start + 1) > kMaxAnsLen) {
-        continue;
-      }
-      orig_results.emplace_back(
-          QaAnswer::Pos(start, end, start_logits[start] + end_logits[end]));
-    }
-  }
-
-  std::sort(orig_results.begin(), orig_results.end());
-
-  std::vector<QaAnswer> answers;
-  for (int i = 0; i < orig_results.size() && i < kPredictAnsNum; i++) {
-    auto orig_pos = orig_results[i];
-    answers.emplace_back(
-        orig_pos.start > 0 ? ConvertIndexToString(orig_pos.start, orig_pos.end)
-                           : "",
-        orig_pos);
-  }
-
-  return answers;
-}
-
-std::string BertQuestionAnswerer::ConvertIndexToString(int start, int end) {
-  int start_index = token_to_orig_map_[start + kOutputOffset];
-  int end_index = token_to_orig_map_[end + kOutputOffset];
-
-  return absl::StrJoin(orig_tokens_.begin() + start_index,
-                       orig_tokens_.begin() + end_index + 1, " ");
-}
-
-absl::Status BertQuestionAnswerer::InitializeFromMetadata() {
-  const ProcessUnit* tokenizer_process_unit =
-      GetMetadataExtractor()->GetInputProcessUnit(kTokenizerProcessUnitIndex);
-  if (tokenizer_process_unit == nullptr) {
-    return CreateStatusWithPayload(
-        absl::StatusCode::kInvalidArgument,
-        "No input process unit found from metadata.",
-        TfLiteSupportStatus::kMetadataInvalidTokenizerError);
-  }
-  ASSIGN_OR_RETURN(tokenizer_,
-                   CreateTokenizerFromProcessUnit(tokenizer_process_unit,
-                                                  GetMetadataExtractor()));
-  return absl::OkStatus();
-}
-
-void BertQuestionAnswerer::InitializeBertTokenizer(
-    const std::string& path_to_vocab) {
-  tokenizer_ = absl::make_unique<BertTokenizer>(path_to_vocab);
-}
-
-void BertQuestionAnswerer::InitializeBertTokenizerFromBinary(
-    const char* vocab_buffer_data,
-    size_t vocab_buffer_size) {
-  tokenizer_ =
-      absl::make_unique<BertTokenizer>(vocab_buffer_data, vocab_buffer_size);
-}
-
-void BertQuestionAnswerer::InitializeSentencepieceTokenizer(
-    const std::string& path_to_spmodel) {
-  tokenizer_ = absl::make_unique<SentencePieceTokenizer>(path_to_spmodel);
-}
-
-void BertQuestionAnswerer::InitializeSentencepieceTokenizerFromBinary(
-    const char* spmodel_buffer_data,
-    size_t spmodel_buffer_size) {
-  tokenizer_ = absl::make_unique<SentencePieceTokenizer>(spmodel_buffer_data,
-                                                         spmodel_buffer_size);
-}
-
-}  // namespace qa
-}  // namespace text
-}  // namespace task
-}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h
deleted file mode 100644
index 54f4b102..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h
+++ /dev/null
@@ -1,171 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_BERT_QUESTION_ANSWERER_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_BERT_QUESTION_ANSWERER_H_
-
-#include "absl/container/flat_hash_map.h"
-#include "absl/status/status.h"
-#include "tensorflow_lite_support/cc/port/statusor.h"
-#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
-#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
-#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
-#include "tensorflow_lite_support/cc/task/text/qa/question_answerer.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h"
-#include "tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h"
-
-namespace tflite {
-namespace task {
-namespace text {
-namespace qa {
-
-// BertQA task API, performs tokenization for models (BERT, Albert, etc.) in
-// preprocess and returns most possible answers.
-//
-// In particular, the branch of BERT models use WordPiece tokenizer, and the
-// branch of Albert models use SentencePiece tokenizer, respectively.
-//
-// Factory methods:
-//   CreateFromFile(path_to_model_with_metadata)
-//   CreateFromBuffer(model_with_metadata_buffer_data,
-//                                model_with_metadata_buffer_size)
-//   CreateFromFd(file_descriptor_to_model_with_metadata)
-//     Generic API to create the QuestionAnswerer for bert models with metadata
-//     populated. The API expects a Bert based TFLite model with metadata
-//     containing the following information:
-//       - input_process_units for Wordpiece/Sentencepiece Tokenizer. Wordpiece
-//         Tokenizer can be used for a MobileBert[0] model, Sentencepiece
-//         Tokenizer Tokenizer can be used for an Albert[1] model
-//       - 3 input tensors with names "ids", "mask" and "segment_ids"
-//       - 2 output tensors with names "end_logits" and "start_logits"
-//      [0]: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
-//      [1]: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
-//
-//   CreateBertQuestionAnswererFromFile(path_to_model, path_to_vocab)
-//     Creates a BertQuestionAnswerer from TFLite model file and vocab file for
-//     WordPiece tokenizer. Used in C++ environment.
-//     One suitable model is:
-//       https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
-//
-//   CreateBertQuestionAnswererFromBuffer(model_buffer_data, model_buffer_size,
-//                                        vocab_buffer_data, vocab_buffer_size)
-//     Creates a BertQuestionAnswerer from TFLite model buffer and vocab file
-//     buffer for WordPiece tokenizer. Used in Jave (JNI) environment.
-//
-//   CreateAlbertQuestionAnswererFromFile(path_to_model, path_to_spmodel)
-//     Creates an AlbertQuestionAnswerer from TFLite model file and
-//     SentencePiece model file. Used in C++ environment.
-//     One suitable model is:
-//       https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
-//
-//   CreateAlbertQuestionAnswererFromBuffer(model_buffer_data,
-//                                          model_buffer_size,
-//                                          spmodel_buffer_data,
-//                                          spmodel_buffer_size)
-//     Creates an AlbertQuestionAnswerer from TFLite model file buffer and
-//     SentencePiece model file buffer. Used in Jave (JNI) environment.
-//
-
-class BertQuestionAnswerer : public QuestionAnswerer {
- public:
-  // TODO(b/150904655): add support to parameterize.
-  static constexpr int kMaxQueryLen = 64;
-  static constexpr int kMaxSeqLen = 384;
-  static constexpr int kPredictAnsNum = 5;
-  static constexpr int kMaxAnsLen = 32;
-  // TODO(b/151954803): clarify the offset usage
-  static constexpr int kOutputOffset = 1;
-  static constexpr int kNumLiteThreads = 4;
-  static constexpr bool kUseLowerCase = true;
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateFromFile(const std::string& path_to_model_with_metadata);
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateFromBuffer(const char* model_with_metadata_buffer_data,
-                   size_t model_with_metadata_buffer_size);
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateFromFd(int fd);
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateBertQuestionAnswererFromFile(const std::string& path_to_model,
-                                     const std::string& path_to_vocab);
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateBertQuestionAnswererFromBuffer(const char* model_buffer_data,
-                                       size_t model_buffer_size,
-                                       const char* vocab_buffer_data,
-                                       size_t vocab_buffer_size);
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateAlbertQuestionAnswererFromFile(const std::string& path_to_model,
-                                       const std::string& path_to_spmodel);
-
-  static tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>>
-  CreateAlbertQuestionAnswererFromBuffer(const char* model_buffer_data,
-                                         size_t model_buffer_size,
-                                         const char* spmodel_buffer_data,
-                                         size_t spmodel_buffer_size);
-
-  explicit BertQuestionAnswerer(std::unique_ptr<core::TfLiteEngine> engine)
-      : QuestionAnswerer(std::move(engine)) {}
-
-  // Answers question based on the context. Could be empty if no answer was
-  // found from the given context.
-  std::vector<QaAnswer> Answer(const std::string& context,
-                               const std::string& question) override;
-
- private:
-  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
-                          const std::string& lowercased_context,
-                          const std::string& lowercased_query) override;
-
-  tflite::support::StatusOr<std::vector<QaAnswer>> Postprocess(
-      const std::vector<const TfLiteTensor*>& output_tensors,
-      const std::string& lowercased_context,
-      const std::string& lowercased_query) override;
-
-  // Initialize API with a BertTokenizer from the vocabulary file.
-  void InitializeBertTokenizer(const std::string& path_to_vocab);
-  // Initialize API with a BertTokenizer from the vocabulary buffer.
-  void InitializeBertTokenizerFromBinary(const char* vocab_buffer_data,
-                                         size_t vocab_buffer_size);
-
-  // Initialize API with a SentencepieceTokenizer from the model file.
-  void InitializeSentencepieceTokenizer(const std::string& path_to_spmodel);
-  // Initialize API with a SentencepieceTokenizer from the model buffer.
-  void InitializeSentencepieceTokenizerFromBinary(
-      const char* spmodel_buffer_data,
-      size_t spmodel_buffer_size);
-
-  // Initialize the API with the tokenizer set in the metadata.
-  absl::Status InitializeFromMetadata();
-
-  std::string ConvertIndexToString(int start, int end);
-
-  std::unique_ptr<tflite::support::text::tokenizer::Tokenizer> tokenizer_;
-  // Maps index of input token to index of untokenized word from original input.
-  absl::flat_hash_map<size_t, size_t> token_to_orig_map_;
-  // Original tokens of context.
-  std::vector<std::string> orig_tokens_;
-};
-
-}  // namespace qa
-}  // namespace text
-}  // namespace task
-}  // namespace tflite
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_BERT_QUESTION_ANSWERER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/question_answerer.h
deleted file mode 100644
index b4bd641f..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/qa/question_answerer.h
+++ /dev/null
@@ -1,65 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_QUESTION_ANSWERER_H_
-#define TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_QUESTION_ANSWERER_H_
-
-#include <string>
-#include <utility>
-#include <vector>
-
-#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
-#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
-
-namespace tflite {
-namespace task {
-namespace text {
-namespace qa {
-
-// Struct for the Answer to QuestionAnswerer.
-struct QaAnswer {
-  // struct to represent the logit and offset of the answer related to context.
-  struct Pos {
-    Pos(int arg_start, int arg_end, float arg_logit)
-        : start(arg_start), end(arg_end), logit(arg_logit) {}
-    int start, end;
-    float logit;
-    bool operator<(const Pos& rhs) const { return rhs.logit < logit; }
-  };
-
-  QaAnswer(std::string arg_text, Pos arg_pos)
-      : text(std::move(arg_text)), pos(arg_pos) {}
-  std::string text;
-  Pos pos;
-};
-
-// Interface for an Question-Answer API.
-class QuestionAnswerer : public core::BaseTaskApi<std::vector<QaAnswer>,
-                                                  const std::string&,
-                                                  const std::string&> {
- public:
-  explicit QuestionAnswerer(std::unique_ptr<core::TfLiteEngine> engine)
-      : BaseTaskApi(std::move(engine)) {}
-
-  virtual std::vector<QaAnswer> Answer(const std::string& context,
-                                       const std::string& question) = 0;
-};
-
-}  // namespace qa
-}  // namespace text
-}  // namespace task
-}  // namespace tflite
-
-#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_QA_QUESTION_ANSWERER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h
new file mode 100644
index 0000000..df21662
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/question_answerer.h
@@ -0,0 +1,63 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_QUESTION_ANSWERER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_QUESTION_ANSWERER_H_
+
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+// Struct for the Answer to QuestionAnswerer.
+struct QaAnswer {
+  // struct to represent the logit and offset of the answer related to context.
+  struct Pos {
+    Pos(int arg_start, int arg_end, float arg_logit)
+        : start(arg_start), end(arg_end), logit(arg_logit) {}
+    int start, end;
+    float logit;
+    bool operator<(const Pos& rhs) const { return rhs.logit < logit; }
+  };
+
+  QaAnswer(std::string arg_text, Pos arg_pos)
+      : text(std::move(arg_text)), pos(arg_pos) {}
+  std::string text;
+  Pos pos;
+};
+
+// Interface for an Question-Answer API.
+class QuestionAnswerer : public core::BaseTaskApi<std::vector<QaAnswer>,
+                                                  const std::string&,
+                                                  const std::string&> {
+ public:
+  explicit QuestionAnswerer(std::unique_ptr<core::TfLiteEngine> engine)
+      : BaseTaskApi(std::move(engine)) {}
+
+  virtual std::vector<QaAnswer> Answer(const std::string& context,
+                                       const std::string& question) = 0;
+};
+
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_QA_QUESTION_ANSWERER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc
new file mode 100644
index 0000000..2937a175
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.cc
@@ -0,0 +1,330 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h"
+
+#include <algorithm>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/text/proto/retrieval.pb.h"
+
+namespace tflite {
+namespace ops {
+namespace custom {
+TfLiteRegistration* Register_SENTENCEPIECE_TOKENIZER();
+TfLiteRegistration* Register_RAGGED_TENSOR_TO_TENSOR();
+}  // namespace custom
+}  // namespace ops
+}  // namespace tflite
+
+namespace tflite {
+namespace task {
+namespace text {
+namespace retrieval {
+
+using ::absl::Status;
+using ::absl::StatusCode;
+using internal::QAInput;
+using internal::QAOutput;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::core::FindTensorByName;
+using ::tflite::task::core::PopulateTensor;
+using ::tflite::task::core::PopulateVectorToRepeated;
+using ::tflite::task::core::TaskAPIFactory;
+using FeatureVector = UniversalSentenceEncoderQA::FeatureVector;
+
+namespace {
+constexpr char kQueryTextTensorName[] = "inp_text";
+constexpr char kResponseTextTensorName[] = "res_text";
+constexpr char kResponseContextTensorName[] = "res_context";
+constexpr char kQueryEncodingTensorName[] = "query_encoding";
+constexpr char kResponseEncodingTensorName[] = "response_encoding";
+
+// Sanity check for options to ensure required fields.
+absl::Status SanityCheckOptions(const RetrievalOptions& options) {
+  if (!options.has_base_options()) {
+    return CreateStatusWithPayload(StatusCode::kInvalidArgument,
+                                   "Missing mandatory `base_options` field",
+                                   TfLiteSupportStatus::kInvalidArgumentError);
+  }
+  return absl::OkStatus();
+}
+
+// Copy vector from model output.
+inline absl::Status CopyVector(const TfLiteTensor* src, FeatureVector* target) {
+  return PopulateVectorToRepeated(src, target->mutable_value_float());
+}
+
+// Dot product of two vectors. Returns error status if size is mismatched.
+template <class TCollection, class T = float>
+tflite::support::StatusOr<T> Dot(const TCollection& a, const TCollection& b) {
+  if (a.size() != b.size()) {
+    return Status(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("mismatched vector size %d != %d", a.size(), b.size()));
+  }
+  auto dist = T();
+  for (size_t i = 0; i < a.size(); ++i) {
+    dist += T(a[i]) * T(b[i]);
+  }
+  return dist;
+}
+}  // namespace
+
+namespace internal {
+struct QAInput {
+  std::string query_text;
+  std::string response_text;
+  std::string response_context;
+};
+
+struct QAOutput {
+  // Directly populate from raw tensor pointers to avoid extra copy.
+  const TfLiteTensor* query_encoding;     // not owned.
+  const TfLiteTensor* response_encoding;  // not owned.
+};
+}  // namespace internal
+
+// Creates custom op resolver for USE QA task.
+std::unique_ptr<tflite_shims::ops::builtin::BuiltinOpResolver>
+CreateQACustomOpResolver() {
+  auto resolver =
+      absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>();
+  resolver->AddCustom(
+      "TFSentencepieceTokenizeOp",
+      ::tflite::ops::custom::Register_SENTENCEPIECE_TOKENIZER());
+  resolver->AddCustom(
+      "RaggedTensorToTensor",
+      ::tflite::ops::custom::Register_RAGGED_TENSOR_TO_TENSOR());
+  return resolver;
+}
+
+constexpr int UniversalSentenceEncoderQA::kFinalEmbeddingSize;
+
+StatusOr<RetrievalOutput> UniversalSentenceEncoderQA::Retrieve(
+    const RetrievalInput& input) {
+  if (input.query_text().empty()) {
+    return Status(StatusCode::kInvalidArgument, "query text cannot be empty.");
+  }
+  if (input.responses().empty()) {
+    return Status(StatusCode::kInvalidArgument, "responses cannot be empty.");
+  }
+
+  RetrievalOutput output;
+  // Run inference.
+  // (1) Query is only encoded for once.
+  // (2) If responses are raw text, run model to get encoded vectors; otherwise,
+  //     the encoded vector is kept from the input when given.
+  for (size_t i = 0; i < input.responses_size(); ++i) {
+    const auto& resp = input.responses(i);
+
+    if (resp.has_raw_text()) {
+      // If response is in th raw text, encode both query and response.
+      const auto out = Run(input.query_text(), resp.raw_text().text(),
+                           resp.raw_text().context());
+
+      // Only encode query for the first time.
+      if (i == 0) {
+        RETURN_IF_ERROR(
+            CopyVector(out.query_encoding, output.mutable_query_encoding()));
+      }
+
+      // For each answer, set the response result.
+      auto r = output.mutable_response_results()->Add();
+      RETURN_IF_ERROR(CopyVector(out.response_encoding, r->mutable_encoding()));
+    } else {
+      // If response is already encoded, encode query only and keep response
+      // encoding.
+
+      // Only encode query for the first time.
+      if (i == 0) {
+        const auto& q = EncodeQuery(input.query_text());
+        *output.mutable_query_encoding() = q.value();
+      }
+
+      // For each answer, set the response result from text_encoding
+      auto r = output.mutable_response_results()->Add();
+      *r->mutable_encoding() = resp.text_encoding();
+    }
+  }
+
+  // Calculate scores.
+  for (size_t i = 0; i < output.response_results_size(); ++i) {
+    auto* r = output.mutable_response_results(i);
+    // TODO(tianlin): For a large size of results, it is more efficient to use
+    // matrix multiplication.
+    const auto& score = Similarity(output.query_encoding(), r->encoding());
+    if (!score.ok()) {
+      return score.status();
+    }
+    r->set_score(score.value());
+  }
+  return output;
+}
+
+StatusOr<FeatureVector> UniversalSentenceEncoderQA::EncodeQuery(
+    absl::string_view query_text) {
+  if (query_text.empty()) {
+    return Status(StatusCode::kInvalidArgument, "query text cannot be empty.");
+  }
+
+  const auto& output = Run(query_text, "", "");
+  FeatureVector v;
+  RETURN_IF_ERROR(CopyVector(output.query_encoding, &v));
+  return v;
+}
+
+StatusOr<FeatureVector> UniversalSentenceEncoderQA::EncodeResponse(
+    absl::string_view response_text,
+    absl::string_view response_context) {
+  if (response_text.empty() && response_context.empty()) {
+    return Status(
+        StatusCode::kInvalidArgument,
+        "either response text or context should be set to non-empty.");
+  }
+
+  const auto& output = Run("", response_text, response_context);
+  FeatureVector v;
+  RETURN_IF_ERROR(CopyVector(output.response_encoding, &v));
+  return v;
+}
+
+StatusOr<float> UniversalSentenceEncoderQA::Similarity(const FeatureVector& a,
+                                                       const FeatureVector& b) {
+  const auto& av = a.value_float();
+  const auto& bv = b.value_float();
+  return Dot(av, bv);
+}
+
+std::vector<size_t> UniversalSentenceEncoderQA::Top(
+    const RetrievalOutput& output,
+    size_t k) {
+  // Ensure k in [0, total_size).
+  // If k == 0, it means that all outputs are ranked.
+  if (k == 0) {
+    k = output.response_results_size();
+  } else {
+    k = std::min(k, size_t(output.response_results_size()));
+  }
+
+  std::vector<size_t> pos(output.response_results_size());
+  for (size_t i = 0; i < output.response_results_size(); ++i) {
+    pos[i] = i;
+  }
+  const auto greater_score = [&output](size_t i, size_t j) {
+    return output.response_results(i).score() >
+           output.response_results(j).score();
+  };
+  std::partial_sort(pos.begin(), pos.begin() + k, pos.end(), greater_score);
+
+  // Return sorted.
+  return std::vector<size_t>(pos.begin(), pos.begin() + k);
+}
+
+Status UniversalSentenceEncoderQA::Preprocess(
+    const std::vector<TfLiteTensor*>& input_tensors,
+    const QAInput& input) {
+  auto* input_tensor_metadatas =
+      GetMetadataExtractor()->GetInputTensorMetadata();
+  TfLiteTensor* query_text_tensor =
+      input_tensor_metadatas
+          ? FindTensorByName(input_tensors, input_tensor_metadatas,
+                             kQueryTextTensorName)
+          : input_tensors[0];
+  TfLiteTensor* response_text_tensor =
+      input_tensor_metadatas
+          ? FindTensorByName(input_tensors, input_tensor_metadatas,
+                             kResponseTextTensorName)
+          : input_tensors[2];
+  TfLiteTensor* response_context_tensor =
+      input_tensor_metadatas
+          ? FindTensorByName(input_tensors, input_tensor_metadatas,
+                             kResponseContextTensorName)
+          : input_tensors[1];
+
+  RETURN_IF_ERROR(PopulateTensor(input.query_text, query_text_tensor));
+  RETURN_IF_ERROR(PopulateTensor(input.response_text, response_text_tensor));
+  RETURN_IF_ERROR(
+      PopulateTensor(input.response_context, response_context_tensor));
+
+  return absl::OkStatus();
+}
+
+StatusOr<QAOutput> UniversalSentenceEncoderQA::Postprocess(
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const QAInput& /*input*/) {
+  auto* output_tensor_metadatas =
+      GetMetadataExtractor()->GetOutputTensorMetadata();
+
+  const TfLiteTensor* output_query_encoding_tensor =
+      output_tensor_metadatas
+          ? FindTensorByName(output_tensors, output_tensor_metadatas,
+                             kQueryEncodingTensorName)
+          : output_tensors[0];
+  const TfLiteTensor* output_response_encoding_tensor =
+      output_tensor_metadatas
+          ? FindTensorByName(output_tensors, output_tensor_metadatas,
+                             kResponseEncodingTensorName)
+          : output_tensors[1];
+
+  QAOutput output;
+  output.query_encoding = output_query_encoding_tensor;
+  output.response_encoding = output_response_encoding_tensor;
+  return output;
+}
+
+internal::QAOutput UniversalSentenceEncoderQA::Run(
+    absl::string_view query_text,
+    absl::string_view response_text,
+    absl::string_view response_context) {
+  QAInput input;
+  input.query_text = query_text;
+  input.response_text = response_text;
+  input.response_context = response_context;
+  return Infer(input).value();
+}
+
+StatusOr<std::unique_ptr<UniversalSentenceEncoderQA>>
+UniversalSentenceEncoderQA::CreateFromOption(
+    const RetrievalOptions& options,
+    std::unique_ptr<tflite::OpResolver> resolver) {
+  RETURN_IF_ERROR(SanityCheckOptions(options));
+
+  // Copy options to ensure the ExternalFile outlives the duration of this
+  // created object.
+  auto options_copy = absl::make_unique<RetrievalOptions>(options);
+
+  ASSIGN_OR_RETURN(
+      auto encoder,
+      TaskAPIFactory::CreateFromBaseOptions<UniversalSentenceEncoderQA>(
+          &options_copy->base_options(), std::move(resolver)));
+  encoder->proto_options_ = std::move(options_copy);
+  return std::move(encoder);
+}
+
+}  // namespace retrieval
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h
new file mode 100644
index 0000000..0269033
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h
@@ -0,0 +1,107 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_UNIVERSAL_SENTENCE_ENCODER_QA_H_
+#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_UNIVERSAL_SENTENCE_ENCODER_QA_H_
+
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/str_format.h"       // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/processor/proto/embedding.pb.h"
+#include "tensorflow_lite_support/cc/task/text/proto/retrieval.pb.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+namespace retrieval {
+
+// QAInput and QAOutput for UniversalSentenceEncoderQA internally.
+namespace internal {
+struct QAInput;
+struct QAOutput;
+}  // namespace internal
+
+// Creates custom op resolver for USE QA task.
+std::unique_ptr<tflite_shims::ops::builtin::BuiltinOpResolver>
+CreateQACustomOpResolver();
+
+// Universal Sentence Encoder (USE) Question Answerer. The model uses USE as the
+// backbone and answers a question.
+class UniversalSentenceEncoderQA
+    : public core::BaseTaskApi<internal::QAOutput, const internal::QAInput&> {
+ public:
+  using BaseTaskApi::BaseTaskApi;
+  using FeatureVector = ::tflite::task::processor::FeatureVector;
+
+  // TODO(b/198995952): add support to parameterize.
+  static constexpr int kFinalEmbeddingSize = 100;
+
+  static tflite::support::StatusOr<std::unique_ptr<UniversalSentenceEncoderQA>>
+  CreateFromOption(const tflite::task::text::RetrievalOptions& options,
+                   std::unique_ptr<tflite::OpResolver> resolver =
+                       CreateQACustomOpResolver());
+
+  // Retrieves output from the input by running TFLite engine.
+  // Returns an error, if either query_text or responses is empty.
+  tflite::support::StatusOr<RetrievalOutput> Retrieve(
+      const RetrievalInput& input);
+
+  // Encodes query from the text.
+  // Returns an error, if query text is empty.
+  tflite::support::StatusOr<FeatureVector> EncodeQuery(
+      absl::string_view query_text);
+
+  // Encodes response from the text and/or context.
+  // Returns an error, if both text and context are empty.
+  tflite::support::StatusOr<FeatureVector> EncodeResponse(
+      absl::string_view response_text,
+      absl::string_view response_context);
+
+  // Calculates similarity between two encoded vectors (require same size).
+  static tflite::support::StatusOr<float> Similarity(const FeatureVector& a,
+                                                     const FeatureVector& b);
+
+  // Gets top k corresponding to output response scores in descending order.
+  // If k == 0, all responses are ranked.
+  static std::vector<size_t> Top(const RetrievalOutput& output, size_t k = 0);
+
+ private:
+  absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
+                          const internal::QAInput& input) override;
+
+  tflite::support::StatusOr<internal::QAOutput> Postprocess(
+      const std::vector<const TfLiteTensor*>& output_tensors,
+      const internal::QAInput& input) override;
+
+  internal::QAOutput Run(absl::string_view query_text,
+                         absl::string_view response_text,
+                         absl::string_view response_context);
+
+  std::unique_ptr<tflite::task::text::RetrievalOptions> proto_options_;
+};
+
+}  // namespace retrieval
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
+
+#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_TEXT_UNIVERSAL_SENTENCE_ENCODER_QA_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/BUILD
index d426486f..ab6d7b9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/BUILD
@@ -1,3 +1,5 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
 package(
     default_visibility = [
         "//visibility:public",
@@ -5,19 +7,28 @@
     licenses = ["notice"],  # Apache 2.0
 )
 
-cc_library(
+# IMPORTANT: in order to use hardware acceleration delegates, configurable through the
+# `compute_settings` field of the ObjectDetectorOptions, you must additionally link to
+# the appropriate delegate plugin target (e.g. `gpu_plugin` for GPU) from:
+# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/BUILD
+# To use EDGETPU_CORAL, link to `edgetpu_coral_plugin` from:
+# https://github.com/tensorflow/tflite-support/blob/a58a4f9225c411fa9ba29f821523e6e283988d23/tensorflow_lite_support/acceleration/configuration/BUILD#L11
+cc_library_with_tflite(
     name = "object_detector",
     srcs = ["object_detector.cc"],
     hdrs = ["object_detector.h"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/core:external_file_handler",
-        "//tensorflow_lite_support/cc/task/core:task_api_factory",
         "//tensorflow_lite_support/cc/task/core:task_utils",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
-        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/core:label_map_item",
         "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
@@ -25,6 +36,7 @@
         "//tensorflow_lite_support/cc/task/vision/proto:detections_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:object_detector_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:score_calibration",
         "//tensorflow_lite_support/metadata:metadata_schema_cc",
         "//tensorflow_lite_support/metadata/cc:metadata_extractor",
         "@com_google_absl//absl/container:flat_hash_set",
@@ -32,26 +44,35 @@
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
         "@com_google_absl//absl/strings:str_format",
-        "@org_tensorflow//tensorflow/lite:framework",
+        "@com_google_glog//:glog",
         "@org_tensorflow//tensorflow/lite/c:common",
         "@org_tensorflow//tensorflow/lite/core/api",
     ],
 )
 
-cc_library(
+# IMPORTANT: in order to use hardware acceleration delegates, configurable through the
+# `compute_settings` field of the ImageClassifierOptions, you must additionally link to
+# the appropriate delegate plugin target (e.g. `gpu_plugin` for GPU) from:
+# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/BUILD
+# To use EDGETPU_CORAL, link to `edgetpu_coral_plugin` from:
+# https://github.com/tensorflow/tflite-support/blob/a58a4f9225c411fa9ba29f821523e6e283988d23/tensorflow_lite_support/acceleration/configuration/BUILD#L11
+cc_library_with_tflite(
     name = "image_classifier",
     srcs = ["image_classifier.cc"],
     hdrs = ["image_classifier.h"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/core:external_file_handler",
-        "//tensorflow_lite_support/cc/task/core:task_api_factory",
         "//tensorflow_lite_support/cc/task/core:task_utils",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
-        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
         "//tensorflow_lite_support/cc/task/vision/core:classification_head",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/core:label_map_item",
@@ -69,26 +90,34 @@
         "@com_google_absl//absl/strings",
         "@com_google_absl//absl/strings:str_format",
         "@flatbuffers",
-        "@org_tensorflow//tensorflow/lite:framework",
         "@org_tensorflow//tensorflow/lite/c:common",
         "@org_tensorflow//tensorflow/lite/core/api",
     ],
 )
 
-cc_library(
+# IMPORTANT: in order to use hardware acceleration delegates, configurable through the
+# `compute_settings` field of the ImageSegmenterOptions, you must additionally link to
+# the appropriate delegate plugin target (e.g. `gpu_plugin` for GPU) from:
+# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/BUILD
+# To use EDGETPU_CORAL, link to `edgetpu_coral_plugin` from:
+# https://github.com/tensorflow/tflite-support/blob/a58a4f9225c411fa9ba29f821523e6e283988d23/tensorflow_lite_support/acceleration/configuration/BUILD#L11
+cc_library_with_tflite(
     name = "image_segmenter",
     srcs = ["image_segmenter.cc"],
     hdrs = ["image_segmenter.h"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/core:external_file_handler",
-        "//tensorflow_lite_support/cc/task/core:task_api_factory",
         "//tensorflow_lite_support/cc/task/core:task_utils",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
-        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/core:label_map_item",
         "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
@@ -106,3 +135,41 @@
         "@org_tensorflow//tensorflow/lite/core/api",
     ],
 )
+
+# IMPORTANT: in order to use hardware acceleration delegates, configurable through the
+# `compute_settings` field of the ImageEmbedderOptions, you must additionally link to
+# the appropriate delegate plugin target (e.g. `gpu_plugin` for GPU) from:
+# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/BUILD
+# To use EDGETPU_CORAL, link to `edgetpu_coral_plugin` from:
+# https://github.com/tensorflow/tflite-support/blob/a58a4f9225c411fa9ba29f821523e6e283988d23/tensorflow_lite_support/acceleration/configuration/BUILD#L11
+cc_library_with_tflite(
+    name = "image_embedder",
+    srcs = ["image_embedder.cc"],
+    hdrs = ["image_embedder.h"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision/core:base_vision_task_api",
+        "//tensorflow_lite_support/cc/task/processor:embedding_postprocessor",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:integral_types",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:external_file_handler",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:embeddings_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_embedder_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "@com_google_absl//absl/container:node_hash_set",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/core/api:op_resolver",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/BUILD
index 1df86cb..9043269 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/BUILD
@@ -1,28 +1,33 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
 package(
     default_visibility = [
-        "//visibility:public",
+        "//tensorflow_lite_support:internal",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
 
 exports_files(srcs = ["base_vision_task_api.h"])
 
-cc_library(
+cc_library_with_tflite(
     name = "base_vision_task_api",
     hdrs = [
         "base_vision_task_api.h",
     ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision/utils:image_tensor_specs",
+        "//tensorflow_lite_support/cc/task/processor:image_preprocessor",
+    ],
     deps = [
         ":frame_buffer",
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:status_macros",
-        "//tensorflow_lite_support/cc/task/core:base_task_api",
         "//tensorflow_lite_support/cc/task/core:task_utils",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
         "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
-        "//tensorflow_lite_support/cc/task/vision/utils:image_tensor_specs",
         "//tensorflow_lite_support/metadata:metadata_schema_cc",
         "@com_google_absl//absl/memory",
         "@com_google_absl//absl/status",
@@ -35,6 +40,7 @@
     name = "frame_buffer",
     srcs = ["frame_buffer.cc"],
     hdrs = ["frame_buffer.h"],
+    visibility = ["//visibility:public"],
     deps = [
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:statusor",
@@ -51,6 +57,9 @@
     name = "label_map_item",
     srcs = ["label_map_item.cc"],
     hdrs = ["label_map_item.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:statusor",
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
index c787876b..d3557fc 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h
@@ -21,9 +21,9 @@
 #include <utility>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/status/status.h"
-#include "absl/time/clock.h"
+#include "absl/memory/memory.h"  // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/time/clock.h"     // from @com_google_absl
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/integral_types.h"
@@ -31,6 +31,7 @@
 #include "tensorflow_lite_support/cc/task/core/base_task_api.h"
 #include "tensorflow_lite_support/cc/task/core/task_utils.h"
 #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/processor/image_preprocessor.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
@@ -56,19 +57,15 @@
   BaseVisionTaskApi(const BaseVisionTaskApi&) = delete;
   BaseVisionTaskApi& operator=(const BaseVisionTaskApi&) = delete;
 
-  // Number of bytes required for 8-bit per pixel RGB color space.
-  static constexpr int kRgbPixelBytes = 3;
-
   // Sets the ProcessEngine used for image pre-processing. Must be called before
   // any inference is performed. Can be called between inferences to override
   // the current process engine.
   void SetProcessEngine(const FrameBufferUtils::ProcessEngine& process_engine) {
-    frame_buffer_utils_ = FrameBufferUtils::Create(process_engine);
+    process_engine_ = process_engine;
   }
 
  protected:
-  using tflite::task::core::
-      BaseTaskApi<OutputType, const FrameBuffer&, const BoundingBox&>::engine_;
+  FrameBufferUtils::ProcessEngine process_engine_;
 
   // Checks input tensor and metadata (if any) are valid, or return an error
   // otherwise. This must be called once at initialization time, before running
@@ -76,19 +73,10 @@
   // Note: the underlying interpreter and metadata extractor are assumed to be
   // already successfully initialized before calling this method.
   virtual absl::Status CheckAndSetInputs() {
-    ASSIGN_OR_RETURN(
-        ImageTensorSpecs input_specs,
-        BuildInputImageTensorSpecs(*engine_->interpreter(),
-                                   *engine_->metadata_extractor()));
-
-    if (input_specs.color_space != tflite::ColorSpaceType_RGB) {
-      return tflite::support::CreateStatusWithPayload(
-          absl::StatusCode::kUnimplemented,
-          "BaseVisionTaskApi only supports RGB color space for now.");
-    }
-
-    input_specs_ = absl::make_unique<ImageTensorSpecs>(input_specs);
-
+    // BaseTaskApi always assume having a single input.
+    ASSIGN_OR_RETURN(preprocessor_,
+                     ::tflite::task::processor::ImagePreprocessor::Create(
+                         this->GetTfLiteEngine(), {0}, process_engine_));
     return absl::OkStatus();
   }
 
@@ -115,153 +103,28 @@
   absl::Status Preprocess(const std::vector<TfLiteTensor*>& input_tensors,
                           const FrameBuffer& frame_buffer,
                           const BoundingBox& roi) override {
-    if (input_specs_ == nullptr) {
+    if (preprocessor_ == nullptr) {
+      return tflite::support::CreateStatusWithPayload(
+          absl::StatusCode::kInternal,
+          "Uninitialized preprocessor: CheckAndSetInputs must be called "
+          "at initialization time.");
+    }
+    if (GetInputSpecs().image_height == 0 && GetInputSpecs().image_width == 0) {
       return tflite::support::CreateStatusWithPayload(
           absl::StatusCode::kInternal,
           "Uninitialized input tensor specs: CheckAndSetInputs must be called "
           "at initialization time.");
     }
-
-    if (frame_buffer_utils_ == nullptr) {
-      return tflite::support::CreateStatusWithPayload(
-          absl::StatusCode::kInternal,
-          "Uninitialized frame buffer utils: SetProcessEngine must be called "
-          "at initialization time.");
-    }
-
-    if (input_tensors.size() != 1) {
-      return tflite::support::CreateStatusWithPayload(
-          absl::StatusCode::kInternal, "A single input tensor is expected.");
-    }
-
-    // Input data to be normalized (if needed) and used for inference. In most
-    // cases, this is the result of image preprocessing. In case no image
-    // preprocessing is needed (see below), this points to the input frame
-    // buffer raw data.
-    const uint8* input_data;
-    size_t input_data_byte_size;
-
-    // Optional buffers in case image preprocessing is needed.
-    std::unique_ptr<FrameBuffer> preprocessed_frame_buffer;
-    std::vector<uint8> preprocessed_data;
-
-    if (IsImagePreprocessingNeeded(frame_buffer, roi)) {
-      // Preprocess input image to fit model requirements.
-      // For now RGB is the only color space supported, which is ensured by
-      // `CheckAndSetInputs`.
-      FrameBuffer::Dimension to_buffer_dimension = {input_specs_->image_width,
-                                                    input_specs_->image_height};
-      input_data_byte_size =
-          GetBufferByteSize(to_buffer_dimension, FrameBuffer::Format::kRGB);
-      preprocessed_data.resize(input_data_byte_size / sizeof(uint8), 0);
-      input_data = preprocessed_data.data();
-
-      FrameBuffer::Plane preprocessed_plane = {
-          /*buffer=*/preprocessed_data.data(),
-          /*stride=*/{input_specs_->image_width * kRgbPixelBytes,
-                      kRgbPixelBytes}};
-      preprocessed_frame_buffer = FrameBuffer::Create(
-          {preprocessed_plane}, to_buffer_dimension, FrameBuffer::Format::kRGB,
-          FrameBuffer::Orientation::kTopLeft);
-
-      RETURN_IF_ERROR(frame_buffer_utils_->Preprocess(
-          frame_buffer, roi, preprocessed_frame_buffer.get()));
-    } else {
-      // Input frame buffer already targets model requirements: skip image
-      // preprocessing. For RGB, the data is always stored in a single plane.
-      input_data = frame_buffer.plane(0).buffer;
-      input_data_byte_size = frame_buffer.plane(0).stride.row_stride_bytes *
-                             frame_buffer.dimension().height;
-    }
-
-    // Then normalize pixel data (if needed) and populate the input tensor.
-    switch (input_specs_->tensor_type) {
-      case kTfLiteUInt8:
-        if (input_tensors[0]->bytes != input_data_byte_size) {
-          return tflite::support::CreateStatusWithPayload(
-              absl::StatusCode::kInternal,
-              "Size mismatch or unsupported padding bytes between pixel data "
-              "and input tensor.");
-        }
-        // No normalization required: directly populate data.
-        tflite::task::core::PopulateTensor(
-            input_data, input_data_byte_size / sizeof(uint8), input_tensors[0]);
-        break;
-      case kTfLiteFloat32: {
-        if (input_tensors[0]->bytes / sizeof(float) !=
-            input_data_byte_size / sizeof(uint8)) {
-          return tflite::support::CreateStatusWithPayload(
-              absl::StatusCode::kInternal,
-              "Size mismatch or unsupported padding bytes between pixel data "
-              "and input tensor.");
-        }
-        // Normalize and populate.
-        float* normalized_input_data =
-            tflite::task::core::AssertAndReturnTypedTensor<float>(
-                input_tensors[0]);
-        const tflite::task::vision::NormalizationOptions&
-            normalization_options = input_specs_->normalization_options.value();
-        if (normalization_options.num_values == 1) {
-          float mean_value = normalization_options.mean_values[0];
-          float inv_std_value = (1.0f / normalization_options.std_values[0]);
-          for (size_t i = 0; i < input_data_byte_size / sizeof(uint8);
-               i++, input_data++, normalized_input_data++) {
-            *normalized_input_data =
-                inv_std_value * (static_cast<float>(*input_data) - mean_value);
-          }
-        } else {
-          std::array<float, 3> inv_std_values = {
-              1.0f / normalization_options.std_values[0],
-              1.0f / normalization_options.std_values[1],
-              1.0f / normalization_options.std_values[2]};
-          for (size_t i = 0; i < input_data_byte_size / sizeof(uint8);
-               i++, input_data++, normalized_input_data++) {
-            *normalized_input_data = inv_std_values[i % 3] *
-                                     (static_cast<float>(*input_data) -
-                                      normalization_options.mean_values[i % 3]);
-          }
-        }
-        break;
-      }
-      case kTfLiteInt8:
-        return tflite::support::CreateStatusWithPayload(
-            absl::StatusCode::kUnimplemented,
-            "kTfLiteInt8 input type is not implemented yet.");
-      default:
-        return tflite::support::CreateStatusWithPayload(
-            absl::StatusCode::kInternal, "Unexpected input tensor type.");
-    }
-
-    return absl::OkStatus();
+    return preprocessor_->Preprocess(frame_buffer, roi);
   }
 
-  // Utils for input image preprocessing (resizing, colorspace conversion, etc).
-  std::unique_ptr<FrameBufferUtils> frame_buffer_utils_;
-
-  // Parameters related to the input tensor which represents an image.
-  std::unique_ptr<ImageTensorSpecs> input_specs_;
+  // Returns the spec for the input image.
+  const vision::ImageTensorSpecs& GetInputSpecs() const {
+    return preprocessor_->GetInputSpecs();
+  }
 
  private:
-  // Returns false if image preprocessing could be skipped, true otherwise.
-  bool IsImagePreprocessingNeeded(const FrameBuffer& frame_buffer,
-                                  const BoundingBox& roi) {
-    // Is crop required?
-    if (roi.origin_x() != 0 || roi.origin_y() != 0 ||
-        roi.width() != frame_buffer.dimension().width ||
-        roi.height() != frame_buffer.dimension().height) {
-      return true;
-    }
-
-    // Are image transformations required?
-    if (frame_buffer.orientation() != FrameBuffer::Orientation::kTopLeft ||
-        frame_buffer.format() != FrameBuffer::Format::kRGB ||
-        frame_buffer.dimension().width != input_specs_->image_width ||
-        frame_buffer.dimension().height != input_specs_->image_height) {
-      return true;
-    }
-
-    return false;
-  }
+  std::unique_ptr<processor::ImagePreprocessor> preprocessor_ = nullptr;
 };
 
 }  // namespace vision
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.cc
index 962cb34b..b5b57f2 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.cc
@@ -14,7 +14,7 @@
 ==============================================================================*/
 #include "tensorflow_lite_support/cc/task/vision/core/classification_head.h"
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h
index 07cd8b9..2e1aa6d 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/classification_head.h
@@ -18,8 +18,8 @@
 #include <string>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/strings/string_view.h"
+#include "absl/memory/memory.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
 #include "tensorflow_lite_support/cc/task/vision/utils/score_calibration.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
index 42ac080..2936f5a 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/frame_buffer.h
@@ -22,12 +22,12 @@
 #include <utility>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_cat.h"
-#include "absl/time/clock.h"
-#include "absl/time/time.h"
-#include "absl/types/optional.h"
+#include "absl/memory/memory.h"    // from @com_google_absl
+#include "absl/status/status.h"    // from @com_google_absl
+#include "absl/strings/str_cat.h"  // from @com_google_absl
+#include "absl/time/clock.h"       // from @com_google_absl
+#include "absl/time/time.h"        // from @com_google_absl
+#include "absl/types/optional.h"   // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 
@@ -74,7 +74,16 @@
 class FrameBuffer {
  public:
   // Colorspace formats.
-  enum class Format { kRGBA, kRGB, kNV12, kNV21, kYV12, kYV21, kGRAY };
+  enum class Format {
+    kRGBA,
+    kRGB,
+    kNV12,
+    kNV21,
+    kYV12,
+    kYV21,
+    kGRAY,
+    kUNKNOWN
+  };
 
   // Stride information.
   struct Stride {
@@ -85,6 +94,13 @@
     // pixels in bytes. It may be larger than the size of a single pixel to
     // account for interleaved image data or padded formats.
     int pixel_stride_bytes;
+
+    bool operator==(const Stride& other) const {
+      return row_stride_bytes == other.row_stride_bytes &&
+             pixel_stride_bytes == other.pixel_stride_bytes;
+    }
+
+    bool operator!=(const Stride& other) const { return !operator==(other); }
   };
 
   // YUV data structure.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc
index ee2d9ad..67fe0753 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.cc
@@ -15,8 +15,8 @@
 ==============================================================================*/
 #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
 
-#include "absl/strings/str_format.h"
-#include "absl/strings/str_split.h"
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "absl/strings/str_split.h"   // from @com_google_absl
 #include "tensorflow_lite_support/cc/common.h"
 
 namespace tflite {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h
index 8a95362..20c316b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/core/label_map_item.h
@@ -18,10 +18,10 @@
 #include <string>
 #include <vector>
 
-#include "absl/container/flat_hash_map.h"
-#include "absl/container/flat_hash_set.h"
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/container/flat_hash_set.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/string_view.h"      // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 
 namespace tflite {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc
index 313f28b..36ab3c3 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.cc
@@ -15,11 +15,10 @@
 
 #include "tensorflow_lite_support/cc/task/vision/image_classifier.h"
 
-#include "absl/algorithm/container.h"
-#include "absl/strings/str_format.h"
-#include "absl/strings/string_view.h"
-#include "flatbuffers/flatbuffers.h"  // from @flatbuffers
-#include "tensorflow/lite/interpreter.h"
+#include "absl/algorithm/container.h"  // from @com_google_absl
+#include "absl/strings/str_format.h"   // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "flatbuffers/flatbuffers.h"   // from @flatbuffers
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
@@ -47,26 +46,6 @@
 using ::tflite::task::core::TaskAPIFactory;
 using ::tflite::task::core::TfLiteEngine;
 
-// Default score value used as a fallback for classes that (1) have no score
-// calibration data or (2) have a very low confident uncalibrated score, i.e.
-// lower than the `min_uncalibrated_score` threshold.
-//
-// (1) This happens when the ScoreCalibration does not cover all the classes
-// listed in the label map. This can be used to enforce the blacklisting of
-// given classes so that they are never returned.
-//
-// (2) This is an optional threshold provided part of the calibration data. It
-// is used to mitigate false alarms on some classes.
-//
-// In both cases, a class that gets assigned a score of -1 is never returned as
-// it gets discarded by the `score_threshold` check (see post-processing logic).
-constexpr float kDefaultCalibratedScore = -1.0f;
-
-// Calibrated scores should be in the [0, 1] range, otherwise an error is
-// returned at post-processing time.
-constexpr float kMinCalibratedScore = 0.0f;
-constexpr float kMaxCalibratedScore = 1.0f;
-
 }  // namespace
 
 /* static */
@@ -78,10 +57,25 @@
   // Copy options to ensure the ExternalFile outlives the constructed object.
   auto options_copy = absl::make_unique<ImageClassifierOptions>(options);
 
-  ASSIGN_OR_RETURN(auto image_classifier,
-                   TaskAPIFactory::CreateFromExternalFileProto<ImageClassifier>(
-                       &options_copy->model_file_with_metadata(),
-                       std::move(resolver), options_copy->num_threads()));
+  std::unique_ptr<ImageClassifier> image_classifier;
+  if (options_copy->has_model_file_with_metadata()) {
+    ASSIGN_OR_RETURN(
+        image_classifier,
+        TaskAPIFactory::CreateFromExternalFileProto<ImageClassifier>(
+            &options_copy->model_file_with_metadata(), std::move(resolver),
+            options_copy->num_threads(), options_copy->compute_settings()));
+  } else if (options_copy->base_options().has_model_file()) {
+    ASSIGN_OR_RETURN(image_classifier,
+                     TaskAPIFactory::CreateFromBaseOptions<ImageClassifier>(
+                         &options_copy->base_options(), std::move(resolver)));
+  } else {
+    // Should never happen because of SanityCheckOptions.
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 0."),
+        TfLiteSupportStatus::kInvalidArgumentError);
+  }
 
   RETURN_IF_ERROR(image_classifier->Init(std::move(options_copy)));
 
@@ -91,10 +85,14 @@
 /* static */
 absl::Status ImageClassifier::SanityCheckOptions(
     const ImageClassifierOptions& options) {
-  if (!options.has_model_file_with_metadata()) {
+  int num_input_models = (options.base_options().has_model_file() ? 1 : 0) +
+                         (options.has_model_file_with_metadata() ? 1 : 0);
+  if (num_input_models != 1) {
     return CreateStatusWithPayload(
         StatusCode::kInvalidArgument,
-        "Missing mandatory `model_file_with_metadata` field",
+        absl::StrFormat("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found %d.",
+                        num_input_models),
         TfLiteSupportStatus::kInvalidArgumentError);
   }
   if (options.max_results() == 0) {
@@ -103,14 +101,6 @@
         "Invalid `max_results` option: value must be != 0",
         TfLiteSupportStatus::kInvalidArgumentError);
   }
-  if (options.score_threshold() < 0 || options.score_threshold() >= 1) {
-    return CreateStatusWithPayload(
-        StatusCode::kInvalidArgument,
-        absl::StrFormat(
-            "`score_threshold` out of range: %f. Valid range is [0,1[.",
-            options.score_threshold()),
-        TfLiteSupportStatus::kInvalidArgumentError);
-  }
   if (options.class_name_whitelist_size() > 0 &&
       options.class_name_blacklist_size() > 0) {
     return CreateStatusWithPayload(
@@ -161,11 +151,11 @@
 }
 
 absl::Status ImageClassifier::CheckAndSetOutputs() {
-  num_outputs_ = TfLiteEngine::OutputCount(engine_->interpreter());
+  num_outputs_ = TfLiteEngine::OutputCount(GetTfLiteEngine()->interpreter());
 
   // Perform sanity checks and extract metadata.
   const ModelMetadataExtractor* metadata_extractor =
-      engine_->metadata_extractor();
+      GetTfLiteEngine()->metadata_extractor();
 
   const flatbuffers::Vector<flatbuffers::Offset<tflite::TensorMetadata>>*
       output_tensor_metadata = metadata_extractor->GetOutputTensorMetadata();
@@ -220,7 +210,7 @@
   int num_quantized_outputs = 0;
   for (int i = 0; i < num_outputs_; ++i) {
     const TfLiteTensor* output_tensor =
-        TfLiteEngine::GetOutput(engine_->interpreter(), i);
+        TfLiteEngine::GetOutput(GetTfLiteEngine()->interpreter(), i);
     const int num_dimensions = output_tensor->dims->size;
     if (num_dimensions == 4) {
       if (output_tensor->dims->data[1] != 1 ||
@@ -370,12 +360,6 @@
       continue;
     }
 
-    // Use a specific default score instead of the one specified by default in
-    // cc/task/vision/utils/score_calibration.h. See `kDefaultCalibratedScore`
-    // documentation for more details.
-    classification_heads_[i].calibration_params->default_score =
-        kDefaultCalibratedScore;
-
     score_calibrations_[i] = absl::make_unique<ScoreCalibration>();
     if (score_calibrations_[i] == nullptr) {
       return CreateStatusWithPayload(
@@ -427,16 +411,16 @@
 
     const TfLiteTensor* output_tensor = output_tensors[i];
     if (has_uint8_outputs_) {
-      const uint8* output_data =
-          AssertAndReturnTypedTensor<uint8>(output_tensor);
+      ASSIGN_OR_RETURN(const uint8* output_data,
+                       AssertAndReturnTypedTensor<uint8>(output_tensor));
       for (int j = 0; j < head.label_map_items.size(); ++j) {
         score_pairs.emplace_back(j, output_tensor->params.scale *
                                         (static_cast<int>(output_data[j]) -
                                          output_tensor->params.zero_point));
       }
     } else {
-      const float* output_data =
-          AssertAndReturnTypedTensor<float>(output_tensor);
+      ASSIGN_OR_RETURN(const float* output_data,
+                       AssertAndReturnTypedTensor<float>(output_tensor));
       for (int j = 0; j < head.label_map_items.size(); ++j) {
         score_pairs.emplace_back(j, output_data[j]);
       }
@@ -447,23 +431,20 @@
       for (auto& score_pair : score_pairs) {
         const std::string& class_name =
             head.label_map_items[score_pair.first].name;
+
+        // In ComputeCalibratedScore, score_pair.second is set to the
+        // default_score value from metadata [1] if the category (1) has no
+        // score calibration data or (2) has a very low confident uncalibrated
+        // score, i.e. lower than the `min_uncalibrated_score` threshold.
+        // Otherwise, score_pair.second is calculated based on the selected
+        // score transformation function, and the value is guaranteed to be in
+        // the range of [0, scale], where scale is a label-dependent sigmoid
+        // parameter.
+        //
+        // [1]:
+        // https://github.com/tensorflow/tflite-support/blob/af26cb6952ccdeee0e849df2b93dbe7e57f6bc48/tensorflow_lite_support/metadata/metadata_schema.fbs#L453
         score_pair.second = score_calibrations_[i]->ComputeCalibratedScore(
             class_name, score_pair.second);
-        if (score_pair.second > kMaxCalibratedScore) {
-          return CreateStatusWithPayload(
-              StatusCode::kInternal,
-              absl::StrFormat("calibrated score is too high: got %f, expected "
-                              "%f as maximum.",
-                              score_pair.second, kMaxCalibratedScore));
-        }
-        if (score_pair.second != kDefaultCalibratedScore &&
-            score_pair.second < kMinCalibratedScore) {
-          return CreateStatusWithPayload(
-              StatusCode::kInternal,
-              absl::StrFormat("calibrated score is too low: got %f, expected "
-                              "%f as minimum.",
-                              score_pair.second, kMinCalibratedScore));
-        }
       }
     }
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h
index 4c3affe..eb0c13e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_classifier.h
@@ -19,10 +19,11 @@
 #include <memory>
 #include <vector>
 
-#include "absl/container/flat_hash_set.h"
-#include "absl/status/status.h"
+#include "absl/container/flat_hash_set.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
@@ -80,7 +81,7 @@
   CreateFromOptions(
       const ImageClassifierOptions& options,
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
 
   // Performs actual classification on the provided FrameBuffer.
   //
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc
new file mode 100644
index 0000000..943a39b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.cc
@@ -0,0 +1,161 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/vision/image_embedder.h"
+
+#include <algorithm>
+
+#include "absl/container/node_hash_set.h"  // from @com_google_absl
+#include "absl/memory/memory.h"            // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/str_format.h"       // from @com_google_absl
+#include "absl/strings/string_view.h"      // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+
+namespace {
+using ::tflite::task::core::TaskAPIFactory;
+
+tflite::support::StatusOr<std::unique_ptr<processor::EmbeddingPostprocessor>>
+CreatePostprocessor(core::TfLiteEngine* engine,
+                    const std::initializer_list<int> output_indices,
+                    const ImageEmbedderOptions& options) {
+  auto new_options = std::make_unique<processor::EmbeddingOptions>();
+  new_options->set_l2_normalize(options.l2_normalize());
+  new_options->set_quantize(options.quantize());
+  return processor::EmbeddingPostprocessor::Create(engine, output_indices,
+                                                   std::move(new_options));
+}
+}  // namespace
+
+/* static */
+tflite::support::StatusOr<double> ImageEmbedder::CosineSimilarity(
+    const FeatureVector& u,
+    const FeatureVector& v) {
+  return processor::EmbeddingPostprocessor::CosineSimilarity(u, v);
+}
+
+/* static */
+tflite::support::StatusOr<std::unique_ptr<ImageEmbedder>>
+ImageEmbedder::CreateFromOptions(const ImageEmbedderOptions& options,
+                                 std::unique_ptr<tflite::OpResolver> resolver) {
+  // Copy options to ensure the ExternalFile-s outlive the constructed object.
+  auto options_copy = absl::make_unique<ImageEmbedderOptions>(options);
+
+  ASSIGN_OR_RETURN(
+      auto image_embedder,
+      TaskAPIFactory::CreateFromExternalFileProto<ImageEmbedder>(
+          &options_copy->model_file_with_metadata(), std::move(resolver),
+          options_copy->num_threads(), options_copy->compute_settings()));
+
+  RETURN_IF_ERROR(image_embedder->Init(std::move(options_copy)));
+
+  return image_embedder;
+}
+
+absl::Status ImageEmbedder::PreInit() {
+  SetProcessEngine(FrameBufferUtils::ProcessEngine::kLibyuv);
+  return absl::OkStatus();
+}
+
+absl::Status ImageEmbedder::PostInit() {
+  // Nothing to do.
+  return absl::OkStatus();
+}
+
+absl::Status ImageEmbedder::Init(
+    std::unique_ptr<ImageEmbedderOptions> options) {
+  // Set options.
+  options_ = std::move(options);
+
+  // Perform pre-initialization actions.
+  RETURN_IF_ERROR(PreInit());
+
+  // Sanity check and set inputs and outputs.
+  RETURN_IF_ERROR(CheckAndSetInputs());
+
+  // Perform post-initialization actions.
+  RETURN_IF_ERROR(PostInit());
+
+  // ImageEmbedder assumes that all output tensors share the same
+  // embedding option.
+  postprocessors_.reserve(GetTfLiteEngine()->interpreter()->outputs().size());
+  for (int i = 0; i < GetTfLiteEngine()->interpreter()->outputs().size(); i++) {
+    ASSIGN_OR_RETURN(auto processor,
+                     CreatePostprocessor(GetTfLiteEngine(), {i}, *options_));
+    postprocessors_.emplace_back(std::move(processor));
+  }
+
+  return absl::OkStatus();
+}
+
+tflite::support::StatusOr<EmbeddingResult> ImageEmbedder::Embed(
+    const FrameBuffer& frame_buffer) {
+  BoundingBox roi;
+  roi.set_width(frame_buffer.dimension().width);
+  roi.set_height(frame_buffer.dimension().height);
+  return Embed(frame_buffer, roi);
+}
+
+tflite::support::StatusOr<EmbeddingResult> ImageEmbedder::Embed(
+    const FrameBuffer& frame_buffer,
+    const BoundingBox& roi) {
+  return InferWithFallback(frame_buffer, roi);
+}
+
+tflite::support::StatusOr<EmbeddingResult> ImageEmbedder::Postprocess(
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const FrameBuffer& /*frame_buffer*/,
+    const BoundingBox& /*roi*/) {
+  EmbeddingResult result;
+  for (int i = 0; i < postprocessors_.size(); ++i) {
+    RETURN_IF_ERROR(
+        postprocessors_.at(i)->Postprocess(result.add_embeddings()));
+  }
+
+  return result;
+}
+
+Embedding ImageEmbedder::GetEmbeddingByIndex(const EmbeddingResult& result,
+                                             int output_index) {
+  if (output_index < 0 || output_index >= postprocessors_.size()) {
+    return Embedding();
+  }
+  return result.embeddings(output_index);
+}
+
+int ImageEmbedder::GetEmbeddingDimension(int output_index) const {
+  if (output_index < 0 || output_index >= postprocessors_.size()) {
+    return -1;
+  }
+  return postprocessors_.at(output_index)->GetEmbeddingDimension();
+}
+
+int ImageEmbedder::GetNumberOfOutputLayers() const {
+  return postprocessors_.size();
+}
+
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h
new file mode 100644
index 0000000..93e2455
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_embedder.h
@@ -0,0 +1,152 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_IMAGE_EMBEDDER_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_IMAGE_EMBEDDER_H_
+
+#include <vector>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
+#include "tensorflow_lite_support/cc/port/integral_types.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+#include "tensorflow_lite_support/cc/task/processor/embedding_postprocessor.h"
+#include "tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/embeddings_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_embedder_options_proto_inc.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+
+// Performs dense feature vector extraction on images.
+//
+// The API expects a TFLite model with optional, but strongly recommended,
+// TFLite Model Metadata.
+//
+// Input tensor:
+//   (kTfLiteUInt8/kTfLiteFloat32)
+//    - image input of size `[batch x height x width x channels]`.
+//    - batch inference is not supported (`batch` is required to be 1).
+//    - only RGB inputs are supported (`channels` is required to be 3).
+//    - if type is kTfLiteFloat32, NormalizationOptions are required to be
+//      attached to the metadata for input normalization.
+// At least one output tensor with:
+//   (kTfLiteUInt8/kTfLiteFloat32)
+//    - `N` components corresponding to the `N` dimensions of the returned
+//      feature vector for this output layer.
+//    - Either 2 or 4 dimensions, i.e. `[1 x N]` or `[1 x 1 x 1 x N]`.
+//
+// TODO(b/180502532): add pointer to example model.
+//
+// A CLI demo tool is available for easily trying out this API, and provides
+// example usage. See:
+// examples/task/vision/desktop/image_embedder_demo.cc
+class ImageEmbedder
+    : public tflite::task::vision::BaseVisionTaskApi<EmbeddingResult> {
+ public:
+  using BaseVisionTaskApi::BaseVisionTaskApi;
+
+  // Creates an ImageEmbedder from the provided options. A non-default
+  // OpResolver can be specified in order to support custom Ops or specify a
+  // subset of built-in Ops.
+  static tflite::support::StatusOr<std::unique_ptr<ImageEmbedder>>
+  CreateFromOptions(
+      const ImageEmbedderOptions& options,
+      std::unique_ptr<tflite::OpResolver> resolver =
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
+
+  // Performs actual feature vector extraction on the provided FrameBuffer.
+  //
+  // The FrameBuffer can be of any size and any of the supported formats, i.e.
+  // RGBA, RGB, NV12, NV21, YV12, YV21. It is automatically pre-processed before
+  // inference in order to (and in this order):
+  // - resize it (with bilinear interpolation, aspect-ratio *not* preserved) to
+  //   the dimensions of the model input tensor,
+  // - convert it to the colorspace of the input tensor (i.e. RGB, which is the
+  //   only supported colorspace for now),
+  // - rotate it according to its `Orientation` so that inference is performed
+  //   on an "upright" image.
+  tflite::support::StatusOr<EmbeddingResult> Embed(
+      const FrameBuffer& frame_buffer);
+
+  // Same as above, except the inference is performed only on the provided
+  // region of interest. Note that the region of interest is not clamped, so
+  // this method will fail if the region is out of bounds of the input image.
+  tflite::support::StatusOr<EmbeddingResult> Embed(
+      const FrameBuffer& frame_buffer,
+      const BoundingBox& roi);
+
+  // Returns the Embedding output by the output_index'th layer. In (the most
+  // common) case where a single embedding is produced, you can just call
+  // GetEmbeddingByIndex(result, 0).
+  // Returns an empty Embedding if `output_index` is out of bounds.
+  Embedding GetEmbeddingByIndex(const EmbeddingResult& result,
+                                int output_index);
+
+  // Returns the dimensionality of the embedding output by the output_index'th
+  // output layer. Returns -1 if `output_index` is out of bounds.
+  int GetEmbeddingDimension(int output_index) const;
+
+  // Returns the number of output layers of the model.
+  int GetNumberOfOutputLayers() const;
+
+  // Utility function to compute cosine similarity [1] between two feature
+  // vectors. May return an InvalidArgumentError if e.g. the feature vectors are
+  // of different types (quantized vs. float), have different sizes, or have a
+  // an L2-norm of 0.
+  //
+  // [1]: https://en.wikipedia.org/wiki/Cosine_similarity
+  static tflite::support::StatusOr<double> CosineSimilarity(
+      const FeatureVector& u,
+      const FeatureVector& v);
+
+ protected:
+  // The options used to build this ImageEmbedder.
+  std::unique_ptr<ImageEmbedderOptions> options_;
+
+  // Post-processing to transform the raw model outputs into embedding results.
+  tflite::support::StatusOr<EmbeddingResult> Postprocess(
+      const std::vector<const TfLiteTensor*>& output_tensors,
+      const FrameBuffer& frame_buffer,
+      const BoundingBox& roi) override;
+
+  // Performs pre-initialization actions.
+  virtual absl::Status PreInit();
+  // Performs post-initialization actions.
+  virtual absl::Status PostInit();
+
+  // Initializes the ImageEmbedder.
+  absl::Status Init(std::unique_ptr<ImageEmbedderOptions> options);
+
+  // Performs scalar quantization on a feature vector whose elements are
+  // assumed to lie in the range [-1.0, 1.0] (values outside this range will be
+  // clamped to -128 or 127).
+  void QuantizeFeatureVector(FeatureVector* feature_vector) const;
+
+ private:
+  std::vector<std::unique_ptr<processor::EmbeddingPostprocessor>>
+      postprocessors_;
+};
+
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_IMAGE_EMBEDDER_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc
index 08ea3b9..20a34a9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.cc
@@ -17,9 +17,9 @@
 
 #include <algorithm>
 
-#include "absl/memory/memory.h"
-#include "absl/strings/str_format.h"
-#include "absl/strings/string_view.h"
+#include "absl/memory/memory.h"        // from @com_google_absl
+#include "absl/strings/str_format.h"   // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow_lite_support/cc/common.h"
@@ -52,7 +52,6 @@
 // segmentation masks are stored with 8 bit per pixel (flattened byte array).
 constexpr uint32 kMaxNumClasses = 256;
 
-// TODO(b/)
 // The colormap used to fill `ColoredLabel`-s, as a flattened array of 256 {R,
 // G, B} components.
 constexpr uint8 kColorMap[768] = {
@@ -138,10 +137,14 @@
 /* static */
 absl::Status ImageSegmenter::SanityCheckOptions(
     const ImageSegmenterOptions& options) {
-  if (!options.has_model_file_with_metadata()) {
+  int num_input_models = (options.base_options().has_model_file() ? 1 : 0) +
+                         (options.has_model_file_with_metadata() ? 1 : 0);
+  if (num_input_models != 1) {
     return CreateStatusWithPayload(
         StatusCode::kInvalidArgument,
-        "Missing mandatory `model_file_with_metadata` field",
+        absl::StrFormat("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found %d.",
+                        num_input_models),
         TfLiteSupportStatus::kInvalidArgumentError);
   }
   if (options.output_type() == ImageSegmenterOptions::UNSPECIFIED) {
@@ -167,10 +170,25 @@
   // Copy options to ensure the ExternalFile outlives the constructed object.
   auto options_copy = absl::make_unique<ImageSegmenterOptions>(options);
 
-  ASSIGN_OR_RETURN(auto image_segmenter,
-                   TaskAPIFactory::CreateFromExternalFileProto<ImageSegmenter>(
-                       &options_copy->model_file_with_metadata(),
-                       std::move(resolver), options_copy->num_threads()));
+  std::unique_ptr<ImageSegmenter> image_segmenter;
+  if (options_copy->has_model_file_with_metadata()) {
+    ASSIGN_OR_RETURN(
+        image_segmenter,
+        TaskAPIFactory::CreateFromExternalFileProto<ImageSegmenter>(
+            &options_copy->model_file_with_metadata(), std::move(resolver),
+            options_copy->num_threads(), options_copy->compute_settings()));
+  } else if (options_copy->base_options().has_model_file()) {
+    ASSIGN_OR_RETURN(image_segmenter,
+                     TaskAPIFactory::CreateFromBaseOptions<ImageSegmenter>(
+                         &options_copy->base_options(), std::move(resolver)));
+  } else {
+    // Should never happen because of SanityCheckOptions.
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 0."),
+        TfLiteSupportStatus::kInvalidArgumentError);
+  }
 
   RETURN_IF_ERROR(image_segmenter->Init(std::move(options_copy)));
 
@@ -203,7 +221,8 @@
 
 absl::Status ImageSegmenter::CheckAndSetOutputs() {
   // First, sanity checks on the model itself.
-  const TfLiteEngine::Interpreter* interpreter = engine_->interpreter();
+  const TfLiteEngine::Interpreter* interpreter =
+      GetTfLiteEngine()->interpreter();
 
   // Check the number of output tensors.
   if (TfLiteEngine::OutputCount(interpreter) != 1) {
@@ -257,7 +276,7 @@
 
   // Build label map from metadata, if available.
   const ModelMetadataExtractor* metadata_extractor =
-      engine_->metadata_extractor();
+      GetTfLiteEngine()->metadata_extractor();
   const flatbuffers::Vector<flatbuffers::Offset<TensorMetadata>>*
       output_tensor_metadata = metadata_extractor->GetOutputTensorMetadata();
   if (output_tensor_metadata != nullptr) {
@@ -374,8 +393,9 @@
         int class_index = 0;
         float max_confidence = 0.0f;
         for (int d = 0; d < output_depth_; ++d) {
-          const float confidence =
-              GetOutputConfidence(*output_tensor, tensor_x, tensor_y, d);
+          ASSIGN_OR_RETURN(
+              const float confidence,
+              GetOutputConfidence(*output_tensor, tensor_x, tensor_y, d));
           if (confidence > max_confidence) {
             class_index = d;
             max_confidence = confidence;
@@ -401,8 +421,10 @@
                           /*to_x=*/&tensor_x,
                           /*to_y=*/&tensor_y);
         for (int d = 0; d < output_depth_; ++d) {
-          confidence_masks->mutable_confidence_mask(d)->add_value(
+          ASSIGN_OR_RETURN(
+              float confidence,
               GetOutputConfidence(*output_tensor, tensor_x, tensor_y, d));
+          confidence_masks->mutable_confidence_mask(d)->add_value(confidence);
         }
       }
     }
@@ -411,17 +433,20 @@
   return result;
 }
 
-float ImageSegmenter::GetOutputConfidence(const TfLiteTensor& output_tensor,
-                                          int x,
-                                          int y,
-                                          int depth) {
+StatusOr<float> ImageSegmenter::GetOutputConfidence(
+    const TfLiteTensor& output_tensor,
+    int x,
+    int y,
+    int depth) {
   int index = output_width_ * output_depth_ * y + output_depth_ * x + depth;
   if (has_uint8_outputs_) {
-    const uint8* data = AssertAndReturnTypedTensor<uint8>(&output_tensor);
+    ASSIGN_OR_RETURN(const uint8* data,
+                     AssertAndReturnTypedTensor<uint8>(&output_tensor));
     return output_tensor.params.scale *
            (static_cast<int>(data[index]) - output_tensor.params.zero_point);
   } else {
-    const float* data = AssertAndReturnTypedTensor<float>(&output_tensor);
+    ASSIGN_OR_RETURN(const float* data,
+                     AssertAndReturnTypedTensor<float>(&output_tensor));
     return data[index];
   }
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h
index e1d484c..e255110 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/image_segmenter.h
@@ -19,8 +19,9 @@
 #include <memory>
 #include <vector>
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h"
@@ -78,7 +79,7 @@
   CreateFromOptions(
       const ImageSegmenterOptions& options,
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
 
   // Performs actual segmentation on the provided FrameBuffer.
   //
@@ -147,10 +148,11 @@
 
   // Returns the output confidence at coordinates {x, y, depth}, dequantizing
   // on-the-fly if needed (i.e. if `has_uint8_outputs_` is true).
-  float GetOutputConfidence(const TfLiteTensor& output_tensor,
-                            int x,
-                            int y,
-                            int depth);
+  tflite::support::StatusOr<float> GetOutputConfidence(
+      const TfLiteTensor& output_tensor,
+      int x,
+      int y,
+      int depth);
 
   // Prebuilt list of ColoredLabel attached to each Segmentation result. The
   // i-th item in this list corresponds to the i-th label map item.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc
index e0f3149..3eb5126 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.cc
@@ -19,11 +19,12 @@
 #include <limits>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/strings/str_format.h"
-#include "absl/strings/string_view.h"
+#include <glog/logging.h>
+#include "absl/memory/memory.h"        // from @com_google_absl
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/str_format.h"   // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow/lite/c/common.h"
-#include "tensorflow/lite/interpreter.h"
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
@@ -33,6 +34,7 @@
 #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/score_calibration.h"
 #include "tensorflow_lite_support/metadata/cc/metadata_extractor.h"
 #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
 
@@ -55,12 +57,27 @@
 using ::tflite::support::StatusOr;
 using ::tflite::support::TfLiteSupportStatus;
 using ::tflite::task::core::AssertAndReturnTypedTensor;
+using ::tflite::task::core::FindIndexByMetadataTensorName;
 using ::tflite::task::core::TaskAPIFactory;
 using ::tflite::task::core::TfLiteEngine;
 
 // The expected number of dimensions of the 4 output tensors, representing in
-// that order: locations, classes, scores, num_results.
+// that order: locations, categories, scores, num_results. The order is
+// coming from the TFLite custom NMS op for object detection post-processing
+// shown in
+// https://github.com/tensorflow/tensorflow/blob/1c419b231b622bd9e9685682545e9064f0fbb42a/tensorflow/lite/kernels/detection_postprocess.cc#L47.
 static constexpr int kOutputTensorsExpectedDims[4] = {3, 2, 2, 1};
+constexpr int kDefaultLocationsIndex = 0;
+constexpr int kDefaultClassesIndex = 1;
+constexpr int kDefaultScoresIndex = 2;
+constexpr int kDefaultNumResultsIndex = 3;
+
+constexpr float kDefaultScoreThreshold = std::numeric_limits<float>::lowest();
+
+constexpr char kLocationTensorName[] = "location";
+constexpr char kCategoryTensorName[] = "category";
+constexpr char kScoreTensorName[] = "score";
+constexpr char kNumberOfDetectionsTensorName[] = "number of detections";
 
 StatusOr<const BoundingBoxProperties*> GetBoundingBoxProperties(
     const TensorMetadata& tensor_metadata) {
@@ -138,7 +155,7 @@
       ModelMetadataExtractor::FindFirstAssociatedFileName(
           tensor_metadata, tflite::AssociatedFileType_TENSOR_VALUE_LABELS,
           locale);
-  absl::string_view display_names_file = nullptr;
+  absl::string_view display_names_file;
   if (!display_names_filename.empty()) {
     ASSIGN_OR_RETURN(display_names_file, metadata_extractor.GetAssociatedFile(
                                              display_names_filename));
@@ -154,14 +171,44 @@
       metadata_extractor.FindFirstProcessUnit(
           tensor_metadata, ProcessUnitOptions_ScoreThresholdingOptions));
   if (score_thresholding_process_unit == nullptr) {
-    return std::numeric_limits<float>::lowest();
+    return kDefaultScoreThreshold;
   }
   return score_thresholding_process_unit->options_as_ScoreThresholdingOptions()
       ->global_score_threshold();
 }
 
+// Use tensor names in metadata to get the output order.
+std::vector<int> GetOutputIndices(
+    const flatbuffers::Vector<flatbuffers::Offset<TensorMetadata>>*
+        tensor_metadatas) {
+  std::vector<int> output_indices = {
+      FindIndexByMetadataTensorName(tensor_metadatas, kLocationTensorName),
+      FindIndexByMetadataTensorName(tensor_metadatas, kCategoryTensorName),
+      FindIndexByMetadataTensorName(tensor_metadatas, kScoreTensorName),
+      FindIndexByMetadataTensorName(tensor_metadatas,
+                                    kNumberOfDetectionsTensorName)};
+
+  for (int i = 0; i < 4; i++) {
+    int output_index = output_indices[i];
+    // If tensor name is not found, set the default output indices.
+    if (output_index == -1) {
+      LOG(WARNING) << absl::StrFormat(
+          "You don't seem to be matching tensor names in metadata list. The "
+          "tensor name \"%s\" at index %d in the model metadata doesn't match "
+          "the available output names: [\"%s\", \"%s\", \"%s\", \"%s\"].",
+          tensor_metadatas->Get(i)->name()->c_str(), i, kLocationTensorName,
+          kCategoryTensorName, kScoreTensorName, kNumberOfDetectionsTensorName);
+      output_indices = {kDefaultLocationsIndex, kDefaultClassesIndex,
+                        kDefaultScoresIndex, kDefaultNumResultsIndex};
+      return output_indices;
+    }
+  }
+  return output_indices;
+}
+
 absl::Status SanityCheckOutputTensors(
-    const std::vector<const TfLiteTensor*>& output_tensors) {
+    const std::vector<const TfLiteTensor*>& output_tensors,
+    const std::vector<int>& output_indices) {
   if (output_tensors.size() != 4) {
     return CreateStatusWithPayload(
         StatusCode::kInternal,
@@ -170,48 +217,55 @@
   }
 
   // Get number of results.
-  if (output_tensors[3]->dims->data[0] != 1) {
+  const TfLiteTensor* num_results_tensor = output_tensors[output_indices[3]];
+  if (num_results_tensor->dims->data[0] != 1) {
     return CreateStatusWithPayload(
         StatusCode::kInternal,
         absl::StrFormat(
             "Expected tensor with dimensions [1] at index 3, found [%d]",
-            output_tensors[3]->dims->data[0]));
+            num_results_tensor->dims->data[0]));
   }
-  int num_results =
-      static_cast<int>(AssertAndReturnTypedTensor<float>(output_tensors[3])[0]);
 
+  ASSIGN_OR_RETURN(float* num_results_data,
+                   AssertAndReturnTypedTensor<float>(num_results_tensor));
+  int num_results = static_cast<int>(num_results_data[0]);
+
+  const TfLiteTensor* location_tensor = output_tensors[output_indices[0]];
   // Check dimensions for the other tensors are correct.
-  if (output_tensors[0]->dims->data[0] != 1 ||
-      output_tensors[0]->dims->data[1] != num_results ||
-      output_tensors[0]->dims->data[2] != 4) {
+  if (location_tensor->dims->data[0] != 1 ||
+      location_tensor->dims->data[1] < num_results ||
+      location_tensor->dims->data[2] != 4) {
     return CreateStatusWithPayload(
         StatusCode::kInternal,
         absl::StrFormat(
-            "Expected locations tensor with dimensions [1,%d,4] at index 0, "
-            "found [%d,%d,%d].",
-            num_results, output_tensors[0]->dims->data[0],
-            output_tensors[0]->dims->data[1],
-            output_tensors[0]->dims->data[2]));
+            "Expected locations tensor with dimensions [1, num_detected_boxes, "
+            "4] at index 0, num_detected_boxes >= %d, found [%d,%d,%d].",
+            num_results, location_tensor->dims->data[0],
+            location_tensor->dims->data[1], location_tensor->dims->data[2]));
   }
-  if (output_tensors[1]->dims->data[0] != 1 ||
-      output_tensors[1]->dims->data[1] != num_results) {
+
+  const TfLiteTensor* class_tensor = output_tensors[output_indices[1]];
+  if (class_tensor->dims->data[0] != 1 ||
+      class_tensor->dims->data[1] < num_results) {
     return CreateStatusWithPayload(
         StatusCode::kInternal,
         absl::StrFormat(
-            "Expected classes tensor with dimensions [1,%d] at index 1, "
-            "found [%d,%d].",
-            num_results, output_tensors[1]->dims->data[0],
-            output_tensors[1]->dims->data[1]));
+            "Expected classes tensor with dimensions [1, num_detected_boxes] "
+            "at index 1, num_detected_boxes >= %d, found [%d,%d].",
+            num_results, class_tensor->dims->data[0],
+            class_tensor->dims->data[1]));
   }
-  if (output_tensors[2]->dims->data[0] != 1 ||
-      output_tensors[2]->dims->data[1] != num_results) {
+
+  const TfLiteTensor* scores_tensor = output_tensors[output_indices[2]];
+  if (scores_tensor->dims->data[0] != 1 ||
+      scores_tensor->dims->data[1] < num_results) {
     return CreateStatusWithPayload(
         StatusCode::kInternal,
         absl::StrFormat(
-            "Expected scores tensor with dimensions [1,%d] at index 2, "
-            "found [%d,%d].",
-            num_results, output_tensors[2]->dims->data[0],
-            output_tensors[2]->dims->data[1]));
+            "Expected scores tensor with dimensions [1, num_detected_boxes] "
+            "at index 2, num_detected_boxes >= %d, found [%d,%d].",
+            num_results, scores_tensor->dims->data[0],
+            scores_tensor->dims->data[1]));
   }
 
   return absl::OkStatus();
@@ -222,10 +276,14 @@
 /* static */
 absl::Status ObjectDetector::SanityCheckOptions(
     const ObjectDetectorOptions& options) {
-  if (!options.has_model_file_with_metadata()) {
+  int num_input_models = (options.base_options().has_model_file() ? 1 : 0) +
+                         (options.has_model_file_with_metadata() ? 1 : 0);
+  if (num_input_models != 1) {
     return CreateStatusWithPayload(
         StatusCode::kInvalidArgument,
-        "Missing mandatory `model_file_with_metadata` field",
+        absl::StrFormat("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found %d.",
+                        num_input_models),
         TfLiteSupportStatus::kInvalidArgumentError);
   }
   if (options.max_results() == 0) {
@@ -260,10 +318,25 @@
   // Copy options to ensure the ExternalFile outlives the constructed object.
   auto options_copy = absl::make_unique<ObjectDetectorOptions>(options);
 
-  ASSIGN_OR_RETURN(auto object_detector,
-                   TaskAPIFactory::CreateFromExternalFileProto<ObjectDetector>(
-                       &options_copy->model_file_with_metadata(),
-                       std::move(resolver), options_copy->num_threads()));
+  std::unique_ptr<ObjectDetector> object_detector;
+  if (options_copy->has_model_file_with_metadata()) {
+    ASSIGN_OR_RETURN(
+        object_detector,
+        TaskAPIFactory::CreateFromExternalFileProto<ObjectDetector>(
+            &options_copy->model_file_with_metadata(), std::move(resolver),
+            options_copy->num_threads(), options_copy->compute_settings()));
+  } else if (options_copy->base_options().has_model_file()) {
+    ASSIGN_OR_RETURN(object_detector,
+                     TaskAPIFactory::CreateFromBaseOptions<ObjectDetector>(
+                         &options_copy->base_options(), std::move(resolver)));
+  } else {
+    // Should never happen because of SanityCheckOptions.
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 0."),
+        TfLiteSupportStatus::kInvalidArgumentError);
+  }
 
   RETURN_IF_ERROR(object_detector->Init(std::move(options_copy)));
 
@@ -286,6 +359,10 @@
   // Initialize class whitelisting/blacklisting, if any.
   RETURN_IF_ERROR(CheckAndSetClassIndexSet());
 
+  // Perform final initialization (by default, initialize score calibration
+  // parameters, if any).
+  RETURN_IF_ERROR(PostInit());
+
   return absl::OkStatus();
 }
 
@@ -294,9 +371,83 @@
   return absl::OkStatus();
 }
 
+absl::Status ObjectDetector::PostInit() {
+  return InitScoreCalibrations();
+}
+
+StatusOr<SigmoidCalibrationParameters> BuildCalibrationParametersIfAny(
+    const tflite::metadata::ModelMetadataExtractor& metadata_extractor,
+    const tflite::TensorMetadata& output_tensor_metadata,
+    const std::vector<LabelMapItem>& label_map_items,
+    bool* has_score_calibration) {
+  SigmoidCalibrationParameters sigmoid_params;
+  *has_score_calibration = false;
+
+  // Build score calibration parameters, if present.
+  //
+  // TODO(tianlin): This code is similar to the block of classification_head.cc
+  // that does sanity checks and builds sigmoid calibration params in:
+  //   https://github.com/tensorflow/tflite-support/blob/64e044408f3d3654de7fc10bca401ed900649ca3/tensorflow_lite_support/cc/task/vision/core/classification_head.cc#L75-L107
+  // Consider to refactor it and reuse the same function.
+  ASSIGN_OR_RETURN(const tflite::ProcessUnit* score_calibration_process_unit,
+                   ModelMetadataExtractor::FindFirstProcessUnit(
+                       output_tensor_metadata,
+                       tflite::ProcessUnitOptions_ScoreCalibrationOptions));
+  if (score_calibration_process_unit != nullptr) {
+    const std::string score_calibration_filename =
+        ModelMetadataExtractor::FindFirstAssociatedFileName(
+            output_tensor_metadata,
+            tflite::AssociatedFileType_TENSOR_AXIS_SCORE_CALIBRATION);
+    ASSIGN_OR_RETURN(
+        absl::string_view score_calibration_file,
+        metadata_extractor.GetAssociatedFile(score_calibration_filename));
+
+    // Set has_score_calibration to true, only if sigmoid_params is built.
+    ASSIGN_OR_RETURN(sigmoid_params,
+                     BuildSigmoidCalibrationParams(
+                         *score_calibration_process_unit
+                              ->options_as_ScoreCalibrationOptions(),
+                         score_calibration_file, label_map_items));
+    *has_score_calibration = true;
+  }
+  return sigmoid_params;
+}
+
+absl::Status ObjectDetector::InitScoreCalibrations() {
+  StatusOr<SigmoidCalibrationParameters> calibration_params_status;
+  bool has_score_calibration = false;
+
+  // Search the output tensor metadata, can try to get calibration_params.
+  const ModelMetadataExtractor* metadata_extractor =
+      GetTfLiteEngine()->metadata_extractor();
+  const flatbuffers::Vector<flatbuffers::Offset<tflite::TensorMetadata>>*
+      output_tensor_metadata = metadata_extractor->GetOutputTensorMetadata();
+  const tflite::TensorMetadata* output_tensor =
+      output_tensor_metadata->Get(kDefaultScoresIndex);
+  ASSIGN_OR_RETURN(
+      auto calibration_params,
+      BuildCalibrationParametersIfAny(*metadata_extractor, *output_tensor,
+                                      label_map_, &has_score_calibration));
+
+  // If no calibration_params is found, just skip score calibration.
+  if (!has_score_calibration) {
+    return absl::OkStatus();
+  }
+
+  score_calibration_ = absl::make_unique<ScoreCalibration>();
+  if (score_calibration_ == nullptr) {
+    return CreateStatusWithPayload(
+        StatusCode::kInternal, "Could not create score calibration object.");
+  }
+  RETURN_IF_ERROR(
+      score_calibration_->InitializeFromParameters(calibration_params));
+  return absl::OkStatus();
+}
+
 absl::Status ObjectDetector::CheckAndSetOutputs() {
   // First, sanity checks on the model itself.
-  const TfLiteEngine::Interpreter* interpreter = engine_->interpreter();
+  const TfLiteEngine::Interpreter* interpreter =
+      GetTfLiteEngine()->interpreter();
   // Check the number of output tensors.
   if (TfLiteEngine::OutputCount(interpreter) != 4) {
     return CreateStatusWithPayload(
@@ -306,29 +457,10 @@
                         TfLiteEngine::OutputCount(interpreter)),
         TfLiteSupportStatus::kInvalidNumOutputTensorsError);
   }
-  // Check tensor dimensions and batch size.
-  for (int i = 0; i < 4; ++i) {
-    const TfLiteTensor* tensor = TfLiteEngine::GetOutput(interpreter, i);
-    if (tensor->dims->size != kOutputTensorsExpectedDims[i]) {
-      return CreateStatusWithPayload(
-          StatusCode::kInvalidArgument,
-          absl::StrFormat("Output tensor at index %d is expected to "
-                          "have %d dimensions, found %d.",
-                          i, kOutputTensorsExpectedDims[i], tensor->dims->size),
-          TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
-    }
-    if (tensor->dims->data[0] != 1) {
-      return CreateStatusWithPayload(
-          StatusCode::kInvalidArgument,
-          absl::StrFormat("Expected batch size of 1, found %d.",
-                          tensor->dims->data[0]),
-          TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
-    }
-  }
 
   // Now, perform sanity checks and extract metadata.
   const ModelMetadataExtractor* metadata_extractor =
-      engine_->metadata_extractor();
+      GetTfLiteEngine()->metadata_extractor();
   // Check that metadata is available.
   if (metadata_extractor->GetModelMetadata() == nullptr ||
       metadata_extractor->GetModelMetadata()->subgraph_metadata() == nullptr) {
@@ -352,10 +484,13 @@
         TfLiteSupportStatus::kMetadataInconsistencyError);
   }
 
+  output_indices_ = GetOutputIndices(output_tensors_metadata);
+
   // Extract mandatory BoundingBoxProperties for easier access at
   // post-processing time, performing sanity checks on the fly.
   ASSIGN_OR_RETURN(const BoundingBoxProperties* bounding_box_properties,
-                   GetBoundingBoxProperties(*output_tensors_metadata->Get(0)));
+                   GetBoundingBoxProperties(
+                       *output_tensors_metadata->Get(output_indices_[0])));
   if (bounding_box_properties->index() == nullptr) {
     bounding_box_corners_order_ = {0, 1, 2, 3};
   } else {
@@ -371,16 +506,39 @@
   // Build label map (if available) from metadata.
   ASSIGN_OR_RETURN(
       label_map_,
-      GetLabelMapIfAny(*metadata_extractor, *output_tensors_metadata->Get(1),
+      GetLabelMapIfAny(*metadata_extractor,
+                       *output_tensors_metadata->Get(output_indices_[1]),
                        options_->display_names_locale()));
 
   // Set score threshold.
   if (options_->has_score_threshold()) {
     score_threshold_ = options_->score_threshold();
   } else {
-    ASSIGN_OR_RETURN(score_threshold_,
-                     GetScoreThreshold(*metadata_extractor,
-                                       *output_tensors_metadata->Get(2)));
+    ASSIGN_OR_RETURN(
+        score_threshold_,
+        GetScoreThreshold(*metadata_extractor,
+                          *output_tensors_metadata->Get(output_indices_[2])));
+  }
+
+  // Check tensor dimensions and batch size.
+  for (int i = 0; i < 4; ++i) {
+    std::size_t j = output_indices_[i];
+    const TfLiteTensor* tensor = TfLiteEngine::GetOutput(interpreter, j);
+    if (tensor->dims->size != kOutputTensorsExpectedDims[i]) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat("Output tensor at index %d is expected to "
+                          "have %d dimensions, found %d.",
+                          j, kOutputTensorsExpectedDims[i], tensor->dims->size),
+          TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+    }
+    if (tensor->dims->data[0] != 1) {
+      return CreateStatusWithPayload(
+          StatusCode::kInvalidArgument,
+          absl::StrFormat("Expected batch size of 1, found %d.",
+                          tensor->dims->data[0]),
+          TfLiteSupportStatus::kInvalidOutputTensorDimensionsError);
+    }
   }
 
   return absl::OkStatus();
@@ -439,9 +597,7 @@
   BoundingBox roi;
   roi.set_width(frame_buffer.dimension().width);
   roi.set_height(frame_buffer.dimension().height);
-  // Rely on `Infer` instead of `InferWithFallback` as DetectionPostprocessing
-  // op doesn't support hardware acceleration at the time.
-  return Infer(frame_buffer, roi);
+  return InferWithFallback(frame_buffer, roi);
 }
 
 StatusOr<DetectionResult> ObjectDetector::Postprocess(
@@ -451,11 +607,13 @@
   // Most of the checks here should never happen, as outputs have been validated
   // at construction time. Checking nonetheless and returning internal errors if
   // something bad happens.
-  RETURN_IF_ERROR(SanityCheckOutputTensors(output_tensors));
+  RETURN_IF_ERROR(SanityCheckOutputTensors(output_tensors, output_indices_));
 
   // Get number of available results.
-  const int num_results =
-      static_cast<int>(AssertAndReturnTypedTensor<float>(output_tensors[3])[0]);
+  ASSIGN_OR_RETURN(
+      float* num_results_data,
+      AssertAndReturnTypedTensor<float>(output_tensors[output_indices_[3]]));
+  const int num_results = static_cast<int>(num_results_data[0]);
   // Compute number of max results to return.
   const int max_results = options_->max_results() > 0
                               ? std::min(options_->max_results(), num_results)
@@ -469,16 +627,32 @@
     upright_input_frame_dimensions.Swap();
   }
 
-  const float* locations = AssertAndReturnTypedTensor<float>(output_tensors[0]);
-  const float* classes = AssertAndReturnTypedTensor<float>(output_tensors[1]);
-  const float* scores = AssertAndReturnTypedTensor<float>(output_tensors[2]);
+  ASSIGN_OR_RETURN(
+      const float* locations,
+      AssertAndReturnTypedTensor<float>(output_tensors[output_indices_[0]]));
+  ASSIGN_OR_RETURN(
+      const float* classes,
+      AssertAndReturnTypedTensor<float>(output_tensors[output_indices_[1]]));
+  ASSIGN_OR_RETURN(
+      const float* scores,
+      AssertAndReturnTypedTensor<float>(output_tensors[output_indices_[2]]));
   DetectionResult results;
   for (int i = 0; i < num_results; ++i) {
     const int class_index = static_cast<int>(classes[i]);
-    const float score = scores[i];
-    if (!IsClassIndexAllowed(class_index) || score < score_threshold_) {
+    if (!IsClassIndexAllowed(class_index)) {
       continue;
     }
+
+    float score = scores[i];
+    // Calibrate score only if score_calibration_ is presented.
+    if (score_calibration_ != nullptr) {
+      const std::string& class_name = label_map_[class_index].name;
+      score = score_calibration_->ComputeCalibratedScore(class_name, score);
+    }
+    if (score <= score_threshold_) {
+      continue;
+    }
+
     Detection* detection = results.add_detections();
     // Denormalize the bounding box cooordinates in the upright frame
     // coordinates system, then rotate back from frame_buffer.orientation() to
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h
index 5305407..c37fa877 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/object_detector.h
@@ -18,9 +18,10 @@
 
 #include <memory>
 
-#include "absl/container/flat_hash_set.h"
-#include "absl/status/status.h"
+#include "absl/container/flat_hash_set.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
 #include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/vision/core/base_vision_task_api.h"
@@ -28,6 +29,7 @@
 #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/detections_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/object_detector_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/score_calibration.h"
 
 namespace tflite {
 namespace task {
@@ -84,7 +86,7 @@
   CreateFromOptions(
       const ObjectDetectorOptions& options,
       std::unique_ptr<tflite::OpResolver> resolver =
-          absl::make_unique<tflite::ops::builtin::BuiltinOpResolver>());
+          absl::make_unique<tflite_shims::ops::builtin::BuiltinOpResolver>());
 
   // Performs actual detection on the provided FrameBuffer.
   //
@@ -134,6 +136,9 @@
   // Performs pre-initialization actions.
   virtual absl::Status PreInit();
 
+  // Performs post-initialization actions.
+  virtual absl::Status PostInit();
+
  private:
   // Performs sanity checks on the model outputs and extracts their metadata.
   absl::Status CheckAndSetOutputs();
@@ -147,6 +152,10 @@
   // Always returns true if no whitelist or blacklist were provided.
   bool IsClassIndexAllowed(int class_index);
 
+  // Initializes the score calibration parameters based on corresponding TFLite
+  // Model Metadata, if any.
+  absl::Status InitScoreCalibrations();
+
   // Given a DetectionResult object containing class indices, fills the name and
   // display name from the label map.
   absl::Status FillResultsFromLabelMap(DetectionResult* result);
@@ -178,6 +187,15 @@
   // discarded. If none is provided via metadata or options, -FLT_MAX is set as
   // default value.
   float score_threshold_;
+
+  // List of score calibration parameters, if any. Built from TFLite Model
+  // Metadata.
+  std::unique_ptr<ScoreCalibration> score_calibration_;
+
+  // Indices of the output tensors to match the output tensors to the correct
+  // index order of the output tensors: [location, categories, scores,
+  // num_detections].
+  std::vector<int> output_indices_;
 };
 
 }  // namespace vision
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/BUILD
index d1430eb..16ea0cd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/BUILD
@@ -1,8 +1,6 @@
-load("//tensorflow_lite_support/cc/port:build_defs.bzl", "support_cc_proto_library")
-
 package(
     default_visibility = [
-        "//tensorflow_lite_support:users",
+        "//visibility:public",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
@@ -14,9 +12,8 @@
     srcs = ["bounding_box.proto"],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "bounding_box_cc_proto",
-    srcs = ["bounding_box.proto"],
     deps = [
         ":bounding_box_proto",
     ],
@@ -33,9 +30,8 @@
     srcs = ["class.proto"],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "class_cc_proto",
-    srcs = ["class.proto"],
     deps = [
         ":class_proto",
     ],
@@ -53,14 +49,14 @@
     name = "object_detector_options_proto",
     srcs = ["object_detector_options.proto"],
     deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_proto",
     ],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "object_detector_options_cc_proto",
-    srcs = ["object_detector_options.proto"],
-    cc_deps = ["//tensorflow_lite_support/cc/task/core/proto:external_file_cc_proto"],
     deps = [
         ":object_detector_options_proto",
     ],
@@ -71,6 +67,7 @@
     hdrs = ["object_detector_options_proto_inc.h"],
     deps = [
         ":object_detector_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
     ],
 )
@@ -84,13 +81,8 @@
     ],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "detections_cc_proto",
-    srcs = ["detections.proto"],
-    cc_deps = [
-        ":bounding_box_cc_proto",
-        ":class_cc_proto",
-    ],
     deps = [
         ":detections_proto",
     ],
@@ -112,14 +104,14 @@
     name = "image_classifier_options_proto",
     srcs = ["image_classifier_options.proto"],
     deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_proto",
     ],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "image_classifier_options_cc_proto",
-    srcs = ["image_classifier_options.proto"],
-    cc_deps = ["//tensorflow_lite_support/cc/task/core/proto:external_file_cc_proto"],
     deps = [
         ":image_classifier_options_proto",
     ],
@@ -130,6 +122,7 @@
     hdrs = ["image_classifier_options_proto_inc.h"],
     deps = [
         ":image_classifier_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
     ],
 )
@@ -142,10 +135,8 @@
     ],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "classifications_cc_proto",
-    srcs = ["classifications.proto"],
-    cc_deps = [":class_cc_proto"],
     deps = [
         ":classifications_proto",
     ],
@@ -166,14 +157,14 @@
     name = "image_segmenter_options_proto",
     srcs = ["image_segmenter_options.proto"],
     deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_proto",
     ],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "image_segmenter_options_cc_proto",
-    srcs = ["image_segmenter_options.proto"],
-    cc_deps = ["//tensorflow_lite_support/cc/task/core/proto:external_file_cc_proto"],
     deps = [
         ":image_segmenter_options_proto",
     ],
@@ -184,6 +175,7 @@
     hdrs = ["image_segmenter_options_proto_inc.h"],
     deps = [
         ":image_segmenter_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
     ],
 )
@@ -193,9 +185,8 @@
     srcs = ["segmentations.proto"],
 )
 
-support_cc_proto_library(
+cc_proto_library(
     name = "segmentations_cc_proto",
-    srcs = ["segmentations.proto"],
     deps = [
         ":segmentations_proto",
     ],
@@ -206,3 +197,48 @@
     hdrs = ["segmentations_proto_inc.h"],
     deps = [":segmentations_cc_proto"],
 )
+
+# ImageEmbedder protos.
+
+proto_library(
+    name = "image_embedder_options_proto",
+    srcs = ["image_embedder_options.proto"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:external_file_proto",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:configuration_proto",
+    ],
+)
+
+cc_proto_library(
+    name = "image_embedder_options_cc_proto",
+    deps = [
+        ":image_embedder_options_proto",
+    ],
+)
+
+cc_library(
+    name = "image_embedder_options_proto_inc",
+    hdrs = ["image_embedder_options_proto_inc.h"],
+    deps = [
+        ":image_embedder_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
+    ],
+)
+
+proto_library(
+    name = "embeddings_proto",
+    srcs = ["embeddings.proto"],
+)
+
+cc_proto_library(
+    name = "embeddings_cc_proto",
+    deps = [
+        ":embeddings_proto",
+    ],
+)
+
+cc_library(
+    name = "embeddings_proto_inc",
+    hdrs = ["embeddings_proto_inc.h"],
+    deps = [":embeddings_cc_proto"],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h
index 2f9a409..38547ed 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h
@@ -13,8 +13,8 @@
 limitations under the License.
 ==============================================================================*/
 
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASS_PROTO_INC_H_
 
 #include "tensorflow_lite_support/cc/task/vision/proto/class.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h
index 62a5f117..1b3d538 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h
@@ -13,10 +13,10 @@
 limitations under the License.
 ==============================================================================*/
 
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASSIFICATIONS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASSIFICATIONS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASSIFICATIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASSIFICATIONS_PROTO_INC_H_
 
 #include "tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h"
 
 #include "tensorflow_lite_support/cc/task/vision/proto/classifications.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASSIFICATIONS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_CLASSIFICATIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/detections_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/detections_proto_inc.h
index 2b63cad..c702511 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/detections_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/detections_proto_inc.h
@@ -13,11 +13,11 @@
 limitations under the License.
 ==============================================================================*/
 
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_DETECTIONS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_DETECTIONS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_DETECTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_DETECTIONS_PROTO_INC_H_
 
 #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h"
 
 #include "tensorflow_lite_support/cc/task/vision/proto/detections.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_DETECTIONS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_DETECTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/embeddings.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/embeddings.proto
new file mode 100644
index 0000000..bff5faf
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/embeddings.proto
@@ -0,0 +1,48 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.vision;
+
+// Defines a dense feature vector. Only one of the two fields is ever present.
+// Feature vectors are assumed to be one-dimensional and L2-normalized.
+message FeatureVector {
+  // Raw output of the embedding layer. Only provided if `quantize` is set to
+  // false in the ImageEmbedderOptions, which is the case by default.
+  repeated float value_float = 1 [packed = true];
+  // Scalar-quantized embedding. Only provided if `quantize` is set to true in
+  // the ImageEmbedderOptions.
+  optional bytes value_string = 2;
+}
+
+// Result produced by one of the embedder model output layers.
+message Embedding {
+  // The output feature vector.
+  optional FeatureVector feature_vector = 1;
+  // The index of the model output layer that produced this feature vector.
+  optional int32 output_index = 2;
+}
+
+// Embeddings produced by the ImageEmbedder.
+message EmbeddingResult {
+  // The embeddings produced by each of the model output layers.
+  //
+  // Except in advanced cases, the embedding model has a single output layer,
+  // and this list is thus made of a single element.
+  repeated Embedding embeddings = 1;
+  // Reserved tags.
+  reserved 2;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/embeddings_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/embeddings_proto_inc.h
new file mode 100644
index 0000000..554aa98
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/embeddings_proto_inc.h
@@ -0,0 +1,20 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_EMBEDDINGS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_EMBEDDINGS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/vision/proto/embeddings.pb.h"
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_EMBEDDINGS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.proto
index 24cd85f..50b7682 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.proto
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.proto
@@ -17,20 +17,29 @@
 
 package tflite.task.vision;
 
+import "tensorflow/lite/experimental/acceleration/configuration/configuration.proto";
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
 import "tensorflow_lite_support/cc/task/core/proto/external_file.proto";
 
 // Options for setting up an ImageClassifier.
-// Next Id: 14
+// Next Id: 15
 message ImageClassifierOptions {
-  // The external model file, as a single standalone TFLite file. If it is
-  // packed with TFLite Model Metadata [1], those are used to populate e.g. the
-  // label map, score calibration and recommended score thresholds. Models
-  // without any such metadata or partial metadata are supported, but may result
-  // in the image classifier providing degraded functionality; typically, a
-  // model that doesn't contain any label map won't be able to return any class
-  // or display names but will be limited to returning class indices.
+  // Base options for configuring Task library, such as specifying the TfLite
+  // model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 14;
+
+  // Legacy method for specifying the TFLite model file. If it is packed with
+  // TFLite Model Metadata [1], those are used to populate e.g. the label map,
+  // score calibration and recommended score thresholds. Models without any such
+  // metadata or partial metadata are supported, but may result in the image
+  // classifier providing degraded functionality; typically, a model that
+  // doesn't contain any label map won't be able to return any class or display
+  // names but will be limited to returning class indices.
   //
   // [1]: https://www.tensorflow.org/lite/convert/metadata
+  //
+  // Deprecated: prefer using `base_options.model_file`, which is mutually
+  // exclusive with this field.
   optional core.ExternalFile model_file_with_metadata = 10;
 
   // The locale to use for display names specified through the TFLite Model
@@ -42,7 +51,7 @@
   // returned.
   optional int32 max_results = 2 [default = -1];
 
-  // Score threshold in [0,1), overrides the ones provided in the model metadata
+  // Score threshold, overrides the ones provided in the model metadata
   // (if any). Results below this value are rejected.
   optional float score_threshold = 3;
 
@@ -56,12 +65,35 @@
   // class names are ignored. Mutually exclusive with class_name_whitelist.
   repeated string class_name_blacklist = 5;
 
-  // The number of threads to be used for TFLite ops that support
-  // multi-threading when running inference with CPU.
+  // Legacy method for specifying the number of threads to be used for TFLite
+  // ops that support multi-threading when running inference with CPU.
   // num_threads should be greater than 0 or equal to -1. Setting num_threads to
   // -1 has the effect to let TFLite runtime set the value.
+  //
+  // Deprecated: only works with `model_file_with_metadata`. Prefer using
+  // `base_options` to specifying the TFLite model and using
+  // `base_options.compute_settings.tflite_settings.cpu_settings.num_threads`,
+  // to configure the number of threads.
   optional int32 num_threads = 13 [default = -1];
 
+  // Legacy method for specifying how to accelerate the model
+  // inference using dedicated delegates. Supported delegate type includes:
+  // NONE, NNAPI, GPU, HEXAGON, XNNPACK, EDGETPU (Google internal),
+  // and EDGETPU_CORAL.
+  //
+  // IMPORTANT: in order to use a delegate, the appropriate delegate plugin
+  // needs to be linked at build time. See comment above the "image_classifier"
+  // target at:
+  // https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/cc/task/vision/BUILD
+  //
+  // See settings definition at:
+  // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/configuration.proto
+  //
+  // Deprecated: only works with `model_file_with_metadata`. Prefer using
+  // `base_options` to specifying the TFLite model and using
+  // `base_options.compute_settings` to configure acceleration options.
+  optional tflite.proto.ComputeSettings compute_settings = 9;
+
   // Reserved tags.
-  reserved 1, 6, 7, 8, 9, 12;
+  reserved 1, 6, 7, 8, 12;
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h
index 03dcd75..97a6deb4 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h
@@ -13,10 +13,11 @@
 limitations under the License.
 ==============================================================================*/
 
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_CLASSIFIER_OPTIONS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_CLASSIFIER_OPTIONS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_CLASSIFIER_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_CLASSIFIER_OPTIONS_PROTO_INC_H_
 
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
 
 #include "tensorflow_lite_support/cc/task/vision/proto/image_classifier_options.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_CLASSIFIER_OPTIONS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_CLASSIFIER_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_embedder_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_embedder_options.proto
new file mode 100644
index 0000000..87693ad
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_embedder_options.proto
@@ -0,0 +1,66 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+syntax = "proto2";
+
+package tflite.task.vision;
+
+import "tensorflow/lite/experimental/acceleration/configuration/configuration.proto";
+import "tensorflow_lite_support/cc/task/core/proto/external_file.proto";
+
+// Options for setting up an ImageEmbedder.
+// Next Id: 10.
+message ImageEmbedderOptions {
+  // The external model file, as a single standalone TFLite, optionally packed
+  // with TFLite Model Metadata [1]. Those are mandatory only if the model input
+  // is of float type (kTfLiteFloat32), which requires `NormalizationOptions` to
+  // be set on the input tensor metadata.
+  //
+  // [1]: https://www.tensorflow.org/lite/convert/metadata
+  optional core.ExternalFile model_file_with_metadata = 9;
+
+  // Whether to normalize the returned feature vector with L2 norm. Use this
+  // option only if the model does not already contain a native L2_NORMALIZATION
+  // TF Lite Op. In most cases, this is already the case and L2 norm is thus
+  // achieved through TF Lite inference.
+  optional bool l2_normalize = 6;
+
+  // Whether the returned embedding should be quantized to bytes via scalar
+  // quantization. Embeddings are implicitly assumed to be unit-norm and
+  // therefore any dimension is guaranteed to have a value in [-1.0, 1.0]. Use
+  // the l2_normalize option if this is not the case.
+  optional bool quantize = 2;
+
+  // The number of threads allowed for model inference. This value is used in
+  // building the TF Lite interpreter.
+  optional int32 num_threads = 7 [default = 1];
+
+  // Advanced settings specifying how to accelerate the model inference using
+  // dedicated delegates. Supported delegate type includes:
+  // NONE, NNAPI, GPU, HEXAGON, XNNPACK, EDGETPU (Google internal),
+  // and EDGETPU_CORAL.
+  //
+  // IMPORTANT: in order to use a delegate, the appropriate delegate plugin
+  // needs to be linked at build time. See comment above the "image_embedder"
+  // target at:
+  // https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/cc/task/vision/BUILD
+  //
+  // See settings definition at:
+  // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/configuration.proto
+  optional tflite.proto.ComputeSettings compute_settings = 8;
+
+  // Reserved tags.
+  reserved 1, 3, 4, 5;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_embedder_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_embedder_options_proto_inc.h
new file mode 100644
index 0000000..606751e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_embedder_options_proto_inc.h
@@ -0,0 +1,22 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_EMBEDDER_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_EMBEDDER_OPTIONS_PROTO_INC_H_
+
+#include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
+
+#include "tensorflow_lite_support/cc/task/vision/proto/image_embedder_options.pb.h"
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_EMBEDDER_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options.proto
index 3afed86aa..1aad5eb 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options.proto
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options.proto
@@ -17,12 +17,18 @@
 
 package tflite.task.vision;
 
+import "tensorflow/lite/experimental/acceleration/configuration/configuration.proto";
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
 import "tensorflow_lite_support/cc/task/core/proto/external_file.proto";
 
 // Options for setting up an ImageSegmenter.
-// Next Id: 8
+// Next Id: 9
 message ImageSegmenterOptions {
-  // The external model file, as a single standalone TFLite file. If it is
+  // Base options for configuring Task library, such as specifying the TfLite
+  // model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 8;
+
+  // Legacy method for specifying the TfLite model file. If it is
   // packed with TFLite Model Metadata [1], those are used to populate label
   // map. Models without any such metadata or partial metadata are supported,
   // but may result in the segmenter providing degraded functionality;
@@ -30,6 +36,9 @@
   // return any class or display names.
   //
   // [1]: https://www.tensorflow.org/lite/convert/metadata
+  //
+  // Deprecated: prefer using `base_options.model_file`, which is mutually
+  // exclusive with this field.
   optional core.ExternalFile model_file_with_metadata = 5;
 
   // The locale to use for display names specified through the TFLite Model
@@ -50,12 +59,35 @@
   // Optional output mask type.
   optional OutputType output_type = 3 [default = CATEGORY_MASK];
 
-  // The number of threads to be used for TFLite ops that support
-  // multi-threading when running inference with CPU.
+  // Legacy method for specifying the number of threads to be used for TFLite
+  // ops that support multi-threading when running inference with CPU.
   // num_threads should be greater than 0 or equal to -1. Setting num_threads to
   // -1 has the effect to let TFLite runtime set the value.
+  //
+  // Deprecated: only works with `model_file_with_metadata`. Prefer using
+  // `base_options` to specifying the TFLite model and using
+  // `base_options.compute_settings.tflite_settings.cpu_settings.num_threads`,
+  // to configure the number of threads.
   optional int32 num_threads = 7 [default = -1];
 
+  // Legacy method for specifying how to accelerate the model
+  // inference using dedicated delegates. Supported delegate type includes:
+  // NONE, NNAPI, GPU, HEXAGON, XNNPACK, EDGETPU (Google internal),
+  // and EDGETPU_CORAL.
+  //
+  // IMPORTANT: in order to use a delegate, the appropriate delegate plugin
+  // needs to be linked at build time. See comment above the "image_segmenter"
+  // target at:
+  // https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/cc/task/vision/BUILD
+  //
+  // See settings definition at:
+  // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/configuration.proto
+  //
+  // Deprecated: only works with `model_file_with_metadata`. Prefer using
+  // `base_options` to specifying the TFLite model and use
+  // `base_options.compute_settings` to configure acceleration options.
+  optional tflite.proto.ComputeSettings compute_settings = 4;
+
   // Reserved tags.
-  reserved 1, 2, 4;
+  reserved 1, 2;
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h
index aaaecf36..f2d34c8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h
@@ -13,10 +13,11 @@
 limitations under the License.
 ==============================================================================*/
 
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_SEGMENTER_OPTIONS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_SEGMENTER_OPTIONS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_SEGMENTER_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_SEGMENTER_OPTIONS_PROTO_INC_H_
 
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
 
 #include "tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_SEGMENTER_OPTIONS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_IMAGE_SEGMENTER_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options.proto b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options.proto
index b55e9740..d10198b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options.proto
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options.proto
@@ -17,16 +17,25 @@
 
 package tflite.task.vision;
 
+import "tensorflow/lite/experimental/acceleration/configuration/configuration.proto";
+import "tensorflow_lite_support/cc/task/core/proto/base_options.proto";
 import "tensorflow_lite_support/cc/task/core/proto/external_file.proto";
 
 // Options for setting up an ObjectDetector.
-// Next Id: 8.
+// Next Id: 10.
 message ObjectDetectorOptions {
-  // The external model file, as a single standalone TFLite file packed with
-  // TFLite Model Metadata [1]. Those are mandatory, and used to populate e.g.
-  // the label map and recommended score threshold.
+  // Base options for configuring Task library, such as specifying the TfLite
+  // model file with metadata, accelerator options, etc.
+  optional tflite.task.core.BaseOptions base_options = 9;
+
+  // Legacy method for specifying the TFLite model file, as a single standalone
+  // TFLite file packed with TFLite Model Metadata [1]. Those are mandatory, and
+  // used to populate e.g. the label map and recommended score threshold.
   //
   // [1]: https://www.tensorflow.org/lite/convert/metadata
+  //
+  // Deprecated: prefer using `base_options.model_file`, which is mutually
+  // exclusive with this field.
   optional core.ExternalFile model_file_with_metadata = 1;
 
   // The locale to use for display names specified through the TFLite Model
@@ -54,9 +63,32 @@
   // class names are ignored. Mutually exclusive with class_name_whitelist.
   repeated string class_name_blacklist = 6;
 
-  // The number of threads to be used for TFLite ops that support
-  // multi-threading when running inference with CPU.
+  // Legacy method for specifying the number of threads to be used for TFLite
+  // ops that support multi-threading when running inference with CPU.
   // num_threads should be greater than 0 or equal to -1. Setting num_threads to
   // -1 has the effect to let TFLite runtime set the value.
+  //
+  // Deprecated: only works with `model_file_with_metadata`. Prefer using
+  // `base_options` to specifying the TFLite model and using
+  // `base_options.compute_settings.tflite_settings.cpu_settings.num_threads`,
+  // to configure the number of threads.
   optional int32 num_threads = 7 [default = -1];
+
+  // Legacy method for specifying how to accelerate the model
+  // inference using dedicated delegates. Supported delegate type includes:
+  // NONE, NNAPI, GPU, HEXAGON, XNNPACK, EDGETPU (Google internal),
+  // and EDGETPU_CORAL.
+  //
+  // IMPORTANT: in order to use a delegate, the appropriate delegate plugin
+  // needs to be linked at build time. See comment above the "object_detector"
+  // target at:
+  // https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/cc/task/vision/BUILD
+  //
+  // See settings definition at:
+  // https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/acceleration/configuration/configuration.proto
+  //
+  // Deprecated: only works with `model_file_with_metadata`. Prefer using
+  // `base_options` to specifying the TFLite model and using
+  // `base_options.compute_settings` to configure acceleration options.
+  optional tflite.proto.ComputeSettings compute_settings = 8;
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options_proto_inc.h
index 2789847..4d966630 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/object_detector_options_proto_inc.h
@@ -13,10 +13,11 @@
 limitations under the License.
 ==============================================================================*/
 
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_OBJECT_DETECTOR_OPTIONS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_OBJECT_DETECTOR_OPTIONS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_OBJECT_DETECTOR_OPTIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_OBJECT_DETECTOR_OPTIONS_PROTO_INC_H_
 
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
 
 #include "tensorflow_lite_support/cc/task/vision/proto/object_detector_options.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_OBJECT_DETECTOR_OPTIONS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_OBJECT_DETECTOR_OPTIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h
index cfc96e6..86d38b5 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h
@@ -12,8 +12,8 @@
 See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
-#ifndef THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_SEGMENTATIONS_PROTO_INC_H_
-#define THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_SEGMENTATIONS_PROTO_INC_H_
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_SEGMENTATIONS_PROTO_INC_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_SEGMENTATIONS_PROTO_INC_H_
 
 #include "tensorflow_lite_support/cc/task/vision/proto/segmentations.pb.h"
-#endif  // THIRD_PARTY_TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_SEGMENTATIONS_PROTO_INC_H_
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_PROTO_SEGMENTATIONS_PROTO_INC_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/BUILD
index 8995145..72e3961 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/BUILD
@@ -1,6 +1,8 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
 package(
     default_visibility = [
-        "//tensorflow_lite_support:users",
+        "//tensorflow_lite_support:internal",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
@@ -9,6 +11,9 @@
     name = "score_calibration",
     srcs = ["score_calibration.cc"],
     hdrs = ["score_calibration.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:status_macros",
@@ -32,6 +37,7 @@
         "frame_buffer_common_utils.h",
         "frame_buffer_utils_interface.h",
     ],
+    visibility = ["//visibility:public"],
     deps = [
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:status_macros",
@@ -52,6 +58,9 @@
     hdrs = [
         "frame_buffer_utils.h",
     ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         ":frame_buffer_common_utils",
         ":libyuv_frame_buffer_utils",
@@ -66,6 +75,7 @@
         "@com_google_absl//absl/strings:str_format",
         "@com_google_absl//absl/types:optional",
         "@com_google_absl//absl/types:variant",
+        "@com_google_glog//:glog",
         "@org_tensorflow//tensorflow/lite/kernels:op_macros",
         "@org_tensorflow//tensorflow/lite/kernels/internal:compatibility",
     ],
@@ -75,6 +85,9 @@
     name = "libyuv_frame_buffer_utils",
     srcs = ["libyuv_frame_buffer_utils.cc"],
     hdrs = ["libyuv_frame_buffer_utils.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         ":frame_buffer_common_utils",
         "//tensorflow_lite_support/cc:common",
@@ -89,21 +102,22 @@
     ],
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "image_tensor_specs",
     srcs = ["image_tensor_specs.cc"],
     hdrs = ["image_tensor_specs.h"],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+    ],
     deps = [
         "//tensorflow_lite_support/cc:common",
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:status_macros",
         "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/core:tflite_engine",
         "//tensorflow_lite_support/metadata:metadata_schema_cc",
         "//tensorflow_lite_support/metadata/cc:metadata_extractor",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/types:optional",
-        "@org_tensorflow//tensorflow/lite:framework",
         "@org_tensorflow//tensorflow/lite/c:common",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc
index 9fbd284..cea7ef3 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.cc
@@ -18,8 +18,8 @@
 #include <string>
 #include <vector>
 
-#include "absl/strings/str_cat.h"
-#include "absl/strings/str_format.h"
+#include "absl/strings/str_cat.h"     // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 
 namespace tflite {
@@ -33,29 +33,17 @@
 constexpr int kRgbChannels = 3;
 constexpr int kGrayChannel = 1;
 
-// Creates a FrameBuffer from raw NV12 buffer and passing arguments.
-std::unique_ptr<FrameBuffer> CreateFromNV12RawBuffer(
+// Creates a FrameBuffer from one plane raw NV21/NV12 buffer and passing
+// arguments.
+StatusOr<std::unique_ptr<FrameBuffer>> CreateFromOnePlaneNVRawBuffer(
     const uint8* input,
     FrameBuffer::Dimension dimension,
-    FrameBuffer::Orientation orientation,
-    const absl::Time timestamp) {
-  const std::vector<FrameBuffer::Plane> planes_nv12 = {
-      {input, /*stride=*/{dimension.width, kGrayChannel}},
-      {input + dimension.Size(), /*stride=*/{dimension.width, 2}}};
-  return FrameBuffer::Create(planes_nv12, dimension, FrameBuffer::Format::kNV12,
-                             orientation, timestamp);
-}
-
-// Creates a FrameBuffer from raw NV21 buffer and passing arguments.
-std::unique_ptr<FrameBuffer> CreateFromNV21RawBuffer(
-    const uint8* input,
-    FrameBuffer::Dimension dimension,
+    FrameBuffer::Format format,
     FrameBuffer::Orientation orientation,
     const absl::Time timestamp) {
   FrameBuffer::Plane input_plane = {/*buffer=*/input,
                                     /*stride=*/{dimension.width, kGrayChannel}};
-  return FrameBuffer::Create({input_plane}, dimension,
-                             FrameBuffer::Format::kNV21, orientation,
+  return FrameBuffer::Create({input_plane}, dimension, format, orientation,
                              timestamp);
 }
 
@@ -101,12 +89,12 @@
     case FrameBuffer::Format::kYV12:
     case FrameBuffer::Format::kYV21:
       return /*y plane*/ dimension.Size() +
-             /*uv plane*/ ((static_cast<float>(dimension.width + 1) / 2) *
-                           (static_cast<float>(dimension.height + 1) / 2) * 2);
+             /*uv plane*/ (dimension.width + 1) / 2 * (dimension.height + 1) /
+                 2 * 2;
     case FrameBuffer::Format::kRGB:
-      return dimension.Size() * 3;
+      return dimension.Size() * kRgbPixelBytes;
     case FrameBuffer::Format::kRGBA:
-      return dimension.Size() * 4;
+      return dimension.Size() * kRgbaPixelBytes;
     case FrameBuffer::Format::kGRAY:
       return dimension.Size();
     default:
@@ -336,10 +324,14 @@
     const uint8* input,
     FrameBuffer::Dimension dimension,
     FrameBuffer::Orientation orientation,
-    const absl::Time timestamp) {
-  FrameBuffer::Plane input_plane = {
-      /*buffer=*/input,
-      /*stride=*/{dimension.width * kRgbaChannels, kRgbaChannels}};
+    const absl::Time timestamp,
+    FrameBuffer::Stride stride) {
+  if (stride == kDefaultStride) {
+    stride.row_stride_bytes = dimension.width * kRgbaChannels;
+    stride.pixel_stride_bytes = kRgbaChannels;
+  }
+  FrameBuffer::Plane input_plane = {/*buffer=*/input,
+                                    /*stride=*/stride};
   return FrameBuffer::Create({input_plane}, dimension,
                              FrameBuffer::Format::kRGBA, orientation,
                              timestamp);
@@ -350,10 +342,14 @@
     const uint8* input,
     FrameBuffer::Dimension dimension,
     FrameBuffer::Orientation orientation,
-    const absl::Time timestamp) {
-  FrameBuffer::Plane input_plane = {
-      /*buffer=*/input,
-      /*stride=*/{dimension.width * kRgbChannels, kRgbChannels}};
+    const absl::Time timestamp,
+    FrameBuffer::Stride stride) {
+  if (stride == kDefaultStride) {
+    stride.row_stride_bytes = dimension.width * kRgbChannels;
+    stride.pixel_stride_bytes = kRgbChannels;
+  }
+  FrameBuffer::Plane input_plane = {/*buffer=*/input,
+                                    /*stride=*/stride};
   return FrameBuffer::Create({input_plane}, dimension,
                              FrameBuffer::Format::kRGB, orientation, timestamp);
 }
@@ -363,9 +359,14 @@
     const uint8* input,
     FrameBuffer::Dimension dimension,
     FrameBuffer::Orientation orientation,
-    const absl::Time timestamp) {
+    const absl::Time timestamp,
+    FrameBuffer::Stride stride) {
+  if (stride == kDefaultStride) {
+    stride.row_stride_bytes = dimension.width * kGrayChannel;
+    stride.pixel_stride_bytes = kGrayChannel;
+  }
   FrameBuffer::Plane input_plane = {/*buffer=*/input,
-                                    /*stride=*/{dimension.width, kGrayChannel}};
+                                    /*stride=*/stride};
   return FrameBuffer::Create({input_plane}, dimension,
                              FrameBuffer::Format::kGRAY, orientation,
                              timestamp);
@@ -410,9 +411,11 @@
     absl::Time timestamp) {
   switch (target_format) {
     case FrameBuffer::Format::kNV12:
-      return CreateFromNV12RawBuffer(buffer, dimension, orientation, timestamp);
+      return CreateFromOnePlaneNVRawBuffer(buffer, dimension, target_format,
+                                           orientation, timestamp);
     case FrameBuffer::Format::kNV21:
-      return CreateFromNV21RawBuffer(buffer, dimension, orientation, timestamp);
+      return CreateFromOnePlaneNVRawBuffer(buffer, dimension, target_format,
+                                           orientation, timestamp);
     case FrameBuffer::Format::kYV12: {
       ASSIGN_OR_RETURN(const FrameBuffer::Dimension uv_dimension,
                        GetUvPlaneDimension(dimension, target_format));
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h
index 45670f4..7ebf69fa 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h
@@ -17,9 +17,9 @@
 
 #include <memory>
 
-#include "absl/status/status.h"
-#include "absl/time/clock.h"
-#include "absl/time/time.h"
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/time/clock.h"     // from @com_google_absl
+#include "absl/time/time.h"      // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
@@ -29,6 +29,11 @@
 namespace vision {
 
 constexpr int kRgbaPixelBytes = 4, kRgbPixelBytes = 3, kGrayPixelBytes = 1;
+// Default stride value for creating frame buffer from raw buffer. When using
+// this default value, the default row stride and pixel stride values will be
+// applied. e.g. for RGB image, row_stride = width * kRgbPixelBytes,
+// pixel_stride = kRgbPixelBytes.
+inline constexpr FrameBuffer::Stride kDefaultStride = {0, 0};
 
 // Miscellaneous Methods
 // -----------------------------------------------------------------
@@ -112,21 +117,24 @@
     const uint8* input,
     FrameBuffer::Dimension dimension,
     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
-    absl::Time timestamp = absl::Now());
+    absl::Time timestamp = absl::Now(),
+    FrameBuffer::Stride stride = kDefaultStride);
 
 // Creates a FrameBuffer from raw RGB buffer and passing arguments.
 std::unique_ptr<FrameBuffer> CreateFromRgbRawBuffer(
     const uint8* input,
     FrameBuffer::Dimension dimension,
     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
-    absl::Time timestamp = absl::Now());
+    absl::Time timestamp = absl::Now(),
+    FrameBuffer::Stride stride = kDefaultStride);
 
 // Creates a FrameBuffer from raw grayscale buffer and passing arguments.
 std::unique_ptr<FrameBuffer> CreateFromGrayRawBuffer(
     const uint8* input,
     FrameBuffer::Dimension dimension,
     FrameBuffer::Orientation orientation = FrameBuffer::Orientation::kTopLeft,
-    absl::Time timestamp = absl::Now());
+    absl::Time timestamp = absl::Now(),
+    FrameBuffer::Stride stride = kDefaultStride);
 
 // Creates a FrameBuffer from raw YUV buffer and passing arguments.
 tflite::support::StatusOr<std::unique_ptr<FrameBuffer>> CreateFromYuvRawBuffer(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc
index f6b3eba..4728c30 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.cc
@@ -22,9 +22,9 @@
 #include <utility>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
+#include "absl/memory/memory.h"       // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow/lite/kernels/internal/compatibility.h"
 #include "tensorflow/lite/kernels/op_macros.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
@@ -331,6 +331,10 @@
   } else if (absl::holds_alternative<CropResizeOperation>(operation)) {
     const auto& crop_resize = absl::get<CropResizeOperation>(operation);
     dimension = crop_resize.resize_dimension;
+  } else if (absl::holds_alternative<UniformCropResizeOperation>(operation)) {
+    const auto& uniform_crop_resize =
+        absl::get<UniformCropResizeOperation>(operation);
+    dimension = uniform_crop_resize.output_dimension;
   }
   return dimension;
 }
@@ -361,9 +365,10 @@
       planes.push_back(
           {buffer, /*stride=*/{/*row_stride_bytes=*/dimension.width,
                                /*pixel_stride_bytes=*/1}});
-      planes.push_back({buffer + (dimension.width * dimension.height),
-                        /*stride=*/{/*row_stride_bytes=*/dimension.width,
-                                    /*pixel_stride_bytes=*/2}});
+      planes.push_back(
+          {buffer + (dimension.width * dimension.height),
+           /*stride=*/{/*row_stride_bytes=*/(dimension.width + 1) / 2 * 2,
+                       /*pixel_stride_bytes=*/2}});
     } break;
     case FrameBuffer::Format::kYV12:
     case FrameBuffer::Format::kYV21: {
@@ -414,6 +419,13 @@
              (params.crop_dimension.width + params.crop_origin_x - 1),
              (params.crop_dimension.height + params.crop_origin_y - 1),
              output_buffer));
+  } else if (absl::holds_alternative<UniformCropResizeOperation>(operation)) {
+    const auto& params = absl::get<UniformCropResizeOperation>(operation);
+    RETURN_IF_ERROR(
+        Crop(buffer, params.crop_origin_x, params.crop_origin_y,
+             (params.crop_dimension.width + params.crop_origin_x - 1),
+             (params.crop_dimension.height + params.crop_origin_y - 1),
+             output_buffer));
   } else if (absl::holds_alternative<ConvertOperation>(operation)) {
     RETURN_IF_ERROR(Convert(buffer, output_buffer));
   } else if (absl::holds_alternative<OrientOperation>(operation)) {
@@ -584,7 +596,8 @@
 absl::Status FrameBufferUtils::Preprocess(
     const FrameBuffer& buffer,
     absl::optional<BoundingBox> bounding_box,
-    FrameBuffer* output_buffer) {
+    FrameBuffer* output_buffer,
+    bool uniform_resizing) {
   std::vector<FrameBufferOperation> frame_buffer_operations;
   // Handle cropping and resizing.
   bool needs_dimension_swap =
@@ -596,29 +609,56 @@
     pre_orient_dimension.Swap();
   }
 
-  if (bounding_box.has_value()) {
-    // Cropping case.
+  if (uniform_resizing && bounding_box.has_value()) {
+    // Crop and uniform resize.
+    frame_buffer_operations.push_back(UniformCropResizeOperation(
+        bounding_box.value().origin_x(), bounding_box.value().origin_y(),
+        FrameBuffer::Dimension{bounding_box.value().width(),
+                               bounding_box.value().height()},
+        pre_orient_dimension));
+  } else if (uniform_resizing) {
+    // Uniform resize only.
+    frame_buffer_operations.push_back(UniformCropResizeOperation(
+        0, 0, buffer.dimension(), pre_orient_dimension));
+  } else if (bounding_box.has_value()) {
+    // Crop and non-uniform resize.
     frame_buffer_operations.push_back(CropResizeOperation(
         bounding_box.value().origin_x(), bounding_box.value().origin_y(),
         FrameBuffer::Dimension{bounding_box.value().width(),
                                bounding_box.value().height()},
         pre_orient_dimension));
   } else if (pre_orient_dimension != buffer.dimension()) {
-    // Resizing case.
+    // non-uniform resize.
     frame_buffer_operations.push_back(
         CropResizeOperation(0, 0, buffer.dimension(), pre_orient_dimension));
   }
 
-  // Handle color space conversion.
-  if (output_buffer->format() != buffer.format()) {
-    frame_buffer_operations.push_back(
-        ConvertOperation(output_buffer->format()));
-  }
-
-  // Handle orientation conversion.
-  if (output_buffer->orientation() != buffer.orientation()) {
-    frame_buffer_operations.push_back(
-        OrientOperation(output_buffer->orientation()));
+  // Handle color space conversion first if the input format is RGB or RGBA,
+  // because the rotation performance for RGB and RGBA formats are not optimzed
+  // in libyuv.
+  if (buffer.format() == FrameBuffer::Format::kRGB ||
+      buffer.format() == FrameBuffer::Format::kRGBA) {
+    if (output_buffer->format() != buffer.format()) {
+      frame_buffer_operations.push_back(
+          ConvertOperation(output_buffer->format()));
+    }
+    // Handle orientation conversion
+    if (output_buffer->orientation() != buffer.orientation()) {
+      frame_buffer_operations.push_back(
+          OrientOperation(output_buffer->orientation()));
+    }
+  } else {
+    // Handle orientation conversion first if the input format is not RGB or
+    // RGBA.
+    if (output_buffer->orientation() != buffer.orientation()) {
+      frame_buffer_operations.push_back(
+          OrientOperation(output_buffer->orientation()));
+    }
+    // Handle color space conversion
+    if (output_buffer->format() != buffer.format()) {
+      frame_buffer_operations.push_back(
+          ConvertOperation(output_buffer->format()));
+    }
   }
 
   // Execute the processing pipeline.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h
index 794495e..4854946 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h
@@ -19,9 +19,9 @@
 #include <memory>
 #include <vector>
 
-#include "absl/status/status.h"
-#include "absl/types/optional.h"
-#include "absl/types/variant.h"
+#include "absl/status/status.h"   // from @com_google_absl
+#include "absl/types/optional.h"  // from @com_google_absl
+#include "absl/types/variant.h"   // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
@@ -112,6 +112,39 @@
   FrameBuffer::Dimension resize_dimension;
 };
 
+// The parameters needed to crop / resize / pad.
+//
+// The coordinate system has its origin at the upper left corner, and
+// positive values extend down and to the right from it.
+//
+// After the operation, the `crop_origin` will become the new origin.
+// `crop_width` and `crop_height` defines the desired cropping region. After
+// cropping, a resize is performed based on the `resize_width` and
+// `resize_height`.
+//
+// To perform just cropping, the `crop_width` and `crop_height` should be the
+// same as `resize_width` `and resize_height`.
+//
+// The cropped region is resized uniformly (respecting the aspect ratio) to best
+// match the size of the given `output_dimension` in both x and y dimensions.
+// The resized region is aligned to the upper left pixel of the output buffer.
+// The unfilled area of the output buffer remains untouched.
+struct UniformCropResizeOperation {
+  UniformCropResizeOperation(int crop_origin_x,
+                             int crop_origin_y,
+                             FrameBuffer::Dimension crop_dimension,
+                             FrameBuffer::Dimension output_dimension)
+      : crop_origin_x(crop_origin_x),
+        crop_origin_y(crop_origin_y),
+        crop_dimension(crop_dimension),
+        output_dimension(output_dimension) {}
+
+  int crop_origin_x;
+  int crop_origin_y;
+  FrameBuffer::Dimension crop_dimension;
+  FrameBuffer::Dimension output_dimension;
+};
+
 // The parameters needed to convert to the specified format.
 struct ConvertOperation {
   explicit ConvertOperation(FrameBuffer::Format to_format)
@@ -128,8 +161,10 @@
 
 // A variant of the supported operations on FrameBuffers. Alias for user
 // convenience.
-using FrameBufferOperation =
-    absl::variant<CropResizeOperation, ConvertOperation, OrientOperation>;
+using FrameBufferOperation = absl::variant<CropResizeOperation,
+                                           ConvertOperation,
+                                           OrientOperation,
+                                           UniformCropResizeOperation>;
 
 // Image processing utility. This utility provides both basic image buffer
 // manipulations (e.g. rotation, format conversion, resizing, etc) as well as
@@ -139,7 +174,8 @@
 // Examples:
 //
 //  // Create an instance of FrameBufferUtils with Halide processing engine.
-//  std::unique_ptr<FrameBufferUtils> utils = FrameBufferUtils::Create(kHalide);
+//  std::unique_ptr<FrameBufferUtils> utils =
+//  FrameBufferUtils::Create(kHalide);
 //
 //  // Perform single basic operation by each individual call.
 //  std::unique_ptr<FrameBuffer> input = FrameBuffer::Create(...);
@@ -263,10 +299,17 @@
   // If the `buffer` is already in desired format, then an extra copy will be
   // performed.
   //
+  // If `uniform_resizing` is set to true, the source region is resized
+  // uniformly (respecting the aspect ratio) to best match the dimension of the
+  // given `output_buffer` in both x and y dimensions. The resized region is
+  // aligned to the upper left pixel of the output buffer. The unfilled area of
+  // the output buffer remains untouched. Default `uniform_resizing` to false;
+  //
   // The input param `bounding_box` is defined in the `buffer` coordinate space.
   absl::Status Preprocess(const FrameBuffer& buffer,
                           absl::optional<BoundingBox> bounding_box,
-                          FrameBuffer* output_buffer);
+                          FrameBuffer* output_buffer,
+                          bool uniform_resizing = false);
 
  private:
   // Returns the new FrameBuffer size after the operation is applied.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h
index 36d1895e..59da220 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h
@@ -16,7 +16,7 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_UTILS_FRAME_BUFFER_UTILS_INTERFACE_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_UTILS_FRAME_BUFFER_UTILS_INTERFACE_H_
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 
 namespace tflite {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.cc
index 51e72fa..afbe07dd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.cc
@@ -14,7 +14,7 @@
 ==============================================================================*/
 #include "tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h"
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h
index 536eed4d..d15be3f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/image_tensor_specs.h
@@ -17,7 +17,7 @@
 
 #include <array>
 
-#include "absl/types/optional.h"
+#include "absl/types/optional.h"  // from @com_google_absl
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
index b50b500..a00c8223 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.cc
@@ -20,15 +20,16 @@
 #include <memory>
 #include <string>
 
-#include "absl/status/status.h"
-#include "absl/strings/str_cat.h"
-#include "absl/strings/str_format.h"
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_cat.h"     // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "libyuv.h"                   // from @libyuv
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
-#include "third_party/libyuv/include/libyuv.h"
 
 namespace tflite {
 namespace task {
@@ -139,7 +140,7 @@
       // the big endian style with R being the first byte in memory.
       int ret = libyuv::NV21ToRAW(
           yuv_data.y_buffer, yuv_data.y_row_stride, yuv_data.v_buffer,
-          yuv_data.uv_pixel_stride,
+          yuv_data.uv_row_stride,
           const_cast<uint8*>(output_buffer->plane(0).buffer),
           output_buffer->plane(0).stride.row_stride_bytes,
           buffer.dimension().width, buffer.dimension().height);
@@ -154,7 +155,7 @@
       // The libyuv ABGR format is interleaved RGBA format in memory.
       int ret = libyuv::NV21ToABGR(
           yuv_data.y_buffer, yuv_data.y_row_stride, yuv_data.v_buffer,
-          yuv_data.uv_pixel_stride,
+          yuv_data.uv_row_stride,
           const_cast<uint8*>(output_buffer->plane(0).buffer),
           output_buffer->plane(0).stride.row_stride_bytes,
           buffer.dimension().width, buffer.dimension().height);
@@ -353,39 +354,30 @@
 
 // Resizes NV12/NV21 `buffer` to the target `output_buffer`.
 absl::Status ResizeNv(const FrameBuffer& buffer, FrameBuffer* output_buffer) {
-  const int buffer_size =
-      GetFrameBufferByteSize(buffer.dimension(), FrameBuffer::Format::kYV21);
-  auto yuv_raw_buffer = absl::make_unique<uint8[]>(buffer_size);
-  ASSIGN_OR_RETURN(
-      std::unique_ptr<FrameBuffer> yuv_buffer,
-      CreateFromRawBuffer(yuv_raw_buffer.get(), buffer.dimension(),
-                          FrameBuffer::Format::kYV21, buffer.orientation()));
-  // TODO(b/151375918): Current implementation is a workaround by converting
-  // input NV12/NV21 buffer to the YV12 formats, resizing the YV12 buffer, and
-  // converting the resized YV12 buffer back to the target format. Consider
-  // optimizes this by adding the support of NV12/NV21 resizing in Libyuv.
-  if (buffer.format() == FrameBuffer::Format::kNV12) {
-    RETURN_IF_ERROR(ConvertFromNv12(buffer, yuv_buffer.get()));
-  } else if (buffer.format() == FrameBuffer::Format::kNV21) {
-    RETURN_IF_ERROR(ConvertFromNv21(buffer, yuv_buffer.get()));
-  } else {
-    return CreateStatusWithPayload(
-        StatusCode::kInternal,
-        absl::StrFormat("Format %i is not supported.", buffer.format()),
-        TfLiteSupportStatus::kImageProcessingError);
+  ASSIGN_OR_RETURN(FrameBuffer::YuvData input_data,
+                   FrameBuffer::GetYuvDataFromFrameBuffer(buffer));
+  ASSIGN_OR_RETURN(FrameBuffer::YuvData output_data,
+                   FrameBuffer::GetYuvDataFromFrameBuffer(*output_buffer));
+  const uint8* src_uv = input_data.u_buffer;
+  const uint8* dst_uv = output_data.u_buffer;
+  if (buffer.format() == FrameBuffer::Format::kNV21) {
+    src_uv = input_data.v_buffer;
+    dst_uv = output_data.v_buffer;
   }
 
-  const int resized_buffer_size = GetFrameBufferByteSize(
-      output_buffer->dimension(), FrameBuffer::Format::kYV12);
-  auto resized_yuv_raw_buffer = absl::make_unique<uint8[]>(resized_buffer_size);
-  ASSIGN_OR_RETURN(std::unique_ptr<FrameBuffer> resized_yuv_buffer,
-                   CreateFromRawBuffer(resized_yuv_raw_buffer.get(),
-                                       output_buffer->dimension(),
-                                       FrameBuffer::Format::kYV12,
-                                       output_buffer->orientation()));
-  RETURN_IF_ERROR(ResizeYv(*yuv_buffer, resized_yuv_buffer.get()));
+  int ret = libyuv::NV12Scale(
+      input_data.y_buffer, input_data.y_row_stride, src_uv,
+      input_data.uv_row_stride, buffer.dimension().width,
+      buffer.dimension().height, const_cast<uint8_t*>(output_data.y_buffer),
+      output_data.y_row_stride, const_cast<uint8_t*>(dst_uv),
+      output_data.uv_row_stride, output_buffer->dimension().width,
+      output_buffer->dimension().height, libyuv::FilterMode::kFilterBilinear);
 
-  RETURN_IF_ERROR(ConvertFromYv(*resized_yuv_buffer, output_buffer));
+  if (ret != 0) {
+    return CreateStatusWithPayload(
+        StatusCode::kUnknown, "Libyuv NV12Scale operation failed.",
+        TfLiteSupportStatus::kImageProcessingBackendError);
+  }
   return absl::OkStatus();
 }
 
@@ -1361,6 +1353,7 @@
           TfLiteSupportStatus::kImageProcessingError);
   }
 }
+
 }  // namespace
 
 absl::Status LibyuvFrameBufferUtils::Crop(const FrameBuffer& buffer,
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h
index 24ed424..6f83559 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/libyuv_frame_buffer_utils.h
@@ -16,7 +16,7 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_UTILS_LIBYUV_FRAME_BUFFER_UTILS_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_TASK_VISION_UTILS_LIBYUV_FRAME_BUFFER_UTILS_H_
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils_interface.h"
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc
index 773ab76..d58969d9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.cc
@@ -14,16 +14,17 @@
 ==============================================================================*/
 #include "tensorflow_lite_support/cc/task/vision/utils/score_calibration.h"
 
+#include <algorithm>
 #include <cmath>
 #include <memory>
 #include <utility>
 #include <vector>
 
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
-#include "absl/strings/str_split.h"
-#include "absl/strings/string_view.h"
-#include "absl/types/optional.h"
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/str_format.h"   // from @com_google_absl
+#include "absl/strings/str_split.h"    // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "absl/types/optional.h"       // from @com_google_absl
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 
@@ -95,6 +96,17 @@
           TfLiteSupportStatus::kMetadataMalformedScoreCalibrationError);
     }
   }
+
+  // Verify if scale is a non-negative value.
+  if (float_params[0] < 0) {
+    return CreateStatusWithPayload(
+        StatusCode::kInvalidArgument,
+        absl::StrFormat(
+            "Expected scale to be a non-negative value, but got %f.",
+            float_params[0]),
+        TfLiteSupportStatus::kMetadataMalformedScoreCalibrationError);
+  }
+
   Sigmoid sigmoid;
   sigmoid.label = std::string(label);
   sigmoid.scale = float_params[0];
@@ -160,13 +172,20 @@
 
   // For numerical stability use 1 / (1+exp(-x)) when scale_shifted_score >= 0
   // and exp(x) / (1+exp(x)) when scale_shifted_score < 0.
+  float calibrated_score;
   if (scale_shifted_score >= 0.0) {
-    return sigmoid.value().scale /
-           (1.0 + std::exp(static_cast<double>(-scale_shifted_score)));
+    calibrated_score =
+        sigmoid.value().scale /
+        (1.0 + std::exp(static_cast<double>(-scale_shifted_score)));
   } else {
     float score_exp = std::exp(static_cast<double>(scale_shifted_score));
-    return sigmoid.value().scale * score_exp / (1.0 + score_exp);
+    calibrated_score = sigmoid.value().scale * score_exp / (1.0 + score_exp);
   }
+  // Scale is non-negative (checked in SigmoidFromLabelAndLine),
+  // thus calibrated_score should be in the range of [0, scale]. However, due to
+  // numberical stability issue, it may fall out of the boundary. Cap the value
+  // to [0, scale] instead.
+  return std::max(std::min(calibrated_score, sigmoid.value().scale), 0.0f);
 }
 
 absl::optional<Sigmoid> ScoreCalibration::FindSigmoidParameters(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h
index 19d966b..e2b403d 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/task/vision/utils/score_calibration.h
@@ -22,10 +22,10 @@
 #include <utility>
 #include <vector>
 
-#include "absl/container/flat_hash_map.h"
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
-#include "absl/types/optional.h"
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/string_view.h"      // from @com_google_absl
+#include "absl/types/optional.h"           // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/vision/core/label_map_item.h"
 #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/BUILD
new file mode 100644
index 0000000..a2a8007
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/BUILD
@@ -0,0 +1,31 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "test_utils",
+    testonly = 1,
+    srcs = ["test_utils.cc"],
+    hdrs = [
+        "message_matchers.h",
+        "test_utils.h",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/port:proto2",
+        "@com_google_absl//absl/strings",
+        "@com_google_glog//:glog",
+    ],
+)
+
+cc_test(
+    name = "common_test",
+    srcs = ["common_test.cc"],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:cord",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc
new file mode 100644
index 0000000..bc2f9dfd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/common_test.cc
@@ -0,0 +1,41 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/common.h"
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/strings/cord.h"   // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+
+namespace tflite {
+namespace support {
+namespace {
+
+using testing::Optional;
+
+TEST(CommonTest, CreateStatusWithPayloadWorks) {
+  absl::Status status = CreateStatusWithPayload(
+      absl::StatusCode::kInvalidArgument, "Bad schema version: BADF",
+      TfLiteSupportStatus::kMetadataInvalidSchemaVersionError);
+  EXPECT_EQ(status.code(), absl::StatusCode::kInvalidArgument);
+  EXPECT_EQ(status.message(), std::string("Bad schema version: BADF"));
+  EXPECT_THAT(status.GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord("200")));
+}
+
+}  // namespace
+}  // namespace support
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/message_matchers.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/message_matchers.h
new file mode 100644
index 0000000..6820e20
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/message_matchers.h
@@ -0,0 +1,89 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TEST_MESSAGE_MATCHERS_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TEST_MESSAGE_MATCHERS_H_
+
+#include <memory>
+
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/proto2.h"
+
+namespace tflite {
+namespace support {
+
+class ProtoMatcher {
+ public:
+  using is_gtest_matcher = void;
+  using MessageType = tflite::support::proto::MessageLite;
+
+  explicit ProtoMatcher(const MessageType& message)
+      : message_(CloneMessage(message)) {}
+
+  bool MatchAndExplain(const MessageType& m,
+                       testing::MatchResultListener*) const {
+    return EqualsMessage(*message_, m);
+  }
+  bool MatchAndExplain(const MessageType* m,
+                       testing::MatchResultListener*) const {
+    return EqualsMessage(*message_, *m);
+  }
+
+  void DescribeTo(std::ostream* os) const {
+    *os << "has the same serialization as " << ExpectedMessageDescription();
+  }
+
+  void DescribeNegationTo(std::ostream* os) const {
+    *os << "does not have the same serialization as "
+        << ExpectedMessageDescription();
+  }
+
+ private:
+  std::unique_ptr<MessageType> CloneMessage(const MessageType& message) {
+    std::unique_ptr<MessageType> clone(message.New());
+    clone->CheckTypeAndMergeFrom(message);
+    return clone;
+  }
+
+  bool EqualsMessage(const MessageType& m_1, const MessageType& m_2) const {
+    std::string s_1, s_2;
+    m_1.SerializeToString(&s_1);
+    m_2.SerializeToString(&s_2);
+    return s_1 == s_2;
+  }
+
+  std::string ExpectedMessageDescription() const {
+    return message_->DebugString();
+  }
+
+  const std::shared_ptr<MessageType> message_;
+};
+
+inline ProtoMatcher EqualsProto(
+    const tflite::support::proto::MessageLite& message) {
+  return ProtoMatcher(message);
+}
+
+// for Pointwise
+MATCHER(EqualsProto, "") {
+  const auto& a = ::testing::get<0>(arg);
+  const auto& b = ::testing::get<1>(arg);
+  return ::testing::ExplainMatchResult(EqualsProto(b), a, result_listener);
+}
+
+}  // namespace support
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TEST_MESSAGE_MATCHERS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/BUILD
new file mode 100644
index 0000000..7376ad3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/BUILD
@@ -0,0 +1,32 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_test_with_tflite",
+)
+
+package(
+    default_visibility = [
+        "//visibility:private",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_test_with_tflite(
+    name = "image_preprocessor_test",
+    srcs = ["image_preprocessor_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/processor:image_preprocessor",
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_absl//absl/status",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc
new file mode 100644
index 0000000..9ae9435
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/processor/image_preprocessor_test.cc
@@ -0,0 +1,116 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/processor/image_preprocessor.h"
+
+#include <memory>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace task {
+namespace processor {
+namespace {
+
+using ::tflite::support::StatusOr;
+using ::tflite::task::JoinPath;
+using ::tflite::task::core::TfLiteEngine;
+using ::tflite::task::vision::DecodeImageFromFile;
+using ::tflite::task::vision::FrameBuffer;
+using ::tflite::task::vision::ImageData;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "vision/";
+
+constexpr char kDilatedConvolutionModelWithMetaData[] = "dilated_conv.tflite";
+
+StatusOr<ImageData> LoadImage(std::string image_name) {
+  return DecodeImageFromFile(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+}
+
+class DynamicInputTest : public tflite_shims::testing::Test {
+ protected:
+  void PreprocessImage() {
+    engine_ = absl::make_unique<TfLiteEngine>();
+    SUPPORT_ASSERT_OK(engine_->BuildModelFromFile(
+        JoinPath("./" /*test src dir*/, kTestDataDirectory,
+                 kDilatedConvolutionModelWithMetaData)));
+    SUPPORT_ASSERT_OK(engine_->InitInterpreter());
+
+    SUPPORT_ASSERT_OK_AND_ASSIGN(auto preprocessor,
+                                 ImagePreprocessor::Create(engine_.get(), {0}));
+
+    SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+    std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+        image.pixel_data, FrameBuffer::Dimension{image.width, image.height});
+
+    SUPPORT_ASSERT_OK(preprocessor->Preprocess(*frame_buffer));
+
+    ImageDataFree(&image);
+  }
+
+  std::unique_ptr<TfLiteEngine> engine_ = nullptr;
+};
+
+// See if output tensor has been re-dimmed as per the input
+// tensor. Expected shape: (1, input_height, input_width, 16).
+TEST_F(DynamicInputTest, OutputDimensionCheck) {
+  PreprocessImage();
+
+  EXPECT_TRUE(engine_->interpreter_wrapper()->InvokeWithoutFallback().ok());
+  EXPECT_EQ(engine_->GetOutputs()[0]->dims->data[0], 1);
+  EXPECT_EQ(engine_->GetOutputs()[0]->dims->data[1],
+            engine_->GetInputs()[0]->dims->data[1]);
+  EXPECT_EQ(engine_->GetOutputs()[0]->dims->data[2],
+            engine_->GetInputs()[0]->dims->data[2]);
+  EXPECT_EQ(engine_->GetOutputs()[0]->dims->data[3], 16);
+}
+
+// Compare pre-processed input with an already pre-processed
+// golden image.
+TEST_F(DynamicInputTest, GoldenImageComparison) {
+  PreprocessImage();
+
+  // Get the processed input image.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      float* processed_input_data,
+      tflite::task::core::AssertAndReturnTypedTensor<float>(
+          engine_->GetInputs()[0]));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+  const uint8* image_data = image.pixel_data;
+  const size_t image_size = image.width * image.height * 3;
+
+  for (size_t i = 0; i < image_size; ++i, ++image_data, ++processed_input_data)
+    EXPECT_NEAR(static_cast<float>(*image_data), *processed_input_data,
+                std::numeric_limits<float>::epsilon());
+
+  ImageDataFree(&image);
+}
+
+}  // namespace
+}  // namespace processor
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/BUILD
new file mode 100644
index 0000000..57f26345
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/BUILD
@@ -0,0 +1,48 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_test_with_tflite",
+)
+
+package(
+    default_visibility = [
+        "//visibility:private",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_test_with_tflite(
+    name = "bert_nl_classifier_test",
+    srcs = ["bert_nl_classifier_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/text:bert_nl_classifier_models",
+    ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+        "//tensorflow_lite_support/cc/task/text:bert_nl_classifier",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+    ],
+)
+
+cc_test(
+    name = "bert_question_answerer_test",
+    timeout = "long",
+    srcs = ["bert_question_answerer_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/text:albert_model",
+        "//tensorflow_lite_support/cc/test/testdata/task/text:mobile_bert_model",
+    ],
+    tags = [
+        "optonly",  # The test takes long, and only run with -c opt.
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/text:bert_question_answerer",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc
new file mode 100644
index 0000000..c4a8cea
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_nl_classifier_test.cc
@@ -0,0 +1,210 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
+
+#include <fcntl.h>
+
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+namespace {
+
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::core::Category;
+using ::tflite::task::core::LoadBinaryContent;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "text/";
+
+constexpr char kTestModelPath[] = "bert_nl_classifier.tflite";
+
+constexpr char kInvalidModelPath[] = "i/do/not/exist.tflite";
+
+constexpr int kMaxSeqLen = 128;
+
+std::string GetFullPath(absl::string_view file_name) {
+  return JoinPath("./" /*test src dir*/, kTestDataDirectory, file_name);
+}
+
+class BertNLClassifierTest : public tflite_shims::testing::Test {};
+
+TEST_F(BertNLClassifierTest, CreateFromOptionsSucceedsWithModelWithMetadata) {
+  BertNLClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestModelPath));
+
+  SUPPORT_ASSERT_OK(BertNLClassifier::CreateFromOptions(options));
+}
+
+TEST_F(BertNLClassifierTest, CreateFromOptionsFailsWithMissingBaseOptions) {
+  BertNLClassifierOptions options;
+  StatusOr<std::unique_ptr<BertNLClassifier>> classifier_or =
+      BertNLClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(classifier_or.status().code(), absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(classifier_or.status().message(),
+              HasSubstr("Missing mandatory `base_options`"));
+  EXPECT_THAT(classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifierCreationFilePath) {
+  SUPPORT_ASSERT_OK(
+      BertNLClassifier::CreateFromFile(GetFullPath(kTestModelPath)));
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifierCreationBinary) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+  SUPPORT_ASSERT_OK(BertNLClassifier::CreateFromBuffer(model_buffer.data(),
+                                                       model_buffer.size()));
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifierCreationFailure) {
+  StatusOr<std::unique_ptr<BertNLClassifier>> classifier_or =
+      BertNLClassifier::CreateFromFile(kInvalidModelPath);
+
+  EXPECT_EQ(classifier_or.status().code(), absl::StatusCode::kNotFound);
+  EXPECT_THAT(classifier_or.status().message(),
+              HasSubstr("Unable to open file at i/do/not/exist.tflite"));
+  EXPECT_THAT(classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              testing::Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kFileNotFoundError))));
+}
+
+Category* GetCategoryWithClassName(const std::string& class_name,
+                                   std::vector<Category>& categories) {
+  for (Category& category : categories) {
+    if (category.class_name == class_name) {
+      return &category;
+    }
+  }
+  return nullptr;
+}
+
+void verify_classifier(std::unique_ptr<BertNLClassifier> classifier,
+                       bool verify_positive) {
+  if (verify_positive) {
+    std::vector<core::Category> results =
+        classifier->Classify("unflinchingly bleak and desperate");
+    EXPECT_GT(GetCategoryWithClassName("negative", results)->score,
+              GetCategoryWithClassName("positive", results)->score);
+  } else {
+    std::vector<Category> results =
+        classifier->Classify("it's a charming and often affecting journey");
+    EXPECT_GT(GetCategoryWithClassName("positive", results)->score,
+              GetCategoryWithClassName("negative", results)->score);
+  }
+}
+
+TEST_F(BertNLClassifierTest, ClassifySucceedsWithBaseOptions) {
+  std::unique_ptr<BertNLClassifier> classifier;
+
+  // Test creating BertNLClassifier when classifier outlives options.
+  {
+    std::string contents =
+        LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+    BertNLClassifierOptions options;
+    options.mutable_base_options()->mutable_model_file()->set_file_content(
+        contents);
+
+    SUPPORT_ASSERT_OK_AND_ASSIGN(classifier,
+                                 BertNLClassifier::CreateFromOptions(options));
+  }
+
+  verify_classifier(std::move(classifier), /*verify_positive=*/false);
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifier_ClassifyNegative) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+                               BertNLClassifier::CreateFromBuffer(
+                                   model_buffer.data(), model_buffer.size()));
+
+  verify_classifier(std::move(classifier), false);
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifier_ClassifyPositive) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+                               BertNLClassifier::CreateFromBuffer(
+                                   model_buffer.data(), model_buffer.size()));
+
+  verify_classifier(std::move(classifier), true);
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifierFd_ClassifyPositive) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<BertNLClassifier> classifier,
+      BertNLClassifier::CreateFromFd(
+          open(GetFullPath(kTestModelPath).c_str(), O_RDONLY)));
+
+  verify_classifier(std::move(classifier), false);
+}
+
+TEST_F(BertNLClassifierTest, TestNLClassifierFd_ClassifyNegative) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<BertNLClassifier> classifier,
+      BertNLClassifier::CreateFromFd(
+          open(GetFullPath(kTestModelPath).c_str(), O_RDONLY)));
+
+  verify_classifier(std::move(classifier), true);
+}
+
+// BertNLClassifier limits the input sequence to kMaxSeqLen, test when input is
+// longer than this the classifier still works correctly.
+TEST_F(BertNLClassifierTest, TestNLClassifier_ClassifyLongPositive_notOOB) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestModelPath).c_str());
+  std::stringstream ss_for_positive_review;
+  ss_for_positive_review
+      << "it's a charming and often affecting journey and this is a long";
+  for (int i = 0; i < kMaxSeqLen; ++i) {
+    ss_for_positive_review << " long";
+  }
+  ss_for_positive_review << " movie review";
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<BertNLClassifier> classifier,
+                               BertNLClassifier::CreateFromBuffer(
+                                   model_buffer.data(), model_buffer.size()));
+
+  std::vector<core::Category> results =
+      classifier->Classify(ss_for_positive_review.str());
+
+  EXPECT_GT(GetCategoryWithClassName("positive", results)->score,
+            GetCategoryWithClassName("negative", results)->score);
+}
+
+}  // namespace
+
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc
new file mode 100644
index 0000000..a70dab7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/bert_question_answerer_test.cc
@@ -0,0 +1,238 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
+
+#include <fcntl.h>
+
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+
+namespace {
+
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::JoinPath;
+using ::tflite::task::core::LoadBinaryContent;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "text/";
+
+constexpr char kTestMobileBertModelPath[] = "mobilebert_float.tflite";
+constexpr char kTestVocabPath[] = "mobilebert_vocab.txt";
+constexpr char kTestMobileBertWithMetadataModelPath[] =
+    "mobilebert_with_metadata.tflite";
+constexpr char kTestAlBertModelPath[] = "albert.tflite";
+constexpr char kTestSPModelPath[] = "30k-clean.model";
+constexpr char kTestAlbertWithMetadataModelPath[] =
+    "albert_with_metadata.tflite";
+
+constexpr char kQuestion[] = "What is a course of study called?";
+constexpr char kAnswer[] = "the curriculum.";
+constexpr char kContext[] =
+    "The role of teacher is often formal and ongoing, carried out at a school "
+    "or other place of formal education. In many countries, a person who "
+    "wishes to become a teacher must first obtain specified professional "
+    "qualifications or credentials from a university or college. These "
+    "professional qualifications may include the study of pedagogy, the "
+    "science of teaching. Teachers, like other professionals, may have to "
+    "continue their education after they qualify, a process known as "
+    "continuing professional development. Teachers may use a lesson plan to "
+    "facilitate student learning, providing a course of study which is called "
+    "the curriculum.";
+constexpr int kPredictAnsNum = 5;
+
+class BertQuestionAnswererTest : public tflite_shims::testing::Test {};
+
+std::string GetFullPath(absl::string_view file_name) {
+  return JoinPath("./" /*test src dir*/, kTestDataDirectory, file_name);
+}
+
+TEST_F(BertQuestionAnswererTest,
+       CreateFromOptionsSucceedsWithModelWithMetadata) {
+  BertQuestionAnswererOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestMobileBertWithMetadataModelPath));
+
+  SUPPORT_ASSERT_OK(BertQuestionAnswerer::CreateFromOptions(options));
+}
+
+TEST_F(BertQuestionAnswererTest, CreateFromOptionsFailsWithMissingBaseOptions) {
+  BertQuestionAnswererOptions options;
+  StatusOr<std::unique_ptr<QuestionAnswerer>> question_answerer_or =
+      BertQuestionAnswerer::CreateFromOptions(options);
+
+  EXPECT_EQ(question_answerer_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(question_answerer_or.status().message(),
+              HasSubstr("Missing mandatory `base_options`"));
+  EXPECT_THAT(question_answerer_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(BertQuestionAnswererTest, AnswerSucceedsWithModelWithMetadata) {
+  std::unique_ptr<QuestionAnswerer> question_answerer;
+
+  // Test creating NLClassifier when question_answerer outlives options.
+  {
+    std::string contents = LoadBinaryContent(
+        GetFullPath(kTestMobileBertWithMetadataModelPath).c_str());
+
+    BertQuestionAnswererOptions options;
+    options.mutable_base_options()->mutable_model_file()->set_file_content(
+        contents);
+
+    SUPPORT_ASSERT_OK_AND_ASSIGN(
+        question_answerer, BertQuestionAnswerer::CreateFromOptions(options));
+  }
+
+  std::vector<QaAnswer> answer = question_answerer->Answer(kContext, kQuestion);
+  ASSERT_EQ(answer.size(), kPredictAnsNum);
+  EXPECT_EQ(answer[0].text, kAnswer);
+}
+
+TEST_F(BertQuestionAnswererTest, TestBertCreationFromBinary) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestMobileBertModelPath).c_str());
+  std::string vocab_buffer =
+      LoadBinaryContent(GetFullPath(kTestVocabPath).c_str());
+  SUPPORT_ASSERT_OK(BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
+      model_buffer.data(), model_buffer.size(), vocab_buffer.data(),
+      vocab_buffer.size()));
+}
+
+TEST_F(BertQuestionAnswererTest, TestBertCreationFromFile) {
+  SUPPORT_ASSERT_OK(BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
+      GetFullPath(kTestMobileBertModelPath).c_str(),
+      GetFullPath(kTestVocabPath).c_str()));
+}
+
+TEST_F(BertQuestionAnswererTest, TestBertAnswer) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<QuestionAnswerer> question_answerer_status,
+      BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
+          GetFullPath(kTestMobileBertModelPath).c_str(),
+          GetFullPath(kTestVocabPath).c_str()));
+
+  std::vector<QaAnswer> answer =
+      question_answerer_status->Answer(kContext, kQuestion);
+  ASSERT_EQ(answer.size(), kPredictAnsNum);
+  EXPECT_EQ(answer[0].text, kAnswer);
+}
+
+TEST_F(BertQuestionAnswererTest, TestAlbertCreationFromBinary) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestAlBertModelPath).c_str());
+  std::string vocab_buffer =
+      LoadBinaryContent(GetFullPath(kTestSPModelPath).c_str());
+  SUPPORT_ASSERT_OK(BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
+      model_buffer.data(), model_buffer.size(), vocab_buffer.data(),
+      vocab_buffer.size()));
+}
+
+TEST_F(BertQuestionAnswererTest, TestAlbertCreationFromFile) {
+  SUPPORT_ASSERT_OK(BertQuestionAnswerer::CreateBertQuestionAnswererFromFile(
+      GetFullPath(kTestAlBertModelPath).c_str(),
+      GetFullPath(kTestSPModelPath).c_str()));
+}
+
+TEST_F(BertQuestionAnswererTest, TestAlbertAnswer) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<QuestionAnswerer> question_answerer_status,
+      BertQuestionAnswerer::CreateAlbertQuestionAnswererFromFile(
+          GetFullPath(kTestAlBertModelPath).c_str(),
+          GetFullPath(kTestSPModelPath).c_str()));
+
+  std::vector<QaAnswer> answer =
+      question_answerer_status->Answer(kContext, kQuestion);
+  ASSERT_EQ(answer.size(), kPredictAnsNum);
+  EXPECT_EQ(answer[0].text, kAnswer);
+}
+
+TEST_F(BertQuestionAnswererTest, TestCreateWithMetadata) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<QuestionAnswerer> question_answerer_status,
+      BertQuestionAnswerer::CreateFromFile(
+          GetFullPath(kTestMobileBertWithMetadataModelPath).c_str()));
+
+  std::vector<QaAnswer> answer =
+      question_answerer_status->Answer(kContext, kQuestion);
+  ASSERT_EQ(answer.size(), kPredictAnsNum);
+  EXPECT_EQ(answer[0].text, kAnswer);
+}
+
+TEST_F(BertQuestionAnswererTest, TestCreateWithMetadataFromBinary) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestAlbertWithMetadataModelPath).c_str());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<QuestionAnswerer> question_answerer_status,
+      BertQuestionAnswerer::CreateFromBuffer(model_buffer.data(),
+                                             model_buffer.size()));
+
+  std::vector<QaAnswer> answer =
+      question_answerer_status->Answer(kContext, kQuestion);
+  ASSERT_EQ(answer.size(), kPredictAnsNum);
+  EXPECT_EQ(answer[0].text, kAnswer);
+}
+
+TEST_F(BertQuestionAnswererTest, TestCreateWithFileDescriptor2) {
+  std::string model_buffer =
+      LoadBinaryContent(GetFullPath(kTestAlbertWithMetadataModelPath).c_str());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<QuestionAnswerer> question_answerer_status,
+      BertQuestionAnswerer::CreateFromFd(open(
+          GetFullPath(kTestAlbertWithMetadataModelPath).c_str(), O_RDONLY)));
+
+  std::vector<QaAnswer> answer =
+      question_answerer_status->Answer(kContext, kQuestion);
+  ASSERT_EQ(answer.size(), kPredictAnsNum);
+  EXPECT_EQ(answer[0].text, kAnswer);
+}
+
+TEST_F(BertQuestionAnswererTest,
+       TestCreateWithMetadataFail_fromModelWithoutMetadata) {
+  StatusOr<std::unique_ptr<QuestionAnswerer>> question_answerer_or =
+      BertQuestionAnswerer::CreateFromFile(
+          GetFullPath(kTestMobileBertModelPath).c_str());
+
+  EXPECT_EQ(question_answerer_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(question_answerer_or.status().message(),
+              HasSubstr("No input process unit found from metadata."));
+  EXPECT_THAT(question_answerer_or.status().GetPayload(
+                  tflite::support::kTfLiteSupportPayload),
+              testing::Optional(absl::Cord(absl::StrCat(
+                  TfLiteSupportStatus::kMetadataInvalidTokenizerError))));
+}
+
+}  // namespace
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/BUILD
new file mode 100644
index 0000000..28c5739
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/BUILD
@@ -0,0 +1,47 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_test_with_tflite",
+)
+
+package(
+    default_visibility = [
+        "//visibility:private",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "nl_classifier_test_utils",
+    srcs = ["nl_classifier_test_utils.cc"],
+    hdrs = ["nl_classifier_test_utils.h"],
+    visibility = ["//tensorflow_lite_support:internal"],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "@org_tensorflow//tensorflow/lite:op_resolver",
+        "@org_tensorflow//tensorflow/lite:string_util",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+        "@org_tensorflow//tensorflow/lite/kernels:kernel_util",
+    ],
+)
+
+cc_test_with_tflite(
+    name = "nl_classifier_test",
+    srcs = ["nl_classifier_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/text:nl_classifier_models",
+    ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+        "//tensorflow_lite_support/cc/task/core:base_task_api",
+        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
+    ],
+    deps = [
+        ":nl_classifier_test_utils",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "@org_tensorflow//tensorflow/lite:string_util",
+        "@org_tensorflow//tensorflow/lite/kernels:deprecated_backends",
+        "@org_tensorflow//tensorflow/lite/kernels:kernel_util",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc
new file mode 100644
index 0000000..81198cf
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test.cc
@@ -0,0 +1,580 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
+
+#include <utility>
+
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/string_util.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/base_task_api.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+
+static constexpr char kInputStr[] = "hello";
+
+namespace tflite {
+namespace task {
+namespace text {
+namespace nlclassifier {
+namespace {
+
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::testing::TestWithParam;
+using ::testing::UnorderedElementsAreArray;
+using ::testing::ValuesIn;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::JoinPath;
+using ::tflite::task::core::LoadBinaryContent;
+using NLClassifierProtoOptions = ::tflite::task::text::NLClassifierOptions;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "text/";
+
+// The model has 1 input tensor and 4 output tensors with the following names
+// and indices.
+// The model also has three custom OPs to mimic classification model behaviors,
+// see CUSTOM_OP_STRING_TO_FLOATS, CUSTOM_OP_STRING_TO_DOUBLES
+// and CUSTOM_OP_GENERATE_LABELS in nl_classifier_test_utils for details.
+constexpr char kTestModelPath[] = "test_model_nl_classifier.tflite";
+
+// The model has 1 input tensor and 1 output tensor
+// The model also has a custom OP to mimic classification model behaviors,
+// see CUSTOM_OP_STRING_TO_BOOLS in nl_classifier_test_utils for details.
+constexpr char kTestModelBoolOutputPath[] =
+    "test_model_nl_classifier_bool_output.tflite";
+
+// The model has same input/output tensors with the above model, except its
+// first output tensor is associated with metadata with name
+// kMetadataOutputScoreTensorName and an associated label file.
+constexpr char kTestModelWithLabelCustomOpsPath[] =
+    "test_model_nl_classifier_with_associated_label.tflite";
+
+constexpr char kTestModelWithLabelBuiltInOpsPath[] =
+    "test_model_nl_classifier_with_associated_label_builtin_ops.tflite";
+
+// This model expects input to be tokenized by a regex tokenizer.
+constexpr char kTestModelWithRegexTokenizer[] =
+    "test_model_nl_classifier_with_regex_tokenizer.tflite";
+
+constexpr char kPositiveInput[] =
+    "This is the best movie I’ve seen in recent years. Strongly recommend "
+    "it!";
+std::vector<core::Category> GetExpectedResultsOfPositiveInput() {
+  return {
+      {"Positive", 0.51342660188674927},
+      {"Negative", 0.48657345771789551},
+  };
+}
+
+constexpr char kNegativeInput[] = "What a waste of my time.";
+std::vector<core::Category> GetExpectedResultsOfNegativeInput() {
+  return {
+      {"Positive", 0.18687039613723755},
+      {"Negative", 0.81312954425811768},
+  };
+}
+
+const uint8_t kOutputDequantizedTensorIndex = 0;
+const uint8_t kOutputQuantizedTensorIndex = 1;
+const uint8_t kOutputLabelTensorIndex = 2;
+const uint8_t kOutputDequantizedTensorFloat64Index = 3;
+constexpr char kInputTensorName[] = "INPUT";
+constexpr char kOutputDequantizedTensorName[] = "OUTPUT_SCORE_DEQUANTIZED";
+constexpr char kOutputDequantizedTensorFloat64Name[] =
+    "OUTPUT_SCORE_DEQUANTIZED_FLOAT64";
+constexpr char kOutputQuantizedTensorName[] = "OUTPUT_SCORE_QUANTIZED";
+constexpr char kOutputLabelTensorName[] = "LABELS";
+constexpr char kMetadataOutputScoreTensorName[] = "scores_dequantized";
+constexpr char kDefaultInputTensorName[] = "INPUT";
+constexpr char kDefaultOutputLabelTensorName[] = "OUTPUT_LABEL";
+constexpr int kDefaultInputTensorIndex = 0;
+constexpr int kDefaultOutputLabelTensorIndex = -1;
+
+// Test the API with different combinations in creating proto
+// NLClassifierOptions
+struct ProtoOptionsTestParam {
+  // description of current test
+  std::string description;
+  NLClassifierProtoOptions options;
+};
+
+std::string GetFullPath(absl::string_view file_name) {
+  return JoinPath("./" /*test src dir*/, kTestDataDirectory, file_name);
+}
+
+class ProtoOptionsTest : public TestWithParam<ProtoOptionsTestParam> {
+ protected:
+  void SetUp() override { ASSERT_EQ(TfLiteInitializeShimsForTest(), 0); }
+};
+
+TEST_F(ProtoOptionsTest, CreateFromOptionsSucceedsWithModelWithMetadata) {
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestModelWithRegexTokenizer));
+
+  SUPPORT_ASSERT_OK(NLClassifier::CreateFromOptions(options));
+}
+
+TEST_F(ProtoOptionsTest, CreateFromOptionsFailsWithMissingBaseOptions) {
+  NLClassifierProtoOptions options;
+  StatusOr<std::unique_ptr<NLClassifier>> nl_classifier_or =
+      NLClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(nl_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(nl_classifier_or.status().message(),
+              HasSubstr("Missing mandatory `base_options`"));
+  EXPECT_THAT(nl_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(ProtoOptionsTest, ClassifySucceedsWithBaseOptions) {
+  std::unique_ptr<NLClassifier> classifier;
+
+  // Test creating NLClassifier when classifier outlives options.
+  {
+    std::string contents =
+        LoadBinaryContent(GetFullPath(kTestModelWithRegexTokenizer).c_str());
+    NLClassifierProtoOptions options;
+    options.mutable_base_options()->mutable_model_file()->set_file_content(
+        contents);
+
+    SUPPORT_ASSERT_OK_AND_ASSIGN(classifier,
+                                 NLClassifier::CreateFromOptions(options));
+  }
+
+  std::vector<core::Category> positive_results =
+      classifier->Classify(kPositiveInput);
+
+  EXPECT_THAT(positive_results,
+              UnorderedElementsAreArray(GetExpectedResultsOfPositiveInput()));
+
+  std::vector<core::Category> negative_results =
+      classifier->Classify(kNegativeInput);
+  EXPECT_THAT(negative_results,
+              UnorderedElementsAreArray(GetExpectedResultsOfNegativeInput()));
+}
+
+TEST_F(ProtoOptionsTest, CreationFromIncorrectInputTensor) {
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath));
+  options.set_input_tensor_name("invalid_tensor_name");
+  options.set_input_tensor_index(-1);
+
+  StatusOr<std::unique_ptr<NLClassifier>> nl_classifier_or =
+      NLClassifier::CreateFromOptions(options, CreateCustomResolver());
+
+  EXPECT_EQ(nl_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(nl_classifier_or.status().message(),
+              HasSubstr("No input tensor found with name "
+                        "invalid_tensor_name or at index -1"));
+  EXPECT_THAT(
+      nl_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+      absl::Cord(absl::StrCat(TfLiteSupportStatus::kInputTensorNotFoundError)));
+}
+
+TEST_F(ProtoOptionsTest, CreationFromIncorrectOutputScoreTensor) {
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath));
+  options.set_output_score_tensor_name("invalid_tensor_name");
+  options.set_output_score_tensor_index(-1);
+
+  StatusOr<std::unique_ptr<NLClassifier>> nl_classifier_or =
+      NLClassifier::CreateFromOptions(options, CreateCustomResolver());
+
+  EXPECT_EQ(nl_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(nl_classifier_or.status().message(),
+              HasSubstr("No output score tensor found with name "
+                        "invalid_tensor_name or at index -1"));
+  EXPECT_THAT(nl_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              absl::Cord(absl::StrCat(
+                  TfLiteSupportStatus::kOutputTensorNotFoundError)));
+}
+
+TEST_F(ProtoOptionsTest, TestInferenceWithRegexTokenizer) {
+  // The model with regex tokenizer doesn't need any custom ops.
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestModelWithRegexTokenizer));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+                               NLClassifier::CreateFromOptions(options));
+
+  std::vector<core::Category> positive_results =
+      classifier->Classify(kPositiveInput);
+
+  EXPECT_THAT(positive_results,
+              UnorderedElementsAreArray(GetExpectedResultsOfPositiveInput()));
+
+  std::vector<core::Category> negative_results =
+      classifier->Classify(kNegativeInput);
+  EXPECT_THAT(negative_results,
+              UnorderedElementsAreArray(GetExpectedResultsOfNegativeInput()));
+}
+
+TEST_F(ProtoOptionsTest, TestInferenceWithBoolOutput) {
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestModelBoolOutputPath));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<NLClassifier> classifier,
+      NLClassifier::CreateFromOptions(options, CreateCustomResolver()));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+  std::vector<core::Category> expected_class = {
+      {"0", 1},
+      {"1", 1},
+      {"2", 0},
+  };
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+TEST_F(ProtoOptionsTest, TestInferenceWithAssociatedLabelCustomOps) {
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestModelWithLabelCustomOpsPath));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<NLClassifier> classifier,
+      NLClassifier::CreateFromOptions(options, CreateCustomResolver()));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+  std::vector<core::Category> expected_class = {
+      {"label0", 255},
+      {"label1", 510},
+      {"label2", 765},
+  };
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+TEST_F(ProtoOptionsTest, TestInferenceWithAssociatedLabelBuiltinOps) {
+  NLClassifierProtoOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      GetFullPath(kTestModelWithLabelBuiltInOpsPath));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+                               NLClassifier::CreateFromOptions(options));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+  std::vector<core::Category> expected_class = {
+      {"Negative", 0.49332118034362793},
+      {"Positive", 0.50667881965637207},
+  };
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+// Parameterized test.
+struct ProtoOptionsTestParamToString {
+  std::string operator()(
+      const testing::TestParamInfo<ProtoOptionsTestParam>& info) const {
+    return info.param.description;
+  }
+};
+
+NLClassifierProtoOptions CreateProtoOptionsFromTensorName(
+    const char* input_tensor_name,
+    const char* output_score_tensor_name,
+    const char* output_label_tensor_name,
+    const char* model_path) {
+  NLClassifierProtoOptions options;
+  options.set_input_tensor_name(input_tensor_name);
+  options.set_output_score_tensor_name(output_score_tensor_name);
+  options.set_output_label_tensor_name(output_label_tensor_name);
+
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      model_path);
+
+  return options;
+}
+
+NLClassifierProtoOptions CreateProtoOptionsFromTensorIndex(
+    const int input_tensor_index,
+    const int output_score_tensor_index,
+    const int output_label_tensor_index,
+    const char* model_path) {
+  NLClassifierProtoOptions options;
+  options.set_input_tensor_index(input_tensor_index);
+  options.set_output_score_tensor_index(output_score_tensor_index);
+  options.set_output_label_tensor_index(output_label_tensor_index);
+
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      model_path);
+
+  return options;
+}
+
+std::vector<ProtoOptionsTestParam> ClassifyParams() {
+  return {
+      {
+          .description = "FindTensorByNameQuantizeOutputUseTensorLabel",
+          .options = CreateProtoOptionsFromTensorName(
+              kDefaultInputTensorName, kOutputQuantizedTensorName,
+              kOutputLabelTensorName, GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByNameQuantizeOutputUseIndexLabel",
+          .options = CreateProtoOptionsFromTensorName(
+              kDefaultInputTensorName, kOutputQuantizedTensorName,
+              kDefaultOutputLabelTensorName,
+              GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByNameDequantizeOutputUseTensorLabel",
+          .options = CreateProtoOptionsFromTensorName(
+              kDefaultInputTensorName, kOutputDequantizedTensorName,
+              kOutputLabelTensorName, GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByNameDequantizeOutputUseIndexLabel",
+          .options = CreateProtoOptionsFromTensorName(
+              kDefaultInputTensorName, kOutputDequantizedTensorName,
+              kDefaultOutputLabelTensorName,
+              GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description =
+              "FindTensorByNameDequantizeFloat64OutputUseTensorLabel",
+          .options = CreateProtoOptionsFromTensorName(
+              kDefaultInputTensorName, kOutputDequantizedTensorFloat64Name,
+              kOutputLabelTensorName, GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByNameDequantizeFloat64OutputUseIndexLabel",
+          .options = CreateProtoOptionsFromTensorName(
+              kDefaultInputTensorName, kOutputDequantizedTensorFloat64Name,
+              kDefaultOutputLabelTensorName,
+              GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByIndexQuantizeOutputUseTensorLabel",
+          .options = CreateProtoOptionsFromTensorIndex(
+              kDefaultInputTensorIndex, kOutputQuantizedTensorIndex,
+              kOutputLabelTensorIndex, GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByIndexQuantizeOutputUseIndexLabel",
+          .options = CreateProtoOptionsFromTensorIndex(
+              kDefaultInputTensorIndex, kOutputQuantizedTensorIndex,
+              kDefaultOutputLabelTensorIndex,
+              GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByIndexDequantizeOutputUseTensorLabel",
+          .options = CreateProtoOptionsFromTensorIndex(
+              kDefaultInputTensorIndex, kOutputDequantizedTensorIndex,
+              kOutputLabelTensorIndex, GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description = "FindTensorByIndexDequantizeOutputUseIndexLabel",
+          .options = CreateProtoOptionsFromTensorIndex(
+              kDefaultInputTensorIndex, kOutputDequantizedTensorIndex,
+              kDefaultOutputLabelTensorIndex,
+              GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description =
+              "FindTensorByIndexDequantizeFloat64OutputUseTensorLabel",
+          .options = CreateProtoOptionsFromTensorIndex(
+              kDefaultInputTensorIndex, kOutputDequantizedTensorFloat64Index,
+              kOutputLabelTensorIndex, GetFullPath(kTestModelPath).c_str()),
+      },
+      {
+          .description =
+              "FindTensorByIndexDequantizeFloat64OutputUseIndexLabel",
+          .options = CreateProtoOptionsFromTensorIndex(
+              kDefaultInputTensorIndex, kOutputDequantizedTensorFloat64Index,
+              kDefaultOutputLabelTensorIndex,
+              GetFullPath(kTestModelPath).c_str()),
+      },
+  };
+}
+
+TEST_P(ProtoOptionsTest, TestClassify) {
+  NLClassifierProtoOptions options = GetParam().options;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<NLClassifier> classifier,
+      NLClassifier::CreateFromOptions(options, CreateCustomResolver()));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+
+  bool assert_label_name =
+      options.output_label_tensor_index() == kOutputLabelTensorIndex ||
+      options.output_label_tensor_name() == kOutputLabelTensorName;
+
+  std::vector<core::Category> expected_class;
+  if (assert_label_name) {
+    expected_class = {
+        {"label0", 255},
+        {"label1", 510},
+        {"label2", 765},
+    };
+  } else {
+    expected_class = {
+        {"0", 255},
+        {"1", 510},
+        {"2", 765},
+    };
+  }
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+INSTANTIATE_TEST_SUITE_P(TestClassify,
+                         ProtoOptionsTest,
+                         ValuesIn(ClassifyParams()),
+                         ProtoOptionsTestParamToString());
+
+// Tests for struct sNLClassifierOptions.
+class StructOptionsTest : public tflite_shims::testing::Test {};
+
+void AssertStatus(absl::Status status,
+                  absl::StatusCode status_code,
+                  TfLiteSupportStatus tfls_code) {
+  ASSERT_EQ(status.code(), status_code);
+  EXPECT_THAT(status.GetPayload(kTfLiteSupportPayload),
+              testing::Optional(absl::Cord(absl::StrCat(tfls_code))));
+}
+
+TEST_F(StructOptionsTest, TestApiCreationFromBuffer) {
+  std::string model_buffer = LoadBinaryContent(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath)
+          .c_str());
+  SUPPORT_ASSERT_OK(NLClassifier::CreateFromBufferAndOptions(
+      model_buffer.data(), model_buffer.size(), {}, CreateCustomResolver()));
+}
+
+TEST_F(StructOptionsTest, TestApiCreationFromFile) {
+  SUPPORT_ASSERT_OK(NLClassifier::CreateFromFileAndOptions(
+      GetFullPath(kTestModelPath), {}, CreateCustomResolver()));
+}
+
+TEST_F(StructOptionsTest, TestApiCreationFromIncorrectInputTensor) {
+  NLClassifierOptions options;
+  options.input_tensor_index = -1;
+  options.input_tensor_name = "I do not exist";
+  AssertStatus(
+      NLClassifier::CreateFromFileAndOptions(
+          JoinPath("./" /*test src dir*/, kTestDataDirectory, kTestModelPath),
+          options, CreateCustomResolver())
+          .status(),
+      absl::StatusCode::kInvalidArgument,
+      TfLiteSupportStatus::kInputTensorNotFoundError);
+}
+
+TEST_F(StructOptionsTest, TestApiCreationFromIncorrectOutputScoreTensor) {
+  NLClassifierOptions options;
+  options.output_score_tensor_index = 123;
+
+  AssertStatus(NLClassifier::CreateFromFileAndOptions(
+                   GetFullPath(kTestModelPath), options, CreateCustomResolver())
+                   .status(),
+               absl::StatusCode::kInvalidArgument,
+               TfLiteSupportStatus::kOutputTensorNotFoundError);
+}
+
+TEST_F(StructOptionsTest, TestInferenceWithRegexTokenizer) {
+  NLClassifierOptions options;
+  options.input_tensor_name = "input_text";
+  options.output_score_tensor_name = "probability";
+
+  // The model with regex tokenizer doesn't need any custom ops.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<NLClassifier> classifier,
+      NLClassifier::CreateFromFileAndOptions(
+          GetFullPath(kTestModelWithRegexTokenizer), options));
+
+  std::vector<core::Category> positive_results =
+      classifier->Classify(kPositiveInput);
+
+  EXPECT_THAT(positive_results,
+              UnorderedElementsAreArray(GetExpectedResultsOfPositiveInput()));
+
+  std::vector<core::Category> negative_results =
+      classifier->Classify(kNegativeInput);
+  EXPECT_THAT(negative_results,
+              UnorderedElementsAreArray(GetExpectedResultsOfNegativeInput()));
+}
+
+TEST_F(StructOptionsTest, TestInferenceWithBoolOutput) {
+  NLClassifierOptions options;
+  options.input_tensor_index = 0;
+  options.output_score_tensor_index = 0;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<NLClassifier> classifier,
+                               NLClassifier::CreateFromFileAndOptions(
+                                   GetFullPath(kTestModelBoolOutputPath),
+                                   options, CreateCustomResolver()));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+  std::vector<core::Category> expected_class = {
+      {"0", 1},
+      {"1", 1},
+      {"2", 0},
+  };
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+TEST_F(StructOptionsTest, TestInferenceWithAssociatedLabelCustomOps) {
+  NLClassifierOptions options;
+  options.output_score_tensor_name = kMetadataOutputScoreTensorName;
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<NLClassifier> classifier,
+      NLClassifier::CreateFromFileAndOptions(
+          GetFullPath(kTestModelWithLabelCustomOpsPath), options,
+          CreateCustomResolver()));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+  std::vector<core::Category> expected_class = {
+      {"label0", 255},
+      {"label1", 510},
+      {"label2", 765},
+  };
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+TEST_F(StructOptionsTest, TestInferenceWithAssociatedLabelBuiltinOps) {
+  NLClassifierOptions options;
+  options.input_tensor_index = 0;
+  options.output_score_tensor_index = 0;
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<NLClassifier> classifier,
+      NLClassifier::CreateFromFileAndOptions(
+          GetFullPath(kTestModelWithLabelBuiltInOpsPath), options));
+  std::vector<core::Category> results = classifier->Classify(kInputStr);
+  std::vector<core::Category> expected_class = {
+      {"Negative", 0.49332118034362793},
+      {"Positive", 0.50667881965637207},
+  };
+
+  EXPECT_THAT(results, UnorderedElementsAreArray(expected_class));
+}
+
+}  // namespace
+}  // namespace nlclassifier
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.cc
new file mode 100644
index 0000000..92835a9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.cc
@@ -0,0 +1,197 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.h"
+
+#include "tensorflow/lite/kernels/builtin_op_kernels.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/string_util.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+
+namespace tflite {
+namespace ops {
+namespace custom {
+
+constexpr char kInputStr[] = "hello";
+
+namespace string_floats {
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  TfLiteIntArray* dims = TfLiteIntArrayCreate(1);
+  dims->data[0] = 3;  // Size of 'data' in Invoke()
+  return context->ResizeTensor(context, output, dims);
+}
+
+TfLiteStatus Invoke(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input_tensor = GetInput(context, node, 0);
+  TF_LITE_ENSURE(context, input_tensor != nullptr);
+  StringRef input_str_ref = GetString(input_tensor, 0);
+  std::string input_str(input_str_ref.str, input_str_ref.len);
+  if (input_str != kInputStr) {
+    return kTfLiteError;
+  }
+  std::vector<float> data = {255, 510, 765};
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  // Default Quantize OP scale is 255, will be quantized to {1, 2, 3}
+  TF_LITE_ENSURE(context,
+                 tflite::task::core::PopulateTensor(data, output).ok());
+  return kTfLiteOk;
+}
+
+// This custom op takes a string tensor in and outputs a float32 tensor with
+// value{0.1, 0.2, 0.3}, it's used to mimic a real text classification model
+// which classifies a string into scores of different categories.
+TfLiteRegistration* Register() {
+  // Dummy implementation of custom OP
+  // This op takes string as input and outputs float[]
+  static TfLiteRegistration r = {
+      .init = nullptr, .free = nullptr, .prepare = Prepare, .invoke = Invoke};
+  return &r;
+}
+};  // namespace string_floats
+
+namespace string_doubles {
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  TfLiteIntArray* dims = TfLiteIntArrayCreate(1);
+  dims->data[0] = 3;  // Size of 'data' in Invoke()
+  return context->ResizeTensor(context, output, dims);
+}
+
+TfLiteStatus Invoke(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input_tensor = GetInput(context, node, 0);
+  TF_LITE_ENSURE(context, input_tensor != nullptr);
+  StringRef input_str_ref = GetString(input_tensor, 0);
+  std::string input_str(input_str_ref.str, input_str_ref.len);
+  if (input_str != kInputStr) {
+    return kTfLiteError;
+  }
+  std::vector<double> data = {255, 510, 765};
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  // Default Quantize OP scale is 255, will be quantized to {1, 2, 3}
+  TF_LITE_ENSURE(context,
+                 tflite::task::core::PopulateTensor(data, output).ok());
+  return kTfLiteOk;
+}
+
+// This custom op takes a string tensor in and outputs a float64 tensor with
+// value{0.1, 0.2, 0.3}, it's used to mimic a real text classification model
+// which classifies a string into scores of different categories.
+TfLiteRegistration* Register() {
+  // Dummy implementation of custom OP
+  // This op takes string as input and outputs double[]
+  static TfLiteRegistration r = {
+      .init = nullptr, .free = nullptr, .prepare = Prepare, .invoke = Invoke};
+  return &r;
+}
+};  // namespace string_doubles
+
+namespace string_bools {
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  TfLiteIntArray* dims = TfLiteIntArrayCreate(1);
+  dims->data[0] = 3;  // Size of 'data' in Invoke()
+  return context->ResizeTensor(context, output, dims);
+}
+
+TfLiteStatus Invoke(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input_tensor = GetInput(context, node, 0);
+  TF_LITE_ENSURE(context, input_tensor != nullptr);
+  StringRef input_str_ref = GetString(input_tensor, 0);
+  std::string input_str(input_str_ref.str, input_str_ref.len);
+  if (input_str != kInputStr) {
+    return kTfLiteError;
+  }
+  bool data[] = {true, true, false};
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  TF_LITE_ENSURE(context,
+                 tflite::task::core::PopulateTensor(data, 3, output).ok());
+  return kTfLiteOk;
+}
+
+// This custom op takes a string tensor in and outputs a bool tensor with
+// value{true, true, false}, it's used to mimic a real text classification model
+// which classifies a string into scores of different categories.
+TfLiteRegistration* Register() {
+  // Dummy implementation of custom OP
+  // This op takes string as input and outputs bool[]
+  static TfLiteRegistration r = {
+      .init = nullptr, .free = nullptr, .prepare = Prepare, .invoke = Invoke};
+  return &r;
+}
+};  // namespace string_bools
+
+TfLiteStatus GenerateLabelsInvoke(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input_tensor = GetInput(context, node, 0);
+  TF_LITE_ENSURE(context, input_tensor != nullptr);
+  StringRef input_str_ref = GetString(input_tensor, 0);
+  std::string input_str(input_str_ref.str, input_str_ref.len);
+  if (input_str != kInputStr) {
+    return kTfLiteError;
+  }
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE(context, output != nullptr);
+  std::vector<std::string> data = {"label0", "label1", "label2"};
+  TF_LITE_ENSURE(context,
+                 tflite::task::core::PopulateTensor(data, output).ok());
+  return kTfLiteOk;
+}
+
+// This custom op takes a string tensor in and outputs a string tensor with
+// value{"label0", "label1", "label2"}, it's used to mimic a real text
+// classification model that stores Class names inside a tensor.
+TfLiteRegistration* Register_CUSTOM_OP_GENERATE_LABELS() {
+  static TfLiteRegistration r = {.init = nullptr,
+                                 .free = nullptr,
+                                 .prepare = nullptr,
+                                 .invoke = GenerateLabelsInvoke};
+  return &r;
+}
+
+}  // namespace custom
+}  // namespace ops
+}  // namespace tflite
+
+namespace tflite {
+namespace task {
+namespace text {
+namespace nlclassifier {
+
+std::unique_ptr<MutableOpResolver> CreateCustomResolver() {
+  MutableOpResolver resolver;
+  resolver.AddBuiltin(::tflite::BuiltinOperator_QUANTIZE,
+                      ::tflite::ops::builtin::Register_QUANTIZE());
+  resolver.AddCustom("CUSTOM_OP_STRING_TO_FLOATS",
+                     ::tflite::ops::custom::string_floats::Register());
+  resolver.AddCustom("CUSTOM_OP_STRING_TO_DOUBLES",
+                     ::tflite::ops::custom::string_doubles::Register());
+  resolver.AddCustom("CUSTOM_OP_STRING_TO_BOOLS",
+                     ::tflite::ops::custom::string_bools::Register());
+  resolver.AddCustom(
+      "CUSTOM_OP_GENERATE_LABELS",
+      ::tflite::ops::custom::Register_CUSTOM_OP_GENERATE_LABELS());
+  return absl::make_unique<MutableOpResolver>(resolver);
+}
+
+}  // namespace nlclassifier
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.h
new file mode 100644
index 0000000..b3c2501
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/text/nlclassifier/nl_classifier_test_utils.h
@@ -0,0 +1,37 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TEST_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_TEST_UTILS_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TEST_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_TEST_UTILS_H_
+
+#include <memory>
+
+#include "tensorflow/lite/op_resolver.h"
+
+namespace tflite {
+namespace task {
+namespace text {
+namespace nlclassifier {
+
+// Create a custom MutableOpResolver to provide custom OP implementations to
+// mimic classification behavior.
+std::unique_ptr<MutableOpResolver> CreateCustomResolver();
+
+}  // namespace nlclassifier
+}  // namespace text
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TEST_TASK_TEXT_NLCLASSIFIER_NL_CLASSIFIER_TEST_UTILS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/BUILD
new file mode 100644
index 0000000..24a4b9108
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/BUILD
@@ -0,0 +1,175 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_test_with_tflite",
+)
+
+package(
+    default_visibility = [
+        "//visibility:private",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_test_with_tflite(
+    name = "image_classifier_test",
+    srcs = ["image_classifier_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision:image_classifier",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_classifier_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:cord",
+        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+    ],
+)
+
+# To test it with Bazel, plugin a Coral device, and run the following command:
+# bazel test tensorflow_lite_support/cc/test/task/vision:image_classifier_coral_test \
+# --define darwinn_portable=1
+cc_test(
+    name = "image_classifier_coral_test",
+    srcs = ["image_classifier_coral_test.cc"],
+    data = [
+        "//tensorflow_lite_support/acceleration/configuration/testdata:test_files",
+    ],
+    tags = [
+        "manual",
+        "notap",  # Requires edge TPU device.
+    ],
+    deps = [
+        "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        "//tensorflow_lite_support/cc/port:configuration_proto_inc",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/vision:image_classifier",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_classifier_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_absl//absl/status",
+    ],
+)
+
+cc_test_with_tflite(
+    name = "object_detector_test",
+    srcs = ["object_detector_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision:object_detector",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:detections_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:object_detector_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:cord",
+        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+    ],
+)
+
+cc_test_with_tflite(
+    name = "image_segmenter_test",
+    srcs = ["image_segmenter_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+        "//tensorflow_lite_support/cc/task/core:task_api_factory",
+        "//tensorflow_lite_support/cc/task/core:tflite_engine",
+        "//tensorflow_lite_support/cc/task/vision:image_segmenter",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/core:task_utils",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_segmenter_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:segmentations_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:cord",
+        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+    ],
+)
+
+cc_test_with_tflite(
+    name = "image_embedder_test",
+    srcs = ["image_embedder_test.cc"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/vision:image_embedder",
+        "@org_tensorflow//tensorflow/lite/core/shims:cc_shims_test_util",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:gtest_main",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:embeddings_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_embedder_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_utils",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/status",
+        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/c:common",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_coral_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_coral_test.cc
new file mode 100644
index 0000000..7e6a311a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_coral_test.cc
@@ -0,0 +1,53 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <memory>
+
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/image_classifier.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+namespace {
+
+using ::tflite::support::StatusOr;
+
+constexpr char kEdgeTpuModelFilePath[] =
+    "tensorflow_lite_support/acceleration/configuration/testdata/"
+    "mobilenet_v1_1.0_224_quant_edgetpu.tflite";
+constexpr char kRegularModelFilePath[] =
+    "tensorflow_lite_support/acceleration/configuration/testdata/"
+    "mobilenet_v1_1.0_224_quant.tflite";
+constexpr char kImagePath[] =
+    "tensorflow_lite_support/acceleration/configuration/testdata/"
+    "burger.jpg";
+
+using ClassifyTest = testing::TestWithParam<std::string>;
+
+}  // namespace
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc
new file mode 100644
index 0000000..ae4e48c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_classifier_test.cc
@@ -0,0 +1,666 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/vision/image_classifier.h"
+
+#include <memory>
+
+#include "absl/flags/flag.h"     // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/strings/cord.h"   // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow/lite/kernels/builtin_op_kernels.h"
+#include "tensorflow/lite/mutable_op_resolver.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_classifier_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+namespace {
+
+using ::testing::ElementsAreArray;
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::JoinPath;
+using ::tflite::task::ParseTextProtoOrDie;
+using ::tflite::task::core::PopulateTensor;
+using ::tflite::task::core::TaskAPIFactory;
+using ::tflite::task::core::TfLiteEngine;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "vision/";
+// Float model.
+constexpr char kMobileNetFloatWithMetadata[] = "mobilenet_v2_1.0_224.tflite";
+// Quantized model.
+constexpr char kMobileNetQuantizedWithMetadata[] =
+    "mobilenet_v1_0.25_224_quant.tflite";
+// Hello world flowers classifier supporting 5 classes (quantized model).
+constexpr char kAutoMLModelWithMetadata[] = "automl_labeler_model.tflite";
+
+StatusOr<ImageData> LoadImage(std::string image_name) {
+  return DecodeImageFromFile(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+}
+
+// If the proto definition changes, please also change this function.
+void ExpectApproximatelyEqual(const ClassificationResult& actual,
+                              const ClassificationResult& expected) {
+  const float kPrecision = 1e-6;
+  EXPECT_EQ(actual.classifications_size(), expected.classifications_size());
+  for (int i = 0; i < actual.classifications_size(); ++i) {
+    const Classifications& a = actual.classifications(i);
+    const Classifications& b = expected.classifications(i);
+    EXPECT_EQ(a.head_index(), b.head_index());
+    EXPECT_EQ(a.classes_size(), b.classes_size());
+    for (int j = 0; j < a.classes_size(); ++j) {
+      EXPECT_EQ(a.classes(j).index(), b.classes(j).index());
+      EXPECT_EQ(a.classes(j).class_name(), b.classes(j).class_name());
+      EXPECT_EQ(a.classes(j).display_name(), b.classes(j).display_name());
+      EXPECT_NEAR(a.classes(j).score(), b.classes(j).score(), kPrecision);
+    }
+  }
+}
+
+class MobileNetQuantizedOpResolver : public ::tflite::MutableOpResolver {
+ public:
+  MobileNetQuantizedOpResolver() {
+    AddBuiltin(::tflite::BuiltinOperator_AVERAGE_POOL_2D,
+               ::tflite::ops::builtin::Register_AVERAGE_POOL_2D());
+    AddBuiltin(::tflite::BuiltinOperator_CONV_2D,
+               ::tflite::ops::builtin::Register_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+               ::tflite::ops::builtin::Register_DEPTHWISE_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_RESHAPE,
+               ::tflite::ops::builtin::Register_RESHAPE());
+    AddBuiltin(::tflite::BuiltinOperator_SOFTMAX,
+               ::tflite::ops::builtin::Register_SOFTMAX());
+  }
+
+  MobileNetQuantizedOpResolver(const MobileNetQuantizedOpResolver& r) = delete;
+};
+
+class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+
+TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+  ImageClassifierOptions options;
+  options.set_max_results(3);
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileNetQuantizedWithMetadata));
+
+  SUPPORT_ASSERT_OK(ImageClassifier::CreateFromOptions(
+      options, absl::make_unique<MobileNetQuantizedOpResolver>()));
+}
+
+class MobileNetQuantizedOpResolverMissingOps
+    : public ::tflite::MutableOpResolver {
+ public:
+  MobileNetQuantizedOpResolverMissingOps() {
+    AddBuiltin(::tflite::BuiltinOperator_SOFTMAX,
+               ::tflite::ops::builtin::Register_SOFTMAX());
+  }
+
+  MobileNetQuantizedOpResolverMissingOps(
+      const MobileNetQuantizedOpResolverMissingOps& r) = delete;
+};
+
+TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+  ImageClassifierOptions options;
+  options.set_max_results(3);
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileNetQuantizedWithMetadata));
+
+  auto image_classifier_or = ImageClassifier::CreateFromOptions(
+      options, absl::make_unique<MobileNetQuantizedOpResolverMissingOps>());
+  EXPECT_EQ(image_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_classifier_or.status().message(),
+              HasSubstr("Didn't find op for builtin opcode"));
+  EXPECT_THAT(image_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kUnsupportedBuiltinOp))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithTwoModelSources) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileNetQuantizedWithMetadata));
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+
+  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+      ImageClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(image_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_classifier_or.status().message(),
+              HasSubstr("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 2."));
+  EXPECT_THAT(image_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithMissingModel) {
+  ImageClassifierOptions options;
+
+  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+      ImageClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(image_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_classifier_or.status().message(),
+              HasSubstr("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 0."));
+  EXPECT_THAT(image_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithInvalidMaxResults) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileNetQuantizedWithMetadata));
+  options.set_max_results(0);
+
+  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+      ImageClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(image_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_classifier_or.status().message(),
+              HasSubstr("Invalid `max_results` option"));
+  EXPECT_THAT(image_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithCombinedWhitelistAndBlacklist) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileNetQuantizedWithMetadata));
+  options.add_class_name_whitelist("foo");
+  options.add_class_name_blacklist("bar");
+
+  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+      ImageClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(image_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_classifier_or.status().message(),
+              HasSubstr("mutually exclusive options"));
+  EXPECT_THAT(image_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, SucceedsWithNumberOfThreads) {
+  ImageClassifierOptions options;
+  options.set_num_threads(4);
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+
+  SUPPORT_ASSERT_OK(ImageClassifier::CreateFromOptions(options));
+}
+
+using NumThreadsTest = testing::TestWithParam<int>;
+
+INSTANTIATE_TEST_SUITE_P(Default, NumThreadsTest, testing::Values(0, -2));
+
+TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+  ImageClassifierOptions options;
+  options.set_num_threads(GetParam());
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+
+  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+      ImageClassifier::CreateFromOptions(options);
+
+  EXPECT_EQ(image_classifier_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_classifier_or.status().message(),
+              HasSubstr("`num_threads` must be greater than "
+                        "0 or equal to -1"));
+  EXPECT_THAT(image_classifier_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST(ClassifyTest, SucceedsWithFloatModel) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ImageClassifierOptions options;
+  options.set_max_results(3);
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  StatusOr<ClassificationResult> result_or =
+      image_classifier->Classify(*frame_buffer);
+  ImageDataFree(&rgb_image);
+  SUPPORT_ASSERT_OK(result_or);
+
+  const ClassificationResult& result = result_or.value();
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes {
+                   index: 934
+                   score: 0.7399742
+                   class_name: "cheeseburger"
+                 }
+                 classes {
+                   index: 925
+                   score: 0.026928535
+                   class_name: "guacamole"
+                 }
+                 classes { index: 932 score: 0.025737215 class_name: "bagel" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+TEST(ClassifyTest, SucceedsWithRegionOfInterest) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+                               LoadImage("multi_objects.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ImageClassifierOptions options;
+  options.set_max_results(1);
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  // Crop around the soccer ball.
+  BoundingBox roi;
+  roi.set_origin_x(406);
+  roi.set_origin_y(110);
+  roi.set_width(148);
+  roi.set_height(153);
+
+  StatusOr<ClassificationResult> result_or =
+      image_classifier->Classify(*frame_buffer, roi);
+  ImageDataFree(&rgb_image);
+  SUPPORT_ASSERT_OK(result_or);
+
+  const ClassificationResult& result = result_or.value();
+  ExpectApproximatelyEqual(result, ParseTextProtoOrDie<ClassificationResult>(
+                                       R"pb(classifications {
+                                              classes {
+                                                index: 806
+                                                score: 0.99673367
+                                                class_name: "soccer ball"
+                                              }
+                                              head_index: 0
+                                            }
+                                       )pb"));
+}
+
+TEST(ClassifyTest, SucceedsWithQuantizedModel) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ImageClassifierOptions options;
+  options.set_max_results(3);
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileNetQuantizedWithMetadata));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  StatusOr<ClassificationResult> result_or =
+      image_classifier->Classify(*frame_buffer);
+  ImageDataFree(&rgb_image);
+  SUPPORT_ASSERT_OK(result_or);
+
+  const ClassificationResult& result = result_or.value();
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes {
+                   index: 934
+                   score: 0.96484375
+                   class_name: "cheeseburger"
+                 }
+                 classes { index: 948 score: 0.0078125 class_name: "mushroom" }
+                 classes { index: 924 score: 0.00390625 class_name: "plate" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+TEST(ClassifyTest, SucceedsWithBaseOptions) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ImageClassifierOptions options;
+  options.set_max_results(3);
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  StatusOr<ClassificationResult> result_or =
+      image_classifier->Classify(*frame_buffer);
+  ImageDataFree(&rgb_image);
+  SUPPORT_ASSERT_OK(result_or);
+
+  const ClassificationResult& result = result_or.value();
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes {
+                   index: 934
+                   score: 0.7399742
+                   class_name: "cheeseburger"
+                 }
+                 classes {
+                   index: 925
+                   score: 0.026928535
+                   class_name: "guacamole"
+                 }
+                 classes { index: 932 score: 0.025737215 class_name: "bagel" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+TEST(ClassifyTest, GetInputCountSucceeds) {
+  ImageClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  int32_t input_count = image_classifier->GetInputCount();
+  EXPECT_THAT(input_count, 1);
+}
+
+TEST(ClassifyTest, GetInputShapeSucceeds) {
+  ImageClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  // Verify the shape array size.
+  const TfLiteIntArray* input_shape_0 = image_classifier->GetInputShape(0);
+  EXPECT_THAT(input_shape_0->size, 4);
+
+  // Verify the shape array data.
+  auto shape_data = input_shape_0->data;
+  std::vector<int> shape_vector(shape_data, shape_data + input_shape_0->size);
+  EXPECT_THAT(shape_vector, ElementsAreArray({1, 224, 224, 3}));
+}
+
+TEST(ClassifyTest, GetOutputCountSucceeds) {
+  ImageClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  int32_t output_count = image_classifier->GetOutputCount();
+  EXPECT_THAT(output_count, 1);
+}
+
+TEST(ClassifyTest, GetOutputShapeSucceeds) {
+  ImageClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileNetFloatWithMetadata));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<ImageClassifier> image_classifier,
+      ImageClassifier::CreateFromOptions(options));
+
+  // Verify the shape array size.
+  const TfLiteIntArray* output_shape_0 = image_classifier->GetOutputShape(0);
+  EXPECT_THAT(output_shape_0->size, 2);
+
+  // Verify the shape array data.
+  auto shape_data = output_shape_0->data;
+  std::vector<int> shape_vector(shape_data, shape_data + output_shape_0->size);
+  EXPECT_THAT(shape_vector, ElementsAreArray({1, 1001}));
+}
+
+class PostprocessTest : public tflite_shims::testing::Test {
+ public:
+  class TestImageClassifier : public ImageClassifier {
+   public:
+    using ImageClassifier::ImageClassifier;
+    using ImageClassifier::Postprocess;
+
+    static StatusOr<std::unique_ptr<TestImageClassifier>> CreateFromOptions(
+        const ImageClassifierOptions& options) {
+      RETURN_IF_ERROR(SanityCheckOptions(options));
+
+      auto options_copy = absl::make_unique<ImageClassifierOptions>(options);
+
+      ASSIGN_OR_RETURN(
+          auto image_classifier,
+          TaskAPIFactory::CreateFromExternalFileProto<TestImageClassifier>(
+              &options_copy->model_file_with_metadata()));
+
+      RETURN_IF_ERROR(image_classifier->Init(std::move(options_copy)));
+
+      return image_classifier;
+    }
+
+    TfLiteTensor* GetOutputTensor() {
+      if (TfLiteEngine::OutputCount(GetTfLiteEngine()->interpreter()) != 1) {
+        return nullptr;
+      }
+      return TfLiteEngine::GetOutput(GetTfLiteEngine()->interpreter(), 0);
+    }
+  };
+
+ protected:
+  void SetUp() override { tflite_shims::testing::Test::SetUp(); }
+  void SetUp(const ImageClassifierOptions& options) {
+    StatusOr<std::unique_ptr<TestImageClassifier>> test_image_classifier_or =
+        TestImageClassifier::CreateFromOptions(options);
+
+    init_status_ = test_image_classifier_or.status();
+
+    if (init_status_.ok()) {
+      test_image_classifier_ = std::move(test_image_classifier_or).value();
+    }
+
+    dummy_frame_buffer_ = CreateFromRgbRawBuffer(/*input=*/nullptr, {});
+  }
+
+  std::unique_ptr<TestImageClassifier> test_image_classifier_;
+  std::unique_ptr<FrameBuffer> dummy_frame_buffer_;
+  absl::Status init_status_;
+};
+
+TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+  options.set_max_results(3);
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_classifier_ != nullptr) << init_status_;
+
+  TfLiteTensor* output_tensor = test_image_classifier_->GetOutputTensor();
+  ASSERT_NE(output_tensor, nullptr);
+
+  std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                 /*sunflowers*/ 32, /*tulips*/ 128};
+  SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      ClassificationResult result,
+      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
+                                          /*roi=*/{}));
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes { index: 2 score: 0.99609375 class_name: "roses" }
+                 classes { index: 4 score: 0.5 class_name: "tulips" }
+                 classes { index: 1 score: 0.25 class_name: "dandelion" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithScoreThresholdOption) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+  options.set_score_threshold(0.4);
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_classifier_ != nullptr) << init_status_;
+
+  TfLiteTensor* output_tensor = test_image_classifier_->GetOutputTensor();
+  ASSERT_NE(output_tensor, nullptr);
+
+  std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                 /*sunflowers*/ 32, /*tulips*/ 128};
+  SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      ClassificationResult result,
+      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
+                                          /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes { index: 2 score: 0.99609375 class_name: "roses" }
+                 classes { index: 4 score: 0.5 class_name: "tulips" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+  options.add_class_name_whitelist("dandelion");
+  options.add_class_name_whitelist("daisy");
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_classifier_ != nullptr) << init_status_;
+
+  TfLiteTensor* output_tensor = test_image_classifier_->GetOutputTensor();
+  ASSERT_NE(output_tensor, nullptr);
+
+  std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                 /*sunflowers*/ 32, /*tulips*/ 128};
+  SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      ClassificationResult result,
+      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
+                                          /*roi=*/{}));
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes { index: 1 score: 0.25 class_name: "dandelion" }
+                 classes { index: 0 score: 0 class_name: "daisy" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithBlacklistOption) {
+  ImageClassifierOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kAutoMLModelWithMetadata));
+  options.add_class_name_blacklist("dandelion");
+  options.add_class_name_blacklist("daisy");
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_classifier_ != nullptr) << init_status_;
+
+  TfLiteTensor* output_tensor = test_image_classifier_->GetOutputTensor();
+  ASSERT_NE(output_tensor, nullptr);
+
+  std::vector<uint8_t> scores = {/*daisy*/ 0, /*dandelion*/ 64, /*roses*/ 255,
+                                 /*sunflowers*/ 32, /*tulips*/ 128};
+  SUPPORT_ASSERT_OK(PopulateTensor(scores, output_tensor));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      ClassificationResult result,
+      test_image_classifier_->Postprocess({output_tensor}, *dummy_frame_buffer_,
+                                          /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<ClassificationResult>(
+          R"pb(classifications {
+                 classes { index: 2 score: 0.99609375 class_name: "roses" }
+                 classes { index: 4 score: 0.5 class_name: "tulips" }
+                 classes { index: 3 score: 0.125 class_name: "sunflowers" }
+                 head_index: 0
+               }
+          )pb"));
+}
+
+}  // namespace
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc
new file mode 100644
index 0000000..8877f28
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_embedder_test.cc
@@ -0,0 +1,451 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/vision/image_embedder.h"
+
+#include <memory>
+
+#include "absl/flags/flag.h"     // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow/lite/kernels/builtin_op_kernels.h"
+#include "tensorflow/lite/mutable_op_resolver.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/embeddings_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_embedder_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+namespace {
+
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::JoinPath;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "vision/";
+// Test model. Float inputs, produces feature vectors that are not
+// L2-normalized as this model doesn't include a L2_NORMALIZATION TFLite Op.
+constexpr char kMobileNetV3[] = "mobilenet_v3_small_100_224_embedder.tflite";
+// Tolerancy for cosine similarity evaluation.
+constexpr double kSimilarityTolerancy = 1e-6;
+
+StatusOr<ImageData> LoadImage(std::string image_name) {
+  return DecodeImageFromFile(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+}
+
+class MobileNetV3OpResolver : public ::tflite::MutableOpResolver {
+ public:
+  MobileNetV3OpResolver() {
+    AddBuiltin(::tflite::BuiltinOperator_MUL,
+               ::tflite::ops::builtin::Register_MUL());
+    AddBuiltin(::tflite::BuiltinOperator_SUB,
+               ::tflite::ops::builtin::Register_SUB());
+    AddBuiltin(::tflite::BuiltinOperator_CONV_2D,
+               ::tflite::ops::builtin::Register_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_HARD_SWISH,
+               ::tflite::ops::builtin::Register_HARD_SWISH());
+    AddBuiltin(::tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+               ::tflite::ops::builtin::Register_DEPTHWISE_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_MEAN,
+               ::tflite::ops::builtin::Register_MEAN());
+    AddBuiltin(::tflite::BuiltinOperator_ADD,
+               ::tflite::ops::builtin::Register_ADD());
+    AddBuiltin(::tflite::BuiltinOperator_AVERAGE_POOL_2D,
+               ::tflite::ops::builtin::Register_AVERAGE_POOL_2D());
+    AddBuiltin(::tflite::BuiltinOperator_RESHAPE,
+               ::tflite::ops::builtin::Register_RESHAPE());
+  }
+
+  MobileNetV3OpResolver(const MobileNetV3OpResolver& r) = delete;
+};
+
+class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+
+TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+
+  SUPPORT_ASSERT_OK(ImageEmbedder::CreateFromOptions(
+      options, absl::make_unique<MobileNetV3OpResolver>()));
+}
+
+class MobileNetV3OpResolverMissingOps : public ::tflite::MutableOpResolver {
+ public:
+  MobileNetV3OpResolverMissingOps() {
+    AddBuiltin(::tflite::BuiltinOperator_SOFTMAX,
+               ::tflite::ops::builtin::Register_SOFTMAX());
+  }
+
+  MobileNetV3OpResolverMissingOps(const MobileNetV3OpResolverMissingOps& r) =
+      delete;
+};
+
+TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+
+  auto image_embedder_or = ImageEmbedder::CreateFromOptions(
+      options, absl::make_unique<MobileNetV3OpResolverMissingOps>());
+  EXPECT_EQ(image_embedder_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_embedder_or.status().message(),
+              HasSubstr("Didn't find op for builtin opcode"));
+  EXPECT_THAT(image_embedder_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kUnsupportedBuiltinOp))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithMissingModel) {
+  ImageEmbedderOptions options;
+
+  StatusOr<std::unique_ptr<ImageEmbedder>> image_embedder_or =
+      ImageEmbedder::CreateFromOptions(options);
+
+  EXPECT_EQ(image_embedder_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_embedder_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+// Checks that CosineSimilarity fails if provided with a quantized and a float
+// feature vector.
+TEST(CosineSimilarityTest, FailsWithDifferentFeatureVectorTypes) {
+  FeatureVector u;
+  *u.mutable_value_string() = "\x01\x02";
+  FeatureVector v;
+  v.add_value_float(0.1);
+  v.add_value_float(0.2);
+
+  StatusOr<double> uv_similarity_or = ImageEmbedder::CosineSimilarity(u, v);
+
+  EXPECT_EQ(uv_similarity_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(uv_similarity_or.status().message(),
+              HasSubstr("quantized and float"));
+}
+
+// Checks that CosineSimilarity fails if provided with feature vectors of
+// different sizes.
+TEST(CosineSimilarityTest, FailsWithDifferentFeatureVectorSizes) {
+  FeatureVector u_float;
+  u_float.add_value_float(0.1);
+  FeatureVector v_float;
+  v_float.add_value_float(0.1);
+  v_float.add_value_float(0.2);
+  FeatureVector u_quantized;
+  *u_quantized.mutable_value_string() = "\x01";
+  FeatureVector v_quantized;
+  *v_quantized.mutable_value_string() = "\x01\x02";
+
+  StatusOr<double> float_similarity_or =
+      ImageEmbedder::CosineSimilarity(u_float, v_float);
+  StatusOr<double> quantized_similarity_or =
+      ImageEmbedder::CosineSimilarity(u_quantized, v_quantized);
+
+  EXPECT_EQ(float_similarity_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(float_similarity_or.status().message(),
+              HasSubstr("different sizes"));
+  EXPECT_EQ(quantized_similarity_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(quantized_similarity_or.status().message(),
+              HasSubstr("different sizes"));
+}
+
+// Checks that CosineSimilarity fails if one of the feature vectors has 0 norm.
+TEST(CosineSimilarityTest, FailsWithZeroNorm) {
+  FeatureVector u_float;
+  u_float.add_value_float(0.0);
+  u_float.add_value_float(0.0);
+  FeatureVector v_float;
+  v_float.add_value_float(0.1);
+  v_float.add_value_float(0.2);
+  FeatureVector u_quantized;
+  // Prevent literal from being interpreted as null-terminated C-style string.
+  *u_quantized.mutable_value_string() = std::string("\x00\x00", 2);
+  FeatureVector v_quantized;
+  *v_quantized.mutable_value_string() = "\x01\x02";
+
+  StatusOr<double> float_similarity_or =
+      ImageEmbedder::CosineSimilarity(u_float, v_float);
+  StatusOr<double> quantized_similarity_or =
+      ImageEmbedder::CosineSimilarity(u_quantized, v_quantized);
+
+  EXPECT_EQ(float_similarity_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(float_similarity_or.status().message(), HasSubstr("0 norm"));
+  EXPECT_EQ(quantized_similarity_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(quantized_similarity_or.status().message(), HasSubstr("0 norm"));
+}
+
+// Checks that CosineSimilarity produces expected results.
+TEST(CosineSimilarityTest, Succeeds) {
+  FeatureVector u_float;
+  u_float.add_value_float(1.0);
+  u_float.add_value_float(0.0);
+  u_float.add_value_float(0.0);
+  u_float.add_value_float(0.0);
+  FeatureVector v_float;
+  v_float.add_value_float(0.5);
+  v_float.add_value_float(0.5);
+  v_float.add_value_float(0.5);
+  v_float.add_value_float(0.5);
+  FeatureVector u_quantized;
+  // Prevent literal from being interpreted as null-terminated C-style string.
+  *u_quantized.mutable_value_string() = std::string("\x7f\x00\x00\x00", 4);
+  FeatureVector v_quantized;
+  // Prevent literal from being interpreted as null-terminated C-style string.
+  *v_quantized.mutable_value_string() = std::string("\x80\x00\x00\x00", 4);
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      double float_similarity,
+      ImageEmbedder::CosineSimilarity(u_float, v_float));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      double quantized_similarity,
+      ImageEmbedder::CosineSimilarity(u_quantized, v_quantized));
+
+  EXPECT_EQ(float_similarity, 0.5);
+  EXPECT_EQ(quantized_similarity, -1.0);
+}
+
+// Extracts feature vectors without L2 normalization on two image (one being
+// slightly cropped from the other) and checks that cosine similarity is high.
+TEST(EmbedTest, SucceedsWithoutL2Normalization) {
+  // Create embedder.
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+                               ImageEmbedder::CreateFromOptions(options));
+  // Load images: one is a crop of the other.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+      image.pixel_data, FrameBuffer::Dimension{image.width, image.height});
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData crop, LoadImage("burger_crop.jpg"));
+  std::unique_ptr<FrameBuffer> crop_frame_buffer = CreateFromRgbRawBuffer(
+      crop.pixel_data, FrameBuffer::Dimension{crop.width, crop.height});
+
+  // Extract both embeddings.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+                               embedder->Embed(*image_frame_buffer));
+  ImageDataFree(&image);
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+                               embedder->Embed(*crop_frame_buffer));
+  ImageDataFree(&crop);
+
+  // Check results sizes
+  EXPECT_EQ(image_result.embeddings_size(), 1);
+  const FeatureVector& image_feature_vector =
+      image_result.embeddings(0).feature_vector();
+  EXPECT_EQ(image_feature_vector.value_float_size(), 1024);
+  EXPECT_EQ(crop_result.embeddings_size(), 1);
+  const FeatureVector& crop_feature_vector =
+      crop_result.embeddings(0).feature_vector();
+  EXPECT_EQ(crop_feature_vector.value_float_size(), 1024);
+  // Check cosine similarity.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
+                                                         crop_feature_vector));
+  double expected_similarity = 0.932738;
+  EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+}
+
+// Same as above, but with `l2_normalize` option set to true.
+TEST(EmbedTest, SucceedsWithL2Normalization) {
+  // Create embedder.
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+  options.set_l2_normalize(true);
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+                               ImageEmbedder::CreateFromOptions(options));
+  // Load images: one is a crop of the other.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+      image.pixel_data, FrameBuffer::Dimension{image.width, image.height});
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData crop, LoadImage("burger_crop.jpg"));
+  std::unique_ptr<FrameBuffer> crop_frame_buffer = CreateFromRgbRawBuffer(
+      crop.pixel_data, FrameBuffer::Dimension{crop.width, crop.height});
+
+  // Extract both embeddings.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+                               embedder->Embed(*image_frame_buffer));
+  ImageDataFree(&image);
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+                               embedder->Embed(*crop_frame_buffer));
+  ImageDataFree(&crop);
+
+  // Check results sizes
+  EXPECT_EQ(image_result.embeddings_size(), 1);
+  const FeatureVector& image_feature_vector =
+      image_result.embeddings(0).feature_vector();
+  EXPECT_EQ(image_feature_vector.value_float_size(), 1024);
+  EXPECT_EQ(crop_result.embeddings_size(), 1);
+  const FeatureVector& crop_feature_vector =
+      crop_result.embeddings(0).feature_vector();
+  EXPECT_EQ(crop_feature_vector.value_float_size(), 1024);
+  // Check cosine similarity.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
+                                                         crop_feature_vector));
+  double expected_similarity = 0.932738;
+  EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+}
+
+// Same as above, but with `quantize` option set to true. Requires also setting
+// `l2_normalize` to true, as per the documentation.
+// Same as above, but with `l2_normalize` option set to true.
+TEST(EmbedTest, SucceedsWithQuantization) {
+  // Create embedder.
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+  options.set_l2_normalize(true);
+  options.set_quantize(true);
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+                               ImageEmbedder::CreateFromOptions(options));
+  // Load images: one is a crop of the other.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+      image.pixel_data, FrameBuffer::Dimension{image.width, image.height});
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData crop, LoadImage("burger_crop.jpg"));
+  std::unique_ptr<FrameBuffer> crop_frame_buffer = CreateFromRgbRawBuffer(
+      crop.pixel_data, FrameBuffer::Dimension{crop.width, crop.height});
+
+  // Extract both embeddings.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+                               embedder->Embed(*image_frame_buffer));
+  ImageDataFree(&image);
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+                               embedder->Embed(*crop_frame_buffer));
+  ImageDataFree(&crop);
+
+  // Check results sizes
+  EXPECT_EQ(image_result.embeddings_size(), 1);
+  const FeatureVector& image_feature_vector =
+      image_result.embeddings(0).feature_vector();
+  EXPECT_EQ(image_feature_vector.value_string().size(), 1024);
+  EXPECT_EQ(crop_result.embeddings_size(), 1);
+  const FeatureVector& crop_feature_vector =
+      crop_result.embeddings(0).feature_vector();
+  EXPECT_EQ(crop_feature_vector.value_string().size(), 1024);
+  // Check cosine similarity.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
+                                                         crop_feature_vector));
+  // Close to but expectedly different from the above tests due to slight loss
+  // of precision during quantization:
+  double expected_similarity = 0.929717;
+  EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+}
+
+// Extracts feature vectors on both the cropped image and the original image
+// with a region of interest set to correspond to the cropped image, and checks
+// that cosine similarity is close to 1.
+TEST(EmbedTest, SucceedsWithRegionOfInterest) {
+  // Create embedder.
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+                               ImageEmbedder::CreateFromOptions(options));
+  // Load images: one is a crop of the other.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData image, LoadImage("burger.jpg"));
+  std::unique_ptr<FrameBuffer> image_frame_buffer = CreateFromRgbRawBuffer(
+      image.pixel_data, FrameBuffer::Dimension{image.width, image.height});
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData crop, LoadImage("burger_crop.jpg"));
+  std::unique_ptr<FrameBuffer> crop_frame_buffer = CreateFromRgbRawBuffer(
+      crop.pixel_data, FrameBuffer::Dimension{crop.width, crop.height});
+  // Bounding box in "burger.jpg" corresponding to "burger_crop.jpg".
+  BoundingBox roi;
+  roi.set_origin_x(0);
+  roi.set_origin_y(0);
+  roi.set_width(400);
+  roi.set_height(325);
+
+  // Extract both embeddings.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& image_result,
+                               embedder->Embed(*image_frame_buffer, roi));
+  ImageDataFree(&image);
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const EmbeddingResult& crop_result,
+                               embedder->Embed(*crop_frame_buffer));
+  ImageDataFree(&crop);
+
+  // Check results sizes
+  EXPECT_EQ(image_result.embeddings_size(), 1);
+  const FeatureVector& image_feature_vector =
+      image_result.embeddings(0).feature_vector();
+  EXPECT_EQ(image_feature_vector.value_float_size(), 1024);
+  EXPECT_EQ(crop_result.embeddings_size(), 1);
+  const FeatureVector& crop_feature_vector =
+      crop_result.embeddings(0).feature_vector();
+  EXPECT_EQ(crop_feature_vector.value_float_size(), 1024);
+  // Check cosine similarity.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      double similarity, ImageEmbedder::CosineSimilarity(image_feature_vector,
+                                                         crop_feature_vector));
+  double expected_similarity = 0.999914;
+  EXPECT_LE(abs(similarity - expected_similarity), kSimilarityTolerancy);
+}
+
+TEST(GetEmbeddingDimension, Succeeds) {
+  // Create embedder.
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+                               ImageEmbedder::CreateFromOptions(options));
+
+  EXPECT_EQ(embedder->GetEmbeddingDimension(0), 1024);
+  EXPECT_EQ(embedder->GetEmbeddingDimension(1), -1);
+}
+
+TEST(GetNumberOfOutputLayers, Succeeds) {
+  // Create embedder.
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kMobileNetV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageEmbedder> embedder,
+                               ImageEmbedder::CreateFromOptions(options));
+
+  EXPECT_EQ(embedder->GetNumberOfOutputLayers(), 1);
+}
+
+}  // namespace
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc
new file mode 100644
index 0000000..dc768a4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/image_segmenter_test.cc
@@ -0,0 +1,585 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/vision/image_segmenter.h"
+
+#include <memory>
+
+#include "absl/flags/flag.h"     // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/strings/cord.h"   // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow/lite/kernels/builtin_op_kernels.h"
+#include "tensorflow/lite/mutable_op_resolver.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/segmentations_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/test/message_matchers.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+namespace task {
+namespace vision {
+namespace {
+
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::tflite::support::EqualsProto;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::JoinPath;
+using ::tflite::task::core::PopulateTensor;
+using ::tflite::task::core::TaskAPIFactory;
+using ::tflite::task::core::TfLiteEngine;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "vision/";
+constexpr char kDeepLabV3[] = "deeplabv3.tflite";
+
+// All results returned by DeepLabV3 are expected to contain these in addition
+// to the segmentation masks.
+constexpr char kDeepLabV3PartialResult[] =
+    R"(width: 257
+       height: 257
+       colored_labels { r: 0 g: 0 b: 0 class_name: "background" }
+       colored_labels { r: 128 g: 0 b: 0 class_name: "aeroplane" }
+       colored_labels { r: 0 g: 128 b: 0 class_name: "bicycle" }
+       colored_labels { r: 128 g: 128 b: 0 class_name: "bird" }
+       colored_labels { r: 0 g: 0 b: 128 class_name: "boat" }
+       colored_labels { r: 128 g: 0 b: 128 class_name: "bottle" }
+       colored_labels { r: 0 g: 128 b: 128 class_name: "bus" }
+       colored_labels { r: 128 g: 128 b: 128 class_name: "car" }
+       colored_labels { r: 64 g: 0 b: 0 class_name: "cat" }
+       colored_labels { r: 192 g: 0 b: 0 class_name: "chair" }
+       colored_labels { r: 64 g: 128 b: 0 class_name: "cow" }
+       colored_labels { r: 192 g: 128 b: 0 class_name: "dining table" }
+       colored_labels { r: 64 g: 0 b: 128 class_name: "dog" }
+       colored_labels { r: 192 g: 0 b: 128 class_name: "horse" }
+       colored_labels { r: 64 g: 128 b: 128 class_name: "motorbike" }
+       colored_labels { r: 192 g: 128 b: 128 class_name: "person" }
+       colored_labels { r: 0 g: 64 b: 0 class_name: "potted plant" }
+       colored_labels { r: 128 g: 64 b: 0 class_name: "sheep" }
+       colored_labels { r: 0 g: 192 b: 0 class_name: "sofa" }
+       colored_labels { r: 128 g: 192 b: 0 class_name: "train" }
+       colored_labels { r: 0 g: 64 b: 128 class_name: "tv" })";
+
+// The maximum fraction of pixels in the candidate mask that can have a
+// different class than the golden mask for the test to pass.
+constexpr float kGoldenMaskTolerance = 1e-2;
+// Magnification factor used when creating the golden category masks to make
+// them more human-friendly. Each pixel in the golden masks has its value
+// multiplied by this factor, i.e. a value of 10 means class index 1, a value of
+// 20 means class index 2, etc.
+constexpr int kGoldenMaskMagnificationFactor = 10;
+
+StatusOr<ImageData> LoadImage(std::string image_name) {
+  return DecodeImageFromFile(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+}
+
+// Checks that the two provided `Segmentation` protos are equal.
+// If the proto definition changes, please also change this function.
+void ExpectApproximatelyEqual(const Segmentation& actual,
+                              const Segmentation& expected) {
+  EXPECT_EQ(actual.height(), expected.height());
+  EXPECT_EQ(actual.width(), expected.width());
+  for (int i = 0; i < actual.colored_labels_size(); i++) {
+    EXPECT_THAT(actual.colored_labels(i),
+                EqualsProto(expected.colored_labels(i)));
+  }
+}
+
+class DeepLabOpResolver : public ::tflite::MutableOpResolver {
+ public:
+  DeepLabOpResolver() {
+    AddBuiltin(::tflite::BuiltinOperator_ADD,
+               ::tflite::ops::builtin::Register_ADD());
+    AddBuiltin(::tflite::BuiltinOperator_AVERAGE_POOL_2D,
+               ::tflite::ops::builtin::Register_AVERAGE_POOL_2D());
+    AddBuiltin(::tflite::BuiltinOperator_CONCATENATION,
+               ::tflite::ops::builtin::Register_CONCATENATION());
+    AddBuiltin(::tflite::BuiltinOperator_CONV_2D,
+               ::tflite::ops::builtin::Register_CONV_2D());
+    // DeepLab uses different versions of DEPTHWISE_CONV_2D.
+    AddBuiltin(::tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+               ::tflite::ops::builtin::Register_DEPTHWISE_CONV_2D(),
+               /*min_version=*/1, /*max_version=*/2);
+    AddBuiltin(::tflite::BuiltinOperator_RESIZE_BILINEAR,
+               ::tflite::ops::builtin::Register_RESIZE_BILINEAR());
+  }
+
+  DeepLabOpResolver(const DeepLabOpResolver& r) = delete;
+};
+
+class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+
+TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+
+  SUPPORT_ASSERT_OK(ImageSegmenter::CreateFromOptions(
+      options, absl::make_unique<DeepLabOpResolver>()));
+}
+
+class DeepLabOpResolverMissingOps : public ::tflite::MutableOpResolver {
+ public:
+  DeepLabOpResolverMissingOps() {
+    AddBuiltin(::tflite::BuiltinOperator_ADD,
+               ::tflite::ops::builtin::Register_ADD());
+  }
+
+  DeepLabOpResolverMissingOps(const DeepLabOpResolverMissingOps& r) = delete;
+};
+
+TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+
+  auto image_segmenter_or = ImageSegmenter::CreateFromOptions(
+      options, absl::make_unique<DeepLabOpResolverMissingOps>());
+
+  EXPECT_EQ(image_segmenter_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_segmenter_or.status().message(),
+              HasSubstr("Didn't find op for builtin opcode"));
+  EXPECT_THAT(image_segmenter_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kUnsupportedBuiltinOp))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithTwoModelSources) {
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+
+  StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
+      ImageSegmenter::CreateFromOptions(options);
+
+  EXPECT_EQ(image_segmenter_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_segmenter_or.status().message(),
+              HasSubstr("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 2."));
+  EXPECT_THAT(image_segmenter_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithMissingModel) {
+  ImageSegmenterOptions options;
+
+  auto image_segmenter_or = ImageSegmenter::CreateFromOptions(options);
+
+  EXPECT_EQ(image_segmenter_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_segmenter_or.status().message(),
+              HasSubstr("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 0."));
+  EXPECT_THAT(image_segmenter_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithUnspecifiedOutputType) {
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  options.set_output_type(ImageSegmenterOptions::UNSPECIFIED);
+
+  auto image_segmenter_or = ImageSegmenter::CreateFromOptions(options);
+
+  EXPECT_EQ(image_segmenter_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_segmenter_or.status().message(),
+              HasSubstr("`output_type` must not be UNSPECIFIED"));
+  EXPECT_THAT(image_segmenter_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, SucceedsWithNumberOfThreads) {
+  ImageSegmenterOptions options;
+  options.set_num_threads(4);
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+
+  SUPPORT_ASSERT_OK(ImageSegmenter::CreateFromOptions(options));
+}
+
+using NumThreadsTest = testing::TestWithParam<int>;
+
+INSTANTIATE_TEST_SUITE_P(Default, NumThreadsTest, testing::Values(0, -2));
+
+TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+  ImageSegmenterOptions options;
+  options.set_num_threads(GetParam());
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+
+  StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
+      ImageSegmenter::CreateFromOptions(options);
+
+  EXPECT_EQ(image_segmenter_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(image_segmenter_or.status().message(),
+              HasSubstr("`num_threads` must be greater than "
+                        "0 or equal to -1"));
+  EXPECT_THAT(image_segmenter_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+// Confidence masks tested in PostProcess unit tests below.
+TEST(SegmentTest, SucceedsWithCategoryMask) {
+  // Load input and build frame buffer.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+                               LoadImage("segmentation_input_rotation0.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+  // Load golden mask output.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData golden_mask,
+                               LoadImage("segmentation_golden_rotation0.png"));
+
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> image_segmenter,
+                               ImageSegmenter::CreateFromOptions(options));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const SegmentationResult result,
+                               image_segmenter->Segment(*frame_buffer));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_category_mask());
+  const uint8* mask =
+      reinterpret_cast<const uint8*>(segmentation.category_mask().data());
+
+  int inconsistent_pixels = 0;
+  int num_pixels = golden_mask.height * golden_mask.width;
+  for (int i = 0; i < num_pixels; ++i) {
+    inconsistent_pixels +=
+        (mask[i] * kGoldenMaskMagnificationFactor != golden_mask.pixel_data[i]);
+  }
+  EXPECT_LT(static_cast<float>(inconsistent_pixels) / num_pixels,
+            kGoldenMaskTolerance);
+  ImageDataFree(&rgb_image);
+  ImageDataFree(&golden_mask);
+}
+
+TEST(SegmentTest, SucceedsWithOrientation) {
+  // Load input and build frame buffer with kRightBottom orientation.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      ImageData rgb_image, LoadImage("segmentation_input_rotation90_flop.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height},
+      FrameBuffer::Orientation::kRightBottom);
+  // Load golden mask output.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      ImageData golden_mask,
+      LoadImage("segmentation_golden_rotation90_flop.png"));
+
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> image_segmenter,
+                               ImageSegmenter::CreateFromOptions(options));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const SegmentationResult result,
+                               image_segmenter->Segment(*frame_buffer));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_category_mask());
+  const uint8* mask =
+      reinterpret_cast<const uint8*>(segmentation.category_mask().data());
+  int inconsistent_pixels = 0;
+  int num_pixels = golden_mask.height * golden_mask.width;
+  for (int i = 0; i < num_pixels; ++i) {
+    inconsistent_pixels +=
+        (mask[i] * kGoldenMaskMagnificationFactor != golden_mask.pixel_data[i]);
+  }
+  EXPECT_LT(static_cast<float>(inconsistent_pixels) / num_pixels,
+            kGoldenMaskTolerance);
+  ImageDataFree(&rgb_image);
+  ImageDataFree(&golden_mask);
+}
+
+TEST(SegmentTest, SucceedsWithBaseOptions) {
+  // Load input and build frame buffer.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+                               LoadImage("segmentation_input_rotation0.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+  // Load golden mask output.
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData golden_mask,
+                               LoadImage("segmentation_golden_rotation0.png"));
+
+  ImageSegmenterOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ImageSegmenter> image_segmenter,
+                               ImageSegmenter::CreateFromOptions(options));
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const SegmentationResult result,
+                               image_segmenter->Segment(*frame_buffer));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_category_mask());
+  const uint8* mask =
+      reinterpret_cast<const uint8*>(segmentation.category_mask().data());
+
+  int inconsistent_pixels = 0;
+  int num_pixels = golden_mask.height * golden_mask.width;
+  for (int i = 0; i < num_pixels; ++i) {
+    inconsistent_pixels +=
+        (mask[i] * kGoldenMaskMagnificationFactor != golden_mask.pixel_data[i]);
+  }
+  EXPECT_LT(static_cast<float>(inconsistent_pixels) / num_pixels,
+            kGoldenMaskTolerance);
+  ImageDataFree(&rgb_image);
+  ImageDataFree(&golden_mask);
+}
+
+class PostprocessTest : public tflite_shims::testing::Test {
+ public:
+  class TestImageSegmenter : public ImageSegmenter {
+   public:
+    using ImageSegmenter::ImageSegmenter;
+    using ImageSegmenter::Postprocess;
+
+    static StatusOr<std::unique_ptr<TestImageSegmenter>> CreateFromOptions(
+        const ImageSegmenterOptions& options) {
+      RETURN_IF_ERROR(SanityCheckOptions(options));
+
+      auto options_copy = absl::make_unique<ImageSegmenterOptions>(options);
+
+      ASSIGN_OR_RETURN(
+          auto image_segmenter,
+          TaskAPIFactory::CreateFromExternalFileProto<TestImageSegmenter>(
+              &options_copy->model_file_with_metadata()));
+
+      RETURN_IF_ERROR(image_segmenter->Init(std::move(options_copy)));
+
+      return image_segmenter;
+    }
+
+    TfLiteTensor* GetOutputTensor() {
+      if (TfLiteEngine::OutputCount(GetTfLiteEngine()->interpreter()) != 1) {
+        return nullptr;
+      }
+      return TfLiteEngine::GetOutput(GetTfLiteEngine()->interpreter(), 0);
+    }
+  };
+
+ protected:
+  void SetUp() override { tflite_shims::testing::Test::SetUp(); }
+  void SetUp(const ImageSegmenterOptions& options) {
+    StatusOr<std::unique_ptr<TestImageSegmenter>> test_image_segmenter_or =
+        TestImageSegmenter::CreateFromOptions(options);
+
+    init_status_ = test_image_segmenter_or.status();
+
+    if (init_status_.ok()) {
+      test_image_segmenter_ = std::move(test_image_segmenter_or).value();
+    }
+  }
+
+  StatusOr<const TfLiteTensor*> FillAndGetOutputTensor() {
+    TfLiteTensor* output_tensor = test_image_segmenter_->GetOutputTensor();
+
+    // Fill top-left corner and pad all other pixels with zeros.
+    std::vector<float> confidence_scores = confidence_scores_;
+    confidence_scores.resize(/*width*/ 257 *
+                             /*height*/ 257 *
+                             /*classes*/ 21);
+    RETURN_IF_ERROR(PopulateTensor(confidence_scores, output_tensor));
+
+    return output_tensor;
+  }
+
+  std::unique_ptr<TestImageSegmenter> test_image_segmenter_;
+  absl::Status init_status_;
+  std::vector<float> confidence_scores_ = {/*background=*/0.01,
+                                           /*aeroplane=*/0.01,
+                                           /*bicycle=*/0.01,
+                                           /*bird=*/0.01,
+                                           /*boat=*/0.01,
+                                           /*bottle=*/0.01,
+                                           /*bus=*/0.21,
+                                           /*car=*/0.60,  // highest (index=7)
+                                           /*cat=*/0.01,
+                                           /*chair=*/0.01,
+                                           /*cow=*/0.01,
+                                           /*dining table=*/0.01,
+                                           /*dog=*/0.01,
+                                           /*horse=*/0.01,
+                                           /*motorbike=*/0.01,
+                                           /*person=*/0.01,
+                                           /*potted plant=*/0.01,
+                                           /*sheep=*/0.01,
+                                           /*sofa=*/0.01,
+                                           /*train=*/0.01,
+                                           /*tv=*/0.01};
+};
+
+TEST_F(PostprocessTest, SucceedsWithCategoryMask) {
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  std::unique_ptr<FrameBuffer> frame_buffer =
+      CreateFromRgbaRawBuffer(/*input=*/nullptr, {});
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+                               FillAndGetOutputTensor());
+  SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+                               test_image_segmenter_->Postprocess(
+                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_category_mask());
+  // Check top-left corner has expected class.
+  const uint8* category_mask =
+      reinterpret_cast<const uint8*>(segmentation.category_mask().data());
+  EXPECT_EQ(category_mask[0], /*car*/ 7);
+}
+
+TEST_F(PostprocessTest, SucceedsWithCategoryMaskAndOrientation) {
+  ImageSegmenterOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  // Frame buffer with kRightBottom orientation.
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbaRawBuffer(
+      /*input=*/nullptr, {}, FrameBuffer::Orientation::kRightBottom);
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+                               FillAndGetOutputTensor());
+  SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+                               test_image_segmenter_->Postprocess(
+                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_category_mask());
+  // Check bottom-right corner has expected class.
+  const uint8* category_mask =
+      reinterpret_cast<const uint8*>(segmentation.category_mask().data());
+  EXPECT_EQ(category_mask[/*width*/ 257 * /*height*/ 257 - 1], /*car*/ 7);
+}
+
+TEST_F(PostprocessTest, SucceedsWithConfidenceMask) {
+  ImageSegmenterOptions options;
+  options.set_output_type(ImageSegmenterOptions::CONFIDENCE_MASK);
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  std::unique_ptr<FrameBuffer> frame_buffer =
+      CreateFromRgbaRawBuffer(/*input=*/nullptr, {});
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+                               FillAndGetOutputTensor());
+  SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+                               test_image_segmenter_->Postprocess(
+                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_confidence_masks());
+  const Segmentation::ConfidenceMasks confidence_masks =
+      segmentation.confidence_masks();
+  EXPECT_EQ(confidence_masks.confidence_mask_size(), confidence_scores_.size());
+  // Check top-left corner has expected confidences.
+  for (int index = 0; index < confidence_scores_.size(); ++index) {
+    const float* confidence_mask = reinterpret_cast<const float*>(
+        confidence_masks.confidence_mask(index).value().data());
+    EXPECT_EQ(confidence_mask[0], confidence_scores_[index]);
+  }
+}
+
+TEST_F(PostprocessTest, SucceedsWithConfidenceMaskAndOrientation) {
+  ImageSegmenterOptions options;
+  options.set_output_type(ImageSegmenterOptions::CONFIDENCE_MASK);
+  options.mutable_model_file_with_metadata()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, kDeepLabV3));
+  // Frame buffer with kRightBottom orientation.
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbaRawBuffer(
+      /*input=*/nullptr, {}, FrameBuffer::Orientation::kRightBottom);
+
+  SetUp(options);
+  ASSERT_TRUE(test_image_segmenter_ != nullptr) << init_status_;
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const TfLiteTensor* output_tensor,
+                               FillAndGetOutputTensor());
+  SUPPORT_ASSERT_OK_AND_ASSIGN(SegmentationResult result,
+                               test_image_segmenter_->Postprocess(
+                                   {output_tensor}, *frame_buffer, /*roi=*/{}));
+
+  EXPECT_EQ(result.segmentation_size(), 1);
+  const Segmentation& segmentation = result.segmentation(0);
+  ExpectApproximatelyEqual(
+      segmentation, ParseTextProtoOrDie<Segmentation>(kDeepLabV3PartialResult));
+  EXPECT_TRUE(segmentation.has_confidence_masks());
+  const Segmentation::ConfidenceMasks confidence_masks =
+      segmentation.confidence_masks();
+  EXPECT_EQ(confidence_masks.confidence_mask_size(), confidence_scores_.size());
+  // Check top-left corner has expected confidences.
+  for (int index = 0; index < confidence_scores_.size(); ++index) {
+    const float* confidence_mask = reinterpret_cast<const float*>(
+        confidence_masks.confidence_mask(index).value().data());
+    EXPECT_EQ(confidence_mask[/*width*/ 257 * /*height*/ 257 - 1],
+              confidence_scores_[index]);
+  }
+}
+
+}  // namespace
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc
new file mode 100644
index 0000000..4a33e4b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/task/vision/object_detector_test.cc
@@ -0,0 +1,642 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/task/vision/object_detector.h"
+
+#include <memory>
+
+#include "absl/flags/flag.h"     // from @com_google_absl
+#include "absl/status/status.h"  // from @com_google_absl
+#include "absl/strings/cord.h"   // from @com_google_absl
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/core/shims/cc/shims_test_util.h"
+#include "tensorflow/lite/kernels/builtin_op_kernels.h"
+#include "tensorflow/lite/mutable_op_resolver.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/gmock.h"
+#include "tensorflow_lite_support/cc/port/gtest.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/status_matchers.h"
+#include "tensorflow_lite_support/cc/task/core/task_api_factory.h"
+#include "tensorflow_lite_support/cc/task/core/task_utils.h"
+#include "tensorflow_lite_support/cc/task/core/tflite_engine.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/detections_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/object_detector_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_utils.h"
+#include "tensorflow_lite_support/cc/test/message_matchers.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+namespace tflite {
+
+namespace ops {
+namespace custom {
+
+// Forward declaration for the custom Detection_PostProcess op.
+//
+// See:
+// https://medium.com/@bsramasubramanian/running-a-tensorflow-lite-model-in-python-with-custom-ops-9b2b46efd355
+TfLiteRegistration* Register_DETECTION_POSTPROCESS();
+
+}  // namespace custom
+}  // namespace ops
+
+namespace task {
+namespace vision {
+namespace {
+
+using ::testing::HasSubstr;
+using ::testing::Optional;
+using ::tflite::support::EqualsProto;
+using ::tflite::support::kTfLiteSupportPayload;
+using ::tflite::support::StatusOr;
+using ::tflite::support::TfLiteSupportStatus;
+using ::tflite::task::JoinPath;
+using ::tflite::task::ParseTextProtoOrDie;
+using ::tflite::task::core::PopulateTensor;
+using ::tflite::task::core::TaskAPIFactory;
+using ::tflite::task::core::TfLiteEngine;
+
+constexpr char kTestDataDirectory[] =
+    "/tensorflow_lite_support/cc/test/testdata/task/"
+    "vision/";
+constexpr char kMobileSsdWithMetadata[] =
+    "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite";
+constexpr char kExpectResults[] =
+    R"pb(detections {
+           bounding_box { origin_x: 54 origin_y: 396 width: 393 height: 196 }
+           classes { index: 16 score: 0.64453125 class_name: "cat" }
+         }
+         detections {
+           bounding_box { origin_x: 602 origin_y: 157 width: 394 height: 447 }
+           classes { index: 16 score: 0.59765625 class_name: "cat" }
+         }
+         detections {
+           bounding_box { origin_x: 261 origin_y: 394 width: 179 height: 209 }
+           # Actually a dog, but the model gets confused.
+           classes { index: 16 score: 0.5625 class_name: "cat" }
+         }
+         detections {
+           bounding_box { origin_x: 389 origin_y: 197 width: 276 height: 409 }
+           classes { index: 17 score: 0.51171875 class_name: "dog" }
+         }
+    )pb";
+constexpr char kMobileSsdWithMetadataDummyScoreCalibration[] =
+    "coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite";
+// The model has different output tensor order.
+constexpr char kEfficientDetWithMetadata[] =
+    "coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite";
+
+StatusOr<ImageData> LoadImage(std::string image_name) {
+  return DecodeImageFromFile(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory, image_name));
+}
+
+// Checks that the two provided `DetectionResult` protos are equal, with a
+// tolerancy on floating-point scores to account for numerical instabilities.
+// If the proto definition changes, please also change this function.
+void ExpectApproximatelyEqual(const DetectionResult& actual,
+                              const DetectionResult& expected) {
+  const float kPrecision = 1e-6;
+  EXPECT_EQ(actual.detections_size(), expected.detections_size());
+  for (int i = 0; i < actual.detections_size(); ++i) {
+    const Detection& a = actual.detections(i);
+    const Detection& b = expected.detections(i);
+    EXPECT_THAT(a.bounding_box(), EqualsProto(b.bounding_box()));
+    EXPECT_EQ(a.classes_size(), 1);
+    EXPECT_EQ(b.classes_size(), 1);
+    EXPECT_EQ(a.classes(0).index(), b.classes(0).index());
+    EXPECT_EQ(a.classes(0).class_name(), b.classes(0).class_name());
+    EXPECT_NEAR(a.classes(0).score(), b.classes(0).score(), kPrecision);
+  }
+}
+
+// OpResolver including the custom Detection_PostProcess op.
+class MobileSsdQuantizedOpResolver : public ::tflite::MutableOpResolver {
+ public:
+  MobileSsdQuantizedOpResolver() {
+    AddBuiltin(::tflite::BuiltinOperator_CONCATENATION,
+               ::tflite::ops::builtin::Register_CONCATENATION());
+    AddBuiltin(::tflite::BuiltinOperator_CONV_2D,
+               ::tflite::ops::builtin::Register_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+               ::tflite::ops::builtin::Register_DEPTHWISE_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_RESHAPE,
+               ::tflite::ops::builtin::Register_RESHAPE());
+    AddBuiltin(::tflite::BuiltinOperator_LOGISTIC,
+               ::tflite::ops::builtin::Register_LOGISTIC());
+    AddBuiltin(::tflite::BuiltinOperator_ADD,
+               ::tflite::ops::builtin::Register_ADD());
+    AddCustom("TFLite_Detection_PostProcess",
+              tflite::ops::custom::Register_DETECTION_POSTPROCESS());
+  }
+
+  MobileSsdQuantizedOpResolver(const MobileSsdQuantizedOpResolver& r) = delete;
+};
+
+class CreateFromOptionsTest : public tflite_shims::testing::Test {};
+
+TEST_F(CreateFromOptionsTest, SucceedsWithSelectiveOpResolver) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  SUPPORT_ASSERT_OK(ObjectDetector::CreateFromOptions(
+      options, absl::make_unique<MobileSsdQuantizedOpResolver>()));
+}
+
+// OpResolver missing the Detection_PostProcess op.
+class MobileSsdQuantizedOpResolverMissingOps
+    : public ::tflite::MutableOpResolver {
+ public:
+  MobileSsdQuantizedOpResolverMissingOps() {
+    AddBuiltin(::tflite::BuiltinOperator_CONCATENATION,
+               ::tflite::ops::builtin::Register_CONCATENATION());
+    AddBuiltin(::tflite::BuiltinOperator_CONV_2D,
+               ::tflite::ops::builtin::Register_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_DEPTHWISE_CONV_2D,
+               ::tflite::ops::builtin::Register_DEPTHWISE_CONV_2D());
+    AddBuiltin(::tflite::BuiltinOperator_RESHAPE,
+               ::tflite::ops::builtin::Register_RESHAPE());
+    AddBuiltin(::tflite::BuiltinOperator_LOGISTIC,
+               ::tflite::ops::builtin::Register_LOGISTIC());
+    AddBuiltin(::tflite::BuiltinOperator_ADD,
+               ::tflite::ops::builtin::Register_ADD());
+  }
+
+  MobileSsdQuantizedOpResolverMissingOps(
+      const MobileSsdQuantizedOpResolverMissingOps& r) = delete;
+};
+
+TEST_F(CreateFromOptionsTest, FailsWithSelectiveOpResolverMissingOps) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  auto object_detector_or = ObjectDetector::CreateFromOptions(
+      options, absl::make_unique<MobileSsdQuantizedOpResolverMissingOps>());
+  EXPECT_EQ(object_detector_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(object_detector_or.status().message(),
+              HasSubstr("Encountered unresolved custom op"));
+  EXPECT_THAT(object_detector_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kUnsupportedCustomOp))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithTwoModelSources) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+      ObjectDetector::CreateFromOptions(options);
+
+  EXPECT_EQ(object_detector_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(object_detector_or.status().message(),
+              HasSubstr("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 2."));
+  EXPECT_THAT(object_detector_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithMissingModel) {
+  ObjectDetectorOptions options;
+
+  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+      ObjectDetector::CreateFromOptions(options);
+
+  EXPECT_EQ(object_detector_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(object_detector_or.status().message(),
+              HasSubstr("Expected exactly one of `base_options.model_file` or "
+                        "`model_file_with_metadata` to be provided, found 0."));
+  EXPECT_THAT(object_detector_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithInvalidMaxResults) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.set_max_results(0);
+
+  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+      ObjectDetector::CreateFromOptions(options);
+
+  EXPECT_EQ(object_detector_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(object_detector_or.status().message(),
+              HasSubstr("Invalid `max_results` option"));
+  EXPECT_THAT(object_detector_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, FailsWithCombinedWhitelistAndBlacklist) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.add_class_name_whitelist("foo");
+  options.add_class_name_blacklist("bar");
+
+  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+      ObjectDetector::CreateFromOptions(options);
+
+  EXPECT_EQ(object_detector_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(object_detector_or.status().message(),
+              HasSubstr("mutually exclusive options"));
+  EXPECT_THAT(object_detector_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+TEST_F(CreateFromOptionsTest, SucceedsWithNumberOfThreads) {
+  ObjectDetectorOptions options;
+  options.set_num_threads(4);
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  SUPPORT_ASSERT_OK(ObjectDetector::CreateFromOptions(options));
+}
+
+using NumThreadsTest = testing::TestWithParam<int>;
+
+INSTANTIATE_TEST_SUITE_P(Default, NumThreadsTest, testing::Values(0, -2));
+
+TEST_P(NumThreadsTest, FailsWithInvalidNumberOfThreads) {
+  ObjectDetectorOptions options;
+  options.set_num_threads(GetParam());
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+      ObjectDetector::CreateFromOptions(options);
+
+  EXPECT_EQ(object_detector_or.status().code(),
+            absl::StatusCode::kInvalidArgument);
+  EXPECT_THAT(object_detector_or.status().message(),
+              HasSubstr("`num_threads` must be greater than "
+                        "0 or equal to -1"));
+  EXPECT_THAT(object_detector_or.status().GetPayload(kTfLiteSupportPayload),
+              Optional(absl::Cord(
+                  absl::StrCat(TfLiteSupportStatus::kInvalidArgumentError))));
+}
+
+class DetectTest : public tflite_shims::testing::Test {};
+
+TEST_F(DetectTest, Succeeds) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+                               LoadImage("cats_and_dogs.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ObjectDetectorOptions options;
+  options.set_max_results(4);
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
+                               ObjectDetector::CreateFromOptions(options));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const DetectionResult result,
+                               object_detector->Detect(*frame_buffer));
+  ImageDataFree(&rgb_image);
+  ExpectApproximatelyEqual(
+      result, ParseTextProtoOrDie<DetectionResult>(kExpectResults));
+}
+
+TEST_F(DetectTest, SucceedswithBaseOptions) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+                               LoadImage("cats_and_dogs.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ObjectDetectorOptions options;
+  options.set_max_results(4);
+  options.mutable_base_options()->mutable_model_file()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
+                               ObjectDetector::CreateFromOptions(options));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const DetectionResult result,
+                               object_detector->Detect(*frame_buffer));
+  ImageDataFree(&rgb_image);
+  ExpectApproximatelyEqual(
+      result, ParseTextProtoOrDie<DetectionResult>(kExpectResults));
+}
+
+TEST_F(DetectTest, SucceedswithScoreCalibrations) {
+  SUPPORT_ASSERT_OK_AND_ASSIGN(ImageData rgb_image,
+                               LoadImage("cats_and_dogs.jpg"));
+  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
+      rgb_image.pixel_data,
+      FrameBuffer::Dimension{rgb_image.width, rgb_image.height});
+
+  ObjectDetectorOptions options;
+  options.set_max_results(4);
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      JoinPath("./" /*test src dir*/, kTestDataDirectory,
+               kMobileSsdWithMetadataDummyScoreCalibration));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(std::unique_ptr<ObjectDetector> object_detector,
+                               ObjectDetector::CreateFromOptions(options));
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(const DetectionResult result,
+                               object_detector->Detect(*frame_buffer));
+  ImageDataFree(&rgb_image);
+  ExpectApproximatelyEqual(
+      result, ParseTextProtoOrDie<DetectionResult>(kExpectResults));
+}
+
+class PostprocessTest : public tflite_shims::testing::Test {
+ public:
+  class TestObjectDetector : public ObjectDetector {
+   public:
+    using ObjectDetector::ObjectDetector;
+    using ObjectDetector::Postprocess;
+
+    static StatusOr<std::unique_ptr<TestObjectDetector>> CreateFromOptions(
+        const ObjectDetectorOptions& options) {
+      RETURN_IF_ERROR(SanityCheckOptions(options));
+
+      auto options_copy = absl::make_unique<ObjectDetectorOptions>(options);
+
+      ASSIGN_OR_RETURN(
+          auto object_detector,
+          TaskAPIFactory::CreateFromExternalFileProto<TestObjectDetector>(
+              &options_copy->model_file_with_metadata()));
+
+      RETURN_IF_ERROR(object_detector->Init(std::move(options_copy)));
+
+      return object_detector;
+    }
+
+    std::vector<TfLiteTensor*> GetOutputTensors() {
+      std::vector<TfLiteTensor*> outputs;
+      int num_outputs =
+          TfLiteEngine::OutputCount(GetTfLiteEngine()->interpreter());
+      outputs.reserve(num_outputs);
+      for (int i = 0; i < num_outputs; i++) {
+        outputs.push_back(
+            TfLiteEngine::GetOutput(GetTfLiteEngine()->interpreter(), i));
+      }
+      return outputs;
+    }
+  };
+
+ protected:
+  void SetUp() override { tflite_shims::testing::Test::SetUp(); }
+  void SetUp(const ObjectDetectorOptions& options) {
+    StatusOr<std::unique_ptr<TestObjectDetector>> test_object_detector_or =
+        TestObjectDetector::CreateFromOptions(options);
+
+    init_status_ = test_object_detector_or.status();
+
+    if (init_status_.ok()) {
+      test_object_detector_ = std::move(test_object_detector_or).value();
+    }
+
+    dummy_frame_buffer_ = CreateFromRgbRawBuffer(/*input=*/nullptr,
+                                                 {/*width=*/20, /*height=*/10});
+  }
+
+  StatusOr<std::vector<const TfLiteTensor*>> FillAndGetOutputTensors() {
+    std::vector<TfLiteTensor*> output_tensors =
+        test_object_detector_->GetOutputTensors();
+    if (output_tensors.size() != 4) {
+      return absl::InternalError(absl::StrFormat(
+          "Expected 4 output tensors, found %d", output_tensors.size()));
+    }
+
+    std::vector<const TfLiteTensor*> result;
+
+    TfLiteTensor* locations = output_tensors[0];
+    std::vector<float> locations_data = {
+        /*left=*/0.2, /*top=*/0.2, /*right=*/0.4, /*bottom=*/0.6,
+        /*left=*/0.4, /*top=*/0.2, /*right=*/0.6, /*bottom=*/0.6,
+        /*left=*/0.2, /*top=*/0.4, /*right=*/0.4, /*bottom=*/0.8};
+    // Pad with zeros to fill the 10 locations.
+    locations_data.resize(4 * 10);
+    RETURN_IF_ERROR(PopulateTensor(locations_data, locations));
+    result.push_back(locations);
+
+    TfLiteTensor* classes = output_tensors[1];
+    std::vector<float> classes_data = {/*bicycle*/ 1, /*car*/ 2,
+                                       /*motorcycle*/ 3};
+    // Pad with zeros to fill the 10 classes.
+    classes_data.resize(10);
+    RETURN_IF_ERROR(PopulateTensor(classes_data, classes));
+    result.push_back(classes);
+
+    TfLiteTensor* scores = output_tensors[2];
+    std::vector<float> scores_data = {0.8, 0.6, 0.4};
+    // Pad with zeros to fill the 10 scores.
+    scores_data.resize(10);
+    RETURN_IF_ERROR(PopulateTensor(scores_data, scores));
+    result.push_back(scores);
+
+    TfLiteTensor* num_results = output_tensors[3];
+    std::vector<float> num_results_data = {10};
+    RETURN_IF_ERROR(PopulateTensor(num_results_data, num_results));
+    result.push_back(num_results);
+
+    return result;
+  }
+
+  std::unique_ptr<TestObjectDetector> test_object_detector_;
+  std::unique_ptr<FrameBuffer> dummy_frame_buffer_;
+  absl::Status init_status_;
+};
+
+TEST_F(PostprocessTest, SucceedsWithScoreThresholdOption) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.set_score_threshold(0.5);
+
+  SetUp(options);
+  ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      const std::vector<const TfLiteTensor*> output_tensors,
+      FillAndGetOutputTensors());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      DetectionResult result,
+      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
+                                         /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<DetectionResult>(
+          R"pb(detections {
+                 bounding_box { origin_x: 4 origin_y: 2 width: 8 height: 2 }
+                 classes { index: 1 score: 0.8 class_name: "bicycle" }
+               }
+               detections {
+                 bounding_box { origin_x: 4 origin_y: 4 width: 8 height: 2 }
+                 classes { index: 2 score: 0.6 class_name: "car" }
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithFrameBufferOrientation) {
+  std::unique_ptr<FrameBuffer> frame_buffer_with_orientation =
+      CreateFromRgbRawBuffer(/*input=*/nullptr, {/*width=*/20, /*height=*/10},
+                             FrameBuffer::Orientation::kBottomRight);
+
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.set_score_threshold(0.5);
+
+  SetUp(options);
+  ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      const std::vector<const TfLiteTensor*> output_tensors,
+      FillAndGetOutputTensors());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      DetectionResult result,
+      test_object_detector_->Postprocess(
+          output_tensors, *frame_buffer_with_orientation, /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<DetectionResult>(
+          R"pb(detections {
+                 bounding_box { origin_x: 8 origin_y: 6 width: 8 height: 2 }
+                 classes { index: 1 score: 0.8 class_name: "bicycle" }
+               }
+               detections {
+                 bounding_box { origin_x: 8 origin_y: 4 width: 8 height: 2 }
+                 classes { index: 2 score: 0.6 class_name: "car" }
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithMaxResultsOption) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.set_max_results(1);
+
+  SetUp(options);
+  ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      const std::vector<const TfLiteTensor*> output_tensors,
+      FillAndGetOutputTensors());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      DetectionResult result,
+      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
+                                         /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<DetectionResult>(
+          R"pb(detections {
+                 bounding_box { origin_x: 4 origin_y: 2 width: 8 height: 2 }
+                 classes { index: 1 score: 0.8 class_name: "bicycle" }
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithWhitelistOption) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.add_class_name_whitelist("car");
+  options.add_class_name_whitelist("motorcycle");
+
+  SetUp(options);
+  ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      const std::vector<const TfLiteTensor*> output_tensors,
+      FillAndGetOutputTensors());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      DetectionResult result,
+      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
+                                         /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<DetectionResult>(
+          R"pb(detections {
+                 bounding_box { origin_x: 4 origin_y: 4 width: 8 height: 2 }
+                 classes { index: 2 score: 0.6 class_name: "car" }
+               }
+               detections {
+                 bounding_box { origin_x: 8 origin_y: 2 width: 8 height: 2 }
+                 classes { index: 3 score: 0.4 class_name: "motorcycle" }
+               }
+          )pb"));
+}
+
+TEST_F(PostprocessTest, SucceedsWithBlacklistOption) {
+  ObjectDetectorOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(JoinPath(
+      "./" /*test src dir*/, kTestDataDirectory, kMobileSsdWithMetadata));
+  options.add_class_name_blacklist("car");
+  // Setting score threshold to discard the 7 padded-with-zeros results.
+  options.set_score_threshold(0.1);
+
+  SetUp(options);
+  ASSERT_TRUE(test_object_detector_ != nullptr) << init_status_;
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      const std::vector<const TfLiteTensor*> output_tensors,
+      FillAndGetOutputTensors());
+
+  SUPPORT_ASSERT_OK_AND_ASSIGN(
+      DetectionResult result,
+      test_object_detector_->Postprocess(output_tensors, *dummy_frame_buffer_,
+                                         /*roi=*/{}));
+
+  ExpectApproximatelyEqual(
+      result,
+      ParseTextProtoOrDie<DetectionResult>(
+          R"pb(detections {
+                 bounding_box { origin_x: 4 origin_y: 2 width: 8 height: 2 }
+                 classes { index: 1 score: 0.8 class_name: "bicycle" }
+               }
+               detections {
+                 bounding_box { origin_x: 8 origin_y: 2 width: 8 height: 2 }
+                 classes { index: 3 score: 0.4 class_name: "motorcycle" }
+               }
+          )pb"));
+}
+
+}  // namespace
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc
new file mode 100644
index 0000000..c16815c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.cc
@@ -0,0 +1,82 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/cc/test/test_utils.h"
+
+#include "absl/strings/str_cat.h"  // from @com_google_absl
+
+namespace tflite {
+namespace task {
+
+std::string JoinPath(absl::string_view path1, absl::string_view path2) {
+  if (path1.empty())
+    return std::string(path2);
+  if (path2.empty())
+    return std::string(path1);
+  if (path1.back() == '/') {
+    if (path2.front() == '/')
+      return absl::StrCat(path1, absl::ClippedSubstr(path2, 1));
+  } else {
+    if (path2.front() != '/')
+      return absl::StrCat(path1, "/", path2);
+  }
+  return absl::StrCat(path1, path2);
+}
+
+namespace internal {
+
+// Given a collection of file paths, append them all together,
+// ensuring that the proper path separators are inserted between them.
+std::string JoinPathImpl(bool honor_abs,
+                         std::initializer_list<absl::string_view> paths) {
+  std::string result;
+
+  if (paths.size() != 0) {
+    // This size calculation is worst-case: it assumes one extra "/" for every
+    // path other than the first.
+    size_t total_size = paths.size() - 1;
+    for (const absl::string_view path : paths)
+      total_size += path.size();
+    result.resize(total_size);
+
+    auto begin = result.begin();
+    auto out = begin;
+    bool trailing_slash = false;
+    for (absl::string_view path : paths) {
+      if (path.empty())
+        continue;
+      if (path.front() == '/') {
+        if (honor_abs) {
+          out = begin;  // wipe out whatever we've built up so far.
+        } else if (trailing_slash) {
+          path.remove_prefix(1);
+        }
+      } else {
+        if (!trailing_slash && out != begin)
+          *out++ = '/';
+      }
+      const size_t this_size = path.size();
+      memcpy(&*out, path.data(), this_size);
+      out += this_size;
+      trailing_slash = out[-1] == '/';
+    }
+    result.erase(out - begin);
+  }
+  return result;
+}
+
+}  // namespace internal
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h
new file mode 100644
index 0000000..1d730d5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/test_utils.h
@@ -0,0 +1,53 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_CC_TEST_UTILS_TEST_UTILS_H_
+#define TENSORFLOW_LITE_SUPPORT_CC_TEST_UTILS_TEST_UTILS_H_
+
+#include <glog/logging.h>
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/proto2.h"
+
+namespace tflite {
+namespace task {
+namespace internal {
+
+// Not part of the public API.
+std::string JoinPathImpl(bool honor_abs,
+                         std::initializer_list<absl::string_view> paths);
+
+}  // namespace internal
+
+std::string JoinPath(absl::string_view path1, absl::string_view path2);
+
+template <typename... T>
+inline std::string JoinPath(absl::string_view path1,
+                            absl::string_view path2,
+                            absl::string_view path3,
+                            const T&... args) {
+  return internal::JoinPathImpl(false, {path1, path2, path3, args...});
+}
+
+template <typename T>
+T ParseTextProtoOrDie(const std::string& input) {
+  T result;
+  CHECK(tflite::support::proto::TextFormat::ParseFromString(input, &result));
+  return result;
+}
+
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_CC_TEST_UTILS_TEST_UTILS_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/BUILD
new file mode 100644
index 0000000..72a88c2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/BUILD
@@ -0,0 +1,79 @@
+load("//tensorflow_lite_support/tools/build_rules:http_files.bzl", "tflite_file", "tflite_model")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "nl_classifier_models",
+    srcs = glob([
+        "test_model_nl_classifier*.tflite",
+    ]),
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+)
+
+filegroup(
+    name = "bert_nl_classifier_models",
+    srcs = [
+        ":bert_nl_classifier",
+    ],
+)
+
+filegroup(
+    name = "mobile_bert_model",
+    srcs = [
+        ":mobilebert_float",
+        ":mobilebert_vocab",
+        ":mobilebert_with_metadata",
+    ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+)
+
+filegroup(
+    name = "albert_model",
+    srcs = [
+        ":30k-clean",
+        ":albert",
+        ":albert_with_metadata",
+    ],
+)
+
+filegroup(
+    name = "regex_tokenizer_files",
+    srcs = [
+        "empty_vocab_for_regex_tokenizer.txt",
+        "vocab_for_regex_tokenizer.txt",
+    ],
+)
+
+filegroup(
+    name = "universal_sentence_encoder_qa",
+    data = [":universal_sentence_encoder_qa_with_metadata"],
+)
+
+tflite_model(name = "bert_nl_classifier")
+
+tflite_model(name = "albert")
+
+tflite_model(name = "albert_with_metadata")
+
+tflite_model(name = "universal_sentence_encoder_qa_with_metadata")
+
+tflite_model(name = "mobilebert_float")
+
+tflite_file(
+    name = "mobilebert_vocab",
+    extension = "txt",
+)
+
+tflite_model(name = "mobilebert_with_metadata")
+
+tflite_file(
+    name = "30k-clean",
+    extension = "model",
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/albert_with_metadata.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/albert_with_metadata.json
new file mode 100644
index 0000000..6d2e748
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/albert_with_metadata.json
@@ -0,0 +1,81 @@
+{
+  "name": "Albert Question and Answerer",
+  "description": "Answers questions based on the content of a given passage. To integrate the model into your app, try the `BertQuestionAnswerer` API in the TensorFlow Lite Task library. `BertQuestionAnswerer` takes a passage string and a query string, and returns the answer strings. It encapsulates the processing logic of inputs and outputs and runs the inference with the best practice.",
+  "version": "v1",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "description": "Tokenized ids of input text as concatenated query and passage.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "mask",
+          "description": "Mask with 1 for real tokens and 0 for padding tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "segment_ids",
+          "description": "0 for query and 1 for passage tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "end_logits",
+          "description": "logits over the sequence which indicates the end position of the answer span with closed interval.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "start_logits",
+          "description": "logits over the sequence which indicates the start position of the answer span with closed interval.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        }
+      ],
+      "input_process_units": [
+        {
+          "options_type": "SentencePieceTokenizerOptions",
+          "options": {
+            "sentencePiece_model": [
+              {
+                "name": "30k-clean.model",
+                "description": "The sentence piece model file."
+              }
+            ],
+            "vocab_file": [
+              {
+                "name": "30k-clean.vocab",
+                "description": "Vocabulary file for the SentencePiece tokenizer. This file is optional during tokenization, while the sentence piece model is mandatory.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ],
+  "author": "TensorFlow",
+  "license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
+  "min_parser_version": "1.1.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/bert_nl_classifier.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/bert_nl_classifier.json
new file mode 100644
index 0000000..44aedf97
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/bert_nl_classifier.json
@@ -0,0 +1,73 @@
+{
+  "name": "MobileBert text classifier",
+  "description": "Classifies the input string based on the known catergories. To integrate the model into your app, try the `BertNLClassifier` API in the TensorFlow Lite Task library. `BertNLClassifier` takes an input string, and returns the classified label with probability. It encapsulates the processing logic of inputs and outputs and runs the inference with the best practice.",
+  "version": "v1",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "description": "Tokenized ids of input text as concatenated query and passage.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "segment_ids",
+          "description": "0 for query and 1 for passage tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "mask",
+          "description": "Mask with 1 for real tokens and 0 for padding tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for classification categories.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ],
+      "input_process_units": [
+        {
+          "options_type": "BertTokenizerOptions",
+          "options": {
+            "vocab_file": [
+              {
+                "name": "vocab.txt",
+                "description": "Vocabulary file for the BertTokenizer.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ],
+  "author": "TensorFlow",
+  "license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
+  "min_parser_version": "1.1.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/empty_vocab_for_regex_tokenizer.txt b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/empty_vocab_for_regex_tokenizer.txt
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/empty_vocab_for_regex_tokenizer.txt
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/mobilebert_with_metadata.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/mobilebert_with_metadata.json
new file mode 100644
index 0000000..d2ba03f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/mobilebert_with_metadata.json
@@ -0,0 +1,75 @@
+{
+  "name": "MobileBert Question and Answerer",
+  "description": "Answers questions based on the content of a given passage. To integrate the model into your app, try the `BertQuestionAnswerer` API in the TensorFlow Lite Task library. `BertQuestionAnswerer` takes a passage string and a query string, and returns the answer strings. It encapsulates the processing logic of inputs and outputs and runs the inference with the best practice.",
+  "version": "v1",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "description": "Tokenized ids of input text as concatenated query and passage.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "mask",
+          "description": "Mask with 1 for real tokens and 0 for padding tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "segment_ids",
+          "description": "0 for query and 1 for passage tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "end_logits",
+          "description": "logits over the sequence which indicates the end position of the answer span with closed interval.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        },
+        {
+          "name": "start_logits",
+          "description": "logits over the sequence which indicates the start position of the answer span with closed interval.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        }
+      ],
+      "input_process_units": [
+        {
+          "options_type": "BertTokenizerOptions",
+          "options": {
+            "vocab_file": [
+              {
+                "name": "vocab.txt",
+                "description": "Vocabulary file for the BertTokenizer.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ],
+  "author": "TensorFlow",
+  "license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
+  "min_parser_version": "1.1.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier.tflite
new file mode 100644
index 0000000..52e614c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_bool_output.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_bool_output.tflite
new file mode 100644
index 0000000..20c6db1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_bool_output.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label.json
new file mode 100644
index 0000000..d0a4301
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label.json
@@ -0,0 +1,50 @@
+{
+  "name": "NL Classifier",
+  "description": "Identify the text string from a set of 3 categories.",
+  "version": "v1",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "text string",
+          "description": "Input string to be classified.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "scores_dequantized",
+          "description": "Scores of the 3 labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "associated_files": [
+            {
+              "name": "test_labels.txt",
+              "description": "Labels for objects that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        },
+        {
+          "name": "scores_quantized"
+        },
+        {
+          "name": "labels"
+        },
+        {
+          "name": "scores_dequantized_float64"
+        }
+      ]
+    }
+  ],
+  "author": "TensorFlow",
+  "license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label.tflite
new file mode 100644
index 0000000..4d04015
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label.tflite
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label_builtin_ops.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label_builtin_ops.json
new file mode 100644
index 0000000..f8d36ad
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label_builtin_ops.json
@@ -0,0 +1,64 @@
+{
+  "name": "AverageWordVec text classifier",
+  "description": "Classify text into predefined categories.",
+  "version": "v1",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input_text",
+          "description": "Embedding vectors representing the input text to be classified. The input need to be converted from raw text to embedding vectors using the attached dictionary file.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "RegexTokenizerOptions",
+              "options": {
+                "delim_regex_pattern": "[^\\w\\']+",
+                "vocab_file": [
+                  {
+                    "name": "vocab.txt",
+                    "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                    "type": "VOCABULARY"
+                  }
+                ]
+              }
+            }
+          ]
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for the categories that the model can classify.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "author": "TensorFlow",
+  "license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
+  "min_parser_version": "1.2.1"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label_builtin_ops.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label_builtin_ops.tflite
new file mode 100644
index 0000000..7bcfa882
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_associated_label_builtin_ops.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_regex_tokenizer.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_regex_tokenizer.json
new file mode 100644
index 0000000..79b63a40
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_regex_tokenizer.json
@@ -0,0 +1,64 @@
+{
+  "name": "Sentiment Analyzer (AverageWordVecModelSpec)",
+  "description": "Detect if the input text's sentiment is positive or negative. The model was trained on the IMDB Movie Reviews dataset so it is more accurate when input text is a movie review.",
+  "version": "v1",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input_text",
+          "description": "Embedding vectors representing the input text to be classified. The input need to be converted from raw text to embedding vectors using the attached dictionary file.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "RegexTokenizerOptions",
+              "options": {
+                "delim_regex_pattern": "[^\\w\\']+",
+                "vocab_file": [
+                  {
+                    "name": "vocab.txt",
+                    "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                    "type": "VOCABULARY"
+                  }
+                ]
+              }
+            }
+          ]
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for the categories that the model can classify.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "author": "TensorFlow",
+  "license": "Apache License. Version 2.0 http://www.apache.org/licenses/LICENSE-2.0.",
+  "min_parser_version": "1.2.1"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_regex_tokenizer.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_regex_tokenizer.tflite
new file mode 100644
index 0000000..f73e77c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/test_model_nl_classifier_with_regex_tokenizer.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/vocab_for_regex_tokenizer.txt b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/vocab_for_regex_tokenizer.txt
new file mode 100644
index 0000000..0a27d7c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/text/vocab_for_regex_tokenizer.txt
@@ -0,0 +1,10000 @@
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/BUILD
new file mode 100644
index 0000000..6de3411
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/BUILD
@@ -0,0 +1,21 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files(glob(["*.*"]))
+
+filegroup(
+    name = "test_models",
+    srcs = glob([
+        "*.tflite",
+    ]),
+)
+
+filegroup(
+    name = "test_images",
+    srcs = glob([
+        "*.jpg",
+        "*.png",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/automl_labeler_model.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/automl_labeler_model.tflite
new file mode 100644
index 0000000..2c3a3b3d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/automl_labeler_model.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger-224.png b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger-224.png
new file mode 100644
index 0000000..7e1e243
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger-224.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger.jpg
new file mode 100644
index 0000000..a94f84e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger.jpg
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger_crop.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger_crop.jpg
new file mode 100644
index 0000000..7aabbb9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger_crop.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger_rotation180.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger_rotation180.jpg
new file mode 100644
index 0000000..42cfff3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/burger_rotation180.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/cats_and_dogs.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/cats_and_dogs.jpg
new file mode 100644
index 0000000..f6be4ab
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/cats_and_dogs.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/cats_and_dogs_rotation180.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/cats_and_dogs_rotation180.jpg
new file mode 100644
index 0000000..23e80cc
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/cats_and_dogs_rotation180.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite
new file mode 100644
index 0000000..9de3534
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_efficientdet_lite0_v1_1.0_quant_2021_09_06.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite
new file mode 100644
index 0000000..02ecbf8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.tflite
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite
new file mode 100644
index 0000000..6416c4c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/deeplabv3.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/deeplabv3.tflite
new file mode 100644
index 0000000..e3fdb7d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/deeplabv3.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/dilated_conv.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/dilated_conv.tflite
new file mode 100644
index 0000000..e871a26
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/dilated_conv.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_1_default_1.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_1_default_1.tflite
new file mode 100644
index 0000000..78a6fad
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_1_default_1.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_1_metadata_1.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_1_metadata_1.tflite
new file mode 100644
index 0000000..443609b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_1_metadata_1.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_quant.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_quant.tflite
new file mode 100644
index 0000000..18a20f9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_quant.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_quant_without_subgraph_metadata.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_quant_without_subgraph_metadata.tflite
new file mode 100644
index 0000000..c29c233
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v1_0.25_224_quant_without_subgraph_metadata.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224.tflite
new file mode 100644
index 0000000..e123012
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224_without_labels.json b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224_without_labels.json
new file mode 100644
index 0000000..7fd6567
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224_without_labels.json
@@ -0,0 +1,28 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ]
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224_without_labels.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224_without_labels.tflite
new file mode 100644
index 0000000..acf3e26
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v2_1.0_224_without_labels.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v3_small_100_224_embedder.tflite b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v3_small_100_224_embedder.tflite
new file mode 100644
index 0000000..7a48343
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/mobilenet_v3_small_100_224_embedder.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/multi_objects.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/multi_objects.jpg
new file mode 100644
index 0000000..992684d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/multi_objects.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation0.png b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation0.png
new file mode 100644
index 0000000..3a44939
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation0.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation0_yuv.png b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation0_yuv.png
new file mode 100644
index 0000000..79f255d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation0_yuv.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation90_flop.png b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation90_flop.png
new file mode 100644
index 0000000..7eefb94
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_golden_rotation90_flop.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_input_rotation0.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_input_rotation0.jpg
new file mode 100644
index 0000000..1b79c037
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_input_rotation0.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_input_rotation90_flop.jpg b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_input_rotation90_flop.jpg
new file mode 100644
index 0000000..51f3bb0
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/segmentation_input_rotation90_flop.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/sparrow.png b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/sparrow.png
new file mode 100644
index 0000000..17eec7b1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/test/testdata/task/vision/sparrow.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc
index 1e3506b..53c8831 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.cc
@@ -61,7 +61,7 @@
 }
 
 WordpieceTokenizerResult BertTokenizer::TokenizeWordpiece(
-    const std::string& input) {
+    const std::string& input) const {
   WordpieceTokenizerResult result;
   std::vector<std::string>& subwords = result.subwords;
   std::vector<int>& wp_absolute_begin_offset = result.wp_begin_offset;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h
index 533a8ee..1de54fa 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h
@@ -20,7 +20,7 @@
 #include <string>
 #include <vector>
 
-#include "absl/container/flat_hash_map.h"
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
 #include "re2/re2.h"
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
 #include "tensorflow_lite_support/cc/utils/common_utils.h"
@@ -115,7 +115,7 @@
 
   // Perform tokenization, return wordpiece-specific tokenized result including
   // subwords and offsets
-  WordpieceTokenizerResult TokenizeWordpiece(const std::string& input);
+  WordpieceTokenizerResult TokenizeWordpiece(const std::string& input) const;
 
   // Check if a certain key is included in the vocab.
   tensorflow::text::LookupStatus Contains(const absl::string_view key,
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc
index bcf13d6..249bc2d 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer_jni.cc
@@ -17,7 +17,7 @@
 
 #include <string>
 
-#include "absl/memory/memory.h"
+#include "absl/memory/memory.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h"
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
index 44c43b2d..ded6fbd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.cc
@@ -17,8 +17,8 @@
 
 #include <iostream>
 
-#include "absl/strings/str_cat.h"
-#include "absl/strings/substitute.h"
+#include "absl/strings/str_cat.h"     // from @com_google_absl
+#include "absl/strings/substitute.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/utils/common_utils.h"
 namespace tflite {
 namespace support {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h
index c53ae49..a82f500 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/regex_tokenizer.h
@@ -16,7 +16,7 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_CC_TEXT_TOKENIZERS_REGEX_TOKENIZER_H_
 #define TENSORFLOW_LITE_SUPPORT_CC_TEXT_TOKENIZERS_REGEX_TOKENIZER_H_
 
-#include "absl/container/node_hash_map.h"
+#include "absl/container/node_hash_map.h"  // from @com_google_absl
 #include "re2/re2.h"
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc
index 6711fe4f..8ca14c5 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_jni.cc
@@ -20,8 +20,8 @@
 #include <utility>
 #include <vector>
 
-#include "absl/memory/memory.h"
-#include "absl/strings/str_split.h"
+#include "absl/memory/memory.h"      // from @com_google_absl
+#include "absl/strings/str_split.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h"
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h
index ed5d3da7..d6e8631 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/sentencepiece_tokenizer.h
@@ -20,7 +20,7 @@
 #include <string>
 #include <vector>
 
-#include "src/sentencepiece_processor.h"
+#include "src/sentencepiece_processor.h"  // from @com_google_sentencepiece
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
 
 namespace tflite {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer.h
index c754506..9c86b2b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer.h
@@ -20,7 +20,7 @@
 #include <string>
 #include <vector>
 
-#include "absl/strings/string_view.h"
+#include "absl/strings/string_view.h"  // from @com_google_absl
 
 namespace tflite {
 namespace support {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
index f3758c8..fd76f3a 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_jni_lib.h
@@ -17,8 +17,6 @@
 
 #include <jni.h>
 
-#include <string>
-
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
index 46786fd7..32957d1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.cc
@@ -15,7 +15,7 @@
 
 #include "tensorflow_lite_support/cc/text/tokenizers/tokenizer_utils.h"
 
-#include "absl/status/status.h"
+#include "absl/status/status.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/common.h"
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/text/tokenizers/bert_tokenizer.h"
@@ -28,7 +28,6 @@
 namespace tokenizer {
 
 using ::tflite::ProcessUnit;
-using ::tflite::SentencePieceTokenizerOptions;
 using ::tflite::support::CreateStatusWithPayload;
 using ::tflite::support::StatusOr;
 using ::tflite::support::TfLiteSupportStatus;
@@ -72,6 +71,12 @@
       return absl::make_unique<BertTokenizer>(vocab_buffer.data(),
                                               vocab_buffer.size());
     }
+    case ProcessUnitOptions_SentencePieceTokenizerOptions: {
+      return CreateStatusWithPayload(
+          absl::StatusCode::kInvalidArgument,
+          "Chromium does not support sentencepiece tokenization",
+          TfLiteSupportStatus::kMetadataInvalidTokenizerError);
+    }
     case ProcessUnitOptions_RegexTokenizerOptions: {
       const tflite::RegexTokenizerOptions* options =
           tokenizer_process_unit->options_as<RegexTokenizerOptions>();
@@ -106,7 +111,7 @@
             TfLiteSupportStatus::kMetadataInvalidTokenizerError);
       }
 
-      return regex_tokenizer;
+      return std::move(regex_tokenizer);
     }
     default:
       return CreateStatusWithPayload(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/BUILD
index 07c832f..fc6de34 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/BUILD
@@ -1,9 +1,11 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite")
+
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "jni_utils",
     srcs = [
         "jni_utils.cc",
@@ -11,8 +13,24 @@
     hdrs = [
         "jni_utils.h",
     ],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:delegate_plugin",
+        "@org_tensorflow//tensorflow/lite/core/shims:delegate_registry",
+        "@org_tensorflow//tensorflow/lite/core/shims:jni_initialization",
+        "@org_tensorflow//tensorflow/lite/experimental/acceleration/configuration:delegate_plugin_converter",
+    ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:configuration_proto_inc",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "@com_google_absl//absl/memory",
+        "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
         "@org_tensorflow//tensorflow/lite/java/jni",
     ],
 )
@@ -25,6 +43,9 @@
     hdrs = [
         "common_utils.h",
     ],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         "@com_google_absl//absl/container:node_hash_map",
         "@com_google_absl//absl/strings",
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc
index 17c4823..3ea6b14 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.cc
@@ -17,7 +17,7 @@
 
 #include <fstream>
 
-#include "absl/strings/str_split.h"
+#include "absl/strings/str_split.h"  // from @com_google_absl
 
 namespace tflite {
 namespace support {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h
index ef1bf33..275c4932 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/common_utils.h
@@ -19,7 +19,7 @@
 #include <string>
 #include <vector>
 
-#include "absl/container/node_hash_map.h"
+#include "absl/container/node_hash_map.h"  // from @com_google_absl
 
 namespace tflite {
 namespace support {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc
index fd0887f..35ce8229 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.cc
@@ -15,11 +15,100 @@
 
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 
+#include <dlfcn.h>
 #include <string.h>
 
+#include "absl/memory/memory.h"       // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow/lite/core/shims/c/experimental/acceleration/configuration/delegate_plugin.h"
+#include "tensorflow/lite/core/shims/cc/experimental/acceleration/configuration/delegate_registry.h"
+#include "tensorflow/lite/experimental/acceleration/configuration/delegate_plugin_converter.h"
+#include "tensorflow_lite_support/cc/common.h"
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+
 namespace tflite {
 namespace support {
 namespace utils {
+namespace {
+
+using ::absl::StatusCode;
+using ::tflite::proto::Delegate;
+using ::tflite::support::CreateStatusWithPayload;
+using ::tflite_shims::delegates::DelegatePluginRegistry;
+
+// delegate_name should be one of the following:
+// gpu / hexagon
+absl::Status loadDelegatePluginLibrary(const std::string& delegate_name) {
+  // Load "lib<delegate_name>_plugin.so".
+  std::string lib_name =
+      absl::StrFormat("lib%s_delegate_plugin.so", delegate_name);
+
+  // Choosing RTLD_NOW over RTLD_LAZY: RTLD_NOW loads symbols now and
+  // makes sure there's no unresolved symbols. Using RTLD_LAZY will not
+  // discover unresolved symbols issues right away, and may lead to crash later
+  // during inference, which should be avoided.
+  // Choosing RTLD_LOCAL over RTLD_GLOBAL: the symbols should not be available
+  // for subsequently loaded libraries.
+  // Not choosing RTLD_DEEPBIND due to portability concerns; also we're using a
+  // linker script to hide internal symbols, so we don't really need it.
+  // Not choosing RTLD_NODELETE to avoid a (bounded) memory leak:
+  // if we used RTLD_NODELETE, dlclose() would not free the memory for the
+  // library.
+  void* handle = dlopen(lib_name.c_str(), RTLD_NOW | RTLD_LOCAL);
+  if (!handle) {
+    return CreateStatusWithPayload(
+        StatusCode::kInternal,
+        absl::StrFormat("Error loading %s. %s", lib_name, dlerror()));
+  }
+
+  // Load the method "TfLite<camel_name>DelegatePluginCApi".
+  std::string camel_name(delegate_name);
+  camel_name[0] = toupper(camel_name[0]);
+  std::string new_method_name =
+      absl::StrFormat("TfLite%sDelegatePluginCApi", camel_name);
+  TfLiteOpaqueDelegatePlugin* (*new_delegate_c)();
+  new_delegate_c = reinterpret_cast<decltype(new_delegate_c)>(
+      dlsym(handle, new_method_name.c_str()));
+  if (!new_delegate_c) {
+    // Ignore the return value of dlclose as we deliberately hide it from users.
+    dlclose(handle);
+    handle = nullptr;
+    return CreateStatusWithPayload(
+        StatusCode::kInternal,
+        absl::StrFormat("Error loading method, %s from %s", new_method_name,
+                        lib_name));
+  }
+
+  // Register the delegate.
+  new DelegatePluginRegistry::Register(
+      absl::StrFormat("%sPlugin", camel_name),
+      tflite::delegates::DelegatePluginConverter(*new_delegate_c()));
+
+  return absl::OkStatus();
+}
+
+}  // namespace
+
+tflite::support::StatusOr<Delegate> ConvertToProtoDelegate(jint delegate) {
+  // The supported delegate types should match
+  // org.tensorflow.lite.task.core.ComputeSettings.Delegate.
+  switch (delegate) {
+    case 0:
+      return Delegate::NONE;
+    case 1:
+      return Delegate::NNAPI;
+    case 2:
+      RETURN_IF_ERROR(loadDelegatePluginLibrary("gpu"));
+      return Delegate::GPU;
+    default:
+      break;
+  }
+  // Should never happen.
+  return CreateStatusWithPayload(
+      StatusCode::kInternal,
+      absl::StrFormat("The delegate type is unsupported: %d", delegate));
+}
 
 std::string JStringToString(JNIEnv* env, jstring jstr) {
   if (jstr == nullptr) {
@@ -96,6 +185,26 @@
   env->ThrowNew(e_class, message);
 }
 
+const char* GetExceptionClassNameForStatusCode(StatusCode status_code) {
+  switch (status_code) {
+    case StatusCode::kOk:
+      return nullptr;
+    case StatusCode::kInvalidArgument:
+      return kIllegalArgumentException;
+    // TODO(b/197650198): Uncomment this before the next major version bump
+    //  and update the signature, as IOException is a checked exception.
+    // case StatusCode::kNotFound:
+    //   return kIOException;
+    case StatusCode::kInternal:
+      return kIllegalStateException;
+    // kUnknown and all other status codes are mapped to a generic
+    // RuntimeException.
+    case StatusCode::kUnknown:
+    default:
+      return kRuntimeException;
+  }
+}
+
 }  // namespace utils
 }  // namespace support
 }  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h
index 1a215e7..7caf49e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/cc/utils/jni_utils.h
@@ -22,7 +22,10 @@
 #include <string>
 #include <vector>
 
-#include "absl/strings/string_view.h"
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/configuration_proto_inc.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
 
 namespace tflite {
 namespace support {
@@ -32,6 +35,8 @@
 const char kIllegalStateException[] = "java/lang/IllegalStateException";
 const char kNullPointerException[] = "java/lang/NullPointerException";
 const char kIndexOutOfBoundsException[] = "java/lang/IndexOutOfBoundsException";
+const char kIOException[] = "java/io/IOException";
+const char kRuntimeException[] = "java/lang/RuntimeException";
 const char kUnsupportedOperationException[] =
     "java/lang/UnsupportedOperationException";
 const char kAssertionError[] = "java/lang/AssertionError";
@@ -71,6 +76,10 @@
   return array_list_object;
 }
 
+// Converts delegate Java int type to delegate proto type.
+tflite::support::StatusOr<tflite::proto::Delegate> ConvertToProtoDelegate(
+    jint delegate);
+
 std::string JStringToString(JNIEnv* env, jstring jstr);
 
 std::vector<std::string> StringListToVector(JNIEnv* env, jobject list_object);
@@ -87,6 +96,8 @@
                                const char* clazz,
                                const char* message);
 
+const char* GetExceptionClassNameForStatusCode(absl::StatusCode status_code);
+
 }  // namespace utils
 }  // namespace support
 }  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/codegen/BUILD
index c56bc6c..b224f98 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/BUILD
@@ -15,6 +15,8 @@
     hdrs = [
         "utils.h",
     ],
+    deps = [
+    ],
 )
 
 cc_library(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc b/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc
index 0754bfe..bb8f1f4 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/codegen/android_java_generator.cc
@@ -656,7 +656,7 @@
 public static {{MODEL_CLASS_NAME}} newInstance(Context context, String modelPath, Model.Options runningOptions) throws IOException {
   Model model = Model.createModel(context, modelPath, runningOptions);
   Metadata metadata = new Metadata(model.getData(), model);
-  MyImageClassifier instance = new MyImageClassifier(model, metadata);)");
+  {{MODEL_CLASS_NAME}} instance = new {{MODEL_CLASS_NAME}}(model, metadata);)");
   for (const auto& tensor : model.inputs) {
     SetCodeWriterWithTensorInfo(code_writer, tensor);
     code_writer->Append(
@@ -779,7 +779,11 @@
   code_writer->Append(R"(buildscript {
     repositories {
         google()
-        jcenter()
+        mavenCentral()  // For versioned releases
+        maven {         // For snapshot releases
+            name 'ossrh-snapshot'
+            url 'http://oss.sonatype.org/content/repositories/snapshots'
+        }
     }
     dependencies {
         classpath 'com.android.tools.build:gradle:3.2.1'
@@ -835,8 +839,8 @@
 
 dependencies {
     compileOnly 'org.checkerframework:checker-qual:2.5.8'
-    api 'org.tensorflow:tensorflow-lite:0.0.0-nightly'
-    api 'org.tensorflow:tensorflow-lite-support:0.0.0-nightly'
+    api 'org.tensorflow:tensorflow-lite:0.0.0-nightly-SNAPSHOT'
+    api 'org.tensorflow:tensorflow-lite-support:0.0.0-nightly-SNAPSHOT'
     api files("$buildDir/libs/tensorflow-lite-support-metadata.jar")
     implementation 'org.apache.commons:commons-compress:1.19'
 })");
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/BUILD
index f47288b..11db944 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/BUILD
@@ -11,24 +11,27 @@
     name = "tf_text_flex_delegate",
     additional_deps = ["@org_tensorflow_text//tensorflow_text:ops_lib"],
     models = [
-        # TODO(b/160817619) Replace with a more complex model.
         "testdata/sentencepiece_tokenizer_flex_op.tflite",
+        "testdata/wiki40b-lm-en.tflite",
     ],
 )
 
 # bazel test --config=monolithic tensorflow_lite_support/custom_ops:tflite_inference_test
 cc_test(
     name = "tflite_inference_test",
-    srcs = ["tflite_inference_main.cc"],
-    args = ["--model=tensorflow_lite_support/custom_ops/testdata/sentencepiece_tokenizer_flex_op.tflite"],
-    data = ["//tensorflow_lite_support/custom_ops:testdata/sentencepiece_tokenizer_flex_op.tflite"],
+    srcs = ["tflite_inference_test.cc"],
+    data = [
+        "//tensorflow_lite_support/custom_ops:testdata/sentencepiece_tokenizer_flex_op.tflite",
+        "//tensorflow_lite_support/custom_ops:testdata/wiki40b-lm-en.tflite",
+    ],
     deps = [
         ":tf_text_flex_delegate",
+        "//testing/base/public:gunit",
         "@org_tensorflow//tensorflow/lite:framework",
         "@org_tensorflow//tensorflow/lite:string_util",
         "@org_tensorflow//tensorflow/lite/c:common",
         "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-        "@org_tensorflow//tensorflow/lite/tools:command_line_flags",
+        "@com_google_googletest//:gtest_main",
     ] + select({
         "@org_tensorflow//tensorflow:android": [
             "@org_tensorflow//tensorflow/core:portable_tensorflow_lib_lite",
@@ -41,19 +44,3 @@
         ],
     }),
 )
-
-# We expect several libraries to already be installed on the system, e.g. via
-# `pip install numpy`
-py_library(
-    name = "expect_numpy_installed",
-)
-
-# `pip install tensorflow`
-py_library(
-    name = "expect_tfpy_installed",
-)
-
-# `pip install tensorflow_text`
-py_library(
-    name = "expect_tftext_installed",
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/BUILD
index 5d63917..300dbd1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/BUILD
@@ -1,4 +1,4 @@
-# Placeholder for internal Python strict compatibility macro.
+# Placeholder for internal Python strict test compatibility macro.
 load("@org_tensorflow//tensorflow:tensorflow.bzl", "pybind_extension")
 
 package(
@@ -70,9 +70,9 @@
     srcs_version = "PY3",
     deps = [
         ":_pywrap_whitespace_tokenizer_op_resolver",
-        "//tensorflow_lite_support/custom_ops:expect_numpy_installed",
-        "//tensorflow_lite_support/custom_ops:expect_tfpy_installed",
-        "//tensorflow_lite_support/custom_ops:expect_tftext_installed",
+        # build rule placeholder: numpy dep,
+        # build rule placeholder: tensorflow dep,
+        # build rule placeholder: tensorflow_text dep,
         "@absl_py//absl/logging",
         "@absl_py//absl/testing:parameterized",
     ],
@@ -137,8 +137,8 @@
     srcs_version = "PY3",
     deps = [
         ":_pywrap_ngrams_op_resolver",
-        "//tensorflow_lite_support/custom_ops:expect_tfpy_installed",
-        "//tensorflow_lite_support/custom_ops:expect_tftext_installed",
+        # build rule placeholder: tensorflow dep,
+        # build rule placeholder: tensorflow_text dep,
         "//tensorflow_lite_support/custom_ops/python:tflite_text_api",
         "@absl_py//absl/logging",
         "@absl_py//absl/testing:parameterized",
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.py b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.py
index e52ca28..33a2231 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ngrams_test.py
@@ -71,14 +71,12 @@
         @tf.function(input_signature=input_signature)
         def __call__(self, values, *args):
           row_splits = list(args)
-          row_splits.reverse()
           input_tensor = tf.RaggedTensor.from_nested_row_splits(
               flat_values=values, nested_row_splits=tuple(row_splits))
           output_tensor = ngrams(
               input_tensor, width, reduction_type=tf_text.Reduction.STRING_JOIN)
           output = [output_tensor.flat_values]
           output.extend(list(output_tensor.nested_row_splits))
-          output.reverse()
           return tuple(output)
 
       tf.saved_model.save(Model(), temp_dir)
@@ -151,29 +149,21 @@
     input_tensor = tf.ragged.constant(test_case)
     tf_output = tf_text.ngrams(
         input_tensor, 2, reduction_type=tf_text.Reduction.STRING_JOIN)
-
     rank = input_tensor.shape.rank
     model = self._make_model(rank, 2, ragged_tensor=True, flex=False)
     interpreter = interpreter_wrapper.InterpreterWithCustomOps(
         model_content=model, custom_op_registerers=['AddNgramsCustomOp'])
-    interpreter.resize_tensor_input(0, input_tensor.flat_values.shape)
+    signature_fn = interpreter.get_signature_runner()
+    signature_kwargs = {}
+    signature_kwargs['values'] = input_tensor.flat_values.numpy()
     for r in range(rank - 1):
-      interpreter.resize_tensor_input(r + 1,
-                                      input_tensor.nested_row_splits[r].shape)
-    interpreter.allocate_tensors()
-    interpreter.set_tensor(interpreter.get_input_details()[0]['index'],
-                           input_tensor.flat_values.numpy())
-    for r in range(rank - 1):
-      interpreter.set_tensor(interpreter.get_input_details()[r + 1]['index'],
-                             input_tensor.nested_row_splits[r].numpy())
-    interpreter.invoke()
-    tflite_output_values = interpreter.get_tensor(
-        interpreter.get_output_details()[0]['index'])
+      signature_kwargs[f'args_{r}'] = input_tensor.nested_row_splits[r].numpy()
+    output = signature_fn(**signature_kwargs)
+    tflite_output_values = output['output_0']
     self.assertEqual(tf_output.flat_values.numpy().tolist(),
                      tflite_output_values.tolist())
     for i in range(rank - 1):
-      tflite_output_cur_row_splits = interpreter.get_tensor(
-          interpreter.get_output_details()[i + 1]['index'])
+      tflite_output_cur_row_splits = output[f'output_{i + 1}']
       self.assertEqual(tf_output.nested_row_splits[i].numpy().tolist(),
                        tflite_output_cur_row_splits.tolist())
 
@@ -187,24 +177,18 @@
     model = self._make_model(rank, 3, ragged_tensor=True, flex=False)
     interpreter = interpreter_wrapper.InterpreterWithCustomOps(
         model_content=model, custom_op_registerers=['AddNgramsCustomOp'])
-    interpreter.resize_tensor_input(0, input_tensor.flat_values.shape)
+    signature_fn = interpreter.get_signature_runner()
+    signature_kwargs = {}
+    signature_kwargs['values'] = (
+        input_tensor.flat_values.numpy().astype('bytes'))
     for r in range(rank - 1):
-      interpreter.resize_tensor_input(r + 1,
-                                      input_tensor.nested_row_splits[r].shape)
-    interpreter.allocate_tensors()
-    interpreter.set_tensor(interpreter.get_input_details()[0]['index'],
-                           input_tensor.flat_values.numpy())
-    for r in range(rank - 1):
-      interpreter.set_tensor(interpreter.get_input_details()[r + 1]['index'],
-                             input_tensor.nested_row_splits[r].numpy())
-    interpreter.invoke()
-    tflite_output_values = interpreter.get_tensor(
-        interpreter.get_output_details()[0]['index'])
+      signature_kwargs[f'args_{r}'] = input_tensor.nested_row_splits[r].numpy()
+    output = signature_fn(**signature_kwargs)
+    tflite_output_values = output['output_0']
     self.assertEqual(tf_output.flat_values.numpy().tolist(),
                      tflite_output_values.tolist())
     for i in range(rank - 1):
-      tflite_output_cur_row_splits = interpreter.get_tensor(
-          interpreter.get_output_details()[i + 1]['index'])
+      tflite_output_cur_row_splits = output[f'output_{i+1}']
       self.assertEqual(tf_output.nested_row_splits[i].numpy().tolist(),
                        tflite_output_cur_row_splits.tolist())
 
@@ -217,19 +201,14 @@
       model = self._make_model(rank, 3, ragged_tensor=True, flex=False)
       interpreter = interpreter_wrapper.InterpreterWithCustomOps(
           model_content=model, custom_op_registerers=['AddNgramsCustomOp'])
-      interpreter.resize_tensor_input(0, input_tensor.flat_values.shape)
-      for r in range(rank - 1):
-        interpreter.resize_tensor_input(r + 1,
-                                        input_tensor.nested_row_splits[r].shape)
-      interpreter.allocate_tensors()
-      interpreter.set_tensor(interpreter.get_input_details()[0]['index'],
-                             input_tensor.flat_values.numpy())
-      for r in range(rank - 1):
-        interpreter.set_tensor(interpreter.get_input_details()[r + 1]['index'],
-                               input_tensor.nested_row_splits[r].numpy())
-      start_time = timeit.default_timer()
-      for _ in range(INVOKES_FOR_SINGLE_OP_BENCHMARK):
-        interpreter.invoke()
+    signature_fn = interpreter.get_signature_runner()
+    signature_kwargs = {}
+    signature_kwargs['values'] = input_tensor.flat_values.numpy()
+    for r in range(rank - 1):
+      signature_kwargs[f'args_{r}'] = input_tensor.nested_row_splits[r].numpy()
+    start_time = timeit.default_timer()
+    for _ in range(INVOKES_FOR_SINGLE_OP_BENCHMARK):
+      _ = signature_fn(**signature_kwargs)
       latency_op = latency_op + timeit.default_timer() - start_time
     latency_op = latency_op / (
         INVOKES_FOR_SINGLE_OP_BENCHMARK * len(TEST_CASES))
@@ -241,20 +220,17 @@
       rank = input_tensor.shape.rank
       model = self._make_model(rank, 3, ragged_tensor=True, flex=True)
       interpreter = interpreter_wrapper.Interpreter(model_content=model)
-      interpreter.resize_tensor_input(0, input_tensor.flat_values.shape)
+      signature_fn = interpreter.get_signature_runner()
+      signature_kwargs = {}
+      signature_kwargs['values'] = input_tensor.flat_values.numpy()
+
       for r in range(rank - 1):
-        interpreter.resize_tensor_input(r + 1,
-                                        input_tensor.nested_row_splits[r].shape)
-      interpreter.allocate_tensors()
-      interpreter.set_tensor(interpreter.get_input_details()[0]['index'],
-                             input_tensor.flat_values.numpy())
-      for r in range(rank - 1):
-        interpreter.set_tensor(interpreter.get_input_details()[r + 1]['index'],
-                               input_tensor.nested_row_splits[r].numpy())
+        signature_kwargs[f'args_{r}'] = input_tensor.nested_row_splits[r].numpy(
+        )
       start_time = timeit.default_timer()
       for _ in range(INVOKES_FOR_FLEX_DELEGATE_BENCHMARK):
-        interpreter.invoke()
-      latency_flex = latency_flex + timeit.default_timer() - start_time
+        _ = signature_fn(**signature_kwargs)
+        latency_flex = latency_flex + timeit.default_timer() - start_time
     latency_flex = latency_flex / (
         INVOKES_FOR_FLEX_DELEGATE_BENCHMARK * len(TEST_CASES))
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/BUILD
index 38a55c6..a512cdc8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/BUILD
@@ -1,7 +1,5 @@
 # RaggedTensors suppport in TFLite
 
-load("@org_tensorflow//tensorflow:tensorflow.bzl", "pybind_extension")
-
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
     licenses = ["notice"],  # Apache 2.0
@@ -51,24 +49,6 @@
     alwayslink = 1,
 )
 
-pybind_extension(
-    name = "pywrap_tflite_registerer",
-    srcs = [
-        "pywrap_tflite_registerer.cc",
-    ],
-    hdrs = ["py_tflite_registerer.h"],
-    additional_exported_symbols = ["TFLite_RaggedTensorToTensorRegisterer"],
-    module_name = "pywrap_tflite_registerer",
-    srcs_version = "PY3ONLY",
-    deps = [
-        ":py_tflite_registerer",
-        "@local_config_python//:python_headers",
-        "@org_tensorflow//tensorflow/lite:framework",
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-        "@pybind11",
-    ],
-)
-
 cc_library(
     name = "ragged_range_tflite",
     srcs = ["ragged_range_tflite.cc"],
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py/BUILD
new file mode 100644
index 0000000..650ab90
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py/BUILD
@@ -0,0 +1,27 @@
+# Python wrapper used for test.
+
+load("@org_tensorflow//tensorflow:tensorflow.bzl", "pybind_extension")
+
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:users",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+pybind_extension(
+    name = "pywrap_tflite_registerer",
+    srcs = [
+        "pywrap_tflite_registerer.cc",
+    ],
+    additional_exported_symbols = ["TFLite_RaggedTensorToTensorRegisterer"],
+    module_name = "pywrap_tflite_registerer",
+    srcs_version = "PY3ONLY",
+    deps = [
+        "//tensorflow_lite_support/custom_ops/kernel/ragged:py_tflite_registerer",
+        "@local_config_python//:python_headers",
+        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+        "@pybind11",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/pywrap_tflite_registerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py/pywrap_tflite_registerer.cc
similarity index 100%
rename from third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/pywrap_tflite_registerer.cc
rename to third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/ragged/py/pywrap_tflite_registerer.cc
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/BUILD
index 2bdb5754..79982c2 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/BUILD
@@ -4,7 +4,6 @@
 load("@flatbuffers//:build_defs.bzl", "flatbuffer_cc_library")
 load("@org_tensorflow//tensorflow:tensorflow.bzl", "tf_gen_op_wrapper_py")
 load(":native.bzl", "micore_tf_copts", "micore_tf_deps")
-load("@org_tensorflow//tensorflow:tensorflow.bzl", "pybind_extension")
 
 package(
     default_visibility = [
@@ -274,6 +273,8 @@
         ":encoder_config",
         ":model_converter",
         ":optimized_encoder",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "@com_google_absl//absl/flags:flag",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings:str_format",
         "@com_google_googletest//:gtest_main",
@@ -296,6 +297,8 @@
         ":double_array_trie_builder",
         ":model_converter",
         ":optimized_decoder",
+        "//tensorflow_lite_support/cc/test:test_utils",
+        "@com_google_absl//absl/flags:flag",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings:str_format",
         "@com_google_googletest//:gtest_main",
@@ -318,47 +321,6 @@
     alwayslink = 1,
 )
 
-pybind_extension(
-    name = "pywrap_tflite_registerer",
-    srcs = [
-        "pywrap_tflite_registerer.cc",
-    ],
-    hdrs = ["py_tflite_registerer.h"],
-    additional_exported_symbols = ["TFLite_SentencepieceTokenizerRegisterer"],
-    module_name = "pywrap_tflite_registerer",
-    srcs_version = "PY3ONLY",
-    deps = [
-        ":py_tflite_registerer",
-        "@local_config_python//:python_headers",
-        "@org_tensorflow//tensorflow/lite:framework",
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
-        "@pybind11",
-    ],
-)
-
-pybind_extension(
-    name = "pywrap_model_converter",
-    srcs = ["pywrap_model_converter.cc"],
-    hdrs = ["model_converter.h"],
-    additional_exported_symbols = [
-        "ConvertSentencepieceModel",
-        "ConvertSentencepieceModelForDecoder",
-        "GetVocabularySize",
-    ],
-    copts = ["-fexceptions"],
-    features = ["-use_header_modules"],
-    module_name = "pywrap_model_converter",
-    srcs_version = "PY3ONLY",
-    deps = [
-        ":model_converter",
-        "//tensorflow_lite_support/cc/port:statusor",
-        "@com_google_absl//absl/status",
-        "@local_config_python//:python_headers",
-        "@org_tensorflow//tensorflow/lite:framework",
-        "@pybind11",
-    ],
-)
-
 config_setting(
     name = "armeabi_v7a_and_fastbuild",
     values = {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.cc
index 72b7262..75388ce 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.cc
@@ -18,7 +18,7 @@
 #include <algorithm>
 #include <memory>
 
-#include "include/darts.h"
+#include "include/darts.h"  // from @darts_clone
 
 namespace tflite {
 namespace ops {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc
index 53f4f66..47ba9fd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.cc
@@ -15,9 +15,9 @@
 
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h"
 
-#include "absl/status/status.h"
-#include "absl/strings/str_replace.h"
-#include "src/sentencepiece_model.pb.h"
+#include "absl/status/status.h"          // from @com_google_absl
+#include "absl/strings/str_replace.h"    // from @com_google_absl
+#include "src/sentencepiece_model.pb.h"  // from @com_google_sentencepiece
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/decoder_config_generated.h"
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.h"
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/encoder_config_generated.h"
@@ -94,8 +94,10 @@
   const auto pieces_trie_fbs = pieces_trie_builder.Finish();
 
   // Converting normalization.
-  const auto [normalization_trie, normalization_strings] =
+  const auto normalization =
       DecodePrecompiledCharsmap(model_config.normalizer_spec());
+  const auto normalization_trie = std::get<0>(normalization);
+  const auto normalization_strings = std::get<1>(normalization);
   const auto normalization_trie_vector =
       builder.CreateVector(normalization_trie);
   TrieBuilder normalization_trie_builder(builder);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc
index 04d1c85..94161c2 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_decoder_test.cc
@@ -19,9 +19,12 @@
 
 #include <gmock/gmock.h>
 #include <gtest/gtest.h>
-#include "src/sentencepiece.pb.h"
-#include "src/sentencepiece_processor.h"
+#include "absl/flags/flag.h"              // from @com_google_absl
+#include "absl/strings/str_format.h"      // from @com_google_absl
+#include "src/sentencepiece.pb.h"         // from @com_google_sentencepiece
+#include "src/sentencepiece_processor.h"  // from @com_google_sentencepiece
 #include "tensorflow/core/platform/env.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h"
 
 namespace tflite {
@@ -33,8 +36,8 @@
 
 tensorflow::Status TFReadFileToString(const std::string& filepath,
                                       std::string* data) {
-  return tensorflow::ReadFileToString(tensorflow::Env::Default(),
-                                      /*test_path*/ filepath, data);
+  return tensorflow::ReadFileToString(tensorflow::Env::Default(), filepath,
+                                      data);
 }
 
 absl::Status StdReadFileToString(const std::string& filepath,
@@ -54,22 +57,25 @@
 }  // namespace internal
 
 namespace {
+using ::tflite::task::JoinPath;
+
 static char kConfigFilePath[] =
-    "tensorflow_lite_support/custom_ops/kernel/"
+    "/tensorflow_lite_support/custom_ops/kernel/"
     "sentencepiece/testdata/sentencepiece.model";
 
 TEST(OptimizedEncoder, ConfigConverter) {
   std::string config;
-  auto status = internal::StdReadFileToString(kConfigFilePath, &config);
 
+  auto status = internal::StdReadFileToString(
+      JoinPath("./" /*test src dir*/, kConfigFilePath), &config);
   ASSERT_TRUE(status.ok());
 
   ::sentencepiece::SentencePieceProcessor processor;
-  ASSERT_OK(processor.LoadFromSerializedProto(config));
+  ASSERT_TRUE(processor.LoadFromSerializedProto(config).ok());
   const auto converted_model = ConvertSentencepieceModelForDecoder(config);
   const std::string test_string("Hello world!\\xF0\\x9F\\x8D\\x95");
   ::sentencepiece::SentencePieceText reference_encoded;
-  CHECK_OK(processor.Encode(test_string, &reference_encoded));
+  ASSERT_TRUE(processor.Encode(test_string, &reference_encoded).ok());
 
   std::vector<int> encoded_vector;
   encoded_vector.reserve(reference_encoded.pieces_size());
@@ -77,7 +83,7 @@
     encoded_vector.push_back(piece.id());
   }
   std::string ref_decoded;
-  ASSERT_OK(processor.Decode(encoded_vector, &ref_decoded));
+  ASSERT_TRUE(processor.Decode(encoded_vector, &ref_decoded).ok());
   const auto decoded = DecodeString(encoded_vector, converted_model.data());
   ASSERT_EQ(decoded.type, DecoderResultType::SUCCESS);
   ASSERT_EQ(ref_decoded, decoded.decoded);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc
index b79c513..4148f8e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder.cc
@@ -39,7 +39,9 @@
   std::vector<int> result_offsets;
   result_offsets.reserve(offsets.size());
   for (int i = 0, j = 0; i < input.size();) {
-    auto [consumed, new_string] = pc(input.data() + i, input.size() - i);
+    auto result = pc(input.data() + i, input.size() - i);
+    auto consumed = std::get<0>(result);
+    auto new_string = std::get<1>(result);
     if (consumed == 0) {
       // Skip the current byte and move forward.
       result_string.push_back(input[i]);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc
index 47a5c04..dd956a2 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/optimized_encoder_test.cc
@@ -19,11 +19,13 @@
 
 #include <gmock/gmock.h>
 #include <gtest/gtest.h>
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
-#include "src/sentencepiece.pb.h"
-#include "src/sentencepiece_processor.h"
+#include "absl/flags/flag.h"              // from @com_google_absl
+#include "absl/status/status.h"           // from @com_google_absl
+#include "absl/strings/str_format.h"      // from @com_google_absl
+#include "src/sentencepiece.pb.h"         // from @com_google_sentencepiece
+#include "src/sentencepiece_processor.h"  // from @com_google_sentencepiece
 #include "tensorflow/core/platform/env.h"
+#include "tensorflow_lite_support/cc/test/test_utils.h"
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/double_array_trie_builder.h"
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/encoder_config_generated.h"
 #include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h"
@@ -37,8 +39,8 @@
 
 tensorflow::Status TFReadFileToString(const std::string& filepath,
                                       std::string* data) {
-  return tensorflow::ReadFileToString(tensorflow::Env::Default(),
-                                      /*test_path*/ filepath, data);
+  return tensorflow::ReadFileToString(tensorflow::Env::Default(), filepath,
+                                      data);
 }
 
 absl::Status StdReadFileToString(const std::string& filepath,
@@ -58,8 +60,10 @@
 
 namespace {
 
+using ::tflite::task::JoinPath;
+
 static char kConfigFilePath[] =
-    "tensorflow_lite_support/custom_ops/kernel/"
+    "/tensorflow_lite_support/custom_ops/kernel/"
     "sentencepiece/testdata/sentencepiece.model";
 
 TEST(OptimizedEncoder, NormalizeStringWhitestpaces) {
@@ -71,12 +75,16 @@
   FinishEncoderConfigBuffer(builder, ecb.Finish());
   const EncoderConfig* config = GetEncoderConfig(builder.GetBufferPointer());
   {
-    const auto [res_string, offsets] = NormalizeString("x  y", *config);
+    const auto result = NormalizeString("x  y", *config);
+    const auto res_string = std::get<0>(result);
+    const auto offsets = std::get<1>(result);
     EXPECT_EQ(res_string, "\xe2\x96\x81x\xe2\x96\x81y");
     EXPECT_THAT(offsets, ::testing::ElementsAre(0, 0, 0, 0, 1, 1, 1, 3));
   }
   {
-    const auto [res_string, offsets] = NormalizeString("\tx  y\n", *config);
+    const auto result = NormalizeString("\tx  y\n", *config);
+    const auto res_string = std::get<0>(result);
+    const auto offsets = std::get<1>(result);
     EXPECT_EQ(res_string, "\xe2\x96\x81x\xe2\x96\x81y");
     EXPECT_THAT(offsets, ::testing::ElementsAre(0, 0, 0, 1, 2, 2, 2, 4));
   }
@@ -101,8 +109,9 @@
   FinishEncoderConfigBuffer(builder, ecb.Finish());
   const EncoderConfig* config = GetEncoderConfig(builder.GetBufferPointer());
   {
-    const auto [res_string, offsets] =
-        NormalizeString("ABAABAAABAAAA", *config);
+    const auto result = NormalizeString("ABAABAAABAAAA", *config);
+    const auto res_string = std::get<0>(result);
+    const auto offsets = std::get<1>(result);
     EXPECT_EQ(res_string, "A1BA2BA3BA4");
     EXPECT_THAT(offsets,
                 ::testing::ElementsAre(0, 0, 1, 2, 2, 4, 5, 5, 8, 9, 9));
@@ -129,8 +138,9 @@
   FinishEncoderConfigBuffer(builder, ecb.Finish());
   const EncoderConfig* config = GetEncoderConfig(builder.GetBufferPointer());
   {
-    const auto [res_string, offsets] =
-        NormalizeString("XXABAABAAABAAAA", *config);
+    const auto result = NormalizeString("XXABAABAAABAAAA", *config);
+    const auto res_string = std::get<0>(result);
+    const auto offsets = std::get<1>(result);
     EXPECT_EQ(res_string, " A1BA2BA3BA4");
     EXPECT_THAT(offsets,
                 ::testing::ElementsAre(0, 2, 2, 3, 4, 4, 6, 7, 7, 10, 11, 11));
@@ -139,7 +149,8 @@
 
 TEST(OptimizedEncoder, ConfigConverter) {
   std::string config;
-  auto status = internal::StdReadFileToString(kConfigFilePath, &config);
+  auto status = internal::StdReadFileToString(
+      JoinPath("./" /*test src dir*/, kConfigFilePath), &config);
   ASSERT_TRUE(status.ok());
 
   ::sentencepiece::SentencePieceProcessor processor;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/pywrap_model_converter.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/pywrap_model_converter.cc
deleted file mode 100644
index f74c156..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/pywrap_model_converter.cc
+++ /dev/null
@@ -1,45 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "pybind11/pybind11.h"
-#include "pybind11/stl.h"
-#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/model_converter.h"
-
-namespace tflite {
-namespace ops {
-namespace custom {
-namespace sentencepiece {
-
-namespace py = pybind11;
-
-PYBIND11_MODULE(pywrap_model_converter, m) {
-  m.def("convert_sentencepiece_model", [](py::bytes model_string) {
-    return py::bytes(ConvertSentencepieceModel(std::string(model_string)));
-  });
-
-  m.def("convert_sentencepiece_model_for_decoder", [](py::bytes model_string) {
-    return py::bytes(
-        ConvertSentencepieceModelForDecoder(std::string(model_string)));
-  });
-
-  m.def("get_vocabulary_size", [](py::bytes model_string) {
-    return GetVocabularySize(std::string(model_string));
-  });
-}
-
-}  // namespace sentencepiece
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/pywrap_tflite_registerer.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/pywrap_tflite_registerer.cc
deleted file mode 100644
index dc380c6..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/kernel/sentencepiece/pywrap_tflite_registerer.cc
+++ /dev/null
@@ -1,35 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "pybind11/pybind11.h"
-#include "pybind11/pytypes.h"
-#include "tensorflow_lite_support/custom_ops/kernel/sentencepiece/py_tflite_registerer.h"
-
-PYBIND11_MODULE(pywrap_tflite_registerer, m) {
-  m.doc() = R"pbdoc(
-    pywrap_tflite_registerer
-    A module with a wrapper that adds to a Python wrapper for TFLite
-    sentencepiece tokenizer.
-  )pbdoc";
-  m.def(
-      "TFLite_SentencepieceTokenizerRegisterer",
-      [](uintptr_t resolver) {
-        TFLite_SentencepieceTokenizerRegisterer(
-            reinterpret_cast<tflite::MutableOpResolver*>(resolver));
-      },
-      R"pbdoc(
-      The function that adds Sentencepiece Tokenizer to the TFLite interpreter.
-      )pbdoc");
-}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/BUILD
index dad8f28..33d3f08 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/BUILD
@@ -9,8 +9,8 @@
     name = "tflite_text_api",
     srcs = ["tflite_text_api.py"],
     deps = [
-        "//tensorflow_lite_support/custom_ops:expect_tfpy_installed",
-        "//tensorflow_lite_support/custom_ops:expect_tftext_installed",
+        # build rule placeholder: tensorflow dep,
+        # build rule placeholder: tensorflow_text dep,
     ],
 )
 
@@ -23,8 +23,8 @@
     ],
     srcs_version = "PY3",
     deps = [
-        "//tensorflow_lite_support/custom_ops:expect_tfpy_installed",
-        "//tensorflow_lite_support/custom_ops/kernel/sentencepiece:pywrap_model_converter",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/custom_ops/kernel/sentencepiece/py:pywrap_model_converter",
     ],
 )
 
@@ -37,9 +37,9 @@
     python_version = "PY3",
     deps = [
         ":sentencepiece_tokenizer",
-        "//tensorflow_lite_support/custom_ops:expect_tfpy_installed",
-        "//tensorflow_lite_support/custom_ops:expect_tftext_installed",
-        "//tensorflow_lite_support/custom_ops/kernel/sentencepiece:pywrap_tflite_registerer",
+        # build rule placeholder: tensorflow dep,
+        # build rule placeholder: tensorflow_text dep,
+        "//tensorflow_lite_support/custom_ops/kernel/sentencepiece/py:pywrap_tflite_registerer",
         "@absl_py//absl:app",
         "@absl_py//absl/flags",
         "@absl_py//absl/logging",
@@ -52,8 +52,8 @@
     srcs = ["ragged_tensor_to_tensor_test.py"],
     python_version = "PY3",
     deps = [
-        "//tensorflow_lite_support/custom_ops:expect_tfpy_installed",
-        "//tensorflow_lite_support/custom_ops/kernel/ragged:pywrap_tflite_registerer",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/custom_ops/kernel/ragged/py:pywrap_tflite_registerer",
         "@absl_py//absl:app",
         "@absl_py//absl/flags",
         "@absl_py//absl/logging",
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/ragged_tensor_to_tensor_test.py b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/ragged_tensor_to_tensor_test.py
index 319131e..b1fa3d1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/ragged_tensor_to_tensor_test.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/ragged_tensor_to_tensor_test.py
@@ -35,7 +35,7 @@
     concrete_function = ragged_tensor_function.get_concrete_function()
 
     converter = tf.lite.TFLiteConverter.from_concrete_functions(
-        [concrete_function])
+        [concrete_function], ragged_tensor_function)
     converter.allow_custom_ops = True
     tflite_model = converter.convert()
     interpreter = interpreter_wrapper.InterpreterWithCustomOps(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer.py b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer.py
index 55aa0c9..21efed56 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer.py
@@ -27,7 +27,7 @@
 from tensorflow.python.framework import load_library
 from tensorflow.python.platform import resource_loader
 gen_sentencepiece_tokenizer_op = load_library.load_op_library(resource_loader.get_path_to_datafile('../kernel/sentencepiece/sentencepiece_tokenizer_op.so'))
-from tensorflow_lite_support.custom_ops.kernel.sentencepiece import pywrap_model_converter as model_converter
+from tensorflow_lite_support.custom_ops.kernel.sentencepiece.py import pywrap_model_converter as model_converter
 
 
 class SentencepieceTokenizer:
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer_test.py b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer_test.py
index e0a9c81..3609b469 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer_test.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/python/sentencepiece_tokenizer_test.py
@@ -33,7 +33,7 @@
 from tensorflow.lite.python import interpreter as interpreter_wrapper  # pylint: disable=g-direct-tensorflow-import
 from tensorflow.python.platform import resource_loader
 from tensorflow_lite_support.custom_ops.python import sentencepiece_tokenizer
-from tensorflow_lite_support.custom_ops.kernel.sentencepiece import pywrap_tflite_registerer
+from tensorflow_lite_support.custom_ops.kernel.sentencepiece.py import pywrap_tflite_registerer
 
 FLAGS = flags.FLAGS
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/testdata/wiki40b-lm-en.tflite b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/testdata/wiki40b-lm-en.tflite
new file mode 100644
index 0000000..15f5b49
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/testdata/wiki40b-lm-en.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/tflite_inference_main.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/tflite_inference_main.cc
deleted file mode 100644
index 2819dee..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/tflite_inference_main.cc
+++ /dev/null
@@ -1,105 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-// This program runs the tflite model specified in --model with random inputs.
-// For string type, the input is filled with a fixed string.
-
-#include <string>
-
-#include <glog/logging.h>
-#include "tensorflow/core/platform/init_main.h"
-#include "tensorflow/lite/c/common.h"
-#include "tensorflow/lite/interpreter.h"
-#include "tensorflow/lite/kernels/register.h"
-#include "tensorflow/lite/model.h"
-#include "tensorflow/lite/model_builder.h"
-#include "tensorflow/lite/string_util.h"
-#include "tensorflow/lite/tools/command_line_flags.h"
-
-void FillRandomString(tflite::DynamicBuffer* buffer,
-                      const TfLiteIntArray* dim_array,
-                      const std::function<std::string()>& random_func) {
-  int num_elements = 1;
-  for (size_t i = 0; i < dim_array->size; i++) {
-    num_elements *= dim_array->data[i];
-  }
-  for (int i = 0; i < num_elements; ++i) {
-    auto str = random_func();
-    buffer->AddString(str.data(), str.length());
-  }
-}
-
-void RunWithRandomInputs(const std::string& filename) {
-  std::unique_ptr<tflite::FlatBufferModel> model =
-      tflite::FlatBufferModel::BuildFromFile(filename.c_str());
-
-  // Build the interpreter
-  tflite::ops::builtin::BuiltinOpResolver resolver;
-  std::unique_ptr<tflite::Interpreter> interpreter;
-  if (tflite::InterpreterBuilder(*model, resolver)(&interpreter) != kTfLiteOk) {
-    LOG(FATAL) << "Could not initialize interpreter for TFLite model.";
-  }
-
-  // Resize input tensors, if desired.
-  if (interpreter->AllocateTensors() != kTfLiteOk) {
-    LOG(FATAL) << "Could not allocate tensor.";
-  }
-
-  // Fill the random data.
-  std::vector<std::vector<uint8_t>> sample;
-  for (int tensor_idx : interpreter->inputs()) {
-    auto tensor = interpreter->tensor(tensor_idx);
-    if (tensor->type == kTfLiteString) {
-      tflite::DynamicBuffer buffer;
-      FillRandomString(&buffer, tensor->dims, []() {
-        return "we're have some friends over saturday to hang out in the "
-               "yard";
-      });
-      buffer.WriteToTensor(tensor, /*new_shape=*/nullptr);
-    } else {
-      std::vector<uint8_t> data(tensor->bytes);
-      for (auto it = data.begin(); it != data.end(); ++it) {
-        *it = random();
-      }
-      sample.push_back(data);
-      tensor->data.raw = reinterpret_cast<char*>(sample.rbegin()->data());
-    }
-  }
-
-  // Running inference.
-  if (interpreter->Invoke() != kTfLiteOk) {
-    LOG(FATAL) << "Failed to run the model.";
-  }
-
-  // Get the output.
-  for (int tensor_idx : interpreter->outputs()) {
-    auto tensor = interpreter->tensor(tensor_idx);
-    LOG(INFO) << "Output type: " << TfLiteTypeGetName(tensor->type);
-  }
-}
-
-int main(int argc, char** argv) {
-  // Parse flags to get the filename.
-  std::string filename;
-  std::vector<tflite::Flag> flag_list{tflite::Flag::CreateFlag(
-      "model", &filename, "The tflite model to run sample inference.",
-      tflite::Flag::kRequired)};
-  tflite::Flags::Parse(&argc, const_cast<const char**>(argv), flag_list);
-  tensorflow::port::InitMain(argv[0], &argc, &argv);
-
-  // Run the model with random inputs.
-  RunWithRandomInputs(filename);
-  return 0;
-}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/tflite_inference_test.cc b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/tflite_inference_test.cc
new file mode 100644
index 0000000..79e0652
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/custom_ops/tflite_inference_test.cc
@@ -0,0 +1,109 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// This program runs the tflite model specified in --model with random inputs.
+// For string type, the input is filled with a fixed string.
+
+#include <string>
+
+#include <gmock/gmock.h>
+#include <gtest/gtest.h>
+#include "tensorflow/core/platform/logging.h"
+#include "tensorflow/lite/c/common.h"
+#include "tensorflow/lite/interpreter.h"
+#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/model.h"
+#include "tensorflow/lite/model_builder.h"
+#include "tensorflow/lite/string_util.h"
+
+void FillRandomString(tflite::DynamicBuffer* buffer,
+                      const TfLiteIntArray* dim_array,
+                      const std::function<std::string()>& random_func) {
+  int num_elements = 1;
+  for (size_t i = 0; i < dim_array->size; i++) {
+    num_elements *= dim_array->data[i];
+  }
+  for (int i = 0; i < num_elements; ++i) {
+    auto str = random_func();
+    buffer->AddString(str.data(), str.length());
+  }
+}
+
+bool RunWithRandomInputs(const std::string& filename) {
+  std::unique_ptr<tflite::FlatBufferModel> model =
+      tflite::FlatBufferModel::BuildFromFile(filename.c_str());
+
+  // Build the interpreter
+  tflite::ops::builtin::BuiltinOpResolver resolver;
+  std::unique_ptr<tflite::Interpreter> interpreter;
+  if (tflite::InterpreterBuilder(*model, resolver)(&interpreter) != kTfLiteOk) {
+    LOG(ERROR) << "Could not initialize interpreter for TFLite model.";
+    return false;
+  }
+
+  // Resize input tensors, if desired.
+  if (interpreter->AllocateTensors() != kTfLiteOk) {
+    LOG(ERROR) << "Could not allocate tensor.";
+    return false;
+  }
+
+  // Fill the random data.
+  std::vector<std::vector<uint8_t>> sample;
+  for (int tensor_idx : interpreter->inputs()) {
+    auto tensor = interpreter->tensor(tensor_idx);
+    if (tensor->type == kTfLiteString) {
+      tflite::DynamicBuffer buffer;
+      FillRandomString(&buffer, tensor->dims, []() {
+        return "we're have some friends over saturday to hang out in the "
+               "yard";
+      });
+      buffer.WriteToTensor(tensor, /*new_shape=*/nullptr);
+    } else {
+      std::vector<uint8_t> data(tensor->bytes);
+      for (auto it = data.begin(); it != data.end(); ++it) {
+        *it = random();
+      }
+      sample.push_back(data);
+      tensor->data.raw = reinterpret_cast<char*>(sample.rbegin()->data());
+    }
+  }
+
+  // Running inference.
+  if (interpreter->Invoke() != kTfLiteOk) {
+    LOG(ERROR) << "Failed to run the model.";
+    return false;
+  }
+
+  // Get the output.
+  for (int tensor_idx : interpreter->outputs()) {
+    auto tensor = interpreter->tensor(tensor_idx);
+    LOG(INFO) << "Output type: " << TfLiteTypeGetName(tensor->type);
+  }
+  return true;
+}
+
+TEST(SelectiveBuiltTest, SentencePieceTokenizerModel) {
+  std::string model =
+      "tensorflow_lite_support/custom_ops/testdata/"
+      "sentencepiece_tokenizer_flex_op.tflite";
+  EXPECT_THAT(RunWithRandomInputs(model), true);
+}
+
+TEST(SelectiveBuiltTest, Wiki40bLmEnModel) {
+  std::string model =
+      "tensorflow_lite_support/custom_ops/testdata/"
+      "wiki40b-lm-en.tflite";
+  EXPECT_THAT(RunWithRandomInputs(model), true);
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/BUILD
new file mode 100644
index 0000000..d70b641
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+config_setting(
+    name = "darwinn_portable",
+    values = {
+        "define": "darwinn_portable=1",
+    },
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/BUILD
new file mode 100644
index 0000000..fa6a12e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/BUILD
@@ -0,0 +1,46 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "audio_classifier_lib",
+    srcs = ["audio_classifier_lib.cc"],
+    hdrs = ["audio_classifier_lib.h"],
+    deps = [
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/audio/utils:wav_io",
+        "//tensorflow_lite_support/cc/task/audio:audio_classifier",
+        "//tensorflow_lite_support/cc/task/audio/core:audio_buffer",
+        "//tensorflow_lite_support/cc/task/audio/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/core:category",
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
+)
+
+# Example usage:
+# bazel run -c opt \
+#  tensorflow_lite_support/examples/task/audio/desktop:audio_classifier_demo \
+#  -- \
+#  --model_path=/path/to/model.tflite \
+#  --audio_wav_path=/path/to/wav.tflite
+cc_binary(
+    name = "audio_classifier_demo",
+    srcs = ["audio_classifier_demo.cc"],
+    deps = [
+        ":audio_classifier_lib",
+        "//tensorflow_lite_support/cc/task/audio:audio_classifier",
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/flags:parse",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/README.md
new file mode 100644
index 0000000..3c51aa4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/README.md
@@ -0,0 +1,98 @@
+# CLI Demos for C++ Audio Task APIs
+
+This folder contains simple command-line tools for easily trying out the C++
+Audio Task APIs.
+
+## Coral Integration
+
+Task Library now supports fast TFLite inference delegated onto
+[Coral Edge TPU devices](https://coral.ai/docs/edgetpu/inference/) on Linux and
+macOS. See the
+[documentation](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview#run_task_library_with_delegates)
+for more details.
+
+To run the demo on a Coral device, add `--define darwinn_portable=1` to the
+bazel command.
+
+Note the `libusb` package is required. It can be installed as follows:
+
+```bash
+# On Linux
+sudo apt-get install libusb-1.0-0-dev
+
+# On macOS using MacPorts
+port install libusb
+# or Homebrew
+brew install libusb
+```
+
+See the example commands in each task demo below.
+
+You can also explore more [pretrained Coral model](https://coral.ai/models) and
+try them in the demo. All the models have populated with
+[TFLite Model Metadata](https://www.tensorflow.org/lite/convert/metadata).
+
+## Audio Classification
+
+### Prerequisites
+You will need:
+
+-   a TFLite audio classification model with metadata (e.g.
+    https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1, an
+    environmental sound classification model available on TensorFlow Hub),
+-   a mono-channel 16-bit PCM WAV file. The sample rate of the WAV file should
+    be the same as what model requires (described in the Metadata).
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1?lite-format=tflite' \
+ -o /tmp/yamnet.tflite
+
+# Download the audio file:
+curl \
+ -L https://storage.googleapis.com/audioset/miaow_16k.wav \
+ -o /tmp/miao.wav
+
+# Run the classification tool:
+bazel run -c opt \
+ tensorflow_lite_support/examples/task/audio/desktop:audio_classifier_demo -- \
+  --model_path=/tmp/yamnet.tflite \
+  --score_threshold=0.5 \
+  --audio_wav_path=/tmp/miao.wav
+```
+
+To run the demo on a [Coral Edge TPU device](https://coral.ai/products/), check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the Coral model:
+curl \
+ -L 'https://tfhub.dev/google/coral-model/yamnet/classification/coral/1?coral-format=tflite' \
+ -o /tmp/yamnet_edgetpu.tflite
+
+# Run the classification tool:
+bazel run -c opt --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/audio/desktop:audio_classifier_demo -- \
+  --model_path=/tmp/yamnet_edgetpu.tflite \
+  --audio_wav_path=/path/to/the/audio_file.wav \
+  --score_threshold=0.5 \
+  --use_coral=true
+```
+
+### Results
+In the console, you should get:
+
+```bash
+Time cost to classify the input audio clip on CPU: 51.4087 ms
+Note: Only showing classes with score higher than 0.5
+
+Head[0]: scores
+	category[Cat]: 0.73828
+	category[Animal]: 0.66797
+	category[Domestic animals, pets]: 0.66797
+```
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc
new file mode 100644
index 0000000..6339ed7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_demo.cc
@@ -0,0 +1,77 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Example usage:
+// bazel run -c opt \
+//  tensorflow_lite_support/examples/task/audio/desktop:audio_classifier_demo \
+//  -- \
+//  --model_path=/path/to/model.tflite \
+//  --audio_wav_path=/path/to/audio.wav
+
+#include <cstddef>
+#include <iostream>
+#include <limits>
+
+#include "absl/flags/flag.h"   // from @com_google_absl
+#include "absl/flags/parse.h"  // from @com_google_absl
+#include "tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h"
+
+ABSL_FLAG(std::string,
+          model_path,
+          "",
+          "Absolute path to the '.tflite' audio classification model.");
+ABSL_FLAG(std::string,
+          audio_wav_path,
+          "",
+          "Absolute path to the 16-bit PCM WAV file to classify. The WAV "
+          "file must be monochannel and has a sampling rate matches the model "
+          "expected sampling rate (as in the Metadata).  If the WAV file is "
+          "longer than what the model requires, only the beginning section is "
+          "used for inference.");
+ABSL_FLAG(float,
+          score_threshold,
+          0.001f,
+          "Apply a filter on the results. Only display classes with score "
+          "higher than the threshold.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
+
+int main(int argc, char** argv) {
+  // Parse command line arguments and perform sanity checks.
+  absl::ParseCommandLine(argc, argv);
+  if (absl::GetFlag(FLAGS_model_path).empty()) {
+    std::cerr << "Missing mandatory 'model_path' argument.\n";
+    return 1;
+  }
+  if (absl::GetFlag(FLAGS_audio_wav_path).empty()) {
+    std::cerr << "Missing mandatory 'audio_wav_path' argument.\n";
+    return 1;
+  }
+
+  // Run classification.
+  auto result = tflite::task::audio::Classify(
+      absl::GetFlag(FLAGS_model_path), absl::GetFlag(FLAGS_audio_wav_path),
+      absl::GetFlag(FLAGS_use_coral));
+  if (result.ok()) {
+    tflite::task::audio::Display(result.value(),
+                                 absl::GetFlag(FLAGS_score_threshold));
+  } else {
+    std::cerr << "Classification failed: " << result.status().message() << "\n";
+    return 1;
+  }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc
new file mode 100644
index 0000000..a843501
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.cc
@@ -0,0 +1,116 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h"
+
+#include <iostream>
+#include <string>
+#include <vector>
+
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/audio_classifier.h"
+#include "tensorflow_lite_support/cc/task/audio/core/audio_buffer.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/audio/utils/wav_io.h"
+#include "tensorflow_lite_support/cc/task/core/category.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+tflite::support::StatusOr<AudioBuffer> LoadAudioBufferFromFile(
+    const std::string& wav_file,
+    int buffer_size,
+    std::vector<float>* wav_data) {
+  std::string contents = ReadFile(wav_file);
+
+  uint32 decoded_sample_count;
+  uint16 decoded_channel_count;
+  uint32 decoded_sample_rate;
+  RETURN_IF_ERROR(DecodeLin16WaveAsFloatVector(
+      contents, wav_data, &decoded_sample_count, &decoded_channel_count,
+      &decoded_sample_rate));
+
+  if (decoded_sample_count > buffer_size) {
+    decoded_sample_count = buffer_size;
+  }
+
+  return AudioBuffer(
+      wav_data->data(), decoded_sample_count,
+      {decoded_channel_count, static_cast<int>(decoded_sample_rate)});
+}
+
+tflite::support::StatusOr<ClassificationResult> Classify(
+    const std::string& model_path,
+    const std::string& wav_file,
+    bool use_coral) {
+  AudioClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      model_path);
+  if (use_coral) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
+  ASSIGN_OR_RETURN(std::unique_ptr<AudioClassifier> classifier,
+                   AudioClassifier::CreateFromOptions(options));
+
+  // `wav_data` holds data loaded from the file and needs to outlive `buffer`.
+  std::vector<float> wav_data;
+  ASSIGN_OR_RETURN(
+      AudioBuffer buffer,
+      LoadAudioBufferFromFile(
+          wav_file, classifier->GetRequiredInputBufferSize(), &wav_data));
+
+  auto start_classify = std::chrono::steady_clock::now();
+  ASSIGN_OR_RETURN(ClassificationResult result, classifier->Classify(buffer));
+  auto end_classify = std::chrono::steady_clock::now();
+  std::string delegate = use_coral ? "Coral Edge TPU" : "CPU";
+  const auto duration_ms =
+      std::chrono::duration<float, std::milli>(end_classify - start_classify);
+  std::cout << "Time cost to classify the input audio clip on " << delegate
+            << ": " << duration_ms.count() << " ms" << std::endl;
+
+  return result;
+}
+
+void Display(const ClassificationResult& result, float score_threshold) {
+  std::cout << "Note: Only showing classes with score higher than "
+            << score_threshold << std::endl;
+
+  for (int i = 0; i < result.classifications_size(); i++) {
+    const auto& head = result.classifications(i);
+    std::cout << absl::StrFormat("\nHead[%d]: %s\n", i, head.head_name());
+    for (int j = 0; j < head.classes_size(); j++) {
+      const auto& category = head.classes(j);
+      if (category.score() < score_threshold)
+        continue;
+      std::cout << absl::StrFormat("\tcategory[%s]: %.5f\t",
+                                   category.class_name(), category.score());
+      if (!category.display_name().empty()) {
+        std::cout << category.display_name();
+      }
+      std::cout << std::endl;
+    }
+  }
+}
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h
new file mode 100644
index 0000000..13b2d77
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/audio_classifier_lib.h
@@ -0,0 +1,43 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_AUDIO_DESKTOP_AUDIO_CLASSIFIER_LIB_H_
+#define TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_AUDIO_DESKTOP_AUDIO_CLASSIFIER_LIB_H_
+
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/core/audio_buffer.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h"
+
+namespace tflite {
+namespace task {
+namespace audio {
+
+// Loads `wav_file` from filesystem and runs classification using TFLite model
+// in `model_path` with default options. If the content of `wav_file` is longer
+// than what the model requires, only the beginning section is used for
+// inference.
+tflite::support::StatusOr<ClassificationResult> Classify(
+    const std::string& model_path,
+    const std::string& wav_file,
+    bool use_coral = false);
+
+// Prints the output classification result in the standard output. It only
+// displays classes whose score is higher than the `score_threshold`.
+void Display(const ClassificationResult& result, float score_threshold);
+
+}  // namespace audio
+}  // namespace task
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_AUDIO_DESKTOP_AUDIO_CLASSIFIER_LIB_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/BUILD
new file mode 100644
index 0000000..20b4db24
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/BUILD
@@ -0,0 +1,21 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+# bazel run \
+# tensorflow_lite_support/examples/task/audio/desktop/python:audio_classifier_demo \
+# -- \
+# --model_path=/path/to/model.tflite \
+# --audio="What a waste of my time."
+py_binary(
+    name = "audio_classifier_demo",
+    srcs = ["audio_classifier_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/audio/desktop:audio_classifier_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/README.md
new file mode 100644
index 0000000..f3e30073
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/README.md
@@ -0,0 +1,109 @@
+# CLI Demos for Python Audio Task APIs
+
+A Python wrapper for the C++ Audio Task APIs.
+
+## Background
+
+This Python API is based on the C++ Audio Task APIs. It uses Python's
+[subprocess](https://docs.python.org/3/library/subprocess.html) to call C++ Audio
+Task APIs.
+
+## Coral Integration
+
+Task Library now supports fast TFLite inference delegated onto
+[Coral Edge TPU devices](https://coral.ai/docs/edgetpu/inference/) on Linux and
+macOS. See the
+[documentation](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview#run_task_library_with_delegates)
+for more details.
+
+To run the demo on a Coral device, add `--define darwinn_portable=1` to the
+bazel command.
+
+Note the `libusb` package is required. It can be installed as follows:
+
+```bash
+# On Linux
+sudo apt-get install libusb-1.0-0-dev
+
+# On macOS using MacPorts
+port install libusb
+# or Homebrew
+brew install libusb
+```
+
+See the example commands in each task demo below.
+
+You can also explore more [pretrained Coral model](https://coral.ai/models) and
+try them in the demo. All the models have populated with
+[TFLite Model Metadata](https://www.tensorflow.org/lite/convert/metadata).
+
+## Audio Classification
+
+### Prerequisites
+You will need:
+
+-   a TFLite audio classification model with metadata (e.g.
+    https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1, an
+    environmental sound classification model available on TensorFlow Hub),
+-   a mono-channel 16-bit PCM WAV file. The sample rate of the WAV file should
+    be the same as what model requires (described in the Metadata).
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1?lite-format=tflite' \
+ -o /tmp/yamnet.tflite
+
+# Download the audio file:
+curl \
+ -L https://storage.googleapis.com/audioset/miaow_16k.wav \
+ -o /tmp/miao.wav
+```
+
+##### Build the demo from source
+
+Run the classification tool:
+
+```bash
+bazel run \
+ tensorflow_lite_support/examples/task/audio/desktop/python:audio_classifier_demo -- \
+  --model_path=/tmp/yamnet.tflite \
+  --score_threshold=0.5 \
+  --audio_wav_path=/tmp/miao.wav
+```
+
+To run the demo on a [Coral Edge TPU device](https://coral.ai/products/), check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the Coral model:
+curl \
+ -L 'https://tfhub.dev/google/coral-model/yamnet/classification/coral/1?coral-format=tflite' \
+ -o /tmp/yamnet_edgetpu.tflite
+
+# Run the classification tool:
+bazel run --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/audio/desktop/python:audio_classifier_demo -- \
+  --model_path=/tmp/yamnet_edgetpu.tflite \
+  --audio_wav_path=/path/to/the/audio_file.wav \
+  --score_threshold=0.5 \
+  --use_coral=true
+```
+
+#### Results
+
+In the console, you should get:
+
+```bash
+Time cost to classify the input audio clip on CPU: 51.4087 ms
+Note: Only showing classes with score higher than 0.5
+
+Head[0]: scores
+	category[Cat]: 0.73828
+	category[Animal]: 0.66797
+	category[Domestic animals, pets]: 0.66797
+```
\ No newline at end of file
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/audio_classifier_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/audio_classifier_demo.py
new file mode 100644
index 0000000..07b6bf9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/audio/desktop/python/audio_classifier_demo.py
@@ -0,0 +1,87 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for Audio Classification."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+flags.DEFINE_string(
+    'model_path', None,
+    'Absolute path to the ".tflite" audio classification model.')
+flags.DEFINE_string(
+    'audio_wav_path', None,
+    'Absolute path to the 16-bit PCM WAV file to classify. The WAV '
+    'file must be monochannel and has a sampling rate matches the model '
+    'expected sampling rate (as in the Metadata).  If the WAV file is '
+    'longer than what the model requires, only the beginning section is '
+    'used for inference.')
+flags.DEFINE_float(
+    'score_threshold', None,
+    'Apply a filter on the results. Only display classes with score '
+    'higher than the threshold.')
+flags.DEFINE_bool(
+    'use_coral', False,
+    'If true, inference will be delegated to a connected Coral Edge TPU '
+    'device.')
+
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('score_threshold')
+flags.mark_flag_as_required('audio_wav_path')
+
+_AUDIO_CLASSIFICATION_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../audio_classifier_demo')
+
+
+def classify(model_path, score_threshold, audio_wav_path, use_coral):
+  """Classifies input audio clip into different categories.
+
+  Args:
+      model_path: Path to model
+      score_threshold: Absolute path to the 16-bit PCM WAV file to classify
+      audio_wav_path: Apply a filter on the results
+      use_coral: Optional; If true, inference will be delegated to a connected 
+        Coral Edge TPU device.
+  """
+  # Run the classification tool:
+  subprocess.run([
+      _AUDIO_CLASSIFICATION_NATIVE_PATH + ' --model_path=' + model_path +
+      ' --score_threshold=' + str(score_threshold) + ' --audio_wav_path="' +
+      audio_wav_path + '" --use_coral=' + str(use_coral)
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.score_threshold, FLAGS.audio_wav_path,
+           FLAGS.use_coral)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/BUILD
index 067d59c..2d69942 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/BUILD
@@ -1,6 +1,6 @@
 package(
     default_visibility = [
-        "//tensorflow_lite_support:users",
+        "//tensorflow_lite_support:internal",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
@@ -16,13 +16,19 @@
     name = "bert_question_answerer_demo",
     srcs = ["bert_question_answerer_demo.cc"],
     deps = [
-        "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/text/qa:bert_question_answerer",
         "@com_google_absl//absl/flags:flag",
         "@com_google_absl//absl/flags:parse",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings:str_format",
-    ],
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/text:bert_question_answerer",
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
 )
 
 # Example usage:
@@ -35,14 +41,20 @@
     name = "bert_nl_classifier_demo",
     srcs = ["bert_nl_classifier_demo.cc"],
     deps = [
-        "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/core:category",
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier",
         "@com_google_absl//absl/flags:flag",
         "@com_google_absl//absl/flags:parse",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings:str_format",
-    ],
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:category",
+        "//tensorflow_lite_support/cc/task/text:bert_nl_classifier",
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
 )
 
 # Example usage:
@@ -57,12 +69,40 @@
     name = "nl_classifier_demo",
     srcs = ["nl_classifier_demo.cc"],
     deps = [
-        "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/core:category",
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
         "@com_google_absl//absl/flags:flag",
         "@com_google_absl//absl/flags:parse",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings:str_format",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:category",
+        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
+)
+
+# Example usage:
+# bazel run -c opt \
+#  tensorflow_lite_support/examples/task/text/desktop:universal_sentence_encoder_qa_main \
+#  -- \
+#  --model_path=/path/to/model_with_metadata.tflite
+cc_binary(
+    name = "universal_sentence_encoder_qa_demo",
+    srcs = [
+        "universal_sentence_encoder_qa_demo.cc",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/task/text:universal_sentence_encoder_qa",
+        "//tensorflow_lite_support/custom_ops/kernel/ragged:py_tflite_registerer",
+        "//tensorflow_lite_support/custom_ops/kernel/sentencepiece:py_tflite_registerer",
+        "//tensorflow_lite_support/custom_ops/kernel/sentencepiece:sentencepiece_tokenizer_op",
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/flags:parse",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/README.md
index 859504f..ecd925b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/README.md
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/README.md
@@ -9,8 +9,8 @@
 
 You will need:
 
-* a TFLite bert based question answerer model from model maker.
-(e.g. [mobilebert][1] or [albert][2] available on TensorFlow Hub).
+*   a TFLite bert based question answerer model from model maker. (e.g.
+    [mobilebert][1] or [albert][2] available on TensorFlow Hub).
 
 #### Usage
 
@@ -19,7 +19,7 @@
 ```bash
 # Download the model:
 curl \
- -L 'https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1?lite-format=tflite' \
+ -L 'https://tfhub.dev/tensorflow/lite-model/mobilebert/1/metadata/1?lite-format=tflite' \
  -o /tmp/mobilebert.tflite
 
 # Run the classification tool:
@@ -40,6 +40,7 @@
 In the console, you should get:
 
 ```
+Time cost to answer the input question on CPU: 783 ms
 answer[0]:  'South America.'
 logit: 1.84847, start_index: 39, end_index: 40
 answer[1]:  'most of the Amazon basin of South America.'
@@ -58,10 +59,8 @@
 
 You will need:
 
-* a TFLite text classification model with certain format.
-(e.g. [movie_review_model][3], a model to classify movie reviews), you'll need
-to configure the input tensor and out tensor for the API, see the [doc][4] for 
-details.
+*   a TFLite text classification model with certain format. (e.g.
+    [movie_review_model][3], a model to classify movie reviews).
 
 #### Usage
 
@@ -77,9 +76,7 @@
 bazel run -c opt \
  tensorflow_lite_support/examples/task/text/desktop:nl_classifier_demo -- \
  --model_path=/tmp/movie_review.tflite \
- --text="What a waste of my time." \
- --input_tensor_name="input_text" \
- --output_score_tensor_name="probability"
+ --text="What a waste of my time."
 ```
 
 #### Results
@@ -87,6 +84,7 @@
 In the console, you should get:
 
 ```
+Time cost to classify the input text on CPU: 0.088 ms
 category[0]: 'Negative' : '0.81313'
 category[1]: 'Positive' : '0.18687'
 ```
@@ -99,7 +97,8 @@
 
 You will need:
 
-* a Bert based TFLite text classification model from model maker. (e.g. [movie_review_model][5] available on TensorFlow Hub).
+*   a Bert based TFLite text classification model from model maker. (e.g.
+    [movie_review_model][5] available on TensorFlow Hub).
 
 #### Usage
 
@@ -123,12 +122,49 @@
 In the console, you should get:
 
 ```
+Time cost to classify the input text on CPU: 491 ms
 category[0]: 'negative' : '0.00006'
 category[1]: 'positive' : '0.99994'
 ```
 
+## UniversalSentenceEncoderQA
+
+#### Prerequisites
+
+You will need:
+
+*   a universal sentence encoder QA model from [TensorFlow Hub][6].
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://tfhub.dev/google/lite-model/universal-sentence-encoder-qa-ondevice/1?lite-format=tflite' \
+ -o /tmp/universal_sentence_encoder_qa_with_metadata.tflite
+
+# Run UniversalSentenceEncoderQA model:
+bazel run -c opt \
+ tensorflow_lite_support/examples/task/text/desktop:universal_sentence_encoder_qa_demo -- \
+ --model_path=/tmp/universal_sentence_encoder_qa_with_metadata.tflite
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+How are you feeling today?
+I'm not feeling very well., , 14.9595
+He looks good., , 8.80944
+Paris is the capital of France., , 5.63753
+```
+
 [1]: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
 [2]: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
 [3]: https://www.tensorflow.org/lite/models/text_classification/overview
 [4]: https://github.com/tensorflow/tflite-support/blob/fe8b69002f5416900285dc69e2baa078c91bd994/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h#L55
 [5]: http://bert/nl/classifier/model
+[6]: https://tfhub.dev/google/lite-model/universal-sentence-encoder-qa-ondevice/1
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc
index e88d565..52032008 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_nl_classifier_demo.cc
@@ -15,32 +15,59 @@
 #include <iostream>
 #include <limits>
 
-#include "absl/flags/flag.h"
-#include "absl/flags/parse.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/category.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h"
+#include "tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
 
 ABSL_FLAG(std::string,
           model_path,
           "",
           "Absolute path to the '.tflite' bert classification model.");
 ABSL_FLAG(std::string, text, "", "Text to classify.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
 
 namespace tflite {
 namespace task {
 namespace text {
-namespace nlclassifier {
+
+namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+}  // namespace
 
 absl::Status Classify() {
-  ASSIGN_OR_RETURN(
-      std::unique_ptr<BertNLClassifier> classifier,
-      BertNLClassifier::CreateFromFile(absl::GetFlag(FLAGS_model_path)));
+  BertNLClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      absl::GetFlag(FLAGS_model_path));
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
 
+  ASSIGN_OR_RETURN(std::unique_ptr<BertNLClassifier> classifier,
+                   BertNLClassifier::CreateFromOptions(options));
+
+  auto start_classify = steady_clock::now();
   std::vector<core::Category> categories =
       classifier->Classify(absl::GetFlag(FLAGS_text));
+  auto end_classify = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to classify the input text on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_classify -
+                                                        start_classify)
+                   .count()
+            << " ms" << std::endl;
 
   for (int i = 0; i < categories.size(); ++i) {
     const core::Category& category = categories[i];
@@ -51,7 +78,6 @@
   return absl::OkStatus();
 }
 
-}  // namespace nlclassifier
 }  // namespace text
 }  // namespace task
 }  // namespace tflite
@@ -69,7 +95,7 @@
   }
 
   // Run classification.
-  absl::Status status = tflite::task::text::nlclassifier::Classify();
+  absl::Status status = tflite::task::text::Classify();
   if (status.ok()) {
     return 0;
   } else {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc
index 534b86a..f2577cf 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/bert_question_answerer_demo.cc
@@ -15,12 +15,12 @@
 #include <iostream>
 #include <limits>
 
-#include "absl/flags/flag.h"
-#include "absl/flags/parse.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
-#include "tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h"
+#include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
 
 ABSL_FLAG(std::string,
           model_path,
@@ -31,19 +31,47 @@
           context,
           "",
           "Context the asked question is based upon.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
 
 namespace tflite {
 namespace task {
 namespace text {
-namespace qa {
+
+namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+}  // namespace
 
 absl::Status Answer() {
-  ASSIGN_OR_RETURN(
-      std::unique_ptr<QuestionAnswerer> answerer,
-      BertQuestionAnswerer::CreateFromFile(absl::GetFlag(FLAGS_model_path)));
+  BertQuestionAnswererOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      absl::GetFlag(FLAGS_model_path));
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
 
+  ASSIGN_OR_RETURN(std::unique_ptr<QuestionAnswerer> answerer,
+                   BertQuestionAnswerer::CreateFromOptions(options));
+
+  auto start_answer = steady_clock::now();
   std::vector<QaAnswer> answers = answerer->Answer(
       absl::GetFlag(FLAGS_context), absl::GetFlag(FLAGS_question));
+  auto end_answer = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to answer the input question on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_answer -
+                                                        start_answer)
+                   .count()
+            << " ms" << std::endl;
+
   for (int i = 0; i < answers.size(); ++i) {
     const QaAnswer& answer = answers[i];
     std::cout << absl::StrFormat(
@@ -54,7 +82,6 @@
   return absl::OkStatus();
 }
 
-}  // namespace qa
 }  // namespace text
 }  // namespace task
 }  // namespace tflite
@@ -75,7 +102,7 @@
     return 1;
   }
   // Run the answerer.
-  absl::Status status = tflite::task::text::qa::Answer();
+  absl::Status status = tflite::task::text::Answer();
   if (status.ok()) {
     return 0;
   } else {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc
index 9e62714..613744ff 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/nl_classifier_demo.cc
@@ -15,10 +15,10 @@
 #include <iostream>
 #include <limits>
 
-#include "absl/flags/flag.h"
-#include "absl/flags/parse.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/category.h"
 #include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
@@ -28,64 +28,47 @@
           "",
           "Absolute path to the '.tflite' classification model.");
 ABSL_FLAG(std::string, text, "", "Text to classify.");
-ABSL_FLAG(int, input_tensor_index, -1, "Input tensor index of the model.");
-ABSL_FLAG(int,
-          output_score_tensor_index,
-          -1,
-          "Output score tensor index of the model.");
-ABSL_FLAG(int,
-          output_label_tensor_index,
-          -1,
-          "Output label tensor index of the model.");
-ABSL_FLAG(std::string,
-          input_tensor_name,
-          "",
-          "Input tensor name of the model.");
-ABSL_FLAG(std::string,
-          output_score_tensor_name,
-          "",
-          "Output score tensor name of the model.");
-ABSL_FLAG(std::string,
-          output_label_tensor_name,
-          "",
-          "Output label tensor name of the model.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
 
 namespace tflite {
 namespace task {
 namespace text {
 namespace nlclassifier {
 
+namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+}  // namespace
+
 absl::Status Classify() {
-  NLClassifierOptions options{};
-  if (absl::GetFlag(FLAGS_input_tensor_index) >= 0) {
-    options.input_tensor_index = absl::GetFlag(FLAGS_input_tensor_index);
-  }
-  if (absl::GetFlag(FLAGS_output_score_tensor_index) >= 0) {
-    options.output_score_tensor_index =
-        absl::GetFlag(FLAGS_output_score_tensor_index);
-  }
-  if (absl::GetFlag(FLAGS_output_label_tensor_index) >= 0) {
-    options.output_label_tensor_index =
-        absl::GetFlag(FLAGS_output_label_tensor_index);
-  }
-  if (!absl::GetFlag(FLAGS_input_tensor_name).empty()) {
-    options.input_tensor_name = absl::GetFlag(FLAGS_input_tensor_name);
-  }
-  if (!absl::GetFlag(FLAGS_output_score_tensor_name).empty()) {
-    options.output_score_tensor_name =
-        absl::GetFlag(FLAGS_output_score_tensor_name);
-  }
-  if (!absl::GetFlag(FLAGS_output_label_tensor_name).empty()) {
-    options.output_label_tensor_name =
-        absl::GetFlag(FLAGS_output_label_tensor_name);
+  tflite::task::text::NLClassifierOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      absl::GetFlag(FLAGS_model_path));
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
   }
 
   ASSIGN_OR_RETURN(std::unique_ptr<NLClassifier> classifier,
-                   NLClassifier::CreateFromFileAndOptions(
-                       absl::GetFlag(FLAGS_model_path), options));
+                   NLClassifier::CreateFromOptions(options));
 
+  auto start_classify = steady_clock::now();
   std::vector<core::Category> categories =
       classifier->Classify(absl::GetFlag(FLAGS_text));
+  auto end_classify = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to classify the input text on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_classify -
+                                                        start_classify)
+                   .count()
+            << " ms" << std::endl;
 
   for (int i = 0; i < categories.size(); ++i) {
     const core::Category& category = categories[i];
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/BUILD
new file mode 100644
index 0000000..06ae5a7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/BUILD
@@ -0,0 +1,56 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+# bazel run \
+# tensorflow_lite_support/examples/task/text/desktop/python:nl_classifier_demo \
+# -- \
+# --model_path=/path/to/model.tflite \
+# --text="What a waste of my time."
+py_binary(
+    name = "nl_classifier_demo",
+    srcs = ["nl_classifier_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/text/desktop:nl_classifier_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
+
+# bazel run \
+# tensorflow_lite_support/examples/task/text/desktop/python:bert_nl_classifier_demo \
+# -- \
+# --model_path=/path/to/model.tflite \
+# --text="it's a charming and often affecting journey"
+py_binary(
+    name = "bert_nl_classifier_demo",
+    srcs = ["bert_nl_classifier_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/text/desktop:bert_nl_classifier_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
+
+# bazel run \
+#  tensorflow_lite_support/examples/task/text/desktop/python:bert_question_answerer_demo -- \
+#  --model_path=/tmp/mobilebert.tflite \
+#  --question="Where is Amazon rainforest?" \
+#  --context="The Amazon rainforest, alternatively, the Amazon Jungle, also known in \
+# English as Amazonia, is a moist broadleaf tropical rainforest in the Amazon \
+# biome that covers most of the Amazon basin of South America. This basin \
+# encompasses 7,000,000 km2 (2,700,000 sq mi), of which \
+# 5,500,000 km2 (2,100,000 sq mi) are covered by the rainforest. This region \
+# includes territory belonging to nine nations."
+py_binary(
+    name = "bert_question_answerer_demo",
+    srcs = ["bert_question_answerer_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/text/desktop:bert_question_answerer_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/README.md
new file mode 100644
index 0000000..b24ee79
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/README.md
@@ -0,0 +1,147 @@
+# CLI Demos for Python Text Task APIs
+
+A Python wrapper for the C++ Text Task APIs.
+
+## Background
+
+This Python API is based on the C++ Text Task APIs. It uses Python's
+[subprocess](https://docs.python.org/3/library/subprocess.html) to call C++ Text
+Task APIs.
+
+## Bert Question Answerer
+
+#### Prerequisites
+
+You will need:
+
+*   a TFLite bert based question answerer model from model maker. (e.g.
+    [mobilebert][1] or [albert][2] available on TensorFlow Hub).
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://tfhub.dev/tensorflow/lite-model/mobilebert/1/metadata/1?lite-format=tflite' \
+ -o /tmp/mobilebert.tflite
+
+# Run the classification tool:
+bazel run \
+ tensorflow_lite_support/examples/task/text/desktop/python:bert_question_answerer_demo -- \
+ --model_path=/tmp/mobilebert.tflite \
+ --question="Where is Amazon rainforest?" \
+ --context="The Amazon rainforest, alternatively, the Amazon Jungle, also known in \
+English as Amazonia, is a moist broadleaf tropical rainforest in the Amazon \
+biome that covers most of the Amazon basin of South America. This basin \
+encompasses 7,000,000 km2 (2,700,000 sq mi), of which \
+5,500,000 km2 (2,100,000 sq mi) are covered by the rainforest. This region \
+includes territory belonging to nine nations."
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+Time cost to answer the input question on CPU: 783 ms
+answer[0]:  'South America.'
+logit: 1.84847, start_index: 39, end_index: 40
+answer[1]:  'most of the Amazon basin of South America.'
+logit: 1.2921, start_index: 34, end_index: 40
+answer[2]:  'the Amazon basin of South America.'
+logit: -0.0959535, start_index: 36, end_index: 40
+answer[3]:  'the Amazon biome that covers most of the Amazon basin of South America.'
+logit: -0.498558, start_index: 28, end_index: 40
+answer[4]:  'Amazon basin of South America.'
+logit: -0.774266, start_index: 37, end_index: 40
+```
+
+## NLClassifier
+
+#### Prerequisites
+
+You will need:
+
+*   a TFLite text classification model with certain format. (e.g.
+    [movie_review_model][3], a model to classify movie reviews).
+
+#### Usage
+
+First, download the pretrained model by:
+
+```bash
+curl \
+ -L 'https://storage.googleapis.com/download.tensorflow.org/models/tflite/text_classification/text_classification_v2.tflite' \
+ -o /tmp/movie_review.tflite
+```
+
+##### Build the demo from source
+
+Run the demo tool:
+
+```bash
+bazel run \
+ tensorflow_lite_support/examples/task/text/desktop/python:nl_classifier_demo \
+ -- \
+ --model_path=/tmp/movie_review.tflite \
+ --text="What a waste of my time."
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+Time cost to classify the input text on CPU: 0.088 ms
+category[0]: 'Negative' : '0.81313'
+category[1]: 'Positive' : '0.18687'
+```
+
+## BertNLClassifier
+
+#### Prerequisites
+
+You will need:
+
+*   a Bert based TFLite text classification model from model maker. (e.g.
+    [movie_review_model][5] available on TensorFlow Hub).
+
+#### Usage
+
+First, download the pretrained model by:
+
+```bash
+curl \
+ -L 'https://url/to/bert/nl/classifier' \
+ -o /tmp/bert_movie_review.tflite
+```
+
+##### Build the demo from source
+
+Run the demo tool:
+
+```bash
+bazel run \
+ tensorflow_lite_support/examples/task/text/desktop/python:bert_nl_classifier_demo \
+ -- \
+ --model_path=/tmp/bert_movie_review.tflite \
+ --text="it's a charming and often affecting journey"
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+Time cost to classify the input text on CPU: 491 ms
+category[0]: 'negative' : '0.00006'
+category[1]: 'positive' : '0.99994'
+```
+
+[1]: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
+[2]: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
+[3]: https://www.tensorflow.org/lite/models/text_classification/overview
+[4]: https://github.com/tensorflow/tflite-support/blob/fe8b69002f5416900285dc69e2baa078c91bd994/tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h#L55
+[5]: http://bert/nl/classifier/model
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/bert_nl_classifier_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/bert_nl_classifier_demo.py
new file mode 100644
index 0000000..4fed738
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/bert_nl_classifier_demo.py
@@ -0,0 +1,65 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for BertNLClassifier."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+flags.DEFINE_string('model_path', None, 'Model Path')
+flags.DEFINE_string('text', None, 'Text to Predict')
+
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('text')
+
+_BERT_NL_CLASSIFIER_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../bert_nl_classifier_demo')
+
+
+def classify(model_path, text):
+  """Classifies input text into different categories.
+
+  Args:
+      model_path: path to model
+      text: input text
+  """
+  # Run the detection tool:
+  subprocess.run([
+      _BERT_NL_CLASSIFIER_NATIVE_PATH + ' --model_path=' + model_path +
+      ' --text="' + text + '"'
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.text)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/bert_question_answerer_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/bert_question_answerer_demo.py
new file mode 100644
index 0000000..7276c0b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/bert_question_answerer_demo.py
@@ -0,0 +1,78 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for BertQuestionAnswerer."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+flags.DEFINE_string(
+    'model_path', None,
+    'Absolute path to the ".tflite" bert question answerer model.')
+flags.DEFINE_string('question', None, 'Question to ask.')
+flags.DEFINE_string('context', None,
+                    'Context the asked question is based upon.')
+flags.DEFINE_bool(
+    'use_coral', False,
+    'If true, inference will be delegated to a connected Coral Edge TPU device.'
+)
+
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('question')
+flags.mark_flag_as_required('context')
+
+_BERT_QUESTION_ANSWERER_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../bert_question_answerer_demo')
+
+
+def classify(model_path, question, context, use_coral):
+  """Predicts the answers for the given question based on the given context
+
+  Args:
+      model_path: Path to model
+      question: Question to ask
+      context: Context the asked question is based upon
+      use_coral: Optional; If true, inference will be delegated to a connected 
+        Coral Edge TPU device.
+  """
+  # Run the detection tool:
+  subprocess.run([
+      _BERT_QUESTION_ANSWERER_NATIVE_PATH + ' --model_path=' + model_path +
+      ' --question="' + question + '" --context="' + context +
+      '" --use_coral=' + str(use_coral)
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.question, FLAGS.context, FLAGS.use_coral)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/nl_classifier_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/nl_classifier_demo.py
new file mode 100644
index 0000000..3b3bda3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/python/nl_classifier_demo.py
@@ -0,0 +1,65 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for NLClassifier."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+flags.DEFINE_string('model_path', None, 'Model Path')
+flags.DEFINE_string('text', None, 'Text to Predict')
+
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('text')
+
+_NL_CLASSIFIER_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../nl_classifier_demo')
+
+
+def classify(model_path, text):
+  """Classifies input text into different categories.
+
+  Args:
+      model_path: path to model
+      text: input text
+  """
+  # Run the detection tool:
+  subprocess.run([
+      _NL_CLASSIFIER_NATIVE_PATH + ' --model_path=' + model_path + ' --text="' +
+      text + '"'
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.text)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc
new file mode 100644
index 0000000..8ba00cb
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/text/desktop/universal_sentence_encoder_qa_demo.cc
@@ -0,0 +1,91 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Demostration the usage of UniversalSentenceEncoderQA.
+#include "absl/flags/flag.h"         // from @com_google_absl
+#include "absl/flags/parse.h"        // from @com_google_absl
+#include "absl/status/status.h"      // from @com_google_absl
+#include "absl/strings/str_split.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/task/text/universal_sentence_encoder_qa.h"
+using tflite::task::text::RetrievalInput;
+using tflite::task::text::RetrievalOptions;
+using tflite::task::text::RetrievalOutput;
+using tflite::task::text::retrieval::UniversalSentenceEncoderQA;
+
+ABSL_FLAG(std::string,
+          model_path,
+          "",
+          "Absolute path to the '.tflite' UniversalSentenceEncoderQA model.");
+ABSL_FLAG(std::string,
+          question,
+          "How are you feeling today?",
+          "Question to ask.");
+ABSL_FLAG(
+    std::string,
+    answers,
+    "I'm not feeling very well.:Paris is the capital of France.:He looks good.",
+    "Candidate answers seperated by `:`.");
+
+int main(int argc, char** argv) {
+  // Parse command line arguments and perform sanity checks.
+  absl::ParseCommandLine(argc, argv);
+  if (absl::GetFlag(FLAGS_model_path).empty()) {
+    std::cerr << "Missing mandatory 'model_path' argument.\n";
+    return 1;
+  }
+  if (absl::GetFlag(FLAGS_question).empty()) {
+    std::cerr << "Missing mandatory 'question' argument.\n";
+    return 1;
+  }
+  if (absl::GetFlag(FLAGS_answers).empty()) {
+    std::cerr << "Missing mandatory 'answers' argument.\n";
+    return 1;
+  }
+
+  RetrievalOptions options;
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
+      absl::GetFlag(FLAGS_model_path));
+  auto status = UniversalSentenceEncoderQA::CreateFromOption(options);
+  CHECK_OK(status);
+  std::unique_ptr<UniversalSentenceEncoderQA> client =
+      std::move(status.value());
+
+  // Create RetrievalInput with a query and responses.
+  RetrievalInput input;
+  // Set a sentence of text as the query.
+  input.set_query_text(absl::GetFlag(FLAGS_question));
+  // Add candidate responses, and each one contains a sentence of text. (May
+  // set context too).
+  for (const auto& ans : absl::StrSplit(absl::GetFlag(FLAGS_answers), ':')) {
+    input.add_responses()->mutable_raw_text()->set_text(ans);
+  }
+
+  // Run inference with the Retrieve function.
+  const absl::StatusOr<RetrievalOutput>& output_status =
+      client->Retrieve(input);
+  CHECK_OK(output_status);  // Check ok
+  const RetrievalOutput& output = output_status.value();
+
+  // Get top results (may set optional parameter k=? to limit top-K results).
+  const std::vector<size_t>& top = client->Top(output);
+
+  // Consume the results according to the ranking. Here we just print them out.
+  std::cout << input.query_text() << std::endl;
+  for (size_t k : top) {
+    std::cout << input.responses(k).raw_text().text() << ", "
+              << input.responses(k).raw_text().context() << ", "
+              << output.response_results(k).score() << std::endl;
+  }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/BUILD
index f61984e..601533c 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/BUILD
@@ -1,6 +1,6 @@
 package(
     default_visibility = [
-        "//tensorflow_lite_support:users",
+        "//tensorflow_lite_support:internal",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
@@ -9,6 +9,10 @@
     name = "image_classifier_demo",
     srcs = ["image_classifier_demo.cc"],
     deps = [
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/flags:parse",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings:str_format",
         "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/core:external_file_handler",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
@@ -18,17 +22,24 @@
         "//tensorflow_lite_support/cc/task/vision/proto:image_classifier_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
         "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
-        "@com_google_absl//absl/flags:flag",
-        "@com_google_absl//absl/flags:parse",
-        "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings:str_format",
-    ],
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
 )
 
 cc_binary(
     name = "object_detector_demo",
     srcs = ["object_detector_demo.cc"],
     deps = [
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/flags:parse",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
         "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/core:external_file_handler",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
@@ -39,18 +50,24 @@
         "//tensorflow_lite_support/cc/task/vision/proto:object_detector_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
         "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
-        "@com_google_absl//absl/flags:flag",
-        "@com_google_absl//absl/flags:parse",
-        "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings",
-        "@com_google_absl//absl/strings:str_format",
-    ],
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
 )
 
 cc_binary(
     name = "image_segmenter_demo",
     srcs = ["image_segmenter_demo.cc"],
     deps = [
+        "@com_google_absl//absl/flags:flag",
+        "@com_google_absl//absl/flags:parse",
+        "@com_google_absl//absl/status",
+        "@com_google_absl//absl/strings",
+        "@com_google_absl//absl/strings:str_format",
         "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/core:external_file_handler",
         "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
@@ -59,10 +76,36 @@
         "//tensorflow_lite_support/cc/task/vision/proto:segmentations_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
         "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
+)
+
+cc_binary(
+    name = "image_embedder_demo",
+    srcs = ["image_embedder_demo.cc"],
+    deps = [
         "@com_google_absl//absl/flags:flag",
         "@com_google_absl//absl/flags:parse",
         "@com_google_absl//absl/status",
-        "@com_google_absl//absl/strings",
         "@com_google_absl//absl/strings:str_format",
-    ],
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core:external_file_handler",
+        "//tensorflow_lite_support/cc/task/core/proto:external_file_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision:image_embedder",
+        "//tensorflow_lite_support/cc/task/vision/proto:embeddings_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/proto:image_embedder_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
+        "//tensorflow_lite_support/examples/task/vision/desktop/utils:image_utils",
+    ] + select({
+        "//tensorflow_lite_support/examples/task:darwinn_portable": [
+            "//tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin",
+        ],
+        "//conditions:default": [
+        ],
+    }),
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/README.md
index 73c6b63..ef7969a 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/README.md
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/README.md
@@ -3,15 +3,44 @@
 This folder contains simple command-line tools for easily trying out the C++
 Vision Task APIs.
 
+## Coral Integration
+
+Task Library now supports fast TFLite inference delegated onto
+[Coral Edge TPU devices][4] on Linux and macOS. See the
+[documentation](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview#run_task_library_with_delegates)
+for more details.
+
+To run the demo on a Coral device, add `--define darwinn_portable=1` to the
+bazel command.
+
+Note the `libusb` package is required. It can be installed as follows:
+
+```bash
+# On Linux
+sudo apt-get install libusb-1.0-0-dev
+
+# On macOS using MacPorts
+port install libusb
+# or Homebrew
+brew install libusb
+```
+
+See the example commands in each task demo below.
+
+You can also explore more [pretrained Coral model](https://coral.ai/models) and
+try them in the demo. All the models have populated with
+[TFLite Model Metadata](https://www.tensorflow.org/lite/convert/metadata).
+
 ## Image Classifier
 
 #### Prerequisites
 
 You will need:
 
-* a TFLite image classification model (e.g. [aiy/vision/classifier/birds_V1][1],
-a bird classification model available on TensorFlow Hub),
-* a PNG, JPEG or GIF image to run classification on, e.g.:
+*   a TFLite image classification model (e.g.
+    [aiy/vision/classifier/birds_V1][1], a bird classification model available
+    on TensorFlow Hub),
+*   a PNG, JPEG or GIF image to run classification on, e.g.:
 
 ![sparrow](g3doc/sparrow.jpg)
 
@@ -34,11 +63,31 @@
  --max_results=3
 ```
 
+To run the demo on a [Coral Edge TPU device][4], check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the Coral model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite' \
+ -o /tmp/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite
+
+# Run the classification tool:
+bazel run -c opt --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/vision/desktop:image_classifier_demo -- \
+ --model_path=/tmp/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/sparrow.jpg \
+ --max_results=3 \
+ --use_coral=true
+```
+
 #### Results
 
 In the console, you should get:
 
 ```
+Time cost to classify the input image on CPU: 109ms
 Results:
   Rank #0:
    index       : 671
@@ -63,9 +112,9 @@
 
 You will need:
 
-* a TFLite object detection model (e.g. [ssd_mobilenet_v1][2], a generic object
-detection model available on TensorFlow Hub),
-* a PNG, JPEG or GIF image to run detection on, e.g.:
+*   a TFLite object detection model (e.g. [ssd_mobilenet_v1][2], a generic
+    object detection model available on TensorFlow Hub),
+*   a PNG, JPEG or GIF image to run detection on, e.g.:
 
 ![dogs](g3doc/dogs.jpg)
 
@@ -89,11 +138,32 @@
  --max_results=2
 ```
 
+To run the demo on a [Coral Edge TPU device][4], check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite' \
+ -o /tmp/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite
+
+# Run the detection tool:
+bazel run -c opt --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/vision/desktop:object_detector_demo -- \
+ --model_path=/tmp/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/dogs.jpg \
+ --output_png=/tmp/detection-output.png \
+ --max_results=2 \
+ --use_coral=true
+```
+
 #### Results
 
 In the console, you should get:
 
 ```
+Time cost to detect the input image on CPU: 123 ms
 Results saved to: /tmp/detection-output.png
 Results:
  Detection #0 (red):
@@ -120,11 +190,11 @@
 
 You will need:
 
-* a TFLite image segmentation model (e.g. [deeplab_v3][3], a generic
-segmentation model available on TensorFlow Hub),
-* a PNG, JPEG or GIF image to run segmentation on, e.g.:
+*   a TFLite image segmentation model (e.g. [deeplab_v3][3], a generic
+    segmentation model available on TensorFlow Hub),
+*   a PNG, JPEG or GIF image to run segmentation on, e.g.:
 
-![plane](g3doc/plane.jpg)
+![cat](g3doc/cat.jpg)
 
 #### Usage
 
@@ -133,40 +203,54 @@
 ```bash
 # Download the model:
 curl \
- -L 'https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/1?lite-format=tflite' \
- -o /tmp/deeplabv3_1_metadata_1.tflite
+ -L 'https://github.com/google-coral/test_data/raw/master/keras_post_training_unet_mv2_128_quant.tflite' \
+ -o /tmp/keras_post_training_unet_mv2_128_quant.tflite
 
 # Run the segmentation tool:
 bazel run -c opt \
  tensorflow_lite_support/examples/task/vision/desktop:image_segmenter_demo -- \
- --model_path=/tmp/deeplabv3_1_metadata_1.tflite \
+ --model_path=/tmp/keras_post_training_unet_mv2_128_quant.tflite \
  --image_path=\
-$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/plane.jpg \
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg \
  --output_mask_png=/tmp/segmentation-output.png
 ```
 
+To run the demo on a [Coral Edge TPU device][4], check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/keras_post_training_unet_mv2_128_quant_edgetpu.tflite' \
+ -o /tmp/keras_post_training_unet_mv2_128_quant_edgetpu.tflite
+
+# Run the segmentation tool:
+bazel run -c opt --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/vision/desktop:image_segmenter_demo -- \
+ --model_path=/tmp/keras_post_training_unet_mv2_128_quant_edgetpu.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg \
+ --output_mask_png=/tmp/segmentation-output.png \
+ --use_coral=true
+```
+
 #### Results
 
 In the console, you should get:
 
 ```
+Time cost to segment the input image on CPU: 89.9316 ms
 Category mask saved to: /tmp/segmentation-output.png
 Color Legend:
  (r: 000, g: 000, b: 000):
   index       : 0
-  class name  : background
+  class name  : pet
  (r: 128, g: 000, b: 000):
   index       : 1
-  class name  : aeroplane
-
-# (omitting multiple lines for conciseness) ...
-
- (r: 128, g: 192, b: 000):
-  index       : 19
-  class name  : train
- (r: 000, g: 064, b: 128):
-  index       : 20
-  class name  : tv
+  class name  : background
+ (r: 000, g: 128, b: 000):
+  index       : 2
+  class name  : border
 Tip: use a color picker on the output PNG file to inspect the output mask with
 this legend.
 ```
@@ -178,3 +262,4 @@
 [1]: https://tfhub.dev/google/lite-model/aiy/vision/classifier/birds_V1/3
 [2]: https://tfhub.dev/tensorflow/lite-model/ssd_mobilenet_v1/1/metadata/2
 [3]: https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/2
+[4]: https://coral.ai/docs/edgetpu/inference/
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg
new file mode 100644
index 0000000..b4acd1a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/plane.jpg b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/plane.jpg
deleted file mode 100644
index 0edefa4..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/plane.jpg
+++ /dev/null
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/segmentation-output.png b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/segmentation-output.png
index e871df3..9a27d30 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/segmentation-output.png
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/g3doc/segmentation-output.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc
index bcca6904..bd2aaaf1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_classifier_demo.cc
@@ -22,10 +22,10 @@
 
 #include <iostream>
 
-#include "absl/flags/flag.h"
-#include "absl/flags/parse.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
@@ -70,14 +70,24 @@
     "Comma-separated list of class names that acts as a blacklist. If "
     "non-empty, classification results whose 'class_name' is in this list "
     "are filtered out. Mutually exclusive with 'class_name_whitelist'.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
 
 namespace tflite {
 namespace task {
 namespace vision {
 
+namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+}  // namespace
+
 ImageClassifierOptions BuildOptions() {
   ImageClassifierOptions options;
-  options.mutable_model_file_with_metadata()->set_file_name(
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
       absl::GetFlag(FLAGS_model_path));
   options.set_max_results(absl::GetFlag(FLAGS_max_results));
   if (absl::GetFlag(FLAGS_score_threshold) >= 0) {
@@ -91,6 +101,12 @@
        absl::GetFlag(FLAGS_class_name_blacklist)) {
     options.add_class_name_blacklist(class_name);
   }
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
   return options;
 }
 
@@ -143,8 +159,18 @@
   }
 
   // Run classification and display results.
+  auto start_classify = steady_clock::now();
   ASSIGN_OR_RETURN(ClassificationResult result,
                    image_classifier->Classify(*frame_buffer));
+  auto end_classify = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to classify the input image on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_classify -
+                                                        start_classify)
+                   .count()
+            << " ms" << std::endl;
+
   DisplayResult(result);
 
   // Cleanup and return.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc
new file mode 100644
index 0000000..040878a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_embedder_demo.cc
@@ -0,0 +1,195 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Computes and displays cosine similarity between the feature vectors extracted
+// on two images.
+//
+// Example usage:
+// bazel run -c opt \
+//  tensorflow_lite_support/examples/task/vision/desktop:image_embedder_demo \
+//  -- \
+//  --model_path=/path/to/model.tflite \
+//  --first_image_path=/path/to/first/image.jpg \
+//  --second_image_path=/path/to/second/image.jpg
+
+#include <iostream>
+
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
+#include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/image_embedder.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/embeddings_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/proto/image_embedder_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
+#include "tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h"
+
+ABSL_FLAG(std::string,
+          model_path,
+          "",
+          "Absolute path to the '.tflite' image embedder model.");
+ABSL_FLAG(std::string,
+          first_image_path,
+          "",
+          "Absolute path to the first image, whose feature vector will be "
+          "extracted and compared to the second image using cosine similarity. "
+          "The image must be RGB or RGBA (grayscale is not supported). The "
+          "image EXIF orientation flag, if any, is NOT taken into account.");
+ABSL_FLAG(std::string,
+          second_image_path,
+          "",
+          "Absolute path to the second image, whose feature vector will be "
+          "extracted and compared to the first image using cosine similarity. "
+          "The image must be RGB or RGBA (grayscale is not supported). The "
+          "image EXIF orientation flag, if any, is NOT taken into account.");
+ABSL_FLAG(bool,
+          l2_normalize,
+          false,
+          "If true, the raw feature vectors returned by the image embedder "
+          "will be normalized with L2-norm. Generally only needed if the model "
+          "doesn't already contain a L2_NORMALIZATION TFLite Op.");
+ABSL_FLAG(
+    bool,
+    quantize,
+    false,
+    "If true, the raw feature vectors returned by the image embedder will "
+    "be quantized to 8 bit integers (uniform quantization) via post-processing "
+    "before cosine similarity is computed.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
+
+namespace tflite {
+namespace task {
+namespace vision {
+
+namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+using ::tflite::support::StatusOr;
+}  // namespace
+
+ImageEmbedderOptions BuildOptions() {
+  ImageEmbedderOptions options;
+  options.mutable_model_file_with_metadata()->set_file_name(
+      absl::GetFlag(FLAGS_model_path));
+  options.set_l2_normalize(absl::GetFlag(FLAGS_l2_normalize));
+  options.set_quantize(absl::GetFlag(FLAGS_quantize));
+
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_compute_settings()->mutable_tflite_settings()->set_delegate(
+        ::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
+  return options;
+}
+
+StatusOr<std::unique_ptr<FrameBuffer>> BuildFrameBufferFromImageData(
+    const ImageData& image) {
+  std::unique_ptr<FrameBuffer> frame_buffer;
+  if (image.channels == 3) {
+    return CreateFromRgbRawBuffer(image.pixel_data,
+                                  {image.width, image.height});
+  } else if (image.channels == 4) {
+    return CreateFromRgbaRawBuffer(image.pixel_data,
+                                   {image.width, image.height});
+  }
+  return absl::InvalidArgumentError(absl::StrFormat(
+      "Expected image with 3 (RGB) or 4 (RGBA) channels, found %d",
+      image.channels));
+}
+
+absl::Status ComputeCosineSimilarity() {
+  // Build ImageEmbedder.
+  const ImageEmbedderOptions& options = BuildOptions();
+  ASSIGN_OR_RETURN(std::unique_ptr<ImageEmbedder> image_embedder,
+                   ImageEmbedder::CreateFromOptions(options));
+
+  // Load images into FrameBuffer objects.
+  ASSIGN_OR_RETURN(ImageData first_image,
+                   DecodeImageFromFile(absl::GetFlag(FLAGS_first_image_path)));
+  ASSIGN_OR_RETURN(std::unique_ptr<FrameBuffer> first_frame_buffer,
+                   BuildFrameBufferFromImageData(first_image));
+  ASSIGN_OR_RETURN(ImageData second_image,
+                   DecodeImageFromFile(absl::GetFlag(FLAGS_second_image_path)));
+  ASSIGN_OR_RETURN(std::unique_ptr<FrameBuffer> second_frame_buffer,
+                   BuildFrameBufferFromImageData(second_image));
+
+  // Extract feature vectors.
+  auto start_embed = steady_clock::now();
+  ASSIGN_OR_RETURN(const EmbeddingResult& first_embedding_result,
+                   image_embedder->Embed(*first_frame_buffer));
+  auto end_embed = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to embed the input image on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_embed - start_embed)
+                   .count()
+            << " ms" << std::endl;
+
+  ASSIGN_OR_RETURN(const EmbeddingResult& second_embedding_result,
+                   image_embedder->Embed(*second_frame_buffer));
+  // Compute cosine similarity.
+  ASSIGN_OR_RETURN(
+      double cosine_similarity,
+      ImageEmbedder::CosineSimilarity(
+          image_embedder->GetEmbeddingByIndex(first_embedding_result, 0)
+              .feature_vector(),
+          image_embedder->GetEmbeddingByIndex(second_embedding_result, 0)
+              .feature_vector()));
+
+  // Display result.
+  std::cout << absl::StrFormat("Cosine similarity: %f\n", cosine_similarity);
+
+  // Cleanup and return.
+  ImageDataFree(&first_image);
+  ImageDataFree(&second_image);
+  return absl::OkStatus();
+}
+
+}  // namespace vision
+}  // namespace task
+}  // namespace tflite
+
+int main(int argc, char** argv) {
+  // Parse command line arguments and perform sanity checks.
+  absl::ParseCommandLine(argc, argv);
+  if (absl::GetFlag(FLAGS_model_path).empty()) {
+    std::cerr << "Missing mandatory 'model_path' argument.\n";
+    return 1;
+  }
+  if (absl::GetFlag(FLAGS_first_image_path).empty()) {
+    std::cerr << "Missing mandatory 'first_image_path' argument.\n";
+    return 1;
+  }
+  if (absl::GetFlag(FLAGS_second_image_path).empty()) {
+    std::cerr << "Missing mandatory 'second_image_path' argument.\n";
+    return 1;
+  }
+
+  // Compute cosine similarity.
+  absl::Status status = tflite::task::vision::ComputeCosineSimilarity();
+  if (status.ok()) {
+    return 0;
+  } else {
+    std::cerr << "Cosine similarity computation failed: " << status.message()
+              << "\n";
+    return 1;
+  }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc
index a7539df..6487fe9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/image_segmenter_demo.cc
@@ -23,11 +23,11 @@
 
 #include <iostream>
 
-#include "absl/flags/flag.h"
-#include "absl/flags/parse.h"
-#include "absl/status/status.h"
-#include "absl/strings/match.h"
-#include "absl/strings/str_format.h"
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/match.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
@@ -52,17 +52,34 @@
           "",
           "Absolute path to the output category mask (confidence masks outputs "
           "are not supported by this tool). Must have a '.png' extension.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
 
 namespace tflite {
 namespace task {
 namespace vision {
 
+namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+}  // namespace
+
 ImageSegmenterOptions BuildOptions() {
   ImageSegmenterOptions options;
-  options.mutable_model_file_with_metadata()->set_file_name(
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
       absl::GetFlag(FLAGS_model_path));
   // Confidence masks are not supported by this tool: output_type is set to
   // CATEGORY_MASK by default.
+
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
   return options;
 }
 
@@ -160,8 +177,18 @@
   }
 
   // Run segmentation and save category mask.
+  auto start_segment = steady_clock::now();
   ASSIGN_OR_RETURN(SegmentationResult result,
                    image_segmenter->Segment(*frame_buffer));
+  auto end_segment = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to segment the input image on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_segment -
+                                                        start_segment)
+                   .count()
+            << " ms" << std::endl;
+
   RETURN_IF_ERROR(EncodeMaskToPngFile(result));
 
   // Display the legend.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc
index f6f626f..9208439 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/object_detector_demo.cc
@@ -24,11 +24,11 @@
 #include <iostream>
 #include <limits>
 
-#include "absl/flags/flag.h"
-#include "absl/flags/parse.h"
-#include "absl/status/status.h"
-#include "absl/strings/match.h"
-#include "absl/strings/str_format.h"
+#include "absl/flags/flag.h"          // from @com_google_absl
+#include "absl/flags/parse.h"         // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/match.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/core/external_file_handler.h"
 #include "tensorflow_lite_support/cc/task/core/proto/external_file_proto_inc.h"
@@ -79,12 +79,22 @@
           "Comma-separated list of class names that acts as a blacklist. If "
           "non-empty, detections results whose 'class_name' is in this list "
           "are filtered out. Mutually exclusive with 'class_name_whitelist'.");
+ABSL_FLAG(bool,
+          use_coral,
+          false,
+          "If true, inference will be delegated to a connected Coral Edge TPU "
+          "device.");
 
 namespace tflite {
 namespace task {
 namespace vision {
 
 namespace {
+using std::chrono::microseconds;
+using std::chrono::steady_clock;
+}  // namespace
+
+namespace {
 // The line thickness (in pixels) for drawing the detection results.
 constexpr int kLineThickness = 3;
 
@@ -105,7 +115,7 @@
 
 ObjectDetectorOptions BuildOptions() {
   ObjectDetectorOptions options;
-  options.mutable_model_file_with_metadata()->set_file_name(
+  options.mutable_base_options()->mutable_model_file()->set_file_name(
       absl::GetFlag(FLAGS_model_path));
   options.set_max_results(absl::GetFlag(FLAGS_max_results));
   if (absl::GetFlag(FLAGS_score_threshold) >
@@ -120,6 +130,12 @@
        absl::GetFlag(FLAGS_class_name_blacklist)) {
     options.add_class_name_blacklist(class_name);
   }
+  if (absl::GetFlag(FLAGS_use_coral)) {
+    options.mutable_base_options()
+        ->mutable_compute_settings()
+        ->mutable_tflite_settings()
+        ->set_delegate(::tflite::proto::Delegate::EDGETPU_CORAL);
+  }
   return options;
 }
 
@@ -212,8 +228,18 @@
   }
 
   // Run object detection and draw results on input image.
+  auto start_detect = steady_clock::now();
   ASSIGN_OR_RETURN(DetectionResult result,
                    object_detector->Detect(*frame_buffer));
+  auto end_detect = steady_clock::now();
+  std::string delegate =
+      absl::GetFlag(FLAGS_use_coral) ? "Coral Edge TPU" : "CPU";
+  std::cout << "Time cost to detect the input image on " << delegate << ": "
+            << std::chrono::duration<float, std::milli>(end_detect -
+                                                        start_detect)
+                   .count()
+            << " ms" << std::endl;
+
   RETURN_IF_ERROR(EncodeResultToPngFile(result, &image));
 
   // Display results as text.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/BUILD
new file mode 100644
index 0000000..baf5e784
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/BUILD
@@ -0,0 +1,55 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+# bazel run \
+#  tensorflow_lite_support/examples/task/vision/desktop/python:image_classifier_demo -- \
+#  --model_path=/tmp/aiy_vision_classifier_birds_V1_3.tflite \
+#  --image_path=\
+# $(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/sparrow.jpg \
+#  --max_results=3
+py_binary(
+    name = "image_classifier_demo",
+    srcs = ["image_classifier_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/vision/desktop:image_classifier_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
+
+# bazel run \
+#  tensorflow_lite_support/examples/task/vision/desktop/python:object_detector_demo -- \
+#  --model_path=/tmp/ssd_mobilenet_v1_1_metadata_1.tflite \
+#  --image_path=\
+# $(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/dogs.jpg \
+#  --output_png=/tmp/detection-output.png \
+#  --max_results=2
+py_binary(
+    name = "object_detector_demo",
+    srcs = ["object_detector_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/vision/desktop:object_detector_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
+
+# bazel run \
+#  tensorflow_lite_support/examples/task/vision/desktop/python:image_segmenter_demo -- \
+#  --model_path=/tmp/keras_post_training_unet_mv2_128_quant.tflite \
+#  --image_path=\
+# $(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg \
+#  --output_mask_png=/tmp/segmentation-output.png
+py_binary(
+    name = "image_segmenter_demo",
+    srcs = ["image_segmenter_demo.py"],
+    data = ["//tensorflow_lite_support/examples/task/vision/desktop:image_segmenter_demo"],
+    deps = [
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/README.md b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/README.md
new file mode 100644
index 0000000..d808ce9b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/README.md
@@ -0,0 +1,270 @@
+# CLI Demos for Python Vision Task APIs
+
+A Python wrapper for the C++ Vision Task APIs.
+
+## Background
+
+This Python API is based on the C++ Vision Task APIs. It uses Python's
+[subprocess](https://docs.python.org/3/library/subprocess.html) to call C++ Vision
+Task APIs.
+
+## Coral Integration
+
+Task Library now supports fast TFLite inference delegated onto
+[Coral Edge TPU devices][4] on Linux and macOS. See the
+[documentation](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview#run_task_library_with_delegates)
+for more details.
+
+To run the demo on a Coral device, add `--define darwinn_portable=1` to the
+bazel command.
+
+Note the `libusb` package is required. It can be installed as follows:
+
+```bash
+# On Linux
+sudo apt-get install libusb-1.0-0-dev
+
+# On macOS using MacPorts
+port install libusb
+# or Homebrew
+brew install libusb
+```
+
+See the example commands in each task demo below.
+
+You can also explore more [pretrained Coral model](https://coral.ai/models) and
+try them in the demo. All the models have populated with
+[TFLite Model Metadata](https://www.tensorflow.org/lite/convert/metadata).
+
+## Image Classifier
+
+#### Prerequisites
+
+You will need:
+
+*   a TFLite image classification model (e.g.
+    [aiy/vision/classifier/birds_V1][1], a bird classification model available
+    on TensorFlow Hub),
+*   a PNG, JPEG or GIF image to run classification on, e.g.:
+
+![sparrow](../g3doc/sparrow.jpg)
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://tfhub.dev/google/lite-model/aiy/vision/classifier/birds_V1/3?lite-format=tflite' \
+ -o /tmp/aiy_vision_classifier_birds_V1_3.tflite
+
+# Run the classification tool:
+bazel run \
+ tensorflow_lite_support/examples/task/vision/desktop/python:image_classifier_demo -- \
+ --model_path=/tmp/aiy_vision_classifier_birds_V1_3.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/sparrow.jpg \
+ --max_results=3
+```
+
+To run the demo on a [Coral Edge TPU device][4], check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the Coral model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite' \
+ -o /tmp/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite
+
+# Run the classification tool:
+bazel run --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/vision/desktop/python:image_classifier_demo -- \
+ --model_path=/tmp/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/sparrow.jpg \
+ --max_results=3 \
+ --use_coral=true
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+Time cost to classify the input image on CPU: 109ms
+Results:
+  Rank #0:
+   index       : 671
+   score       : 0.91406
+   class name  : /m/01bwb9
+   display name: Passer domesticus
+  Rank #1:
+   index       : 670
+   score       : 0.00391
+   class name  : /m/01bwbt
+   display name: Passer montanus
+  Rank #2:
+   index       : 495
+   score       : 0.00391
+   class name  : /m/0bwm6m
+   display name: Passer italiae
+```
+
+## Object Detector
+
+#### Prerequisites
+
+You will need:
+
+*   a TFLite object detection model (e.g. [ssd_mobilenet_v1][2], a generic
+    object detection model available on TensorFlow Hub),
+*   a PNG, JPEG or GIF image to run detection on, e.g.:
+
+![dogs](../g3doc/dogs.jpg)
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://tfhub.dev/tensorflow/lite-model/ssd_mobilenet_v1/1/metadata/1?lite-format=tflite' \
+ -o /tmp/ssd_mobilenet_v1_1_metadata_1.tflite
+
+# Run the detection tool:
+bazel run \
+ tensorflow_lite_support/examples/task/vision/desktop/python:object_detector_demo -- \
+ --model_path=/tmp/ssd_mobilenet_v1_1_metadata_1.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/dogs.jpg \
+ --output_png=/tmp/detection-output.png \
+ --max_results=2
+```
+
+To run the demo on a [Coral Edge TPU device][4], check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite' \
+ -o /tmp/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite
+
+# Run the detection tool:
+bazel run --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/vision/desktop/python:object_detector_demo -- \
+ --model_path=/tmp/ssd_mobilenet_v1_coco_quant_postprocess_edgetpu.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/dogs.jpg \
+ --output_png=/tmp/detection-output.png \
+ --max_results=2 \
+ --use_coral=true
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+Time cost to detect the input image on CPU: 123 ms
+Results saved to: /tmp/detection-output.png
+Results:
+ Detection #0 (red):
+  Box: (x: 355, y: 133, w: 190, h: 206)
+  Top-1 class:
+   index       : 17
+   score       : 0.73828
+   class name  : dog
+ Detection #1 (green):
+  Box: (x: 103, y: 15, w: 138, h: 369)
+  Top-1 class:
+   index       : 17
+   score       : 0.73047
+   class name  : dog
+```
+
+And `/tmp/detection-output.jpg` should contain:
+
+![detection-output](../g3doc/detection-output.png)
+
+## Image Segmenter
+
+#### Prerequisites
+
+You will need:
+
+*   a TFLite image segmentation model (e.g. [deeplab_v3][3], a generic
+    segmentation model available on TensorFlow Hub),
+*   a PNG, JPEG or GIF image to run segmentation on, e.g.:
+
+![cat](../g3doc/cat.jpg)
+
+#### Usage
+
+In the console, run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/keras_post_training_unet_mv2_128_quant.tflite' \
+ -o /tmp/keras_post_training_unet_mv2_128_quant.tflite
+
+# Run the segmentation tool:
+bazel run \
+ tensorflow_lite_support/examples/task/vision/desktop/python:image_segmenter_demo -- \
+ --model_path=/tmp/keras_post_training_unet_mv2_128_quant.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg \
+ --output_mask_png=/tmp/segmentation-output.png
+```
+
+To run the demo on a [Coral Edge TPU device][4], check
+[Coral Integration](#coral-integration) section and then run:
+
+```bash
+# Download the model:
+curl \
+ -L 'https://github.com/google-coral/test_data/raw/master/keras_post_training_unet_mv2_128_quant_edgetpu.tflite' \
+ -o /tmp/keras_post_training_unet_mv2_128_quant_edgetpu.tflite
+
+# Run the segmentation tool:
+bazel run --define darwinn_portable=1 \
+ tensorflow_lite_support/examples/task/vision/desktop/python:image_segmenter_demo -- \
+ --model_path=/tmp/keras_post_training_unet_mv2_128_quant_edgetpu.tflite \
+ --image_path=\
+$(pwd)/tensorflow_lite_support/examples/task/vision/desktop/g3doc/cat.jpg \
+ --output_mask_png=/tmp/segmentation-output.png \
+ --use_coral=true
+```
+
+#### Results
+
+In the console, you should get:
+
+```
+Time cost to segment the input image on CPU: 89.9316 ms
+Category mask saved to: /tmp/segmentation-output.png
+Color Legend:
+ (r: 000, g: 000, b: 000):
+  index       : 0
+  class name  : pet
+ (r: 128, g: 000, b: 000):
+  index       : 1
+  class name  : background
+ (r: 000, g: 128, b: 000):
+  index       : 2
+  class name  : border
+Tip: use a color picker on the output PNG file to inspect the output mask with
+this legend.
+```
+
+And `/tmp/segmentation-output.jpg` should contain the segmentation mask:
+
+![segmentation-output](../g3doc/segmentation-output.png)
+
+[1]: https://tfhub.dev/google/lite-model/aiy/vision/classifier/birds_V1/3
+[2]: https://tfhub.dev/tensorflow/lite-model/ssd_mobilenet_v1/1/metadata/2
+[3]: https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/2
+[4]: https://coral.ai/docs/edgetpu/inference/
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_classifier_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_classifier_demo.py
new file mode 100644
index 0000000..c1ee07b3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_classifier_demo.py
@@ -0,0 +1,107 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for Image Classification."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+
+flags.DEFINE_string('model_path', None,
+                    'Absolute path to the ".tflite" image classifier model.')
+flags.DEFINE_string(
+    'image_path', None,
+    'Absolute path to the image to classify. The image must be RGB or '
+    'RGBA (grayscale is not supported). The image EXIF orientation '
+    'flag, if any, is NOT taken into account.')
+flags.DEFINE_integer('max_results', 5,
+                     'Maximum number of classification results to display.')
+flags.DEFINE_float(
+    'score_threshold', 0,
+    'Classification results with a confidence score below this value are '
+    'rejected. If >= 0, overrides the score threshold(s) provided in the '
+    'TFLite Model Metadata. Ignored otherwise.')
+flags.DEFINE_string(
+    'class_name_whitelist', '',
+    'Comma-separated list of class names that acts as a whitelist. If '
+    'non-empty, classification results whose "class_name" is not in this list '
+    'are filtered out. Mutually exclusive with "class_name_blacklist".')
+flags.DEFINE_string(
+    'class_name_blacklist', '',
+    'Comma-separated list of class names that acts as a blacklist. If '
+    'non-empty, classification results whose "class_name" is in this list '
+    'are filtered out. Mutually exclusive with "class_name_whitelist".')
+flags.DEFINE_bool(
+    'use_coral', False,
+    'If true, inference will be delegated to a connected Coral Edge TPU '
+    'device.')
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('image_path')
+
+_IMAGE_CLASSIFICATION_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../image_classifier_demo')
+
+
+def classify(model_path, image_path, max_results, score_threshold,
+             class_name_whitelist, class_name_blacklist, use_coral):
+  """Classifies input image into different categories.
+
+  Args:
+      model_path: Path to model
+      image_path: Absolute path to the image to classify
+      max_results: Maximum number of classification results to display
+      score_threshold: Optional; Classification results with a confidence 
+        score below this value are rejected
+      class_name_whitelist: Optional; Comma-separated list of class names 
+        that acts as a whitelist
+      class_name_blacklist: Optional; Comma-separated list of class names 
+        that acts as a blacklist
+      use_coral: Optional; If true, inference will be delegated to a 
+        connected Coral Edge TPU device
+  """
+  # Run the classification tool:
+  subprocess.run([
+      _IMAGE_CLASSIFICATION_NATIVE_PATH + ' --model_path=' + model_path +
+      ' --image_path=' + image_path + ' --max_results=' + str(max_results) +
+      ' --score_threshold=' + str(score_threshold) +
+      ' --class_name_whitelist="' + str(class_name_whitelist) +
+      '" --class_name_blacklist="' + str(class_name_blacklist) +
+      '" --use_coral=' + str(use_coral)
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.image_path, FLAGS.max_results,
+           FLAGS.score_threshold, FLAGS.class_name_whitelist,
+           FLAGS.class_name_blacklist, FLAGS.use_coral)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_segmenter_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_segmenter_demo.py
new file mode 100644
index 0000000..f46bf1f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/image_segmenter_demo.py
@@ -0,0 +1,85 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for Image Segmentation."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+
+flags.DEFINE_string('model_path', None,
+                    'Absolute path to the ".tflite" image segmenter model.')
+flags.DEFINE_string(
+    'image_path', None,
+    'Absolute path to the image to segment. The image must be RGB or '
+    'RGBA (grayscale is not supported). The image EXIF orientation '
+    'flag, if any, is NOT taken into account.')
+flags.DEFINE_string(
+    'output_mask_png', None,
+    'Absolute path to the output category mask (confidence masks outputs '
+    'are not supported by this tool). Must have a ".png" extension.')
+flags.DEFINE_bool(
+    'use_coral', False,
+    'If true, inference will be delegated to a connected Coral Edge TPU '
+    'device.')
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('image_path')
+flags.mark_flag_as_required('output_mask_png')
+
+_IMAGE_SEGMENTATION_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../image_segmenter_demo')
+
+
+def classify(model_path, image_path, output_mask_png, use_coral):
+  """Segments the input image.
+
+  Args:
+      model_path: Path to model
+      image_path: Absolute path to the image to segment
+      output_mask_png: Absolute path to the output category mask (confidence 
+        masks outputs are not supported by this tool
+      use_coral: Optional; If true, inference will be delegated to a connected 
+        Coral Edge TPU device
+  """
+  # Run the segmentation tool:
+  subprocess.run([
+      _IMAGE_SEGMENTATION_NATIVE_PATH + ' --model_path=' + model_path +
+      ' --image_path=' + image_path + ' --output_mask_png=' + output_mask_png +
+      ' --use_coral=' + str(use_coral)
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.image_path, FLAGS.output_mask_png,
+           FLAGS.use_coral)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/object_detector_demo.py b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/object_detector_demo.py
new file mode 100644
index 0000000..7842b6c2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/python/object_detector_demo.py
@@ -0,0 +1,116 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Python demo tool for Object Detection."""
+
+import inspect
+import os.path as _os_path
+import subprocess
+import sys
+
+from absl import app
+from absl import flags
+
+FLAGS = flags.FLAGS
+
+flags.DEFINE_string('model_path', None,
+                    'Absolute path to the ".tflite" object detector model.')
+flags.DEFINE_string(
+    'image_path', None,
+    'Absolute path to the image to run detection on. The image must be '
+    'RGB or RGBA (grayscale is not supported). The image EXIF '
+    'orientation flag, if any, is NOT taken into account.')
+flags.DEFINE_string(
+    'output_png', None,
+    'Absolute path to a file where to draw the detection results on top '
+    'of the input image. Must have a ".png" extension.')
+flags.DEFINE_integer('max_results', 5,
+                     'Maximum number of detection results to display.')
+flags.DEFINE_float(
+    'score_threshold', 0,
+    'Detection results with a confidence score below this value are '
+    'rejected. If specified, overrides the score threshold(s) provided in the '
+    'TFLite Model Metadata. Ignored otherwise.')
+flags.DEFINE_string(
+    'class_name_whitelist', '',
+    'Comma-separated list of class names that acts as a whitelist. If '
+    'non-empty, detections results whose "class_name" is not in this list '
+    'are filtered out. Mutually exclusive with "class_name_blacklist".')
+flags.DEFINE_string(
+    'class_name_blacklist', '',
+    'Comma-separated list of class names that acts as a blacklist. If '
+    'non-empty, detections results whose "class_name" is in this list '
+    'are filtered out. Mutually exclusive with "class_name_whitelist".')
+flags.DEFINE_bool(
+    'use_coral', False,
+    'If true, inference will be delegated to a connected Coral Edge TPU '
+    'device.')
+
+# Required flag.
+flags.mark_flag_as_required('model_path')
+flags.mark_flag_as_required('image_path')
+flags.mark_flag_as_required('output_png')
+flags.mark_flag_as_required('max_results')
+
+_OBJECT_DETECTION_NATIVE_PATH = _os_path.join(
+    _os_path.dirname(inspect.getfile(inspect.currentframe())),
+    '../object_detector_demo')
+
+
+def classify(model_path, image_path, output_png, max_results, score_threshold,
+             class_name_whitelist, class_name_blacklist, use_coral):
+  """Detects the input image.
+
+  Args:
+      model_path: Path to model
+      image_path: Absolute path to the image to run detection on
+      output_png: Absolute path to a file where to draw the detection results 
+        on top of the input image
+      max_results: Maximum number of detection results to display
+      score_threshold: Optional; Detection results with a confidence score 
+        below this value are rejected
+      class_name_whitelist: Optional; Comma-separated list of class names 
+        that acts as a whitelist.
+      class_name_blacklist: Optional; Comma-separated list of class names 
+        that acts as a blacklist.
+      use_coral: Optional; If true, inference will be delegated to a 
+        connected Coral Edge TPU device
+  """
+  # Run the detection tool:
+  subprocess.run([
+      _OBJECT_DETECTION_NATIVE_PATH + ' --model_path=' + model_path +
+      ' --image_path=' + image_path + ' --output_png=' + output_png +
+      ' --max_results=' + str(max_results) + ' --score_threshold=' +
+      str(score_threshold) + ' --class_name_whitelist="' +
+      str(class_name_whitelist) + '" --class_name_blacklist="' +
+      str(class_name_blacklist) + '" --use_coral=' + str(use_coral)
+  ],
+                 shell=True,
+                 check=True)
+
+
+def run_main(argv):
+  del argv  # Unused.
+  classify(FLAGS.model_path, FLAGS.image_path, FLAGS.output_png,
+           FLAGS.max_results, FLAGS.score_threshold, FLAGS.class_name_whitelist,
+           FLAGS.class_name_blacklist, FLAGS.use_coral)
+
+
+# Simple wrapper to make the code pip-friendly
+def main():
+  app.run(main=run_main, argv=sys.argv)
+
+
+if __name__ == '__main__':
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/BUILD
index 9a837e2d..481fd8ec 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/BUILD
@@ -1,6 +1,6 @@
 package(
     default_visibility = [
-        "//tensorflow_lite_support:users",
+        "//tensorflow_lite_support:internal",
     ],
     licenses = ["notice"],  # Apache 2.0
 )
@@ -9,6 +9,9 @@
     name = "image_utils",
     srcs = ["image_utils.cc"],
     hdrs = ["image_utils.h"],
+    visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
     deps = [
         "//tensorflow_lite_support/cc/port:integral_types",
         "//tensorflow_lite_support/cc/port:status_macros",
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc
index 004d89a..efdcda9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.cc
@@ -23,11 +23,11 @@
 #define STB_IMAGE_IMPLEMENTATION
 #define STB_IMAGE_WRITE_IMPLEMENTATION
 
-#include "absl/status/status.h"
-#include "absl/strings/match.h"
-#include "absl/strings/str_format.h"
-#include "stb_image.h"
-#include "stb_image_write.h"
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/match.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
+#include "stb_image.h"                // from @stblib
+#include "stb_image_write.h"          // from @stblib
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h
index 38f62b6..9e7e3ba 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/examples/task/vision/desktop/utils/image_utils.h
@@ -15,8 +15,8 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_VISION_DESKTOP_UTILS_IMAGE_UTILS_H_
 #define TENSORFLOW_LITE_SUPPORT_EXAMPLES_TASK_VISION_DESKTOP_UTILS_IMAGE_UTILS_H_
 
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
+#include "absl/status/status.h"        // from @com_google_absl
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/integral_types.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/BUILD
index 07b8951..b1e6c4c 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/BUILD
@@ -1,9 +1,9 @@
-# TensorFlow Lite Task Library - Text
+# TensorFlow Lite Task Library
 
 load(
-    "@org_tensorflow//tensorflow/lite/experimental/ios:ios.bzl",
+    "@org_tensorflow//tensorflow/lite/ios:ios.bzl",
     "TFL_MINIMUM_OS_VERSION",
-    "tflite_ios_static_framework",
+    "tflite_ios_framework",
 )
 load(
     "//tensorflow_lite_support/ios:ios.bzl",
@@ -18,10 +18,17 @@
 strip_c_api_include_path_prefix(
     name = "strip_c_api_include_path",
     hdr_labels = [
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier_c_api.h",
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier_c_api.h",
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier_c_api_common.h",
-        "//tensorflow_lite_support/cc/task/text/qa:bert_qa_c_api.h",
+        "//tensorflow_lite_support/c/task/text:bert_nl_classifier.h",
+        "//tensorflow_lite_support/c/task/text:nl_classifier.h",
+        "//tensorflow_lite_support/c/task/text:nl_classifier_common.h",
+        "//tensorflow_lite_support/c/task/text:bert_question_answerer.h",
+        "//tensorflow_lite_support/c/task/vision:image_classifier.h",
+        "//tensorflow_lite_support/c/task/processor:bounding_box.h",
+        "//tensorflow_lite_support/c/task/vision/core:frame_buffer.h",
+        "//tensorflow_lite_support/c/task/processor:classification_result.h",
+        "//tensorflow_lite_support/c/task/processor:classification_options.h",
+        "//tensorflow_lite_support/c/task/core:base_options.h",
+        "//tensorflow_lite_support/c:common.h",
     ],
 )
 
@@ -29,20 +36,75 @@
 # which includes the TFLite runtime in it.
 #
 # bazel build -c opt --config=ios_fat //tensorflow_lite_support/ios:TensorFlowLiteTaskTextC_framework
-tflite_ios_static_framework(
+tflite_ios_framework(
     name = "TensorFlowLiteTaskTextC_framework",
     hdrs = [
-        ":bert_nl_classifier_c_api.h",
-        ":bert_qa_c_api.h",
-        ":nl_classifier_c_api.h",
-        ":nl_classifier_c_api_common.h",
+        ":bert_nl_classifier.h",
+        ":bert_question_answerer.h",
+        ":nl_classifier.h",
+        ":nl_classifier_common.h",
     ],
     allowlist_symbols_file = ":allowlist_TensorFlowLiteTaskText.txt",
     bundle_name = "TensorFlowLiteTaskTextC",
     minimum_os_version = TFL_MINIMUM_OS_VERSION,
     deps = [
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier_c_api",
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier_c_api",
-        "//tensorflow_lite_support/cc/task/text/qa:bert_qa_c_api",
+        "//tensorflow_lite_support/c/task/text:bert_nl_classifier",
+        "//tensorflow_lite_support/c/task/text:bert_question_answerer",
+        "//tensorflow_lite_support/c/task/text:nl_classifier",
+    ],
+)
+
+# Xcode 12 does not support ios fat libraries. Frameworks built for multiple
+# architectures should be compiled into a .xcframework inside. Bazel currently
+# does not support building .xcframework. You have to build the framework
+# for the architecture you decide to test on.
+# Use the below command to build for arm64 which lets you test the library on
+# iOS devices.
+# bazel build -c opt --config=ios_arm64 //tensorflow_lite_support/ios:TensorFlowLiteTaskVisionC_framework
+tflite_ios_framework(
+    name = "TensorFlowLiteTaskVisionC_framework",
+    hdrs = [
+        ":base_options.h",
+        ":bounding_box.h",
+        ":classification_options.h",
+        ":classification_result.h",
+        ":common.h",
+        ":frame_buffer.h",
+        ":image_classifier.h",
+    ],
+    allowlist_symbols_file = ":allowlist_TensorFlowLiteTaskVision.txt",
+    bundle_name = "TensorFlowLiteTaskVisionC",
+    minimum_os_version = TFL_MINIMUM_OS_VERSION,
+    deps = [
+        "//tensorflow_lite_support/c/task/vision:image_classifier",
+    ],
+)
+
+objc_library(
+    name = "TFLCommon",
+    hdrs = [
+        "sources/TFLCommon.h",
+    ],
+    module_name = "TFLCommon",
+    visibility = [
+        "//tensorflow_lite_support:__subpackages__",
+    ],
+)
+
+objc_library(
+    name = "TFLCommonUtils",
+    srcs = [
+        "sources/TFLCommonUtils.m",
+    ],
+    hdrs = [
+        "sources/TFLCommonUtils.h",
+    ],
+    module_name = "TFLCommonUtils",
+    visibility = [
+        "//tensorflow_lite_support:__subpackages__",
+    ],
+    deps = [
+        "//tensorflow_lite_support/c:common",
+        "//tensorflow_lite_support/ios:TFLCommon",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/TensorFlowLiteTaskText.podspec.template b/third_party/tflite_support/src/tensorflow_lite_support/ios/TensorFlowLiteTaskText.podspec.template
index 62c3f33..63bd9f7b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/TensorFlowLiteTaskText.podspec.template
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/TensorFlowLiteTaskText.podspec.template
@@ -13,7 +13,7 @@
   s.module_name = 'TensorFlowLiteTaskText'
   s.static_framework = true
 
-  s.dependency 'GoogleToolboxForMac', '2.2.1'
+  s.dependency 'GoogleToolboxForMac', '~> 2.2'
 
   objc_dir = 'tensorflow_lite_support/ios/task/text/'
   s.public_header_files = [
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskText.txt b/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskText.txt
index 3af5b0b1..e8ae288 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskText.txt
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskText.txt
@@ -1,3 +1 @@
-_NLClassifier*
-_BertNLClassifier*
-_BertQuestionAnswerer*
+_TfLite*
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskVision.txt b/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskVision.txt
new file mode 100644
index 0000000..e8ae288
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/allowlist_TensorFlowLiteTaskVision.txt
@@ -0,0 +1 @@
+_TfLite*
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h
new file mode 100644
index 0000000..2ca42fb
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommon.h
@@ -0,0 +1,213 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <Foundation/Foundation.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+/**
+ * @enum TFLSupportErrorCode
+ * This enum specifies  error codes for TensorFlow Lite Task Library.
+ * It maintains a 1:1 mapping to TfLiteSupportErrorCode of C libray.
+ */
+typedef NS_ENUM(NSUInteger, TFLSupportErrorCode) {
+
+  /** Unspecified error. */
+  TFLSupportErrorCodeUnspecifiedError = 1,
+
+  /** Invalid argument specified. */
+  TFLSupportErrorCodeInvalidArgumentError = 2,
+
+  /** Invalid FlatBuffer file or buffer specified. */
+  TFLSupportErrorCodeInvalidFlatBufferError = 3,
+
+  /** Model contains a builtin op that isn't supported by the OpResolver or
+   delegates.  */
+  TFLSupportErrorCodeUnsupportedBuiltinOpError = 4,
+
+  /** Model contains a custom op that isn't supported by the OpResolver or
+   * delegates. */
+  TFLSupportErrorCodeUnsupportedCustomOpError = 5,
+
+  /** File I/O error codes. */
+
+  /** No such file.  */
+  TFLSupportErrorCodeFileNotFoundError = 100,
+
+  /** Permission issue. */
+  TFLSupportErrorCodeFilePermissionDeniedError,
+
+  /** I/O error when reading file. */
+  TFLSupportErrorCodeFileReadError,
+
+  /** I/O error when mmap-ing file. */
+  TFLSupportErrorCodeFileMmapError,
+
+  /** TensorFlow Lite metadata error codes. */
+
+  /** Unexpected schema version (aka file_identifier) in the Metadata
+     FlatBuffer. */
+  TFLSupportErrorCodeMetadataInvalidSchemaVersionError = 200,
+
+  /** No such associated file within metadata, or file has not been packed. */
+  TFLSupportErrorCodeMetadataAssociatedFileNotFoundError,
+
+  /** ZIP I/O error when unpacking an associated file. */
+  TFLSupportErrorCodeMetadataAssociatedFileZipError,
+
+  /**
+   * Inconsistency error between the metadata and actual TF Lite model.
+   * E.g.: number of labels and output tensor values differ.
+   */
+  TFLSupportErrorCodeMetadataInconsistencyError,
+
+  /**
+   * Invalid process units specified.
+   * E.g.: multiple ProcessUnits with the same type for a given tensor.
+   */
+  TFLSupportErrorCodeMetadataInvalidProcessUnitsError,
+
+  /**
+   * Inconsistency error with the number of labels.
+   * E.g.: label files for different locales have a different number of labels.
+   */
+  TFLSupportErrorCodeMetadataNumLabelsMismatchError,
+
+  /**
+   * Score calibration parameters parsing error.
+   * E.g.: too many parameters provided in the corresponding associated file.
+   */
+  TFLSupportErrorCodeMetadataMalformedScoreCalibrationError,
+
+  /** Unexpected number of subgraphs for the current task.
+   * E.g.: image classification expects a single subgraph.
+   */
+  TFLSupportErrorCodeMetadataInvalidNumSubgraphsError,
+  /**
+   * A given tensor requires NormalizationOptions but none were found.
+   * E.g.: float input tensor requires normalization to preprocess input images.
+   */
+  TFLSupportErrorCodeMetadataMissingNormalizationOptionsError,
+
+  /**
+   * Invalid ContentProperties specified.
+   * E.g. expected ImageProperties, got BoundingBoxProperties.
+   */
+  TFLSupportErrorCodeMetadataInvalidContentPropertiesError,
+
+  /**
+   * Metadata is mandatory but was not found.
+   * E.g. current task requires TFLite Model Metadata but none was found.
+   */
+  TFLSupportErrorCodeMetadataNotFoundError,
+
+  /**
+   * Associated TENSOR_AXIS_LABELS or TENSOR_VALUE_LABELS file is mandatory but
+   * none was found or it was empty.
+   * E.g. current task requires labels but none were found.
+   */
+  TFLSupportErrorCodeMetadataMissingLabelsError,
+
+  /**
+   * The ProcessingUnit for tokenizer is not correctly configured.
+   * E.g BertTokenizer doesn't have a valid vocab file associated.
+   */
+  TFLSupportErrorCodeMetadataInvalidTokenizerError,
+
+  /** Input tensor(s) error codes. */
+
+  /**
+   * Unexpected number of input tensors for the current task.
+   * E.g. current task expects a single input tensor.
+   */
+  TFLSupportErrorCodeInvalidNumInputTensorsError = 300,
+
+  /**
+   * Unexpected input tensor dimensions for the current task.
+   * E.g.: only 4D input tensors supported.
+   */
+  TFLSupportErrorCodeInvalidInputTensorDimensionsError,
+
+  /**
+   * Unexpected input tensor type for the current task.
+   * E.g.: current task expects a uint8 pixel image as input.
+   */
+  TFLSupportErrorCodeInvalidInputTensorTypeError,
+
+  /**
+   * Unexpected input tensor bytes size.
+   * E.g.: size in bytes does not correspond to the expected number of pixels.
+   */
+  TFLSupportErrorCodeInvalidInputTensorSizeError,
+
+  /**
+   * No correct input tensor found for the model.
+   * E.g.: input tensor name is not part of the text model's input tensors.
+   */
+  TFLSupportErrorCodeInputTensorNotFoundError,
+
+  /** Output tensor(s) error codes. */
+
+  /**
+   * Unexpected output tensor dimensions for the current task.
+   * E.g.: only a batch size of 1 is supported.
+   */
+  TFLSupportErrorCodeInvalidOutputTensorDimensionsError = 400,
+
+  /**
+   * Unexpected input tensor type for the current task.
+   * E.g.: multi-head model with different output tensor types.
+   */
+  TFLSupportErrorCodeInvalidOutputTensorTypeError,
+
+  /**
+   * No correct output tensor found for the model.
+   * E.g.: output tensor name is not part of the text model's output tensors.
+   */
+  TFLSupportErrorCodeOutputTensorNotFoundError,
+
+  /**
+   * Unexpected number of output tensors for the current task.
+   * E.g.: current task expects a single output tensor.
+   */
+  TFLSupportErrorCodeInvalidNumOutputTensorsError,
+
+  /** Image processing error codes. **/
+
+  /**  Unspecified image processing failures. */
+  TFLSupportErrorCodeImageProcessingError = 500,
+
+  /**
+   * Unexpected input or output buffer metadata.
+   * E.g.: rotate RGBA buffer to Grayscale buffer by 90 degrees.
+   */
+  TFLSupportErrorCodeImageProcessingInvalidArgumentError,
+  /**
+   * Image processing operation failures.
+   * E.g. libyuv rotation failed for an unknown reason.
+   */
+  TFLSupportErrorCodeImageProcessingBackendError,
+
+  /** kNotFound indicates some requested entity (such as a file or directory)
+     was not found. */
+  TFLSupportErrorCodeNotFoundError = 900,
+
+  /** kInternal indicates an internal error has occurred and some invariants
+   * expected by the underlying system have not been satisfied. This error code
+   * is reserved for serious errors.
+   */
+  TFLSupportErrorCodeInternalError,
+} NS_SWIFT_NAME(SupportErrorCode);
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h
new file mode 100644
index 0000000..a194b28
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.h
@@ -0,0 +1,63 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#import <Foundation/Foundation.h>
+#include "tensorflow_lite_support/c/common.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+/** Helper utility for the all tasks which encapsulates common functionality. */
+@interface TFLCommonUtils : NSObject
+
+/**
+ * Creates and saves an error originating from the task library with the given
+ * error code and description.
+ *
+ * @param code Error code.
+ * @param description Error description.
+ * @param error Pointer to the memory location where the created error should be
+ * saved. If `nil`, no error will be saved.
+ */
++ (void)customErrorWithCode:(NSInteger)code
+                description:(NSString*)description
+                      error:(NSError**)error;
+
+/**
+ * Creates and saves an error originating from the task library from a C library
+ * error, TfLiteSupportError .
+ *
+ * @param supportError C library error.
+ * @param error Pointer to the memory location where the created error should be
+ * saved. If `nil`, no error will be saved.
+ */
++ (void)errorFromTfLiteSupportError:(TfLiteSupportError*)supportError
+                              error:(NSError**)error;
+
+/**
+ * Allocates a block of memory with the specified size and returns a pointer to
+ * it. If memory cannot be allocated because of an invalid memSize, it saves an
+ * error. In other cases, it terminates program execution.
+ *
+ * @param memSize size of memory to be allocated
+ * @param error Pointer to the memory location where errors if any should be
+ * saved. If `nil`, no error will be saved.
+ *
+ * @return Pointer to the allocated block of memory on successfull allocation.
+ * nil in case as error is encountered because of invalid memSize. If failure is
+ * due to any other reason, method terminates program execution.
+ */
++ (void*)mallocWithSize:(size_t)memSize error:(NSError**)error;
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m
new file mode 100644
index 0000000..2f2d85a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/sources/TFLCommonUtils.m
@@ -0,0 +1,63 @@
+// Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//    http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "tensorflow_lite_support/ios/sources/TFLCommonUtils.h"
+#import "tensorflow_lite_support/ios/sources/TFLCommon.h"
+
+/** Error domain of TensorFlow Lite Support related errors. */
+static NSString* const TFLSupportTaskErrorDomain = @"org.tensorflow.lite.tasks";
+
+@implementation TFLCommonUtils
+
++ (void)customErrorWithCode:(NSInteger)code
+                description:(NSString*)description
+                      error:(NSError**)error {
+  if (error)
+    *error =
+        [NSError errorWithDomain:TFLSupportTaskErrorDomain
+                            code:code
+                        userInfo:@{NSLocalizedDescriptionKey : description}];
+}
+
++ (void)errorFromTfLiteSupportError:(TfLiteSupportError*)supportError
+                              error:(NSError**)error {
+  if (supportError && error)
+    *error = [NSError errorWithDomain:TFLSupportTaskErrorDomain
+                                 code:supportError->code
+                             userInfo:@{
+                               NSLocalizedDescriptionKey : [NSString
+                                   stringWithCString:supportError->message
+                                            encoding:NSUTF8StringEncoding]
+                             }];
+}
+
++ (void*)mallocWithSize:(size_t)memSize error:(NSError**)error {
+  if (!memSize) {
+    [TFLCommonUtils
+        customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+                description:
+                    @"Invalid memory size passed for allocation of object."
+                      error:error];
+    return NULL;
+  }
+
+  void* allocedMemory = malloc(memSize);
+  if (!allocedMemory && memSize) {
+    exit(-1);
+  }
+
+  return allocedMemory;
+}
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/BUILD
new file mode 100644
index 0000000..6102841
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/BUILD
@@ -0,0 +1,30 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+objc_library(
+    name = "TFLBaseOptions",
+    srcs = [
+        "sources/TFLBaseOptions.m",
+    ],
+    hdrs = [
+        "sources/TFLBaseOptions.h",
+    ],
+    module_name = "TFLBaseOptions",
+)
+
+objc_library(
+    name = "TFLBaseOptionsHelpers",
+    srcs = [
+        "sources/TFLBaseOptions+Helpers.m",
+    ],
+    hdrs = [
+        "sources/TFLBaseOptions+Helpers.h",
+    ],
+    module_name = "TFLBaseOptionsHelpers",
+    deps = [
+        "//tensorflow_lite_support/c/task/core:base_options",
+        "//tensorflow_lite_support/ios/task/core:TFLBaseOptions",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h
new file mode 100644
index 0000000..90864c7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h
@@ -0,0 +1,24 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#include "tensorflow_lite_support/c/task/core/base_options.h"
+#import "third_party/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+@interface TFLBaseOptions (Helpers)
+- (void)copyBaseOptionsToCBaseOptions:(TfLiteBaseOptions*)cBaseOptions;
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m
new file mode 100644
index 0000000..ddab0f7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.m
@@ -0,0 +1,25 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h"
+
+@implementation TFLBaseOptions (Helpers)
+
+- (void)copyBaseOptionsToCBaseOptions:(TfLiteBaseOptions*)cBaseOptions {
+  if (self.modelFile.filePath) {
+    cBaseOptions->model_file.file_path = self.modelFile.filePath.UTF8String;
+  }
+}
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h
new file mode 100644
index 0000000..0f92dd1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h
@@ -0,0 +1,78 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+ http://www.apache.org/licenses/LICENSE-2.0
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <Foundation/Foundation.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+/**
+ * Holds cpu settings.
+ */
+NS_SWIFT_NAME(CpuSettings)
+@interface TFLCpuSettings : NSObject <NSCopying>
+
+/** Specifies the number of threads to be used for TFLite ops that support
+ * multi-threadingwhen running inference with CPU.
+ * @discussion This property hould be greater than 0 or equal to -1. Setting  it
+ * to -1 has the effect to let TFLite runtime set the value.
+ */
+@property(nonatomic, assign) int numThreads;
+
+@end
+
+/**
+ * Holds settings for one possible acceleration configuration.
+ */
+NS_SWIFT_NAME(ComputeSettings)
+@interface TFLComputeSettings : NSObject <NSCopying>
+
+/** Holds cpu settings. */
+@property(nonatomic, copy) TFLCpuSettings* cpuSettings;
+
+@end
+
+/**
+ * Holds settings for one possible acceleration configuration.
+ */
+NS_SWIFT_NAME(ExternalFile)
+@interface TFLExternalFile : NSObject <NSCopying>
+
+/** Path to the file in bundle. */
+@property(nonatomic, copy) NSString* filePath;
+/// Add provision for other sources in future.
+
+@end
+
+/**
+ * Holds the base options that is used for creation of any type of task. It has
+ * fields with important information acceleration configuration, tflite model
+ * source etc.
+ */
+NS_SWIFT_NAME(BaseOptions)
+@interface TFLBaseOptions : NSObject <NSCopying>
+
+/**
+ * The external model file, as a single standalone TFLite file. It could be
+ * packed with TFLite Model Metadata[1] and associated files if exist. Fail to
+ * provide the necessary metadata and associated files might result in errors.
+ */
+@property(nonatomic, copy) TFLExternalFile* modelFile;
+
+/**
+ * Holds settings for one possible acceleration configuration including.cpu/gpu
+ * settings. Please see documentation of TfLiteComputeSettings and its members
+ * for more details.
+ */
+@property(nonatomic, copy) TFLComputeSettings* computeSettings;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m
new file mode 100644
index 0000000..1e536cd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.m
@@ -0,0 +1,94 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h"
+
+@implementation TFLCpuSettings
+@synthesize numThreads;
+
+- (instancetype)init {
+  self = [super init];
+  if (self) {
+    self.numThreads = -1;
+  }
+  return self;
+}
+
+- (id)copyWithZone:(NSZone*)zone {
+  TFLCpuSettings* cpuSettings = [[TFLCpuSettings alloc] init];
+
+  [cpuSettings setNumThreads:self.numThreads];
+
+  return cpuSettings;
+}
+
+@end
+
+@implementation TFLComputeSettings
+@synthesize cpuSettings;
+
+- (instancetype)init {
+  self = [super init];
+  if (self) {
+    self.cpuSettings = [[TFLCpuSettings alloc] init];
+  }
+  return self;
+}
+
+- (id)copyWithZone:(NSZone*)zone {
+  TFLComputeSettings* computeSettings = [[TFLComputeSettings alloc] init];
+
+  [computeSettings setCpuSettings:self.cpuSettings];
+
+  return computeSettings;
+}
+
+@end
+
+@implementation TFLExternalFile
+@synthesize filePath;
+
+- (id)copyWithZone:(NSZone*)zone {
+  TFLExternalFile* externalFile = [[TFLExternalFile alloc] init];
+
+  [externalFile setFilePath:self.filePath];
+
+  return externalFile;
+}
+
+@end
+
+@implementation TFLBaseOptions
+@synthesize modelFile;
+@synthesize computeSettings;
+
+- (instancetype)init {
+  self = [super init];
+  if (self) {
+    self.computeSettings = [[TFLComputeSettings alloc] init];
+    self.modelFile = [[TFLExternalFile alloc] init];
+  }
+  return self;
+}
+
+- (id)copyWithZone:(NSZone*)zone {
+  TFLBaseOptions* baseOptions = [[TFLBaseOptions alloc] init];
+
+  [baseOptions setModelFile:self.modelFile];
+  [baseOptions setComputeSettings:self.computeSettings];
+
+  return baseOptions;
+}
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/BUILD
new file mode 100644
index 0000000..f6600e0
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/BUILD
@@ -0,0 +1,43 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:internal"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+objc_library(
+    name = "TFLClassificationOptions",
+    srcs = [
+        "sources/TFLClassificationOptions.m",
+    ],
+    hdrs = [
+        "sources/TFLClassificationOptions.h",
+    ],
+    module_name = "TFLClassificationOptions",
+)
+
+objc_library(
+    name = "TFLClassificationResult",
+    srcs = [
+        "sources/TFLClassificationResult.m",
+    ],
+    hdrs = [
+        "sources/TFLClassificationResult.h",
+    ],
+    module_name = "TFLClassificationResult",
+)
+
+objc_library(
+    name = "TFLClassificationOptionsHelpers",
+    srcs = [
+        "sources/TFLClassificationOptions+Helpers.m",
+    ],
+    hdrs = [
+        "sources/TFLClassificationOptions+Helpers.h",
+    ],
+    module_name = "TFLClassificationOptionsHelpers",
+    deps = [
+        "//tensorflow_lite_support/c/task/processor:classification_options",
+        "//tensorflow_lite_support/ios:TFLCommon",
+        "//tensorflow_lite_support/ios:TFLCommonUtils",
+        "//tensorflow_lite_support/ios/task/processor:TFLClassificationOptions",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h
new file mode 100644
index 0000000..78a1f965
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h
@@ -0,0 +1,29 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#include "tensorflow_lite_support/c/task/processor/classification_options.h"
+#import "third_party/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+@interface TFLClassificationOptions (Helpers)
+- (BOOL)copyClassificationOptionsToCClassificationOptions:
+            (TfLiteClassificationOptions*)cClassificationOptions
+                                                    error:(NSError**)error;
+
+- (void)deleteCStringArraysOfClassificationOptions:
+    (TfLiteClassificationOptions*)cClassificationOptions;
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m
new file mode 100644
index 0000000..07254ab
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.m
@@ -0,0 +1,118 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/sources/TFLCommon.h"
+#import "tensorflow_lite_support/ios/sources/TFLCommonUtils.h"
+#import "tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h"
+
+@implementation TFLClassificationOptions (Helpers)
+
++ (char**)cStringArrayFromNSArray:(NSArray<NSString*>*)strings
+                            error:(NSError**)error {
+  if (strings.count <= 0) {
+    [TFLCommonUtils
+        customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+                description:
+                    @"Invalid length of strings found for list type options."
+                      error:error];
+    return NULL;
+  }
+
+  char** cStrings = (char**)calloc(strings.count, sizeof(char*));
+
+  if (!cStrings) {
+    [TFLCommonUtils
+        customErrorWithCode:TFLSupportErrorCodeInternalError
+                description:@"Could not initialize list type options."
+                      error:error];
+    return nil;
+  }
+
+  for (NSInteger i = 0; i < strings.count; i++) {
+    char* cString = [TFLCommonUtils
+        mallocWithSize:[strings[i]
+                           lengthOfBytesUsingEncoding:NSUTF8StringEncoding] +
+                       1
+                 error:error];
+    if (!cString)
+      return nil;
+
+    strcpy(cString, strings[i].UTF8String);
+  }
+
+  return cStrings;
+}
+
++ (void)deleteCStringsArray:(char**)cStrings count:(int)count {
+  for (NSInteger i = 0; i < count; i++) {
+    free(cStrings[i]);
+  }
+
+  free(cStrings);
+}
+
+- (BOOL)copyClassificationOptionsToCClassificationOptions:
+            (TfLiteClassificationOptions*)cClassificationOptions
+                                                    error:(NSError**)error {
+  cClassificationOptions->score_threshold = self.scoreThreshold;
+  cClassificationOptions->max_results = (int)self.maxResults;
+
+  if (self.labelDenyList) {
+    char** cClassNameBlackList =
+        [TFLClassificationOptions cStringArrayFromNSArray:self.labelDenyList
+                                                    error:error];
+    if (!cClassNameBlackList) {
+      return NO;
+    }
+    cClassificationOptions->label_denylist.list = cClassNameBlackList;
+    cClassificationOptions->label_denylist.length =
+        (int)self.labelDenyList.count;
+  }
+
+  if (self.labelAllowList) {
+    char** cClassNameWhiteList =
+        [TFLClassificationOptions cStringArrayFromNSArray:self.labelAllowList
+                                                    error:error];
+    if (!cClassNameWhiteList) {
+      return NO;
+    }
+
+    cClassificationOptions->label_allowlist.list = cClassNameWhiteList;
+    cClassificationOptions->label_allowlist.length =
+        (int)self.labelAllowList.count;
+  }
+
+  if (self.displayNamesLocal) {
+    cClassificationOptions->display_names_local =
+        (char*)self.displayNamesLocal.UTF8String;
+  }
+
+  return YES;
+}
+
+- (void)deleteCStringArraysOfClassificationOptions:
+    (TfLiteClassificationOptions*)cClassificationOptions {
+  if (self.labelAllowList) {
+    [TFLClassificationOptions
+        deleteCStringsArray:cClassificationOptions->label_allowlist.list
+                      count:cClassificationOptions->label_allowlist.length];
+  }
+
+  if (self.labelDenyList) {
+    [TFLClassificationOptions
+        deleteCStringsArray:cClassificationOptions->label_denylist.list
+                      count:cClassificationOptions->label_denylist.length];
+  }
+}
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h
new file mode 100644
index 0000000..cc0c8a8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h
@@ -0,0 +1,42 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <Foundation/Foundation.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+/**
+ * Holds settings for any single classification task.
+ */
+@interface TFLClassificationOptions : NSObject <NSCopying>
+
+/** If set, all classes  in this list will be filtered out from the results . */
+@property(nonatomic, copy) NSArray* labelDenyList;
+
+/** If set, all classes not in this list will be filtered out from the results .
+ */
+@property(nonatomic, copy) NSArray* labelAllowList;
+
+/** Display names local for display names*/
+@property(nonatomic, copy) NSString* displayNamesLocal;
+
+/** Results with score threshold greater than this value are returned . */
+@property(nonatomic, assign) float scoreThreshold;
+
+/** Limit to the number of classes that can be returned in results. */
+@property(nonatomic, assign) NSInteger maxResults;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m
new file mode 100644
index 0000000..dca232d6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.m
@@ -0,0 +1,46 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h"
+
+@implementation TFLClassificationOptions
+@synthesize scoreThreshold;
+@synthesize maxResults;
+@synthesize labelAllowList;
+@synthesize labelDenyList;
+@synthesize displayNamesLocal;
+
+- (instancetype)init {
+  self = [super init];
+  if (self) {
+    self.maxResults = -1;
+    self.scoreThreshold = 0;
+  }
+  return self;
+}
+
+- (id)copyWithZone:(NSZone*)zone {
+  TFLClassificationOptions* classificationOptions =
+      [[TFLClassificationOptions alloc] init];
+
+  [classificationOptions setScoreThreshold:self.scoreThreshold];
+  [classificationOptions setMaxResults:self.maxResults];
+  [classificationOptions setLabelDenyList:self.labelDenyList];
+  [classificationOptions setLabelAllowList:self.labelAllowList];
+  [classificationOptions setDisplayNamesLocal:self.displayNamesLocal];
+
+  return classificationOptions;
+}
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h
new file mode 100644
index 0000000..c0d6fb3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h
@@ -0,0 +1,60 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#import <Foundation/Foundation.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+/** Encapsulates information about a class in the classification results. */
+@interface TFLCategory : NSObject
+
+/** Display name of the class. */
+@property(nonatomic, copy) NSString* displayName;
+
+/** Class name of the class . */
+@property(nonatomic, copy) NSString* label;
+
+/** Confidence score for this class . */
+@property(nonatomic, assign) float score;
+
+/** The index of the class in the corresponding label map, usually packed in the
+ * TFLite Model Metadata. */
+@property(nonatomic, assign) NSInteger classIndex;
+
+@end
+
+/** Encapsulates list of predicted classes (aka labels) for a given image
+ * classifier head. */
+@interface TFLClassifications : NSObject
+
+/**
+ * The index of the image classifier head these classes refer to. This is useful
+ * for multi-head models.
+ */
+@property(nonatomic, assign) int headIndex;
+
+/** The array of predicted classes, usually sorted by descending scores
+ * (e.g.from high to low probability). */
+@property(nonatomic, copy) NSArray<TFLCategory*>* categories;
+
+@end
+
+/** Encapsulates results of any classification task. */
+@interface TFLClassificationResult : NSObject
+
+@property(nonatomic, copy) NSArray<TFLClassifications*>* classifications;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.m
new file mode 100644
index 0000000..febf230b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.m
@@ -0,0 +1,33 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#import "tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h"
+
+@implementation TFLCategory
+@synthesize displayName;
+@synthesize label;
+@synthesize score;
+@synthesize classIndex;
+@end
+
+@implementation TFLClassifications
+@synthesize headIndex;
+@synthesize categories;
+
+@end
+
+@implementation TFLClassificationResult
+@synthesize classifications;
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/BUILD
new file mode 100644
index 0000000..13b9809
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/BUILD
@@ -0,0 +1,19 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:__subpackages__"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+objc_library(
+    name = "TFLClassificationUtils",
+    srcs = [
+        "sources/TFLClassificationUtils.m",
+    ],
+    hdrs = [
+        "sources/TFLClassificationUtils.h",
+    ],
+    module_name = "TFLClassificationUtils",
+    deps = [
+        "//tensorflow_lite_support/c/task/processor:classification_result",
+        "//tensorflow_lite_support/ios/task/processor:TFLClassificationResult",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h
new file mode 100644
index 0000000..c52876e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h
@@ -0,0 +1,46 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <Foundation/Foundation.h>
+#import "third_party/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h"
+
+#include "tensorflow_lite_support/c/task/processor/classification_result.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+/** Helper utility for conversion between TFLite Task C Library Classification
+ * Results and iOS Classification Results . */
+@interface TFLClassificationUtils : NSObject
+
+/**
+ * Creates and retrurns a TFLClassificationResult from a
+ * TfLiteClassificationResult returned by TFLite Task C Library Classification
+ * tasks.
+ *
+ * @param cClassificationResult Classification results returned by TFLite Task C
+ * Library Classification tasks
+ *
+ * @return Classification Result of type TFLClassificationResult to be returned
+ * by inference methods of the iOS TF Lite Task Classification tasks.
+ */
++ (TFLClassificationResult*)classificationResultFromCClassificationResults:
+    (TfLiteClassificationResult*)cClassificationResult;
+
+- (instancetype)init NS_UNAVAILABLE;
+
++ (instancetype)new NS_UNAVAILABLE;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m
new file mode 100644
index 0000000..b5d884d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.m
@@ -0,0 +1,61 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h"
+
+@implementation TFLClassificationUtils
+
++ (TFLClassificationResult*)classificationResultFromCClassificationResults:
+    (TfLiteClassificationResult*)cClassificationResult {
+  if (cClassificationResult == nil)
+    return nil;
+
+  NSMutableArray* classificationHeads = [[NSMutableArray alloc] init];
+  for (int i = 0; i < cClassificationResult->size; i++) {
+    TfLiteClassifications cClassifications =
+        cClassificationResult->classifications[i];
+    NSMutableArray* classes = [[NSMutableArray alloc] init];
+    for (int j = 0; j < cClassifications.size; j++) {
+      TfLiteCategory cCategory = cClassifications.categories[j];
+      TFLCategory* resultCategory = [[TFLCategory alloc] init];
+
+      if (cCategory.display_name != nil) {
+        resultCategory.displayName =
+            [NSString stringWithCString:cCategory.display_name
+                               encoding:NSUTF8StringEncoding];
+      }
+
+      if (cCategory.label != nil) {
+        resultCategory.label =
+            [NSString stringWithCString:cCategory.label
+                               encoding:NSUTF8StringEncoding];
+      }
+
+      resultCategory.score = cCategory.score;
+      resultCategory.classIndex = (NSInteger)cCategory.index;
+      [classes addObject:resultCategory];
+    }
+    TFLClassifications* classificationHead = [[TFLClassifications alloc] init];
+    classificationHead.categories = classes;
+    classificationHead.headIndex = i;
+    [classificationHeads addObject:classificationHead];
+  }
+
+  TFLClassificationResult* classificationResult =
+      [[TFLClassificationResult alloc] init];
+  classificationResult.classifications = classificationHeads;
+  return classificationResult;
+}
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/BUILD
index fb369e9..1d11afd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/BUILD
@@ -1,10 +1,10 @@
 load("@build_bazel_rules_swift//swift:swift.bzl", "swift_library")
-load("@org_tensorflow//tensorflow/lite/experimental/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
+load("@org_tensorflow//tensorflow/lite/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
 load("@build_bazel_rules_apple//apple:ios.bzl", "ios_unit_test")
 load("@org_tensorflow//tensorflow/lite:special_rules.bzl", "tflite_ios_lab_runner")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -13,8 +13,9 @@
     srcs = ["Sources/TFLBertNLClassifier.m"],
     hdrs = ["Sources/TFLBertNLClassifier.h"],
     module_name = "TFLBertNLClassifier",
+    visibility = ["//tensorflow_lite_support:internal"],
     deps = [
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier_c_api",
+        "//tensorflow_lite_support/c/task/text:bert_nl_classifier",
         "@google_toolbox_for_mac//:GTM_Defines",
     ],
 )
@@ -24,12 +25,11 @@
     testonly = 1,
     srcs = ["Tests/TFLBertNLClassifierTest.swift"],
     data = [
-        "//tensorflow_lite_support/cc/test/testdata/task/text:nl_classifier_models",
+        "//tensorflow_lite_support/cc/test/testdata/task/text:bert_nl_classifier_models",
     ],
     tags = TFL_DEFAULT_TAGS,
     deps = [
         ":TFLBertNLClassifier",
-        "//third_party/swift/xctest",
     ],
 )
 
@@ -48,7 +48,7 @@
     testonly = 1,
     srcs = ["Tests/TFLBertNLClassifierTest.m"],
     data = [
-        "//tensorflow_lite_support/cc/test/testdata/task/text:nl_classifier_models",
+        "//tensorflow_lite_support/cc/test/testdata/task/text:bert_nl_classifier_models",
     ],
     tags = TFL_DEFAULT_TAGS,
     deps = [
@@ -71,8 +71,9 @@
     srcs = ["Sources/TFLNLClassifier.m"],
     hdrs = ["Sources/TFLNLClassifier.h"],
     module_name = "TFLNLClassifier",
+    visibility = ["//tensorflow_lite_support:internal"],
     deps = [
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier_c_api",
+        "//tensorflow_lite_support/c/task/text:nl_classifier",
         "@google_toolbox_for_mac//:GTM_Defines",
     ],
 )
@@ -87,7 +88,6 @@
     tags = TFL_DEFAULT_TAGS,
     deps = [
         ":TFLNLClassifier",
-        "//third_party/swift/xctest",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h
index 3ec5716..ac81a15 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h
@@ -17,6 +17,16 @@
 NS_ASSUME_NONNULL_BEGIN
 
 /**
+ * Options to configure TFLBertNLClassifier.
+ */
+@interface TFLBertNLClassifierOptions : NSObject
+
+// @deprecated maxSeqLen is now read from the model (i.e. input tensor size)
+// automatically.
+@property(nonatomic) int maxSeqLen;
+@end
+
+/**
  * Classifier API for NLClassification tasks with Bert models, categorizes
  * string into different classes. The API expects a Bert based TFLite model with
  * metadata populated.
@@ -41,6 +51,17 @@
     NS_SWIFT_NAME(bertNLClassifier(modelPath:));
 
 /**
+ * Creates TFLBertNLClassifier from a model file.
+ *
+ * @param modelPath Path to the classification model.
+ * @return A TFLBertNLClassifier instance.
+ */
++ (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath
+                                      options:
+                                          (TFLBertNLClassifierOptions*)options
+    NS_SWIFT_NAME(bertNLClassifier(modelPath:options:));
+
+/**
  * Performs classification on a NSString input, returns <NSString *, NSNumber *>
  * for categories and socres.
  *
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m
index e5dfaaf..8c45ee6 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.m
@@ -14,30 +14,48 @@
 ==============================================================================*/
 #import "tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLBertNLClassifier.h"
 #import "GTMDefines.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier_c_api.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h"
+#include "tensorflow_lite_support/c/task/text/bert_nl_classifier.h"
+#include "tensorflow_lite_support/c/task/text/nl_classifier_common.h"
 
 NS_ASSUME_NONNULL_BEGIN
 
+@implementation TFLBertNLClassifierOptions
+@synthesize maxSeqLen;
+@end
+
 @interface TFLBertNLClassifier ()
 /** BertNLClassifier backed by C API */
-@property(nonatomic) BertNLClassifier* bertNLClassifier;
+@property(nonatomic) TfLiteBertNLClassifier* bertNLClassifier;
 @end
 
 @implementation TFLBertNLClassifier
 
 - (void)dealloc {
-  BertNLClassifierDelete(_bertNLClassifier);
+  TfLiteBertNLClassifierDelete(_bertNLClassifier);
 }
 
 + (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath {
-  BertNLClassifier* classifier = BertNLClassifierFromFile(modelPath.UTF8String);
+  TfLiteBertNLClassifier* classifier =
+      TfLiteBertNLClassifierCreate(modelPath.UTF8String);
 
   _GTMDevAssert(classifier, @"Failed to create BertNLClassifier");
   return [[TFLBertNLClassifier alloc] initWithBertNLClassifier:classifier];
 }
 
-- (instancetype)initWithBertNLClassifier:(BertNLClassifier*)bertNLClassifier {
++ (instancetype)bertNLClassifierWithModelPath:(NSString*)modelPath
+                                      options:
+                                          (TFLBertNLClassifierOptions*)options {
+  // Note that maxSeqLen has been deprecated. Passing it to the C API is a
+  // no-op.
+  TfLiteBertNLClassifierOptions cOptions = {.max_seq_len = options.maxSeqLen};
+  TfLiteBertNLClassifier* classifier =
+      TfLiteBertNLClassifierCreateFromOptions(modelPath.UTF8String, &cOptions);
+  _GTMDevAssert(classifier, @"Failed to create BertNLClassifier");
+  return [[TFLBertNLClassifier alloc] initWithBertNLClassifier:classifier];
+}
+
+- (instancetype)initWithBertNLClassifier:
+    (TfLiteBertNLClassifier*)bertNLClassifier {
   self = [super init];
   if (self) {
     _bertNLClassifier = bertNLClassifier;
@@ -46,12 +64,12 @@
 }
 
 - (NSDictionary<NSString*, NSNumber*>*)classifyWithText:(NSString*)text {
-  struct Categories* cCategories =
-      BertNLClassifierClassify(_bertNLClassifier, text.UTF8String);
+  Categories* cCategories =
+      TfLiteBertNLClassifierClassify(_bertNLClassifier, text.UTF8String);
   NSMutableDictionary<NSString*, NSNumber*>* ret =
       [NSMutableDictionary dictionary];
   for (int i = 0; i < cCategories->size; i++) {
-    struct Category cCategory = cCategories->categories[i];
+    Category cCategory = cCategories->categories[i];
     [ret setValue:[NSNumber numberWithDouble:cCategory.score]
            forKey:[NSString stringWithUTF8String:cCategory.text]];
   }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m
index d15dfa3..39eb15c 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.m
@@ -14,8 +14,8 @@
 ==============================================================================*/
 #import "tensorflow_lite_support/ios/task/text/nlclassifier/Sources/TFLNLClassifier.h"
 #import "GTMDefines.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api.h"
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier_c_api_common.h"
+#include "tensorflow_lite_support/c/task/text/nl_classifier.h"
+#include "tensorflow_lite_support/c/task/text/nl_classifier_common.h"
 
 NS_ASSUME_NONNULL_BEGIN
 
@@ -30,31 +30,31 @@
 
 @interface TFLNLClassifier ()
 /** NLClassifier backed by C API */
-@property(nonatomic) NLClassifier* nlClassifier;
+@property(nonatomic) TfLiteNLClassifier* nlClassifier;
 @end
 
 @implementation TFLNLClassifier
 
 - (void)dealloc {
-  NLClassifierDelete(_nlClassifier);
+  TfLiteNLClassifierDelete(_nlClassifier);
 }
 
 + (instancetype)nlClassifierWithModelPath:(NSString*)modelPath
                                   options:(TFLNLClassifierOptions*)options {
-  struct NLClassifierOptions cOptions = {
+  TfLiteNLClassifierOptions cOptions = {
       .input_tensor_index = options.inputTensorIndex,
       .output_score_tensor_index = options.outputScoreTensorIndex,
       .output_label_tensor_index = options.outputLabelTensorIndex,
       .input_tensor_name = options.inputTensorName.UTF8String,
       .output_score_tensor_name = options.outputScoreTensorName.UTF8String,
       .output_label_tensor_name = options.outputLabelTensorName.UTF8String};
-  NLClassifier* classifier =
-      NLClassifierFromFileAndOptions(modelPath.UTF8String, &cOptions);
+  TfLiteNLClassifier* classifier =
+      TfLiteNLClassifierCreateFromOptions(modelPath.UTF8String, &cOptions);
   _GTMDevAssert(classifier, @"Failed to create NLClassifier");
   return [[TFLNLClassifier alloc] initWithNLClassifier:classifier];
 }
 
-- (instancetype)initWithNLClassifier:(NLClassifier*)nlClassifier {
+- (instancetype)initWithNLClassifier:(TfLiteNLClassifier*)nlClassifier {
   self = [super init];
   if (self) {
     _nlClassifier = nlClassifier;
@@ -63,12 +63,12 @@
 }
 
 - (NSDictionary<NSString*, NSNumber*>*)classifyWithText:(NSString*)text {
-  struct Categories* cCategories =
-      NLClassifierClassify(_nlClassifier, text.UTF8String);
+  Categories* cCategories =
+      TfLiteNLClassifierClassify(_nlClassifier, text.UTF8String);
   NSMutableDictionary<NSString*, NSNumber*>* ret =
       [NSMutableDictionary dictionary];
   for (int i = 0; i < cCategories->size; i++) {
-    struct Category cCategory = cCategories->categories[i];
+    Category cCategory = cCategories->categories[i];
     [ret setValue:[NSNumber numberWithDouble:cCategory.score]
            forKey:[NSString stringWithUTF8String:cCategory.text]];
   }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m
index 4f121b8..407be10 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.m
@@ -20,6 +20,7 @@
 
 @interface TFLBertNLClassifierTest : XCTestCase
 @property(nonatomic, nullable) NSString* bertModelPath;
+@property(nonatomic, nullable) TFLBertNLClassifierOptions* modelOptions;
 @end
 
 @implementation TFLBertNLClassifierTest
@@ -28,7 +29,7 @@
 - (void)setUp {
   [super setUp];
   NSBundle* bundle = [NSBundle bundleForClass:[self class]];
-  self.bertModelPath = [bundle pathForResource:@"test_model_nl_classifier_bert"
+  self.bertModelPath = [bundle pathForResource:@"bert_nl_classifier"
                                         ofType:@"tflite"];
 }
 
@@ -57,5 +58,39 @@
   XCTAssertGreaterThan([categories[@"negative"] doubleValue],
                        [categories[@"positive"] doubleValue]);
 }
+
+- (void)testCreateFromOptionsClassifyPositiveResult {
+  self.modelOptions = [[TFLBertNLClassifierOptions alloc] init];
+  [self.modelOptions setMaxSeqLen:128];
+
+  TFLBertNLClassifier* bertNLClassifier =
+      [TFLBertNLClassifier bertNLClassifierWithModelPath:self.bertModelPath
+                                                 options:self.modelOptions];
+
+  XCTAssertNotNil(bertNLClassifier);
+
+  NSDictionary<NSString*, NSNumber*>* categories = [bertNLClassifier
+      classifyWithText:@"it's a charming and often affecting journey"];
+
+  XCTAssertGreaterThan([categories[@"positive"] doubleValue],
+                       [categories[@"negative"] doubleValue]);
+}
+
+- (void)testCreateFromOptionsClassifyNegativeResult {
+  self.modelOptions = [[TFLBertNLClassifierOptions alloc] init];
+  [self.modelOptions setMaxSeqLen:128];
+
+  TFLBertNLClassifier* bertNLClassifier =
+      [TFLBertNLClassifier bertNLClassifierWithModelPath:self.bertModelPath
+                                                 options:self.modelOptions];
+
+  XCTAssertNotNil(bertNLClassifier);
+
+  NSDictionary<NSString*, NSNumber*>* categories =
+      [bertNLClassifier classifyWithText:@"unflinchingly bleak and desperate"];
+
+  XCTAssertGreaterThan([categories[@"negative"] doubleValue],
+                       [categories[@"positive"] doubleValue]);
+}
 @end
 NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.swift b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.swift
index d331b04..133b8f1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.swift
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/nlclassifier/Tests/TFLBertNLClassifierTest.swift
@@ -19,7 +19,7 @@
 class TFLBertNLClassifierTest: XCTestCase {
 
   static let bundle = Bundle(for: TFLBertNLClassifierTest.self)
-  static let bertModelPath = bundle.path(forResource: "test_model_nl_classifier_bert", ofType: "tflite")!
+  static let bertModelPath = bundle.path(forResource: "bert_nl_classifier", ofType: "tflite")!
 
   func testClassifyPositiveResult() {
     let bertNLClassifier = TFLBertNLClassifier.bertNLClassifier(
@@ -42,4 +42,32 @@
 
     XCTAssertGreaterThan(categories["negative"]!.doubleValue, categories["positive"]!.doubleValue)
   }
+
+  func testCreateFromOptionsClassifyPositiveResult() {
+    let modelOptions = TFLBertNLClassifierOptions()
+    modelOptions.maxSeqLen = 128
+    let bertNLClassifier = TFLBertNLClassifier.bertNLClassifier(
+      modelPath: TFLBertNLClassifierTest.bertModelPath,
+      options: modelOptions)
+
+    XCTAssertNotNil(bertNLClassifier)
+
+    let categories = bertNLClassifier.classify(text: "it's a charming and often affecting journey")
+
+    XCTAssertGreaterThan(categories["positive"]!.doubleValue, categories["negative"]!.doubleValue)
+  }
+
+  func testCreateFromOptionsClassifyNegativeResult() {
+    let modelOptions = TFLBertNLClassifierOptions()
+    modelOptions.maxSeqLen = 128
+    let bertNLClassifier = TFLBertNLClassifier.bertNLClassifier(
+      modelPath: TFLBertNLClassifierTest.bertModelPath,
+      options: modelOptions)
+
+    XCTAssertNotNil(bertNLClassifier)
+
+    let categories = bertNLClassifier.classify(text: "unflinchingly bleak and desperate")
+
+    XCTAssertGreaterThan(categories["negative"]!.doubleValue, categories["positive"]!.doubleValue)
+  }
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/BUILD
index 7998a8e..4b15aed 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/BUILD
@@ -1,10 +1,10 @@
 load("@build_bazel_rules_swift//swift:swift.bzl", "swift_library")
-load("@org_tensorflow//tensorflow/lite/experimental/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
+load("@org_tensorflow//tensorflow/lite/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
 load("@build_bazel_rules_apple//apple:ios.bzl", "ios_unit_test")
 load("@org_tensorflow//tensorflow/lite:special_rules.bzl", "tflite_ios_lab_runner")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -13,8 +13,9 @@
     srcs = ["Sources/TFLBertQuestionAnswerer.m"],
     hdrs = ["Sources/TFLBertQuestionAnswerer.h"],
     module_name = "TFLBertQuestionAnswerer",
+    visibility = ["//tensorflow_lite_support:internal"],
     deps = [
-        "//tensorflow_lite_support/cc/task/text/qa:bert_qa_c_api",
+        "//tensorflow_lite_support/c/task/text:bert_question_answerer",
         "@google_toolbox_for_mac//:GTM_Defines",
     ],
 )
@@ -30,7 +31,6 @@
     tags = TFL_DEFAULT_TAGS,
     deps = [
         ":TFLBertQuestionAnswerer",
-        "//third_party/swift/xctest",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m
index 2f410f4..b470c46 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.m
@@ -14,7 +14,7 @@
 ==============================================================================*/
 #import "tensorflow_lite_support/ios/task/text/qa/Sources/TFLBertQuestionAnswerer.h"
 #import "GTMDefines.h"
-#include "tensorflow_lite_support/cc/task/text/qa/bert_qa_c_api.h"
+#include "tensorflow_lite_support/c/task/text/bert_question_answerer.h"
 
 NS_ASSUME_NONNULL_BEGIN
 
@@ -25,25 +25,25 @@
 
 @interface TFLBertQuestionAnswerer ()
 /** BertQuestionAnswerer backed by C API */
-@property(nonatomic) BertQuestionAnswerer* bertQuestionAnswerer;
+@property(nonatomic) TfLiteBertQuestionAnswerer* bertQuestionAnswerer;
 @end
 
 @implementation TFLBertQuestionAnswerer
 
 - (void)dealloc {
-  BertQuestionAnswererDelete(_bertQuestionAnswerer);
+  TfLiteBertQuestionAnswererDelete(_bertQuestionAnswerer);
 }
 
 + (instancetype)questionAnswererWithModelPath:(NSString*)modelPath {
-  BertQuestionAnswerer* bert_qa =
-      BertQuestionAnswererFromFile(modelPath.UTF8String);
+  TfLiteBertQuestionAnswerer* bert_qa =
+      TfLiteBertQuestionAnswererCreate(modelPath.UTF8String);
 
   _GTMDevAssert(bert_qa, @"Failed to create BertQuestionAnswerer");
   return [[TFLBertQuestionAnswerer alloc] initWithBertQuestionAnswerer:bert_qa];
 }
 
 - (instancetype)initWithBertQuestionAnswerer:
-    (BertQuestionAnswerer*)bertQuestionAnswerer {
+    (TfLiteBertQuestionAnswerer*)bertQuestionAnswerer {
   self = [super init];
   if (self) {
     _bertQuestionAnswerer = bertQuestionAnswerer;
@@ -53,12 +53,12 @@
 
 - (NSArray<TFLQAAnswer*>*)answerWithContext:(NSString*)context
                                    question:(NSString*)question {
-  struct QaAnswers* cAnswers = BertQuestionAnswererAnswer(
+  TfLiteQaAnswers* cAnswers = TfLiteBertQuestionAnswererAnswer(
       _bertQuestionAnswerer, context.UTF8String, question.UTF8String);
   NSMutableArray<TFLQAAnswer*>* ret =
       [NSMutableArray arrayWithCapacity:cAnswers->size];
   for (int i = 0; i < cAnswers->size; i++) {
-    struct QaAnswer cAnswer = cAnswers->answers[i];
+    TfLiteQaAnswer cAnswer = cAnswers->answers[i];
     TFLQAAnswer* answer = [[TFLQAAnswer alloc] init];
     struct TFLPos pos = {
         .start = cAnswer.start, .end = cAnswer.end, .logit = cAnswer.logit};
@@ -66,7 +66,7 @@
     [answer setText:[NSString stringWithUTF8String:cAnswer.text]];
     [ret addObject:answer];
   }
-  BertQuestionAnswererQaAnswersDelete(cAnswers);
+  TfLiteQaAnswersDelete(cAnswers);
   return ret;
 }
 @end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/BUILD
new file mode 100644
index 0000000..c17dbc8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/BUILD
@@ -0,0 +1,26 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:__subpackages__"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+objc_library(
+    name = "TFLImageClassifier",
+    srcs = [
+        "sources/TFLImageClassifier.m",
+    ],
+    hdrs = [
+        "sources/TFLImageClassifier.h",
+    ],
+    module_name = "TFLImageClassifier",
+    deps = [
+        "//tensorflow_lite_support/c/task/vision:image_classifier",
+        "//tensorflow_lite_support/ios:TFLCommonUtils",
+        "//tensorflow_lite_support/ios/task/core:TFLBaseOptions",
+        "//tensorflow_lite_support/ios/task/core:TFLBaseOptionsHelpers",
+        "//tensorflow_lite_support/ios/task/processor:TFLClassificationOptions",
+        "//tensorflow_lite_support/ios/task/processor:TFLClassificationOptionsHelpers",
+        "//tensorflow_lite_support/ios/task/processor:TFLClassificationResult",
+        "//tensorflow_lite_support/ios/task/processor/utils:TFLClassificationUtils",
+        "//tensorflow_lite_support/ios/task/vision/utils:GMLImageUtils",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h
new file mode 100644
index 0000000..1b988f2b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h
@@ -0,0 +1,113 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <Foundation/Foundation.h>
+
+#import "third_party/tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions.h"
+#import "third_party/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions.h"
+#import "third_party/tensorflow_lite_support/ios/task/processor/sources/TFLClassificationResult.h"
+#import "third_party/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+/**
+ * Options to configure TFLImageClassifier.
+ */
+@interface TFLImageClassifierOptions : NSObject
+
+/**
+ * Base options that is used for creation of any type of task.
+ * @seealso TFLBaseOptions
+ */
+@property(nonatomic, copy) TFLBaseOptions* baseOptions;
+
+/**
+ * Options that configure the display and filtering of results.
+ * @seealso TFLClassificationOptions
+ */
+@property(nonatomic, copy) TFLClassificationOptions* classificationOptions;
+
+/**
+ * Initializes TFLImageClassifierOptions with the model path set to the
+ * specified path to a model file.
+ * @description The external model file, must be a single standalone TFLite
+ * file. It could be packed with TFLite Model Metadata[1] and associated files
+ * if exist. Fail to provide the necessary metadata and associated files might
+ * result in errors. Check the [documentation]
+ * (https://www.tensorflow.org/lite/convert/metadata) for each task about the
+ * specific requirement.
+ *
+ * @param modelPath Path to a TFLite model file.
+ * @return An instance of TFLImageClassifierOptions set to the specified
+ * modelPath.
+ */
+- (nullable instancetype)initWithModelPath:(nonnull NSString*)modelPath;
+
+@end
+
+/**
+ * A TensorFlow Lite Task Image Classifiier.
+ */
+@interface TFLImageClassifier : NSObject
+
+/**
+ * Creates TFLImageClassifier from a model file and specified options .
+ *
+ * @param options TFLImageClassifierOptions instance with the necessary
+ * properties set.
+ *
+ * @return A TFLImageClassifier instance.
+ */
++ (nullable instancetype)imageClassifierWithOptions:
+                             (nonnull TFLImageClassifierOptions*)options
+                                              error:(NSError**)error
+    NS_SWIFT_NAME(imageClassifier(options:));
+
+/**
+ * Performs classification on a GMLImage input, returns an array of
+ * categorization results where each member in the array is an array of
+ * TFLClass objects for each classification head.
+ *
+ * @param image input to the model.
+ * @return An NSArray<NSArray<TFLClass *>*> * of classification results.
+ */
+- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
+                                                    error:(NSError* _Nullable*)
+                                                              error
+    NS_SWIFT_NAME(classify(gmlImage:));
+
+/**
+ * Performs classification on a GMLImage input on the pixels in the
+ * specified bounding box, returns an array of categorization results
+ * where each member in the array is an array of TFLClass objects for
+ * each classification head.
+ *
+ * @param image input to the model.
+ * @param roi CGRect specifying region of interest in image.
+ *
+ * @return An NSArray<NSArray<TFLClass *>*> * of classification results.
+ */
+- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
+                                         regionOfInterest:(CGRect)roi
+                                                    error:(NSError* _Nullable*)
+                                                              error
+    NS_SWIFT_NAME(classify(gmlImage:regionOfInterest:));
+
+- (instancetype)init NS_UNAVAILABLE;
+
++ (instancetype)new NS_UNAVAILABLE;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m
new file mode 100644
index 0000000..06d6793
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.m
@@ -0,0 +1,143 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h"
+#import "tensorflow_lite_support/ios/sources/TFLCommon.h"
+#import "tensorflow_lite_support/ios/sources/TFLCommonUtils.h"
+#import "tensorflow_lite_support/ios/task/core/sources/TFLBaseOptions+Helpers.h"
+#import "tensorflow_lite_support/ios/task/processor/sources/TFLClassificationOptions+Helpers.h"
+#import "tensorflow_lite_support/ios/task/processor/utils/sources/TFLClassificationUtils.h"
+#import "tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h"
+
+#include "tensorflow_lite_support/c/task/vision/image_classifier.h"
+
+@interface TFLImageClassifier ()
+/** ImageClassifier backed by C API */
+@property(nonatomic) TfLiteImageClassifier* imageClassifier;
+@end
+
+@implementation TFLImageClassifierOptions
+@synthesize baseOptions;
+@synthesize classificationOptions;
+
+- (instancetype)init {
+  self = [super init];
+  if (self) {
+    self.baseOptions = [[TFLBaseOptions alloc] init];
+    self.classificationOptions = [[TFLClassificationOptions alloc] init];
+  }
+  return self;
+}
+
+- (nullable instancetype)initWithModelPath:(nonnull NSString*)modelPath {
+  self = [self init];
+  if (self) {
+    self.baseOptions.modelFile.filePath = modelPath;
+  }
+  return self;
+}
+
+@end
+
+@implementation TFLImageClassifier
+- (void)dealloc {
+  TfLiteImageClassifierDelete(_imageClassifier);
+}
+
+- (instancetype)initWithImageClassifier:
+    (TfLiteImageClassifier*)imageClassifier {
+  self = [super init];
+  if (self) {
+    _imageClassifier = imageClassifier;
+  }
+  return self;
+}
+
++ (nullable instancetype)imageClassifierWithOptions:
+                             (nonnull TFLImageClassifierOptions*)options
+                                              error:(NSError**)error {
+  TfLiteImageClassifierOptions cOptions = TfLiteImageClassifierOptionsCreate();
+  if (![options.classificationOptions
+          copyClassificationOptionsToCClassificationOptions:
+              &(cOptions.classification_options)
+                                                      error:error])
+    return nil;
+
+  [options.baseOptions copyBaseOptionsToCBaseOptions:&(cOptions.base_options)];
+
+  TfLiteSupportError* createClassifierError = nil;
+  TfLiteImageClassifier* imageClassifier =
+      TfLiteImageClassifierFromOptions(&cOptions, &createClassifierError);
+
+  [options.classificationOptions deleteCStringArraysOfClassificationOptions:
+                                     &(cOptions.classification_options)];
+
+  if (!imageClassifier) {
+    [TFLCommonUtils errorFromTfLiteSupportError:createClassifierError
+                                          error:error];
+    TfLiteSupportErrorDelete(createClassifierError);
+    return nil;
+  }
+
+  return [[TFLImageClassifier alloc] initWithImageClassifier:imageClassifier];
+}
+
+- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
+                                                    error:(NSError* _Nullable*)
+                                                              error {
+  return [self classifyWithGMLImage:image
+                   regionOfInterest:CGRectMake(0, 0, image.width, image.height)
+                              error:error];
+}
+
+- (nullable TFLClassificationResult*)classifyWithGMLImage:(GMLImage*)image
+                                         regionOfInterest:(CGRect)roi
+                                                    error:(NSError* _Nullable*)
+                                                              error {
+  TfLiteFrameBuffer* cFrameBuffer =
+      [GMLImageUtils cFrameBufferFromGMLImage:image error:error];
+
+  if (!cFrameBuffer) {
+    return nil;
+  }
+
+  TfLiteBoundingBox boundingBox = {.origin_x = roi.origin.x,
+                                   .origin_y = roi.origin.y,
+                                   .width = roi.size.width,
+                                   .height = roi.size.height};
+
+  TfLiteSupportError* classifyError = nil;
+  TfLiteClassificationResult* cClassificationResult =
+      TfLiteImageClassifierClassifyWithRoi(_imageClassifier, cFrameBuffer,
+                                           &boundingBox, &classifyError);
+
+  free(cFrameBuffer->buffer);
+  cFrameBuffer->buffer = nil;
+
+  free(cFrameBuffer);
+  cFrameBuffer = nil;
+
+  if (!cClassificationResult) {
+    [TFLCommonUtils errorFromTfLiteSupportError:classifyError error:error];
+    TfLiteSupportErrorDelete(classifyError);
+    return nil;
+  }
+
+  TFLClassificationResult* classificationHeadsResults = [TFLClassificationUtils
+      classificationResultFromCClassificationResults:cClassificationResult];
+  TfLiteClassificationResultDelete(cClassificationResult);
+
+  return classificationHeadsResults;
+}
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/BUILD
new file mode 100644
index 0000000..4b2ba81
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/BUILD
@@ -0,0 +1,22 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:__subpackages__"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+objc_library(
+    name = "GMLImageUtils",
+    srcs = [
+        "sources/GMLImageUtils.m",
+    ],
+    hdrs = [
+        "sources/GMLImageUtils.h",
+    ],
+    module_name = "GMLImageUtils",
+    sdk_frameworks = ["Accelerate"],
+    deps = [
+        "//tensorflow_lite_support/c/task/vision/core:frame_buffer",
+        "//tensorflow_lite_support/ios:TFLCommon",
+        "//tensorflow_lite_support/ios:TFLCommonUtils",
+        "//tensorflow_lite_support/odml/ios/image:MLImage",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h
new file mode 100644
index 0000000..298485b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h
@@ -0,0 +1,50 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <Foundation/Foundation.h>
+
+#include "tensorflow_lite_support/c/task/vision/core/frame_buffer.h"
+#import "third_party/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+/** Helper utility for performing operations on GMLImage specific to the
+ * TF Lite Task Vision library
+ */
+@interface GMLImageUtils : NSObject
+/**
+ * Creates and returns a TfLiteFrameBuffer from a GMLImage. TfLiteFrameBuffer
+ * is used by the TFLite Task Vision C library to hold the backing buffer of
+ * any image. Image inputs to the TFLite Task Vision C library is of type
+ * TfLiteFrameBuffer.
+ *
+ * @param gmlImage Image of type GMLImage which is to be converted into a
+ * TfLiteFrameBuffer.
+ * @param error Pointer to the memory location where errors if any should be
+ * saved. If `nil`, no error will be saved.
+ *
+ * @return The TfLiteFrameBuffer created from the gmlImage which can be used
+ * with the TF Lite Task Vision C library.
+ */
++ (nullable TfLiteFrameBuffer*)cFrameBufferFromGMLImage:(GMLImage*)gmlImage
+                                                  error:(NSError* _Nullable*)
+                                                            error;
+
+- (instancetype)init NS_UNAVAILABLE;
+
++ (instancetype)new NS_UNAVAILABLE;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m
new file mode 100644
index 0000000..72425b3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.m
@@ -0,0 +1,333 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import "tensorflow_lite_support/ios/task/vision/utils/sources/GMLImageUtils.h"
+#import "tensorflow_lite_support/ios/sources/TFLCommon.h"
+#import "tensorflow_lite_support/ios/sources/TFLCommonUtils.h"
+
+#include "tensorflow_lite_support/c/task/vision/core/frame_buffer.h"
+
+#import <Accelerate/Accelerate.h>
+#import <CoreGraphics/CoreGraphics.h>
+#import <CoreImage/CoreImage.h>
+#import <CoreVideo/CoreVideo.h>
+
+@interface TFLCVPixelBufferUtils : NSObject
++ (uint8_t* _Nullable)
+    convertBGRAtoRGBforPixelBufferBaseAddress:(CVPixelBufferRef)pixelBuffer
+                                        error:(NSError**)error;
+@end
+
+@interface UIImage (RawPixelDataUtils)
+- (TfLiteFrameBuffer*)frameBufferWithError:(NSError**)error;
+@end
+
+@implementation TFLCVPixelBufferUtils
+
++ (uint8_t*)convertBGRAtoRGBforPixelBufferBaseAddress:
+                (CVPixelBufferRef)pixelBuffer
+                                                error:(NSError**)error {
+  size_t width = CVPixelBufferGetWidth(pixelBuffer);
+  size_t height = CVPixelBufferGetHeight(pixelBuffer);
+  size_t stride = CVPixelBufferGetBytesPerRow(pixelBuffer);
+
+  int destinationChannelCount = 3;
+  size_t destinationBytesPerRow = destinationChannelCount * width;
+
+  uint8_t* pixelBufferBaseAddress =
+      (uint8_t*)CVPixelBufferGetBaseAddress(pixelBuffer);
+
+  uint8_t* destPixelBufferAddress =
+      [TFLCommonUtils mallocWithSize:height * destinationBytesPerRow
+                               error:error];
+
+  if (!destPixelBufferAddress) {
+    return NULL;
+  }
+
+  vImage_Buffer srcBuffer = {.data = pixelBufferBaseAddress,
+                             .height = height,
+                             .width = width,
+                             .rowBytes = stride};
+
+  vImage_Buffer destBuffer = {.data = destPixelBufferAddress,
+                              .height = height,
+                              .width = width,
+                              .rowBytes = destinationBytesPerRow};
+
+  vImage_Error convertError = kvImageNoError;
+  convertError =
+      vImageConvert_BGRA8888toRGB888(&srcBuffer, &destBuffer, kvImageNoFlags);
+
+  if (convertError != kvImageNoError) {
+    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeImageProcessingError
+                            description:@"Image format conversion failed."
+                                  error:error];
+
+    return NULL;
+  }
+
+  return destPixelBufferAddress;
+}
+
+@end
+
+@implementation UIImage (RawPixelDataUtils)
+
+- (TfLiteFrameBuffer*)frameBufferWithError:(NSError**)error {
+  TfLiteFrameBuffer* frameBuffer = NULL;
+
+  if (self.CGImage) {
+    frameBuffer = [self frameBufferFromCGImage:self.CGImage error:error];
+  } else if (self.CIImage) {
+    frameBuffer = [self frameBufferFromCIImage:self.CIImage error:error];
+  } else {
+    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+                            description:@"UIImage should be initialized from"
+                                         " CIImage or CGImage."
+                                  error:error];
+  }
+
+  return frameBuffer;
+}
+
++ (UInt8* _Nullable)pixelDataFromCGImage:(CGImageRef)cgImage
+                                   error:(NSError**)error {
+  long width = CGImageGetWidth(cgImage);
+  long height = CGImageGetHeight(cgImage);
+
+  int bitsPerComponent = 8;
+  UInt8* buffer_to_return = NULL;
+
+  CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
+  CGContextRef context =
+      CGBitmapContextCreate(nil, width, height, bitsPerComponent, 0, colorSpace,
+                            kCGImageAlphaNoneSkipLast);
+
+  if (context) {
+    CGContextDrawImage(context, CGRectMake(0, 0, width, height), cgImage);
+    buffer_to_return = [UIImage
+        populateRGBBufferFromSourceRGBABuffer:CGBitmapContextGetData(context)
+                                        width:width
+                                       height:height];
+    CGContextRelease(context);
+  }
+
+  if (buffer_to_return == NULL) {
+    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeImageProcessingError
+                            description:@"Image format conversion failed."
+                                  error:error];
+  }
+
+  CGColorSpaceRelease(colorSpace);
+
+  return buffer_to_return;
+}
+
++ (nullable UInt8*)populateRGBBufferFromSourceRGBABuffer:(UInt8*)buffer
+                                                   width:(size_t)width
+                                                  height:(size_t)height {
+  if (!buffer)
+    return nil;
+
+  int sourceChannelCount = 4;
+  int destChannelCount = 3;
+
+  UInt8* buffer_to_return = malloc(height * destChannelCount * width);
+  if (!buffer_to_return) {
+    return nil;
+  }
+  for (int row = 0; row < width; row++) {
+    for (int col = 0; col < height; col++) {
+      long offset = sourceChannelCount * (col * width + row);
+      long rgbOffset = destChannelCount * (col * width + row);
+      buffer_to_return[rgbOffset] = buffer[offset];
+      buffer_to_return[rgbOffset + 1] = buffer[offset + 1];
+      buffer_to_return[rgbOffset + 2] = buffer[offset + 2];
+    }
+  }
+  return buffer_to_return;
+}
+
+- (TfLiteFrameBuffer*)frameBufferFromCGImage:(CGImageRef)cgImage
+                                       error:(NSError**)error {
+  UInt8* buffer = [UIImage pixelDataFromCGImage:cgImage error:error];
+
+  if (buffer == NULL) {
+    return NULL;
+  }
+
+  TfLiteFrameBuffer* cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
+
+  cFrameBuffer->dimension.width = (int)CGImageGetWidth(cgImage);
+  cFrameBuffer->dimension.height = (int)CGImageGetHeight(cgImage);
+  cFrameBuffer->buffer = buffer;
+
+  enum TfLiteFrameBufferFormat cPixelFormat = kRGB;
+  cFrameBuffer->format = cPixelFormat;
+
+  return cFrameBuffer;
+}
+
+- (TfLiteFrameBuffer*)frameBufferFromCIImage:(CIImage*)ciImage
+                                       error:(NSError**)error {
+  uint8_t* buffer = nil;
+
+  int width = 0;
+  int height = 0;
+  if (ciImage.pixelBuffer) {
+    buffer = [TFLCVPixelBufferUtils
+        convertBGRAtoRGBforPixelBufferBaseAddress:ciImage.pixelBuffer
+                                            error:error];
+    width = (int)CVPixelBufferGetWidth(ciImage.pixelBuffer);
+    height = (int)CVPixelBufferGetHeight(ciImage.pixelBuffer);
+
+  } else if (ciImage.CGImage) {
+    buffer = [UIImage pixelDataFromCGImage:ciImage.CGImage error:error];
+    width = (int)CGImageGetWidth(ciImage.CGImage);
+    height = (int)CGImageGetWidth(ciImage.CGImage);
+  } else {
+    [TFLCommonUtils customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+                            description:@"CIImage should have CGImage or "
+                                         "CVPixelBuffer info."
+                                  error:error];
+  }
+
+  if (buffer == NULL) {
+    return NULL;
+  }
+
+  TfLiteFrameBuffer* cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
+  cFrameBuffer->buffer = buffer;
+  cFrameBuffer->dimension.width = width;
+  cFrameBuffer->dimension.height = height;
+
+  enum TfLiteFrameBufferFormat cPixelFormat = kRGBA;
+  cFrameBuffer->format = cPixelFormat;
+
+  return cFrameBuffer;
+}
+
+@end
+
+@implementation GMLImageUtils
+
++ (nullable TfLiteFrameBuffer*)cFrameBufferFromGMLImage:(GMLImage*)gmlImage
+                                                  error:(NSError* _Nullable*)
+                                                            error {
+  TfLiteFrameBuffer* cFrameBuffer = NULL;
+
+  switch (gmlImage.imageSourceType) {
+    case GMLImageSourceTypeSampleBuffer: {
+      CVPixelBufferRef sampleImagePixelBuffer =
+          CMSampleBufferGetImageBuffer(gmlImage.sampleBuffer);
+      cFrameBuffer =
+          [GMLImageUtils bufferFromCVPixelBuffer:sampleImagePixelBuffer
+                                           error:error];
+      break;
+    }
+    case GMLImageSourceTypePixelBuffer: {
+      cFrameBuffer = [GMLImageUtils bufferFromCVPixelBuffer:gmlImage.pixelBuffer
+                                                      error:error];
+      break;
+    }
+    case GMLImageSourceTypeImage: {
+      cFrameBuffer = [GMLImageUtils frameBufferFromUIImage:gmlImage.image
+                                                     error:error];
+    }
+
+    default:
+      [TFLCommonUtils
+          customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+                  description:@"Invalid source type for GMLImage."
+                        error:error];
+      break;
+  }
+
+  return cFrameBuffer;
+}
+
++ (TfLiteFrameBuffer*)frameBufferFromUIImage:(UIImage*)image
+                                       error:(NSError**)error {
+  return [image frameBufferWithError:error];
+}
+
++ (TfLiteFrameBuffer*)bufferFromCVPixelBuffer:(CVPixelBufferRef)pixelBuffer
+                                        error:(NSError**)error {
+  uint8_t* buffer = nil;
+  enum TfLiteFrameBufferFormat cPixelFormat = kRGB;
+
+  CVPixelBufferLockBaseAddress(pixelBuffer, 0);
+  OSType pixelBufferFormat = CVPixelBufferGetPixelFormatType(pixelBuffer);
+
+  switch (pixelBufferFormat) {
+    case kCVPixelFormatType_24RGB: {
+      cPixelFormat = kRGB;
+      buffer = [GMLImageUtils copyPixelufferDataForInference:pixelBuffer
+                                                       error:error];
+      break;
+    }
+    case kCVPixelFormatType_32RGBA: {
+      cPixelFormat = kRGBA;
+      buffer = [GMLImageUtils copyPixelufferDataForInference:pixelBuffer
+                                                       error:error];
+      break;
+    }
+    case kCVPixelFormatType_32BGRA: {
+      cPixelFormat = kRGB;
+      buffer = [TFLCVPixelBufferUtils
+          convertBGRAtoRGBforPixelBufferBaseAddress:pixelBuffer
+                                              error:error];
+      break;
+    }
+
+    default: {
+      [TFLCommonUtils
+          customErrorWithCode:TFLSupportErrorCodeInvalidArgumentError
+                  description:
+                      @"Unsupported pixel format for TfLiteFrameBufferFormat."
+                        error:error];
+      break;
+    }
+  }
+
+  CVPixelBufferUnlockBaseAddress(pixelBuffer, 0);
+
+  if (!buffer) {
+    return nil;
+  }
+
+  TfLiteFrameBuffer* cFrameBuffer = malloc(sizeof(TfLiteFrameBuffer));
+
+  cFrameBuffer->dimension.width = (int)CVPixelBufferGetWidth(pixelBuffer);
+  cFrameBuffer->dimension.height = (int)CVPixelBufferGetHeight(pixelBuffer);
+  cFrameBuffer->buffer = buffer;
+  cFrameBuffer->format = cPixelFormat;
+
+  return cFrameBuffer;
+}
+
++ (UInt8*)copyPixelufferDataForInference:(CVPixelBufferRef)pixelBuffer
+                                   error:(NSError**)error {
+  size_t height = CVPixelBufferGetHeight(pixelBuffer);
+  size_t stride = CVPixelBufferGetBytesPerRow(pixelBuffer);
+  UInt8* buffer = [TFLCommonUtils mallocWithSize:height * stride error:error];
+
+  if (buffer)
+    memcpy(buffer, CVPixelBufferGetBaseAddress(pixelBuffer), height * stride);
+
+  return buffer;
+}
+
+@end
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/BUILD
new file mode 100644
index 0000000..6ae128e1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/BUILD
@@ -0,0 +1,57 @@
+load("@build_bazel_rules_swift//swift:swift.bzl", "swift_library")
+load("@org_tensorflow//tensorflow/lite/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
+load("@build_bazel_rules_apple//apple:ios.bzl", "ios_unit_test")
+load("@org_tensorflow//tensorflow/lite:special_rules.bzl", "tflite_ios_lab_runner")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:__subpackages__"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+swift_library(
+    name = "TFLImageClassifierSwiftTestLibrary",
+    testonly = 1,
+    srcs = ["TFLImageClassifierTests.swift"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tags = TFL_DEFAULT_TAGS,
+    deps = [
+        "//tensorflow_lite_support/ios/task/vision:TFLImageClassifier",
+    ],
+)
+
+ios_unit_test(
+    name = "TFLImageClassifierSwiftTest",
+    minimum_os_version = TFL_MINIMUM_OS_VERSION,
+    runner = tflite_ios_lab_runner("IOS_LATEST"),
+    tags = TFL_DEFAULT_TAGS + TFL_DISABLED_SANITIZER_TAGS,
+    deps = [
+        ":TFLImageClassifierSwiftTestLibrary",
+    ],
+)
+
+objc_library(
+    name = "TFLImageClassifierObjcTestLibrary",
+    testonly = 1,
+    srcs = ["TFLImageClassifierTests.m"],
+    data = [
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_images",
+        "//tensorflow_lite_support/cc/test/testdata/task/vision:test_models",
+    ],
+    tags = TFL_DEFAULT_TAGS,
+    deps = [
+        "//tensorflow_lite_support/ios/task/vision:TFLImageClassifier",
+    ],
+)
+
+ios_unit_test(
+    name = "TFLImageClassifierObjcTest",
+    minimum_os_version = TFL_MINIMUM_OS_VERSION,
+    runner = tflite_ios_lab_runner("IOS_LATEST"),
+    tags = TFL_DEFAULT_TAGS + TFL_DISABLED_SANITIZER_TAGS,
+    deps = [
+        ":TFLImageClassifierObjcTestLibrary",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m
new file mode 100644
index 0000000..f269594
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.m
@@ -0,0 +1,160 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+#import <XCTest/XCTest.h>
+#import "tensorflow_lite_support/ios/task/vision/sources/TFLImageClassifier.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+@interface TFLImageClassifierTests : XCTestCase
+@property(nonatomic, nullable) NSString* modelPath;
+@end
+
+@implementation TFLImageClassifierTests
+
+- (GMLImage*)imageFromBundleWithName:(NSString*)name ofType:(NSString*)type {
+  NSString* imagePath =
+      [[NSBundle bundleForClass:[self class]] pathForResource:name ofType:type];
+  XCTAssertNotNil(imagePath);
+  UIImage* image = [[UIImage alloc] initWithContentsOfFile:imagePath];
+  XCTAssertNotNil(image);
+
+  GMLImage* gmlImage = [[GMLImage alloc] initWithImage:image];
+  XCTAssertNotNil(gmlImage);
+
+  return gmlImage;
+}
+- (void)setUp {
+  // Put setup code here. This method is called before the invocation of each
+  // test method in the class. static let bundle = Bundle(for:
+  // TFLSentencepieceTokenizerTest.self)
+  self.modelPath = [[NSBundle bundleForClass:[self class]]
+      pathForResource:@"mobilenet_v2_1.0_224"
+               ofType:@"tflite"];
+  XCTAssertNotNil(self.modelPath);
+}
+
+- (void)tearDown {
+  // Put teardown code here. This method is called after the invocation of each
+  // test method in the class.
+}
+
+- (void)testSuccessfullImageInferenceOnMLImageWithUIImage {
+  TFLImageClassifierOptions* imageClassifierOptions =
+      [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+
+  TFLImageClassifier* imageClassifier =
+      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
+                                               error:nil];
+  XCTAssertNotNil(imageClassifier);
+  GMLImage* gmlImage = [self imageFromBundleWithName:@"burger" ofType:@"jpg"];
+
+  TFLClassificationResult* classificationResults =
+      [imageClassifier classifyWithGMLImage:gmlImage error:nil];
+  XCTAssertTrue([classificationResults.classifications count] > 0);
+  XCTAssertTrue([classificationResults.classifications[0].categories count] >
+                0);
+
+  TFLCategory* category =
+      classificationResults.classifications[0].categories[0];
+  XCTAssertTrue([category.label isEqual:@"cheeseburger"]);
+  // TODO: match the score as image_classifier_test.cc
+  XCTAssertEqualWithAccuracy(category.score, 0.748976, 0.001);
+}
+
+- (void)testModelOptionsWithMaxResults {
+  TFLImageClassifierOptions* imageClassifierOptions =
+      [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+  int maxResults = 3;
+  imageClassifierOptions.classificationOptions.maxResults = maxResults;
+
+  TFLImageClassifier* imageClassifier =
+      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
+                                               error:nil];
+  XCTAssertNotNil(imageClassifier);
+
+  GMLImage* gmlImage = [self imageFromBundleWithName:@"burger" ofType:@"jpg"];
+
+  TFLClassificationResult* classificationResults =
+      [imageClassifier classifyWithGMLImage:gmlImage error:nil];
+  XCTAssertTrue([classificationResults.classifications count] > 0);
+  XCTAssertLessThanOrEqual(
+      [classificationResults.classifications[0].categories count], maxResults);
+
+  TFLCategory* category =
+      classificationResults.classifications[0].categories[0];
+  XCTAssertTrue([category.label isEqual:@"cheeseburger"]);
+  // TODO: match the score as image_classifier_test.cc
+  XCTAssertEqualWithAccuracy(category.score, 0.748976, 0.001);
+}
+
+- (void)testInferenceWithBoundingBox {
+  TFLImageClassifierOptions* imageClassifierOptions =
+      [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+  int maxResults = 3;
+  imageClassifierOptions.classificationOptions.maxResults = maxResults;
+
+  TFLImageClassifier* imageClassifier =
+      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
+                                               error:nil];
+  XCTAssertNotNil(imageClassifier);
+
+  GMLImage* gmlImage = [self imageFromBundleWithName:@"multi_objects"
+                                              ofType:@"jpg"];
+
+  CGRect roi = CGRectMake(406, 110, 148, 153);
+  TFLClassificationResult* classificationResults =
+      [imageClassifier classifyWithGMLImage:gmlImage
+                           regionOfInterest:roi
+                                      error:nil];
+  XCTAssertTrue([classificationResults.classifications count] > 0);
+  XCTAssertTrue([classificationResults.classifications[0].categories count] >
+                0);
+
+  TFLCategory* category =
+      classificationResults.classifications[0].categories[0];
+  // TODO: match the label and score as image_classifier_test.cc
+  // XCTAssertTrue([category.label isEqual:@"soccer ball"]);
+  // XCTAssertEqualWithAccuracy(category.score, 0.256512, 0.001);
+}
+
+- (void)testInferenceWithRGBAImage {
+  TFLImageClassifierOptions* imageClassifierOptions =
+      [[TFLImageClassifierOptions alloc] initWithModelPath:self.modelPath];
+
+  TFLImageClassifier* imageClassifier =
+      [TFLImageClassifier imageClassifierWithOptions:imageClassifierOptions
+                                               error:nil];
+  XCTAssertNotNil(imageClassifier);
+
+  GMLImage* gmlImage = [self imageFromBundleWithName:@"sparrow" ofType:@"png"];
+  XCTAssertNotNil(gmlImage);
+
+  TFLClassificationResult* classificationResults =
+      [imageClassifier classifyWithGMLImage:gmlImage error:nil];
+  XCTAssertTrue([classificationResults.classifications count] > 0);
+  XCTAssertTrue([classificationResults.classifications[0].categories count] >
+                0);
+
+  TFLCategory* category =
+      classificationResults.classifications[0].categories[0];
+  XCTAssertTrue([category.label isEqual:@"junco"]);
+  // TODO: inspect if score is correct. Better to test againest "burger",
+  // because we know the expected result for "burger.jpg".
+  XCTAssertEqualWithAccuracy(category.score, 0.253016, 0.001);
+}
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.swift b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.swift
new file mode 100644
index 0000000..0375168
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/test/task/vision/image_classifier/TFLImageClassifierTests.swift
@@ -0,0 +1,136 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+ ==============================================================================*/
+import XCTest
+
+@testable import TFLImageClassifier
+
+class TFLImageClassifierTests: XCTestCase {
+
+  static let bundle = Bundle(for: TFLImageClassifierTests.self)
+  static let modelPath = bundle.path(
+    forResource: "mobilenet_v2_1.0_224",
+    ofType: "tflite")!
+
+  func testSuccessfullInferenceOnMLImageWithUIImage() throws {
+
+    let modelPath = try XCTUnwrap(TFLImageClassifierTests.modelPath)
+
+    let imageClassifierOptions = TFLImageClassifierOptions(modelPath: modelPath)
+    XCTAssertNotNil(imageClassifierOptions)
+
+    let imageClassifier =
+      try TFLImageClassifier.imageClassifier(options: imageClassifierOptions!)
+
+    let gmlImage = try gmlImage(withName: "burger", ofType: "jpg")
+    let classificationResults: TFLClassificationResult =
+      try imageClassifier.classify(gmlImage: gmlImage)
+
+    XCTAssertNotNil(classificationResults)
+    XCTAssertEqual(classificationResults.classifications.count, 1)
+    XCTAssertGreaterThan(classificationResults.classifications[0].categories.count, 0)
+    // TODO: match the score as image_classifier_test.cc
+    let category = classificationResults.classifications[0].categories[0]
+    XCTAssertEqual(category.label, "cheeseburger")
+    XCTAssertEqual(category.score, 0.748976, accuracy: 0.001)
+  }
+
+  func testModelOptionsWithMaxResults() throws {
+
+    let modelPath = try XCTUnwrap(TFLImageClassifierTests.modelPath)
+
+    let imageClassifierOptions = TFLImageClassifierOptions(modelPath: modelPath)
+    XCTAssertNotNil(imageClassifierOptions)
+
+    let maxResults = 3
+    imageClassifierOptions!.classificationOptions.maxResults = maxResults
+
+    let imageClassifier =
+      try TFLImageClassifier.imageClassifier(options: imageClassifierOptions!)
+
+    let gmlImage = try gmlImage(withName: "burger", ofType: "jpg")
+
+    let classificationResults: TFLClassificationResult = try imageClassifier.classify(
+      gmlImage: gmlImage)
+
+    XCTAssertNotNil(classificationResults)
+    XCTAssertEqual(classificationResults.classifications.count, 1)
+    XCTAssertLessThanOrEqual(classificationResults.classifications[0].categories.count, maxResults)
+
+    // TODO: match the score as image_classifier_test.cc
+    let category = classificationResults.classifications[0].categories[0]
+    XCTAssertEqual(category.label, "cheeseburger")
+    XCTAssertEqual(category.score, 0.748976, accuracy: 0.001)
+  }
+
+  func testInferenceWithBoundingBox() throws {
+
+    let modelPath = try XCTUnwrap(TFLImageClassifierTests.modelPath)
+
+    let imageClassifierOptions = TFLImageClassifierOptions(modelPath: modelPath)
+    XCTAssertNotNil(imageClassifierOptions)
+
+    let imageClassifier =
+      try TFLImageClassifier.imageClassifier(options: imageClassifierOptions!)
+
+    let gmlImage = try gmlImage(withName: "multi_objects", ofType: "jpg")
+
+    let roi = CGRect(x: 406, y: 110, width: 148, height: 153)
+    let classificationResults =
+      try imageClassifier.classify(gmlImage: gmlImage, regionOfInterest: roi)
+
+    XCTAssertNotNil(classificationResults)
+    XCTAssertEqual(classificationResults.classifications.count, 1)
+    XCTAssertGreaterThan(classificationResults.classifications[0].categories.count, 0)
+
+    // TODO: match the label and score as image_classifier_test.cc
+    // let category = classificationResults.classifications[0].categories[0]
+    // XCTAssertEqual(category.label, "soccer ball")
+    // XCTAssertEqual(category.score, 0.256512, accuracy:0.001);
+  }
+
+  func testInferenceWithRGBAImage() throws {
+
+    let modelPath = try XCTUnwrap(TFLImageClassifierTests.modelPath)
+
+    let imageClassifierOptions = TFLImageClassifierOptions(modelPath: modelPath)
+    XCTAssertNotNil(imageClassifierOptions)
+
+    let imageClassifier =
+      try TFLImageClassifier.imageClassifier(options: imageClassifierOptions!)
+
+    let gmlImage = try gmlImage(withName: "sparrow", ofType: "png")
+
+    let classificationResults =
+      try imageClassifier.classify(gmlImage: gmlImage)
+
+    XCTAssertNotNil(classificationResults)
+    XCTAssertEqual(classificationResults.classifications.count, 1)
+    XCTAssertGreaterThan(classificationResults.classifications[0].categories.count, 0)
+
+    let category = classificationResults.classifications[0].categories[0]
+    XCTAssertEqual(category.label, "junco")
+    XCTAssertEqual(category.score, 0.253016, accuracy: 0.001)
+  }
+
+  private func gmlImage(withName name: String, ofType type: String) throws -> MLImage {
+    let imagePath =
+      try XCTUnwrap(TFLImageClassifierTests.bundle.path(forResource: name, ofType: type))
+    let image = UIImage(contentsOfFile: imagePath)
+    let imageForInference = try XCTUnwrap(image)
+    let gmlImage = try XCTUnwrap(MLImage(image: imageForInference))
+
+    return gmlImage
+  }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/BUILD
index 34ba9c6..b894465 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/BUILD
@@ -1,5 +1,5 @@
 load("@build_bazel_rules_swift//swift:swift.bzl", "swift_library")
-load("@org_tensorflow//tensorflow/lite/experimental/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
+load("@org_tensorflow//tensorflow/lite/ios:ios.bzl", "TFL_DEFAULT_TAGS", "TFL_DISABLED_SANITIZER_TAGS", "TFL_MINIMUM_OS_VERSION")
 load("@build_bazel_rules_apple//apple:ios.bzl", "ios_unit_test")
 load("@org_tensorflow//tensorflow/lite:special_rules.bzl", "tflite_ios_lab_runner")
 
@@ -50,7 +50,6 @@
     tags = TFL_DEFAULT_TAGS,
     deps = [
         ":TFLBertTokenizer",
-        "//third_party/swift/xctest",
     ],
 )
 
@@ -91,7 +90,6 @@
     tags = TFL_DEFAULT_TAGS,
     deps = [
         ":TFLSentencepieceTokenizer",
-        "//third_party/swift/xctest",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Tests/TFLBertTokenizerTest.swift b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Tests/TFLBertTokenizerTest.swift
index e805f30..b69af12e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Tests/TFLBertTokenizerTest.swift
+++ b/third_party/tflite_support/src/tensorflow_lite_support/ios/text/tokenizers/Tests/TFLBertTokenizerTest.swift
@@ -18,7 +18,7 @@
 
 class TFLBertTokenizerTest: XCTestCase {
   static let bundle = Bundle(for: TFLBertTokenizerTest.self)
-  static let mobileBertVocabPath = bundle.path(forResource: "vocab", ofType: "txt")!
+  static let mobileBertVocabPath = bundle.path(forResource: "mobilebert_vocab", ofType: "txt")!
 
   func testInitBertTokenizerFromPath() {
     let bertTokenizer = TFLBertTokenizer(vocabPath: TFLBertTokenizerTest.mobileBertVocabPath)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm b/third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
deleted file mode 100644
index 6fb0a7f..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.mm
+++ /dev/null
@@ -1,27 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-#inmport "base/strings/sys_string_conversions.h"
-#import "third_party/tensorflow_lite_support/ios/utils/Sources/TFLStringUtil.h"
-
-std::string MakeString(NSString* str) {
-  return SysNSStringToUTF8(str);
-}
-
-NSString* MakeNSString(const std::string& str) {
-  return [[NSString alloc]
-      initWithBytes:const_cast<void*>(static_cast<const void*>(str.data()))
-             length:str.length()
-           encoding:NSUTF8StringEncoding];
-}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/BUILD
index 8dfbf8f..4076307c 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/BUILD
@@ -1,7 +1,6 @@
 # Description:
 # TensorFlow Lite Support API in Java.
 
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
 
 package(
@@ -15,36 +14,44 @@
     "debug_version_script.lds",
 ])
 
+filegroup(
+    name = "java_srcs",
+    srcs = glob(["src/java/org/tensorflow/lite/support/**/*.java"]),
+)
+
+# Android Library target for TFLite Support Library. It depends on TensorFlow
+# Lite runtime (tensorflow/lite/java:tensorflowlite). If you don't want to
+# introduce the native library into dependencies, use
+# "tensorflowlite_support_java" instead, which depends on
+# tensorflow/lite/java:tensorflowlite_java_stable.
 android_library(
     name = "tensorflowlite_support",
-    srcs = glob(
-        ["src/java/org/tensorflow/lite/support/**/*.java"],
-    ),
-    javacopts = JAVACOPTS,
+    srcs = [],
+    javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
+    exports = [
+        ":tensorflowlite_support_java",
+    ],
     deps = [
-        "@org_checkerframework_qual",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite",
+        ":tensorflowlite_support_java",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
     ],
 )
 
 android_library(
     name = "tensorflowlite_support_java",
-    srcs = glob(
-        ["src/java/org/tensorflow/lite/support/**/*.java"],
-    ),
-    javacopts = JAVACOPTS,
+    srcs = [":java_srcs"],
+    javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
+    # LINT.IfChange(dep)
     deps = [
+        "@com_google_auto_value",
+        "@maven//:androidx_annotation_annotation",
+        "@maven//:com_google_android_odml_image",
         "@org_checkerframework_qual",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",  # TODO(b/198734357): Use api when TF dep catches up.
     ],
-)
-
-# TODO(b/156482505): Remove this target.
-alias(
-    name = "tensorflow-lite-support-nogpu",
-    actual = ":tensorflow-lite-support",
+    # LINT.ThenChange(<INTERNAL>/release/build_support_api_pom.sh:dep)
 )
 
 # This alias matches the associated .aar library name output style.
@@ -52,22 +59,3 @@
     name = "tensorflow-lite-support",
     actual = ":tensorflowlite_support",
 )
-
-java_library(
-    name = "tensorflowlite_support_precondition_lib",
-    srcs = ["src/java/org/tensorflow/lite/support/common/SupportPreconditions.java"],
-    javacopts = JAVACOPTS,
-    deps = [
-        "@org_checkerframework_qual",
-    ],
-)
-
-android_library(
-    name = "tensorflowlite_support_precondition",
-    srcs = ["src/java/org/tensorflow/lite/support/common/SupportPreconditions.java"],
-    javacopts = JAVACOPTS,
-    manifest = "AndroidManifest.xml",
-    deps = [
-        "@org_checkerframework_qual",
-    ],
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/README.md b/third_party/tflite_support/src/tensorflow_lite_support/java/README.md
index 8d37bf8..0d604d33 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/README.md
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/README.md
@@ -5,7 +5,7 @@
 tensorflow.org](https://www.tensorflow.org/lite/inference_with_metadata/overview)
 for more information about all the efforts under TensorFlow Lite Support.
 
-This directory contains the Java code for the TensorFlow Lite SupportLibrary
+This directory contains the Java code for the TensorFlow Lite Support Library
 and TensorFlow Lite Task Library.
 
 ## TensorFlow Lite Android Support Library
@@ -28,6 +28,7 @@
 
 
 ## TensorFlow Lite Android Task Library
+
 TensorFlow Lite Task Library provides optimized ready-to-use model interfaces
 for popular machine learning tasks, such as image classification, question and
 answer, etc. The model interfaces are specifically designed for each task to
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/default_version_script.lds b/third_party/tflite_support/src/tensorflow_lite_support/java/default_version_script.lds
index 46bbffe..d7701cf2 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/default_version_script.lds
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/default_version_script.lds
@@ -1,6 +1,8 @@
 VERS_1.0 {
   # Export JNI and native C symbols.
   global:
+    # Required for libunwind. This is needed if built and then run internally.
+    google_find_phdr;
     Java_*;
     JNI_OnLoad;
     JNI_OnUnload;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java
new file mode 100644
index 0000000..e066146
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/audio/TensorAudio.java
@@ -0,0 +1,346 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.audio;
+
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+
+import static java.lang.System.arraycopy;
+
+import android.media.AudioFormat;
+import android.media.AudioRecord;
+import android.os.Build;
+
+import androidx.annotation.RequiresApi;
+
+import com.google.auto.value.AutoValue;
+
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.nio.ByteBuffer;
+import java.nio.ByteOrder;
+import java.nio.FloatBuffer;
+
+/**
+ * Defines a ring buffer and some utility functions to prepare the input audio samples.
+ *
+ * <p>It maintains a <a href="https://en.wikipedia.org/wiki/Circular_buffer">Ring Buffer</a> to hold
+ * input audio data. Clients could feed input audio data via `load` methods and access the
+ * aggregated audio samples via `getTensorBuffer` method.
+ *
+ * <p>Note that this class can only handle input audio in Float (in {@link
+ * android.media.AudioFormat#ENCODING_PCM_16BIT}) or Short (in {@link
+ * android.media.AudioFormat#ENCODING_PCM_FLOAT}). Internally it converts and stores all the audio
+ * samples in PCM Float encoding.
+ *
+ * <p>Typical usage in Kotlin
+ *
+ * <pre>
+ *   val tensor = TensorAudio.create(format, modelInputLength)
+ *   tensor.load(newData)
+ *   interpreter.run(tensor.getTensorBuffer(), outputBuffer);
+ * </pre>
+ *
+ * <p>Another sample usage with {@link android.media.AudioRecord}
+ *
+ * <pre>
+ *   val tensor = TensorAudio.create(format, modelInputLength)
+ *   Timer().scheduleAtFixedRate(delay, period) {
+ *     tensor.load(audioRecord)
+ *     interpreter.run(tensor.getTensorBuffer(), outputBuffer)
+ *   }
+ * </pre>
+ */
+public class TensorAudio {
+    private static final String TAG = TensorAudio.class.getSimpleName();
+    private final FloatRingBuffer buffer;
+    private final TensorAudioFormat format;
+
+    /**
+     * Creates a {@link android.media.AudioRecord} instance with a ring buffer whose size is {@code
+     * sampleCounts} * {@code format.getChannels()}.
+     *
+     * @param format the expected {@link TensorAudioFormat} of audio data loaded into this class.
+     * @param sampleCounts the number of samples to be fed into the model
+     */
+    public static TensorAudio create(TensorAudioFormat format, int sampleCounts) {
+        return new TensorAudio(format, sampleCounts);
+    }
+
+    /**
+     * Creates a {@link TensorAudio} instance with a ring buffer whose size is {@code sampleCounts}
+     * *
+     * {@code format.getChannelCount()}.
+     *
+     * @param format the {@link android.media.AudioFormat} required by the TFLite model. It defines
+     *     the number of channels and sample rate.
+     * @param sampleCounts the number of samples to be fed into the model
+     */
+    public static TensorAudio create(AudioFormat format, int sampleCounts) {
+        return new TensorAudio(TensorAudioFormat.create(format), sampleCounts);
+    }
+
+    /**
+     * Wraps a few constants describing the format of the incoming audio samples, namely number of
+     * channels and the sample rate. By default, channels is set to 1.
+     */
+    @AutoValue
+    public abstract static class TensorAudioFormat {
+        private static final int DEFAULT_CHANNELS = 1;
+
+        /** Creates a {@link TensorAudioFormat} instance from Android AudioFormat class. */
+        @RequiresApi(Build.VERSION_CODES.M)
+        public static TensorAudioFormat create(AudioFormat format) {
+            return TensorAudioFormat.builder()
+                    .setChannels(format.getChannelCount())
+                    .setSampleRate(format.getSampleRate())
+                    .build();
+        }
+
+        public abstract int getChannels();
+
+        public abstract int getSampleRate();
+
+        public static Builder builder() {
+            return new AutoValue_TensorAudio_TensorAudioFormat.Builder().setChannels(
+                    DEFAULT_CHANNELS);
+        }
+
+        /** Builder for {@link TensorAudioFormat} */
+        @AutoValue.Builder
+        public abstract static class Builder {
+            /* By default, it's set to have 1 channel. */
+            public abstract Builder setChannels(int value);
+
+            public abstract Builder setSampleRate(int value);
+
+            abstract TensorAudioFormat autoBuild();
+
+            public TensorAudioFormat build() {
+                TensorAudioFormat format = autoBuild();
+                checkArgument(
+                        format.getChannels() > 0, "Number of channels should be greater than 0");
+                checkArgument(format.getSampleRate() > 0, "Sample rate should be greater than 0");
+                return format;
+            }
+        }
+    }
+
+    /**
+     * Stores the input audio samples {@code src} in the ring buffer.
+     *
+     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_FLOAT}. For
+     *     multi-channel input, the array is interleaved.
+     */
+    public void load(float[] src) {
+        load(src, 0, src.length);
+    }
+
+    /**
+     * Stores the input audio samples {@code src} in the ring buffer.
+     *
+     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_FLOAT}. For
+     *     multi-channel input, the array is interleaved.
+     * @param offsetInFloat starting position in the {@code src} array
+     * @param sizeInFloat the number of float values to be copied
+     * @throws IllegalArgumentException for incompatible audio format or incorrect input size
+     */
+    public void load(float[] src, int offsetInFloat, int sizeInFloat) {
+        checkArgument(sizeInFloat % format.getChannels() == 0,
+                String.format("Size (%d) needs to be a multiplier of the number of channels (%d)",
+                        sizeInFloat, format.getChannels()));
+        buffer.load(src, offsetInFloat, sizeInFloat);
+    }
+
+    /**
+     * Converts the input audio samples {@code src} to ENCODING_PCM_FLOAT, then stores it in the
+     * ring buffer.
+     *
+     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_16BIT}. For
+     *     multi-channel input, the array is interleaved.
+     */
+    public void load(short[] src) {
+        load(src, 0, src.length);
+    }
+
+    /**
+     * Converts the input audio samples {@code src} to ENCODING_PCM_FLOAT, then stores it in the
+     * ring buffer.
+     *
+     * @param src input audio samples in {@link android.media.AudioFormat#ENCODING_PCM_16BIT}. For
+     *     multi-channel input, the array is interleaved.
+     * @param offsetInShort starting position in the src array
+     * @param sizeInShort the number of short values to be copied
+     * @throws IllegalArgumentException if the source array can't be copied
+     */
+    public void load(short[] src, int offsetInShort, int sizeInShort) {
+        checkArgument(offsetInShort + sizeInShort <= src.length,
+                String.format(
+                        "Index out of range. offset (%d) + size (%d) should <= newData.length (%d)",
+                        offsetInShort, sizeInShort, src.length));
+        float[] floatData = new float[sizeInShort];
+        for (int i = offsetInShort; i < sizeInShort; i++) {
+            // Convert the data to PCM Float encoding i.e. values between -1 and 1
+            floatData[i] = src[i] / Short.MAX_VALUE;
+        }
+        load(floatData);
+    }
+
+    /**
+     * Loads latest data from the {@link android.media.AudioRecord} in a non-blocking way. Only
+     * supporting ENCODING_PCM_16BIT and ENCODING_PCM_FLOAT.
+     *
+     * @param record an instance of {@link android.media.AudioRecord}
+     * @return number of captured audio values whose size is {@code channelCount * sampleCount}. If
+     *     there was no new data in the AudioRecord or an error occurred, this method will return 0.
+     * @throws IllegalArgumentException for unsupported audio encoding format
+     * @throws IllegalStateException if reading from AudioRecord failed
+     */
+    @RequiresApi(Build.VERSION_CODES.M)
+    public int load(AudioRecord record) {
+        checkArgument(this.format.equals(TensorAudioFormat.create(record.getFormat())),
+                "Incompatible audio format.");
+        int loadedValues = 0;
+        if (record.getAudioFormat() == AudioFormat.ENCODING_PCM_FLOAT) {
+            float[] newData = new float[record.getChannelCount() * record.getBufferSizeInFrames()];
+            loadedValues = record.read(newData, 0, newData.length, AudioRecord.READ_NON_BLOCKING);
+            if (loadedValues > 0) {
+                load(newData, 0, loadedValues);
+                return loadedValues;
+            }
+        } else if (record.getAudioFormat() == AudioFormat.ENCODING_PCM_16BIT) {
+            short[] newData = new short[record.getChannelCount() * record.getBufferSizeInFrames()];
+            loadedValues = record.read(newData, 0, newData.length, AudioRecord.READ_NON_BLOCKING);
+            if (loadedValues > 0) {
+                load(newData, 0, loadedValues);
+                return loadedValues;
+            }
+        } else {
+            throw new IllegalArgumentException(
+                    "Unsupported encoding. Requires ENCODING_PCM_16BIT or ENCODING_PCM_FLOAT.");
+        }
+
+        switch (loadedValues) {
+            case AudioRecord.ERROR_INVALID_OPERATION:
+                throw new IllegalStateException("AudioRecord.ERROR_INVALID_OPERATION");
+
+            case AudioRecord.ERROR_BAD_VALUE:
+                throw new IllegalStateException("AudioRecord.ERROR_BAD_VALUE");
+
+            case AudioRecord.ERROR_DEAD_OBJECT:
+                throw new IllegalStateException("AudioRecord.ERROR_DEAD_OBJECT");
+
+            case AudioRecord.ERROR:
+                throw new IllegalStateException("AudioRecord.ERROR");
+
+            default:
+                return 0;
+        }
+    }
+
+    /**
+     * Returns a float {@link TensorBuffer} holding all the available audio samples in {@link
+     * android.media.AudioFormat#ENCODING_PCM_FLOAT} i.e. values are in the range of [-1, 1].
+     */
+    public TensorBuffer getTensorBuffer() {
+        ByteBuffer byteBuffer = buffer.getBuffer();
+        TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(
+                new int[] {/* batch= */ 1,
+                        /* modelInputLengthInFloat= */ byteBuffer.asFloatBuffer().limit()},
+                DataType.FLOAT32);
+        tensorBuffer.loadBuffer(byteBuffer);
+        return tensorBuffer;
+    }
+
+    /* Returns the {@link TensorAudioFormat} associated with the tensor. */
+    public TensorAudioFormat getFormat() {
+        return format;
+    }
+
+    private TensorAudio(TensorAudioFormat format, int sampleCounts) {
+        this.format = format;
+        this.buffer = new FloatRingBuffer(sampleCounts * format.getChannels());
+    }
+
+    /** Actual implementation of the ring buffer. */
+    private static class FloatRingBuffer {
+        private final float[] buffer;
+        private int nextIndex = 0;
+
+        public FloatRingBuffer(int flatSize) {
+            buffer = new float[flatSize];
+        }
+
+        /**
+         * Loads the entire float array to the ring buffer. If the float array is longer than ring
+         * buffer's capacity, samples with lower indices in the array will be ignored.
+         */
+        public void load(float[] newData) {
+            load(newData, 0, newData.length);
+        }
+
+        /**
+         * Loads a slice of the float array to the ring buffer. If the float array is longer than
+         * ring buffer's capacity, samples with lower indices in the array will be ignored.
+         */
+        public void load(float[] newData, int offset, int size) {
+            checkArgument(offset + size <= newData.length,
+                    String.format(
+                            "Index out of range. offset (%d) + size (%d) should <= newData.length (%d)",
+                            offset, size, newData.length));
+            // If buffer can't hold all the data, only keep the most recent data of size
+            // buffer.length
+            if (size > buffer.length) {
+                offset = size - buffer.length;
+                size = buffer.length;
+            }
+            if (nextIndex + size < buffer.length) {
+                // No need to wrap nextIndex, just copy newData[offset:offset + size]
+                // to buffer[nextIndex:nextIndex+size]
+                arraycopy(newData, offset, buffer, nextIndex, size);
+            } else {
+                // Need to wrap nextIndex, perform copy in two chunks.
+                int firstChunkSize = buffer.length - nextIndex;
+                // First copy newData[offset:offset+firstChunkSize] to
+                // buffer[nextIndex:buffer.length]
+                arraycopy(newData, offset, buffer, nextIndex, firstChunkSize);
+                // Then copy newData[offset+firstChunkSize:offset+size] to
+                // buffer[0:size-firstChunkSize]
+                arraycopy(newData, offset + firstChunkSize, buffer, 0, size - firstChunkSize);
+            }
+
+            nextIndex = (nextIndex + size) % buffer.length;
+        }
+
+        public ByteBuffer getBuffer() {
+            // Create non-direct buffers. On Pixel 4, creating direct buffer costs around 0.1 ms,
+            // which can be 5x ~ 10x longer compared to non-direct buffer backed by arrays (around
+            // 0.01ms), so generally we don't create direct buffer for every invocation.
+            ByteBuffer byteBuffer =
+                    ByteBuffer.allocate(DataType.FLOAT32.byteSize() * buffer.length);
+            byteBuffer.order(ByteOrder.nativeOrder());
+            FloatBuffer result = byteBuffer.asFloatBuffer();
+            result.put(buffer, nextIndex, buffer.length - nextIndex);
+            result.put(buffer, 0, nextIndex);
+            byteBuffer.rewind();
+            return byteBuffer;
+        }
+
+        public int getCapacity() {
+            return buffer.length;
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java
index 6e44108..6090f85 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/FileUtil.java
@@ -19,6 +19,7 @@
 import android.content.res.AssetFileDescriptor;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 
 import java.io.BufferedReader;
 import java.io.FileInputStream;
@@ -132,8 +133,10 @@
 
     /**
      * Loads vocabulary from an input stream of an opened vocabulary file (which is a single-column
-     * text file). See details for vocabulary files in {@link FileUtil#loadVocabularyFile(Context,
-     * String)}.
+     * text file).
+     *
+     * <p>A vocabulary file is a single-column plain text file whose contents are split into lines,
+     * and each line is an individual value. The file should be in assets of the context.
      *
      * @param inputStream the input stream of an opened vocabulary file.
      * @return a list of vocabulary words.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java
index 3f3d58a..a94adb89 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/Processor.java
@@ -15,9 +15,7 @@
 
 package org.tensorflow.lite.support.common;
 
-/**
- * Processes T object with prepared {@link Operator<T>}.
- */
+/** Processes T object with prepared {@code Operator<T>}. */
 public interface Processor<T> {
     T process(T input);
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java
index b374ff5..aa900b7 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SequentialProcessor.java
@@ -16,6 +16,7 @@
 package org.tensorflow.lite.support.common;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 
 import java.util.ArrayList;
 import java.util.Collections;
@@ -24,7 +25,7 @@
 import java.util.Map;
 
 /**
- * A processor base class that chains a serial of {@link Operator<T>} and executes them.
+ * A processor base class that chains a serial of {@code Operator<T>} and executes them.
  *
  * <p>Typically, users could use its subclasses, e.g. {@link
  * org.tensorflow.lite.support.image.ImageProcessor} rather than directly use this one.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SupportPreconditions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SupportPreconditions.java
deleted file mode 100644
index 7f47848..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/SupportPreconditions.java
+++ /dev/null
@@ -1,188 +0,0 @@
-/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-package org.tensorflow.lite.support.common;
-
-import org.checkerframework.checker.nullness.qual.Nullable;
-
-/** Static error checking util methods. */
-public final class SupportPreconditions {
-    /**
-     * Ensures that an object reference passed as a parameter to the calling method is not null.
-     *
-     * @param reference an object reference
-     * @return the non-null reference that was validated
-     * @throws NullPointerException if {@code reference} is null
-     */
-    public static <T extends Object> T checkNotNull(T reference) {
-        if (reference == null) {
-            throw new NullPointerException("The object reference is null.");
-        }
-        return reference;
-    }
-
-    /**
-     * Ensures that an object reference passed as a parameter to the calling method is not null.
-     *
-     * @param reference an object reference
-     * @param errorMessage the exception message to use if the check fails; will be converted to a
-     *     string using {@link String#valueOf(Object)}
-     * @return the non-null reference that was validated
-     * @throws NullPointerException if {@code reference} is null
-     */
-    public static <T extends Object> T checkNotNull(T reference, @Nullable Object errorMessage) {
-        if (reference == null) {
-            throw new NullPointerException(String.valueOf(errorMessage));
-        }
-        return reference;
-    }
-
-    /**
-     * Ensures that the given String is not empty and not null.
-     *
-     * @param string the String to test
-     * @return the non-null non-empty String that was validated
-     * @throws IllegalArgumentException if {@code string} is null or empty
-     */
-    public static String checkNotEmpty(String string) {
-        if (string == null || string.length() == 0) {
-            throw new IllegalArgumentException("Given String is empty or null.");
-        }
-        return string;
-    }
-
-    /**
-     * Ensures that the given String is not empty and not null.
-     *
-     * @param string the String to test
-     * @param errorMessage the exception message to use if the check fails; will be converted to a
-     *     string using {@link String#valueOf(Object)}
-     * @return the non-null non-empty String that was validated
-     * @throws IllegalArgumentException if {@code string} is null or empty
-     */
-    public static String checkNotEmpty(String string, Object errorMessage) {
-        if (string == null || string.length() == 0) {
-            throw new IllegalArgumentException(String.valueOf(errorMessage));
-        }
-        return string;
-    }
-
-    /**
-     * Ensures the truth of an expression involving one or more parameters to the calling method.
-     *
-     * @param expression a boolean expression.
-     * @throws IllegalArgumentException if {@code expression} is false.
-     */
-    public static void checkArgument(boolean expression) {
-        if (!expression) {
-            throw new IllegalArgumentException();
-        }
-    }
-
-    /**
-     * Ensures the truth of an expression involving one or more parameters to the calling method.
-     *
-     * @param expression a boolean expression.
-     * @param errorMessage the exception message to use if the check fails; will be converted to a
-     *     string using {@link String#valueOf(Object)}.
-     * @throws IllegalArgumentException if {@code expression} is false.
-     */
-    public static void checkArgument(boolean expression, @Nullable Object errorMessage) {
-        if (!expression) {
-            throw new IllegalArgumentException(String.valueOf(errorMessage));
-        }
-    }
-
-    /**
-     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
-     * size
-     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
-     *
-     * @param index a user-supplied index identifying an element of an array, list or string
-     * @param size the size of that array, list or string
-     * @return the value of {@code index}
-     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
-     *         size}
-     * @throws IllegalArgumentException if {@code size} is negative
-     */
-    public static int checkElementIndex(int index, int size) {
-        return checkElementIndex(index, size, "index");
-    }
-
-    /**
-     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
-     * size
-     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
-     *
-     * @param index a user-supplied index identifying an element of an array, list or string
-     * @param size the size of that array, list or string
-     * @param desc the text to use to describe this index in an error message
-     * @return the value of {@code index}
-     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
-     *         size}
-     * @throws IllegalArgumentException if {@code size} is negative
-     */
-    public static int checkElementIndex(int index, int size, @Nullable String desc) {
-        // Carefully optimized for execution by hotspot (explanatory comment above)
-        if (index < 0 || index >= size) {
-            throw new IndexOutOfBoundsException(badElementIndex(index, size, desc));
-        }
-        return index;
-    }
-
-    /**
-     * Ensures the truth of an expression involving the state of the calling instance, but not
-     * involving any parameters to the calling method.
-     *
-     * @param expression a boolean expression
-     * @throws IllegalStateException if {@code expression} is false
-     * @see Verify#verify Verify.verify()
-     */
-    public static void checkState(boolean expression) {
-        if (!expression) {
-            throw new IllegalStateException();
-        }
-    }
-
-    /**
-     * Ensures the truth of an expression involving the state of the calling instance, but not
-     * involving any parameters to the calling method.
-     *
-     * @param expression a boolean expression
-     * @param errorMessage the exception message to use if the check fails; will be converted to a
-     *     string using {@link String#valueOf(Object)}
-     * @throws IllegalStateException if {@code expression} is false
-     * @see Verify#verify Verify.verify()
-     */
-    public static void checkState(boolean expression, @Nullable Object errorMessage) {
-        if (!expression) {
-            throw new IllegalStateException(String.valueOf(errorMessage));
-        }
-    }
-
-    private static String badElementIndex(int index, int size, @Nullable String desc) {
-        if (index < 0) {
-            return String.format("%s (%s) must not be negative", desc, index);
-        } else if (size < 0) {
-            throw new IllegalArgumentException("negative size: " + size);
-        } else { // index >= size
-            return String.format("%s (%s) must be less than size (%s)", desc, index, size);
-        }
-    }
-
-    private SupportPreconditions() {
-        throw new AssertionError("SupportPreconditions is Uninstantiable.");
-    }
-}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java
index cb22f57..4391c45 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/TensorProcessor.java
@@ -29,7 +29,7 @@
  * </pre>
  *
  * @see TensorProcessor.Builder to build a {@link TensorProcessor} instance.
- * @see TensorProcessor#process(TensorBuffer) to apply the processor on a {@link TensorBuffer}.
+ * @see TensorProcessor#process to apply the processor on a {@link TensorBuffer}.
  */
 public class TensorProcessor extends SequentialProcessor<TensorBuffer> {
     private TensorProcessor(Builder builder) {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java
new file mode 100644
index 0000000..29faa545
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/SupportPreconditions.java
@@ -0,0 +1,186 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common.internal;
+
+import org.checkerframework.checker.nullness.qual.Nullable;
+
+/** Static error checking util methods. */
+public final class SupportPreconditions {
+    /**
+     * Ensures that an object reference passed as a parameter to the calling method is not null.
+     *
+     * @param reference an object reference
+     * @return the non-null reference that was validated
+     * @throws NullPointerException if {@code reference} is null
+     */
+    public static <T extends Object> T checkNotNull(T reference) {
+        if (reference == null) {
+            throw new NullPointerException("The object reference is null.");
+        }
+        return reference;
+    }
+
+    /**
+     * Ensures that an object reference passed as a parameter to the calling method is not null.
+     *
+     * @param reference an object reference
+     * @param errorMessage the exception message to use if the check fails; will be converted to a
+     *     string using {@link String#valueOf(Object)}
+     * @return the non-null reference that was validated
+     * @throws NullPointerException if {@code reference} is null
+     */
+    public static <T extends Object> T checkNotNull(T reference, @Nullable Object errorMessage) {
+        if (reference == null) {
+            throw new NullPointerException(String.valueOf(errorMessage));
+        }
+        return reference;
+    }
+
+    /**
+     * Ensures that the given String is not empty and not null.
+     *
+     * @param string the String to test
+     * @return the non-null non-empty String that was validated
+     * @throws IllegalArgumentException if {@code string} is null or empty
+     */
+    public static String checkNotEmpty(String string) {
+        if (string == null || string.length() == 0) {
+            throw new IllegalArgumentException("Given String is empty or null.");
+        }
+        return string;
+    }
+
+    /**
+     * Ensures that the given String is not empty and not null.
+     *
+     * @param string the String to test
+     * @param errorMessage the exception message to use if the check fails; will be converted to a
+     *     string using {@link String#valueOf(Object)}
+     * @return the non-null non-empty String that was validated
+     * @throws IllegalArgumentException if {@code string} is null or empty
+     */
+    public static String checkNotEmpty(String string, Object errorMessage) {
+        if (string == null || string.length() == 0) {
+            throw new IllegalArgumentException(String.valueOf(errorMessage));
+        }
+        return string;
+    }
+
+    /**
+     * Ensures the truth of an expression involving one or more parameters to the calling method.
+     *
+     * @param expression a boolean expression.
+     * @throws IllegalArgumentException if {@code expression} is false.
+     */
+    public static void checkArgument(boolean expression) {
+        if (!expression) {
+            throw new IllegalArgumentException();
+        }
+    }
+
+    /**
+     * Ensures the truth of an expression involving one or more parameters to the calling method.
+     *
+     * @param expression a boolean expression.
+     * @param errorMessage the exception message to use if the check fails; will be converted to a
+     *     string using {@link String#valueOf(Object)}.
+     * @throws IllegalArgumentException if {@code expression} is false.
+     */
+    public static void checkArgument(boolean expression, @Nullable Object errorMessage) {
+        if (!expression) {
+            throw new IllegalArgumentException(String.valueOf(errorMessage));
+        }
+    }
+
+    /**
+     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
+     * size
+     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
+     *
+     * @param index a user-supplied index identifying an element of an array, list or string
+     * @param size the size of that array, list or string
+     * @return the value of {@code index}
+     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
+     *         size}
+     * @throws IllegalArgumentException if {@code size} is negative
+     */
+    public static int checkElementIndex(int index, int size) {
+        return checkElementIndex(index, size, "index");
+    }
+
+    /**
+     * Ensures that {@code index} specifies a valid <i>element</i> in an array, list or string of
+     * size
+     * {@code size}. An element index may range from zero, inclusive, to {@code size}, exclusive.
+     *
+     * @param index a user-supplied index identifying an element of an array, list or string
+     * @param size the size of that array, list or string
+     * @param desc the text to use to describe this index in an error message
+     * @return the value of {@code index}
+     * @throws IndexOutOfBoundsException if {@code index} is negative or is not less than {@code
+     *         size}
+     * @throws IllegalArgumentException if {@code size} is negative
+     */
+    public static int checkElementIndex(int index, int size, @Nullable String desc) {
+        // Carefully optimized for execution by hotspot (explanatory comment above)
+        if (index < 0 || index >= size) {
+            throw new IndexOutOfBoundsException(badElementIndex(index, size, desc));
+        }
+        return index;
+    }
+
+    /**
+     * Ensures the truth of an expression involving the state of the calling instance, but not
+     * involving any parameters to the calling method.
+     *
+     * @param expression a boolean expression
+     * @throws IllegalStateException if {@code expression} is false
+     */
+    public static void checkState(boolean expression) {
+        if (!expression) {
+            throw new IllegalStateException();
+        }
+    }
+
+    /**
+     * Ensures the truth of an expression involving the state of the calling instance, but not
+     * involving any parameters to the calling method.
+     *
+     * @param expression a boolean expression
+     * @param errorMessage the exception message to use if the check fails; will be converted to a
+     *     string using {@link String#valueOf(Object)}
+     * @throws IllegalStateException if {@code expression} is false
+     */
+    public static void checkState(boolean expression, @Nullable Object errorMessage) {
+        if (!expression) {
+            throw new IllegalStateException(String.valueOf(errorMessage));
+        }
+    }
+
+    private static String badElementIndex(int index, int size, @Nullable String desc) {
+        if (index < 0) {
+            return String.format("%s (%s) must not be negative", desc, index);
+        } else if (size < 0) {
+            throw new IllegalArgumentException("negative size: " + size);
+        } else { // index >= size
+            return String.format("%s (%s) must be less than size (%s)", desc, index, size);
+        }
+    }
+
+    private SupportPreconditions() {
+        throw new AssertionError("SupportPreconditions is Uninstantiable.");
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/package-info.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/package-info.java
new file mode 100644
index 0000000..48b43d3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/internal/package-info.java
@@ -0,0 +1,22 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+/**
+ * @hide This package is for classes that are implementation details of org.tensorflow.lite.support
+ *     AND are used from different packages within org.tensorflow.lite.support (and which cannot
+ *     therefore simply be declared as package-private). Classes in this package should only be used
+ *     from within other classes in org.tensorflow.lite.support.
+ */
+package org.tensorflow.lite.support.common.internal;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java
index 7722abd..a14cd1f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/CastOp.java
@@ -16,8 +16,8 @@
 package org.tensorflow.lite.support.common.ops;
 
 import org.tensorflow.lite.DataType;
-import org.tensorflow.lite.support.common.SupportPreconditions;
 import org.tensorflow.lite.support.common.TensorOperator;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
 
 /** Casts a {@link TensorBuffer} to a specified data type. */
@@ -33,9 +33,9 @@
      * <p>When this Op is executed, if the original {@link TensorBuffer} is already in {@code
      * destinationType}, the original buffer will be directly returned.
      *
-     * @param destinationType: The type of the casted {@link TensorBuffer}.
+     * @param destinationType The type of the casted {@link TensorBuffer}.
      * @throws IllegalArgumentException if {@code destinationType} is neither {@link DataType#UINT8}
-     * nor {@link DataType#FLOAT32}.
+     *     nor {@link DataType#FLOAT32}.
      */
     public CastOp(DataType destinationType) {
         SupportPreconditions.checkArgument(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java
index e5c89e8..912df13 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/common/ops/NormalizeOp.java
@@ -17,8 +17,8 @@
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.tensorflow.lite.DataType;
-import org.tensorflow.lite.support.common.SupportPreconditions;
 import org.tensorflow.lite.support.common.TensorOperator;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
 import org.tensorflow.lite.support.tensorbuffer.TensorBufferFloat;
 
@@ -49,9 +49,9 @@
      * happen, and original input will be directly returned in execution.
      *
      * <p>Note: The returned {@link TensorBuffer} is always a {@link DataType#FLOAT32} tensor at
-     * present, except that the input is a {@link DataType#UINT8} tensor, {@code mean} is set to 0
+     * present, except when the input is a {@link DataType#UINT8} tensor, {@code mean} is set to 0
      * and
-     * {@code stddev} is set to 1.
+     * {@code stddev} is set to 1, so that the original {@link DataType#UINT8} tensor is returned.
      *
      * @param mean the mean value to be subtracted first.
      * @param stddev the standard deviation value to divide then.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java
index 0268f82..f9b6a1f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BitmapContainer.java
@@ -15,11 +15,12 @@
 
 package org.tensorflow.lite.support.image;
 
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkArgument;
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkNotNull;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkNotNull;
 
 import android.graphics.Bitmap;
 import android.graphics.Bitmap.Config;
+import android.media.Image;
 
 import org.tensorflow.lite.DataType;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
@@ -64,6 +65,12 @@
     }
 
     @Override
+    public Image getMediaImage() {
+        throw new UnsupportedOperationException(
+                "Converting from Bitmap to android.media.Image is unsupported.");
+    }
+
+    @Override
     public int getWidth() {
         return bitmap.getWidth();
     }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java
index fe53692..a2e833b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/BoundingBoxUtil.java
@@ -15,7 +15,7 @@
 
 package org.tensorflow.lite.support.image;
 
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
 
 import android.graphics.RectF;
 
@@ -31,8 +31,8 @@
 /**
  * Helper class for converting values that represents bounding boxes into rectangles.
  *
- * <p>The class provides a static function to create bounding boxes as {@link RectF} from different
- * types of configurations.
+ * <p>The class provides a static function to create bounding boxes as {@link
+ * android.graphics.RectF} from different types of configurations.
  *
  * <p>Generally, a bounding box could be represented by 4 float values, but the values could be
  * interpreted in many ways. We now support 3 {@link Type} of configurations, and the order of
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java
index 79f7c421..716cacd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ColorSpaceType.java
@@ -15,10 +15,11 @@
 
 package org.tensorflow.lite.support.image;
 
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
 
 import android.graphics.Bitmap;
 import android.graphics.Bitmap.Config;
+import android.graphics.ImageFormat;
 
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
 
@@ -27,7 +28,7 @@
 /** Represents the type of color space of an image. */
 public enum ColorSpaceType {
     /** Each pixel has red, green, and blue color components. */
-    RGB {
+    RGB(0) {
         // The channel axis should always be 3 for RGB images.
         private static final int CHANNEL_VALUE = 3;
 
@@ -56,6 +57,11 @@
         }
 
         @Override
+        int getNumElements(int height, int width) {
+            return height * width * CHANNEL_VALUE;
+        }
+
+        @Override
         String getShapeInfoMessage() {
             return "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
                     + " representing R, G, B in order. ";
@@ -68,7 +74,7 @@
     },
 
     /** Each pixel is a single element representing only the amount of light. */
-    GRAYSCALE {
+    GRAYSCALE(1) {
         // The channel axis should always be 1 for grayscale images.
         private static final int CHANNEL_VALUE = 1;
 
@@ -103,6 +109,11 @@
         }
 
         @Override
+        int getNumElements(int height, int width) {
+            return height * width;
+        }
+
+        @Override
         String getShapeInfoMessage() {
             return "The shape of a grayscale image should be (h, w) or (1, h, w, 1). ";
         }
@@ -111,6 +122,54 @@
         Config toBitmapConfig() {
             return Config.ALPHA_8;
         }
+    },
+
+    /** YUV420sp format, encoded as "YYYYYYYY UVUV". */
+    NV12(2) {
+        @Override
+        int getNumElements(int height, int width) {
+            return getYuv420NumElements(height, width);
+        }
+    },
+
+    /**
+     * YUV420sp format, encoded as "YYYYYYYY VUVU", the standard picture format on Android Camera1
+     * preview.
+     */
+    NV21(3) {
+        @Override
+        int getNumElements(int height, int width) {
+            return getYuv420NumElements(height, width);
+        }
+    },
+
+    /** YUV420p format, encoded as "YYYYYYYY VV UU". */
+    YV12(4) {
+        @Override
+        int getNumElements(int height, int width) {
+            return getYuv420NumElements(height, width);
+        }
+    },
+
+    /** YUV420p format, encoded as "YYYYYYYY UU VV". */
+    YV21(5) {
+        @Override
+        int getNumElements(int height, int width) {
+            return getYuv420NumElements(height, width);
+        }
+    },
+
+    /**
+     * YUV420 format corresponding to {@link android.graphics.ImageFormat#YUV_420_888}. The actual
+     * encoding format (i.e. NV12 / Nv21 / YV12 / YV21) depends on the implementation of the image.
+     *
+     * <p>Use this format only when you load an {@link android.media.Image}.
+     */
+    YUV_420_888(6) {
+        @Override
+        int getNumElements(int height, int width) {
+            return getYuv420NumElements(height, width);
+        }
     };
 
     private static final int BATCH_DIM = 0; // The first element of the normalizaed shape.
@@ -118,6 +177,11 @@
     private static final int HEIGHT_DIM = 1; // The second element of the normalizaed shape.
     private static final int WIDTH_DIM = 2; // The third element of the normalizaed shape.
     private static final int CHANNEL_DIM = 3; // The fourth element of the normalizaed shape.
+    private final int value;
+
+    ColorSpaceType(int value) {
+        this.value = value;
+    }
 
     /**
      * Converts a bitmap configuration into the corresponding color space type.
@@ -137,30 +201,79 @@
     }
 
     /**
+     * Converts an {@link ImageFormat} value into the corresponding color space type.
+     *
+     * @throws IllegalArgumentException if the config is unsupported
+     */
+    static ColorSpaceType fromImageFormat(int imageFormat) {
+        switch (imageFormat) {
+            case ImageFormat.NV21:
+                return ColorSpaceType.NV21;
+            case ImageFormat.YV12:
+                return ColorSpaceType.YV12;
+            case ImageFormat.YUV_420_888:
+                return ColorSpaceType.YUV_420_888;
+            default:
+                throw new IllegalArgumentException(
+                        "ImageFormat: " + imageFormat + ", is not supported yet.");
+        }
+    }
+
+    public int getValue() {
+        return value;
+    }
+
+    /**
      * Verifies if the given shape matches the color space type.
      *
      * @throws IllegalArgumentException if {@code shape} does not match the color space type
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
      */
     void assertShape(int[] shape) {
+        assertRgbOrGrayScale("assertShape()");
+
         int[] normalizedShape = getNormalizedShape(shape);
         checkArgument(isValidNormalizedShape(normalizedShape),
                 getShapeInfoMessage() + "The provided image shape is " + Arrays.toString(shape));
     }
 
     /**
+     * Verifies if the given {@code numElements} in an image buffer matches {@code height} / {@code
+     * width} under this color space type. For example, the {@code numElements} of an RGB image of
+     * 30 x 20 should be {@code 30 * 20 * 3 = 1800}; the {@code numElements} of a NV21 image of 30 x
+     * 20 should be {@code 30 * 20 + ((30 + 1) / 2 * (20 + 1) / 2) * 2 = 952}.
+     *
+     * @throws IllegalArgumentException if {@code shape} does not match the color space type
+     */
+    void assertNumElements(int numElements, int height, int width) {
+        checkArgument(numElements >= getNumElements(height, width),
+                String.format(
+                        "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
+                                + " expected number of elements should be at least %d.",
+                        numElements, this.name(), height, width, getNumElements(height, width)));
+    }
+
+    /**
      * Converts a {@link TensorBuffer} that represents an image to a Bitmap with the color space
      * type.
      *
-     * @throws IllegalArgumentException if the shape of buffer does not match the color space type
+     * @throws IllegalArgumentException if the shape of buffer does not match the color space type,
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
      */
-    abstract Bitmap convertTensorBufferToBitmap(TensorBuffer buffer);
+    Bitmap convertTensorBufferToBitmap(TensorBuffer buffer) {
+        throw new UnsupportedOperationException(
+                "convertTensorBufferToBitmap() is unsupported for the color space type "
+                + this.name());
+    }
 
     /**
      * Returns the width of the given shape corresponding to the color space type.
      *
      * @throws IllegalArgumentException if {@code shape} does not match the color space type
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
      */
     int getWidth(int[] shape) {
+        assertRgbOrGrayScale("getWidth()");
         assertShape(shape);
         return getNormalizedShape(shape)[WIDTH_DIM];
     }
@@ -169,24 +282,65 @@
      * Returns the height of the given shape corresponding to the color space type.
      *
      * @throws IllegalArgumentException if {@code shape} does not match the color space type
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
      */
     int getHeight(int[] shape) {
+        assertRgbOrGrayScale("getHeight()");
         assertShape(shape);
         return getNormalizedShape(shape)[HEIGHT_DIM];
     }
 
-    abstract int getChannelValue();
-
+    /**
+     * Returns the channel value corresponding to the color space type.
+     *
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+     */
+    int getChannelValue() {
+        throw new UnsupportedOperationException(
+                "getChannelValue() is unsupported for the color space type " + this.name());
+    }
     /**
      * Gets the normalized shape in the form of (1, h, w, c). Sometimes, a given shape may not have
      * batch or channel axis.
+     *
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
      */
-    abstract int[] getNormalizedShape(int[] shape);
+    int[] getNormalizedShape(int[] shape) {
+        throw new UnsupportedOperationException(
+                "getNormalizedShape() is unsupported for the color space type " + this.name());
+    }
 
-    abstract String getShapeInfoMessage();
+    /**
+     * Returns the shape information corresponding to the color space type.
+     *
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+     */
+    String getShapeInfoMessage() {
+        throw new UnsupportedOperationException(
+                "getShapeInfoMessage() is unsupported for the color space type " + this.name());
+    }
 
-    /** Converts the color space type to the corresponding bitmap config. */
-    abstract Config toBitmapConfig();
+    /**
+     * Converts the color space type to the corresponding bitmap config.
+     *
+     * @throws UnsupportedOperationException if the color space type is not RGB or GRAYSCALE
+     */
+    Config toBitmapConfig() {
+        throw new UnsupportedOperationException(
+                "toBitmapConfig() is unsupported for the color space type " + this.name());
+    }
+
+    /**
+     * Gets the number of elements given the height and width of an image. For example, the number
+     * of elements of an RGB image of 30 x 20 is {@code 30 * 20 * 3 = 1800}; the number of elements
+     * of a NV21 image of 30 x 20 is {@code 30 * 20 + ((30 + 1) / 2 * (20 + 1) / 2) * 2 = 952}.
+     */
+    abstract int getNumElements(int height, int width);
+
+    private static int getYuv420NumElements(int height, int width) {
+        // Height and width of U/V planes are half of the Y plane.
+        return height * width + ((height + 1) / 2) * ((width + 1) / 2) * 2;
+    }
 
     /** Inserts a value at the specified position and return the new array. */
     private static int[] insertValue(int[] array, int pos, int value) {
@@ -202,10 +356,15 @@
     }
 
     protected boolean isValidNormalizedShape(int[] shape) {
-        if (shape[BATCH_DIM] == BATCH_VALUE && shape[HEIGHT_DIM] > 0 && shape[WIDTH_DIM] > 0
-                && shape[CHANNEL_DIM] == getChannelValue()) {
-            return true;
+        return shape[BATCH_DIM] == BATCH_VALUE && shape[HEIGHT_DIM] > 0 && shape[WIDTH_DIM] > 0
+                && shape[CHANNEL_DIM] == getChannelValue();
+    }
+
+    /** Some existing methods are only valid for RGB and GRAYSCALE images. */
+    private void assertRgbOrGrayScale(String unsupportedMethodName) {
+        if (this != ColorSpaceType.RGB && this != ColorSpaceType.GRAYSCALE) {
+            throw new UnsupportedOperationException(unsupportedMethodName
+                    + " only supports RGB and GRAYSCALE formats, but not " + this.name());
         }
-        return false;
     }
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java
index b4481fb..5c097da 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageContainer.java
@@ -16,6 +16,7 @@
 package org.tensorflow.lite.support.image;
 
 import android.graphics.Bitmap;
+import android.media.Image;
 
 import org.tensorflow.lite.DataType;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
@@ -50,6 +51,9 @@
      */
     TensorBuffer getTensorBuffer(DataType dataType);
 
+    /** Gets the {@link Image} representation of the underlying image format. */
+    Image getMediaImage();
+
     /** Returns the color space type of the image. */
     ColorSpaceType getColorSpaceType();
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java
index c555b6a..7ed5306 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageConversions.java
@@ -109,7 +109,6 @@
         int[] intValues = new int[w * h];
         bitmap.getPixels(intValues, 0, w, 0, 0, w, h);
         // TODO(b/138904567): Find a way to avoid creating multiple intermediate buffers every time.
-        int flatSize = w * h * 3;
         int[] shape = new int[] {h, w, 3};
         switch (buffer.getDataType()) {
             case UINT8:
@@ -119,9 +118,8 @@
                     byteArr[j++] = (byte) ((intValues[i] >> 8) & 0xff);
                     byteArr[j++] = (byte) (intValues[i] & 0xff);
                 }
-                ByteBuffer byteBuffer = ByteBuffer.allocateDirect(flatSize);
+                ByteBuffer byteBuffer = ByteBuffer.wrap(byteArr);
                 byteBuffer.order(ByteOrder.nativeOrder());
-                byteBuffer.put(byteArr);
                 buffer.loadBuffer(byteBuffer, shape);
                 break;
             case FLOAT32:
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java
index 5e253265..d7a853ee 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProcessor.java
@@ -15,13 +15,16 @@
 
 package org.tensorflow.lite.support.image;
 
+import static java.lang.Math.max;
+import static java.lang.Math.min;
+
 import android.graphics.PointF;
 import android.graphics.RectF;
 
 import org.tensorflow.lite.support.common.Operator;
 import org.tensorflow.lite.support.common.SequentialProcessor;
-import org.tensorflow.lite.support.common.SupportPreconditions;
 import org.tensorflow.lite.support.common.TensorOperator;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 import org.tensorflow.lite.support.image.ops.Rot90Op;
 import org.tensorflow.lite.support.image.ops.TensorOperatorWrapper;
 
@@ -110,8 +113,17 @@
                 new PointF(rect.left, rect.top), inputImageHeight, inputImageWidth);
         PointF p2 = inverseTransform(
                 new PointF(rect.right, rect.bottom), inputImageHeight, inputImageWidth);
-        return new RectF(Math.min(p1.x, p2.x), Math.min(p1.y, p2.y), Math.max(p1.x, p2.x),
-                Math.max(p1.y, p2.y));
+        return new RectF(min(p1.x, p2.x), min(p1.y, p2.y), max(p1.x, p2.x), max(p1.y, p2.y));
+    }
+
+    /**
+     * Processes a {@link TensorImage} object with prepared {@link TensorOperator}.
+     *
+     * @throws IllegalArgumentException if the image is not supported by any op.
+     */
+    @Override
+    public TensorImage process(TensorImage image) {
+        return super.process(image);
     }
 
     /**
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java
new file mode 100644
index 0000000..f61f59f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ImageProperties.java
@@ -0,0 +1,76 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkState;
+
+import com.google.auto.value.AutoValue;
+
+/**
+ * Represents the properties of an image object when being loaded to a {@link TensorImage}. See
+ * {@link TensorImage#load}. {@link ImageProperties} currently is only used with {@link
+ * org.tensorflow.lite.support.tensorbuffer.TensorBuffer}.
+ */
+@AutoValue
+public abstract class ImageProperties {
+    private static final int DEFAULT_HEIGHT = -1;
+    private static final int DEFAULT_WIDTH = -1;
+
+    public abstract int getHeight();
+
+    public abstract int getWidth();
+
+    public abstract ColorSpaceType getColorSpaceType();
+
+    public static Builder builder() {
+        return new AutoValue_ImageProperties.Builder()
+                .setHeight(DEFAULT_HEIGHT)
+                .setWidth(DEFAULT_WIDTH);
+    }
+
+    /**
+     * Builder for {@link ImageProperties}. Different image objects may require different
+     * properties. See the detais below:
+     *
+     * <ul>
+     *   {@link org.tensorflow.lite.support.tensorbuffer.TensorBuffer}:
+     *   <li>Mandatory proterties: height / width / colorSpaceType. The shape of the TensorBuffer
+     *       object will not be used to determine image height and width.
+     * </ul>
+     */
+    @AutoValue.Builder
+    public abstract static class Builder {
+        public abstract Builder setHeight(int height);
+
+        public abstract Builder setWidth(int width);
+
+        public abstract Builder setColorSpaceType(ColorSpaceType colorSpaceType);
+
+        abstract ImageProperties autoBuild();
+
+        public ImageProperties build() {
+            ImageProperties properties = autoBuild();
+            // If width or hight are not configured by the Builder, they will be -1.
+            // Enforcing all properties to be populated (AutoValue will error out if objects, like
+            // colorSpaceType, are not set up), since they are required for TensorBuffer images.
+            // If in the future we have some image object types that only require a portion of these
+            // properties, we can delay the check when TensorImage#load() is executed.
+            checkState(properties.getHeight() >= 0, "Negative image height is not allowed.");
+            checkState(properties.getWidth() >= 0, "Negative image width is not allowed.");
+            return properties;
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java
new file mode 100644
index 0000000..519aaca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MediaImageContainer.java
@@ -0,0 +1,85 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkNotNull;
+
+import android.graphics.Bitmap;
+import android.graphics.ImageFormat;
+import android.media.Image;
+
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/** Holds an {@link Image} and converts it to other image formats as needed. */
+final class MediaImageContainer implements ImageContainer {
+    private final Image image;
+
+    /**
+     * Creates a {@link MediaImageContainer} object with a YUV_420_888 {@link Image}.
+     *
+     * @throws IllegalArgumentException if the {@link ImageFormat} of {@code image} is not ARGB_8888
+     */
+    static MediaImageContainer create(Image image) {
+        return new MediaImageContainer(image);
+    }
+
+    private MediaImageContainer(Image image) {
+        checkNotNull(image, "Cannot load null Image.");
+        checkArgument(image.getFormat() == ImageFormat.YUV_420_888,
+                "Only supports loading YUV_420_888 Image.");
+        this.image = image;
+    }
+
+    @Override
+    public MediaImageContainer clone() {
+        throw new UnsupportedOperationException(
+                "android.media.Image is an abstract class and cannot be cloned.");
+    }
+
+    @Override
+    public Bitmap getBitmap() {
+        throw new UnsupportedOperationException(
+                "Converting an android.media.Image to Bitmap is not supported.");
+    }
+
+    @Override
+    public TensorBuffer getTensorBuffer(DataType dataType) {
+        throw new UnsupportedOperationException(
+                "Converting an android.media.Image to TesorBuffer is not supported.");
+    }
+
+    @Override
+    public Image getMediaImage() {
+        return image;
+    }
+
+    @Override
+    public int getWidth() {
+        return image.getWidth();
+    }
+
+    @Override
+    public int getHeight() {
+        return image.getHeight();
+    }
+
+    @Override
+    public ColorSpaceType getColorSpaceType() {
+        return ColorSpaceType.fromImageFormat(image.getFormat());
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java
new file mode 100644
index 0000000..03017bf
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/MlImageAdapter.java
@@ -0,0 +1,119 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import com.google.android.odml.image.BitmapExtractor;
+import com.google.android.odml.image.ByteBufferExtractor;
+import com.google.android.odml.image.MediaImageExtractor;
+import com.google.android.odml.image.MlImage;
+import com.google.android.odml.image.MlImage.ImageFormat;
+import com.google.auto.value.AutoValue;
+
+import java.nio.ByteBuffer;
+
+/** Converts {@code MlImage} to {@link TensorImage} and vice versa. */
+public class MlImageAdapter {
+    /** Proxies an {@link ImageFormat} and its equivalent {@link ColorSpaceType}. */
+    @AutoValue
+    abstract static class ImageFormatProxy {
+        abstract ColorSpaceType getColorSpaceType();
+
+        @ImageFormat
+        abstract int getImageFormat();
+
+        static ImageFormatProxy createFromImageFormat(@ImageFormat int format) {
+            switch (format) {
+                case MlImage.IMAGE_FORMAT_RGB:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.RGB, format);
+                case MlImage.IMAGE_FORMAT_NV12:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.NV12, format);
+                case MlImage.IMAGE_FORMAT_NV21:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.NV21, format);
+                case MlImage.IMAGE_FORMAT_YV12:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.YV12, format);
+                case MlImage.IMAGE_FORMAT_YV21:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.YV21, format);
+                case MlImage.IMAGE_FORMAT_YUV_420_888:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.YUV_420_888, format);
+                case MlImage.IMAGE_FORMAT_ALPHA:
+                    return new AutoValue_MlImageAdapter_ImageFormatProxy(
+                            ColorSpaceType.GRAYSCALE, format);
+                case MlImage.IMAGE_FORMAT_RGBA:
+                case MlImage.IMAGE_FORMAT_JPEG:
+                case MlImage.IMAGE_FORMAT_UNKNOWN:
+                    throw new IllegalArgumentException(
+                            "Cannot create ColorSpaceType from MlImage format: " + format);
+                default:
+                    throw new AssertionError("Illegal @ImageFormat: " + format);
+            }
+        }
+    }
+
+    /**
+     * Creates a {@link TensorImage} from an {@link MlImage}.
+     *
+     * <p>IMPORTANT: The returned {@link TensorImage} shares storage with {@code mlImage}, so do not
+     * modify the contained object in the {@link TensorImage}, as {@code MlImage} expects its
+     * contained data are immutable. Also, callers should use {@code
+     * MlImage#getInternal()#acquire()} and {@code MlImage#release()} to avoid the {@code mlImage}
+     * being released unexpectedly.
+     *
+     * @throws IllegalArgumentException if the {@code mlImage} is built from an unsupported
+     *         container.
+     */
+    public static TensorImage createTensorImageFrom(MlImage mlImage) {
+        // TODO(b/190670174): Choose the best storage from multiple containers.
+        com.google.android.odml.image.ImageProperties mlImageProperties =
+                mlImage.getContainedImageProperties().get(0);
+        switch (mlImageProperties.getStorageType()) {
+            case MlImage.STORAGE_TYPE_BITMAP:
+                return TensorImage.fromBitmap(BitmapExtractor.extract(mlImage));
+            case MlImage.STORAGE_TYPE_MEDIA_IMAGE:
+                TensorImage mediaTensorImage = new TensorImage();
+                mediaTensorImage.load(MediaImageExtractor.extract(mlImage));
+                return mediaTensorImage;
+            case MlImage.STORAGE_TYPE_BYTEBUFFER:
+                ByteBuffer buffer = ByteBufferExtractor.extract(mlImage);
+                ImageFormatProxy formatProxy =
+                        ImageFormatProxy.createFromImageFormat(mlImageProperties.getImageFormat());
+                TensorImage byteBufferTensorImage = new TensorImage();
+                ImageProperties properties =
+                        ImageProperties.builder()
+                                .setColorSpaceType(formatProxy.getColorSpaceType())
+                                .setHeight(mlImage.getHeight())
+                                .setWidth(mlImage.getWidth())
+                                .build();
+                byteBufferTensorImage.load(buffer, properties);
+                return byteBufferTensorImage;
+            default:
+                throw new IllegalArgumentException(
+                        "Illegal storage type: " + mlImageProperties.getStorageType());
+        }
+    }
+
+    /** Creatas a {@link ColorSpaceType} from {@code MlImage.ImageFormat}. */
+    public static ColorSpaceType createColorSpaceTypeFrom(@ImageFormat int imageFormat) {
+        return ImageFormatProxy.createFromImageFormat(imageFormat).getColorSpaceType();
+    }
+
+    private MlImageAdapter() {}
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java
index 0ed88e8..6dfef70 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorBufferContainer.java
@@ -15,7 +15,10 @@
 
 package org.tensorflow.lite.support.image;
 
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+
 import android.graphics.Bitmap;
+import android.media.Image;
 import android.util.Log;
 
 import org.tensorflow.lite.DataType;
@@ -25,28 +28,53 @@
 final class TensorBufferContainer implements ImageContainer {
     private final TensorBuffer buffer;
     private final ColorSpaceType colorSpaceType;
+    private final int height;
+    private final int width;
     private static final String TAG = TensorBufferContainer.class.getSimpleName();
 
     /**
      * Creates a {@link TensorBufferContainer} object with the specified {@link
      * TensorImage#ColorSpaceType}.
      *
+     * <p>Only supports {@link ColorSapceType#RGB} and {@link ColorSpaceType#GRAYSCALE}. Use {@link
+     * #create(TensorBuffer, ImageProperties)} for other color space types.
+     *
      * @throws IllegalArgumentException if the shape of the {@link TensorBuffer} does not match the
-     *     specified color space type
+     *     specified color space type, or if the color space type is not supported
      */
     static TensorBufferContainer create(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
-        return new TensorBufferContainer(buffer, colorSpaceType);
+        checkArgument(
+                colorSpaceType == ColorSpaceType.RGB || colorSpaceType == ColorSpaceType.GRAYSCALE,
+                "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
+                        + " `create(TensorBuffer, ImageProperties)` for other color space types.");
+
+        return new TensorBufferContainer(buffer, colorSpaceType,
+                colorSpaceType.getHeight(buffer.getShape()),
+                colorSpaceType.getWidth(buffer.getShape()));
     }
 
-    private TensorBufferContainer(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
-        colorSpaceType.assertShape(buffer.getShape());
+    static TensorBufferContainer create(TensorBuffer buffer, ImageProperties imageProperties) {
+        return new TensorBufferContainer(buffer, imageProperties.getColorSpaceType(),
+                imageProperties.getHeight(), imageProperties.getWidth());
+    }
+
+    private TensorBufferContainer(
+            TensorBuffer buffer, ColorSpaceType colorSpaceType, int height, int width) {
+        checkArgument(colorSpaceType != ColorSpaceType.YUV_420_888,
+                "The actual encoding format of YUV420 is required. Choose a ColorSpaceType from: NV12,"
+                        + " NV21, YV12, YV21. Use YUV_420_888 only when loading an android.media.Image.");
+
+        colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
         this.buffer = buffer;
         this.colorSpaceType = colorSpaceType;
+        this.height = height;
+        this.width = width;
     }
 
     @Override
     public TensorBufferContainer clone() {
-        return create(TensorBuffer.createFrom(buffer, buffer.getDataType()), colorSpaceType);
+        return new TensorBufferContainer(TensorBuffer.createFrom(buffer, buffer.getDataType()),
+                colorSpaceType, getHeight(), getWidth());
     }
 
     @Override
@@ -73,13 +101,23 @@
     }
 
     @Override
+    public Image getMediaImage() {
+        throw new UnsupportedOperationException(
+                "Converting from TensorBuffer to android.media.Image is unsupported.");
+    }
+
+    @Override
     public int getWidth() {
-        return colorSpaceType.getWidth(buffer.getShape());
+        // In case the underlying buffer in Tensorbuffer gets updated after TensorImage is created.
+        colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
+        return width;
     }
 
     @Override
     public int getHeight() {
-        return colorSpaceType.getHeight(buffer.getShape());
+        // In case the underlying buffer in Tensorbuffer gets updated after TensorImage is created.
+        colorSpaceType.assertNumElements(buffer.getFlatSize(), height, width);
+        return height;
     }
 
     @Override
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java
index 0ab62ae..a5a1252 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/TensorImage.java
@@ -15,9 +15,10 @@
 
 package org.tensorflow.lite.support.image;
 
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
 
 import android.graphics.Bitmap;
+import android.media.Image;
 
 import org.tensorflow.lite.DataType;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
@@ -32,15 +33,16 @@
  * <p>At present, only RGB images are supported, and the A channel is always ignored.
  *
  * <p>Details of data storage: a {@link TensorImage} object may have 2 potential sources of truth: a
- * {@link Bitmap} or a {@link TensorBuffer}. {@link TensorImage} maintains the state and only
- * converts one to the other when needed. A typical use case of {@link TensorImage} is to first load
- * a {@link Bitmap} image, then process it using {@link ImageProcessor}, and finally get the
- * underlying {@link ByteBuffer} of the {@link TensorBuffer} and feed it into the TFLite
- * interpreter.
+ * {@link android.graphics.Bitmap} or a {@link TensorBuffer}. {@link TensorImage} maintains the
+ * state and only converts one to the other when needed. A typical use case of {@link TensorImage}
+ * is to first load a {@link android.graphics.Bitmap} image, then process it using {@link
+ * ImageProcessor}, and finally get the underlying {@link ByteBuffer} of the {@link TensorBuffer}
+ * and feed it into the TFLite interpreter.
  *
  * <p>IMPORTANT: to achieve the best performance, {@link TensorImage} avoids copying data whenever
  * it's possible. Therefore, it doesn't own its data. Callers should not modify data objects those
- * are passed to {@link TensorImage#load(Bitmap)} or {@link TensorImage#load(TensorBuffer)}.
+ * are passed to {@link TensorImage#load(Bitmap)} or {@link TensorImage#load(TensorBuffer,
+ * ColorSpaceType)}.
  *
  * <p>IMPORTANT: all methods are not proved thread-safe.
  *
@@ -87,10 +89,11 @@
     }
 
     /**
-     * Initializes a {@link TensorImage} object of {@link DataType#UINT8} with a {@link Bitmap} .
+     * Initializes a {@link TensorImage} object of {@link DataType#UINT8} with a {@link
+     * android.graphics.Bitmap} .
      *
-     * @see TensorImage#load(Bitmap) for reusing the object when it's expensive to create objects
-     *     frequently, because every call of {@code fromBitmap} creates a new {@link TensorImage}.
+     * @see #load(Bitmap) for reusing the object when it's expensive to create objects frequently,
+     *     because every call of {@code fromBitmap} creates a new {@link TensorImage}.
      */
     public static TensorImage fromBitmap(Bitmap bitmap) {
         TensorImage image = new TensorImage();
@@ -113,11 +116,12 @@
     }
 
     /**
-     * Loads a {@link Bitmap} image object into this {@link TensorImage}.
+     * Loads a {@link android.graphics.Bitmap} image object into this {@link TensorImage}.
      *
      * <p>Note: if the {@link TensorImage} has data type other than {@link DataType#UINT8}, numeric
      * casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
-     * #getBuffer}, where the {@link Bitmap} will be converted into a {@link TensorBuffer}.
+     * #getBuffer}, where the {@link android.graphics.Bitmap} will be converted into a {@link
+     * TensorBuffer}.
      *
      * <p>Important: when loading a bitmap, DO NOT MODIFY the bitmap from the caller side anymore.
      * The
@@ -187,21 +191,84 @@
 
     /**
      * Loads a {@link TensorBuffer} containing pixel values with the specific {@link
-     * ColorSapceType}.
+     * ColorSpaceType}.
+     *
+     * <p>Only supports {@link ColorSpaceType#RGB} and {@link ColorSpaceType#GRAYSCALE}. Use {@link
+     * #load(TensorBuffer, ImageProperties)} for other color space types.
      *
      * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
      * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
      * #getBuffer}.
      *
-     * @throws IllegalArgumentException if the shape of buffer does not match the color space type
-     * @see ColorSpaceType#assertShape
+     * @param buffer the {@link TensorBuffer} to be loaded. Its shape should be either (h, w, 3) or
+     *     (1, h, w, 3) for RGB images, and either (h, w) or (1, h, w) for GRAYSCALE images
+     * @throws IllegalArgumentException if the shape of buffer does not match the color space type,
+     *         or
+     *     if the color space type is not supported
      */
     public void load(TensorBuffer buffer, ColorSpaceType colorSpaceType) {
+        checkArgument(
+                colorSpaceType == ColorSpaceType.RGB || colorSpaceType == ColorSpaceType.GRAYSCALE,
+                "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
+                        + " `load(TensorBuffer, ImageProperties)` for other color space types.");
+
         container = TensorBufferContainer.create(buffer, colorSpaceType);
     }
 
     /**
-     * Returns a {@link Bitmap} representation of this {@link TensorImage}.
+     * Loads a {@link TensorBuffer} containing pixel values with the specific {@link
+     * ImageProperties}.
+     *
+     * <p>The shape of the {@link TensorBuffer} will not be used to determine image height and
+     * width. Set image properties through {@link ImageProperties}.
+     *
+     * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
+     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+     * #getBuffer}.
+     *
+     * @throws IllegalArgumentException if buffer size is less than the image size indicated by
+     *         image
+     *     height, width, and color space type in {@link ImageProperties}
+     */
+    public void load(TensorBuffer buffer, ImageProperties imageProperties) {
+        container = TensorBufferContainer.create(buffer, imageProperties);
+    }
+
+    /**
+     * Loads a {@link ByteBuffer} containing pixel values with the specific {@link ImageProperties}.
+     *
+     * <p>Note: if the data type of {@code buffer} does not match that of this {@link TensorImage},
+     * numeric casting and clamping will be applied when calling {@link #getTensorBuffer} and {@link
+     * #getBuffer}.
+     *
+     * @throws IllegalArgumentException if buffer size is less than the image size indicated by
+     *         image
+     *     height, width, and color space type in {@link ImageProperties}
+     */
+    public void load(ByteBuffer buffer, ImageProperties imageProperties) {
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+        tensorBuffer.loadBuffer(buffer, new int[] {buffer.limit()});
+        container = TensorBufferContainer.create(tensorBuffer, imageProperties);
+    }
+
+    /**
+     * Loads an {@link android.media.Image} object into this {@link TensorImage}.
+     *
+     * <p>The main usage of this method is to load an {@link android.media.Image} object as model
+     * input to the <a href="TFLite Task
+     * Library">https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview</a>.
+     * {@link TensorImage} backed by {@link android.media.Image} is not supported by {@link
+     * ImageProcessor}.
+     *
+     * <p>* @throws IllegalArgumentException if the {@link android.graphics.ImageFormat} of {@code
+     * image} is not YUV_420_888
+     */
+    public void load(Image image) {
+        container = MediaImageContainer.create(image);
+    }
+
+    /**
+     * Returns a {@link android.graphics.Bitmap} representation of this {@link TensorImage}.
      *
      * <p>Numeric casting and clamping will be applied if the stored data is not uint8.
      *
@@ -211,9 +278,9 @@
      * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for
      * performance concern, but if modification is necessary, please make a copy.
      *
-     * @return a reference to a {@link Bitmap} in {@code ARGB_8888} config ("A" channel is always
-     *     opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType} of this {@link
-     *     TensorBuffer}.
+     * @return a reference to a {@link android.graphics.Bitmap} in {@code ARGB_8888} config ("A"
+     *     channel is always opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType}
+     * of this {@link TensorBuffer}.
      * @throws IllegalStateException if the {@link TensorImage} never loads data
      */
     public Bitmap getBitmap() {
@@ -265,6 +332,29 @@
     }
 
     /**
+     * Returns an {@link android.media.Image} representation of this {@link TensorImage}.
+     *
+     * <p>This method only works when the {@link TensorImage} is backed by an {@link
+     * android.media.Image}, meaning you need to first load an {@link android.media.Image} through
+     * {@link #load(Image)}.
+     *
+     * <p>Important: it's only a reference. DO NOT MODIFY. We don't create a copy here for
+     * performance concern, but if modification is necessary, please make a copy.
+     *
+     * @return a reference to a {@link android.graphics.Bitmap} in {@code ARGB_8888} config ("A"
+     *     channel is always opaque) or in {@code ALPHA_8}, depending on the {@link ColorSpaceType}
+     * of this {@link TensorBuffer}.
+     * @throws IllegalStateException if the {@link TensorImage} never loads data
+     */
+    public Image getMediaImage() {
+        if (container == null) {
+            throw new IllegalStateException("No image has been loaded yet.");
+        }
+
+        return container.getMediaImage();
+    }
+
+    /**
      * Gets the data type of this {@link TensorImage}.
      *
      * @return a data type. Currently only {@link DataType#UINT8} and {@link DataType#FLOAT32} are
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java
index 8105e1b..adccf23d 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeOp.java
@@ -15,10 +15,13 @@
 
 package org.tensorflow.lite.support.image.ops;
 
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+
 import android.graphics.Bitmap;
 import android.graphics.PointF;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
+import org.tensorflow.lite.support.image.ColorSpaceType;
 import org.tensorflow.lite.support.image.ImageOperator;
 import org.tensorflow.lite.support.image.TensorImage;
 
@@ -40,9 +43,9 @@
     /**
      * Creates a ResizeOp which can resize images to specified size in specified method.
      *
-     * @param targetHeight: The expected height of resized image.
-     * @param targetWidth: The expected width of resized image.
-     * @param resizeMethod: The algorithm to use for resizing. Options: {@link ResizeMethod}
+     * @param targetHeight The expected height of resized image.
+     * @param targetWidth The expected width of resized image.
+     * @param resizeMethod The algorithm to use for resizing. Options: {@link ResizeMethod}
      */
     public ResizeOp(int targetHeight, int targetWidth, ResizeMethod resizeMethod) {
         this.targetHeight = targetHeight;
@@ -62,6 +65,9 @@
     @Override
     @NonNull
     public TensorImage apply(@NonNull TensorImage image) {
+        checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
+                "Only RGB images are supported in ResizeOp, but not "
+                        + image.getColorSpaceType().name());
         Bitmap scaled = Bitmap.createScaledBitmap(
                 image.getBitmap(), targetWidth, targetHeight, useBilinear);
         image.load(scaled);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java
index c3fd264..e5de5bb 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOp.java
@@ -15,6 +15,8 @@
 
 package org.tensorflow.lite.support.image.ops;
 
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+
 import android.graphics.Bitmap;
 import android.graphics.Bitmap.Config;
 import android.graphics.Canvas;
@@ -22,6 +24,7 @@
 import android.graphics.Rect;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
+import org.tensorflow.lite.support.image.ColorSpaceType;
 import org.tensorflow.lite.support.image.ImageOperator;
 import org.tensorflow.lite.support.image.TensorImage;
 
@@ -43,8 +46,8 @@
      * Creates a ResizeWithCropOrPadOp which could crop/pad images to specified size. It adopts
      * center-crop and zero-padding.
      *
-     * @param targetHeight: The expected height of cropped/padded image.
-     * @param targetWidth: The expected width of cropped/padded image.
+     * @param targetHeight The expected height of cropped/padded image.
+     * @param targetWidth The expected width of cropped/padded image.
      */
     public ResizeWithCropOrPadOp(int targetHeight, int targetWidth) {
         this.targetHeight = targetHeight;
@@ -65,6 +68,9 @@
     @Override
     @NonNull
     public TensorImage apply(@NonNull TensorImage image) {
+        checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
+                "Only RGB images are supported in ResizeWithCropOrPadOp, but not "
+                        + image.getColorSpaceType().name());
         Bitmap input = image.getBitmap();
         int srcL;
         int srcR;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java
index 72e5d0d..86413c9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/Rot90Op.java
@@ -15,11 +15,14 @@
 
 package org.tensorflow.lite.support.image.ops;
 
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+
 import android.graphics.Bitmap;
 import android.graphics.Matrix;
 import android.graphics.PointF;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
+import org.tensorflow.lite.support.image.ColorSpaceType;
 import org.tensorflow.lite.support.image.ImageOperator;
 import org.tensorflow.lite.support.image.TensorImage;
 
@@ -36,7 +39,7 @@
      * Creates a Rot90 Op which will rotate image by 90 degree for {@code k} times
      * counter-clockwise.
      *
-     * @param k: The number of times the image is rotated by 90 degrees. If it's positive, the image
+     * @param k The number of times the image is rotated by 90 degrees. If it's positive, the image
      *     will be rotated counter-clockwise. If it's negative, the op will rotate image clockwise.
      */
     public Rot90Op(int k) {
@@ -55,6 +58,9 @@
     @NonNull
     @Override
     public TensorImage apply(@NonNull TensorImage image) {
+        checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
+                "Only RGB images are supported in Rot90Op, but not "
+                        + image.getColorSpaceType().name());
         Bitmap input = image.getBitmap();
         if (numRotation == 0) {
             return image;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java
index 90d457b..feb2b3b7 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TensorOperatorWrapper.java
@@ -18,8 +18,9 @@
 import android.graphics.PointF;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
-import org.tensorflow.lite.support.common.SupportPreconditions;
 import org.tensorflow.lite.support.common.TensorOperator;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
+import org.tensorflow.lite.support.image.ColorSpaceType;
 import org.tensorflow.lite.support.image.ImageOperator;
 import org.tensorflow.lite.support.image.TensorImage;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
@@ -52,9 +53,11 @@
         SupportPreconditions.checkNotNull(image, "Op cannot apply on null image.");
         TensorBuffer resBuffer = tensorOp.apply(image.getTensorBuffer());
         // Some ops may change the data type of the underlying TensorBuffer, such as CastOp.
-        // Therefore, need to create a new TensorImage with the correct data type.
+        // Therefore, need to create a new TensorImage with the correct data type. However the
+        // underlying ops should not touch the color type.
+        ColorSpaceType colorSpaceType = image.getColorSpaceType();
         TensorImage resImage = new TensorImage(resBuffer.getDataType());
-        resImage.load(resBuffer);
+        resImage.load(resBuffer, colorSpaceType);
         return resImage;
     }
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java
new file mode 100644
index 0000000..1a6f905
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/image/ops/TransformToGrayscaleOp.java
@@ -0,0 +1,114 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image.ops;
+
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+
+import android.graphics.Bitmap;
+import android.graphics.Canvas;
+import android.graphics.ColorFilter;
+import android.graphics.ColorMatrixColorFilter;
+import android.graphics.Paint;
+import android.graphics.PointF;
+
+import org.tensorflow.lite.support.image.ColorSpaceType;
+import org.tensorflow.lite.support.image.ImageOperator;
+import org.tensorflow.lite.support.image.TensorImage;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/**
+ * Transforms an image to GrayScale as an image processing unit.
+ *
+ * <p>Supported color spaces:
+ *
+ * <ul>
+ *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+ * </ul>
+ *
+ * <p>The conversion is based on OpenCV RGB to GRAY conversion
+ * https://docs.opencv.org/master/de/d25/imgproc_color_conversions.html#color_convert_rgb_gray
+ */
+public class TransformToGrayscaleOp implements ImageOperator {
+    // A matrix is created that will be applied later to canvas to generate grayscale image
+    // The luminance of each pixel is calculated as the weighted sum of the 3 RGB values
+    // Y = 0.299R + 0.587G + 0.114B
+    private static final float[] BITMAP_RGBA_GRAYSCALE_TRANSFORMATION =
+            new float[] {0.299F, 0.587F, 0.114F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F,
+                    0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 0.0F, 1.0F, 0.0F};
+
+    /** Creates a TransformToGrayscaleOp. */
+    public TransformToGrayscaleOp() {}
+
+    /**
+     * Applies the transformation to grayscale and returns a {@link TensorImage}.
+     *
+     * <p>If the input image is already {@link
+     * org.tensorflow.lite.support.image.ColorSpaceType#GRAYSCALE}, this op will be a no-op.
+     *
+     * @throws IllegalArgumentException if the {@code image} is not {@link
+     *     org.tensorflow.lite.support.image.ColorSpaceType#RGB} or {@link
+     *     org.tensorflow.lite.support.image.ColorSpaceType#GRAYSCALE}.
+     */
+    @Override
+    public TensorImage apply(TensorImage image) {
+        if (image.getColorSpaceType() == ColorSpaceType.GRAYSCALE) {
+            return image;
+        } else {
+            checkArgument(image.getColorSpaceType() == ColorSpaceType.RGB,
+                    "Only RGB images are supported in TransformToGrayscaleOp, but not "
+                            + image.getColorSpaceType().name());
+        }
+        int h = image.getHeight();
+        int w = image.getWidth();
+        Bitmap bmpGrayscale = Bitmap.createBitmap(w, h, Bitmap.Config.ARGB_8888);
+        Canvas canvas = new Canvas(bmpGrayscale);
+        Paint paint = new Paint();
+        ColorMatrixColorFilter colorMatrixFilter =
+                new ColorMatrixColorFilter(BITMAP_RGBA_GRAYSCALE_TRANSFORMATION);
+        paint.setColorFilter((ColorFilter) colorMatrixFilter);
+        canvas.drawBitmap(image.getBitmap(), 0.0F, 0.0F, paint);
+
+        // Get the pixels from the generated grayscale image
+        int[] intValues = new int[w * h];
+        bmpGrayscale.getPixels(intValues, 0, w, 0, 0, w, h);
+        // Shape with one channel
+        int[] shape = new int[] {1, h, w, 1};
+
+        // Get R channel from ARGB color
+        for (int i = 0; i < intValues.length; i++) {
+            intValues[i] = ((intValues[i] >> 16) & 0xff);
+        }
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, image.getDataType());
+        buffer.loadArray(intValues, shape);
+        image.load(buffer, ColorSpaceType.GRAYSCALE);
+        return image;
+    }
+
+    @Override
+    public int getOutputImageHeight(int inputImageHeight, int inputImageWidth) {
+        return inputImageHeight;
+    }
+
+    @Override
+    public int getOutputImageWidth(int inputImageHeight, int inputImageWidth) {
+        return inputImageWidth;
+    }
+
+    @Override
+    public PointF inverseTransform(PointF point, int inputImageHeight, int inputImageWidth) {
+        return point;
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java
index 07116cb..af56b70 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/Category.java
@@ -15,13 +15,20 @@
 
 package org.tensorflow.lite.support.label;
 
+import org.tensorflow.lite.annotations.UsedByReflection;
+
 import java.util.Objects;
 
 /**
- * Category is a util class, contains a label, its display name and a float value as score.
- * Typically it's used as result of classification tasks.
+ * Category is a util class, contains a label, its display name, a float value as score, and the
+ * index of the label in the corresponding label file. Typically it's used as result of
+ * classification tasks.
  */
+@UsedByReflection("TFLiteSupport/Task")
 public final class Category {
+    private static final int DEFAULT_INDEX = -1;
+    private static final float TOLERANCE = 1e-6f;
+    private final int index;
     private final String label;
     private final String displayName;
     private final float score;
@@ -29,23 +36,37 @@
     /**
      * Constructs a {@link Category} object.
      *
+     * @param label the label of this category object
      * @param displayName the display name of the label, which may be translated for different
      *     locales. For exmaple, a label, "apple", may be translated into Spanish for display
      * purpose, so that the displayName is "manzana".
+     * @param score the probability score of this label category
+     * @param index the index of the label in the corresponding label file
      */
+    @UsedByReflection("TFLiteSupport/Task")
+    public static Category create(String label, String displayName, float score, int index) {
+        return new Category(label, displayName, score, index);
+    }
+
+    /** Constructs a {@link Category} object with the default index (-1). */
+    @UsedByReflection("TFLiteSupport/Task")
     public static Category create(String label, String displayName, float score) {
-        return new Category(label, displayName, score);
+        return new Category(label, displayName, score, DEFAULT_INDEX);
     }
 
-    /** Constructs a {@link Category} object with an empty displayName. */
+    /**
+     * Constructs a {@link Category} object with an empty displayName and the default index (-1).
+     */
+    @UsedByReflection("TFLiteSupport/Task")
     public Category(String label, float score) {
-        this(label, /*displayName=*/"", score);
+        this(label, /*displayName=*/"", score, DEFAULT_INDEX);
     }
 
-    private Category(String label, String displayName, float score) {
+    private Category(String label, String displayName, float score, int index) {
         this.label = label;
         this.displayName = displayName;
         this.score = score;
+        this.index = index;
     }
 
     /** Gets the reference of category's label. */
@@ -68,25 +89,34 @@
         return score;
     }
 
+    /**
+     * Gets the index of the category. The index value might be -1, which means it has not been set
+     * up properly and is invalid.
+     */
+    public int getIndex() {
+        return index;
+    }
+
     @Override
     public boolean equals(Object o) {
         if (o instanceof Category) {
             Category other = (Category) o;
             return (other.getLabel().equals(this.label)
                     && other.getDisplayName().equals(this.displayName)
-                    && other.getScore() == this.score);
+                    && Math.abs(other.getScore() - this.score) < TOLERANCE
+                    && other.getIndex() == this.index);
         }
         return false;
     }
 
     @Override
     public int hashCode() {
-        return Objects.hash(label, displayName, score);
+        return Objects.hash(label, displayName, score, index);
     }
 
     @Override
     public String toString() {
-        return "<Category \"" + label + "\" (displayName=" + displayName + "\" (score=" + score
-                + ")>";
+        return "<Category \"" + label + "\" (displayName=" + displayName + " score=" + score
+                + " index=" + index + ")>";
     }
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java
index d135b4b..56ee89f0 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/LabelUtil.java
@@ -18,7 +18,7 @@
 import android.util.Log;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
-import org.tensorflow.lite.support.common.SupportPreconditions;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
 
 import java.util.ArrayList;
@@ -32,14 +32,15 @@
      * dictionary. Example: if the given tensor is [3, 1, 0], and given labels is ["background",
      * "apple", "banana", "cherry", "date"], the result will be ["date", "banana", "apple"].
      *
-     * @param tensorBuffer: A tensor with index values. The values should be non-negative integers,
-     *     and each value {@code x} will be converted to {@code labels[x + offset]}. If the tensor
-     * is given as a float {@link TensorBuffer}, values will be cast to integers. All values that
+     * @param tensorBuffer A tensor with index values. The values should be non-negative integers,
+     *         and
+     *     each value {@code x} will be converted to {@code labels[x + offset]}. If the tensor is
+     *     given as a float {@link TensorBuffer}, values will be cast to integers. All values that
      * are out of bound will map to empty string.
-     * @param labels: A list of strings, used as a dictionary to look up. The index of the array
+     * @param labels A list of strings, used as a dictionary to look up. The index of the array
      *     element will be used as the key. To get better performance, use an object that implements
      *     RandomAccess, such as {@link ArrayList}.
-     * @param offset: The offset value when look up int values in the {@code labels}.
+     * @param offset The offset value when look up int values in the {@code labels}.
      * @return the mapped strings. The length of the list is {@link TensorBuffer#getFlatSize}.
      * @throws IllegalArgumentException if {@code tensorBuffer} or {@code labels} is null.
      */
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java
index ff78f40..edd683c 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/TensorLabel.java
@@ -19,7 +19,7 @@
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.tensorflow.lite.DataType;
-import org.tensorflow.lite.support.common.SupportPreconditions;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
 
 import java.nio.ByteBuffer;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java
index 33411f1..e44edc6 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/label/ops/LabelAxisOp.java
@@ -19,7 +19,7 @@
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.tensorflow.lite.support.common.FileUtil;
-import org.tensorflow.lite.support.common.SupportPreconditions;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 import org.tensorflow.lite.support.label.TensorLabel;
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java
index 96ddb39..af2061e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/model/Model.java
@@ -19,10 +19,11 @@
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.checkerframework.checker.nullness.qual.Nullable;
-import org.tensorflow.lite.Interpreter;
+import org.tensorflow.lite.InterpreterApi;
+import org.tensorflow.lite.InterpreterFactory;
 import org.tensorflow.lite.Tensor;
 import org.tensorflow.lite.support.common.FileUtil;
-import org.tensorflow.lite.support.common.SupportPreconditions;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 
 import java.io.IOException;
 import java.nio.MappedByteBuffer;
@@ -79,7 +80,7 @@
     }
 
     /** An instance of the driver class to run model inference with Tensorflow Lite. */
-    private final Interpreter interpreter;
+    private final InterpreterApi interpreter;
 
     /** Path to tflite model file in asset folder. */
     private final String modelPath;
@@ -104,8 +105,8 @@
         /**
          * Creates a builder which loads tflite model from asset folder using memory-mapped files.
          *
-         * @param context: Application context to access assets.
-         * @param modelPath: Asset path of the model (.tflite file).
+         * @param context Application context to access assets.
+         * @param modelPath Asset path of the model (.tflite file).
          * @throws IOException if an I/O error occurs when loading the tflite model.
          */
         @NonNull
@@ -182,7 +183,7 @@
      */
     public static Model createModel(@NonNull MappedByteBuffer byteModel, @NonNull String modelPath,
             @NonNull Options options) {
-        Interpreter.Options interpreterOptions = new Interpreter.Options();
+        InterpreterApi.Options interpreterOptions = new InterpreterApi.Options();
         GpuDelegateProxy gpuDelegateProxy = null;
         switch (options.device) {
             case NNAPI:
@@ -198,7 +199,7 @@
                 break;
         }
         interpreterOptions.setNumThreads(options.numThreads);
-        Interpreter interpreter = new Interpreter(byteModel, interpreterOptions);
+        InterpreterApi interpreter = new InterpreterFactory().create(byteModel, interpreterOptions);
         return new Model(modelPath, byteModel, interpreter, gpuDelegateProxy);
     }
 
@@ -215,7 +216,7 @@
     }
 
     /**
-     * Gets the Tensor associated with the provdied input index.
+     * Gets the Tensor associated with the provided input index.
      *
      * @throws IllegalStateException if the interpreter is closed.
      */
@@ -224,7 +225,7 @@
     }
 
     /**
-     * Gets the Tensor associated with the provdied output index.
+     * Gets the Tensor associated with the provided output index.
      *
      * @throws IllegalStateException if the interpreter is closed.
      */
@@ -269,7 +270,7 @@
     }
 
     private Model(@NonNull String modelPath, @NonNull MappedByteBuffer byteModel,
-            @NonNull Interpreter interpreter, @Nullable GpuDelegateProxy gpuDelegateProxy) {
+            @NonNull InterpreterApi interpreter, @Nullable GpuDelegateProxy gpuDelegateProxy) {
         this.modelPath = modelPath;
         this.byteModel = byteModel;
         this.interpreter = interpreter;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java
index 7e1355ef..ec6c800e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBuffer.java
@@ -15,9 +15,9 @@
 
 package org.tensorflow.lite.support.tensorbuffer;
 
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkArgument;
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkNotNull;
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkState;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkNotNull;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkState;
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.tensorflow.lite.DataType;
@@ -50,19 +50,19 @@
      * some examples:
      *
      * <pre>
-     * Creating a float TensorBuffer with shape {2, 3}:
+     * // Creating a float TensorBuffer with shape {2, 3}:
      * int[] shape = new int[] {2, 3};
      * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
      * </pre>
      *
      * <pre>
-     * Creating an uint8 TensorBuffer of a scalar:
+     * // Creating an uint8 TensorBuffer of a scalar:
      * int[] shape = new int[] {};
      * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
      * </pre>
      *
      * <pre>
-     * Creating an empty uint8 TensorBuffer:
+     * // Creating an empty uint8 TensorBuffer:
      * int[] shape = new int[] {0};
      * TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
      * </pre>
@@ -91,7 +91,25 @@
      * the created {@link TensorBuffer} is {0}.
      *
      * <p>Dynamic TensorBuffers will reallocate memory when loading arrays or data buffers of
-     * different buffer sizes.
+     * different buffer sizes. Here are some examples:
+     *
+     * <pre>
+     * // Creating a float dynamic TensorBuffer:
+     * TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+     * // Loading a float array:
+     * float[] arr1 = new float[] {1, 2, 3};
+     * tensorBuffer.loadArray(arr, new int[] {arr1.length});
+     * // loading another float array:
+     * float[] arr2 = new float[] {1, 2, 3, 4, 5};
+     * tensorBuffer.loadArray(arr, new int[] {arr2.length});
+     * // loading a third float array with the same size as arr2, assuming shape doesn't change:
+     * float[] arr3 = new float[] {5, 4, 3, 2, 1};
+     * tensorBuffer.loadArray(arr);
+     * // loading a forth float array with different size as arr3 and omitting the shape will result
+     * // in error:
+     * float[] arr4 = new float[] {3, 2, 1};
+     * tensorBuffer.loadArray(arr); // Error: The size of byte buffer and the shape do not match.
+     * </pre>
      *
      * @param dataType The dataType of the {@link TensorBuffer} to be created.
      */
@@ -144,12 +162,12 @@
     }
 
     /**
-     * Gets the {@link TensorBuffer#flatSize} of the buffer.
+     * Gets the flatSize of the buffer.
      *
      * @throws IllegalStateException if the underlying data is corrupted
      */
     public int getFlatSize() {
-        assertShapeIsCorect();
+        assertShapeIsCorrect();
         return flatSize;
     }
 
@@ -160,7 +178,7 @@
      */
     @NonNull
     public int[] getShape() {
-        assertShapeIsCorect();
+        assertShapeIsCorrect();
         return Arrays.copyOf(shape, shape.length);
     }
 
@@ -185,7 +203,7 @@
      * For example, a TensorBuffer with shape {2, 3} that represents the following array,
      * [[0.0f, 1.0f, 2.0f], [3.0f, 4.0f, 5.0f]].
      *
-     * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrived by:
+     * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrieved by:
      * float v = tensorBuffer.getFloatValue(3);
      * </pre>
      *
@@ -212,7 +230,7 @@
      * For example, a TensorBuffer with shape {2, 3} that represents the following array,
      * [[0.0f, 1.0f, 2.0f], [3.0f, 4.0f, 5.0f]].
      *
-     * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrived by:
+     * The fourth element (whose value is 3.0f) in the TensorBuffer can be retrieved by:
      * int v = tensorBuffer.getIntValue(3);
      * Note that v is converted from 3.0f to 3 as a result of type conversion.
      * </pre>
@@ -255,8 +273,10 @@
      * TensorBufferUint8} , the values will be clamped to [0, 255] and then be casted to uint8 by
      * {255, 0}.
      *
-     * <p>Size of {@code src} should always match the flat size of this {@link TensorBuffer}, for
-     * both fixed-size and dynamic {@link TensorBuffer}.
+     * <p>Using this method assumes that the shape of {@code src} is the same as the shape of this
+     * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code src.length}) should always
+     * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
+     * TensorBuffer}. Use {@link #loadArray(int[], int[])} if {@code src} has a different shape.
      *
      * @param src The source array to be loaded.
      */
@@ -287,8 +307,10 @@
      * with values {400.32f, -23.04f}, the values will be clamped to [0, 255] and then be casted to
      * uint8 by {255, 0}.
      *
-     * <p>Size of {@code src} should always match the flat size of this {@link TensorBuffer}, for
-     * both fixed-size and dynamic {@link TensorBuffer}.
+     * <p>Using this method assumes that the shape of {@code src} is the same as the shape of this
+     * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code src.length}) should always
+     * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
+     * TensorBuffer}. Use {@link #loadArray(float[], int[])} if {@code src} has a different shape.
      *
      * @param src The source array to be loaded.
      */
@@ -302,6 +324,9 @@
      * <p>Important: The loaded buffer is a reference. DO NOT MODIFY. We don't create a copy here
      * for performance concern, but if modification is necessary, please make a copy.
      *
+     * <p>For the best performance, always load a direct {@link ByteBuffer} or a {@link ByteBuffer}
+     * backed by an array.
+     *
      * @param buffer The byte buffer to load.
      * @throws NullPointerException if {@code buffer} is null.
      * @throws IllegalArgumentException if the size of {@code buffer} and {@code typeSize} do not
@@ -309,11 +334,22 @@
      */
     public void loadBuffer(@NonNull ByteBuffer buffer, @NonNull int[] shape) {
         checkNotNull(buffer, "Byte buffer cannot be null.");
+        checkArgument(isShapeValid(shape), "Values in TensorBuffer shape should be non-negative.");
+
         int flatSize = computeFlatSize(shape);
         checkArgument((buffer.limit() == getTypeSize() * flatSize),
-                "The size of byte buffer and the shape do not match.");
+                "The size of byte buffer and the shape do not match. Expected: "
+                        + getTypeSize() * flatSize + " Actual: " + buffer.limit());
 
-        resize(shape);
+        if (!isDynamic) {
+            // Make sure the new shape fits the buffer size when TensorBuffer has fixed size.
+            checkArgument(Arrays.equals(shape, this.shape));
+        }
+
+        // Update to the new shape, since shape dim values might change.
+        this.shape = shape.clone();
+        this.flatSize = flatSize;
+
         buffer.rewind();
         this.buffer = buffer;
     }
@@ -322,9 +358,21 @@
      * Loads a byte buffer into this {@link TensorBuffer}. Buffer size must match the flat size of
      * this {@link TensorBuffer}.
      *
+     * <p>Using this method assumes that the shape of {@code buffer} is the same as the shape of
+     * this
+     * {@link TensorBuffer}. Thus the size of {@code buffer} ({@code buffer.limit()}) should always
+     * match the flat size of this {@link TensorBuffer}, for both fixed-size and dynamic {@link
+     * TensorBuffer}. Use {@link #loadBuffer(ByteBuffer, int[])} if {@code buffer} has a different
+     * shape.
+     *
      * <p>Important: The loaded buffer is a reference. DO NOT MODIFY. We don't create a copy here
      * for performance concern, but if modification is necessary, please make a copy.
      *
+     * <p>For the best performance, always load a direct {@link ByteBuffer} or a {@link ByteBuffer}
+     * backed by an array.
+     *
+     * <p>If the {@code buffer} is read-only, we adopt a copy-on-write strategy for performance.
+     *
      * @param buffer The byte buffer to load.
      */
     public void loadBuffer(@NonNull ByteBuffer buffer) {
@@ -373,6 +421,18 @@
         }
     }
 
+    /** Copies the underlying {@link ByteBuffer} if it's readonly. */
+    protected synchronized void copyByteBufferIfReadOnly() {
+        if (!buffer.isReadOnly()) {
+            return;
+        }
+        ByteBuffer newByteBuffer = ByteBuffer.allocateDirect(buffer.capacity());
+        newByteBuffer.order(buffer.order());
+        newByteBuffer.put(buffer);
+        newByteBuffer.rewind();
+        buffer = newByteBuffer;
+    }
+
     /**
      * Allocates buffer with corresponding size of the {@code shape}. If shape is an empty array,
      * this
@@ -402,7 +462,7 @@
      * Verifies if the shape of the {@link TensorBuffer} matched the size of the underlying {@link
      * ByteBuffer}.
      */
-    private void assertShapeIsCorect() {
+    private void assertShapeIsCorrect() {
         int flatSize = computeFlatSize(shape);
         checkState((buffer.limit() == getTypeSize() * flatSize),
                 String.format(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java
index 74d7e18..632db6c8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloat.java
@@ -17,7 +17,7 @@
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.tensorflow.lite.DataType;
-import org.tensorflow.lite.support.common.SupportPreconditions;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 
 import java.nio.FloatBuffer;
 
@@ -89,6 +89,7 @@
         SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
         SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
                 "The size of the array to be loaded does not match the specified shape.");
+        copyByteBufferIfReadOnly();
         resize(shape);
         buffer.rewind();
 
@@ -101,6 +102,7 @@
         SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
         SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
                 "The size of the array to be loaded does not match the specified shape.");
+        copyByteBufferIfReadOnly();
         resize(shape);
         buffer.rewind();
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java
index 8bbbf95..2924ef0a 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8.java
@@ -17,7 +17,7 @@
 
 import org.checkerframework.checker.nullness.qual.NonNull;
 import org.tensorflow.lite.DataType;
-import org.tensorflow.lite.support.common.SupportPreconditions;
+import org.tensorflow.lite.support.common.internal.SupportPreconditions;
 
 /** Represents data buffer with 8-bit unsigned integer values. */
 public final class TensorBufferUint8 extends TensorBuffer {
@@ -90,6 +90,7 @@
         SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
         SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
                 "The size of the array to be loaded does not match the specified shape.");
+        copyByteBufferIfReadOnly();
         resize(shape);
         buffer.rewind();
 
@@ -106,6 +107,7 @@
         SupportPreconditions.checkNotNull(src, "The array to be loaded cannot be null.");
         SupportPreconditions.checkArgument(src.length == computeFlatSize(shape),
                 "The size of the array to be loaded does not match the specified shape.");
+        copyByteBufferIfReadOnly();
         resize(shape);
         buffer.rewind();
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/AndroidManifest.xml
new file mode 100644
index 0000000..cecae01
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/AndroidManifest.xml
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="utf-8"?>
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+    package="org.tensorflow.lite.task.audio">
+  <uses-sdk android:minSdkVersion="23" android:targetSdkVersion="29"/>
+</manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/BUILD
new file mode 100644
index 0000000..1769dac
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/BUILD
@@ -0,0 +1,40 @@
+load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
+load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+
+package(
+    default_visibility = ["//visibility:public"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files([
+    "AndroidManifest.xml",
+])
+
+android_library(
+    name = "task_library_audio",
+    srcs = [
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier:audio_classifier_src",
+    ],
+    # TODO(b/163039980): Use JAVACOPTS in TF. "-Xep:RemoveUnusedImports:ERROR" wierdly break the build.
+    javacopts = ["-source 7 -target 7"],
+    manifest = "AndroidManifest.xml",
+    visibility = ["//visibility:public"],
+    # LINT.IfChange(dep)
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support_java",
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
+        "//tensorflow_lite_support/java/src/native/task/audio:task_audio_native",
+        "@com_google_auto_value",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
+    ],
+    # LINT.ThenChange(<INTERNAL>/release/build_task_pom.sh:dep)
+)
+
+# AAR target for OSS release.
+#
+# bazel build -c opt --config=monolithic --config=android_arm64 --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a \
+#   tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio:task-library-audio
+aar_with_jni(
+    name = "task-library-audio",
+    android_library = ":task_library_audio",
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java
new file mode 100644
index 0000000..b3eb11f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/AudioClassifier.java
@@ -0,0 +1,510 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.task.audio.classifier;
+
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkState;
+
+import android.content.Context;
+import android.media.AudioFormat;
+import android.media.AudioRecord;
+import android.media.MediaRecorder;
+import android.os.ParcelFileDescriptor;
+
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.annotations.UsedByReflection;
+import org.tensorflow.lite.support.audio.TensorAudio;
+import org.tensorflow.lite.support.audio.TensorAudio.TensorAudioFormat;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+import org.tensorflow.lite.task.core.BaseOptions;
+import org.tensorflow.lite.task.core.BaseTaskApi;
+import org.tensorflow.lite.task.core.TaskJniUtils;
+import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
+
+import java.io.File;
+import java.io.IOException;
+import java.nio.ByteBuffer;
+import java.nio.MappedByteBuffer;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * Performs classification on audio waveforms.
+ *
+ * <p>The API expects a TFLite model with <a
+ * href="https://www.tensorflow.org/lite/convert/metadata">TFLite Model Metadata.</a>.
+ *
+ * <p>The API supports models with one audio input tensor and one classification output tensor. To
+ * be more specific, here are the requirements.
+ *
+ * <ul>
+ *   <li>Input audio tensor ({@code kTfLiteFloat32})
+ *       <ul>
+ *         <li>input audio buffer of size {@code [batch x samples]}.
+ *         <li>batch inference is not supported ({@code batch} is required to be 1).
+ *       </ul>
+ *   <li>Output score tensor ({@code kTfLiteFloat32})
+ *       <ul>
+ *         <li>with {@code N} classes of either 2 or 4 dimensions, such as {@code [1 x N]} or {@code
+ *             [1 x 1 x 1 x N]}
+ *         <li>the label file is required to be packed to the metadata. See the <a
+ *             href="https://www.tensorflow.org/lite/convert/metadata#label_output">example of
+ *             creating metadata for an image classifier</a>. If no label files are packed, it will
+ *             use index as label in the result.
+ *       </ul>
+ * </ul>
+ *
+ * See <a href="https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1">an example</a>
+ * of such model, and <a
+ * href="https://github.com/tensorflow/tflite-support/tree/master/tensorflow_lite_support/examples/task/audio/desktop">a
+ * CLI demo tool</a> for easily trying out this API.
+ */
+public final class AudioClassifier extends BaseTaskApi {
+    private static final String AUDIO_CLASSIFIER_NATIVE_LIB = "task_audio_jni";
+    private static final int OPTIONAL_FD_LENGTH = -1;
+    private static final int OPTIONAL_FD_OFFSET = -1;
+
+    /**
+     * Creates an {@link AudioClassifier} instance from the default {@link AudioClassifierOptions}.
+     *
+     * @param modelPath path of the classification model with metadata in the assets
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static AudioClassifier createFromFile(Context context, String modelPath)
+            throws IOException {
+        return createFromFileAndOptions(
+                context, modelPath, AudioClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates an {@link AudioClassifier} instance from the default {@link AudioClassifierOptions}.
+     *
+     * @param modelFile the classification model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static AudioClassifier createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, AudioClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates an {@link AudioClassifier} instance with a model buffer and the default {@link
+     * AudioClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     classification model
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     */
+    public static AudioClassifier createFromBuffer(final ByteBuffer modelBuffer) {
+        return createFromBufferAndOptions(modelBuffer, AudioClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates an {@link AudioClassifier} instance from {@link AudioClassifierOptions}.
+     *
+     * @param modelPath path of the classification model with metadata in the assets
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static AudioClassifier createFromFileAndOptions(
+            Context context, String modelPath, AudioClassifierOptions options) throws IOException {
+        return new AudioClassifier(TaskJniUtils.createHandleFromFdAndOptions(
+                context, new FdAndOptionsHandleProvider<AudioClassifierOptions>() {
+                    @Override
+                    public long createHandle(int fileDescriptor, long fileDescriptorLength,
+                            long fileDescriptorOffset, AudioClassifierOptions options) {
+                        return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
+                                fileDescriptorOffset, options,
+                                TaskJniUtils.createProtoBaseOptionsHandle(
+                                        options.getBaseOptions()));
+                    }
+                }, AUDIO_CLASSIFIER_NATIVE_LIB, modelPath, options));
+    }
+
+    /**
+     * Creates an {@link AudioClassifier} instance.
+     *
+     * @param modelFile the classification model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static AudioClassifier createFromFileAndOptions(
+            File modelFile, final AudioClassifierOptions options) throws IOException {
+        try (ParcelFileDescriptor descriptor =
+                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+            return new AudioClassifier(
+                    TaskJniUtils.createHandleFromLibrary(new TaskJniUtils.EmptyHandleProvider() {
+                        @Override
+                        public long createHandle() {
+                            return initJniWithModelFdAndOptions(descriptor.getFd(),
+                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
+                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options,
+                                    TaskJniUtils.createProtoBaseOptionsHandle(
+                                            options.getBaseOptions()));
+                        }
+                    }, AUDIO_CLASSIFIER_NATIVE_LIB));
+        }
+    }
+
+    /**
+     * Creates an {@link AudioClassifier} instance with a model buffer and {@link
+     * AudioClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     classification model
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     */
+    public static AudioClassifier createFromBufferAndOptions(
+            final ByteBuffer modelBuffer, final AudioClassifierOptions options) {
+        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+            throw new IllegalArgumentException(
+                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
+        }
+        return new AudioClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                return initJniWithByteBuffer(modelBuffer, options,
+                        TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+            }
+        }, AUDIO_CLASSIFIER_NATIVE_LIB));
+    }
+
+    /**
+     * Constructor to initialize the JNI with a pointer from C++.
+     *
+     * @param nativeHandle a pointer referencing memory allocated in C++
+     */
+    private AudioClassifier(long nativeHandle) {
+        super(nativeHandle);
+    }
+
+    /** Options for setting up an {@link AudioClassifier}. */
+    @UsedByReflection("audio_classifier_jni.cc")
+    public static class AudioClassifierOptions {
+        // Not using AutoValue for this class because scoreThreshold cannot have default value
+        // (otherwise, the default value would override the one in the model metadata) and
+        // `Optional` is not an option here, because
+        // 1. java.util.Optional require Java 8 while we need to support Java 7.
+        // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See
+        // the comments for labelAllowList.
+        private final BaseOptions baseOptions;
+        private final String displayNamesLocale;
+        private final int maxResults;
+        private final float scoreThreshold;
+        private final boolean isScoreThresholdSet;
+        // As an open source project, we've been trying avoiding depending on common java libraries,
+        // such as Guava, because it may introduce conflicts with clients who also happen to use
+        // those libraries. Therefore, instead of using ImmutableList here, we convert the List into
+        // unmodifiableList in setLabelAllowList() and setLabelDenyList() to make it less
+        // vulnerable.
+        private final List<String> labelAllowList;
+        private final List<String> labelDenyList;
+
+        public static Builder builder() {
+            return new Builder();
+        }
+
+        /** A builder that helps to configure an instance of AudioClassifierOptions. */
+        public static class Builder {
+            private BaseOptions baseOptions = BaseOptions.builder().build();
+            private String displayNamesLocale = "en";
+            private int maxResults = -1;
+            private float scoreThreshold;
+            private boolean isScoreThresholdSet;
+            private List<String> labelAllowList = new ArrayList<>();
+            private List<String> labelDenyList = new ArrayList<>();
+
+            private Builder() {}
+
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public Builder setBaseOptions(BaseOptions baseOptions) {
+                this.baseOptions = baseOptions;
+                return this;
+            }
+
+            /**
+             * Sets the locale to use for display names specified through the TFLite Model Metadata,
+             * if any.
+             *
+             * <p>Defaults to English({@code "en"}). See the <a
+             * href="https://github.com/tensorflow/tflite-support/blob/3ce83f0cfe2c68fecf83e019f2acc354aaba471f/tensorflow_lite_support/metadata/metadata_schema.fbs#L147">TFLite
+             * Metadata schema file.</a> for the accepted pattern of locale.
+             */
+            public Builder setDisplayNamesLocale(String displayNamesLocale) {
+                this.displayNamesLocale = displayNamesLocale;
+                return this;
+            }
+
+            /**
+             * Sets the maximum number of top scored results to return.
+             *
+             * @param maxResults if < 0, all results will be returned. If 0, an invalid argument
+             *         error is
+             *     returned. Defaults to -1.
+             * @throws IllegalArgumentException if maxResults is 0
+             */
+            public Builder setMaxResults(int maxResults) {
+                if (maxResults == 0) {
+                    throw new IllegalArgumentException("maxResults cannot be 0.");
+                }
+                this.maxResults = maxResults;
+                return this;
+            }
+
+            /**
+             * Sets the score threshold.
+             *
+             * <p>It overrides the one provided in the model metadata (if any). Results below this
+             * value are rejected.
+             */
+            public Builder setScoreThreshold(float scoreThreshold) {
+                this.scoreThreshold = scoreThreshold;
+                isScoreThresholdSet = true;
+                return this;
+            }
+
+            /**
+             * Sets the optional allowlist of labels.
+             *
+             * <p>If non-empty, classifications whose label is not in this set will be filtered out.
+             * Duplicate or unknown labels are ignored. Mutually exclusive with labelDenyList.
+             */
+            public Builder setLabelAllowList(List<String> labelAllowList) {
+                this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
+                return this;
+            }
+
+            /**
+             * Sets the optional denylist of labels.
+             *
+             * <p>If non-empty, classifications whose label is in this set will be filtered out.
+             * Duplicate or unknown labels are ignored. Mutually exclusive with labelAllowList.
+             */
+            public Builder setLabelDenyList(List<String> labelDenyList) {
+                this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
+                return this;
+            }
+
+            public AudioClassifierOptions build() {
+                return new AudioClassifierOptions(this);
+            }
+        }
+
+        @UsedByReflection("audio_classifier_jni.cc")
+        public String getDisplayNamesLocale() {
+            return displayNamesLocale;
+        }
+
+        @UsedByReflection("audio_classifier_jni.cc")
+        public int getMaxResults() {
+            return maxResults;
+        }
+
+        @UsedByReflection("audio_classifier_jni.cc")
+        public float getScoreThreshold() {
+            return scoreThreshold;
+        }
+
+        @UsedByReflection("audio_classifier_jni.cc")
+        public boolean getIsScoreThresholdSet() {
+            return isScoreThresholdSet;
+        }
+
+        @UsedByReflection("audio_classifier_jni.cc")
+        public List<String> getLabelAllowList() {
+            return new ArrayList<>(labelAllowList);
+        }
+
+        @UsedByReflection("audio_classifier_jni.cc")
+        public List<String> getLabelDenyList() {
+            return new ArrayList<>(labelDenyList);
+        }
+
+        public BaseOptions getBaseOptions() {
+            return baseOptions;
+        }
+
+        private AudioClassifierOptions(Builder builder) {
+            displayNamesLocale = builder.displayNamesLocale;
+            maxResults = builder.maxResults;
+            scoreThreshold = builder.scoreThreshold;
+            isScoreThresholdSet = builder.isScoreThresholdSet;
+            labelAllowList = builder.labelAllowList;
+            labelDenyList = builder.labelDenyList;
+            baseOptions = builder.baseOptions;
+        }
+    }
+
+    /**
+     * Performs actual classification on the provided audio tensor.
+     *
+     * @param tensor a {@link TensorAudio} containing the input audio clip in float with values
+     *     between [-1, 1). The {@code tensor} argument should have the same flat size as the TFLite
+     *     model's input tensor. It's recommended to create {@code tensor} using {@code
+     *     createInputTensorAudio} method.
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if error occurs when classifying the audio clip from the native
+     *     code
+     */
+    public List<Classifications> classify(TensorAudio tensor) {
+        TensorBuffer buffer = tensor.getTensorBuffer();
+        TensorAudioFormat format = tensor.getFormat();
+        checkState(buffer.getBuffer().hasArray(),
+                "Input tensor buffer should be a non-direct buffer with a backed array (i.e. not readonly"
+                        + " buffer).");
+        return classifyNative(getNativeHandle(), buffer.getBuffer().array(), format.getChannels(),
+                format.getSampleRate());
+    }
+
+    /**
+     * Creates a {@link TensorAudio} instance to store input audio samples.
+     *
+     * @return a {@link TensorAudio} with the same size as model input tensor
+     * @throws IllegalArgumentException if the model is not compatible
+     */
+    public TensorAudio createInputTensorAudio() {
+        TensorAudioFormat format = getRequiredTensorAudioFormat();
+
+        long bufferSize = getRequiredInputBufferSize();
+        long samples = bufferSize / format.getChannels();
+        return TensorAudio.create(format, (int) samples);
+    }
+
+    /** Returns the required input buffer size in number of float elements. */
+    public long getRequiredInputBufferSize() {
+        return getRequiredInputBufferSizeNative(getNativeHandle());
+    }
+
+    /**
+     * Creates an {@link android.media.AudioRecord} instance to record audio stream. The returned
+     * AudioRecord instance is initialized and client needs to call {@link
+     * android.media.AudioRecord#startRecording} method to start recording.
+     *
+     * @return an {@link android.media.AudioRecord} instance in {@link
+     *     android.media.AudioRecord#STATE_INITIALIZED}
+     * @throws IllegalArgumentException if the model required channel count is unsupported
+     * @throws IllegalStateException if AudioRecord instance failed to initialize
+     */
+    public AudioRecord createAudioRecord() {
+        TensorAudioFormat format = getRequiredTensorAudioFormat();
+        int channelConfig = 0;
+
+        switch (format.getChannels()) {
+            case 1:
+                channelConfig = AudioFormat.CHANNEL_IN_MONO;
+                break;
+            case 2:
+                channelConfig = AudioFormat.CHANNEL_IN_STEREO;
+                break;
+            default:
+                throw new IllegalArgumentException(String.format(
+                        "Number of channels required by the model is %d. getAudioRecord method only"
+                                + " supports 1 or 2 audio channels.",
+                        format.getChannels()));
+        }
+
+        int bufferSizeInBytes = AudioRecord.getMinBufferSize(
+                format.getSampleRate(), channelConfig, AudioFormat.ENCODING_PCM_FLOAT);
+        if (bufferSizeInBytes == AudioRecord.ERROR
+                || bufferSizeInBytes == AudioRecord.ERROR_BAD_VALUE) {
+            throw new IllegalStateException(String.format(
+                    "AudioRecord.getMinBufferSize failed. Returned: %d", bufferSizeInBytes));
+        }
+        // The buffer of AudioRecord should be strictly longer than what model requires so that
+        // clients could run `TensorAudio::load(record)` together with `AudioClassifier::classify`.
+        int bufferSizeMultiplier = 2;
+        int modelRequiredBufferSize = (int) getRequiredInputBufferSize()
+                * DataType.FLOAT32.byteSize() * bufferSizeMultiplier;
+        if (bufferSizeInBytes < modelRequiredBufferSize) {
+            bufferSizeInBytes = modelRequiredBufferSize;
+        }
+        AudioRecord audioRecord = new AudioRecord(
+                // including MIC, UNPROCESSED, and CAMCORDER.
+                MediaRecorder.AudioSource.VOICE_RECOGNITION, format.getSampleRate(), channelConfig,
+                AudioFormat.ENCODING_PCM_FLOAT, bufferSizeInBytes);
+        checkState(audioRecord.getState() == AudioRecord.STATE_INITIALIZED,
+                "AudioRecord failed to initialize");
+        return audioRecord;
+    }
+
+    /** Returns the {@link TensorAudioFormat} required by the model. */
+    public TensorAudioFormat getRequiredTensorAudioFormat() {
+        return TensorAudioFormat.builder()
+                .setChannels(getRequiredChannels())
+                .setSampleRate(getRequiredSampleRate())
+                .build();
+    }
+
+    private int getRequiredChannels() {
+        return getRequiredChannelsNative(getNativeHandle());
+    }
+
+    private int getRequiredSampleRate() {
+        return getRequiredSampleRateNative(getNativeHandle());
+    }
+
+    // TODO(b/183343074): JNI method invocation is very expensive, taking about .2ms
+    // each time. Consider combining the native getter methods into 1 and cache it in Java layer.
+    private static native long getRequiredInputBufferSizeNative(long nativeHandle);
+
+    private static native int getRequiredChannelsNative(long nativeHandle);
+
+    private static native int getRequiredSampleRateNative(long nativeHandle);
+
+    private static native List<Classifications> classifyNative(
+            long nativeHandle, byte[] audioBuffer, int channels, int sampleRate);
+
+    private static native long initJniWithModelFdAndOptions(int fileDescriptor,
+            long fileDescriptorLength, long fileDescriptorOffset, AudioClassifierOptions options,
+            long baseOptionsHandle);
+
+    private static native long initJniWithByteBuffer(
+            ByteBuffer modelBuffer, AudioClassifierOptions options, long baseOptionsHandle);
+
+    /**
+     * Releases memory pointed by {@code nativeHandle}, namely a C++ `AudioClassifier` instance.
+     *
+     * @param nativeHandle pointer to memory allocated
+     */
+    @Override
+    protected void deinit(long nativeHandle) {
+        deinitJni(nativeHandle);
+    }
+
+    /**
+     * Native method to release memory pointed by {@code nativeHandle}, namely a C++
+     * `AudioClassifier` instance.
+     *
+     * @param nativeHandle pointer to memory allocated
+     */
+    private static native void deinitJni(long nativeHandle);
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/BUILD
new file mode 100644
index 0000000..d5678f7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/BUILD
@@ -0,0 +1,37 @@
+load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+
+package(
+    default_visibility = ["//visibility:public"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "audio_classifier_src",
+    srcs = glob(["**/*.java"]),
+)
+
+# Default target that uses BuiltInOpResolver, registers all built-in OPs.
+android_library(
+    name = "audio_classifier",
+    exports = [
+        ":audio_classifier_java",
+        "//tensorflow_lite_support/java/src/native/task/audio/classifier:audio_classifier_native",
+    ],
+)
+
+# Java-only target, needs to be used together with a native target similar to
+# //third_party/tensorflow_lite_support/java/src/native/task/audio/classifier:audio_classifier_native.
+# Use this target when you want to provide a MutableOpResolver with customized
+# OPs and/or a subset of BuiltInOps to reduce binary size.
+android_library(
+    name = "audio_classifier_java",
+    srcs = [":audio_classifier_src"],
+    javacopts = ["-source 7 -target 7"],
+    manifest = "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio:AndroidManifest.xml",
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support_java",
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
+        "@com_google_auto_value",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java
new file mode 100644
index 0000000..7d5b07f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio/classifier/Classifications.java
@@ -0,0 +1,50 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.task.audio.classifier;
+
+import com.google.auto.value.AutoValue;
+
+import org.tensorflow.lite.annotations.UsedByReflection;
+import org.tensorflow.lite.support.label.Category;
+
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * The classification results of one head in a multihead (a.k.a. multi-output) {@link
+ * AudioClassifier}. A multihead {@link AudioClassifier} can perform classification for multiple
+ * purposes, such as a fine grained classifier to distinguish different bird sounds.
+ */
+// TODO(b/183343074): Create a common class that can be used for both Audio and Vision tasks.
+@AutoValue
+@UsedByReflection("audio_classifier_jni.cc")
+public abstract class Classifications {
+    @UsedByReflection("audio_classifier_jni.cc")
+    static Classifications create(List<Category> categories, int headIndex, String headName) {
+        return new AutoValue_Classifications(
+                Collections.unmodifiableList(new ArrayList<Category>(categories)), headIndex,
+                headName);
+    }
+
+    // Same reason for not using ImmutableList as stated in
+    // {@link ImageClassifier#ImageClassifierOptions#labelAllowList}.
+    public abstract List<Category> getCategories();
+
+    public abstract int getHeadIndex();
+
+    public abstract String getHeadName();
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BUILD
index f82b800..4f3e538 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BUILD
@@ -1,5 +1,4 @@
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
@@ -9,11 +8,13 @@
 android_library(
     name = "base-task-api",
     srcs = glob(["**/*.java"]),
-    javacopts = JAVACOPTS,
+    javacopts = ["-source 7 -target 7"],
     visibility = ["//visibility:public"],
+    # LINT.IfChange(dep)
     deps = [
         "@com_google_auto_value",
     ],
+    # LINT.ThenChange(<INTERNAL>/release/build_task_base_pom.sh:dep)
 )
 
 alias(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java
new file mode 100644
index 0000000..b2d7223
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/BaseOptions.java
@@ -0,0 +1,85 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.task.core;
+
+import com.google.auto.value.AutoValue;
+
+/** Options to configure Task APIs in general. */
+@AutoValue
+public abstract class BaseOptions {
+    private static final int DEFAULT_NUM_THREADS = -1;
+
+    /** Builder for {@link BaseOptions}. */
+    @AutoValue.Builder
+    public abstract static class Builder {
+        /**
+         * Sets the advanced accelerator options.
+         *
+         * <p>Note: this method will override those highlevel API to choose an delegate, such as
+         * {@link #useGpu} and {@link #useNnapi}.
+         */
+        public abstract Builder setComputeSettings(ComputeSettings computeSettings);
+
+        /**
+         * Sets the number of threads to be used for TFLite ops that support multi-threading when
+         * running inference with CPU. Defaults to -1.
+         *
+         * <p>{@code numThreads} should be greater than 0 or equal to -1. Setting numThreads to -1
+         * has the effect to let TFLite runtime set the value.
+         */
+        public abstract Builder setNumThreads(int numThreads);
+
+        /**
+         * Uses GPU for inference. The advanced GPU configuration settings will be set to default
+         * values.
+         *
+         * <p>Note: this method will override the settings from {@link #setComputeSettings}.
+         *
+         * <p>To manipulate the advanced GPU configuration settings, use {@link
+         * #setComputeSettings}.
+         */
+        public Builder useGpu() {
+            return setComputeSettings(
+                    ComputeSettings.builder().setDelegate(ComputeSettings.Delegate.GPU).build());
+        }
+
+        /**
+         * Uses NNAPI for inference. The advanced NNAPI configuration settings will be set to
+         * default values.
+         *
+         * <p>Note: this method will override the settings from {@link #setComputeSettings}.
+         *
+         * <p>To manipulate the advanced NNAPI configuration settings, use {@link
+         * #setComputeSettings}.
+         */
+        public Builder useNnapi() {
+            return setComputeSettings(
+                    ComputeSettings.builder().setDelegate(ComputeSettings.Delegate.NNAPI).build());
+        }
+
+        public abstract BaseOptions build();
+    }
+
+    public static Builder builder() {
+        return new AutoValue_BaseOptions.Builder()
+                .setComputeSettings(ComputeSettings.builder().build())
+                .setNumThreads(DEFAULT_NUM_THREADS);
+    }
+
+    abstract ComputeSettings getComputeSettings();
+
+    abstract int getNumThreads();
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java
new file mode 100644
index 0000000..0c2d042
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/ComputeSettings.java
@@ -0,0 +1,55 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.task.core;
+
+import com.google.auto.value.AutoValue;
+
+/** Options to configure how to accelerate the model inference using dedicated delegates. */
+@AutoValue
+public abstract class ComputeSettings {
+    /** TFLite accelerator delegate options. */
+    public enum Delegate {
+        NONE(0),
+        NNAPI(1),
+        GPU(2);
+
+        private final int value;
+
+        Delegate(int value) {
+            this.value = value;
+        }
+
+        public int getValue() {
+            return value;
+        }
+    }
+
+    /** Builder for {@link ComputeSettings}. */
+    @AutoValue.Builder
+    public abstract static class Builder {
+        public abstract Builder setDelegate(Delegate delegate);
+
+        public abstract ComputeSettings build();
+    }
+
+    public static Builder builder() {
+        return new AutoValue_ComputeSettings.Builder().setDelegate(DEFAULT_DELEGATE);
+    }
+
+    public abstract Delegate getDelegate();
+
+    private static final Delegate DEFAULT_DELEGATE = Delegate.NONE;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java
index 7dd1022..9d5b7754 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/TaskJniUtils.java
@@ -84,7 +84,7 @@
         tryLoadLibrary(libName);
         try {
             return provider.createHandle();
-        } catch (Exception e) {
+        } catch (RuntimeException e) {
             String errorMessage = "Error getting native address of native library: " + libName;
             Log.e(TAG, errorMessage, e);
             throw new IllegalStateException(errorMessage, e);
@@ -137,14 +137,12 @@
         }
     }
 
-    private TaskJniUtils() {}
-
     /**
-     * Try load a native library, if it's already loaded return directly.
+     * Try loading a native library, if it's already loaded return directly.
      *
      * @param libName name of the lib
      */
-    static void tryLoadLibrary(String libName) {
+    public static void tryLoadLibrary(String libName) {
         try {
             System.loadLibrary(libName);
         } catch (UnsatisfiedLinkError e) {
@@ -153,4 +151,22 @@
             throw new UnsatisfiedLinkError(errorMessage);
         }
     }
+
+    public static long createProtoBaseOptionsHandle(BaseOptions baseOptions) {
+        return createProtoBaseOptionsHandleWithLegacyNumThreads(
+                baseOptions, /*legacyNumThreads =*/-1);
+    }
+
+    public static long createProtoBaseOptionsHandleWithLegacyNumThreads(
+            BaseOptions baseOptions, int legacyNumThreads) {
+        // NumThreads should be configured through BaseOptions. However, if NumThreads is configured
+        // through the legacy API of the Task Java API (then it will not equal to -1, the default
+        // value), use it to overide the one in baseOptions.
+        return createProtoBaseOptions(baseOptions.getComputeSettings().getDelegate().getValue(),
+                legacyNumThreads == -1 ? baseOptions.getNumThreads() : legacyNumThreads);
+    }
+
+    private TaskJniUtils() {}
+
+    private static native long createProtoBaseOptions(int delegate, int numThreads);
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java
index 1107348..b1784d02 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core/vision/ImageProcessingOptions.java
@@ -41,7 +41,8 @@
  * expressed in the unrotated frame of reference coordinates system, i.e. in {@code [0,
  * TensorImage.getWidth()) x [0, TensorImage.getHeight())}, which are the dimensions of the
  * underlying image data before any orientation gets applied. If the region is out of these bounds,
- * the inference method, such as {@link ImageClassifier#classify}, will return error.
+ * the inference method, such as {@link
+ * org.tensorflow.lite.task.vision.classifier.ImageClassifier#classify}, will return error.
  */
 @AutoValue
 public abstract class ImageProcessingOptions {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/AndroidManifest.xml
index d4d1dbad..107e933 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/AndroidManifest.xml
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/AndroidManifest.xml
@@ -1,5 +1,5 @@
 <?xml version="1.0" encoding="utf-8"?>
 <manifest xmlns:android="http://schemas.android.com/apk/res/android"
     package="org.tensorflow.lite.task.text">
-  <uses-sdk android:minSdkVersion="19" android:targetSdkVersion="29"/>
+  <uses-sdk android:minSdkVersion="21" android:targetSdkVersion="29"/>
 </manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/BUILD
index 695e1bef..2d9837e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/BUILD
@@ -1,30 +1,34 @@
-load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
 exports_files(["AndroidManifest.xml"])
 
-android_library(
+android_library_with_tflite(
     name = "task_library_text",
     srcs = [
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier:nl_classifier_src",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa:bert_question_answerer_src",
     ],
-    javacopts = JAVACOPTS,
+    javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/text:task_text_native",
+    ],
     visibility = ["//visibility:public"],
+    # LINT.IfChange(dep)
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/text:task_text_native",
         "@com_google_auto_value",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@maven//:androidx_annotation_annotation",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
+    # LINT.ThenChange(<INTERNAL>/release/build_task_pom.sh:dep)
 )
 
 # AAR target for OSS release.
@@ -34,4 +38,10 @@
 aar_with_jni(
     name = "task-library-text",
     android_library = ":task_library_text",
+    headers = [
+        "//tensorflow_lite_support/c/task/text:bert_nl_classifier.h",
+        "//tensorflow_lite_support/c/task/text:nl_classifier.h",
+        "//tensorflow_lite_support/c/task/text:nl_classifier_common.h",
+        "//tensorflow_lite_support/c/task/text:bert_question_answerer.h",
+    ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BUILD
index a1d78d8..0079bfda9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BUILD
@@ -1,9 +1,9 @@
-load("@build_bazel_rules_android//android:rules.bzl", "android_library")
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
+load("@build_bazel_rules_android//android:rules.bzl", "android_library")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -12,6 +12,17 @@
     srcs = glob(["**/*.java"]),
 )
 
+# Default target that uses BuiltInOpResolver, registers all built-in OPs.
+android_library_with_tflite(
+    name = "nl_classifier",
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_native",
+    ],
+    exports = [
+        ":nl_classifier_java",
+    ],
+)
+
 # Java-only target, need to be used together with a native target similar to
 # third_party/tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_native.
 # Use this target when you want to provide a MutableOpResolver with customized
@@ -21,28 +32,13 @@
     srcs = [
         "NLClassifier.java",
     ],
-    javacopts = JAVACOPTS,
+    javacopts = ["-source 7 -target 7"],
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
         "@com_google_auto_value",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
-    ],
-)
-
-# Default target that uses BuiltInOpResolver, registers all built-in OPs.
-android_library(
-    name = "nl_classifier",
-    srcs = [
-        "NLClassifier.java",
-    ],
-    javacopts = JAVACOPTS,
-    deps = [
-        "//tensorflow_lite_support/java:tensorflowlite_support_java",
-        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_native",
-        "@com_google_auto_value",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@maven//:androidx_annotation_annotation",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
 )
 
@@ -56,16 +52,20 @@
 )
 
 # Default target that uses BuiltInOpResolver, registers all built-in OPs.
-android_library(
+android_library_with_tflite(
     name = "bert_nl_classifier",
     srcs = [
         "BertNLClassifier.java",
     ],
-    javacopts = JAVACOPTS,
+    javacopts = ["-source 7 -target 7"],
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert:bert_nl_classifier_native",
+    ],
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier:bert_nl_classifier_native",
+        "@com_google_auto_value",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java
index 74cb686..ce912c9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/BertNLClassifier.java
@@ -18,7 +18,11 @@
 import android.content.Context;
 import android.os.ParcelFileDescriptor;
 
+import com.google.auto.value.AutoValue;
+
+import org.tensorflow.lite.annotations.UsedByReflection;
 import org.tensorflow.lite.support.label.Category;
+import org.tensorflow.lite.task.core.BaseOptions;
 import org.tensorflow.lite.task.core.BaseTaskApi;
 import org.tensorflow.lite.task.core.TaskJniUtils;
 import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
@@ -46,6 +50,171 @@
 public class BertNLClassifier extends BaseTaskApi {
     private static final String BERT_NL_CLASSIFIER_NATIVE_LIBNAME = "task_text_jni";
 
+    /** Options to configure BertNLClassifier. */
+    @AutoValue
+    @UsedByReflection("bert_nl_classifier_jni.cc")
+    public abstract static class BertNLClassifierOptions {
+        static final int DEFAULT_MAX_SEQ_LEN = 128;
+
+        abstract int getMaxSeqLen();
+
+        abstract BaseOptions getBaseOptions();
+
+        public static Builder builder() {
+            return new AutoValue_BertNLClassifier_BertNLClassifierOptions.Builder()
+                    .setMaxSeqLen(DEFAULT_MAX_SEQ_LEN)
+                    .setBaseOptions(BaseOptions.builder().build());
+        }
+
+        /** Builder for {@link BertNLClassifierOptions}. */
+        @AutoValue.Builder
+        public abstract static class Builder {
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public abstract Builder setBaseOptions(BaseOptions baseOptions);
+
+            /**
+             * Set the maximum sequence length.
+             *
+             * @deprecated maximum sequence length is now read from the model (i.e. input tensor
+             *         size)
+             *     automatically
+             */
+            @Deprecated
+            public abstract Builder setMaxSeqLen(int value);
+
+            public abstract BertNLClassifierOptions build();
+        }
+    }
+
+    /**
+     * Creates {@link BertNLClassifier} from a model file with metadata and default {@link
+     * BertNLClassifierOptions}.
+     *
+     * @param context Android context
+     * @param modelPath Path to the classification model
+     * @return a {@link BertNLClassifier} instance
+     * @throws IOException If model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertNLClassifier createFromFile(final Context context, final String modelPath)
+            throws IOException {
+        return createFromBuffer(TaskJniUtils.loadMappedFile(context, modelPath));
+    }
+
+    /**
+     * Creates {@link BertNLClassifier} from a {@link File} object with metadata and default {@link
+     * BertNLClassifierOptions}.
+     *
+     * @param modelFile The classification model {@link File} instance
+     * @return a {@link BertNLClassifier} instance
+     * @throws IOException If model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertNLClassifier createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, BertNLClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates {@link BertNLClassifier} from a model file with metadata and {@link
+     * BertNLClassifierOptions}.
+     *
+     * @param context Android context.
+     * @param modelPath Path to the classification model
+     * @param options to configure the classifier
+     * @return a {@link BertNLClassifier} instance
+     * @throws IOException If model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertNLClassifier createFromFileAndOptions(final Context context,
+            final String modelPath, BertNLClassifierOptions options) throws IOException {
+        return createFromBufferAndOptions(TaskJniUtils.loadMappedFile(context, modelPath), options);
+    }
+
+    /**
+     * Creates {@link BertNLClassifier} from a {@link File} object with metadata and {@link
+     * BertNLClassifierOptions}.
+     *
+     * @param modelFile The classification model {@link File} instance
+     * @param options to configure the classifier
+     * @return a {@link BertNLClassifier} instance
+     * @throws IOException If model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertNLClassifier createFromFileAndOptions(
+            File modelFile, final BertNLClassifierOptions options) throws IOException {
+        try (ParcelFileDescriptor descriptor =
+                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+            return new BertNLClassifier(
+                    TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+                        @Override
+                        public long createHandle() {
+                            return initJniWithFileDescriptor(descriptor.getFd(), options,
+                                    TaskJniUtils.createProtoBaseOptionsHandle(
+                                            options.getBaseOptions()));
+                        }
+                    }, BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
+        }
+    }
+
+    /**
+     * Creates {@link BertNLClassifier} with a model buffer and default {@link
+     * BertNLClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the model
+     * @return a {@link BertNLClassifier} instance
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertNLClassifier createFromBuffer(final ByteBuffer modelBuffer) {
+        return createFromBufferAndOptions(modelBuffer, BertNLClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates {@link BertNLClassifier} with a model buffer and {@link BertNLClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the model
+     * @param options to configure the classifier
+     * @return a {@link BertNLClassifier} instance
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertNLClassifier createFromBufferAndOptions(
+            final ByteBuffer modelBuffer, final BertNLClassifierOptions options) {
+        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+            throw new IllegalArgumentException(
+                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
+        }
+        return new BertNLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                return initJniWithByteBuffer(modelBuffer, options,
+                        TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions()));
+            }
+        }, BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
+    }
+
+    /**
+     * Performs classification on a string input, returns classified {@link Category}s.
+     *
+     * @param text input text to the model.
+     * @return A list of Category results.
+     */
+    public List<Category> classify(String text) {
+        return classifyNative(getNativeHandle(), text);
+    }
+
     /**
      * Constructor to initialize the JNI with a pointer from C++.
      *
@@ -55,67 +224,11 @@
         super(nativeHandle);
     }
 
-    /**
-     * Create {@link BertNLClassifier} from a model file with metadata.
-     *
-     * @param context Android context
-     * @param pathToModel Path to the classification model.
-     * @return {@link BertNLClassifier} instance.
-     * @throws IOException If model file fails to load.
-     */
-    public static BertNLClassifier createFromFile(final Context context, final String pathToModel)
-            throws IOException {
-        return createFromBuffer(TaskJniUtils.loadMappedFile(context, pathToModel));
-    }
+    private static native long initJniWithByteBuffer(
+            ByteBuffer modelBuffer, BertNLClassifierOptions options, long baseOptionsHandle);
 
-    /**
-     * Create {@link BertNLClassifier} from a {@link File} object with metadata.
-     *
-     * @param modelFile The classification model {@link File} instance.
-     * @return {@link BertNLClassifier} instance.
-     * @throws IOException If model file fails to load.
-     */
-    public static BertNLClassifier createFromFile(File modelFile) throws IOException {
-        try (ParcelFileDescriptor descriptor =
-                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
-            return new BertNLClassifier(
-                    TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
-                        @Override
-                        public long createHandle() {
-                            return initJniWithFileDescriptor(descriptor.getFd());
-                        }
-                    }, BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
-        }
-    }
-
-    /**
-     * Create {@link BertNLClassifier} with {@link MappedByteBuffer}.
-     *
-     * @param modelBuffer In memory buffer of the model.
-     * @return {@link BertNLClassifier} instance.
-     */
-    public static BertNLClassifier createFromBuffer(final MappedByteBuffer modelBuffer) {
-        return new BertNLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
-            @Override
-            public long createHandle() {
-                return initJniWithByteBuffer(modelBuffer);
-            }
-        }, BERT_NL_CLASSIFIER_NATIVE_LIBNAME));
-    }
-
-    /**
-     * Perform classification on a string input, returns classified {@link Category}s.
-     *
-     * @param text input text to the model.
-     * @return A list of Category results.
-     */
-    public List<Category> classify(String text) {
-        return classifyNative(getNativeHandle(), text);
-    }
-
-    private static native long initJniWithByteBuffer(ByteBuffer modelBuffer);
-
-    private static native long initJniWithFileDescriptor(int fd);
+    private static native long initJniWithFileDescriptor(
+            int fd, BertNLClassifierOptions options, long baseOptionsHandle);
 
     private static native List<Category> classifyNative(long nativeHandle, String text);
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java
index 082b662..b8aa32be 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/nlclassifier/NLClassifier.java
@@ -18,10 +18,13 @@
 import android.content.Context;
 import android.os.ParcelFileDescriptor;
 
+import androidx.annotation.Nullable;
+
 import com.google.auto.value.AutoValue;
 
 import org.tensorflow.lite.annotations.UsedByReflection;
 import org.tensorflow.lite.support.label.Category;
+import org.tensorflow.lite.task.core.BaseOptions;
 import org.tensorflow.lite.task.core.BaseTaskApi;
 import org.tensorflow.lite.task.core.TaskJniUtils;
 import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
@@ -82,22 +85,25 @@
         private static final String DEFAULT_OUTPUT_LABEL_TENSOR_NAME = "OUTPUT_LABEL";
 
         @UsedByReflection("nl_classifier_jni.cc")
-        abstract int inputTensorIndex();
+        abstract int getInputTensorIndex();
 
         @UsedByReflection("nl_classifier_jni.cc")
-        abstract int outputScoreTensorIndex();
+        abstract int getOutputScoreTensorIndex();
 
         @UsedByReflection("nl_classifier_jni.cc")
-        abstract int outputLabelTensorIndex();
+        abstract int getOutputLabelTensorIndex();
 
         @UsedByReflection("nl_classifier_jni.cc")
-        abstract String inputTensorName();
+        abstract String getInputTensorName();
 
         @UsedByReflection("nl_classifier_jni.cc")
-        abstract String outputScoreTensorName();
+        abstract String getOutputScoreTensorName();
 
         @UsedByReflection("nl_classifier_jni.cc")
-        abstract String outputLabelTensorName();
+        abstract String getOutputLabelTensorName();
+
+        @Nullable
+        abstract BaseOptions getBaseOptions();
 
         public static Builder builder() {
             return new AutoValue_NLClassifier_NLClassifierOptions.Builder()
@@ -112,17 +118,101 @@
         /** Builder for {@link NLClassifierOptions}. */
         @AutoValue.Builder
         public abstract static class Builder {
-            public abstract Builder setInputTensorIndex(int value);
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public abstract Builder setBaseOptions(@Nullable BaseOptions baseOptions);
 
-            public abstract Builder setOutputScoreTensorIndex(int value);
+            /**
+             * Configure the input/output tensors for NLClassifier:
+             *
+             * <p>- No special configuration is needed if the model has only one input tensor and
+             * one output tensor.
+             *
+             * <p>- When the model has multiple input or output tensors, use the following
+             * configurations to specifiy the desired tensors: <br>
+             * -- tensor names: {@code inputTensorName}, {@code outputScoreTensorName}, {@code
+             * outputLabelTensorName}<br>
+             * -- tensor indices: {@code inputTensorIndex}, {@code outputScoreTensorIndex}, {@code
+             * outputLabelTensorIndex} <br>
+             * Tensor names has higher priorities than tensor indices in locating the tensors. It
+             * means the tensors will be first located according to tensor names. If not found, then
+             * the tensors will be located according to tensor indices.
+             *
+             * <p>- Failing to match the input text tensor or output score tensor with neither
+             * tensor names nor tensor indices will trigger a runtime error. However, failing to
+             * locate the output label tensor will not trigger an error because the label tensor is
+             * optional.
+             */
 
-            public abstract Builder setOutputLabelTensorIndex(int value);
+            /**
+             * Set the name of the input text tensor, if the model has multiple inputs. Only the
+             * input tensor specified will be used for inference; other input tensors will be
+             * ignored. Dafualt to {@code "INPUT"}.
+             *
+             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
+             * details.
+             */
+            public abstract Builder setInputTensorName(String inputTensorName);
 
-            public abstract Builder setInputTensorName(String value);
+            /**
+             * Set the name of the output score tensor, if the model has multiple outputs. Dafualt
+             * to
+             * {@code "OUTPUT_SCORE"}.
+             *
+             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
+             * details.
+             */
+            public abstract Builder setOutputScoreTensorName(String outputScoreTensorName);
 
-            public abstract Builder setOutputScoreTensorName(String value);
+            /**
+             * Set the name of the output label tensor, if the model has multiple outputs. Dafualt
+             * to
+             * {@code "OUTPUT_LABEL"}.
+             *
+             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
+             * details.
+             *
+             * <p>By default, label file should be packed with the output score tensor through Model
+             * Metadata. See the <a
+             * href="https://www.tensorflow.org/lite/convert/metadata_writer_tutorial#natural_language_classifiers">MetadataWriter
+             * for NLClassifier</a>. NLClassifier reads and parses labels from the label file
+             * automatically. However, some models may output a specific label tensor instead. In
+             * this case, NLClassifier reads labels from the output label tensor.
+             */
+            public abstract Builder setOutputLabelTensorName(String outputLabelTensorName);
 
-            public abstract Builder setOutputLabelTensorName(String value);
+            /**
+             * Set the index of the input text tensor among all input tensors, if the model has
+             * multiple inputs. Only the input tensor specified will be used for inference; other
+             * input tensors will be ignored. Dafualt to 0.
+             *
+             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
+             * details.
+             */
+            public abstract Builder setInputTensorIndex(int inputTensorIndex);
+
+            /**
+             * Set the index of the output score tensor among all output tensors, if the model has
+             * multiple outputs. Dafualt to 0.
+             *
+             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
+             * details.
+             */
+            public abstract Builder setOutputScoreTensorIndex(int outputScoreTensorIndex);
+
+            /**
+             * Set the index of the optional output label tensor among all output tensors, if the
+             * model has multiple outputs.
+             *
+             * <p>See the document above {@code outputLabelTensorName} for more information about
+             * what the output label tensor is.
+             *
+             * <p>See the section, Configure the input/output tensors for NLClassifier, for more
+             * details.
+             *
+             * <p>{@code outputLabelTensorIndex} dafualts to -1, meaning to disable the output label
+             * tensor.
+             */
+            public abstract Builder setOutputLabelTensorIndex(int outputLabelTensorIndex);
 
             public abstract NLClassifierOptions build();
         }
@@ -131,6 +221,121 @@
     private static final String NL_CLASSIFIER_NATIVE_LIBNAME = "task_text_jni";
 
     /**
+     * Creates {@link NLClassifier} from default {@link NLClassifierOptions}.
+     *
+     * @param context Android context
+     * @param modelPath path to the classification model relative to asset dir
+     * @return an {@link NLClassifier} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static NLClassifier createFromFile(Context context, String modelPath)
+            throws IOException {
+        return createFromFileAndOptions(context, modelPath, NLClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates {@link NLClassifier} from default {@link NLClassifierOptions}.
+     *
+     * @param modelFile the classification model {@link File} instance
+     * @return an {@link NLClassifier} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static NLClassifier createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, NLClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates {@link NLClassifier} from {@link NLClassifierOptions}.
+     *
+     * @param context Android context
+     * @param modelPath path to the classification model relative to asset dir
+     * @param options configurations for the model.
+     * @return an {@link NLClassifier} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static NLClassifier createFromFileAndOptions(
+            Context context, String modelPath, NLClassifierOptions options) throws IOException {
+        return createFromBufferAndOptions(TaskJniUtils.loadMappedFile(context, modelPath), options);
+    }
+
+    /**
+     * Creates {@link NLClassifier} from {@link NLClassifierOptions}.
+     *
+     * @param modelFile the classification model {@link File} instance
+     * @param options configurations for the model
+     * @return an {@link NLClassifier} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static NLClassifier createFromFileAndOptions(
+            File modelFile, final NLClassifierOptions options) throws IOException {
+        try (ParcelFileDescriptor descriptor =
+                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+            return new NLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+                @Override
+                public long createHandle() {
+                    long baseOptionsHandle = options.getBaseOptions() == null
+                            ? 0 // pass an invalid native handle
+                            : TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions());
+                    return initJniWithFileDescriptor(
+                            options, descriptor.getFd(), baseOptionsHandle);
+                }
+            }, NL_CLASSIFIER_NATIVE_LIBNAME));
+        }
+    }
+
+    /**
+     * Creates {@link NLClassifier} with a model {@link ByteBuffer} and {@link NLClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     classification model
+     * @param options configurations for the model
+     * @return {@link NLClassifier} instance
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     */
+    public static NLClassifier createFromBufferAndOptions(
+            final ByteBuffer modelBuffer, final NLClassifierOptions options) {
+        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+            throw new IllegalArgumentException(
+                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
+        }
+
+        return new NLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                long baseOptionsHandle = options.getBaseOptions() == null
+                        ? 0 // pass an invalid native handle
+                        : TaskJniUtils.createProtoBaseOptionsHandle(options.getBaseOptions());
+                return initJniWithByteBuffer(options, modelBuffer, baseOptionsHandle);
+            }
+        }, NL_CLASSIFIER_NATIVE_LIBNAME));
+    }
+
+    /**
+     * Performs classification on a string input, returns classified {@link Category}s.
+     *
+     * @param text input text to the model
+     * @return a list of Category results
+     */
+    public List<Category> classify(String text) {
+        return classifyNative(getNativeHandle(), text);
+    }
+
+    /**
      * Constructor to initialize the JNI with a pointer from C++.
      *
      * @param nativeHandle a pointer referencing memory allocated in C++.
@@ -139,106 +344,19 @@
         super(nativeHandle);
     }
 
-    /**
-     * Create {@link NLClassifier} from default {@link NLClassifierOptions}.
-     *
-     * @param context Android context.
-     * @param pathToModel Path to the classification model relative to asset dir.
-     * @return {@link NLClassifier} instance.
-     * @throws IOException If model file fails to load.
-     */
-    public static NLClassifier createFromFile(Context context, String pathToModel)
-            throws IOException {
-        return createFromFileAndOptions(
-                context, pathToModel, NLClassifierOptions.builder().build());
-    }
-
-    /**
-     * Create {@link NLClassifier} from default {@link NLClassifierOptions}.
-     *
-     * @param modelFile The classification model {@link File} instance.
-     * @return {@link NLClassifier} instance.
-     * @throws IOException If model file fails to load.
-     */
-    public static NLClassifier createFromFile(File modelFile) throws IOException {
-        return createFromFileAndOptions(modelFile, NLClassifierOptions.builder().build());
-    }
-
-    /**
-     * Create {@link NLClassifier} from {@link NLClassifierOptions}.
-     *
-     * @param context Android context
-     * @param pathToModel Path to the classification model relative to asset dir.
-     * @param options Configurations for the model.
-     * @return {@link NLClassifier} instance.
-     * @throws IOException If model file fails to load.
-     */
-    public static NLClassifier createFromFileAndOptions(
-            Context context, String pathToModel, NLClassifierOptions options) throws IOException {
-        return createFromBufferAndOptions(
-                TaskJniUtils.loadMappedFile(context, pathToModel), options);
-    }
-
-    /**
-     * Create {@link NLClassifier} from {@link NLClassifierOptions}.
-     *
-     * @param modelFile The classification model {@link File} instance.
-     * @param options Configurations for the model.
-     * @return {@link NLClassifier} instance.
-     * @throws IOException If model file fails to load.
-     */
-    public static NLClassifier createFromFileAndOptions(
-            File modelFile, final NLClassifierOptions options) throws IOException {
-        try (ParcelFileDescriptor descriptor =
-                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
-            return new NLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
-                @Override
-                public long createHandle() {
-                    return initJniWithFileDescriptor(options, descriptor.getFd());
-                }
-            }, NL_CLASSIFIER_NATIVE_LIBNAME));
-        }
-    }
-
-    /**
-     * Create {@link NLClassifier} with {@link MappedByteBuffer} from {@link NLClassifierOptions}.
-     *
-     * @param modelBuffer In memory buffer of the classification model.
-     * @param options Configurations for the model.
-     * @return {@link NLClassifier} instance.
-     */
-    public static NLClassifier createFromBufferAndOptions(
-            final ByteBuffer modelBuffer, final NLClassifierOptions options) {
-        return new NLClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
-            @Override
-            public long createHandle() {
-                return initJniWithByteBuffer(options, modelBuffer);
-            }
-        }, NL_CLASSIFIER_NATIVE_LIBNAME));
-    }
-
-    /**
-     * Perform classification on a string input, returns classified {@link Category}s.
-     *
-     * @param text input text to the model.
-     * @return A list of Category results.
-     */
-    public List<Category> classify(String text) {
-        return classifyNative(getNativeHandle(), text);
-    }
-
-    private static native long initJniWithByteBuffer(
-            NLClassifierOptions options, ByteBuffer modelBuffer);
-
-    private static native long initJniWithFileDescriptor(NLClassifierOptions options, int fd);
-
-    private static native List<Category> classifyNative(long nativeHandle, String text);
-
     @Override
     protected void deinit(long nativeHandle) {
         deinitJni(nativeHandle);
     }
 
+    private static native long initJniWithByteBuffer(
+            NLClassifierOptions options, ByteBuffer modelBuffer, long baseOptionsHandle);
+
+    private static native long initJniWithFileDescriptor(
+            NLClassifierOptions options, int fd, long baseOptionsHandle);
+
+    private static native List<Category> classifyNative(long nativeHandle, String text);
+
     /**
      * Native implementation to release memory pointed by the pointer.
      *
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BUILD
index 3dad142..0d35eb8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BUILD
@@ -1,9 +1,9 @@
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
-load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
+load("@build_bazel_rules_android//android:rules.bzl", "android_library")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -12,14 +12,29 @@
     srcs = glob(["**/*.java"]),
 )
 
-android_library(
+# Default target that uses BuiltInOpResolver, registers all built-in OPs.
+android_library_with_tflite(
     name = "bert_question_answerer",
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/text/qa:bert_question_answerer_native",
+    ],
+    exports = [
+        ":bert_question_answerer_java",
+    ],
+)
+
+# Java-only target, need to be used together with a native target similar to
+# //third_party/tensorflow_lite_support/java/src/native/task/text/qa:bert_question_answerer_native.
+# Use this target when you want to provide a MutableOpResolver with customized
+# OPs and/or a subset of BuiltInOps to reduce binary size.
+android_library(
+    name = "bert_question_answerer_java",
     srcs = glob(["*.java"]),
-    javacopts = JAVACOPTS,
+    javacopts = ["-source 7 -target 7"],
     deps = [
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/text/qa:bert_question_answerer_native",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@com_google_auto_value",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java
index fb91562..39648d9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text/qa/BertQuestionAnswerer.java
@@ -18,9 +18,13 @@
 import android.content.Context;
 import android.os.ParcelFileDescriptor;
 
+import com.google.auto.value.AutoValue;
+
+import org.tensorflow.lite.task.core.BaseOptions;
 import org.tensorflow.lite.task.core.BaseTaskApi;
 import org.tensorflow.lite.task.core.TaskJniUtils;
 import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
+import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
 import org.tensorflow.lite.task.core.TaskJniUtils.MultipleBuffersHandleProvider;
 
 import java.io.File;
@@ -28,122 +32,186 @@
 import java.nio.ByteBuffer;
 import java.util.List;
 
-/** Task API for BertQA models. */
+/**
+ * Returns the most possible answers on a given question for QA models (BERT, Albert, etc.).
+ *
+ * <p>The API expects a Bert based TFLite model with metadata containing the following information:
+ *
+ * <ul>
+ *   <li>input_process_units for Wordpiece/Sentencepiece Tokenizer - Wordpiece Tokenizer can be used
+ *       for a <a
+ *       href="https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1">MobileBert</a> model,
+ *       Sentencepiece Tokenizer Tokenizer can be used for an <a
+ *       href="https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1">Albert</a> model.
+ *   <li>3 input tensors with names "ids", "mask" and "segment_ids".
+ *   <li>2 output tensors with names "end_logits" and "start_logits".
+ * </ul>
+ */
 public class BertQuestionAnswerer extends BaseTaskApi implements QuestionAnswerer {
     private static final String BERT_QUESTION_ANSWERER_NATIVE_LIBNAME = "task_text_jni";
-
-    private BertQuestionAnswerer(long nativeHandle) {
-        super(nativeHandle);
-    }
+    private static final int OPTIONAL_FD_LENGTH = -1;
+    private static final int OPTIONAL_FD_OFFSET = -1;
 
     /**
-     * Generic API to create the QuestionAnswerer for bert models with metadata populated. The API
-     * expects a Bert based TFLite model with metadata containing the following information:
-     *
-     * <ul>
-     *   <li>input_process_units for Wordpiece/Sentencepiece Tokenizer - Wordpiece Tokenizer can be
-     *       used for a <a
-     *       href="https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1">MobileBert</a>
-     *       model, Sentencepiece Tokenizer Tokenizer can be used for an <a
-     *       href="https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1">Albert</a>
-     *       model.
-     *   <li>3 input tensors with names "ids", "mask" and "segment_ids".
-     *   <li>2 output tensors with names "end_logits" and "start_logits".
-     * </ul>
+     * Creates a {@link BertQuestionAnswerer} instance from the default {@link
+     * BertQuestionAnswererOptions}.
      *
      * @param context android context
-     * @param pathToModel file path to the model with metadata. Note: The model should not be
-     *     compressed
-     * @return {@link BertQuestionAnswerer} instance
-     * @throws IOException If model file fails to load.
+     * @param modelPath file path to the model with metadata. Note: The model should not be
+     *         compressed
+     * @return a {@link BertQuestionAnswerer} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
-    public static BertQuestionAnswerer createFromFile(Context context, String pathToModel)
+    public static BertQuestionAnswerer createFromFile(Context context, String modelPath)
             throws IOException {
-        return new BertQuestionAnswerer(TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
-                context, new MultipleBuffersHandleProvider() {
-                    @Override
-                    public long createHandle(ByteBuffer... buffers) {
-                        return BertQuestionAnswerer.initJniWithModelWithMetadataByteBuffers(
-                                buffers);
-                    }
-                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, pathToModel));
+        return createFromFileAndOptions(
+                context, modelPath, BertQuestionAnswererOptions.builder().build());
     }
 
     /**
-     * Generic API to create the QuestionAnswerer for bert models with metadata populated. The API
-     * expects a Bert based TFLite model with metadata containing the following information:
+     * Creates a {@link BertQuestionAnswerer} instance from the default {@link
+     * BertQuestionAnswererOptions}.
      *
-     * <ul>
-     *   <li>input_process_units for Wordpiece/Sentencepiece Tokenizer - Wordpiece Tokenizer can be
-     *       used for a <a
-     *       href="https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1">MobileBert</a>
-     *       model, Sentencepiece Tokenizer Tokenizer can be used for an <a
-     *       href="https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1">Albert</a>
-     *       model.
-     *   <li>3 input tensors with names "ids", "mask" and "segment_ids".
-     *   <li>2 output tensors with names "end_logits" and "start_logits".
-     * </ul>
-     *
-     * @param modelFile {@link File} object of the model
-     * @return {@link BertQuestionAnswerer} instance
-     * @throws IOException If model file fails to load.
+     * @param modelFile a {@link File} object of the model
+     * @return a {@link BertQuestionAnswerer} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static BertQuestionAnswerer createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, BertQuestionAnswererOptions.builder().build());
+    }
+
+    /**
+     * Creates a {@link BertQuestionAnswerer} instance from {@link BertQuestionAnswererOptions}.
+     *
+     * @param context android context
+     * @param modelPath file path to the model with metadata. Note: The model should not be
+     *         compressed
+     * @return a {@link BertQuestionAnswerer} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertQuestionAnswerer createFromFileAndOptions(Context context, String modelPath,
+            BertQuestionAnswererOptions options) throws IOException {
+        return new BertQuestionAnswerer(TaskJniUtils.createHandleFromFdAndOptions(
+                context, new FdAndOptionsHandleProvider<BertQuestionAnswererOptions>() {
+                    @Override
+                    public long createHandle(int fileDescriptor, long fileDescriptorLength,
+                            long fileDescriptorOffset, BertQuestionAnswererOptions options) {
+                        return initJniWithFileDescriptor(fileDescriptor, fileDescriptorLength,
+                                fileDescriptorOffset,
+                                TaskJniUtils.createProtoBaseOptionsHandle(
+                                        options.getBaseOptions()));
+                    }
+                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, modelPath, options));
+    }
+
+    /**
+     * Creates a {@link BertQuestionAnswerer} instance from {@link BertQuestionAnswererOptions}.
+     *
+     * @param modelFile a {@link File} object of the model
+     * @return a {@link BertQuestionAnswerer} instance
+     * @throws IOException if model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static BertQuestionAnswerer createFromFileAndOptions(
+            File modelFile, final BertQuestionAnswererOptions options) throws IOException {
         try (ParcelFileDescriptor descriptor =
                         ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
             return new BertQuestionAnswerer(
                     TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
                         @Override
                         public long createHandle() {
-                            return initJniWithFileDescriptor(descriptor.getFd());
+                            return initJniWithFileDescriptor(
+                                    /*fileDescriptor=*/descriptor.getFd(),
+                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
+                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET,
+                                    TaskJniUtils.createProtoBaseOptionsHandle(
+                                            options.getBaseOptions()));
                         }
                     }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME));
         }
     }
 
     /**
-     * Creates the API instance with a bert model and vocabulary file.
+     * Creates a {@link BertQuestionAnswerer} instance with a Bert model and a vocabulary file.
      *
      * <p>One suitable model is: https://tfhub.dev/tensorflow/lite-model/mobilebert/1/default/1
      *
      * @param context android context
-     * @param pathToModel file path to the bert model. Note: The model should not be compressed
-     * @param pathToVocab file path to the vocabulary file. Note: The file should not be compressed
-     * @return {@link BertQuestionAnswerer} instance
-     * @throws IOException If model file fails to load.
+     * @param modelPath file path to the Bert model. Note: The model should not be compressed
+     * @param vocabPath file path to the vocabulary file. Note: The file should not be compressed
+     * @return a {@link BertQuestionAnswerer} instance
+     * @throws IOException If model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static BertQuestionAnswerer createBertQuestionAnswererFromFile(
-            Context context, String pathToModel, String pathToVocab) throws IOException {
+            Context context, String modelPath, String vocabPath) throws IOException {
         return new BertQuestionAnswerer(TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
                 context, new MultipleBuffersHandleProvider() {
                     @Override
                     public long createHandle(ByteBuffer... buffers) {
-                        return BertQuestionAnswerer.initJniWithBertByteBuffers(buffers);
+                        return initJniWithBertByteBuffers(buffers);
                     }
-                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, pathToModel, pathToVocab));
+                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, modelPath, vocabPath));
     }
 
     /**
-     * Creates the API instance with an albert model and sentence piece model file.
+     * Creates a {@link BertQuestionAnswerer} instance with an Albert model and a sentence piece
+     * model file.
      *
      * <p>One suitable model is: https://tfhub.dev/tensorflow/lite-model/albert_lite_base/squadv1/1
      *
      * @param context android context
-     * @param pathToModel file path to the albert model. Note: The model should not be compressed
-     * @param pathToSentencePieceModel file path to the sentence piece model file. Note: The model
+     * @param modelPath file path to the Albert model. Note: The model should not be compressed
+     * @param sentencePieceModelPath file path to the sentence piece model file. Note: The model
      *     should not be compressed
-     * @return {@link BertQuestionAnswerer} instance
-     * @throws IOException If model file fails to load.
+     * @return a {@link BertQuestionAnswerer} instance
+     * @throws IOException If model file fails to load
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
-    public static BertQuestionAnswerer createAlbertQuestionAnswererFromFile(Context context,
-            String pathToModel, String pathToSentencePieceModel) throws IOException {
+    public static BertQuestionAnswerer createAlbertQuestionAnswererFromFile(
+            Context context, String modelPath, String sentencePieceModelPath) throws IOException {
         return new BertQuestionAnswerer(TaskJniUtils.createHandleWithMultipleAssetFilesFromLibrary(
                 context, new MultipleBuffersHandleProvider() {
                     @Override
                     public long createHandle(ByteBuffer... buffers) {
-                        return BertQuestionAnswerer.initJniWithAlbertByteBuffers(buffers);
+                        return initJniWithAlbertByteBuffers(buffers);
                     }
-                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, pathToModel, pathToSentencePieceModel));
+                }, BERT_QUESTION_ANSWERER_NATIVE_LIBNAME, modelPath, sentencePieceModelPath));
+    }
+
+    /** Options for setting up a {@link BertQuestionAnswerer}. */
+    @AutoValue
+    public abstract static class BertQuestionAnswererOptions {
+        abstract BaseOptions getBaseOptions();
+
+        public static Builder builder() {
+            return new AutoValue_BertQuestionAnswerer_BertQuestionAnswererOptions.Builder()
+                    .setBaseOptions(BaseOptions.builder().build());
+        }
+
+        /** Builder for {@link BertQuestionAnswererOptions}. */
+        @AutoValue.Builder
+        public abstract static class Builder {
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public abstract Builder setBaseOptions(BaseOptions baseOptions);
+
+            public abstract BertQuestionAnswererOptions build();
+        }
     }
 
     @Override
@@ -152,6 +220,10 @@
         return answerNative(getNativeHandle(), context, question);
     }
 
+    private BertQuestionAnswerer(long nativeHandle) {
+        super(nativeHandle);
+    }
+
     // modelBuffers[0] is tflite model file buffer, and modelBuffers[1] is vocab file buffer.
     private static native long initJniWithBertByteBuffers(ByteBuffer... modelBuffers);
 
@@ -159,10 +231,8 @@
     // buffer.
     private static native long initJniWithAlbertByteBuffers(ByteBuffer... modelBuffers);
 
-    // modelBuffers[0] is tflite model file buffer with metadata to specify which tokenizer to use.
-    private static native long initJniWithModelWithMetadataByteBuffers(ByteBuffer... modelBuffers);
-
-    private static native long initJniWithFileDescriptor(int fd);
+    private static native long initJniWithFileDescriptor(int fileDescriptor,
+            long fileDescriptorLength, long fileDescriptorOffset, long baseOptionsHandle);
 
     private static native List<QaAnswer> answerNative(
             long nativeHandle, String context, String question);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/AndroidManifest.xml
index e77a0734..f331580 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/AndroidManifest.xml
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/AndroidManifest.xml
@@ -1,5 +1,5 @@
 <?xml version="1.0" encoding="utf-8"?>
 <manifest xmlns:android="http://schemas.android.com/apk/res/android"
     package="org.tensorflow.lite.task.vision">
-  <uses-sdk android:minSdkVersion="19" android:targetSdkVersion="29"/>
+  <uses-sdk android:minSdkVersion="21" android:targetSdkVersion="29"/>
 </manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/BUILD
index 661a766..70657c1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/BUILD
@@ -1,8 +1,8 @@
-load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -10,25 +10,30 @@
     "AndroidManifest.xml",
 ])
 
-android_library(
+android_library_with_tflite(
     name = "task_library_vision",
     srcs = [
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier:image_classifier_src",
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core:base_vision_api_src",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector:object_detector_src",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter:image_segmenter_src",
     ],
-    # TODO(b/163039980): Use JAVACOPTS in TF. "-Xep:RemoveUnusedImports:ERROR" wierdly break the build.
     javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/vision:task_vision_native",
+    ],
     visibility = ["//visibility:public"],
+    # LINT.IfChange(dep)
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/vision:task_vision_native",
         "@com_google_auto_value",
         "@maven//:androidx_annotation_annotation",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@maven//:com_google_android_odml_image",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
+    # LINT.ThenChange(<INTERNAL>/release/build_task_pom.sh:dep)
 )
 
 # AAR target for OSS release.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/AndroidManifest.xml
index ce07182..c0033ce 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/AndroidManifest.xml
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/AndroidManifest.xml
@@ -1,5 +1,5 @@
 <?xml version="1.0" encoding="utf-8"?>
 <manifest xmlns:android="http://schemas.android.com/apk/res/android"
     package="org.tensorflow.lite.task.vision.classifier">
-  <uses-sdk android:minSdkVersion="19" android:targetSdkVersion="29"/>
+  <uses-sdk android:minSdkVersion="21" android:targetSdkVersion="29"/>
 </manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/BUILD
index c6a70a0..a4d48cda 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/BUILD
@@ -1,9 +1,9 @@
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -13,20 +13,44 @@
 
 filegroup(
     name = "image_classifier_src",
-    srcs = glob(["**/*.java"]),
+    srcs = glob(
+        ["**/*.java"],
+    ),
 )
 
-android_library(
+# Default target that uses BuiltInOpResolver, registers all built-in OPs.
+# IMPORTANT: In order to use hardware acceleration delegates, you must
+# additionally link to the appropriate delegate plugin target as follows:
+# 1. GPU delegate plugin: tensorflow_lite_support/acceleration/configuration:gpu_delegate_plugin_android
+# 2. NNAPI delegate plugin: included in this target.
+android_library_with_tflite(
     name = "image_classifier",
-    srcs = glob(["*.java"]),
-    javacopts = JAVACOPTS,
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/vision/classifier:image_classifier_native",
+    ],
+    exports = [
+        ":image_classifier_java",
+    ],
+)
+
+# Java-only target, needs to be used together with a native target similar to
+# tensorflow_lite_support/java/src/native/task/vision/classifier:image_classifier_native.
+# Use this target when you want to provide a MutableOpResolver with customized
+# OPs and/or a subset of BuiltInOps to reduce binary size.
+android_library(
+    name = "image_classifier_java",
+    srcs = [
+        ":image_classifier_src",
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core:base_vision_api_src",
+    ],
+    javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/vision/classifier:image_classifier_native",
         "@com_google_auto_value",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@maven//:com_google_android_odml_image",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java
index c1007c11..48038f6 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/classifier/ImageClassifier.java
@@ -17,17 +17,25 @@
 
 import android.content.Context;
 import android.graphics.Rect;
+import android.os.ParcelFileDescriptor;
 
-import org.tensorflow.lite.DataType;
+import com.google.android.odml.image.MlImage;
+
 import org.tensorflow.lite.annotations.UsedByReflection;
+import org.tensorflow.lite.support.image.MlImageAdapter;
 import org.tensorflow.lite.support.image.TensorImage;
-import org.tensorflow.lite.task.core.BaseTaskApi;
+import org.tensorflow.lite.task.core.BaseOptions;
 import org.tensorflow.lite.task.core.TaskJniUtils;
+import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
 import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
 import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
+import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi.InferenceProvider;
 
+import java.io.File;
 import java.io.IOException;
 import java.nio.ByteBuffer;
+import java.nio.MappedByteBuffer;
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.List;
@@ -54,6 +62,10 @@
  *       <ul>
  *         <li>with {@code N} classes of either 2 or 4 dimensions, such as {@code [1 x N]} or {@code
  *             [1 x 1 x 1 x N]}
+ *         <li>the label file is required to be packed to the metadata. See the <a
+ *             href="https://www.tensorflow.org/lite/convert/metadata#label_output">example of
+ *             creating metadata for an image classifier</a>. If no label files are packed, it will
+ *             use index as label in the result.
  *       </ul>
  * </ul>
  *
@@ -61,16 +73,19 @@
  * href="https://tfhub.dev/bohemian-visual-recognition-alliance/lite-model/models/mushroom-identification_v1/1">TensorFlow
  * Hub.</a>.
  */
-public final class ImageClassifier extends BaseTaskApi {
+public final class ImageClassifier extends BaseVisionTaskApi {
     private static final String IMAGE_CLASSIFIER_NATIVE_LIB = "task_vision_jni";
+    private static final int OPTIONAL_FD_LENGTH = -1;
+    private static final int OPTIONAL_FD_OFFSET = -1;
 
     /**
      * Creates an {@link ImageClassifier} instance from the default {@link ImageClassifierOptions}.
      *
      * @param modelPath path of the classification model with metadata in the assets
      * @throws IOException if an I/O error occurs when loading the tflite model
-     * @throws AssertionError if error occurs when creating {@link ImageClassifier} from the native
-     *     code
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static ImageClassifier createFromFile(Context context, String modelPath)
             throws IOException {
@@ -79,12 +94,41 @@
     }
 
     /**
+     * Creates an {@link ImageClassifier} instance from the default {@link ImageClassifierOptions}.
+     *
+     * @param modelFile the classification model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ImageClassifier createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, ImageClassifierOptions.builder().build());
+    }
+
+    /**
+     * Creates an {@link ImageClassifier} instance with a model buffer and the default {@link
+     * ImageClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     classification model
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ImageClassifier createFromBuffer(final ByteBuffer modelBuffer) {
+        return createFromBufferAndOptions(modelBuffer, ImageClassifierOptions.builder().build());
+    }
+
+    /**
      * Creates an {@link ImageClassifier} instance from {@link ImageClassifierOptions}.
      *
      * @param modelPath path of the classification model with metadata in the assets
      * @throws IOException if an I/O error occurs when loading the tflite model
-     * @throws AssertionError if error occurs when creating {@link ImageClassifier} from the native
-     *     code
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static ImageClassifier createFromFileAndOptions(
             Context context, String modelPath, ImageClassifierOptions options) throws IOException {
@@ -94,17 +138,73 @@
                     public long createHandle(int fileDescriptor, long fileDescriptorLength,
                             long fileDescriptorOffset, ImageClassifierOptions options) {
                         return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
-                                fileDescriptorOffset, options);
+                                fileDescriptorOffset, options,
+                                TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                        options.getBaseOptions(), options.getNumThreads()));
                     }
                 }, IMAGE_CLASSIFIER_NATIVE_LIB, modelPath, options));
     }
 
     /**
+     * Creates an {@link ImageClassifier} instance.
+     *
+     * @param modelFile the classification model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ImageClassifier createFromFileAndOptions(
+            File modelFile, final ImageClassifierOptions options) throws IOException {
+        try (ParcelFileDescriptor descriptor =
+                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+            return new ImageClassifier(
+                    TaskJniUtils.createHandleFromLibrary(new TaskJniUtils.EmptyHandleProvider() {
+                        @Override
+                        public long createHandle() {
+                            return initJniWithModelFdAndOptions(descriptor.getFd(),
+                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
+                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options,
+                                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                            options.getBaseOptions(), options.getNumThreads()));
+                        }
+                    }, IMAGE_CLASSIFIER_NATIVE_LIB));
+        }
+    }
+
+    /**
+     * Creates an {@link ImageClassifier} instance with a model buffer and {@link
+     * ImageClassifierOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     classification model
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ImageClassifier createFromBufferAndOptions(
+            final ByteBuffer modelBuffer, final ImageClassifierOptions options) {
+        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+            throw new IllegalArgumentException(
+                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
+        }
+        return new ImageClassifier(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                return initJniWithByteBuffer(modelBuffer, options,
+                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                options.getBaseOptions(), options.getNumThreads()));
+            }
+        }, IMAGE_CLASSIFIER_NATIVE_LIB));
+    }
+
+    /**
      * Constructor to initialize the JNI with a pointer from C++.
      *
      * @param nativeHandle a pointer referencing memory allocated in C++
      */
-    private ImageClassifier(long nativeHandle) {
+    ImageClassifier(long nativeHandle) {
         super(nativeHandle);
     }
 
@@ -117,6 +217,7 @@
         // 1. java.util.Optional require Java 8 while we need to support Java 7.
         // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See
         // the comments for labelAllowList.
+        private final BaseOptions baseOptions;
         private final String displayNamesLocale;
         private final int maxResults;
         private final float scoreThreshold;
@@ -128,6 +229,7 @@
         // vulnerable.
         private final List<String> labelAllowList;
         private final List<String> labelDenyList;
+        private final int numThreads;
 
         public static Builder builder() {
             return new Builder();
@@ -135,14 +237,22 @@
 
         /** A builder that helps to configure an instance of ImageClassifierOptions. */
         public static class Builder {
+            private BaseOptions baseOptions = BaseOptions.builder().build();
             private String displayNamesLocale = "en";
             private int maxResults = -1;
             private float scoreThreshold;
             private boolean isScoreThresholdSet = false;
             private List<String> labelAllowList = new ArrayList<>();
             private List<String> labelDenyList = new ArrayList<>();
+            private int numThreads = -1;
 
-            private Builder() {}
+            Builder() {}
+
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public Builder setBaseOptions(BaseOptions baseOptions) {
+                this.baseOptions = baseOptions;
+                return this;
+            }
 
             /**
              * Sets the locale to use for display names specified through the TFLite Model Metadata,
@@ -174,7 +284,7 @@
             }
 
             /**
-             * Sets the score threshold in [0,1).
+             * Sets the score threshold.
              *
              * <p>It overrides the one provided in the model metadata (if any). Results below this
              * value are rejected.
@@ -207,6 +317,23 @@
                 return this;
             }
 
+            /**
+             * Sets the number of threads to be used for TFLite ops that support multi-threading
+             * when running inference with CPU. Defaults to -1.
+             *
+             * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has
+             * the effect to let TFLite runtime set the value.
+             *
+             * @deprecated use {@link BaseOptions} to configure number of threads instead. This
+             *         method
+             *     will override the number of threads configured from {@link BaseOptions}.
+             */
+            @Deprecated
+            public Builder setNumThreads(int numThreads) {
+                this.numThreads = numThreads;
+                return this;
+            }
+
             public ImageClassifierOptions build() {
                 return new ImageClassifierOptions(this);
             }
@@ -242,71 +369,144 @@
             return new ArrayList<>(labelDenyList);
         }
 
-        private ImageClassifierOptions(Builder builder) {
+        @UsedByReflection("image_classifier_jni.cc")
+        public int getNumThreads() {
+            return numThreads;
+        }
+
+        public BaseOptions getBaseOptions() {
+            return baseOptions;
+        }
+
+        ImageClassifierOptions(Builder builder) {
             displayNamesLocale = builder.displayNamesLocale;
             maxResults = builder.maxResults;
             scoreThreshold = builder.scoreThreshold;
             isScoreThresholdSet = builder.isScoreThresholdSet;
             labelAllowList = builder.labelAllowList;
             labelDenyList = builder.labelDenyList;
+            numThreads = builder.numThreads;
+            baseOptions = builder.baseOptions;
         }
     }
 
     /**
-     * Performs actual classification on the provided image.
+     * Performs actual classification on the provided {@link TensorImage}.
      *
-     * @param image a {@link TensorImage} object that represents an RGB image
-     * @throws AssertionError if error occurs when classifying the image from the native code
+     * <p>{@link ImageClassifier} supports the following {@link TensorImage} color space types:
+     *
+     * <ul>
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+     * </ul>
+     *
+     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+     * @throws IllegalArgumentException if the color space type of image is unsupported
      */
     public List<Classifications> classify(TensorImage image) {
         return classify(image, ImageProcessingOptions.builder().build());
     }
 
     /**
-     * Performs actual classification on the provided image with {@link ImageProcessingOptions}.
+     * Performs actual classification on the provided {@link TensorImage} with {@link
+     * ImageProcessingOptions}.
      *
      * <p>{@link ImageClassifier} supports the following options:
      *
      * <ul>
-     *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions#Builder#setRoi}). It
+     *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions.Builder#setRoi}). It
      *       defaults to the entire image.
-     *   <li>image rotation (through {@link ImageProcessingOptions#Builder#setOrientation}). It
-     *       defaults to {@link ImageProcessingOptions#Orientation#TOP_LEFT}.
+     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}.
      * </ul>
      *
-     * @param image a {@link TensorImage} object that represents an RGB image
-     * @throws AssertionError if error occurs when classifying the image from the native code
+     * <p>{@link ImageClassifier} supports the following {@link TensorImage} color space types:
+     *
+     * <ul>
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+     * </ul>
+     *
+     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+     * @throws IllegalArgumentException if the color space type of image is unsupported
      */
     public List<Classifications> classify(TensorImage image, ImageProcessingOptions options) {
+        return run(new InferenceProvider<List<Classifications>>() {
+            @Override
+            public List<Classifications> run(
+                    long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+                return classify(frameBufferHandle, width, height, options);
+            }
+        }, image, options);
+    }
+
+    /**
+     * Performs actual classification on the provided {@code MlImage}.
+     *
+     * @param image an {@code MlImage} object that represents an image
+     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+     */
+    public List<Classifications> classify(MlImage image) {
+        return classify(image, ImageProcessingOptions.builder().build());
+    }
+
+    /**
+     * Performs actual classification on the provided {@code MlImage} with {@link
+     * ImageProcessingOptions}.
+     *
+     * <p>{@link ImageClassifier} supports the following options:
+     *
+     * <ul>
+     *   <li>Region of interest (ROI) (through {@link ImageProcessingOptions.Builder#setRoi}). It
+     *       defaults to the entire image.
+     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
+     *       MlImage#getRotation()} is not effective.
+     * </ul>
+     *
+     * @param image a {@code MlImage} object that represents an image
+     * @param options configures options including ROI and rotation
+     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+     */
+    public List<Classifications> classify(MlImage image, ImageProcessingOptions options) {
+        image.getInternal().acquire();
+        TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+        List<Classifications> result = classify(tensorImage, options);
+        image.close();
+        return result;
+    }
+
+    private List<Classifications> classify(
+            long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
         checkNotClosed();
 
-        // image_classifier_jni.cc expects an uint8 image. Convert image of other types into uint8.
-        TensorImage imageUint8 = image.getDataType() == DataType.UINT8
-                ? image
-                : TensorImage.createFrom(image, DataType.UINT8);
+        Rect roi = options.getRoi().isEmpty() ? new Rect(0, 0, width, height) : options.getRoi();
 
-        Rect roi = options.getRoi().isEmpty()
-                ? new Rect(0, 0, imageUint8.getWidth(), imageUint8.getHeight())
-                : options.getRoi();
-
-        return classifyNative(getNativeHandle(), imageUint8.getBuffer(), imageUint8.getWidth(),
-                imageUint8.getHeight(), new int[] {roi.left, roi.top, roi.width(), roi.height()},
-                options.getOrientation().getValue());
+        return classifyNative(getNativeHandle(), frameBufferHandle,
+                new int[] {roi.left, roi.top, roi.width(), roi.height()});
     }
 
     private static native long initJniWithModelFdAndOptions(int fileDescriptor,
-            long fileDescriptorLength, long fileDescriptorOffset, ImageClassifierOptions options);
+            long fileDescriptorLength, long fileDescriptorOffset, ImageClassifierOptions options,
+            long baseOptionsHandle);
+
+    private static native long initJniWithByteBuffer(
+            ByteBuffer modelBuffer, ImageClassifierOptions options, long baseOptionsHandle);
 
     /**
      * The native method to classify an image with the ROI and orientation.
      *
      * @param roi the ROI of the input image, an array representing the bounding box as {left, top,
      *     width, height}
-     * @param orientation the integer value corresponding to {@link
-     *     ImageProcessingOptions#Orientation}
      */
     private static native List<Classifications> classifyNative(
-            long nativeHandle, ByteBuffer image, int width, int height, int[] roi, int orientation);
+            long nativeHandle, long frameBufferHandle, int[] roi);
 
     @Override
     protected void deinit(long nativeHandle) {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BUILD
new file mode 100644
index 0000000..19a6c99
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BUILD
@@ -0,0 +1,15 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+# BaseVisionTaskApi is built with the source code of vision tasks together.
+# Alternatively, we could build BaseVisionTaskApi into an individual library
+# with its own .so, and vision tasks could all depend on it. However, it will
+# increate the binary size of task-library-vision.aar by 3 MB, because the
+# native dependencies of BaseVisionTaskApi are not shared with those vision
+# tasks.
+filegroup(
+    name = "base_vision_api_src",
+    srcs = glob(["**/*.java"]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java
new file mode 100644
index 0000000..59ab62a9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core/BaseVisionTaskApi.java
@@ -0,0 +1,204 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.task.vision.core;
+
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkNotNull;
+
+import android.graphics.ImageFormat;
+import android.media.Image;
+import android.media.Image.Plane;
+
+import com.google.auto.value.AutoValue;
+
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.ColorSpaceType;
+import org.tensorflow.lite.support.image.TensorImage;
+import org.tensorflow.lite.task.core.BaseTaskApi;
+import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+
+import java.nio.ByteBuffer;
+
+/** Base class for Task Vision APIs. */
+public abstract class BaseVisionTaskApi extends BaseTaskApi {
+    /** Syntax sugar to run vision tasks with FrameBuffer and image processing options. */
+    public interface InferenceProvider<T> {
+        T run(long frameBufferHandle, int width, int height, ImageProcessingOptions options);
+    }
+
+    protected BaseVisionTaskApi(long nativeHandle) {
+        super(nativeHandle);
+    }
+
+    /** Runs inference with {@link TensorImage} and {@link ImageProcessingOptions}. */
+    protected <T> T run(
+            InferenceProvider<T> provider, TensorImage image, ImageProcessingOptions options) {
+        FrameBufferData frameBufferData =
+                createFrameBuffer(image, options.getOrientation().getValue());
+        T results = provider.run(frameBufferData.getFrameBufferHandle(), image.getWidth(),
+                image.getHeight(), options);
+        deleteFrameBuffer(frameBufferData.getFrameBufferHandle(),
+                frameBufferData.getByteArrayHandle(), frameBufferData.getByteArray());
+        return results;
+    }
+
+    private static FrameBufferData createFrameBuffer(TensorImage image, int orientation) {
+        ColorSpaceType colorSpaceType = image.getColorSpaceType();
+        switch (colorSpaceType) {
+            case RGB:
+            case NV12:
+            case NV21:
+            case YV12:
+            case YV21:
+                // All these types can be converted to ByteBuffer inside TensorImage. Creating
+                // FrameBuffer base on the image ByteBuffer.
+                return createFrameBufferFromByteBuffer(image, orientation);
+            case YUV_420_888:
+                // YUV_420_888 is a specific type for android.media.Image.
+                return createFrameBufferFromMediaImage(image, orientation);
+            default:
+                throw new IllegalArgumentException(
+                        "Color space type, " + colorSpaceType.name() + ", is unsupported.");
+        }
+    }
+
+    /**
+     * Creates FrameBuffer from the {@link android.media.Image} stored in the given {@link
+     * TensorImage}.
+     */
+    private static FrameBufferData createFrameBufferFromMediaImage(
+            TensorImage image, int orientation) {
+        Image mediaImage = image.getMediaImage();
+
+        checkArgument(mediaImage.getFormat() == ImageFormat.YUV_420_888,
+                "Only supports loading YUV_420_888 Image.");
+
+        Plane[] planes = mediaImage.getPlanes();
+        checkArgument(planes.length == 3,
+                String.format("The input image should have 3 planes, but got %d plane(s).",
+                        planes.length));
+
+        // Verify and rewind planes.
+        for (Plane plane : planes) {
+            ByteBuffer buffer = plane.getBuffer();
+            checkNotNull(buffer, "The image buffer is corrupted and the plane is null.");
+            // From the public documentation, plane.getBuffer() should always return a direct
+            // ByteBuffer. See
+            // https://developer.android.com/reference/android/media/Image.Plane#getBuffer()
+            checkArgument(buffer.isDirect(),
+                    "The image plane buffer is not a direct ByteBuffer, and is not supported.");
+            buffer.rewind();
+        }
+
+        return FrameBufferData.create(
+                createFrameBufferFromPlanes(planes[0].getBuffer(), planes[1].getBuffer(),
+                        planes[2].getBuffer(), mediaImage.getWidth(), mediaImage.getHeight(),
+                        planes[0].getRowStride(),
+                        // row_stride and pixel_stride should be identical for U/V planes.
+                        planes[1].getRowStride(), planes[1].getPixelStride(), orientation),
+                // FrameBuffer created with direct ByteBuffer does not require memory freeing.
+                /*byteArrayHandle=*/0,
+                /*byteArray=*/new byte[0]);
+    }
+
+    /** Creates FrameBuffer from the {@link ByteBuffer} stored in the given {@link TensorImage}. */
+    private static FrameBufferData createFrameBufferFromByteBuffer(
+            TensorImage image, int orientation) {
+        // base_vision_api_jni.cc expects an uint8 image. Convert image of other types into uint8.
+        TensorImage imageUint8 = image.getDataType() == DataType.UINT8
+                ? image
+                : TensorImage.createFrom(image, DataType.UINT8);
+
+        ByteBuffer byteBuffer = imageUint8.getBuffer();
+        byteBuffer.rewind();
+        ColorSpaceType colorSpaceType = image.getColorSpaceType();
+        if (byteBuffer.isDirect()) {
+            return FrameBufferData.create(
+                    createFrameBufferFromByteBuffer(byteBuffer, imageUint8.getWidth(),
+                            imageUint8.getHeight(), orientation, colorSpaceType.getValue()),
+                    // FrameBuffer created with direct ByteBuffer does not require memory freeing.
+                    /*byteArrayHandle=*/0,
+                    /*byteArray=*/new byte[0]);
+        } else {
+            // If the byte array is copied in jni (during GetByteArrayElements), need to free
+            // the copied array once inference is done.
+            long[] byteArrayHandle = new long[1];
+            byte[] byteArray = getBytesFromByteBuffer(byteBuffer);
+            return FrameBufferData.create(
+                    createFrameBufferFromBytes(byteArray, imageUint8.getWidth(),
+                            imageUint8.getHeight(), orientation, colorSpaceType.getValue(),
+                            byteArrayHandle),
+                    byteArrayHandle[0], byteArray);
+        }
+    }
+
+    /** Holds the FrameBuffer and the underlying data pointers in C++. */
+    @AutoValue
+    abstract static class FrameBufferData {
+        /**
+         * Initializes a {@link FrameBufferData} object.
+         *
+         * @param frameBufferHandle the native handle to the FrameBuffer object.
+         * @param byteArrayHandle the native handle to the data array that backs up the FrameBuffer
+         *     object. If the FrameBuffer is created on a byte array, this byte array need to be
+         * freed after inference is done. If the FrameBuffer is created on a direct ByteBuffer, no
+         * byte array needs to be freed, and byteArrayHandle will be 0.
+         * @param byteArray the byte array that is used to create the c++ byte array object, which
+         *         is
+         *     needed when releasing byteArrayHandle. If the FrameBuffer is created on a direct
+         *     ByteBuffer (no byte array needs to be freed), pass in an empty array for {@code
+         *     byteArray}.
+         */
+        public static FrameBufferData create(
+                long frameBufferHandle, long byteArrayHandle, byte[] byteArray) {
+            return new AutoValue_BaseVisionTaskApi_FrameBufferData(
+                    frameBufferHandle, byteArrayHandle, byteArray);
+        }
+
+        abstract long getFrameBufferHandle();
+
+        abstract long getByteArrayHandle();
+
+        // Package private method for transferring data.
+        @SuppressWarnings("mutable")
+        abstract byte[] getByteArray();
+    }
+
+    private static native long createFrameBufferFromByteBuffer(
+            ByteBuffer image, int width, int height, int orientation, int colorSpaceType);
+
+    private static native long createFrameBufferFromBytes(byte[] image, int width, int height,
+            int orientation, int colorSpaceType, long[] byteArrayHandle);
+
+    private static native long createFrameBufferFromPlanes(ByteBuffer yBuffer, ByteBuffer uBuffer,
+            ByteBuffer vBuffer, int width, int height, int yRowStride, int uvRowStride,
+            int uvPixelStride, int orientation);
+
+    private static native void deleteFrameBuffer(
+            long frameBufferHandle, long byteArrayHandle, byte[] byteArray);
+
+    private static byte[] getBytesFromByteBuffer(ByteBuffer byteBuffer) {
+        // If the ByteBuffer has a back up array, use it directly without copy.
+        if (byteBuffer.hasArray() && byteBuffer.arrayOffset() == 0) {
+            return byteBuffer.array();
+        }
+        // Copy out the data otherwise.
+        byteBuffer.rewind();
+        byte[] bytes = new byte[byteBuffer.limit()];
+        byteBuffer.get(bytes, 0, bytes.length);
+        return bytes;
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/AndroidManifest.xml
index 5fefccd..9d585a2b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/AndroidManifest.xml
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/AndroidManifest.xml
@@ -1,5 +1,5 @@
 <?xml version="1.0" encoding="utf-8"?>
 <manifest xmlns:android="http://schemas.android.com/apk/res/android"
     package="org.tensorflow.lite.task.vision.detector">
-  <uses-sdk android:minSdkVersion="19" android:targetSdkVersion="29"/>
+  <uses-sdk android:minSdkVersion="21" android:targetSdkVersion="29"/>
 </manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/BUILD
index d0d541ab..81249e8f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/BUILD
@@ -1,9 +1,9 @@
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -16,17 +16,34 @@
     srcs = glob(["**/*.java"]),
 )
 
-android_library(
+# Default target that uses BuiltInOpResolver, registers all built-in OPs.
+android_library_with_tflite(
     name = "object_detector",
-    srcs = glob(["*.java"]),
-    javacopts = JAVACOPTS,
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/vision/detector:object_detector_native",
+    ],
+    exports = [
+        ":object_detector_java",
+    ],
+)
+
+# Java-only target, need to be used together with a native target similar to
+# //third_party/tensorflow_lite_support/java/src/native/task/vision/detector:object_detector_native.
+# Use this target when you want to provide a MutableOpResolver with customized
+# OPs and/or a subset of BuiltInOps to reduce binary size.
+android_library(
+    name = "object_detector_java",
+    srcs = glob(["*.java"]) + [
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core:base_vision_api_src",
+    ],
+    javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/vision/detector:object_detector_native",
         "@com_google_auto_value",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@maven//:com_google_android_odml_image",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java
index ebcab12..c0585b8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/detector/ObjectDetector.java
@@ -16,17 +16,24 @@
 package org.tensorflow.lite.task.vision.detector;
 
 import android.content.Context;
+import android.os.ParcelFileDescriptor;
 
-import org.tensorflow.lite.DataType;
+import com.google.android.odml.image.MlImage;
+
 import org.tensorflow.lite.annotations.UsedByReflection;
+import org.tensorflow.lite.support.image.MlImageAdapter;
 import org.tensorflow.lite.support.image.TensorImage;
-import org.tensorflow.lite.task.core.BaseTaskApi;
+import org.tensorflow.lite.task.core.BaseOptions;
 import org.tensorflow.lite.task.core.TaskJniUtils;
+import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
 import org.tensorflow.lite.task.core.TaskJniUtils.FdAndOptionsHandleProvider;
 import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
 
+import java.io.File;
 import java.io.IOException;
 import java.nio.ByteBuffer;
+import java.nio.MappedByteBuffer;
 import java.util.ArrayList;
 import java.util.Collections;
 import java.util.List;
@@ -81,16 +88,19 @@
  * href="https://tfhub.dev/google/lite-model/object_detection/mobile_object_localizer_v1/1/metadata/1">TensorFlow
  * Hub.</a>.
  */
-public final class ObjectDetector extends BaseTaskApi {
+public final class ObjectDetector extends BaseVisionTaskApi {
     private static final String OBJECT_DETECTOR_NATIVE_LIB = "task_vision_jni";
+    private static final int OPTIONAL_FD_LENGTH = -1;
+    private static final int OPTIONAL_FD_OFFSET = -1;
 
     /**
      * Creates an {@link ObjectDetector} instance from the default {@link ObjectDetectorOptions}.
      *
      * @param modelPath path to the detection model with metadata in the assets
      * @throws IOException if an I/O error occurs when loading the tflite model
-     * @throws AssertionError if error occurs when creating {@link ObjectDetector} from the native
-     *     code
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static ObjectDetector createFromFile(Context context, String modelPath)
             throws IOException {
@@ -99,12 +109,40 @@
     }
 
     /**
+     * Creates an {@link ObjectDetector} instance from the default {@link ObjectDetectorOptions}.
+     *
+     * @param modelFile the detection model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ObjectDetector createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, ObjectDetectorOptions.builder().build());
+    }
+
+    /**
+     * Creates an {@link ObjectDetector} instance with a model buffer and the default {@link
+     * ObjectDetectorOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the detection
+     *     model
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer} * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ObjectDetector createFromBuffer(final ByteBuffer modelBuffer) {
+        return createFromBufferAndOptions(modelBuffer, ObjectDetectorOptions.builder().build());
+    }
+
+    /**
      * Creates an {@link ObjectDetector} instance from {@link ObjectDetectorOptions}.
      *
      * @param modelPath path to the detection model with metadata in the assets
      * @throws IOException if an I/O error occurs when loading the tflite model
-     * @throws AssertionError if error occurs when creating {@link ObjectDetector} from the native
-     *     code
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static ObjectDetector createFromFileAndOptions(
             Context context, String modelPath, ObjectDetectorOptions options) throws IOException {
@@ -114,12 +152,68 @@
                     public long createHandle(int fileDescriptor, long fileDescriptorLength,
                             long fileDescriptorOffset, ObjectDetectorOptions options) {
                         return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
-                                fileDescriptorOffset, options);
+                                fileDescriptorOffset, options,
+                                TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                        options.getBaseOptions(), options.getNumThreads()));
                     }
                 }, OBJECT_DETECTOR_NATIVE_LIB, modelPath, options));
     }
 
     /**
+     * Creates an {@link ObjectDetector} instance from {@link ObjectDetectorOptions}.
+     *
+     * @param modelFile the detection model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ObjectDetector createFromFileAndOptions(
+            File modelFile, final ObjectDetectorOptions options) throws IOException {
+        try (ParcelFileDescriptor descriptor =
+                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+            return new ObjectDetector(
+                    TaskJniUtils.createHandleFromLibrary(new TaskJniUtils.EmptyHandleProvider() {
+                        @Override
+                        public long createHandle() {
+                            return initJniWithModelFdAndOptions(descriptor.getFd(),
+                                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
+                                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options,
+                                    TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                            options.getBaseOptions(), options.getNumThreads()));
+                        }
+                    }, OBJECT_DETECTOR_NATIVE_LIB));
+        }
+    }
+
+    /**
+     * Creates an {@link ObjectDetector} instance with a model buffer and {@link
+     * ObjectDetectorOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the detection
+     *     model
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ObjectDetector createFromBufferAndOptions(
+            final ByteBuffer modelBuffer, final ObjectDetectorOptions options) {
+        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+            throw new IllegalArgumentException(
+                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
+        }
+        return new ObjectDetector(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                return initJniWithByteBuffer(modelBuffer, options,
+                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                options.getBaseOptions(), options.getNumThreads()));
+            }
+        }, OBJECT_DETECTOR_NATIVE_LIB));
+    }
+
+    /**
      * Constructor to initialize the JNI with a pointer from C++.
      *
      * @param nativeHandle a pointer referencing memory allocated in C++
@@ -137,6 +231,7 @@
         // 1. java.util.Optional require Java 8 while we need to support Java 7.
         // 2. The Guava library (com.google.common.base.Optional) is avoided in this project. See
         // the comments for labelAllowList.
+        private final BaseOptions baseOptions;
         private final String displayNamesLocale;
         private final int maxResults;
         private final float scoreThreshold;
@@ -148,6 +243,7 @@
         // vulnerable.
         private final List<String> labelAllowList;
         private final List<String> labelDenyList;
+        private final int numThreads;
 
         public static Builder builder() {
             return new Builder();
@@ -155,15 +251,23 @@
 
         /** A builder that helps to configure an instance of ObjectDetectorOptions. */
         public static class Builder {
+            private BaseOptions baseOptions = BaseOptions.builder().build();
             private String displayNamesLocale = "en";
             private int maxResults = -1;
             private float scoreThreshold;
             private boolean isScoreThresholdSet = false;
             private List<String> labelAllowList = new ArrayList<>();
             private List<String> labelDenyList = new ArrayList<>();
+            private int numThreads = -1;
 
             private Builder() {}
 
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public Builder setBaseOptions(BaseOptions baseOptions) {
+                this.baseOptions = baseOptions;
+                return this;
+            }
+
             /**
              * Sets the locale to use for display names specified through the TFLite Model Metadata,
              * if any.
@@ -210,9 +314,9 @@
              *
              * <p>If non-empty, detection results whose label is not in this set will be filtered
              * out. Duplicate or unknown labels are ignored. Mutually exclusive with {@code
-             * labelDenyList}. It will cause {@link AssertionError} when calling {@link
-             * #createFromFileAndOptions}, if both
-             * {@code labelDenyList} and {@code labelAllowList} are set.
+             * labelDenyList}. It will cause {@link IllegalStateException} when calling {@link
+             * #createFromFileAndOptions}, if both {@code labelDenyList} and {@code labelAllowList}
+             * are set.
              */
             public Builder setLabelAllowList(List<String> labelAllowList) {
                 this.labelAllowList = Collections.unmodifiableList(new ArrayList<>(labelAllowList));
@@ -224,15 +328,32 @@
              *
              * <p>If non-empty, detection results whose label is in this set will be filtered out.
              * Duplicate or unknown labels are ignored. Mutually exclusive with {@code
-             * labelAllowList}. It will cause {@link AssertionError} when calling {@link
-             * #createFromFileAndOptions}, if both
-             * {@code labelDenyList} and {@code labelAllowList} are set.
+             * labelAllowList}. It will cause {@link IllegalStateException} when calling {@link
+             * #createFromFileAndOptions}, if both {@code labelDenyList} and {@code labelAllowList}
+             * are set.
              */
             public Builder setLabelDenyList(List<String> labelDenyList) {
                 this.labelDenyList = Collections.unmodifiableList(new ArrayList<>(labelDenyList));
                 return this;
             }
 
+            /**
+             * Sets the number of threads to be used for TFLite ops that support multi-threading
+             * when running inference with CPU. Defaults to -1.
+             *
+             * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has
+             * the effect to let TFLite runtime set the value.
+             *
+             * @deprecated use {@link BaseOptions} to configure number of threads instead. This
+             *         method
+             *     will override the number of threads configured from {@link BaseOptions}.
+             */
+            @Deprecated
+            public Builder setNumThreads(int numThreads) {
+                this.numThreads = numThreads;
+                return this;
+            }
+
             public ObjectDetectorOptions build() {
                 return new ObjectDetectorOptions(this);
             }
@@ -268,6 +389,15 @@
             return new ArrayList<>(labelDenyList);
         }
 
+        @UsedByReflection("object_detector_jni.cc")
+        public int getNumThreads() {
+            return numThreads;
+        }
+
+        public BaseOptions getBaseOptions() {
+            return baseOptions;
+        }
+
         private ObjectDetectorOptions(Builder builder) {
             displayNamesLocale = builder.displayNamesLocale;
             maxResults = builder.maxResults;
@@ -275,14 +405,28 @@
             isScoreThresholdSet = builder.isScoreThresholdSet;
             labelAllowList = builder.labelAllowList;
             labelDenyList = builder.labelDenyList;
+            numThreads = builder.numThreads;
+            baseOptions = builder.baseOptions;
         }
     }
 
     /**
      * Performs actual detection on the provided image.
      *
-     * @param image a {@link TensorImage} object that represents a RGB image
-     * @throws AssertionError if error occurs when processing the image from the native code
+     * <p>{@link ObjectDetector} supports the following {@link TensorImage} color space types:
+     *
+     * <ul>
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+     * </ul>
+     *
+     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the color space type of image is unsupported
      */
     public List<Detection> detect(TensorImage image) {
         return detect(image, ImageProcessingOptions.builder().build());
@@ -291,28 +435,91 @@
     /**
      * Performs actual detection on the provided image.
      *
-     * @param image a {@link TensorImage} object that represents a RGB image
-     * @param options {@link ObjectDetector} only supports image rotation (through {@link
-     *     ImageProcessingOptions#Builder#setOrientation}) currently. The orientation of an image
-     *     defaults to {@link ImageProcessingOptions#Orientation#TOP_LEFT}.
-     * @throws AssertionError if error occurs when processing the image from the native code
+     * <p>{@link ObjectDetector} supports the following {@link TensorImage} color space types:
+     *
+     * <ul>
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+     * </ul>
+     *
+     * <p>{@link ObjectDetector} supports the following options:
+     *
+     * <ul>
+     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}.
+     * </ul>
+     *
+     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+     * @param options the options to configure how to preprocess the image
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the color space type of image is unsupported
      */
     public List<Detection> detect(TensorImage image, ImageProcessingOptions options) {
+        return run(new InferenceProvider<List<Detection>>() {
+            @Override
+            public List<Detection> run(
+                    long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+                return detect(frameBufferHandle, options);
+            }
+        }, image, options);
+    }
+
+    /**
+     * Performs actual detection on the provided {@code MlImage}.
+     *
+     * @param image an {@code MlImage} object that represents an image
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+     */
+    public List<Detection> detect(MlImage image) {
+        return detect(image, ImageProcessingOptions.builder().build());
+    }
+
+    /**
+     * Performs actual detection on the provided {@code MlImage} with {@link
+     * ImageProcessingOptions}.
+     *
+     * <p>{@link ObjectDetector} supports the following options:
+     *
+     * <ul>
+     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
+     *       MlImage#getRotation()} is not effective.
+     * </ul>
+     *
+     * @param image an {@code MlImage} object that represents an image
+     * @param options the options to configure how to preprocess the image
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+     */
+    public List<Detection> detect(MlImage image, ImageProcessingOptions options) {
+        image.getInternal().acquire();
+        TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+        List<Detection> result = detect(tensorImage, options);
+        image.close();
+        return result;
+    }
+
+    private List<Detection> detect(long frameBufferHandle, ImageProcessingOptions options) {
         checkNotClosed();
 
-        // object_detector_jni.cc expects an uint8 image. Convert image of other types into uint8.
-        TensorImage imageUint8 = image.getDataType() == DataType.UINT8
-                ? image
-                : TensorImage.createFrom(image, DataType.UINT8);
-        return detectNative(getNativeHandle(), imageUint8.getBuffer(), imageUint8.getWidth(),
-                imageUint8.getHeight(), options.getOrientation().getValue());
+        return detectNative(getNativeHandle(), frameBufferHandle);
     }
 
     private static native long initJniWithModelFdAndOptions(int fileDescriptor,
-            long fileDescriptorLength, long fileDescriptorOffset, ObjectDetectorOptions options);
+            long fileDescriptorLength, long fileDescriptorOffset, ObjectDetectorOptions options,
+            long baseOptionsHandle);
 
-    private static native List<Detection> detectNative(
-            long nativeHandle, ByteBuffer image, int width, int height, int orientation);
+    private static native long initJniWithByteBuffer(
+            ByteBuffer modelBuffer, ObjectDetectorOptions options, long baseOptionsHandle);
+
+    private static native List<Detection> detectNative(long nativeHandle, long frameBufferHandle);
 
     @Override
     protected void deinit(long nativeHandle) {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/AndroidManifest.xml
index 991d481..d9c4568 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/AndroidManifest.xml
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/AndroidManifest.xml
@@ -1,5 +1,5 @@
 <?xml version="1.0" encoding="utf-8"?>
 <manifest xmlns:android="http://schemas.android.com/apk/res/android"
     package="org.tensorflow.lite.task.vision.segmenter">
-  <uses-sdk android:minSdkVersion="19" android:targetSdkVersion="29"/>
+  <uses-sdk android:minSdkVersion="21" android:targetSdkVersion="29"/>
 </manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/BUILD
index 506d5bf..31a2b11 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/BUILD
@@ -1,8 +1,9 @@
 load("@org_tensorflow//tensorflow/lite/java:aar_with_jni.bzl", "aar_with_jni")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "android_library_with_tflite")
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//visibility:public"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -15,19 +16,35 @@
     srcs = glob(["**/*.java"]),
 )
 
-android_library(
+# Default target that uses BuiltInOpResolver, registers all built-in OPs.
+android_library_with_tflite(
     name = "image_segmenter",
-    srcs = glob(["*.java"]),
-    # TODO(b/163039980): Use JAVACOPTS in TF. "-Xep:RemoveUnusedImports:ERROR" wierdly break the build.
+    tflite_exports = [
+        "//tensorflow_lite_support/java/src/native/task/vision/segmenter:image_segmenter_native",
+    ],
+    exports = [
+        ":image_segmenter_java",
+    ],
+)
+
+# Java-only target, need to be used together with a native target similar to
+# //third_party/tensorflow_lite_support/java/src/native/task/vision/segmenter:image_segmenter_native",
+# Use this target when you want to provide a MutableOpResolver with customized
+# OPs and/or a subset of BuiltInOps to reduce binary size.
+android_library(
+    name = "image_segmenter_java",
+    srcs = glob(["*.java"]) + [
+        "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/core:base_vision_api_src",
+    ],
     javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
     deps = [
         "//tensorflow_lite_support/java:tensorflowlite_support_java",
         "//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base_task_api",
-        "//tensorflow_lite_support/java/src/native/task/vision/segmenter:image_segmenter_native",
         "@com_google_auto_value",
         "@maven//:androidx_annotation_annotation",
-        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java",
+        "@maven//:com_google_android_odml_image",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_java_stable",
     ],
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java
index b175e0b..991fede 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ColoredLabel.java
@@ -34,7 +34,7 @@
      * @param label the label string, as provided in the label map packed in the TFLite Model
      *     Metadata.
      * @param displayName the display name of label, as configured through {@link
-     *     ImageSegmenter#ImageSegmenterOptions#Builder#setDisplayNamesLocale}
+     *     ImageSegmenter.ImageSegmenterOptions.Builder#setDisplayNamesLocale}
      * @param argb the color components for the label in ARGB. See <a
      *     href="https://developer.android.com/reference/android/graphics/Color#color-ints">Android
      *     Color ints.</a> for more details.
@@ -45,12 +45,12 @@
     }
 
     /**
-     * Creates a {@link ColoredLabel} object with a {@link Color} instance.
+     * Creates a {@link ColoredLabel} object with a {@link android.graphics.Color} instance.
      *
      * @param label the label string, as provided in the label map packed in the TFLite Model
      *     Metadata.
      * @param displayName the display name of label, as configured through {@link
-     *     ImageSegmenter#ImageSegmenterOptions#Builder#setDisplayNamesLocale}
+     *     ImageSegmenter.ImageSegmenterOptions.Builder#setDisplayNamesLocale}
      * @param color the color components for the label. The Color instatnce is supported on Android
      *     API level 26 and above. For API level lower than 26, use {@link #create(String, String,
      *     int)}. See <a
@@ -76,7 +76,7 @@
     public abstract int getArgb();
 
     /**
-     * Gets the {@link Color} instance of the underlying color.
+     * Gets the {@link android.graphics.Color} instance of the underlying color.
      *
      * <p>The Color instatnce is supported on Android API level 26 and above. For API level lower
      * than 26, use {@link #getArgb()}. See <a
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java
index b7776dc..4c3b363 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/ImageSegmenter.java
@@ -17,19 +17,25 @@
 
 import android.content.Context;
 import android.content.res.AssetFileDescriptor;
+import android.os.ParcelFileDescriptor;
 
+import com.google.android.odml.image.MlImage;
 import com.google.auto.value.AutoValue;
 
-import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.MlImageAdapter;
 import org.tensorflow.lite.support.image.TensorImage;
-import org.tensorflow.lite.task.core.BaseTaskApi;
+import org.tensorflow.lite.task.core.BaseOptions;
 import org.tensorflow.lite.task.core.TaskJniUtils;
 import org.tensorflow.lite.task.core.TaskJniUtils.EmptyHandleProvider;
 import org.tensorflow.lite.task.core.vision.ImageProcessingOptions;
+import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi;
+import org.tensorflow.lite.task.vision.core.BaseVisionTaskApi.InferenceProvider;
 
+import java.io.File;
 import java.io.IOException;
 import java.nio.ByteBuffer;
 import java.nio.ByteOrder;
+import java.nio.MappedByteBuffer;
 import java.util.ArrayList;
 import java.util.Arrays;
 import java.util.List;
@@ -60,7 +66,7 @@
  *             is the number of classes supported by the model.
  *         <li>optional (but recommended) label map(s) can be attached as AssociatedFile-s with type
  *             TENSOR_AXIS_LABELS, containing one label per line. The first such AssociatedFile (if
- *             any) is used to fill the class name, i.e. {@link ColoredLabel#getClassName} of the
+ *             any) is used to fill the class name, i.e. {@link ColoredLabel#getlabel} of the
  *             results. The display name, i.e. {@link ColoredLabel#getDisplayName}, is filled from
  *             the AssociatedFile (if any) whose locale matches the `display_names_locale` field of
  *             the `ImageSegmenterOptions` used at creation time ("en" by default, i.e. English). If
@@ -71,8 +77,10 @@
  * <p>An example of such model can be found on <a
  * href="https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/1">TensorFlow Hub.</a>.
  */
-public final class ImageSegmenter extends BaseTaskApi {
+public final class ImageSegmenter extends BaseVisionTaskApi {
     private static final String IMAGE_SEGMENTER_NATIVE_LIB = "task_vision_jni";
+    private static final int OPTIONAL_FD_LENGTH = -1;
+    private static final int OPTIONAL_FD_OFFSET = -1;
 
     private final OutputType outputType;
 
@@ -81,8 +89,9 @@
      *
      * @param modelPath path of the segmentation model with metadata in the assets
      * @throws IOException if an I/O error occurs when loading the tflite model
-     * @throws AssertionError if error occurs when creating {@link ImageSegmenter} from the native
-     *     code
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static ImageSegmenter createFromFile(Context context, String modelPath)
             throws IOException {
@@ -91,32 +100,101 @@
     }
 
     /**
+     * Creates an {@link ImageSegmenter} instance from the default {@link ImageSegmenterOptions}.
+     *
+     * @param modelFile the segmentation model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ImageSegmenter createFromFile(File modelFile) throws IOException {
+        return createFromFileAndOptions(modelFile, ImageSegmenterOptions.builder().build());
+    }
+
+    /**
+     * Creates an {@link ImageSegmenter} instance with a model buffer and the default {@link
+     * ImageSegmenterOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     segmentation model
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     */
+    public static ImageSegmenter createFromBuffer(final ByteBuffer modelBuffer) {
+        return createFromBufferAndOptions(modelBuffer, ImageSegmenterOptions.builder().build());
+    }
+
+    /**
      * Creates an {@link ImageSegmenter} instance from {@link ImageSegmenterOptions}.
      *
      * @param modelPath path of the segmentation model with metadata in the assets
      * @throws IOException if an I/O error occurs when loading the tflite model
-     * @throws AssertionError if error occurs when creating {@link ImageSegmenter} from the native
-     *     code
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
      */
     public static ImageSegmenter createFromFileAndOptions(Context context, String modelPath,
             final ImageSegmenterOptions options) throws IOException {
         try (AssetFileDescriptor assetFileDescriptor = context.getAssets().openFd(modelPath)) {
-            long nativeHandle = TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
-                @Override
-                public long createHandle() {
-                    return initJniWithModelFdAndOptions(
-                            /*fileDescriptor=*/assetFileDescriptor.getParcelFileDescriptor()
-                                    .getFd(),
-                            /*fileDescriptorLength=*/assetFileDescriptor.getLength(),
-                            /*fileDescriptorOffset=*/assetFileDescriptor.getStartOffset(),
-                            options.getDisplayNamesLocale(), options.getOutputType().getValue());
-                }
-            }, IMAGE_SEGMENTER_NATIVE_LIB);
-            return new ImageSegmenter(nativeHandle, options.getOutputType());
+            return createFromModelFdAndOptions(
+                    /*fileDescriptor=*/assetFileDescriptor.getParcelFileDescriptor().getFd(),
+                    /*fileDescriptorLength=*/assetFileDescriptor.getLength(),
+                    /*fileDescriptorOffset=*/assetFileDescriptor.getStartOffset(), options);
         }
     }
 
     /**
+     * Creates an {@link ImageSegmenter} instance from {@link ImageSegmenterOptions}.
+     *
+     * @param modelFile the segmentation model {@link File} instance
+     * @throws IOException if an I/O error occurs when loading the tflite model
+     * @throws IllegalArgumentException if an argument is invalid
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     */
+    public static ImageSegmenter createFromFileAndOptions(
+            File modelFile, final ImageSegmenterOptions options) throws IOException {
+        try (ParcelFileDescriptor descriptor =
+                        ParcelFileDescriptor.open(modelFile, ParcelFileDescriptor.MODE_READ_ONLY)) {
+            return createFromModelFdAndOptions(
+                    /*fileDescriptor=*/descriptor.getFd(),
+                    /*fileDescriptorLength=*/OPTIONAL_FD_LENGTH,
+                    /*fileDescriptorOffset=*/OPTIONAL_FD_OFFSET, options);
+        }
+    }
+
+    /**
+     * Creates an {@link ImageSegmenter} instance with a model buffer and {@link
+     * ImageSegmenterOptions}.
+     *
+     * @param modelBuffer a direct {@link ByteBuffer} or a {@link MappedByteBuffer} of the
+     *     segmentation model
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the model buffer is not a direct {@link ByteBuffer} or a
+     *     {@link MappedByteBuffer}
+     */
+    public static ImageSegmenter createFromBufferAndOptions(
+            final ByteBuffer modelBuffer, final ImageSegmenterOptions options) {
+        if (!(modelBuffer.isDirect() || modelBuffer instanceof MappedByteBuffer)) {
+            throw new IllegalArgumentException(
+                    "The model buffer should be either a direct ByteBuffer or a MappedByteBuffer.");
+        }
+        return new ImageSegmenter(TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                return initJniWithByteBuffer(modelBuffer, options.getDisplayNamesLocale(),
+                        options.getOutputType().getValue(),
+                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                options.getBaseOptions(), options.getNumThreads()));
+            }
+        }, IMAGE_SEGMENTER_NATIVE_LIB), options.getOutputType());
+    }
+
+    /**
      * Constructor to initialize the JNI with a pointer from C++.
      *
      * @param nativeHandle a pointer referencing memory allocated in C++
@@ -131,20 +209,30 @@
     public abstract static class ImageSegmenterOptions {
         private static final String DEFAULT_DISPLAY_NAME_LOCALE = "en";
         private static final OutputType DEFAULT_OUTPUT_TYPE = OutputType.CATEGORY_MASK;
+        private static final int NUM_THREADS = -1;
+
+        public abstract BaseOptions getBaseOptions();
 
         public abstract String getDisplayNamesLocale();
 
         public abstract OutputType getOutputType();
 
+        public abstract int getNumThreads();
+
         public static Builder builder() {
             return new AutoValue_ImageSegmenter_ImageSegmenterOptions.Builder()
                     .setDisplayNamesLocale(DEFAULT_DISPLAY_NAME_LOCALE)
-                    .setOutputType(DEFAULT_OUTPUT_TYPE);
+                    .setOutputType(DEFAULT_OUTPUT_TYPE)
+                    .setNumThreads(NUM_THREADS)
+                    .setBaseOptions(BaseOptions.builder().build());
         }
 
         /** Builder for {@link ImageSegmenterOptions}. */
         @AutoValue.Builder
         public abstract static class Builder {
+            /** Sets the general options to configure Task APIs, such as accelerators. */
+            public abstract Builder setBaseOptions(BaseOptions baseOptions);
+
             /**
              * Sets the locale to use for display names specified through the TFLite Model Metadata,
              * if any.
@@ -157,6 +245,20 @@
 
             public abstract Builder setOutputType(OutputType outputType);
 
+            /**
+             * Sets the number of threads to be used for TFLite ops that support multi-threading
+             * when running inference with CPU. Defaults to -1.
+             *
+             * <p>numThreads should be greater than 0 or equal to -1. Setting numThreads to -1 has
+             * the effect to let TFLite runtime set the value.
+             *
+             * @deprecated use {@link BaseOptions} to configure number of threads instead. This
+             *         method
+             *     will override the number of threads configured from {@link BaseOptions}.
+             */
+            @Deprecated
+            public abstract Builder setNumThreads(int numThreads);
+
             public abstract ImageSegmenterOptions build();
         }
     }
@@ -164,12 +266,24 @@
     /**
      * Performs actual segmentation on the provided image.
      *
-     * @param image a {@link TensorImage} object that represents an RGB image
+     * <p>{@link ImageSegmenter} supports the following {@link TensorImage} color space types:
+     *
+     * <ul>
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+     * </ul>
+     *
+     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
      * @return results of performing image segmentation. Note that at the time, a single {@link
      *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
      *     for later extension to e.g. instance segmentation models, which may return one
      * segmentation per object.
-     * @throws AssertionError if error occurs when segmenting the image from the native code
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the color space type of image is unsupported
      */
     public List<Segmentation> segment(TensorImage image) {
         return segment(image, ImageProcessingOptions.builder().build());
@@ -178,29 +292,97 @@
     /**
      * Performs actual segmentation on the provided image with {@link ImageProcessingOptions}.
      *
-     * @param image a {@link TensorImage} object that represents an RGB image
-     * @param options {@link ImageSegmenter} only supports image rotation (through {@link
-     *     ImageProcessingOptions#Builder#setOrientation}) currently. The orientation of an image
-     *     defaults to {@link ImageProcessingOptions#Orientation#TOP_LEFT}.
+     * <p>{@link ImageSegmenter} supports the following {@link TensorImage} color space types:
+     *
+     * <ul>
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#RGB}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#NV21}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV12}
+     *   <li>{@link org.tensorflow.lite.support.image.ColorSpaceType#YV21}
+     * </ul>
+     *
+     * <p>{@link ImageSegmenter} supports the following options:
+     *
+     * <ul>
+     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}
+     * </ul>
+     *
+     * @param image a UINT8 {@link TensorImage} object that represents an RGB or YUV image
+     * @param options the options configure how to preprocess the image
      * @return results of performing image segmentation. Note that at the time, a single {@link
      *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
      *     for later extension to e.g. instance segmentation models, which may return one
      * segmentation per object.
-     * @throws AssertionError if error occurs when segmenting the image from the native code
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the color space type of image is unsupported
      */
     public List<Segmentation> segment(TensorImage image, ImageProcessingOptions options) {
+        return run(new InferenceProvider<List<Segmentation>>() {
+            @Override
+            public List<Segmentation> run(
+                    long frameBufferHandle, int width, int height, ImageProcessingOptions options) {
+                return segment(frameBufferHandle, options);
+            }
+        }, image, options);
+    }
+
+    /**
+     * Performs actual segmentation on the provided {@code MlImage}.
+     *
+     * @param image an {@code MlImage} to segment.
+     * @return results of performing image segmentation. Note that at the time, a single {@link
+     *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
+     *     for later extension to e.g. instance segmentation models, which may return one
+     * segmentation per object.
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the storage type or format of the image is unsupported
+     */
+    public List<Segmentation> segment(MlImage image) {
+        return segment(image, ImageProcessingOptions.builder().build());
+    }
+
+    /**
+     * Performs actual segmentation on the provided {@code MlImage} with {@link
+     * ImageProcessingOptions}.
+     *
+     * <p>{@link ImageSegmenter} supports the following options:
+     *
+     * <ul>
+     *   <li>image rotation (through {@link ImageProcessingOptions.Builder#setOrientation}). It
+     *       defaults to {@link ImageProcessingOptions.Orientation#TOP_LEFT}. {@link
+     *       MlImage#getRotation()} is not effective.
+     * </ul>
+     *
+     * @param image an {@code MlImage} to segment.
+     * @param options the options configure how to preprocess the image.
+     * @return results of performing image segmentation. Note that at the time, a single {@link
+     *     Segmentation} element is expected to be returned. The result is stored in a {@link List}
+     *     for later extension to e.g. instance segmentation models, which may return one
+     * segmentation per object.
+     * @throws IllegalStateException if there is an internal error
+     * @throws RuntimeException if there is an otherwise unspecified error
+     * @throws IllegalArgumentException if the color space type of image is unsupported
+     */
+    public List<Segmentation> segment(MlImage image, ImageProcessingOptions options) {
+        image.getInternal().acquire();
+        TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+        List<Segmentation> result = segment(tensorImage, options);
+        image.close();
+        return result;
+    }
+
+    public List<Segmentation> segment(long frameBufferHandle, ImageProcessingOptions options) {
         checkNotClosed();
 
-        // image_segmenter_jni.cc expects an uint8 image. Convert image of other types into uint8.
-        TensorImage imageUint8 = image.getDataType() == DataType.UINT8
-                ? image
-                : TensorImage.createFrom(image, DataType.UINT8);
         List<byte[]> maskByteArrays = new ArrayList<>();
         List<ColoredLabel> coloredLabels = new ArrayList<>();
         int[] maskShape = new int[2];
-        segmentNative(getNativeHandle(), imageUint8.getBuffer(), imageUint8.getWidth(),
-                imageUint8.getHeight(), maskByteArrays, maskShape, coloredLabels,
-                options.getOrientation().getValue());
+        segmentNative(
+                getNativeHandle(), frameBufferHandle, maskByteArrays, maskShape, coloredLabels);
 
         List<ByteBuffer> maskByteBuffers = new ArrayList<>();
         for (byte[] bytes : maskByteArrays) {
@@ -214,9 +396,28 @@
                 outputType.createMasksFromBuffer(maskByteBuffers, maskShape), coloredLabels));
     }
 
+    private static ImageSegmenter createFromModelFdAndOptions(final int fileDescriptor,
+            final long fileDescriptorLength, final long fileDescriptorOffset,
+            final ImageSegmenterOptions options) {
+        long nativeHandle = TaskJniUtils.createHandleFromLibrary(new EmptyHandleProvider() {
+            @Override
+            public long createHandle() {
+                return initJniWithModelFdAndOptions(fileDescriptor, fileDescriptorLength,
+                        fileDescriptorOffset, options.getDisplayNamesLocale(),
+                        options.getOutputType().getValue(),
+                        TaskJniUtils.createProtoBaseOptionsHandleWithLegacyNumThreads(
+                                options.getBaseOptions(), options.getNumThreads()));
+            }
+        }, IMAGE_SEGMENTER_NATIVE_LIB);
+        return new ImageSegmenter(nativeHandle, options.getOutputType());
+    }
+
     private static native long initJniWithModelFdAndOptions(int fileDescriptor,
             long fileDescriptorLength, long fileDescriptorOffset, String displayNamesLocale,
-            int outputType);
+            int outputType, long baseOptionsHandle);
+
+    private static native long initJniWithByteBuffer(ByteBuffer modelBuffer,
+            String displayNamesLocale, int outputType, long baseOptionsHandle);
 
     /**
      * The native method to segment the image.
@@ -224,9 +425,8 @@
      * <p>{@code maskBuffers}, {@code maskShape}, {@code coloredLabels} will be updated in the
      * native layer.
      */
-    private static native void segmentNative(long nativeHandle, ByteBuffer image, int width,
-            int height, List<byte[]> maskByteArrays, int[] maskShape,
-            List<ColoredLabel> coloredLabels, int orientation);
+    private static native void segmentNative(long nativeHandle, long frameBufferHandle,
+            List<byte[]> maskByteArrays, int[] maskShape, List<ColoredLabel> coloredLabels);
 
     @Override
     protected void deinit(long nativeHandle) {
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java
index 113cacdd..8c69cf5 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision/segmenter/OutputType.java
@@ -17,7 +17,7 @@
 
 import static org.tensorflow.lite.DataType.FLOAT32;
 import static org.tensorflow.lite.DataType.UINT8;
-import static org.tensorflow.lite.support.common.SupportPreconditions.checkArgument;
+import static org.tensorflow.lite.support.common.internal.SupportPreconditions.checkArgument;
 import static org.tensorflow.lite.support.image.ColorSpaceType.GRAYSCALE;
 
 import org.tensorflow.lite.support.image.TensorImage;
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/AndroidManifest.xml
new file mode 100644
index 0000000..b2e2262
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/AndroidManifest.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="utf-8"?>
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+    package="org.tensorflow.lite.support">
+    <uses-sdk android:minSdkVersion="19" />
+</manifest>
+
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/BUILD
new file mode 100644
index 0000000..ecabe42
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/BUILD
@@ -0,0 +1,467 @@
+load("@build_bazel_rules_android//android:rules.bzl", "android_library", "android_local_test")
+load("//tensorflow_lite_support/tools/build_rules/android_test:android_library_instrumentation_tests.bzl", "android_library_instrumentation_tests")
+
+package(
+    default_testonly = 1,
+)
+
+licenses(["notice"])  # Apache License 2.0
+
+INSTRUMENTED_TESTS = glob(["**/*InstrumentedTest.java"])
+
+# Focus testing on the oldest and newest officially supported APIs.
+DEFAULT_INSTRUMENTED_DEVICES = [
+]
+
+exports_files(["AndroidManifest.xml"])
+
+android_library(
+    name = "test_lib",
+    testonly = 1,
+    assets = glob(["assets/**"]),
+    assets_dir = "assets",
+    manifest = "AndroidManifest.xml",
+)
+
+android_local_test(
+    name = "GpuDelegateProxyTest",
+    srcs = ["model/GpuDelegateProxyTest.java"],
+    manifest = "AndroidManifest.xml",
+    nocompress_extensions = ["tflite"],
+    tags = [
+        "noasan",
+        "nomsan",
+        "notsan",
+    ],
+    test_class = "org.tensorflow.lite.support.model.GpuDelegateProxyTest",
+    deps = [
+        ":test_lib",
+        "//tensorflow_lite_support/java:tensorflow-lite-support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+# TODO(138904571): add a bzl file to declare tests automatically for every java test file.
+# Note: This test is not able to be run with --test_strategy=local.
+android_local_test(
+    name = "ModelTest",
+    srcs = ["model/ModelTest.java"],
+    manifest = "AndroidManifest.xml",
+    nocompress_extensions = ["tflite"],
+    tags = [
+        "noasan",
+        "nomsan",
+        "notsan",
+    ],
+    test_class = "org.tensorflow.lite.support.model.ModelTest",
+    deps = [
+        ":test_lib",
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorBufferTest",
+    srcs = [
+        "tensorbuffer/TensorBufferTest.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.tensorbuffer.TensorBufferTest",
+    deps = [
+        ":test_lib",
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorBufferFloatTest",
+    srcs = [
+        "tensorbuffer/TensorBufferFloatTest.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.tensorbuffer.TensorBufferFloatTest",
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorBufferUint8Test",
+    srcs = [
+        "tensorbuffer/TensorBufferUint8Test.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.tensorbuffer.TensorBufferUint8Test",
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorImageTest",
+    size = "small",
+    srcs = [
+        "image/TensorImageTest.java",
+        "image/TestImageCreator.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.image.TensorImageTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_mockito_mockito_core",
+        "@maven//:org_mockito_mockito_inline",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "BoundingBoxUtilTest",
+    size = "small",
+    srcs = ["image/BoundingBoxUtilTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.image.BoundingBoxUtilTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "ImageConversionsTest",
+    size = "small",
+    srcs = [
+        "image/ImageConversionsTest.java",
+        "image/TestImageCreator.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.image.ImageConversionsTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "ImageProcessorTest",
+    srcs = ["image/ImageProcessorTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.image.ImageProcessorTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "NormalizeOpTest",
+    srcs = ["common/ops/NormalizeOpTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.common.ops.NormalizeOpTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "CastOpTest",
+    srcs = ["common/ops/CastOpTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.common.ops.CastOpTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "DequantizeOpTest",
+    srcs = ["common/ops/DequantizeOpTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.common.ops.DequantizeOpTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "QuantizeOpTest",
+    srcs = ["common/ops/QuantizeOpTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.common.ops.QuantizeOpTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlitelib_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "LabelAxisOpTest",
+    srcs = ["label/ops/LabelAxisOpTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.label.ops.LabelAxisOpTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        ":test_lib",
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "CategoryTest",
+    srcs = ["label/CategoryTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.label.CategoryTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "LabelUtilTest",
+    srcs = ["label/LabelUtilTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.label.LabelUtilTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorLabelTest",
+    srcs = ["label/TensorLabelTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.label.TensorLabelTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "FileUtilTest",
+    srcs = ["common/FileUtilTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.common.FileUtilTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        ":test_lib",
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorProcessorTest",
+    srcs = ["common/TensorProcessorTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.common.TensorProcessorTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "ColorSpaceTypeTest",
+    size = "small",
+    srcs = [
+        "image/ColorSpaceTypeTest.java",
+        "image/TestImageCreator.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "org.tensorflow.lite.support.image.ColorSpaceTypeTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
+        "@maven//:org_robolectric_robolectric",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TensorAudioTest",
+    size = "small",
+    srcs = [
+        "audio/TensorAudioTest.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    manifest_values = {
+        "minSdkVersion": "23",
+    },
+    test_class = "org.tensorflow.lite.support.audio.TensorAudioTest",
+    visibility = ["//visibility:private"],
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",
+        "@maven//:org_mockito_mockito_core",
+        "@maven//:org_mockito_mockito_inline",
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+test_suite(
+    name = "instrumentation_tests",
+    tags = [
+        "no_oss",
+        "tflite_emulator_test_android",
+    ],
+)
+
+android_library(
+    name = "test_image_creator",
+    testonly = 1,
+    srcs = ["image/TestImageCreator.java"],
+    manifest = "AndroidManifest.xml",
+    deps = [
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+    ],
+)
+
+# This rule specifies a bundle of tests, in which each test source file converts
+# to a test target.
+android_library_instrumentation_tests(
+    name = "instrumented_unittests",
+    srcs = INSTRUMENTED_TESTS,
+    binary_args = {
+        "multidex": "legacy",
+    },
+    tags = [
+        "no_oss",
+        "noasan",  # Avoid build breakage
+        "nomsan",  # Avoid build breakage
+        "notsan",  # Avoid build breakage
+        "nozapfhahn",  # Avoid coverage test breakage
+        "tflite_emulator_test_android",
+    ],
+    target_devices = DEFAULT_INSTRUMENTED_DEVICES,
+    test_java_package = "org.tensorflow.lite.support",
+    deps = [
+        ":test_image_creator",
+        ":test_lib",
+        "//tensorflow_lite_support/java:tensorflowlite_support",
+        "@maven//:androidx_multidex_multidex",
+        "@maven//:androidx_test_core",
+        "@maven//:androidx_test_ext_junit",
+        "@maven//:androidx_test_runner",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:junit_junit",  # android
+        "@maven//:org_mockito_mockito_core",
+        "@maven//:org_mockito_mockito_inline",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_gpu",
+        "@org_tensorflow//tensorflow/lite/java:tensorflowlite_stable",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/color_grid.png b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/color_grid.png
new file mode 100644
index 0000000..3cbfac5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/color_grid.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/flower_labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/flower_labels.txt
new file mode 100644
index 0000000..08f0b16
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/flower_labels.txt
@@ -0,0 +1,5 @@
+daisy
+dandelion
+roses
+sunflowers
+tulips
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/grey_grid.png b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/grey_grid.png
new file mode 100644
index 0000000..5cf066fe
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/grey_grid.png
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/labels.txt
new file mode 100644
index 0000000..fe81123
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/labels.txt
@@ -0,0 +1,1001 @@
+background
+tench
+goldfish
+great white shark
+tiger shark
+hammerhead
+electric ray
+stingray
+cock
+hen
+ostrich
+brambling
+goldfinch
+house finch
+junco
+indigo bunting
+robin
+bulbul
+jay
+magpie
+chickadee
+water ouzel
+kite
+bald eagle
+vulture
+great grey owl
+European fire salamander
+common newt
+eft
+spotted salamander
+axolotl
+bullfrog
+tree frog
+tailed frog
+loggerhead
+leatherback turtle
+mud turtle
+terrapin
+box turtle
+banded gecko
+common iguana
+American chameleon
+whiptail
+agama
+frilled lizard
+alligator lizard
+Gila monster
+green lizard
+African chameleon
+Komodo dragon
+African crocodile
+American alligator
+triceratops
+thunder snake
+ringneck snake
+hognose snake
+green snake
+king snake
+garter snake
+water snake
+vine snake
+night snake
+boa constrictor
+rock python
+Indian cobra
+green mamba
+sea snake
+horned viper
+diamondback
+sidewinder
+trilobite
+harvestman
+scorpion
+black and gold garden spider
+barn spider
+garden spider
+black widow
+tarantula
+wolf spider
+tick
+centipede
+black grouse
+ptarmigan
+ruffed grouse
+prairie chicken
+peacock
+quail
+partridge
+African grey
+macaw
+sulphur-crested cockatoo
+lorikeet
+coucal
+bee eater
+hornbill
+hummingbird
+jacamar
+toucan
+drake
+red-breasted merganser
+goose
+black swan
+tusker
+echidna
+platypus
+wallaby
+koala
+wombat
+jellyfish
+sea anemone
+brain coral
+flatworm
+nematode
+conch
+snail
+slug
+sea slug
+chiton
+chambered nautilus
+Dungeness crab
+rock crab
+fiddler crab
+king crab
+American lobster
+spiny lobster
+crayfish
+hermit crab
+isopod
+white stork
+black stork
+spoonbill
+flamingo
+little blue heron
+American egret
+bittern
+crane
+limpkin
+European gallinule
+American coot
+bustard
+ruddy turnstone
+red-backed sandpiper
+redshank
+dowitcher
+oystercatcher
+pelican
+king penguin
+albatross
+grey whale
+killer whale
+dugong
+sea lion
+Chihuahua
+Japanese spaniel
+Maltese dog
+Pekinese
+Shih-Tzu
+Blenheim spaniel
+papillon
+toy terrier
+Rhodesian ridgeback
+Afghan hound
+basset
+beagle
+bloodhound
+bluetick
+black-and-tan coonhound
+Walker hound
+English foxhound
+redbone
+borzoi
+Irish wolfhound
+Italian greyhound
+whippet
+Ibizan hound
+Norwegian elkhound
+otterhound
+Saluki
+Scottish deerhound
+Weimaraner
+Staffordshire bullterrier
+American Staffordshire terrier
+Bedlington terrier
+Border terrier
+Kerry blue terrier
+Irish terrier
+Norfolk terrier
+Norwich terrier
+Yorkshire terrier
+wire-haired fox terrier
+Lakeland terrier
+Sealyham terrier
+Airedale
+cairn
+Australian terrier
+Dandie Dinmont
+Boston bull
+miniature schnauzer
+giant schnauzer
+standard schnauzer
+Scotch terrier
+Tibetan terrier
+silky terrier
+soft-coated wheaten terrier
+West Highland white terrier
+Lhasa
+flat-coated retriever
+curly-coated retriever
+golden retriever
+Labrador retriever
+Chesapeake Bay retriever
+German short-haired pointer
+vizsla
+English setter
+Irish setter
+Gordon setter
+Brittany spaniel
+clumber
+English springer
+Welsh springer spaniel
+cocker spaniel
+Sussex spaniel
+Irish water spaniel
+kuvasz
+schipperke
+groenendael
+malinois
+briard
+kelpie
+komondor
+Old English sheepdog
+Shetland sheepdog
+collie
+Border collie
+Bouvier des Flandres
+Rottweiler
+German shepherd
+Doberman
+miniature pinscher
+Greater Swiss Mountain dog
+Bernese mountain dog
+Appenzeller
+EntleBucher
+boxer
+bull mastiff
+Tibetan mastiff
+French bulldog
+Great Dane
+Saint Bernard
+Eskimo dog
+malamute
+Siberian husky
+dalmatian
+affenpinscher
+basenji
+pug
+Leonberg
+Newfoundland
+Great Pyrenees
+Samoyed
+Pomeranian
+chow
+keeshond
+Brabancon griffon
+Pembroke
+Cardigan
+toy poodle
+miniature poodle
+standard poodle
+Mexican hairless
+timber wolf
+white wolf
+red wolf
+coyote
+dingo
+dhole
+African hunting dog
+hyena
+red fox
+kit fox
+Arctic fox
+grey fox
+tabby
+tiger cat
+Persian cat
+Siamese cat
+Egyptian cat
+cougar
+lynx
+leopard
+snow leopard
+jaguar
+lion
+tiger
+cheetah
+brown bear
+American black bear
+ice bear
+sloth bear
+mongoose
+meerkat
+tiger beetle
+ladybug
+ground beetle
+long-horned beetle
+leaf beetle
+dung beetle
+rhinoceros beetle
+weevil
+fly
+bee
+ant
+grasshopper
+cricket
+walking stick
+cockroach
+mantis
+cicada
+leafhopper
+lacewing
+dragonfly
+damselfly
+admiral
+ringlet
+monarch
+cabbage butterfly
+sulphur butterfly
+lycaenid
+starfish
+sea urchin
+sea cucumber
+wood rabbit
+hare
+Angora
+hamster
+porcupine
+fox squirrel
+marmot
+beaver
+guinea pig
+sorrel
+zebra
+hog
+wild boar
+warthog
+hippopotamus
+ox
+water buffalo
+bison
+ram
+bighorn
+ibex
+hartebeest
+impala
+gazelle
+Arabian camel
+llama
+weasel
+mink
+polecat
+black-footed ferret
+otter
+skunk
+badger
+armadillo
+three-toed sloth
+orangutan
+gorilla
+chimpanzee
+gibbon
+siamang
+guenon
+patas
+baboon
+macaque
+langur
+colobus
+proboscis monkey
+marmoset
+capuchin
+howler monkey
+titi
+spider monkey
+squirrel monkey
+Madagascar cat
+indri
+Indian elephant
+African elephant
+lesser panda
+giant panda
+barracouta
+eel
+coho
+rock beauty
+anemone fish
+sturgeon
+gar
+lionfish
+puffer
+abacus
+abaya
+academic gown
+accordion
+acoustic guitar
+aircraft carrier
+airliner
+airship
+altar
+ambulance
+amphibian
+analog clock
+apiary
+apron
+ashcan
+assault rifle
+backpack
+bakery
+balance beam
+balloon
+ballpoint
+Band Aid
+banjo
+bannister
+barbell
+barber chair
+barbershop
+barn
+barometer
+barrel
+barrow
+baseball
+basketball
+bassinet
+bassoon
+bathing cap
+bath towel
+bathtub
+beach wagon
+beacon
+beaker
+bearskin
+beer bottle
+beer glass
+bell cote
+bib
+bicycle-built-for-two
+bikini
+binder
+binoculars
+birdhouse
+boathouse
+bobsled
+bolo tie
+bonnet
+bookcase
+bookshop
+bottlecap
+bow
+bow tie
+brass
+brassiere
+breakwater
+breastplate
+broom
+bucket
+buckle
+bulletproof vest
+bullet train
+butcher shop
+cab
+caldron
+candle
+cannon
+canoe
+can opener
+cardigan
+car mirror
+carousel
+carpenter's kit
+carton
+car wheel
+cash machine
+cassette
+cassette player
+castle
+catamaran
+CD player
+cello
+cellular telephone
+chain
+chainlink fence
+chain mail
+chain saw
+chest
+chiffonier
+chime
+china cabinet
+Christmas stocking
+church
+cinema
+cleaver
+cliff dwelling
+cloak
+clog
+cocktail shaker
+coffee mug
+coffeepot
+coil
+combination lock
+computer keyboard
+confectionery
+container ship
+convertible
+corkscrew
+cornet
+cowboy boot
+cowboy hat
+cradle
+crane
+crash helmet
+crate
+crib
+Crock Pot
+croquet ball
+crutch
+cuirass
+dam
+desk
+desktop computer
+dial telephone
+diaper
+digital clock
+digital watch
+dining table
+dishrag
+dishwasher
+disk brake
+dock
+dogsled
+dome
+doormat
+drilling platform
+drum
+drumstick
+dumbbell
+Dutch oven
+electric fan
+electric guitar
+electric locomotive
+entertainment center
+envelope
+espresso maker
+face powder
+feather boa
+file
+fireboat
+fire engine
+fire screen
+flagpole
+flute
+folding chair
+football helmet
+forklift
+fountain
+fountain pen
+four-poster
+freight car
+French horn
+frying pan
+fur coat
+garbage truck
+gasmask
+gas pump
+goblet
+go-kart
+golf ball
+golfcart
+gondola
+gong
+gown
+grand piano
+greenhouse
+grille
+grocery store
+guillotine
+hair slide
+hair spray
+half track
+hammer
+hamper
+hand blower
+hand-held computer
+handkerchief
+hard disc
+harmonica
+harp
+harvester
+hatchet
+holster
+home theater
+honeycomb
+hook
+hoopskirt
+horizontal bar
+horse cart
+hourglass
+iPod
+iron
+jack-o'-lantern
+jean
+jeep
+jersey
+jigsaw puzzle
+jinrikisha
+joystick
+kimono
+knee pad
+knot
+lab coat
+ladle
+lampshade
+laptop
+lawn mower
+lens cap
+letter opener
+library
+lifeboat
+lighter
+limousine
+liner
+lipstick
+Loafer
+lotion
+loudspeaker
+loupe
+lumbermill
+magnetic compass
+mailbag
+mailbox
+maillot
+maillot
+manhole cover
+maraca
+marimba
+mask
+matchstick
+maypole
+maze
+measuring cup
+medicine chest
+megalith
+microphone
+microwave
+military uniform
+milk can
+minibus
+miniskirt
+minivan
+missile
+mitten
+mixing bowl
+mobile home
+Model T
+modem
+monastery
+monitor
+moped
+mortar
+mortarboard
+mosque
+mosquito net
+motor scooter
+mountain bike
+mountain tent
+mouse
+mousetrap
+moving van
+muzzle
+nail
+neck brace
+necklace
+nipple
+notebook
+obelisk
+oboe
+ocarina
+odometer
+oil filter
+organ
+oscilloscope
+overskirt
+oxcart
+oxygen mask
+packet
+paddle
+paddlewheel
+padlock
+paintbrush
+pajama
+palace
+panpipe
+paper towel
+parachute
+parallel bars
+park bench
+parking meter
+passenger car
+patio
+pay-phone
+pedestal
+pencil box
+pencil sharpener
+perfume
+Petri dish
+photocopier
+pick
+pickelhaube
+picket fence
+pickup
+pier
+piggy bank
+pill bottle
+pillow
+ping-pong ball
+pinwheel
+pirate
+pitcher
+plane
+planetarium
+plastic bag
+plate rack
+plow
+plunger
+Polaroid camera
+pole
+police van
+poncho
+pool table
+pop bottle
+pot
+potter's wheel
+power drill
+prayer rug
+printer
+prison
+projectile
+projector
+puck
+punching bag
+purse
+quill
+quilt
+racer
+racket
+radiator
+radio
+radio telescope
+rain barrel
+recreational vehicle
+reel
+reflex camera
+refrigerator
+remote control
+restaurant
+revolver
+rifle
+rocking chair
+rotisserie
+rubber eraser
+rugby ball
+rule
+running shoe
+safe
+safety pin
+saltshaker
+sandal
+sarong
+sax
+scabbard
+scale
+school bus
+schooner
+scoreboard
+screen
+screw
+screwdriver
+seat belt
+sewing machine
+shield
+shoe shop
+shoji
+shopping basket
+shopping cart
+shovel
+shower cap
+shower curtain
+ski
+ski mask
+sleeping bag
+slide rule
+sliding door
+slot
+snorkel
+snowmobile
+snowplow
+soap dispenser
+soccer ball
+sock
+solar dish
+sombrero
+soup bowl
+space bar
+space heater
+space shuttle
+spatula
+speedboat
+spider web
+spindle
+sports car
+spotlight
+stage
+steam locomotive
+steel arch bridge
+steel drum
+stethoscope
+stole
+stone wall
+stopwatch
+stove
+strainer
+streetcar
+stretcher
+studio couch
+stupa
+submarine
+suit
+sundial
+sunglass
+sunglasses
+sunscreen
+suspension bridge
+swab
+sweatshirt
+swimming trunks
+swing
+switch
+syringe
+table lamp
+tank
+tape player
+teapot
+teddy
+television
+tennis ball
+thatch
+theater curtain
+thimble
+thresher
+throne
+tile roof
+toaster
+tobacco shop
+toilet seat
+torch
+totem pole
+tow truck
+toyshop
+tractor
+trailer truck
+tray
+trench coat
+tricycle
+trimaran
+tripod
+triumphal arch
+trolleybus
+trombone
+tub
+turnstile
+typewriter keyboard
+umbrella
+unicycle
+upright
+vacuum
+vase
+vault
+velvet
+vending machine
+vestment
+viaduct
+violin
+volleyball
+waffle iron
+wall clock
+wallet
+wardrobe
+warplane
+washbasin
+washer
+water bottle
+water jug
+water tower
+whiskey jug
+whistle
+wig
+window screen
+window shade
+Windsor tie
+wine bottle
+wing
+wok
+wooden spoon
+wool
+worm fence
+wreck
+yawl
+yurt
+web site
+comic book
+crossword puzzle
+street sign
+traffic light
+book jacket
+menu
+plate
+guacamole
+consomme
+hot pot
+trifle
+ice cream
+ice lolly
+French loaf
+bagel
+pretzel
+cheeseburger
+hotdog
+mashed potato
+head cabbage
+broccoli
+cauliflower
+zucchini
+spaghetti squash
+acorn squash
+butternut squash
+cucumber
+artichoke
+bell pepper
+cardoon
+mushroom
+Granny Smith
+strawberry
+orange
+lemon
+fig
+pineapple
+banana
+jackfruit
+custard apple
+pomegranate
+hay
+carbonara
+chocolate sauce
+dough
+meat loaf
+pizza
+potpie
+burrito
+red wine
+espresso
+cup
+eggnog
+alp
+bubble
+cliff
+coral reef
+geyser
+lakeside
+promontory
+sandbar
+seashore
+valley
+volcano
+ballplayer
+groom
+scuba diver
+rapeseed
+daisy
+yellow lady's slipper
+corn
+acorn
+hip
+buckeye
+coral fungus
+agaric
+gyromitra
+stinkhorn
+earthstar
+hen-of-the-woods
+bolete
+ear
+toilet tissue
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/mobilenet_v1_1.0_224_info.txt b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/mobilenet_v1_1.0_224_info.txt
new file mode 100644
index 0000000..1a50fa03
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/assets/mobilenet_v1_1.0_224_info.txt
@@ -0,0 +1,3 @@
+Model: mobilenet_v1_1.0_224
+Input: input
+Output: MobilenetV1/Predictions/Reshape_1
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java
new file mode 100644
index 0000000..903f791
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/audio/TensorAudioTest.java
@@ -0,0 +1,285 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.audio;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.mockito.ArgumentMatchers.any;
+import static org.mockito.ArgumentMatchers.anyInt;
+import static org.mockito.ArgumentMatchers.eq;
+import static org.mockito.Mockito.mock;
+import static org.mockito.Mockito.when;
+
+import android.media.AudioFormat;
+import android.media.AudioRecord;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Suite;
+import org.junit.runners.Suite.SuiteClasses;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.support.audio.TensorAudio.TensorAudioFormat;
+
+/** Test for {@link TensorAudio}. */
+@RunWith(Suite.class)
+@SuiteClasses({
+        TensorAudioTest.General.class,
+})
+public class TensorAudioTest {
+    /** General tests of TensorAudio. */
+    @RunWith(RobolectricTestRunner.class)
+    public static final class General extends TensorAudioTest {
+        @Test
+        public void createSucceedsWithTensorAudioFormat() throws Exception {
+            TensorAudio tensor = TensorAudio.create(
+                    TensorAudioFormat.builder().setChannels(1).setSampleRate(2).build(), 100);
+            assertThat(tensor.getFormat().getChannels()).isEqualTo(1);
+            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(2);
+            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(100);
+        }
+
+        @Test
+        public void createSucceedsWithTensorAudioFormatWithMultipleChannels() throws Exception {
+            TensorAudio tensor = TensorAudio.create(
+                    TensorAudioFormat.builder().setChannels(5).setSampleRate(2).build(), 100);
+            assertThat(tensor.getFormat().getChannels()).isEqualTo(5);
+            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(2);
+            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(500);
+        }
+
+        @Test
+        public void createSucceededsWithDefaultArguments() throws Exception {
+            TensorAudio tensor =
+                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(20).build(), 1000);
+            // Number of channels defaults to 1.
+            assertThat(tensor.getFormat().getChannels()).isEqualTo(1);
+            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(20);
+            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(1000);
+        }
+
+        @Test
+        public void createSucceedsWithAudioFormat() throws Exception {
+            AudioFormat format = new AudioFormat.Builder()
+                                         .setChannelMask(AudioFormat.CHANNEL_IN_STEREO)
+                                         .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
+                                         .setSampleRate(16000)
+                                         .build();
+            TensorAudio tensor = TensorAudio.create(format, 100);
+            // STEREO has 2 channels
+            assertThat(tensor.getFormat().getChannels()).isEqualTo(2);
+            assertThat(tensor.getFormat().getSampleRate()).isEqualTo(16000);
+            // flatSize = channelCount * sampleCount
+            assertThat(tensor.getTensorBuffer().getFlatSize()).isEqualTo(200);
+        }
+
+        @Test
+        public void createFailedWithInvalidSampleRate() throws Exception {
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    ()
+                            -> TensorAudio.create(
+                                    TensorAudioFormat.builder().setSampleRate(0).build(), 100));
+            // Sample rate 0 is not allowed
+            assertThat(exception).hasMessageThat().ignoringCase().contains("sample rate");
+        }
+
+        @Test
+        public void createFailedWithInvalidChannels() throws Exception {
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    ()
+                            -> TensorAudio.create(TensorAudioFormat.builder()
+                                                          .setSampleRate(1)
+                                                          .setChannels(-1)
+                                                          .build(),
+                                    100));
+            // Negative channels is not allowed
+            assertThat(exception).hasMessageThat().ignoringCase().contains("channels");
+        }
+
+        @Test
+        public void loadSucceedsFromArray() throws Exception {
+            TensorAudioFormat format =
+                    TensorAudioFormat.builder().setChannels(2).setSampleRate(2).build();
+            TensorAudio tensor = TensorAudio.create(format, 2);
+            assertThat(tensor.getTensorBuffer().getFloatArray()).isEqualTo(new float[4]);
+
+            tensor.load(new float[] {2.f, 0});
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .usingTolerance(0.001f)
+                    .containsExactly(new float[] {0, 0, 2.f, 0});
+
+            tensor.load(new float[] {2.f, 3.f}, 0, 2);
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .usingTolerance(0.001f)
+                    .containsExactly(new float[] {2.f, 0, 2.f, 3.f});
+
+            tensor.load(new short[] {Short.MAX_VALUE, Short.MIN_VALUE});
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .usingTolerance(0.001f)
+                    .containsExactly(new float[] {2.f, 3.f, 1.f, -1.f});
+
+            tensor.load(new short[] {1, 2, 3, 0, 1, Short.MIN_VALUE, 3, 4, 5}, 3, 6);
+            // The entire sequence becomes {2.f, 0, 2.f, 3.f, 1.f, -1.f, 0, 0, -1.f, 0, 0, 0} but
+            // the ring buffer is only keep the last 4 results.
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .usingTolerance(0.001f)
+                    .containsExactly(new float[] {-1.f, 0, 0, 0});
+        }
+
+        @Test
+        public void loadFailsWithIndexOutOfRange() throws Exception {
+            TensorAudioFormat format = TensorAudioFormat.builder().setSampleRate(2).build();
+            TensorAudio tensor = TensorAudio.create(format, 5);
+
+            assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[100], 99, 2));
+
+            assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[100], 99, 2));
+        }
+
+        @Test
+        public void loadFailsWithIncompatibleInputSize() throws Exception {
+            TensorAudioFormat format =
+                    TensorAudioFormat.builder().setChannels(3).setSampleRate(2).build();
+            TensorAudio tensor = TensorAudio.create(format, 5);
+
+            assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[1]));
+
+            assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[2]));
+
+            assertThrows(IllegalArgumentException.class, () -> tensor.load(new float[2], 1, 1));
+
+            assertThrows(IllegalArgumentException.class, () -> tensor.load(new short[5], 2, 4));
+        }
+
+        @Test
+        public void loadAudioRecordSucceeds() throws Exception {
+            TensorAudio tensor =
+                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+            tensor.load(new float[] {1, 2, 3, 4, 5});
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .isEqualTo(new float[] {2.f, 3.f, 4.f, 5.f});
+
+            AudioRecord record = mock(AudioRecord.class);
+            when(record.getBufferSizeInFrames()).thenReturn(5);
+            when(record.getChannelCount()).thenReturn(1);
+            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_FLOAT);
+            when(record.getFormat())
+                    .thenReturn(new AudioFormat.Builder()
+                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+                                        .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
+                                        .setSampleRate(16000)
+                                        .build());
+            // Unused
+            when(record.read(
+                         any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+                    .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
+            // Used
+            when(record.read(
+                         any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+                    .thenReturn(1);
+            assertThat(tensor.load(record)).isEqualTo(1);
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .isEqualTo(new float[] {3.f, 4.f, 5.f, 0});
+
+            record = mock(AudioRecord.class);
+            when(record.getBufferSizeInFrames()).thenReturn(5);
+            when(record.getChannelCount()).thenReturn(1);
+            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_16BIT);
+            when(record.getFormat())
+                    .thenReturn(new AudioFormat.Builder()
+                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+                                        .setEncoding(AudioFormat.ENCODING_PCM_16BIT)
+                                        .setSampleRate(16000)
+                                        .build());
+            // Used
+            when(record.read(
+                         any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+                    .thenReturn(2);
+            // Unused
+            when(record.read(
+                         any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+                    .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
+            assertThat(tensor.load(record)).isEqualTo(2);
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .isEqualTo(new float[] {5.f, 0, 0, 0});
+        }
+
+        @Test
+        public void loadAudioRecordFailsWithErrorState() throws Exception {
+            TensorAudio tensor =
+                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+            tensor.load(new float[] {1, 2, 3, 4, 5});
+            assertThat(tensor.getTensorBuffer().getFloatArray())
+                    .isEqualTo(new float[] {2.f, 3.f, 4.f, 5.f});
+
+            AudioRecord record = mock(AudioRecord.class);
+            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_FLOAT);
+            when(record.getFormat())
+                    .thenReturn(new AudioFormat.Builder()
+                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+                                        .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
+                                        .setSampleRate(16000)
+                                        .build());
+            // Unused
+            when(record.read(
+                         any(short[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+                    .thenReturn(AudioRecord.ERROR_INVALID_OPERATION);
+            // Used
+            when(record.read(
+                         any(float[].class), anyInt(), anyInt(), eq(AudioRecord.READ_NON_BLOCKING)))
+                    .thenReturn(AudioRecord.ERROR_DEAD_OBJECT);
+            IllegalStateException exception =
+                    assertThrows(IllegalStateException.class, () -> tensor.load(record));
+            assertThat(exception).hasMessageThat().contains("ERROR_DEAD_OBJECT");
+        }
+
+        @Test
+        public void loadAudioRecordFailsWithUnsupportedAudioEncoding() throws Exception {
+            TensorAudio tensor =
+                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+            AudioRecord record = mock(AudioRecord.class);
+            when(record.getFormat())
+                    .thenReturn(new AudioFormat.Builder()
+                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+                                        .setEncoding(AudioFormat.ENCODING_PCM_8BIT) // Not supported
+                                        .setSampleRate(16000)
+                                        .build());
+            when(record.getAudioFormat()).thenReturn(AudioFormat.ENCODING_PCM_8BIT);
+
+            IllegalArgumentException exception =
+                    assertThrows(IllegalArgumentException.class, () -> tensor.load(record));
+            assertThat(exception).hasMessageThat().ignoringCase().contains("unsupported encoding");
+        }
+
+        @Test
+        public void loadAudioRecordFailsWithIncompatibleAudioFormat() throws Exception {
+            TensorAudio tensor =
+                    TensorAudio.create(TensorAudioFormat.builder().setSampleRate(16000).build(), 4);
+            AudioRecord record = mock(AudioRecord.class);
+            when(record.getFormat())
+                    .thenReturn(new AudioFormat.Builder()
+                                        .setChannelMask(AudioFormat.CHANNEL_IN_MONO)
+                                        .setEncoding(AudioFormat.ENCODING_PCM_FLOAT)
+                                        .setSampleRate(44100) // Mismatch
+                                        .build());
+
+            IllegalArgumentException exception =
+                    assertThrows(IllegalArgumentException.class, () -> tensor.load(record));
+            assertThat(exception).hasMessageThat().ignoringCase().contains(
+                    "Incompatible audio format");
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java
new file mode 100644
index 0000000..1d26476
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/FileUtilTest.java
@@ -0,0 +1,98 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import android.content.Context;
+
+import androidx.test.core.app.ApplicationProvider;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+import java.io.ByteArrayInputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.nio.MappedByteBuffer;
+import java.nio.charset.Charset;
+import java.util.List;
+
+/** Tests of {@link org.tensorflow.lite.support.common.FileUtil}. */
+@RunWith(RobolectricTestRunner.class)
+public final class FileUtilTest {
+    private final Context context = ApplicationProvider.getApplicationContext();
+    private static final String LABEL_PATH = "flower_labels.txt";
+
+    @Test
+    public void testLoadLabels() throws IOException {
+        List<String> labels = FileUtil.loadLabels(context, LABEL_PATH);
+        assertThat(labels)
+                .containsExactly("daisy", "dandelion", "roses", "sunflowers", "tulips")
+                .inOrder();
+    }
+
+    @Test
+    public void testLoadLabelsFromInputStream() throws IOException {
+        InputStream inputStream = context.getAssets().open(LABEL_PATH);
+        assertThat(FileUtil.loadLabels(inputStream))
+                .containsExactly("daisy", "dandelion", "roses", "sunflowers", "tulips")
+                .inOrder();
+    }
+
+    @Test
+    public void whitespaceLabelsShouldNotCount() throws IOException {
+        String s = "a\nb\n \n\n\nc";
+        InputStream stream = new ByteArrayInputStream(s.getBytes(Charset.defaultCharset()));
+        assertThat(FileUtil.loadLabels(stream)).hasSize(3);
+    }
+
+    @Test
+    public void testLoadLabelsNullContext() throws IOException {
+        Context nullContext = null;
+        Assert.assertThrows(
+                NullPointerException.class, () -> FileUtil.loadLabels(nullContext, LABEL_PATH));
+    }
+
+    @Test
+    public void testLoadLabelsNullFilePath() throws IOException {
+        String nullFilePath = null;
+        Assert.assertThrows(
+                NullPointerException.class, () -> FileUtil.loadLabels(context, nullFilePath));
+    }
+
+    @Test
+    public void testLoadMappedFile() throws IOException {
+        MappedByteBuffer byteModel = FileUtil.loadMappedFile(context, LABEL_PATH);
+        assertThat(byteModel).isNotNull();
+    }
+
+    @Test
+    public void testLoadMappedFileWithNullContext() throws IOException {
+        Context nullContext = null;
+        Assert.assertThrows(
+                NullPointerException.class, () -> FileUtil.loadMappedFile(nullContext, LABEL_PATH));
+    }
+
+    @Test
+    public void loadMappedFileWithNullFilePath() throws IOException {
+        String nullFilePath = null;
+        Assert.assertThrows(
+                NullPointerException.class, () -> FileUtil.loadMappedFile(context, nullFilePath));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java
new file mode 100644
index 0000000..82f97f25
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/TensorProcessorTest.java
@@ -0,0 +1,84 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.common.ops.NormalizeOp;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/** Tests for {@link TensorProcessor}. */
+@RunWith(RobolectricTestRunner.class)
+public final class TensorProcessorTest {
+    private static final int EXAMPLE_NUM_FEATURES = 1000;
+    private static final float MEAN = 127.5f;
+    private static final float STDDEV = 127.5f;
+
+    @Test
+    public void testBuild() {
+        TensorProcessor processor =
+                new TensorProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+        assertThat(processor).isNotNull();
+    }
+
+    @Test
+    public void testNormalize() {
+        TensorBuffer input = createExampleTensorBuffer();
+        TensorProcessor processor =
+                new TensorProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+        TensorBuffer output = processor.process(input);
+
+        float[] pixels = output.getFloatArray();
+        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_FEATURES);
+        for (float p : pixels) {
+            assertThat(p).isAtLeast(-1);
+            assertThat(p).isAtMost(1);
+        }
+    }
+
+    @Test
+    public void testMultipleNormalize() {
+        TensorBuffer input = createExampleTensorBuffer();
+        TensorProcessor processor =
+                new TensorProcessor.Builder()
+                        .add(new NormalizeOp(MEAN, STDDEV)) // [0, 255] -> [-1, 1]
+                        .add(new NormalizeOp(-1, 2)) // [-1, 1] -> [0, 1]
+                        .build();
+        TensorBuffer output = processor.process(input);
+
+        float[] pixels = output.getFloatArray();
+        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_FEATURES);
+        for (float p : pixels) {
+            assertThat(p).isAtLeast(0);
+            assertThat(p).isAtMost(1);
+        }
+    }
+
+    // Creates a TensorBuffer of size {1, 1000}, containing values in range [0, 255].
+    private static TensorBuffer createExampleTensorBuffer() {
+        TensorBuffer buffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+        int[] features = new int[EXAMPLE_NUM_FEATURES];
+        for (int i = 0; i < EXAMPLE_NUM_FEATURES; i++) {
+            features[i] = i % 256;
+        }
+        buffer.loadArray(features, new int[] {1, EXAMPLE_NUM_FEATURES});
+        return buffer;
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java
new file mode 100644
index 0000000..e8ba24d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/CastOpTest.java
@@ -0,0 +1,81 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/** Tests of {@link CastOp}. */
+@RunWith(RobolectricTestRunner.class)
+public final class CastOpTest {
+    private static final float[] FLOAT_ARRAY = new float[] {1.1f, 3.3f, 5.5f, 7.7f, 9.9f};
+    private static final float[] CASTED_FLOAT_ARRAY = new float[] {1.0f, 3.0f, 5.0f, 7.0f, 9.0f};
+    private static final int[] INT_ARRAY = new int[] {1, 3, 5, 7, 9};
+    private static final int[] SHAPE = new int[] {5};
+
+    @Test
+    public void castFloat32ToUint8ShouldSuccess() {
+        TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+        floatBuffer.loadArray(FLOAT_ARRAY, SHAPE);
+        CastOp op = new CastOp(DataType.UINT8);
+        TensorBuffer uint8Buffer = op.apply(floatBuffer);
+        assertThat(uint8Buffer.getDataType()).isEqualTo(DataType.UINT8);
+        assertThat(uint8Buffer.getIntArray()).isEqualTo(INT_ARRAY);
+    }
+
+    @Test
+    public void castUint8ToFloat32ShouldSuccess() {
+        TensorBuffer uint8Buffer = TensorBuffer.createDynamic(DataType.UINT8);
+        uint8Buffer.loadArray(INT_ARRAY, SHAPE);
+        CastOp op = new CastOp(DataType.FLOAT32);
+        TensorBuffer floatBuffer = op.apply(uint8Buffer);
+        assertThat(floatBuffer.getDataType()).isEqualTo(DataType.FLOAT32);
+        assertThat(floatBuffer.getFloatArray()).isEqualTo(CASTED_FLOAT_ARRAY);
+    }
+
+    @Test
+    public void castFloat32ToFloat32ShouldNotRecreate() {
+        TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+        floatBuffer.loadArray(FLOAT_ARRAY, SHAPE);
+        CastOp op = new CastOp(DataType.FLOAT32);
+        TensorBuffer newBuffer = op.apply(floatBuffer);
+        assertThat(newBuffer.getDataType()).isEqualTo(DataType.FLOAT32);
+        assertThat(newBuffer).isSameInstanceAs(floatBuffer);
+    }
+
+    @Test
+    public void castUint8ToUint8ShouldNotRecreate() {
+        TensorBuffer uint8Buffer = TensorBuffer.createDynamic(DataType.UINT8);
+        uint8Buffer.loadArray(INT_ARRAY, SHAPE);
+        CastOp op = new CastOp(DataType.UINT8);
+        TensorBuffer newBuffer = op.apply(uint8Buffer);
+        assertThat(newBuffer.getDataType()).isEqualTo(DataType.UINT8);
+        assertThat(newBuffer).isSameInstanceAs(uint8Buffer);
+    }
+
+    @Test
+    public void castToUnsupportedDataTypeShouldThrow() {
+        for (DataType type : new DataType[] {DataType.INT32, DataType.INT64, DataType.STRING}) {
+            Assert.assertThrows(IllegalArgumentException.class, () -> new CastOp(type));
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java
new file mode 100644
index 0000000..a69bcd7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/DequantizeOpTest.java
@@ -0,0 +1,40 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/** Tests of {@link DequantizeOp}. */
+@RunWith(RobolectricTestRunner.class)
+public final class DequantizeOpTest {
+    @Test
+    public void dequantizeShouldSucess() {
+        int[] originalData = new int[] {191, 159, 63, 127, 255, 0};
+        DequantizeOp op = new DequantizeOp(127.0f, 1.0f / 128);
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {6}, DataType.UINT8);
+        input.loadArray(originalData);
+        TensorBuffer dequantized = op.apply(input);
+        assertThat(dequantized.getDataType()).isEqualTo(DataType.FLOAT32);
+        assertThat(dequantized.getFloatArray())
+                .isEqualTo(new float[] {0.5f, 0.25f, -0.5f, 0, 1, -0.9921875f});
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java
new file mode 100644
index 0000000..aabc6be
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/NormalizeOpTest.java
@@ -0,0 +1,151 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.tensorflow.lite.DataType.FLOAT32;
+import static org.tensorflow.lite.DataType.UINT8;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/**
+ * Tests of {@link NormalizeOp}.
+ */
+@RunWith(RobolectricTestRunner.class)
+public final class NormalizeOpTest {
+    private static final float MEAN = 50;
+    private static final float STDDEV = 50;
+    private static final int NUM_ELEMENTS = 100;
+
+    @Test
+    public void testNormalizeIntBuffer() {
+        int[] inputArr = new int[NUM_ELEMENTS];
+        for (int i = 0; i < NUM_ELEMENTS; i++) {
+            inputArr[i] = i;
+        }
+        TensorBuffer input = TensorBuffer.createDynamic(DataType.UINT8);
+        input.loadArray(inputArr, new int[] {inputArr.length});
+        NormalizeOp op = new NormalizeOp(MEAN, STDDEV);
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(FLOAT32);
+        float[] outputArr = output.getFloatArray();
+        for (int i = 0; i < NUM_ELEMENTS; i++) {
+            assertThat(outputArr[i]).isEqualTo((inputArr[i] - MEAN) / STDDEV);
+        }
+    }
+
+    @Test
+    public void testNormalizeFloatBuffer() {
+        float[] inputArr = new float[NUM_ELEMENTS];
+        for (int i = 0; i < NUM_ELEMENTS; i++) {
+            inputArr[i] = i;
+        }
+        TensorBuffer input = TensorBuffer.createDynamic(FLOAT32);
+        input.loadArray(inputArr, new int[] {inputArr.length});
+        NormalizeOp op = new NormalizeOp(MEAN, STDDEV);
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(FLOAT32);
+        float[] outputArr = output.getFloatArray();
+        for (int i = 0; i < NUM_ELEMENTS; i++) {
+            assertThat(outputArr[i]).isEqualTo((inputArr[i] - MEAN) / STDDEV);
+        }
+    }
+
+    @Test
+    public void testZeroStddev() {
+        Assert.assertThrows(IllegalArgumentException.class, () -> new NormalizeOp(1, 0));
+    }
+
+    @Test
+    public void testIdentityShortcut() {
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+        NormalizeOp op = new NormalizeOp(0, 1);
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(UINT8);
+        assertThat(output).isSameInstanceAs(input);
+    }
+
+    @Test
+    public void testNormalizeOp_zeroMeanAndZeroStddev() {
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+        NormalizeOp op = new NormalizeOp(0, 0);
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(UINT8);
+        assertThat(output).isSameInstanceAs(input);
+    }
+
+    @Test
+    public void testNormalizeOp_zeroMeanAndInifityStddev() {
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+        NormalizeOp op = new NormalizeOp(0, Float.POSITIVE_INFINITY);
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(UINT8);
+        assertThat(output).isSameInstanceAs(input);
+    }
+
+    @Test
+    public void testMultiChannelNormalize() {
+        float[] inputArr = new float[NUM_ELEMENTS];
+        for (int i = 0; i < NUM_ELEMENTS; i++) {
+            inputArr[i] = i;
+        }
+        TensorBuffer input = TensorBuffer.createDynamic(FLOAT32);
+        input.loadArray(inputArr, new int[] {20, 5});
+        float[] means = new float[] {1, 2, 3, 4, 5};
+        float[] stddevs = new float[] {6, 7, 8, 9, 10};
+        NormalizeOp op = new NormalizeOp(means, stddevs);
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(FLOAT32);
+        float[] outputArr = output.getFloatArray();
+        for (int i = 0; i < NUM_ELEMENTS; i++) {
+            assertThat(outputArr[i]).isEqualTo((i - means[i % 5]) / stddevs[i % 5]);
+        }
+    }
+
+    @Test
+    public void testMultiChannelShortcut() {
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+        NormalizeOp op = new NormalizeOp(new float[] {0, 0, 0}, new float[] {1, 1, 1});
+        TensorBuffer output = op.apply(input);
+        assertThat(output.getDataType()).isEqualTo(UINT8);
+        assertThat(output).isSameInstanceAs(input);
+    }
+
+    @Test
+    public void testMismatchedNumbersOfMeansAndStddevs() {
+        Assert.assertThrows(IllegalArgumentException.class,
+                () -> new NormalizeOp(new float[] {2, 3}, new float[] {1}));
+    }
+
+    @Test
+    public void testMismatchedInputTensorChannelNum() {
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {3, 3}, UINT8);
+        NormalizeOp op = new NormalizeOp(new float[] {0, 0}, new float[] {1, 2});
+        Assert.assertThrows(IllegalArgumentException.class, () -> op.apply(input));
+    }
+
+    @Test
+    public void testAnyChannelInvalidStddev() {
+        Assert.assertThrows(IllegalArgumentException.class,
+                () -> new NormalizeOp(new float[] {2, 3}, new float[] {1, 0}));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java
new file mode 100644
index 0000000..519cd28
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/common/ops/QuantizeOpTest.java
@@ -0,0 +1,39 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.common.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/** Tests of {@link QuantizeOp}. */
+@RunWith(RobolectricTestRunner.class)
+public final class QuantizeOpTest {
+    @Test
+    public void quantizeShouldSuccess() {
+        float[] originalData = {0.5f, 0.25f, -0.5f, 0, 1, -0.9921875f}; // -0.9921875 == -127 / 128
+        QuantizeOp op = new QuantizeOp(127.0f, 1.0f / 128);
+        TensorBuffer input = TensorBuffer.createFixedSize(new int[] {6}, DataType.FLOAT32);
+        input.loadArray(originalData);
+        TensorBuffer quantized = op.apply(input);
+        assertThat(quantized.getDataType()).isEqualTo(DataType.FLOAT32);
+        assertThat(quantized.getIntArray()).isEqualTo(new int[] {191, 159, 63, 127, 255, 0});
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java
new file mode 100644
index 0000000..e8edb58
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/BoundingBoxUtilTest.java
@@ -0,0 +1,169 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import android.graphics.RectF;
+
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.BoundingBoxUtil.CoordinateType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.util.List;
+
+/** Tests of {@link BoundingBoxUtil}. */
+@RunWith(RobolectricTestRunner.class)
+public class BoundingBoxUtilTest {
+    private TensorBuffer tensorBuffer;
+
+    @Before
+    public void setUp() {
+        // 2 bounding boxes with additional batch dimension.
+        tensorBuffer = TensorBuffer.createFixedSize(new int[] {1, 2, 4}, DataType.FLOAT32);
+    }
+
+    @Test
+    public void convertDefaultRatioBoundaries() {
+        tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.75f, 0.8f, 0.5f, 0.0f, 1.0f, 1.0f});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
+                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 500, 400);
+
+        assertThat(boxList).hasSize(2);
+        assertThat(boxList.get(0)).isEqualTo(new RectF(100, 100, 300, 400));
+        assertThat(boxList.get(1)).isEqualTo(new RectF(200, 0, 400, 500));
+    }
+
+    @Test
+    public void convertComplexTensor() {
+        tensorBuffer = TensorBuffer.createFixedSize(new int[] {3, 4, 2}, DataType.FLOAT32);
+        tensorBuffer.loadArray(new float[] {// sub tensor 0
+                0, 1, 10, 11, 20, 21, 30, 31,
+                // sub tensor 1
+                100, 101, 110, 111, 120, 121, 130, 131,
+                // sub tensor 2
+                200, 201, 210, 211, 220, 221, 230, 231});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, 1,
+                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.PIXEL, 0, 0);
+
+        assertThat(boxList).hasSize(6);
+        assertThat(boxList.get(0)).isEqualTo(new RectF(0, 10, 20, 30));
+        assertThat(boxList.get(1)).isEqualTo(new RectF(1, 11, 21, 31));
+        assertThat(boxList.get(2)).isEqualTo(new RectF(100, 110, 120, 130));
+        assertThat(boxList.get(3)).isEqualTo(new RectF(101, 111, 121, 131));
+    }
+
+    @Test
+    public void convertIndexedRatioBoundaries() {
+        tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.75f, 0.8f, 0.5f, 0.0f, 1.0f, 1.0f});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {1, 0, 3, 2}, -1,
+                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 500, 400);
+
+        assertThat(boxList).hasSize(2);
+        assertThat(boxList.get(0)).isEqualTo(new RectF(80, 125, 320, 375));
+        assertThat(boxList.get(1)).isEqualTo(new RectF(0, 250, 400, 500));
+    }
+
+    @Test
+    public void convertPixelBoundaries() {
+        tensorBuffer.loadArray(new float[] {100, 100, 300, 400, 200, 0, 400, 500});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
+                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.PIXEL, 500, 400);
+
+        assertThat(boxList)
+                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+                .inOrder();
+    }
+
+    @Test
+    public void convertRatioUpperLeft() {
+        tensorBuffer.loadArray(new float[] {0.25f, 0.2f, 0.5f, 0.6f, 0.5f, 0.0f, 0.5f, 1.0f});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
+                BoundingBoxUtil.Type.UPPER_LEFT, CoordinateType.RATIO, 500, 400);
+
+        assertThat(boxList).hasSize(2);
+        assertThat(boxList)
+                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+                .inOrder();
+    }
+
+    @Test
+    public void convertPixelUpperLeft() {
+        tensorBuffer.loadArray(new float[] {100, 100, 200, 300, 200, 0, 200, 500});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
+                BoundingBoxUtil.Type.UPPER_LEFT, CoordinateType.PIXEL, 500, 400);
+
+        assertThat(boxList)
+                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+                .inOrder();
+    }
+
+    @Test
+    public void convertRatioCenter() {
+        tensorBuffer.loadArray(new float[] {0.5f, 0.5f, 0.5f, 0.6f, 0.75f, 0.5f, 0.5f, 1.0f});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
+                BoundingBoxUtil.Type.CENTER, CoordinateType.RATIO, 500, 400);
+
+        assertThat(boxList)
+                .containsExactly(new RectF(100, 99.99999f, 300, 400), new RectF(200, 0, 400, 500))
+                .inOrder();
+    }
+
+    @Test
+    public void convertPixelCenter() {
+        tensorBuffer.loadArray(new float[] {200, 250, 200, 300, 300, 250, 200, 500});
+
+        List<RectF> boxList = BoundingBoxUtil.convert(tensorBuffer, new int[] {0, 1, 2, 3}, -1,
+                BoundingBoxUtil.Type.CENTER, CoordinateType.PIXEL, 500, 400);
+
+        assertThat(boxList)
+                .containsExactly(new RectF(100, 100, 300, 400), new RectF(200, 0, 400, 500))
+                .inOrder();
+    }
+
+    @Test
+    public void convertTensorWithUnexpectedShapeShouldThrow() {
+        TensorBuffer badShapeTensor =
+                TensorBuffer.createFixedSize(new int[] {1, 5}, DataType.FLOAT32);
+
+        Assert.assertThrows(IllegalArgumentException.class,
+                ()
+                        -> BoundingBoxUtil.convert(badShapeTensor, new int[] {0, 1, 2, 3}, -1,
+                                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 300, 400));
+    }
+
+    @Test
+    public void convertIntTensorShouldThrow() {
+        TensorBuffer badTypeTensor = TensorBuffer.createFixedSize(new int[] {1, 4}, DataType.UINT8);
+
+        Assert.assertThrows(IllegalArgumentException.class,
+                ()
+                        -> BoundingBoxUtil.convert(badTypeTensor, new int[] {0, 1, 2, 3}, -1,
+                                BoundingBoxUtil.Type.BOUNDARIES, CoordinateType.RATIO, 300, 400));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java
new file mode 100644
index 0000000..329b5aa3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeInstrumentedTest.java
@@ -0,0 +1,49 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleBitmap;
+import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleTensorBuffer;
+
+import android.graphics.Bitmap;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.JUnit4;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+@RunWith(JUnit4.class)
+public final class ColorSpaceTypeInstrumentedTest {
+    @Test
+    public void convertTensorBufferToBitmapShouldSuccessWithGrayscaleWithUint8() {
+        TensorBuffer buffer = createGrayscaleTensorBuffer(DataType.UINT8, false);
+        Bitmap bitmap = ColorSpaceType.GRAYSCALE.convertTensorBufferToBitmap(buffer);
+
+        Bitmap expectedBitmap = createGrayscaleBitmap();
+        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+    }
+
+    @Test
+    public void convertTensorBufferToBitmapShouldSuccessWithGrayscaleWithFloat() {
+        TensorBuffer buffer = createGrayscaleTensorBuffer(DataType.FLOAT32, false);
+        Bitmap bitmap = ColorSpaceType.GRAYSCALE.convertTensorBufferToBitmap(buffer);
+
+        Bitmap expectedBitmap = createGrayscaleBitmap();
+        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java
new file mode 100644
index 0000000..9261225
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ColorSpaceTypeTest.java
@@ -0,0 +1,390 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.tensorflow.lite.support.image.TestImageCreator.createRgbBitmap;
+import static org.tensorflow.lite.support.image.TestImageCreator.createRgbTensorBuffer;
+
+import android.graphics.Bitmap;
+import android.graphics.Bitmap.Config;
+import android.graphics.ImageFormat;
+
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.rules.ErrorCollector;
+import org.junit.runner.RunWith;
+import org.junit.runners.Suite;
+import org.junit.runners.Suite.SuiteClasses;
+import org.robolectric.ParameterizedRobolectricTestRunner;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameter;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameters;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.util.Arrays;
+import java.util.Collection;
+
+/** Tests of {@link ImageConversions}. */
+@RunWith(Suite.class)
+@SuiteClasses({ColorSpaceTypeTest.ValidShapeTest.class, ColorSpaceTypeTest.InvalidShapeTest.class,
+        ColorSpaceTypeTest.BitmapConfigTest.class, ColorSpaceTypeTest.ImageFormatTest.class,
+        ColorSpaceTypeTest.YuvImageTest.class, ColorSpaceTypeTest.AssertNumElementsTest.class,
+        ColorSpaceTypeTest.General.class})
+public class ColorSpaceTypeTest {
+    /** Parameterized tests for valid shapes. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class ValidShapeTest extends ColorSpaceTypeTest {
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        /** The shape that matches the colorSpaceType. */
+        @Parameter(1)
+        public int[] validShape;
+
+        /** The height of validShape. */
+        @Parameter(2)
+        public int expectedHeight;
+
+        /** The width of validShape. */
+        @Parameter(3)
+        public int expectedWidth;
+
+        @Parameters(name = "colorSpaceType={0}; validShape={1}; height={2}; width={3}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 3}, 10, 20},
+                    {ColorSpaceType.RGB, new int[] {10, 20, 3}, 10, 20},
+                    {ColorSpaceType.GRAYSCALE, new int[] {10, 20}, 10, 20},
+                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 1}, 10, 20},
+            });
+        }
+
+        @Test
+        public void getHeightSucceedsWithValidShape() {
+            assertThat(colorSpaceType.getHeight(validShape)).isEqualTo(expectedHeight);
+        }
+
+        @Test
+        public void getWidthSucceedsWithValidShape() {
+            assertThat(colorSpaceType.getWidth(validShape)).isEqualTo(expectedWidth);
+        }
+    }
+
+    /** Parameterized tests for invalid shapes. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class InvalidShapeTest extends ColorSpaceTypeTest {
+        private static final String RGB_ASSERT_SHAPE_MESSAGE =
+                "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+                + " representing R, G, B in order. The provided image shape is ";
+        private static final String GRAYSCALE_ASSERT_SHAPE_MESSAGE =
+                "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+                + " shape is ";
+
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        /** The shape that does not match the colorSpaceType. */
+        @Parameter(1)
+        public int[] invalidShape;
+
+        @Parameter(2)
+        public String errorMessage;
+
+        @Parameters(name = "colorSpaceType={0}; invalidShape={1}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.RGB, new int[] {2, 10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, -10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, -20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {-10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, -20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {2, 10, 20},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 3},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {1, -10, 20},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, -20},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {10, 20, 4},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {10}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {-10, 20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {10, -20}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+            });
+        }
+
+        @Test
+        public void assertShapeFaislsWithInvalidShape() {
+            IllegalArgumentException exception = assertThrows(
+                    IllegalArgumentException.class, () -> colorSpaceType.assertShape(invalidShape));
+            assertThat(exception).hasMessageThat().contains(
+                    errorMessage + Arrays.toString(invalidShape));
+        }
+
+        @Test
+        public void getHeightFaislsWithInvalidShape() {
+            IllegalArgumentException exception = assertThrows(
+                    IllegalArgumentException.class, () -> colorSpaceType.getHeight(invalidShape));
+            assertThat(exception).hasMessageThat().contains(
+                    errorMessage + Arrays.toString(invalidShape));
+        }
+
+        @Test
+        public void getWidthFaislsWithInvalidShape() {
+            IllegalArgumentException exception = assertThrows(
+                    IllegalArgumentException.class, () -> colorSpaceType.getWidth(invalidShape));
+            assertThat(exception).hasMessageThat().contains(
+                    errorMessage + Arrays.toString(invalidShape));
+        }
+    }
+
+    /** Parameterized tests for Bitmap Config. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class BitmapConfigTest extends ColorSpaceTypeTest {
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        /** The Bitmap configuration match the colorSpaceType. */
+        @Parameter(1)
+        public Config config;
+
+        @Parameters(name = "colorSpaceType={0}; config={1}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.RGB, Config.ARGB_8888},
+                    {ColorSpaceType.GRAYSCALE, Config.ALPHA_8},
+            });
+        }
+
+        @Test
+        public void fromBitmapConfigSucceedsWithSupportedConfig() {
+            assertThat(ColorSpaceType.fromBitmapConfig(config)).isEqualTo(colorSpaceType);
+        }
+
+        @Test
+        public void toBitmapConfigSucceedsWithSupportedConfig() {
+            assertThat(colorSpaceType.toBitmapConfig()).isEqualTo(config);
+        }
+    }
+
+    /** Parameterized tests for ImageFormat. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class ImageFormatTest extends ColorSpaceTypeTest {
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        /** The ImageFormat that matches the colorSpaceType. */
+        @Parameter(1)
+        public int imageFormat;
+
+        @Parameters(name = "colorSpaceType={0}; imageFormat={1}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.NV21, ImageFormat.NV21},
+                    {ColorSpaceType.YV12, ImageFormat.YV12},
+                    {ColorSpaceType.YUV_420_888, ImageFormat.YUV_420_888},
+            });
+        }
+
+        @Test
+        public void fromImageFormatSucceedsWithSupportedImageFormat() {
+            assertThat(ColorSpaceType.fromImageFormat(imageFormat)).isEqualTo(colorSpaceType);
+        }
+    }
+
+    /** Parameterized tests for YUV image formats: NV12, NV21, YV12, YV21, YUV_420_888. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class YuvImageTest extends ColorSpaceTypeTest {
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        @Parameters(name = "colorSpaceType={0}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.NV12},
+                    {ColorSpaceType.NV21},
+                    {ColorSpaceType.YV12},
+                    {ColorSpaceType.YV21},
+                    {ColorSpaceType.YUV_420_888},
+            });
+        }
+
+        @Test
+        public void convertTensorBufferToBitmapShouldFail() {
+            UnsupportedOperationException exception =
+                    assertThrows(UnsupportedOperationException.class,
+                            ()
+                                    -> colorSpaceType.convertTensorBufferToBitmap(
+                                            TensorBuffer.createDynamic(DataType.FLOAT32)));
+            assertThat(exception).hasMessageThat().contains(
+                    "convertTensorBufferToBitmap() is unsupported for the color space type "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void getWidthShouldFail() {
+            UnsupportedOperationException exception =
+                    assertThrows(UnsupportedOperationException.class,
+                            () -> colorSpaceType.getWidth(new int[] {}));
+            assertThat(exception).hasMessageThat().contains(
+                    "getWidth() only supports RGB and GRAYSCALE formats, but not "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void getHeightShouldFail() {
+            UnsupportedOperationException exception =
+                    assertThrows(UnsupportedOperationException.class,
+                            () -> colorSpaceType.getHeight(new int[] {}));
+            assertThat(exception).hasMessageThat().contains(
+                    "getHeight() only supports RGB and GRAYSCALE formats, but not "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void assertShapeShouldFail() {
+            UnsupportedOperationException exception =
+                    assertThrows(UnsupportedOperationException.class,
+                            () -> colorSpaceType.assertShape(new int[] {}));
+            assertThat(exception).hasMessageThat().contains(
+                    "assertShape() only supports RGB and GRAYSCALE formats, but not "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void getChannelValueShouldFail() {
+            UnsupportedOperationException exception = assertThrows(
+                    UnsupportedOperationException.class, () -> colorSpaceType.getChannelValue());
+            assertThat(exception).hasMessageThat().contains(
+                    "getChannelValue() is unsupported for the color space type "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void getNormalizedShapeShouldFail() {
+            UnsupportedOperationException exception =
+                    assertThrows(UnsupportedOperationException.class,
+                            () -> colorSpaceType.getNormalizedShape(new int[] {}));
+            assertThat(exception).hasMessageThat().contains(
+                    "getNormalizedShape() is unsupported for the color space type "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void getShapeInfoMessageShouldFail() {
+            UnsupportedOperationException exception =
+                    assertThrows(UnsupportedOperationException.class,
+                            () -> colorSpaceType.getShapeInfoMessage());
+            assertThat(exception).hasMessageThat().contains(
+                    "getShapeInfoMessage() is unsupported for the color space type "
+                    + colorSpaceType.name());
+        }
+
+        @Test
+        public void toBitmapConfigShouldFail() {
+            UnsupportedOperationException exception = assertThrows(
+                    UnsupportedOperationException.class, () -> colorSpaceType.toBitmapConfig());
+            assertThat(exception).hasMessageThat().contains(
+                    "toBitmapConfig() is unsupported for the color space type "
+                    + colorSpaceType.name());
+        }
+    }
+
+    /** Parameterized tests for assertNumElements/getNumElements with all image formats. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class AssertNumElementsTest extends ColorSpaceTypeTest {
+        private static final int HEIGHT = 2;
+        private static final int WIDTH = 3;
+        private static final int LESS_NUM_ELEMENTS = 5; // less than expected
+        private static final int MORE_NUM_ELEMENTS = 20; // more than expected. OK.
+        @Rule
+        public ErrorCollector errorCollector = new ErrorCollector();
+
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        @Parameter(1)
+        public int expectedNumElements;
+
+        @Parameters(name = "colorSpaceType={0};expectedNumElements={1}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.RGB, 18},
+                    {ColorSpaceType.GRAYSCALE, 6},
+                    {ColorSpaceType.NV12, 10},
+                    {ColorSpaceType.NV21, 10},
+                    {ColorSpaceType.YV12, 10},
+                    {ColorSpaceType.YV21, 10},
+            });
+        }
+
+        @Test
+        public void getNumElementsShouldSucceedWithExpectedNumElements() {
+            assertThat(colorSpaceType.getNumElements(HEIGHT, WIDTH)).isEqualTo(expectedNumElements);
+        }
+
+        @Test
+        public void assertNumElementsShouldSucceedWithMoreNumElements() {
+            errorCollector.checkSucceeds(() -> {
+                colorSpaceType.assertNumElements(MORE_NUM_ELEMENTS, HEIGHT, WIDTH);
+                return null;
+            });
+        }
+
+        @Test
+        public void assertNumElementsShouldFailWithLessNumElements() {
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    () -> colorSpaceType.assertNumElements(LESS_NUM_ELEMENTS, HEIGHT, WIDTH));
+            assertThat(exception).hasMessageThat().contains(String.format(
+                    "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
+                            + " expected number of elements should be at least %d.",
+                    LESS_NUM_ELEMENTS, colorSpaceType.name(), HEIGHT, WIDTH, expectedNumElements));
+        }
+    }
+
+    /** General tests of ColorSpaceTypeTest. */
+    @RunWith(RobolectricTestRunner.class)
+    public static final class General extends ColorSpaceTypeTest {
+        @Test
+        public void convertTensorBufferToBitmapShouldSuccessWithRGB() {
+            TensorBuffer buffer = createRgbTensorBuffer(DataType.UINT8, false);
+            Bitmap bitmap = ColorSpaceType.RGB.convertTensorBufferToBitmap(buffer);
+
+            Bitmap expectedBitmap = createRgbBitmap();
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void fromBitmapConfigFailsWithUnsupportedConfig() {
+            Config unsupportedConfig = Config.ARGB_4444;
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    () -> ColorSpaceType.fromBitmapConfig(unsupportedConfig));
+            assertThat(exception).hasMessageThat().contains(
+                    "Bitmap configuration: " + unsupportedConfig + ", is not supported yet.");
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java
new file mode 100644
index 0000000..49efc427
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsInstrumentedTest.java
@@ -0,0 +1,234 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static android.graphics.Bitmap.Config.ARGB_8888;
+import static android.graphics.Color.BLACK;
+import static android.graphics.Color.BLUE;
+import static android.graphics.Color.GREEN;
+import static android.graphics.Color.RED;
+import static android.graphics.Color.WHITE;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.tensorflow.lite.support.image.ImageConversions.convertGrayscaleTensorBufferToBitmap;
+
+import android.content.Context;
+import android.content.res.AssetManager;
+import android.graphics.Bitmap;
+import android.graphics.BitmapFactory;
+import android.util.Log;
+
+import androidx.test.core.app.ApplicationProvider;
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Suite;
+import org.junit.runners.Suite.SuiteClasses;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.io.IOException;
+import java.util.Arrays;
+
+/** Instrumented unit test for {@link ImageConversions}. */
+@RunWith(Suite.class)
+@SuiteClasses({ImageConversionsInstrumentedTest.TensorBufferToBitmap.class,
+        ImageConversionsInstrumentedTest.BitmapToTensorBuffer.class})
+public class ImageConversionsInstrumentedTest {
+    /** Tests for the TensorBuffer data type and normalized form. */
+    // Note that parameterized test with android_library_instrumentation_tests is currently not
+    // supported internally.
+    @RunWith(AndroidJUnit4.class)
+    public static final class TensorBufferToBitmap extends ImageConversionsInstrumentedTest {
+        @Test
+        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithFloatNormalized() {
+            DataType dataType = DataType.FLOAT32;
+            boolean isNormalized = true;
+
+            TensorBuffer buffer =
+                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+
+            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithFloatUnnormalized() {
+            DataType dataType = DataType.FLOAT32;
+            boolean isNormalized = false;
+
+            TensorBuffer buffer =
+                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+
+            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithUint8Normalized() {
+            DataType dataType = DataType.UINT8;
+            boolean isNormalized = true;
+
+            TensorBuffer buffer =
+                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+
+            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void convertGrayscaleTensorBufferToBitmapShouldSuccessWithUint8Unnormalized() {
+            DataType dataType = DataType.UINT8;
+            boolean isNormalized = false;
+
+            TensorBuffer buffer =
+                    TestImageCreator.createGrayscaleTensorBuffer(dataType, isNormalized);
+            Bitmap bitmap = convertGrayscaleTensorBufferToBitmap(buffer);
+
+            Bitmap expectedBitmap = TestImageCreator.createGrayscaleBitmap();
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void
+        convertGrayscaleTensorBufferToBitmapShouldRejectBufferWithInvalidShapeWithFloat() {
+            DataType dataType = DataType.FLOAT32;
+            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10}, dataType);
+
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    () -> convertGrayscaleTensorBufferToBitmap(buffer));
+            assertThat(exception).hasMessageThat().contains(
+                    "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+                    + " shape is " + Arrays.toString(buffer.getShape()));
+        }
+
+        @Test
+        public void
+        convertGrayscaleTensorBufferToBitmapShouldRejectBufferWithInvalidShapeWithUint8() {
+            DataType dataType = DataType.UINT8;
+            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10}, dataType);
+
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    () -> convertGrayscaleTensorBufferToBitmap(buffer));
+            assertThat(exception).hasMessageThat().contains(
+                    "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+                    + " shape is " + Arrays.toString(buffer.getShape()));
+        }
+    }
+
+    /** BitmapToTensorBuffer tests of ImageConversionsInstrumentedTest. */
+    @RunWith(AndroidJUnit4.class)
+    public static final class BitmapToTensorBuffer extends ImageConversionsInstrumentedTest {
+        private Bitmap greyGrid;
+        private Bitmap colorGrid;
+        private TensorBuffer buffer;
+
+        static final String GREY_GRID_PATH = "grey_grid.png";
+        static final String COLOR_GRID_PATH = "color_grid.png";
+
+        @Before
+        public void loadAssets() {
+            Context context = ApplicationProvider.getApplicationContext();
+            AssetManager assetManager = context.getAssets();
+            try {
+                greyGrid = BitmapFactory.decodeStream(assetManager.open(GREY_GRID_PATH));
+                colorGrid = BitmapFactory.decodeStream(assetManager.open(COLOR_GRID_PATH));
+            } catch (IOException e) {
+                Log.e("Test", "Cannot load asset files");
+            }
+            Assert.assertEquals(ARGB_8888, greyGrid.getConfig());
+            Assert.assertEquals(ARGB_8888, colorGrid.getConfig());
+            buffer = TensorBuffer.createDynamic(DataType.UINT8);
+        }
+
+        @Test
+        public void testBitmapDimensionLayout() {
+            // This test is not only for proving the correctness of bitmap -> TensorBuffer
+            // conversion, but also for us to better understand how Android Bitmap is storing pixels
+            // - height first or width first. We use a black image which has a white corner to
+            // understand what happens. By setting up the correct loop to pass the test, we can
+            // reveal the order of pixels returned from `getPixels`. The result shows that Android
+            // stores bitmap in an h-first manner. The returned array of `getPixels` is like [ 1st
+            // row, 2nd row, ... ] which is the same with TFLite.
+            Assert.assertEquals(100, greyGrid.getWidth());
+            Assert.assertEquals(100, greyGrid.getHeight());
+            Assert.assertEquals(BLACK, greyGrid.getPixel(25, 25)); // left top
+            Assert.assertEquals(BLACK, greyGrid.getPixel(75, 25)); // right top
+            Assert.assertEquals(WHITE, greyGrid.getPixel(25, 75)); // left bottom
+            Assert.assertEquals(BLACK, greyGrid.getPixel(75, 75)); // right bottom
+
+            ImageConversions.convertBitmapToTensorBuffer(greyGrid, buffer);
+            Assert.assertArrayEquals(new int[] {100, 100, 3}, buffer.getShape());
+            Assert.assertEquals(DataType.UINT8, buffer.getDataType());
+
+            int[] pixels = buffer.getIntArray();
+            int index = 0;
+            for (int h = 0; h < 100; h++) {
+                for (int w = 0; w < 100; w++) {
+                    int expected = (w < 50 && h >= 50) ? 255 : 0;
+                    Assert.assertEquals(expected, pixels[index++]);
+                    Assert.assertEquals(expected, pixels[index++]);
+                    Assert.assertEquals(expected, pixels[index++]);
+                }
+            }
+        }
+
+        @Test
+        public void testBitmapARGB8888ChannelLayout() {
+            // This test is not only for proving the correctness of bitmap -> TensorBuffer
+            // conversion, but also for us to better understand how Android Bitmap is storing pixels
+            // - RGB channel or other possible ordering. We use an colored grid image to understand
+            // what happens. It's a simple grid image with 4 grid in different colors. Passed
+            // through our Bitmap -> TensorBuffer conversion which simply unpack channels from an
+            // integer returned from `getPixel`, its channel sequence could be revealed directly.
+            // The result shows that Android Bitmap has no magic when loading channels. If loading
+            // from PNG images, channel order still remains R-G-B.
+            Assert.assertEquals(100, colorGrid.getWidth());
+            Assert.assertEquals(100, colorGrid.getHeight());
+            Assert.assertEquals(BLUE, colorGrid.getPixel(25, 25)); // left top
+            Assert.assertEquals(BLACK, colorGrid.getPixel(75, 25)); // right top
+            Assert.assertEquals(GREEN, colorGrid.getPixel(25, 75)); // left bottom
+            Assert.assertEquals(RED, colorGrid.getPixel(75, 75)); // right bottom
+
+            ImageConversions.convertBitmapToTensorBuffer(colorGrid, buffer);
+            Assert.assertArrayEquals(new int[] {100, 100, 3}, buffer.getShape());
+            Assert.assertEquals(DataType.UINT8, buffer.getDataType());
+
+            int[] pixels = buffer.getIntArray();
+            Assert.assertArrayEquals(
+                    new int[] {0, 0, 255}, getChannels(pixels, 25, 25)); // left top
+            Assert.assertArrayEquals(new int[] {0, 0, 0}, getChannels(pixels, 25, 75)); // right top
+            Assert.assertArrayEquals(
+                    new int[] {0, 255, 0}, getChannels(pixels, 75, 25)); // left bottom
+            Assert.assertArrayEquals(
+                    new int[] {255, 0, 0}, getChannels(pixels, 75, 75)); // right bottom
+        }
+
+        /** Helper function only for {@link #testBitmapARGB8888ChannelLayout()}. */
+        private static int[] getChannels(int[] pixels, int h, int w) {
+            int id = (h * 100 + w) * 3;
+            return new int[] {pixels[id++], pixels[id++], pixels[id]};
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java
new file mode 100644
index 0000000..c91db9d1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageConversionsTest.java
@@ -0,0 +1,127 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.tensorflow.lite.support.image.ImageConversions.convertBitmapToTensorBuffer;
+import static org.tensorflow.lite.support.image.ImageConversions.convertRgbTensorBufferToBitmap;
+
+import android.graphics.Bitmap;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Suite;
+import org.junit.runners.Suite.SuiteClasses;
+import org.robolectric.ParameterizedRobolectricTestRunner;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameter;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameters;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.util.Arrays;
+import java.util.Collection;
+
+/** Tests of {@link ImageConversions}. */
+@RunWith(Suite.class)
+@SuiteClasses({ImageConversionsTest.TensorBufferToBitmap.class, ImageConversionsTest.General.class})
+public class ImageConversionsTest {
+    /** Parameterized tests for the TensorBuffer data type and normalized form. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class TensorBufferToBitmap extends ImageConversionsTest {
+        /** The data type that used to create the TensorBuffer. */
+        @Parameter(0)
+        public DataType dataType;
+
+        /** Indicates whether the shape is in the normalized form of (1, h, w, 3). */
+        @Parameter(1)
+        public boolean isNormalized;
+
+        @Parameters(name = "dataType={0}; isNormalized={1}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {DataType.FLOAT32, true},
+                    {DataType.UINT8, true},
+                    {DataType.FLOAT32, false},
+                    {DataType.UINT8, false},
+            });
+        }
+
+        @Test
+        public void convertRgbTensorBufferToBitmapShouldSuccess() {
+            TensorBuffer buffer = TestImageCreator.createRgbTensorBuffer(dataType, isNormalized);
+            Bitmap bitmap = convertRgbTensorBufferToBitmap(buffer);
+
+            Bitmap expectedBitmap = TestImageCreator.createRgbBitmap();
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void convertRgbTensorBufferToBitmapShouldRejectBufferWithInvalidShape() {
+            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {2, 5, 10, 3}, dataType);
+
+            IllegalArgumentException exception = assertThrows(
+                    IllegalArgumentException.class, () -> convertRgbTensorBufferToBitmap(buffer));
+            assertThat(exception).hasMessageThat().contains(
+                    "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+                    + " representing R, G, B in order. The provided image shape is "
+                    + Arrays.toString(buffer.getShape()));
+        }
+    }
+
+    /** General tests of ImageConversionsTest. */
+    @RunWith(RobolectricTestRunner.class)
+    public static final class General extends ImageConversionsTest {
+        private static final Bitmap rgbBitmap = TestImageCreator.createRgbBitmap();
+        private static final TensorBuffer rgbTensorBuffer =
+                TestImageCreator.createRgbTensorBuffer(DataType.UINT8, false);
+
+        @Test
+        public void convertBitmapToTensorBufferShouldSuccess() {
+            TensorBuffer intBuffer =
+                    TensorBuffer.createFixedSize(new int[] {10, 10, 3}, DataType.UINT8);
+            convertBitmapToTensorBuffer(rgbBitmap, intBuffer);
+            assertThat(areEqualIntTensorBuffer(intBuffer, rgbTensorBuffer)).isTrue();
+        }
+
+        @Test
+        public void convertBitmapToTensorBufferShouldThrowShapeNotExactlySame() {
+            TensorBuffer intBuffer =
+                    TensorBuffer.createFixedSize(new int[] {5, 20, 3}, DataType.UINT8);
+            Assert.assertThrows(IllegalArgumentException.class,
+                    () -> convertBitmapToTensorBuffer(rgbBitmap, intBuffer));
+        }
+
+        @Test
+        public void convertBitmapToTensorBufferShouldCastIntToFloatIfNeeded() {
+            TensorBuffer floatBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+            convertBitmapToTensorBuffer(rgbBitmap, floatBuffer);
+            assertThat(areEqualIntTensorBuffer(floatBuffer, rgbTensorBuffer)).isTrue();
+        }
+    }
+
+    private static boolean areEqualIntTensorBuffer(TensorBuffer tb1, TensorBuffer tb2) {
+        if (!Arrays.equals(tb1.getShape(), tb2.getShape())) {
+            return false;
+        }
+        int[] arr1 = tb1.getIntArray();
+        int[] arr2 = tb2.getIntArray();
+        return Arrays.equals(arr1, arr2);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java
new file mode 100644
index 0000000..e9cbfc1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorInstrumentedTest.java
@@ -0,0 +1,146 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import android.graphics.Bitmap;
+
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.ops.ResizeWithCropOrPadOp;
+import org.tensorflow.lite.support.image.ops.Rot90Op;
+
+/** Instrumented unit test for {@link ImageProcessor}. */
+@RunWith(AndroidJUnit4.class)
+public final class ImageProcessorInstrumentedTest {
+    private Bitmap exampleBitmap;
+    private TensorImage input;
+    private ImageProcessor processor;
+
+    private static final int EXAMPLE_WIDTH = 10;
+    private static final int EXAMPLE_HEIGHT = 15;
+
+    @Before
+    public void setUp() {
+        // The default number of rotation is once.
+        processor = new ImageProcessor.Builder().add(new Rot90Op()).build();
+        exampleBitmap = createExampleBitmap();
+        input = new TensorImage(DataType.UINT8);
+        input.load(exampleBitmap);
+    }
+
+    @Test
+    public void updateNumberOfRotations_rotateTwice() {
+        int numberOfRotations = 2;
+
+        processor.updateNumberOfRotations(numberOfRotations);
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertExampleBitmapWithTwoRotations(outputBitmap);
+    }
+
+    @Test
+    public void updateNumberOfRotationsWithOpIndex_rotateTwiceAndOpIndex0() {
+        int numberOfRotations = 2;
+        int occurrence = 0;
+
+        processor.updateNumberOfRotations(numberOfRotations, occurrence);
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertExampleBitmapWithTwoRotations(outputBitmap);
+    }
+
+    @Test
+    public void updateNumberOfRotationsWithOpIndex_negativeOpIndex() {
+        int numberOfRotations = 2;
+        int negativeOpIndex = -1;
+
+        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
+                () -> processor.updateNumberOfRotations(numberOfRotations, negativeOpIndex));
+        assertThat(exception).hasMessageThat().isEqualTo("occurrence (-1) must not be negative");
+    }
+
+    @Test
+    public void updateNumberOfRotationsWithOpIndex_occurrenceEqualToTheNumberOfRot90Op() {
+        int numberOfRotations = 2;
+        int occurrence = 1;
+
+        IndexOutOfBoundsException exception = assertThrows(IndexOutOfBoundsException.class,
+                () -> processor.updateNumberOfRotations(numberOfRotations, occurrence));
+        assertThat(exception).hasMessageThat().isEqualTo(
+                "occurrence (1) must be less than size (1)");
+    }
+
+    @Test
+    public void updateNumberOfRotationsWithOpIndex_noRot90OpIsAddedToImageProcessor() {
+        int numberOfRotations = 2;
+        int occurrence = 1;
+        // Add an op other than Rot90Op into ImageProcessor.
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new ResizeWithCropOrPadOp(5, 5)).build();
+
+        IllegalStateException exception = assertThrows(IllegalStateException.class,
+                () -> processor.updateNumberOfRotations(numberOfRotations, occurrence));
+        assertThat(exception).hasMessageThat().isEqualTo(
+                "The Rot90Op has not been added to the ImageProcessor.");
+    }
+
+    @Test
+    public void updateNumberOfRotationsWithOpIndex_twoRot90Ops() {
+        // The overall effect of the two rotations is equivalent to rotating for twice.
+        int numberOfRotations0 = 5;
+        int numberOfRotations1 = 1;
+
+        // Add two Rot90Ops into ImageProcessor.
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new Rot90Op()).add(new Rot90Op()).build();
+        processor.updateNumberOfRotations(numberOfRotations0, /*occurrence=*/0);
+        processor.updateNumberOfRotations(numberOfRotations1, /*occurrence=*/1);
+
+        TensorImage output = processor.process(input);
+        Bitmap outputBitmap = output.getBitmap();
+        assertExampleBitmapWithTwoRotations(outputBitmap);
+    }
+
+    private void assertExampleBitmapWithTwoRotations(Bitmap bitmapRotated) {
+        assertThat(bitmapRotated.getWidth()).isEqualTo(EXAMPLE_WIDTH);
+        assertThat(bitmapRotated.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
+        for (int i = 0; i < exampleBitmap.getWidth(); i++) {
+            for (int j = 0; j < exampleBitmap.getHeight(); j++) {
+                assertThat(exampleBitmap.getPixel(i, j))
+                        .isEqualTo(bitmapRotated.getPixel(
+                                EXAMPLE_WIDTH - 1 - i, EXAMPLE_HEIGHT - 1 - j));
+            }
+        }
+    }
+
+    private static Bitmap createExampleBitmap() {
+        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
+        }
+        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java
new file mode 100644
index 0000000..a93ba546
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ImageProcessorTest.java
@@ -0,0 +1,147 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import android.graphics.Bitmap;
+import android.graphics.RectF;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.common.ops.NormalizeOp;
+import org.tensorflow.lite.support.image.ops.ResizeOp;
+import org.tensorflow.lite.support.image.ops.ResizeOp.ResizeMethod;
+import org.tensorflow.lite.support.image.ops.ResizeWithCropOrPadOp;
+import org.tensorflow.lite.support.image.ops.Rot90Op;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+/** Tests for {@link ImageProcessor}. */
+@RunWith(RobolectricTestRunner.class)
+public final class ImageProcessorTest {
+    private static final int EXAMPLE_WIDTH = 10;
+    private static final int EXAMPLE_HEIGHT = 15;
+    private static final int EXAMPLE_NUM_PIXELS = EXAMPLE_HEIGHT * EXAMPLE_WIDTH;
+    private static final int EXAMPLE_NUM_CHANNELS = 3;
+    private static final float MEAN = 127.5f;
+    private static final float STDDEV = 127.5f;
+
+    @Test
+    public void testBuild() {
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+        assertThat(processor).isNotNull();
+    }
+
+    @Test
+    public void testNormalize() {
+        TensorImage input = new TensorImage(DataType.FLOAT32);
+        input.load(createExampleBitmap());
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new NormalizeOp(MEAN, STDDEV)).build();
+        TensorImage output = processor.process(input);
+
+        float[] pixels = output.getTensorBuffer().getFloatArray();
+        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_CHANNELS * EXAMPLE_NUM_PIXELS);
+        for (float p : pixels) {
+            assertThat(p).isAtLeast(-1);
+            assertThat(p).isAtMost(1);
+        }
+    }
+
+    @Test
+    public void testMultipleNormalize() {
+        TensorImage input = new TensorImage(DataType.FLOAT32);
+        input.load(createExampleBitmap());
+        ImageProcessor processor =
+                new ImageProcessor.Builder()
+                        .add(new NormalizeOp(MEAN, STDDEV)) // [0, 255] -> [-1, 1]
+                        .add(new NormalizeOp(-1, 2)) // [-1, 1] -> [0, 1]
+                        .build();
+        TensorImage output = processor.process(input);
+
+        float[] pixels = output.getTensorBuffer().getFloatArray();
+        assertThat(pixels.length).isEqualTo(EXAMPLE_NUM_CHANNELS * EXAMPLE_NUM_PIXELS);
+        for (float p : pixels) {
+            assertThat(p).isAtLeast(0);
+            assertThat(p).isAtMost(1);
+        }
+    }
+
+    @Test
+    public void inverseTransformRectCorrectly() {
+        ImageProcessor processor = new ImageProcessor.Builder()
+                                           .add(new ResizeOp(200, 300, ResizeMethod.BILINEAR))
+                                           .add(new ResizeWithCropOrPadOp(100, 200))
+                                           .add(new Rot90Op(1))
+                                           .add(new NormalizeOp(127, 128))
+                                           .build();
+        RectF transformed = new RectF(0, 50, 100, 150);
+        RectF original = processor.inverseTransform(transformed, 400, 600);
+        assertThat(original.top).isEqualTo(100);
+        assertThat(original.left).isEqualTo(200);
+        assertThat(original.right).isEqualTo(400);
+        assertThat(original.bottom).isEqualTo(300);
+    }
+
+    @Test
+    public void resizeShouldFailWithNonRgbImages() {
+        int[] data = new int[] {1, 2, 3};
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+        tensorBuffer.loadArray(data, new int[] {1, 3});
+        TensorImage image = new TensorImage();
+        image.load(tensorBuffer, ColorSpaceType.GRAYSCALE);
+
+        ImageProcessor processor = new ImageProcessor.Builder()
+                                           .add(new ResizeOp(200, 300, ResizeMethod.BILINEAR))
+                                           .build();
+
+        IllegalArgumentException exception =
+                assertThrows(IllegalArgumentException.class, () -> processor.process(image));
+        assertThat(exception).hasMessageThat().contains(
+                "Only RGB images are supported in ResizeOp, but not "
+                + image.getColorSpaceType().name());
+    }
+
+    @Test
+    public void normalizeShouldSuccessWithNonRgbImages() {
+        int[] data = new int[] {1, 2, 3};
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+        tensorBuffer.loadArray(data, new int[] {1, 3});
+        TensorImage image = new TensorImage();
+        image.load(tensorBuffer, ColorSpaceType.GRAYSCALE);
+
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new NormalizeOp(0.5f, 1f)).build();
+        TensorImage output = processor.process(image);
+
+        float[] pixels = output.getTensorBuffer().getFloatArray();
+        assertThat(pixels).isEqualTo(new float[] {0.5f, 1.5f, 2.5f});
+    }
+
+    private static Bitmap createExampleBitmap() {
+        int[] colors = new int[EXAMPLE_NUM_PIXELS];
+        for (int i = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
+        }
+
+        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java
new file mode 100644
index 0000000..e8caefc
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/MlImageAdapterTest.java
@@ -0,0 +1,181 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.mockito.Mockito.when;
+
+import android.graphics.Bitmap;
+import android.media.Image;
+
+import com.google.android.odml.image.BitmapMlImageBuilder;
+import com.google.android.odml.image.ByteBufferMlImageBuilder;
+import com.google.android.odml.image.MediaMlImageBuilder;
+import com.google.android.odml.image.MlImage;
+import com.google.android.odml.image.MlImage.ImageFormat;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Suite;
+import org.junit.runners.Suite.SuiteClasses;
+import org.mockito.Mock;
+import org.mockito.MockitoAnnotations;
+import org.robolectric.ParameterizedRobolectricTestRunner;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameter;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameters;
+import org.robolectric.RobolectricTestRunner;
+
+import java.io.IOException;
+import java.nio.ByteBuffer;
+import java.util.Arrays;
+import java.util.Collection;
+
+/** Test for {@link MlImageAdapter}. */
+@RunWith(Suite.class)
+@SuiteClasses({
+        MlImageAdapterTest.CreateTensorImageFromSupportedByteBufferMlImage.class,
+        MlImageAdapterTest.CreateTensorImageFromUnsupportedByteBufferMlImage.class,
+        MlImageAdapterTest.General.class,
+})
+public class MlImageAdapterTest {
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class CreateTensorImageFromSupportedByteBufferMlImage
+            extends MlImageAdapterTest {
+        @Parameter(0)
+        @ImageFormat
+        public int imageFormat;
+
+        @Parameter(1)
+        public ColorSpaceType colorSpaceType;
+
+        @Parameters(name = "imageFormat={0}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {MlImage.IMAGE_FORMAT_RGB, ColorSpaceType.RGB},
+                    {MlImage.IMAGE_FORMAT_ALPHA, ColorSpaceType.GRAYSCALE},
+                    {MlImage.IMAGE_FORMAT_NV21, ColorSpaceType.NV21},
+                    {MlImage.IMAGE_FORMAT_NV12, ColorSpaceType.NV12},
+                    {MlImage.IMAGE_FORMAT_YV12, ColorSpaceType.YV12},
+                    {MlImage.IMAGE_FORMAT_YV21, ColorSpaceType.YV21},
+            });
+        }
+
+        @Test
+        public void createTensorImageFrom_supportedByteBufferMlImage_succeeds() throws IOException {
+            ByteBuffer buffer = ByteBuffer.allocateDirect(6).asReadOnlyBuffer();
+            buffer.rewind();
+            MlImage image = new ByteBufferMlImageBuilder(buffer, 1, 2, imageFormat).build();
+
+            TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+
+            assertThat(tensorImage.getWidth()).isEqualTo(1);
+            assertThat(tensorImage.getHeight()).isEqualTo(2);
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(colorSpaceType);
+            assertThat(tensorImage.getBuffer().position()).isEqualTo(0);
+            assertThat(tensorImage.getBuffer()).isEquivalentAccordingToCompareTo(buffer);
+        }
+    }
+
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class CreateTensorImageFromUnsupportedByteBufferMlImage
+            extends MlImageAdapterTest {
+        @Parameter(0)
+        @ImageFormat
+        public int imageFormat;
+
+        @Parameters(name = "imageFormat={0}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {MlImage.IMAGE_FORMAT_RGBA},
+                    {MlImage.IMAGE_FORMAT_JPEG},
+                    {MlImage.IMAGE_FORMAT_YUV_420_888},
+                    {MlImage.IMAGE_FORMAT_UNKNOWN},
+            });
+        }
+
+        @Test
+        public void createTensorImageFrom_unsupportedByteBufferMlImage_throws() throws IOException {
+            ByteBuffer buffer = ByteBuffer.allocateDirect(6).asReadOnlyBuffer();
+            buffer.rewind();
+            MlImage image = new ByteBufferMlImageBuilder(buffer, 1, 2, imageFormat).build();
+
+            assertThrows(IllegalArgumentException.class,
+                    () -> MlImageAdapter.createTensorImageFrom(image));
+        }
+    }
+
+    @RunWith(RobolectricTestRunner.class)
+    public static final class General extends MlImageAdapterTest {
+        @Mock
+        Image mediaImageMock;
+
+        @Before
+        public void setUp() {
+            MockitoAnnotations.openMocks(this);
+        }
+
+        @Test
+        public void createTensorImageFrom_bitmapMlImage_succeeds() throws IOException {
+            Bitmap bitmap = Bitmap.createBitmap(
+                    new int[] {0xff000100, 0xff000001}, 1, 2, Bitmap.Config.ARGB_8888);
+            MlImage image = new BitmapMlImageBuilder(bitmap).build();
+            ByteBuffer expectedBuffer = ByteBuffer.allocateDirect(6);
+            for (byte b : new byte[] {0, 1, 0, 0, 0, 1}) {
+                expectedBuffer.put(b);
+            }
+            expectedBuffer.rewind();
+
+            TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+
+            assertThat(tensorImage.getWidth()).isEqualTo(1);
+            assertThat(tensorImage.getHeight()).isEqualTo(2);
+            assertThat(tensorImage.getBuffer().position()).isEqualTo(0);
+            assertThat(tensorImage.getBuffer()).isEquivalentAccordingToCompareTo(expectedBuffer);
+        }
+
+        @Test
+        public void createTensorImageFrom_yuv420888MediaImageMlImage_succeeds() throws IOException {
+            setUpMediaImageMock(mediaImageMock, android.graphics.ImageFormat.YUV_420_888, 1, 2);
+            MlImage image = new MediaMlImageBuilder(mediaImageMock).build();
+
+            TensorImage tensorImage = MlImageAdapter.createTensorImageFrom(image);
+
+            assertThat(tensorImage.getWidth()).isEqualTo(1);
+            assertThat(tensorImage.getHeight()).isEqualTo(2);
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.YUV_420_888);
+        }
+
+        @Test
+        public void createTensorImageFrom_nonYuv420888MediaImageMlImage_throws()
+                throws IOException {
+            setUpMediaImageMock(mediaImageMock, android.graphics.ImageFormat.YUV_422_888, 1, 2);
+            MlImage image = new MediaMlImageBuilder(mediaImageMock).build();
+
+            assertThrows(IllegalArgumentException.class,
+                    () -> MlImageAdapter.createTensorImageFrom(image));
+        }
+
+        private static void setUpMediaImageMock(
+                Image mediaImageMock, int imageFormat, int width, int height) {
+            when(mediaImageMock.getFormat()).thenReturn(imageFormat);
+            when(mediaImageMock.getWidth()).thenReturn(width);
+            when(mediaImageMock.getHeight()).thenReturn(height);
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java
new file mode 100644
index 0000000..83b54d0
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageInstrumentedTest.java
@@ -0,0 +1,142 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.tensorflow.lite.DataType.FLOAT32;
+import static org.tensorflow.lite.DataType.UINT8;
+import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleBitmap;
+import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleTensorBuffer;
+import static org.tensorflow.lite.support.image.TestImageCreator.createRgbBitmap;
+import static org.tensorflow.lite.support.image.TestImageCreator.createRgbTensorBuffer;
+
+import android.graphics.Bitmap;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.JUnit4;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+@RunWith(JUnit4.class)
+public final class TensorImageInstrumentedTest {
+    /**
+     * Difference between the pair of float and uint8 values. It is used to test the data
+     * conversion.
+     */
+    private static final float DELTA = 0.1f;
+
+    // Note that parameterized test with android_library_instrumentation_tests is currently not
+    // supported in internally.
+    @Test
+    public void loadAndGetBitmapSucceedsWithFloatBufferFloatImage() {
+        DataType tensorBufferDataType = FLOAT32;
+        DataType tensorImageDataType = FLOAT32;
+        boolean isNormalized = true;
+        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+
+        TensorBuffer tensorBuffer =
+                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+        TensorImage tensorImage = new TensorImage(tensorImageDataType);
+
+        tensorImage.load(tensorBuffer, colorSpaceType);
+        Bitmap bitmap = tensorImage.getBitmap();
+
+        Bitmap expectedBitmap = createBitmap(colorSpaceType);
+        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+    }
+
+    @Test
+    public void loadAndGetBitmapSucceedsWithFloatBufferUINT8Image() {
+        DataType tensorBufferDataType = FLOAT32;
+        DataType tensorImageDataType = UINT8;
+        boolean isNormalized = false;
+        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+
+        TensorBuffer tensorBuffer =
+                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+        TensorImage tensorImage = new TensorImage(tensorImageDataType);
+
+        tensorImage.load(tensorBuffer, colorSpaceType);
+        Bitmap bitmap = tensorImage.getBitmap();
+
+        Bitmap expectedBitmap = createBitmap(colorSpaceType);
+        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+    }
+
+    @Test
+    public void loadAndGetBitmapSucceedsWithUINT8BufferFloatImage() {
+        DataType tensorBufferDataType = UINT8;
+        DataType tensorImageDataType = FLOAT32;
+        boolean isNormalized = true;
+        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+
+        TensorBuffer tensorBuffer =
+                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+        TensorImage tensorImage = new TensorImage(tensorImageDataType);
+
+        tensorImage.load(tensorBuffer, colorSpaceType);
+        Bitmap bitmap = tensorImage.getBitmap();
+
+        Bitmap expectedBitmap = createBitmap(colorSpaceType);
+        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+    }
+
+    @Test
+    public void loadAndGetBitmapSucceedsWithUINT8BufferUINT8Image() {
+        DataType tensorBufferDataType = UINT8;
+        DataType tensorImageDataType = UINT8;
+        boolean isNormalized = false;
+        ColorSpaceType colorSpaceType = ColorSpaceType.GRAYSCALE;
+
+        TensorBuffer tensorBuffer =
+                createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+        TensorImage tensorImage = new TensorImage(tensorImageDataType);
+
+        tensorImage.load(tensorBuffer, colorSpaceType);
+        Bitmap bitmap = tensorImage.getBitmap();
+
+        Bitmap expectedBitmap = createBitmap(colorSpaceType);
+        assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+    }
+
+    private static TensorBuffer createTensorBuffer(
+            DataType dataType, boolean isNormalized, ColorSpaceType colorSpaceType, float delta) {
+        switch (colorSpaceType) {
+            case RGB:
+                return createRgbTensorBuffer(dataType, isNormalized, delta);
+            case GRAYSCALE:
+                return createGrayscaleTensorBuffer(dataType, isNormalized, delta);
+            default:
+                break;
+        }
+        throw new IllegalArgumentException(
+                "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+    }
+
+    private static Bitmap createBitmap(ColorSpaceType colorSpaceType) {
+        switch (colorSpaceType) {
+            case RGB:
+                return createRgbBitmap();
+            case GRAYSCALE:
+                return createGrayscaleBitmap();
+            default:
+                break;
+        }
+        throw new IllegalArgumentException(
+                "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java
new file mode 100644
index 0000000..b3130f4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TensorImageTest.java
@@ -0,0 +1,735 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertArrayEquals;
+import static org.junit.Assert.assertThrows;
+import static org.mockito.Mockito.when;
+import static org.tensorflow.lite.DataType.FLOAT32;
+import static org.tensorflow.lite.DataType.UINT8;
+import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleBitmap;
+import static org.tensorflow.lite.support.image.TestImageCreator.createGrayscaleTensorBuffer;
+import static org.tensorflow.lite.support.image.TestImageCreator.createRgbBitmap;
+import static org.tensorflow.lite.support.image.TestImageCreator.createRgbTensorBuffer;
+
+import android.graphics.Bitmap;
+import android.graphics.Bitmap.Config;
+import android.graphics.Color;
+import android.graphics.ImageFormat;
+import android.media.Image;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Suite;
+import org.junit.runners.Suite.SuiteClasses;
+import org.mockito.Mock;
+import org.mockito.MockitoAnnotations;
+import org.robolectric.ParameterizedRobolectricTestRunner;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameter;
+import org.robolectric.ParameterizedRobolectricTestRunner.Parameters;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.nio.ByteBuffer;
+import java.util.Arrays;
+import java.util.Collection;
+
+/** Tests of {@link org.tensorflow.lite.support.image.TensorImage}. */
+@RunWith(Suite.class)
+@SuiteClasses(
+        {TensorImageTest.General.class, TensorImageTest.LoadTensorBufferWithRgbAndGrayscale.class,
+                TensorImageTest.LoadTensorBufferWithInvalidShapeTest.class,
+                TensorImageTest.LoadTensorBufferWithYUV.class,
+                TensorImageTest.LoadTensorBufferWithImageProperties.class})
+public class TensorImageTest {
+    @RunWith(RobolectricTestRunner.class)
+    public static final class General extends TensorImageTest {
+        private static final Bitmap exampleBitmap = createExampleBitmap();
+        private static final float[] exampleFloatPixels = createExampleFloatPixels();
+        private static final int[] exampleUint8Pixels = createExampleUint8Pixels();
+
+        private static final int EXAMPLE_WIDTH = 5;
+        private static final int EXAMPLE_HEIGHT = 10;
+        private static final int EXAMPLE_NUM_PIXELS = EXAMPLE_HEIGHT * EXAMPLE_WIDTH;
+        private static final int EXAMPLE_NUM_CHANNELS = 3;
+        private static final int[] EXAMPLE_SHAPE = {
+                EXAMPLE_HEIGHT, EXAMPLE_WIDTH, EXAMPLE_NUM_CHANNELS};
+        private static final float MEAN = 127.5f;
+        private static final float STDDEV = 127.5f;
+
+        @Mock
+        Image imageMock;
+
+        @Before
+        public void setUp() {
+            MockitoAnnotations.initMocks(this);
+        }
+
+        @Test
+        public void defaultConstructorCreatesUint8TensorImage() {
+            TensorImage image = new TensorImage();
+            assertThat(image.getDataType()).isEqualTo(UINT8);
+        }
+
+        @Test
+        public void createFromSucceedsWithUint8TensorImage() {
+            TensorImage uint8Image = new TensorImage(UINT8);
+            uint8Image.load(new int[] {1, 2, 3, 4, -5, 600}, new int[] {2, 1, 3});
+
+            TensorImage floatImage = TensorImage.createFrom(uint8Image, FLOAT32);
+            float[] pixels = floatImage.getTensorBuffer().getFloatArray();
+            assertThat(pixels).isEqualTo(new float[] {1.0f, 2.0f, 3.0f, 4.0f, 0.0f, 255.0f});
+        }
+
+        @Test
+        public void createFromSucceedsWithFloatTensorImage() {
+            TensorImage floatImage = new TensorImage(FLOAT32);
+            floatImage.load(new float[] {1, 2.495f, 3.5f, 4.5f, -5, 600}, new int[] {2, 1, 3});
+
+            TensorImage uint8Image = TensorImage.createFrom(floatImage, UINT8);
+            int[] pixels = uint8Image.getTensorBuffer().getIntArray();
+            assertThat(pixels).isEqualTo(new int[] {1, 2, 3, 4, 0, 255});
+        }
+
+        @Test
+        public void loadBitmapSucceedsWithUint8TensorImage() {
+            Bitmap rgbBitmap = createRgbBitmap();
+            TensorBuffer rgbTensorBuffer = createRgbTensorBuffer(UINT8, false, 0.0f);
+            TensorImage uint8Image = new TensorImage(UINT8);
+
+            uint8Image.load(rgbBitmap);
+            assertThat(uint8Image.getBitmap().sameAs(rgbBitmap)).isTrue();
+            assertEqualTensorBuffers(uint8Image.getTensorBuffer(), rgbTensorBuffer);
+            assertThat(uint8Image.getDataType()).isEqualTo(UINT8);
+        }
+
+        @Test
+        public void loadBitmapSucceedsWithFloatTensorImage() {
+            Bitmap rgbBitmap = createRgbBitmap();
+            TensorBuffer rgbTensorBuffer = createRgbTensorBuffer(FLOAT32, false, 0.0f);
+            TensorImage floatImage = new TensorImage(FLOAT32);
+
+            floatImage.load(rgbBitmap);
+            assertThat(floatImage.getBitmap().sameAs(rgbBitmap)).isTrue();
+            assertEqualTensorBuffers(floatImage.getTensorBuffer(), rgbTensorBuffer);
+            assertThat(floatImage.getDataType()).isEqualTo(FLOAT32);
+        }
+
+        @Test
+        public void loadFloatArrayWithUint8TensorImage() {
+            TensorImage uint8Image = new TensorImage(UINT8);
+
+            uint8Image.load(exampleFloatPixels, EXAMPLE_SHAPE);
+            assertThat(uint8Image.getBitmap()).isNotNull();
+            assertThat(uint8Image.getTensorBuffer().getFloatArray())
+                    .isEqualTo(new float[exampleFloatPixels.length]); // All zero because of
+                                                                      // normalization and casting
+                                                                      // when loading.
+        }
+
+        @Test
+        public void loadFloatArrayWithFloatTensorImage() {
+            TensorImage floatImage = new TensorImage(FLOAT32);
+
+            floatImage.load(exampleFloatPixels, EXAMPLE_SHAPE);
+            assertThat(floatImage.getTensorBuffer().getFloatArray()).isEqualTo(exampleFloatPixels);
+        }
+
+        @Test
+        public void loadUint8ArrayWithUint8TensorImage() {
+            TensorImage uint8Image = new TensorImage(UINT8);
+
+            uint8Image.load(exampleUint8Pixels, EXAMPLE_SHAPE);
+            assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
+            assertThat(uint8Image.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
+        }
+
+        @Test
+        public void loadUint8ArrayWithFloatTensorImage() {
+            TensorImage floatImage = new TensorImage(FLOAT32);
+
+            floatImage.load(exampleUint8Pixels, EXAMPLE_SHAPE);
+            assertThat(floatImage.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
+        }
+
+        @Test
+        public void loadTensorBufferWithUint8TensorImage() {
+            TensorImage uint8Image = new TensorImage(UINT8);
+
+            uint8Image.load(exampleBitmap);
+            TensorBuffer buffer = uint8Image.getTensorBuffer();
+            uint8Image.load(buffer);
+            assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
+        }
+
+        @Test
+        public void loadTensorBufferWithFloatTensorImage() {
+            TensorImage floatImage = new TensorImage(FLOAT32);
+
+            floatImage.load(exampleBitmap);
+            TensorBuffer buffer = floatImage.getTensorBuffer();
+            floatImage.load(buffer);
+            assertThat(floatImage.getTensorBuffer().getIntArray()).isEqualTo(exampleUint8Pixels);
+        }
+
+        @Test
+        public void loadAndGetMediaImageSucceedsWithYuv420888Format() {
+            setUpImageMock(imageMock, ImageFormat.YUV_420_888);
+            TensorImage tensorImage = new TensorImage(UINT8);
+
+            tensorImage.load(imageMock);
+            Image imageReturned = tensorImage.getMediaImage();
+
+            assertThat(imageReturned).isEqualTo(imageMock);
+        }
+
+        @Test
+        public void loadMediaImageFailsWithNonYuv420888Format() {
+            setUpImageMock(imageMock, ImageFormat.YUV_422_888);
+            TensorImage tensorImage = new TensorImage(UINT8);
+
+            IllegalArgumentException exception =
+                    assertThrows(IllegalArgumentException.class, () -> tensorImage.load(imageMock));
+            assertThat(exception).hasMessageThat().contains(
+                    "Only supports loading YUV_420_888 Image.");
+        }
+
+        @Test
+        public void getBitmapWithUint8TensorImage() {
+            TensorImage uint8Image = new TensorImage(UINT8);
+
+            uint8Image.load(exampleBitmap);
+            assertThat(uint8Image.getBitmap().sameAs(exampleBitmap)).isTrue();
+            // Also check zero copy is effective here (input and output are references of the same
+            // object).
+            assertThat(uint8Image.getBitmap()).isSameInstanceAs(exampleBitmap);
+            // Also check we don't create new Bitmap only with reading operations.
+            assertThat(uint8Image.getBuffer().limit())
+                    .isEqualTo(EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS);
+            assertThat(uint8Image.getBitmap()).isSameInstanceAs(exampleBitmap);
+
+            uint8Image.load(exampleUint8Pixels, EXAMPLE_SHAPE);
+            assertThat(uint8Image.getBitmap()).isNotSameInstanceAs(exampleBitmap);
+        }
+
+        @Test
+        public void getBitmapWithFloatTensorImage() {
+            TensorImage floatImage = new TensorImage(FLOAT32);
+
+            floatImage.load(exampleBitmap);
+            assertThat(floatImage.getBitmap()).isSameInstanceAs(exampleBitmap);
+        }
+
+        @Test
+        public void getBitmapWithEmptyTensorImage() {
+            TensorImage uint8Image = new TensorImage(UINT8);
+
+            assertThrows(IllegalStateException.class, uint8Image::getBitmap);
+        }
+
+        @Test
+        public void getMediaImageFailsWithBackedBitmap() {
+            TensorImage tensorImage = TensorImage.fromBitmap(exampleBitmap);
+
+            UnsupportedOperationException exception = assertThrows(
+                    UnsupportedOperationException.class, () -> tensorImage.getMediaImage());
+            assertThat(exception).hasMessageThat().contains(
+                    "Converting from Bitmap to android.media.Image is unsupported.");
+        }
+
+        @Test
+        public void getMediaImageFailsWithBackedTensorBuffer() {
+            TensorImage tensorImage = new TensorImage(UINT8);
+            tensorImage.load(exampleFloatPixels, EXAMPLE_SHAPE);
+
+            UnsupportedOperationException exception = assertThrows(
+                    UnsupportedOperationException.class, () -> tensorImage.getMediaImage());
+            assertThat(exception).hasMessageThat().contains(
+                    "Converting from TensorBuffer to android.media.Image is unsupported.");
+        }
+
+        @Test
+        public void getShapeOfInternalBitmapShouldSuccess() {
+            Bitmap bitmap = Bitmap.createBitmap(300, 400, Config.ARGB_8888);
+            TensorImage image = TensorImage.fromBitmap(bitmap);
+
+            int width = image.getWidth();
+            int height = image.getHeight();
+
+            assertThat(width).isEqualTo(300);
+            assertThat(height).isEqualTo(400);
+        }
+
+        @Test
+        public void getShapeOfInternalTensorBufferShouldSuccess() {
+            TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {1, 400, 300, 3}, UINT8);
+            TensorImage image = new TensorImage();
+            image.load(buffer);
+
+            int width = image.getWidth();
+            int height = image.getHeight();
+
+            assertThat(width).isEqualTo(300);
+            assertThat(height).isEqualTo(400);
+        }
+
+        @Test
+        public void getShapeOfNullImageShouldThrow() {
+            TensorImage image = new TensorImage();
+
+            assertThrows(IllegalStateException.class, image::getHeight);
+        }
+
+        @Test
+        public void getShapeOfACorruptedBufferShouldThrowRatherThanCrash() {
+            int[] data = new int[] {1, 2, 3, 4, 5, 6};
+            TensorBuffer buffer = TensorBuffer.createDynamic(UINT8);
+            buffer.loadArray(data, new int[] {1, 1, 2, 3});
+            TensorImage image = new TensorImage();
+            image.load(buffer);
+            // Reload data but with an invalid shape, which leads to `buffer` corrupted.
+            int[] newData = new int[] {1, 2, 3};
+            buffer.loadArray(newData, new int[] {1, 1, 1, 3});
+
+            assertThrows(IllegalArgumentException.class, image::getHeight);
+        }
+
+        @Test
+        public void getColorSpaceTypeSucceedsWithBitmapARGB_8888() {
+            Bitmap rgbBitmap = createRgbBitmap();
+            TensorImage tensorImage = TensorImage.fromBitmap(rgbBitmap);
+
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+        }
+
+        @Test
+        public void getColorSpaceTypeSucceedsWithRgbTensorBuffer() {
+            TensorBuffer rgbBuffer = createRgbTensorBuffer(UINT8, false);
+            TensorImage tensorImage = new TensorImage();
+            tensorImage.load(rgbBuffer);
+
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+        }
+
+        @Test
+        public void getColorSpaceTypeSucceedsWithGrayscaleTensorBuffer() {
+            TensorBuffer grayBuffer = createGrayscaleTensorBuffer(UINT8, false);
+            TensorImage tensorImage = new TensorImage();
+            tensorImage.load(grayBuffer, ColorSpaceType.GRAYSCALE);
+
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
+        }
+
+        @Test
+        public void getColorSpaceTypeSucceedsWithRepeatedLoading() {
+            TensorBuffer grayBuffer = createGrayscaleTensorBuffer(UINT8, false);
+            TensorBuffer rgbBuffer = createRgbTensorBuffer(UINT8, false);
+            Bitmap rgbBitmap = createRgbBitmap();
+            TensorImage tensorImage = new TensorImage();
+
+            tensorImage.load(rgbBuffer);
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+            tensorImage.load(grayBuffer, ColorSpaceType.GRAYSCALE);
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
+            tensorImage.load(rgbBitmap);
+            assertThat(tensorImage.getColorSpaceType()).isEqualTo(ColorSpaceType.RGB);
+        }
+
+        @Test
+        public void getColorSpaceTypeFailsWhenNoImageHasBeenLoaded() {
+            TensorImage tensorImage = new TensorImage();
+
+            IllegalStateException exception =
+                    assertThrows(IllegalStateException.class, tensorImage::getColorSpaceType);
+            assertThat(exception).hasMessageThat().contains("No image has been loaded yet.");
+        }
+
+        /**
+         * Creates an example bit map, which is a 10x10 ARGB bitmap and pixels are set by: pixel[i]
+         * = {A: 0, B: i + 2, G: i + 1, G: i}, where i is the flatten index
+         */
+        private static Bitmap createExampleBitmap() {
+            int[] colors = new int[EXAMPLE_NUM_PIXELS];
+            for (int i = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+                colors[i] = Color.rgb(i, i + 1, i + 2);
+            }
+
+            return Bitmap.createBitmap(
+                    colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+        }
+
+        private static float[] createExampleFloatPixels() {
+            float[] pixels = new float[EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS];
+            for (int i = 0, j = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+                pixels[j++] = (i - MEAN) / STDDEV;
+                pixels[j++] = (i + 1 - MEAN) / STDDEV;
+                pixels[j++] = (i + 2 - MEAN) / STDDEV;
+            }
+            return pixels;
+        }
+
+        private static int[] createExampleUint8Pixels() {
+            int[] pixels = new int[EXAMPLE_NUM_PIXELS * EXAMPLE_NUM_CHANNELS];
+            for (int i = 0, j = 0; i < EXAMPLE_NUM_PIXELS; i++) {
+                pixels[j++] = i;
+                pixels[j++] = i + 1;
+                pixels[j++] = i + 2;
+            }
+            return pixels;
+        }
+    }
+
+    /** Parameterized tests for loading TensorBuffers with RGB and Grayscale images. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class LoadTensorBufferWithRgbAndGrayscale extends TensorImageTest {
+        /**
+         * Difference between the pair of float and uint8 values. It is used to test the data
+         * conversion.
+         */
+        private static final float DELTA = 0.1f;
+
+        /** The data type that used to create the TensorBuffer. */
+        @Parameter(0)
+        public DataType tensorBufferDataType;
+
+        /** Indicates whether the shape is in the normalized form of (1, h, w, 3). */
+        @Parameter(1)
+        public boolean isNormalized;
+
+        /** The color space type of the TensorBuffer. */
+        @Parameter(2)
+        public ColorSpaceType colorSpaceType;
+
+        /** The data type that used to create the TensorImage. */
+        @Parameter(3)
+        public DataType tensorImageDataType;
+
+        @Parameters(name = "tensorBufferDataType={0}; isNormalized={1}; colorSpaceType={2};"
+                        + " tensorImageDataType={3}")
+        public static Collection<Object[]>
+        data() {
+            return Arrays.asList(new Object[][] {
+                    {FLOAT32, true, ColorSpaceType.RGB, FLOAT32},
+                    {FLOAT32, false, ColorSpaceType.RGB, UINT8},
+                    {UINT8, true, ColorSpaceType.RGB, FLOAT32},
+                    {UINT8, false, ColorSpaceType.RGB, UINT8},
+            });
+        }
+
+        @Test
+        public void loadAndGetBitmapSucceedsWithTensorBufferAndColorSpaceType() {
+            TensorBuffer tensorBuffer =
+                    createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+            TensorImage tensorImage = new TensorImage(tensorImageDataType);
+
+            tensorImage.load(tensorBuffer, colorSpaceType);
+            Bitmap bitmap = tensorImage.getBitmap();
+
+            Bitmap expectedBitmap = createBitmap(colorSpaceType);
+            assertThat(bitmap.sameAs(expectedBitmap)).isTrue();
+        }
+
+        @Test
+        public void loadAndGetTensorBufferSucceedsWithTensorBufferAndColorSpaceType() {
+            TensorBuffer tensorBuffer =
+                    createTensorBuffer(tensorBufferDataType, isNormalized, colorSpaceType, DELTA);
+            TensorImage tensorImage = new TensorImage(tensorImageDataType);
+
+            tensorImage.load(tensorBuffer, colorSpaceType);
+            TensorBuffer buffer = tensorImage.getTensorBuffer();
+
+            // If tensorBufferDataType is UINT8, expectedTensorBuffer should not contain delta.
+            float expectedResidual = tensorBufferDataType == UINT8 ? 0.f : DELTA;
+            TensorBuffer expectedTensorBuffer = createTensorBuffer(
+                    tensorImageDataType, isNormalized, colorSpaceType, expectedResidual);
+            assertEqualTensorBuffers(buffer, expectedTensorBuffer);
+        }
+
+        private static TensorBuffer createTensorBuffer(DataType dataType, boolean isNormalized,
+                ColorSpaceType colorSpaceType, float delta) {
+            switch (colorSpaceType) {
+                case RGB:
+                    return createRgbTensorBuffer(dataType, isNormalized, delta);
+                case GRAYSCALE:
+                    return createGrayscaleTensorBuffer(dataType, isNormalized, delta);
+                default:
+                    break;
+            }
+            throw new IllegalArgumentException(
+                    "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+        }
+
+        private static Bitmap createBitmap(ColorSpaceType colorSpaceType) {
+            switch (colorSpaceType) {
+                case RGB:
+                    return createRgbBitmap();
+                case GRAYSCALE:
+                    return createGrayscaleBitmap();
+                default:
+                    break;
+            }
+            throw new IllegalArgumentException(
+                    "The ColorSpaceType, " + colorSpaceType + ", is unsupported.");
+        }
+    }
+
+    /** Parameterized tests for loading TensorBuffers with YUV images. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class LoadTensorBufferWithYUV extends TensorImageTest {
+        private static final int HEIGHT = 2;
+        private static final int WIDTH = 3;
+
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        @Parameters(name = "colorSpaceType={0}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.NV12},
+                    {ColorSpaceType.NV21},
+                    {ColorSpaceType.YV12},
+                    {ColorSpaceType.YV21},
+            });
+        }
+
+        @Test
+        public void loadTensorBufferWithColorSpaceShouldFail() {
+            TensorImage tensorImage = new TensorImage();
+
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    ()
+                            -> tensorImage.load(
+                                    TensorBuffer.createDynamic(DataType.FLOAT32), colorSpaceType));
+            assertThat(exception).hasMessageThat().contains(
+                    "Only ColorSpaceType.RGB and ColorSpaceType.GRAYSCALE are supported. Use"
+                    + " `load(TensorBuffer, ImageProperties)` for other color space types.");
+        }
+
+        @Test
+        public void loadTensorBufferAndGetBitmapShouldFail() {
+            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+            tensorBuffer.loadArray(data, new int[] {data.length});
+
+            ImageProperties imageProperties = ImageProperties.builder()
+                                                      .setHeight(HEIGHT)
+                                                      .setWidth(WIDTH)
+                                                      .setColorSpaceType(colorSpaceType)
+                                                      .build();
+
+            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+            tensorImage.load(tensorBuffer, imageProperties);
+
+            UnsupportedOperationException exception = assertThrows(
+                    UnsupportedOperationException.class, () -> tensorImage.getBitmap());
+            assertThat(exception).hasMessageThat().contains(
+                    "convertTensorBufferToBitmap() is unsupported for the color space type "
+                    + colorSpaceType.name());
+        }
+    }
+
+    /** Parameterized tests for loading TensorBuffers with ImageProperties. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class LoadTensorBufferWithImageProperties extends TensorImageTest {
+        private static final int HEIGHT = 2;
+        private static final int WIDTH = 3;
+        private static final int WRONG_WIDTH = 10;
+
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        @Parameters(name = "colorSpaceType={0}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.RGB},
+                    {ColorSpaceType.GRAYSCALE},
+                    {ColorSpaceType.NV12},
+                    {ColorSpaceType.NV21},
+                    {ColorSpaceType.YV12},
+                    {ColorSpaceType.YV21},
+            });
+        }
+
+        @Test
+        public void loadAndGetTensorBufferShouldSucceedWithCorrectProperties() {
+            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+            tensorBuffer.loadArray(data, new int[] {data.length});
+
+            ImageProperties imageProperties = ImageProperties.builder()
+                                                      .setHeight(HEIGHT)
+                                                      .setWidth(WIDTH)
+                                                      .setColorSpaceType(colorSpaceType)
+                                                      .build();
+
+            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+            tensorImage.load(tensorBuffer, imageProperties);
+
+            assertEqualTensorBuffers(tensorImage.getTensorBuffer(), tensorBuffer);
+        }
+
+        @Test
+        public void loadAndGetTensorBufferShouldSucceedWithLargerBuffer() {
+            // Should allow buffer to be greater than the size specified by height and width.
+            int moreElements = 1;
+            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH) + moreElements];
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+            tensorBuffer.loadArray(data, new int[] {data.length});
+
+            ImageProperties imageProperties = ImageProperties.builder()
+                                                      .setHeight(HEIGHT)
+                                                      .setWidth(WIDTH)
+                                                      .setColorSpaceType(colorSpaceType)
+                                                      .build();
+
+            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+            tensorImage.load(tensorBuffer, imageProperties);
+
+            assertEqualTensorBuffers(tensorImage.getTensorBuffer(), tensorBuffer);
+        }
+
+        @Test
+        public void loadAndGetByteBufferShouldSucceedWithCorrectProperties() {
+            ByteBuffer byteBuffer =
+                    ByteBuffer.allocate(colorSpaceType.getNumElements(HEIGHT, WIDTH));
+
+            ImageProperties imageProperties = ImageProperties.builder()
+                                                      .setHeight(HEIGHT)
+                                                      .setWidth(WIDTH)
+                                                      .setColorSpaceType(colorSpaceType)
+                                                      .build();
+
+            TensorImage tensorImage = new TensorImage(DataType.UINT8);
+            tensorImage.load(byteBuffer, imageProperties);
+
+            assertEqualByteBuffers(tensorImage.getBuffer(), byteBuffer);
+        }
+
+        @Test
+        public void loadTensorBufferWithShouldFailWithWrongImageShape() {
+            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+            tensorBuffer.loadArray(data, new int[] {data.length});
+
+            ImageProperties imageProperties = ImageProperties.builder()
+                                                      .setHeight(HEIGHT)
+                                                      .setWidth(WRONG_WIDTH)
+                                                      .setColorSpaceType(colorSpaceType)
+                                                      .build();
+
+            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    () -> tensorImage.load(tensorBuffer, imageProperties));
+            assertThat(exception).hasMessageThat().contains(String.format(
+                    "The given number of elements (%d) does not match the image (%s) in %d x %d. The"
+                            + " expected number of elements should be at least %d.",
+                    data.length, colorSpaceType.name(), HEIGHT, WRONG_WIDTH,
+                    colorSpaceType.getNumElements(HEIGHT, WRONG_WIDTH)));
+        }
+
+        @Test
+        public void getShapeOfInternalTensorBufferShouldSuccess() {
+            int[] data = new int[colorSpaceType.getNumElements(HEIGHT, WIDTH)];
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+            tensorBuffer.loadArray(data, new int[] {data.length});
+
+            ImageProperties imageProperties = ImageProperties.builder()
+                                                      .setHeight(HEIGHT)
+                                                      .setWidth(WIDTH)
+                                                      .setColorSpaceType(colorSpaceType)
+                                                      .build();
+
+            TensorImage tensorImage = new TensorImage(DataType.FLOAT32);
+            tensorImage.load(tensorBuffer, imageProperties);
+
+            assertThat(tensorImage.getWidth()).isEqualTo(WIDTH);
+            assertThat(tensorImage.getHeight()).isEqualTo(HEIGHT);
+        }
+    }
+
+    /** Parameterized tests for loading TensorBuffer with invalid shapes. */
+    @RunWith(ParameterizedRobolectricTestRunner.class)
+    public static final class LoadTensorBufferWithInvalidShapeTest extends TensorImageTest {
+        private static final String RGB_ASSERT_SHAPE_MESSAGE =
+                "The shape of a RGB image should be (h, w, c) or (1, h, w, c), and channels"
+                + " representing R, G, B in order. The provided image shape is ";
+        private static final String GRAYSCALE_ASSERT_SHAPE_MESSAGE =
+                "The shape of a grayscale image should be (h, w) or (1, h, w, 1). The provided image"
+                + " shape is ";
+
+        @Parameter(0)
+        public ColorSpaceType colorSpaceType;
+
+        /** The shape that does not match the colorSpaceType. */
+        @Parameter(1)
+        public int[] invalidShape;
+
+        @Parameter(2)
+        public String errorMessage;
+
+        @Parameters(name = "colorSpaceType={0}; invalidShape={1}")
+        public static Collection<Object[]> data() {
+            return Arrays.asList(new Object[][] {
+                    {ColorSpaceType.RGB, new int[] {2, 10, 20, 3}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {1, 10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, 20, 3, 4}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, 20, 5}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.RGB, new int[] {10, 20}, RGB_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {2, 10, 20},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {1, 10, 20, 3},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {10, 20, 4},
+                            GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+                    {ColorSpaceType.GRAYSCALE, new int[] {10}, GRAYSCALE_ASSERT_SHAPE_MESSAGE},
+            });
+        }
+
+        @Test
+        public void loadTensorBufferWithInvalidShape() {
+            TensorBuffer tensorBuffer = TensorBuffer.createFixedSize(invalidShape, UINT8);
+            TensorImage tensorImage = new TensorImage();
+
+            IllegalArgumentException exception = assertThrows(IllegalArgumentException.class,
+                    () -> tensorImage.load(tensorBuffer, colorSpaceType));
+            assertThat(exception).hasMessageThat().contains(
+                    errorMessage + Arrays.toString(invalidShape));
+        }
+    }
+
+    private static void assertEqualTensorBuffers(
+            TensorBuffer tensorBuffer1, TensorBuffer tensorBuffer2) {
+        assertEqualByteBuffers(tensorBuffer1.getBuffer(), tensorBuffer2.getBuffer());
+        assertArrayEquals(tensorBuffer1.getShape(), tensorBuffer2.getShape());
+    }
+
+    private static void assertEqualByteBuffers(ByteBuffer buffer1, ByteBuffer buffer2) {
+        buffer1.rewind();
+        buffer2.rewind();
+        assertThat(buffer1.equals(buffer2)).isTrue();
+    }
+
+    private static void setUpImageMock(Image imageMock, int imageFormat) {
+        when(imageMock.getFormat()).thenReturn(imageFormat);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java
new file mode 100644
index 0000000..4ac2eca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/TestImageCreator.java
@@ -0,0 +1,128 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image;
+
+import android.graphics.Bitmap;
+import android.graphics.Color;
+
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.nio.ByteBuffer;
+
+/** Creates test images for other test files. */
+final class TestImageCreator {
+    /**
+     * Creates an example bitmap, which is a 10x10 ARGB bitmap and pixels are set by: <br>
+     * pixel[i] = {A: 255, B: i + 2, G: i + 1, R: i}, where i is the flatten index.
+     */
+    static Bitmap createRgbBitmap() {
+        int[] colors = new int[100];
+        for (int i = 0; i < 100; i++) {
+            colors[i] = Color.rgb(i, i + 1, i + 2);
+        }
+        return Bitmap.createBitmap(colors, 10, 10, Bitmap.Config.ARGB_8888);
+    }
+
+    /**
+     * Creates a 10*10*3 float or uint8 TensorBuffer representing the same image in createRgbBitmap.
+     *
+     * <p>Adds a default delta, 0.1f, to the generated float values, such that the float array is
+     * [0.1, 1.1, 2.1, 3.1, ...], while the uint8 array is[0, 1, 2, 3, ...].
+     *
+     * @param isNormalized if true, the shape is (1, h, w, 3), otherwise it's (h, w, 3)
+     */
+    static TensorBuffer createRgbTensorBuffer(DataType dataType, boolean isNormalized) {
+        return createRgbTensorBuffer(dataType, isNormalized, /*delta=*/0.1f);
+    }
+
+    /**
+     * Creates a 10*10*3 float or uint8 TensorBuffer representing the same image in createRgbBitmap.
+     *
+     * @param isNormalized if true, the shape is (1, h, w, 3), otherwise it's (h, w)
+     * @param delta the delta that applied to the float values, such that the float array is [0 + +
+     *     delta, 1+ delta, 2+ delta, 3+ delta, ...], while the uint8 array is [0, 1, 2, 3, ...]
+     */
+    static TensorBuffer createRgbTensorBuffer(
+            DataType dataType, boolean isNormalized, float delta) {
+        float[] rgbValues = new float[300];
+        for (int i = 0, j = 0; i < 100; i++) {
+            rgbValues[j++] = i + delta;
+            rgbValues[j++] = i + 1 + delta;
+            rgbValues[j++] = i + 2 + delta;
+        }
+
+        int[] shape = isNormalized ? new int[] {1, 10, 10, 3} : new int[] {10, 10, 3};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, dataType);
+        // If dataType is UINT8, rgbValues will be converted into uint8, such as from
+        // [0.1, 1.1, 2.1, 3.1, ...] to [0, 1, 2, 3, ...].
+        buffer.loadArray(rgbValues, shape);
+        return buffer;
+    }
+
+    /**
+     * Creates an example bitmap, which is a 10x10 ALPHA_8 bitmap and pixels are set by: <br>
+     * pixel[i] = i, where i is the flatten index.
+     */
+    static Bitmap createGrayscaleBitmap() {
+        byte[] grayValues = new byte[100];
+        for (int i = 0; i < 100; i++) {
+            grayValues[i] = (byte) i;
+        }
+        ByteBuffer buffer = ByteBuffer.wrap(grayValues);
+        Bitmap bitmap = Bitmap.createBitmap(10, 10, Bitmap.Config.ALPHA_8);
+        buffer.rewind();
+        bitmap.copyPixelsFromBuffer(buffer);
+        return bitmap;
+    }
+
+    /**
+     * Creates a 10*10 float or uint8 TensorBuffer representing the same image in
+     * createGrayscaleBitmap.
+     *
+     * <p>Adds a default delta, 0.1f, to the generated float values, such that the float array is
+     * [0.1, 1.1, 2.1, 3.1, ...], while the uint8 array is[0, 1, 2, 3, ...].
+     *
+     * @param isNormalized if true, the shape is (1, h, w, 1), otherwise it's (h, w)
+     */
+    static TensorBuffer createGrayscaleTensorBuffer(DataType dataType, boolean isNormalized) {
+        return createGrayscaleTensorBuffer(dataType, isNormalized, /*delta=*/0.1f);
+    }
+
+    /**
+     * Creates a 10*10 float or uint8 TensorBuffer representing the same image in
+     * createGrayscaleBitmap.
+     *
+     * @param isNormalized if true, the shape is (1, h, w, 1), otherwise it's (h, w)
+     * @param delta the delta that applied to the float values, such that the float array is [0 +
+     *     delta, 1+ delta, 2+ delta, 3+ delta, ...], while the uint8 array is [0, 1, 2, 3, ...]
+     */
+    static TensorBuffer createGrayscaleTensorBuffer(
+            DataType dataType, boolean isNormalized, float delta) {
+        float[] grayValues = new float[100];
+        for (int i = 0; i < 100; i++) {
+            grayValues[i] = i + delta;
+        }
+        int[] shape = isNormalized ? new int[] {1, 10, 10, 1} : new int[] {10, 10};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, dataType);
+        // If dataType is UINT8, grayValues will be converted into uint8, such as from
+        // [0.1, 1.1, 2.1, 3.1, ...] to [0, 1, 2, 3, ...].
+        buffer.loadArray(grayValues, shape);
+        return buffer;
+    }
+
+    private TestImageCreator() {}
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java
new file mode 100644
index 0000000..070e1789
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeOpInstrumentedTest.java
@@ -0,0 +1,94 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import android.graphics.Bitmap;
+import android.graphics.PointF;
+
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.ImageProcessor;
+import org.tensorflow.lite.support.image.TensorImage;
+import org.tensorflow.lite.support.image.ops.ResizeOp.ResizeMethod;
+
+/** Instrumented unit test for {@link ResizeOp}. */
+@RunWith(AndroidJUnit4.class)
+public class ResizeOpInstrumentedTest {
+    private static final int EXAMPLE_WIDTH = 10;
+    private static final int EXAMPLE_HEIGHT = 15;
+
+    private Bitmap exampleBitmap;
+    private TensorImage input;
+
+    @Before
+    public void setUp() {
+        exampleBitmap = createExampleBitmap();
+        input = new TensorImage(DataType.UINT8);
+        input.load(exampleBitmap);
+    }
+
+    @Test
+    public void resizeShouldSuccess() {
+        int targetWidth = EXAMPLE_WIDTH * 2;
+        int targetHeight = EXAMPLE_HEIGHT * 2;
+        ImageProcessor processor =
+                new ImageProcessor.Builder()
+                        .add(new ResizeOp(targetHeight, targetWidth, ResizeMethod.NEAREST_NEIGHBOR))
+                        .build();
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
+        assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
+        for (int i = 0; i < outputBitmap.getWidth(); i++) {
+            for (int j = 0; j < outputBitmap.getHeight(); j++) {
+                int expected = exampleBitmap.getPixel(i / 2, j / 2);
+                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+            }
+        }
+    }
+
+    @Test
+    public void inverseTransformPointShouldSuccess() {
+        ResizeOp op = new ResizeOp(200, 300, ResizeMethod.NEAREST_NEIGHBOR);
+        PointF transformed = new PointF(32.0f, 42.0f);
+        // The original image size is 900x400 assumed
+        PointF original = op.inverseTransform(transformed, 400, 900);
+        assertThat(original.x).isEqualTo(96);
+        assertThat(original.y).isEqualTo(84);
+        PointF outside = op.inverseTransform(new PointF(500, 1000), 400, 900);
+        assertThat(outside.x).isEqualTo(1500);
+        assertThat(outside.y).isEqualTo(2000);
+    }
+
+    /**
+     * Creates an example bitmap, which is a 10x15 ARGB bitmap and pixels are set by: - pixel[i] =
+     * {A: 255, B: i + 2, G: i + 1, G: i}, where i is the flatten index
+     */
+    private static Bitmap createExampleBitmap() {
+        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
+        }
+        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java
new file mode 100644
index 0000000..85c7779
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/ResizeWithCropOrPadOpInstrumentedTest.java
@@ -0,0 +1,159 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import android.graphics.Bitmap;
+import android.graphics.PointF;
+
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.ImageProcessor;
+import org.tensorflow.lite.support.image.TensorImage;
+
+/** Instrumented unit test for {@link ResizeWithCropOrPadOp}. */
+@RunWith(AndroidJUnit4.class)
+public class ResizeWithCropOrPadOpInstrumentedTest {
+    private Bitmap exampleBitmap;
+    private TensorImage input;
+
+    private static final int EXAMPLE_WIDTH = 10;
+    private static final int EXAMPLE_HEIGHT = 15;
+
+    @Before
+    public void setUp() {
+        exampleBitmap = createExampleBitmap();
+        input = new TensorImage(DataType.UINT8);
+        input.load(exampleBitmap);
+    }
+
+    @Test
+    public void testResizeWithCrop() {
+        int targetWidth = 6;
+        int targetHeight = 5;
+        ImageProcessor processor =
+                new ImageProcessor.Builder()
+                        .add(new ResizeWithCropOrPadOp(targetHeight, targetWidth))
+                        .build();
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
+        assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
+        for (int i = 0; i < outputBitmap.getWidth(); i++) {
+            for (int j = 0; j < outputBitmap.getHeight(); j++) {
+                int expected = exampleBitmap.getPixel(i + (EXAMPLE_WIDTH - targetWidth) / 2,
+                        j + (EXAMPLE_HEIGHT - targetHeight) / 2);
+                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+            }
+        }
+    }
+
+    @Test
+    public void testResizeWithPad() {
+        int targetWidth = 15;
+        int targetHeight = 20;
+        ImageProcessor processor =
+                new ImageProcessor.Builder()
+                        .add(new ResizeWithCropOrPadOp(targetHeight, targetWidth))
+                        .build();
+        TensorImage output = processor.process(input);
+        // Pad 2 rows / columns on top / left, and 3 rows / columns on bottom / right
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertThat(outputBitmap.getWidth()).isEqualTo(targetWidth);
+        assertThat(outputBitmap.getHeight()).isEqualTo(targetHeight);
+        int leftPad = (targetWidth - EXAMPLE_WIDTH) / 2;
+        int topPad = (targetHeight - EXAMPLE_HEIGHT) / 2;
+        for (int i = 0; i < outputBitmap.getWidth(); i++) {
+            for (int j = 0; j < outputBitmap.getHeight(); j++) {
+                int expected = 0; // ZERO padding
+                if (i >= leftPad && i < leftPad + EXAMPLE_WIDTH && j >= topPad
+                        && j < topPad + EXAMPLE_HEIGHT) {
+                    expected = exampleBitmap.getPixel(i - leftPad, j - topPad);
+                }
+                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+            }
+        }
+    }
+
+    @Test
+    public void testResizeWithCropAndPad() {
+        int targetSize = 12;
+        // Pad 1 column on left & right, crop 1 row on top and 2 rows on bottom
+        ImageProcessor processor = new ImageProcessor.Builder()
+                                           .add(new ResizeWithCropOrPadOp(targetSize, targetSize))
+                                           .build();
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertThat(outputBitmap.getWidth()).isEqualTo(targetSize);
+        assertThat(outputBitmap.getHeight()).isEqualTo(targetSize);
+
+        int leftPad = (targetSize - EXAMPLE_WIDTH) / 2;
+        int topCrop = (EXAMPLE_HEIGHT - targetSize) / 2;
+        for (int i = 0; i < outputBitmap.getWidth(); i++) {
+            for (int j = 0; j < outputBitmap.getHeight(); j++) {
+                int expected = 0;
+                if (i >= leftPad && i < leftPad + EXAMPLE_WIDTH) {
+                    expected = exampleBitmap.getPixel(i - leftPad, j + topCrop);
+                }
+                assertThat(outputBitmap.getPixel(i, j)).isEqualTo(expected);
+            }
+        }
+    }
+
+    @Test
+    public void inverseTransformCorrectlyWhenCropped() {
+        ResizeWithCropOrPadOp op = new ResizeWithCropOrPadOp(300, 300);
+        // The point (100, 50) is transformed from 600x500 image
+        PointF original = op.inverseTransform(new PointF(100, 50), 500, 600);
+        assertThat(original.x).isEqualTo(250);
+        assertThat(original.y).isEqualTo(150);
+        PointF cropped = op.inverseTransform(new PointF(-10, -10), 500, 600);
+        assertThat(cropped.x).isEqualTo(140);
+        assertThat(cropped.y).isEqualTo(90);
+    }
+
+    @Test
+    public void inverseTransformCorrectlyWhenPadded() {
+        ResizeWithCropOrPadOp op = new ResizeWithCropOrPadOp(300, 300);
+        // The point (100, 50) is transformed from 100x200 image
+        PointF original = op.inverseTransform(new PointF(100, 50), 200, 100);
+        assertThat(original.x).isEqualTo(0);
+        assertThat(original.y).isEqualTo(0);
+        PointF outside = op.inverseTransform(new PointF(50, 10), 200, 100);
+        assertThat(outside.x).isEqualTo(-50);
+        assertThat(outside.y).isEqualTo(-40);
+    }
+
+    /**
+     * Creates an example bitmap, which is a 10x15 ARGB bitmap and pixels are set by: - pixel[i] =
+     * {A: 255, R: i + 2, G: i + 1, B: i}, where i is the flatten index
+     */
+    private static Bitmap createExampleBitmap() {
+        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
+        }
+        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java
new file mode 100644
index 0000000..d00fe0e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/Rot90OpInstrumentedTest.java
@@ -0,0 +1,99 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import android.graphics.Bitmap;
+import android.graphics.PointF;
+
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.ImageProcessor;
+import org.tensorflow.lite.support.image.TensorImage;
+
+/** Instrumented unit test for {@link Rot90Op}. */
+@RunWith(AndroidJUnit4.class)
+public class Rot90OpInstrumentedTest {
+    private Bitmap exampleBitmap;
+    private TensorImage input;
+
+    private static final int EXAMPLE_WIDTH = 10;
+    private static final int EXAMPLE_HEIGHT = 15;
+
+    @Before
+    public void setUp() {
+        exampleBitmap = createExampleBitmap();
+        input = new TensorImage(DataType.UINT8);
+        input.load(exampleBitmap);
+    }
+
+    @Test
+    public void testRot90() {
+        ImageProcessor processor = new ImageProcessor.Builder().add(new Rot90Op()).build();
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertThat(outputBitmap.getWidth()).isEqualTo(EXAMPLE_HEIGHT);
+        assertThat(outputBitmap.getHeight()).isEqualTo(EXAMPLE_WIDTH);
+        for (int i = 0; i < exampleBitmap.getWidth(); i++) {
+            for (int j = 0; j < exampleBitmap.getHeight(); j++) {
+                assertThat(exampleBitmap.getPixel(i, j))
+                        .isEqualTo(outputBitmap.getPixel(j, EXAMPLE_WIDTH - 1 - i));
+            }
+        }
+    }
+
+    @Test
+    public void testRot90Twice() {
+        ImageProcessor processor = new ImageProcessor.Builder().add(new Rot90Op(2)).build();
+        TensorImage output = processor.process(input);
+
+        Bitmap outputBitmap = output.getBitmap();
+        assertThat(outputBitmap.getWidth()).isEqualTo(EXAMPLE_WIDTH);
+        assertThat(outputBitmap.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
+        for (int i = 0; i < exampleBitmap.getWidth(); i++) {
+            for (int j = 0; j < exampleBitmap.getHeight(); j++) {
+                assertThat(exampleBitmap.getPixel(i, j))
+                        .isEqualTo(outputBitmap.getPixel(
+                                EXAMPLE_WIDTH - 1 - i, EXAMPLE_HEIGHT - 1 - j));
+            }
+        }
+    }
+
+    @Test
+    public void inverseTransformCorrectlyWhenRotated() {
+        Rot90Op op = new Rot90Op(3);
+        PointF original = op.inverseTransform(new PointF(20, 10), 200, 100);
+        assertThat(original.x).isEqualTo(10);
+        assertThat(original.y).isEqualTo(180);
+        PointF outside = op.inverseTransform(new PointF(-10, 110), 200, 100);
+        assertThat(outside.x).isEqualTo(110);
+        assertThat(outside.y).isEqualTo(210);
+    }
+
+    private static Bitmap createExampleBitmap() {
+        int[] colors = new int[EXAMPLE_WIDTH * EXAMPLE_HEIGHT];
+        for (int i = 0; i < EXAMPLE_WIDTH * EXAMPLE_HEIGHT; i++) {
+            colors[i] = (i << 16) | ((i + 1) << 8) | (i + 2);
+        }
+        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java
new file mode 100644
index 0000000..f024f68
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/image/ops/TransformToGrayScaleOpInstrumentedTest.java
@@ -0,0 +1,97 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.image.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.mockito.Mockito.doReturn;
+import static org.tensorflow.lite.DataType.UINT8;
+
+import android.graphics.Bitmap;
+import android.graphics.Color;
+import android.graphics.ImageFormat;
+import android.media.Image;
+
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Before;
+import org.junit.Rule;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.mockito.Mock;
+import org.mockito.junit.MockitoJUnit;
+import org.mockito.junit.MockitoRule;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.image.ColorSpaceType;
+import org.tensorflow.lite.support.image.ImageProcessor;
+import org.tensorflow.lite.support.image.TensorImage;
+
+/** Instrumented unit test for {@link TransformToGrayscaleOp}. */
+@RunWith(AndroidJUnit4.class)
+public class TransformToGrayScaleOpInstrumentedTest {
+    @Rule
+    public final MockitoRule mockito = MockitoJUnit.rule();
+
+    private TensorImage input;
+
+    private static final int EXAMPLE_WIDTH = 2;
+    private static final int EXAMPLE_HEIGHT = 3;
+    @Mock
+    Image imageMock;
+
+    @Before
+    public void setUp() {
+        Bitmap exampleBitmap = createExampleBitmap();
+        input = new TensorImage(DataType.UINT8);
+        input.load(exampleBitmap);
+    }
+
+    @Test
+    public void apply_onRgb_succeeds() {
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new TransformToGrayscaleOp()).build();
+
+        TensorImage output = processor.process(input);
+        int[] pixels = output.getTensorBuffer().getIntArray();
+
+        assertThat(output.getWidth()).isEqualTo(EXAMPLE_WIDTH);
+        assertThat(output.getHeight()).isEqualTo(EXAMPLE_HEIGHT);
+        assertThat(output.getColorSpaceType()).isEqualTo(ColorSpaceType.GRAYSCALE);
+        assertThat(pixels).isEqualTo(new int[] {0, 255, 76, 29, 150, 179});
+    }
+
+    @Test
+    public void apply_onYuv_throws() {
+        setUpImageMock(imageMock, ImageFormat.YUV_420_888);
+        TensorImage tensorImage = new TensorImage(UINT8);
+        tensorImage.load(imageMock);
+        ImageProcessor processor =
+                new ImageProcessor.Builder().add(new TransformToGrayscaleOp()).build();
+
+        assertThrows(IllegalArgumentException.class, () -> processor.process(tensorImage));
+    }
+
+    private static Bitmap createExampleBitmap() {
+        int[] colors = new int[] {
+                Color.BLACK, Color.WHITE, Color.RED, Color.BLUE, Color.GREEN, Color.CYAN};
+        return Bitmap.createBitmap(colors, EXAMPLE_WIDTH, EXAMPLE_HEIGHT, Bitmap.Config.ARGB_8888);
+    }
+
+    private static void setUpImageMock(Image imageMock, int imageFormat) {
+        doReturn(imageFormat).when(imageMock).getFormat();
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java
new file mode 100644
index 0000000..98d1f92
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/CategoryTest.java
@@ -0,0 +1,121 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.label;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+/** Tests of {@link org.tensorflow.lite.support.label.Category}. */
+@RunWith(RobolectricTestRunner.class)
+public final class CategoryTest {
+    private static final String APPLE_LABEL = "apple";
+    private static final String DEFAULT_DISPLAY_NAME = "";
+    private static final String APPLE_DISPLAY_NAME = "manzana"; // "apple" in Spanish.
+    private static final float APPLE_SCORE = 0.5f;
+    private static final int APPLE_INDEX = 10;
+
+    @Test
+    public void createShouldSucceed() {
+        Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+
+        assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
+        assertThat(category.getDisplayName()).isEqualTo(APPLE_DISPLAY_NAME);
+        assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
+    }
+
+    @Test
+    public void createWithIndexShouldSucceed() {
+        Category category =
+                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+
+        assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
+        assertThat(category.getDisplayName()).isEqualTo(APPLE_DISPLAY_NAME);
+        assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
+        assertThat(category.getIndex()).isEqualTo(APPLE_INDEX);
+    }
+
+    @Test
+    public void constructorShouldSucceed() {
+        Category category = new Category(APPLE_LABEL, APPLE_SCORE);
+
+        assertThat(category.getLabel()).isEqualTo(APPLE_LABEL);
+        // Using the constructor, displayName will be default to an empty string.
+        assertThat(category.getDisplayName()).isEqualTo(DEFAULT_DISPLAY_NAME);
+        assertThat(category.getScore()).isWithin(1e-7f).of(APPLE_SCORE);
+    }
+
+    @Test
+    public void toStringWithCreateShouldProvideReadableResult() {
+        Category category = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+        String categoryString = category.toString();
+
+        assertThat(categoryString)
+                .isEqualTo("<Category \"" + APPLE_LABEL + "\" (displayName=" + APPLE_DISPLAY_NAME
+                        + " score=" + APPLE_SCORE + " index=-1"
+                        + ")>");
+    }
+
+    @Test
+    public void toStringWithCreateIndexShouldProvideReadableResult() {
+        Category category =
+                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+        String categoryString = category.toString();
+
+        assertThat(categoryString)
+                .isEqualTo("<Category \"" + APPLE_LABEL + "\" (displayName=" + APPLE_DISPLAY_NAME
+                        + " score=" + APPLE_SCORE + " index=" + APPLE_INDEX + ")>");
+    }
+
+    @Test
+    public void toStringWithConstuctorShouldProvideReadableResult() {
+        Category category = new Category(APPLE_LABEL, APPLE_SCORE);
+        String categoryString = category.toString();
+
+        assertThat(categoryString)
+                .isEqualTo("<Category \"" + APPLE_LABEL + "\" (displayName=" + DEFAULT_DISPLAY_NAME
+                        + " score=" + APPLE_SCORE + " index=-1"
+                        + ")>");
+    }
+
+    @Test
+    public void equalsShouldSucceedWithCreate() {
+        Category categoryA = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+        Category categoryB = Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE);
+
+        assertThat(categoryA).isEqualTo(categoryB);
+    }
+
+    @Test
+    public void equalsShouldSucceedWithCreateIndex() {
+        Category categoryA =
+                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+        Category categoryB =
+                Category.create(APPLE_LABEL, APPLE_DISPLAY_NAME, APPLE_SCORE, APPLE_INDEX);
+
+        assertThat(categoryA).isEqualTo(categoryB);
+    }
+
+    @Test
+    public void equalsShouldSucceedWithConstructor() {
+        Category categoryA = new Category(APPLE_LABEL, APPLE_SCORE);
+        Category categoryB = new Category(APPLE_LABEL, APPLE_SCORE);
+
+        assertThat(categoryA).isEqualTo(categoryB);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java
new file mode 100644
index 0000000..91c81c4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/LabelUtilTest.java
@@ -0,0 +1,54 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.label;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.util.Arrays;
+import java.util.List;
+
+/** Tests of {@link org.tensorflow.lite.support.label.LabelUtil}. */
+@RunWith(RobolectricTestRunner.class)
+public class LabelUtilTest {
+    @Test
+    public void mapIndexToStringsWithInvalidValues() {
+        String[] labels = new String[] {"background", "apple", "banana", "cherry", "date"};
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+        tensorBuffer.loadArray(new int[] {0, 1, 2, 3, 2, 5}, new int[] {1, 6});
+        List<String> categories =
+                LabelUtil.mapValueToLabels(tensorBuffer, Arrays.asList(labels), 1);
+        assertThat(categories.toArray())
+                .isEqualTo(new String[] {"apple", "banana", "cherry", "date", "cherry", ""});
+    }
+
+    @Test
+    public void mapFloatIndexShouldCast() {
+        String[] labels = new String[] {"background", "apple", "banana", "cherry", "date"};
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+        tensorBuffer.loadArray(new float[] {-1.1f, -0.3f, 0.3f, 1.2f, 1.8f, 1}, new int[] {1, 6});
+        List<String> categories =
+                LabelUtil.mapValueToLabels(tensorBuffer, Arrays.asList(labels), 1);
+        assertThat(categories.toArray())
+                .isEqualTo(new String[] {
+                        "background", "apple", "apple", "banana", "banana", "banana"});
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java
new file mode 100644
index 0000000..857a77a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/TensorLabelTest.java
@@ -0,0 +1,203 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.label;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/** Tests of {@link org.tensorflow.lite.support.label.TensorLabel}. */
+@RunWith(RobolectricTestRunner.class)
+public final class TensorLabelTest {
+    @Test
+    public void createTensorLabelWithNullAxisLabelsShouldFail() {
+        int[] shape = {2};
+        int[] arr = {1, 2};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        buffer.loadArray(arr, shape);
+        Map<Integer, List<String>> nullAxisLabels = null;
+
+        Assert.assertThrows(
+                NullPointerException.class, () -> new TensorLabel(nullAxisLabels, buffer));
+    }
+
+    @Test
+    public void createTensorLabelWithNullTensorBufferShouldFail() {
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
+        TensorBuffer nullTensorBuffer = null;
+
+        Assert.assertThrows(
+                NullPointerException.class, () -> new TensorLabel(axisLabels, nullTensorBuffer));
+    }
+
+    @Test
+    public void createTensorLabelWithStringListShouldSuccess() {
+        TensorBuffer buffer = TensorBuffer.createFixedSize(new int[] {1, 4, 3}, DataType.FLOAT32);
+
+        TensorLabel tensorLabel = new TensorLabel(Arrays.asList("a", "b", "c", "d"), buffer);
+
+        assertThat(tensorLabel.getMapWithTensorBuffer()).isNotNull();
+        assertThat(tensorLabel.getMapWithTensorBuffer().keySet())
+                .contains("c"); // randomly pick one
+    }
+
+    @Test
+    public void createTensorLabelWithEmptyShapeShouldFail() {
+        int[] shape = new int[] {};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
+
+        Assert.assertThrows(
+                IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+    }
+
+    @Test
+    public void createTensorLabelWithMismatchedAxisShouldFail() {
+        int[] shape = {1, 4};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        axisLabels.put(0, Arrays.asList("a", "b", "c", "d"));
+
+        Assert.assertThrows(
+                IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+    }
+
+    @Test
+    public void createTensorLabelWithMismatchedShapeShouldFail() {
+        int[] shape = {1, 3};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        axisLabels.put(1, Arrays.asList("a", "b", "c", "d"));
+
+        Assert.assertThrows(
+                IllegalArgumentException.class, () -> new TensorLabel(axisLabels, buffer));
+    }
+
+    @Test
+    public void getMapWithFloatBufferValuesShouldSuccess() {
+        int numberLabel = 4;
+        float[] inputArr = {0.5f, 0.2f, 0.2f, 0.1f};
+        int[] shape = {1, numberLabel};
+        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        input.loadArray(inputArr, shape);
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        int labelAxis = 1;
+        axisLabels.put(labelAxis, Arrays.asList("a", "b", "c", "d"));
+
+        TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
+        Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
+
+        for (int i = 0; i < numberLabel; i++) {
+            String label = axisLabels.get(labelAxis).get(i);
+            assertThat(map).containsKey(label);
+            float[] array = map.get(label).getFloatArray();
+            assertThat(array).hasLength(1);
+            assertThat(array[0]).isEqualTo(inputArr[i]);
+        }
+    }
+
+    @Test
+    public void getMapWithIntBufferValuesShouldSuccess() {
+        int numberLabel = 3;
+        int[] inputArr = {1, 2, 0};
+        int[] shape = {1, 1, numberLabel};
+        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        input.loadArray(inputArr, shape);
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        int labelAxis = 2;
+        axisLabels.put(labelAxis, Arrays.asList("x", "y", "z"));
+
+        TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
+        Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
+
+        for (int i = 0; i < numberLabel; i++) {
+            String label = axisLabels.get(labelAxis).get(i);
+            assertThat(map).containsKey(label);
+            int[] array = map.get(label).getIntArray();
+            assertThat(array).hasLength(1);
+            assertThat(array[0]).isEqualTo(inputArr[i]);
+        }
+    }
+
+    @Test
+    public void getFloatMapShouldSuccess() {
+        int[] shape = {1, 3};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        buffer.loadArray(new float[] {1.0f, 2.0f, 3.0f});
+
+        TensorLabel tensorLabeled = new TensorLabel(Arrays.asList("a", "b", "c"), buffer);
+        Map<String, Float> map = tensorLabeled.getMapWithFloatValue();
+
+        assertThat(map).hasSize(3);
+        assertThat(map).containsEntry("a", 1.0f);
+        assertThat(map).containsEntry("b", 2.0f);
+        assertThat(map).containsEntry("c", 3.0f);
+    }
+
+    @Test
+    public void getMapFromMultiDimensionalTensorBufferShouldSuccess() {
+        int numberLabel = 2;
+        int numDim = 3;
+        float[] inputArr = {0.5f, 0.1f, 0.3f, 0.2f, 0.2f, 0.1f};
+        int[] shape = {numberLabel, numDim};
+        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        input.loadArray(inputArr, shape);
+        Map<Integer, List<String>> axisLabels = new HashMap<>();
+        int labelAxis = 0;
+        axisLabels.put(labelAxis, Arrays.asList("pos", "neg"));
+
+        TensorLabel tensorLabeled = new TensorLabel(axisLabels, input);
+        Map<String, TensorBuffer> map = tensorLabeled.getMapWithTensorBuffer();
+
+        for (int i = 0; i < numberLabel; i++) {
+            String label = axisLabels.get(labelAxis).get(i);
+            assertThat(map).containsKey(label);
+
+            float[] array = map.get(label).getFloatArray();
+            assertThat(array).hasLength(numDim);
+            for (int j = 0; j < numDim; j++) {
+                assertThat(array[j]).isEqualTo(inputArr[i * numDim + j]);
+            }
+        }
+    }
+
+    @Test
+    public void getCategoryListShouldSuccess() {
+        int[] shape = {1, 3};
+        TensorBuffer buffer = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        buffer.loadArray(new float[] {1.0f, 2.0f, 3.0f});
+
+        TensorLabel tensorLabeled = new TensorLabel(Arrays.asList("a", "b", "c"), buffer);
+        List<Category> categories = tensorLabeled.getCategoryList();
+
+        assertThat(categories).hasSize(3);
+        assertThat(categories)
+                .containsExactly(
+                        new Category("a", 1.0f), new Category("b", 2.0f), new Category("c", 3.0f));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java
new file mode 100644
index 0000000..c1afe99
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/label/ops/LabelAxisOpTest.java
@@ -0,0 +1,122 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.label.ops;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import android.content.Context;
+
+import androidx.test.core.app.ApplicationProvider;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+import org.tensorflow.lite.support.common.FileUtil;
+import org.tensorflow.lite.support.label.TensorLabel;
+import org.tensorflow.lite.support.tensorbuffer.TensorBuffer;
+
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+
+/** Tests of {@link org.tensorflow.lite.support.label.ops.LabelAxisOp}. */
+@RunWith(RobolectricTestRunner.class)
+public final class LabelAxisOpTest {
+    private final Context context = ApplicationProvider.getApplicationContext();
+    private static final String LABEL_PATH = "flower_labels.txt";
+
+    @Test
+    public void testAddAxisLabelByStringList() {
+        int numberLabel = 2;
+        float[] inputArr = {0.7f, 0.3f};
+
+        int[] shape = {numberLabel};
+        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        input.loadArray(inputArr, shape);
+
+        List<String> labels = Arrays.asList("pos", "neg");
+        LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(0, labels).build();
+        TensorLabel output = op.apply(input);
+        Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
+
+        assertThat(map).containsKey("pos");
+        float[] array = map.get("pos").getFloatArray();
+        assertThat(array).hasLength(1);
+        assertThat(array[0]).isEqualTo(0.7f);
+
+        assertThat(map).containsKey("neg");
+        array = map.get("neg").getFloatArray();
+        assertThat(array).hasLength(1);
+        assertThat(array[0]).isEqualTo(0.3f);
+    }
+
+    @Test
+    public void testAddAxisLabelWithMultiDimensionTensor() throws IOException {
+        int numberLabel = 2;
+        int numDim = 3;
+        float[] inputArr = {0.5f, 0.1f, 0.3f, 0.2f, 0.2f, 0.1f};
+
+        int[] shape = {1, numberLabel, numDim};
+        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        input.loadArray(inputArr, shape);
+
+        List<String> labels = Arrays.asList("pos", "neg");
+        LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(1, labels).build();
+
+        TensorLabel output = op.apply(input);
+        Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
+
+        assertThat(map).containsKey("pos");
+        float[] array = map.get("pos").getFloatArray();
+        assertThat(array).hasLength(numDim);
+        assertThat(array).isEqualTo(new float[] {0.5f, 0.1f, 0.3f});
+
+        assertThat(map).containsKey("neg");
+        array = map.get("neg").getFloatArray();
+        assertThat(array).hasLength(numDim);
+        assertThat(array).isEqualTo(new float[] {0.2f, 0.2f, 0.1f});
+    }
+
+    @Test
+    public void testAddAxisLabelByFilePath() throws IOException {
+        int numberLabel = 5;
+        int[] inputArr = new int[numberLabel];
+        for (int i = 0; i < numberLabel; i++) {
+            inputArr[i] = i;
+        }
+
+        int[] shape = {numberLabel};
+        TensorBuffer input = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        input.loadArray(inputArr, shape);
+
+        LabelAxisOp op = new LabelAxisOp.Builder().addAxisLabel(context, 0, LABEL_PATH).build();
+        TensorLabel output = op.apply(input);
+        Map<String, TensorBuffer> map = output.getMapWithTensorBuffer();
+
+        List<String> labels = FileUtil.loadLabels(context, LABEL_PATH);
+        for (int i = 0; i < numberLabel; i++) {
+            String label = labels.get(i);
+
+            assertThat(map).containsKey(label);
+
+            int[] array = map.get(label).getIntArray();
+            assertThat(array).hasLength(1);
+            assertThat(array[0]).isEqualTo(inputArr[i]);
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java
new file mode 100644
index 0000000..d7449187
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyInstrumentedTest.java
@@ -0,0 +1,39 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+package org.tensorflow.lite.support.model;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import androidx.test.ext.junit.runners.AndroidJUnit4;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+
+/**
+ * Instrumented unit test for {@link GpuDelegateProxy}.
+ *
+ * <p>In this test, "tensorflow-lite-gpu" is provided.
+ */
+@RunWith(AndroidJUnit4.class)
+public final class GpuDelegateProxyInstrumentedTest {
+    @Test
+    public void createGpuDelegateProxyShouldSuccess() {
+        GpuDelegateProxy proxy = GpuDelegateProxy.maybeNewInstance();
+
+        assertThat(proxy).isNotNull();
+        proxy.getNativeHandle();
+        proxy.close();
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java
new file mode 100644
index 0000000..4eb2e29
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/GpuDelegateProxyTest.java
@@ -0,0 +1,32 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+package org.tensorflow.lite.support.model;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+/** Tests of {@link org.tensorflow.lite.support.model.GpuDelegateProxy}. */
+@RunWith(RobolectricTestRunner.class)
+public final class GpuDelegateProxyTest {
+    @Test
+    public void createGpuDelegateProxyWithoutDependencyShouldReturnNull() {
+        GpuDelegateProxy proxy = GpuDelegateProxy.maybeNewInstance();
+
+        assertThat(proxy).isNull();
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java
new file mode 100644
index 0000000..342e82b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/model/ModelTest.java
@@ -0,0 +1,160 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.model;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.fail;
+
+import android.content.Context;
+
+import androidx.test.core.app.ApplicationProvider;
+
+import org.junit.Ignore;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.support.model.Model.Device;
+import org.tensorflow.lite.support.model.Model.Options;
+
+import java.io.IOException;
+import java.nio.MappedByteBuffer;
+import java.util.HashMap;
+import java.util.Map;
+
+/** Tests of {@link org.tensorflow.lite.support.model.Model}. */
+@RunWith(RobolectricTestRunner.class)
+public final class ModelTest {
+    private final Context context = ApplicationProvider.getApplicationContext();
+    private static final String MODEL_PATH = "add.tflite";
+
+    @Ignore
+    @Test
+    public void testLoadLocalModel() throws IOException {
+        MappedByteBuffer byteModel = new Model.Builder(context, MODEL_PATH).build().getData();
+        assertThat(byteModel).isNotNull();
+    }
+
+    @Ignore
+    @Test
+    public void testBuildMultiThreadModel() throws IOException {
+        MappedByteBuffer byteModel =
+                new Model.Builder(context, MODEL_PATH).setNumThreads(4).build().getData();
+        assertThat(byteModel).isNotNull();
+    }
+
+    @Ignore
+    @Test
+    public void buildModelWithOptionsShouldSuccess() throws IOException {
+        Options options = new Options.Builder().setNumThreads(2).setDevice(Device.NNAPI).build();
+        Model model = Model.createModel(context, MODEL_PATH, options);
+        assertThat(model.getData()).isNotNull();
+    }
+
+    @Ignore
+    @Test
+    public void testGetModelPath() throws IOException {
+        String modelPath = new Model.Builder(context, MODEL_PATH).build().getPath();
+        assertThat(modelPath).isEqualTo(MODEL_PATH);
+    }
+
+    @Test
+    public void testNonExistingLocalModel() {
+        try {
+            new Model.Builder(context, "non_exist_model_file").build();
+            fail();
+        } catch (IOException e) {
+            assertThat(e).hasMessageThat().contains("non_exist_model_file");
+        }
+    }
+
+    @Test
+    public void testNullLocalModelPath() throws IOException {
+        try {
+            new Model.Builder(context, null).build();
+            fail();
+        } catch (NullPointerException e) {
+            assertThat(e).hasMessageThat().contains("File path cannot be null.");
+        }
+    }
+
+    @Test
+    public void testNullContext() throws IOException {
+        try {
+            new Model.Builder(null, MODEL_PATH).build();
+            fail();
+        } catch (NullPointerException e) {
+            assertThat(e).hasMessageThat().contains("Context should not be null.");
+        }
+    }
+
+    @Ignore
+    @Test
+    public void testGetInputTensor() throws IOException {
+        Options options = new Options.Builder().build();
+        Model model = Model.createModel(context, MODEL_PATH, options);
+        assertThat(model.getInputTensor(0)).isNotNull();
+    }
+
+    @Ignore
+    @Test
+    public void testGetOutputTensor() throws IOException {
+        Options options = new Options.Builder().build();
+        Model model = Model.createModel(context, MODEL_PATH, options);
+        assertThat(model.getOutputTensor(0)).isNotNull();
+    }
+
+    @Ignore
+    @Test
+    public void testRun() throws IOException {
+        Context context = ApplicationProvider.getApplicationContext();
+        Model model = new Model.Builder(context, MODEL_PATH).build();
+        runModel(model);
+    }
+
+    @Ignore
+    @Test
+    public void testMultiThreadingRun() throws IOException {
+        Context context = ApplicationProvider.getApplicationContext();
+        Model model = new Model.Builder(context, MODEL_PATH).setNumThreads(4).build();
+        runModel(model);
+    }
+
+    @Ignore
+    @Test
+    public void testNnApiRun() throws IOException {
+        Context context = ApplicationProvider.getApplicationContext();
+        Model model = new Model.Builder(context, MODEL_PATH).setDevice(Device.NNAPI).build();
+        runModel(model);
+    }
+
+    private static void runModel(Model model) throws IOException {
+        // Creates the inputs.
+        float[] x = {1.5f};
+        float[] y = {0.5f};
+        float[] expectedSum = {2.0f};
+        Object[] inputs = {x, y};
+
+        // Creates the outputs buffer.
+        float[] sum = new float[1];
+        Map<Integer, Object> outputs = new HashMap<>();
+        outputs.put(0, sum);
+
+        // Runs inference.
+        model.run(inputs, outputs);
+        assertThat(sum).isEqualTo(expectedSum);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java
new file mode 100644
index 0000000..82b59b3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferFloatTest.java
@@ -0,0 +1,76 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.tensorbuffer;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+
+/** Tests of {@link org.tensorflow.lite.support.tensorbuffer.TensorBufferFloat}. */
+@RunWith(RobolectricTestRunner.class)
+public final class TensorBufferFloatTest {
+    @Test
+    public void testCreateDynamic() {
+        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat();
+        assertThat(tensorBufferFloat).isNotNull();
+    }
+
+    @Test
+    public void testCreateFixedSize() {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
+        assertThat(tensorBufferFloat).isNotNull();
+        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(6);
+    }
+
+    @Test
+    public void testCreateFixedSizeWithScalarShape() {
+        int[] shape = new int[] {};
+        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
+        assertThat(tensorBufferFloat).isNotNull();
+        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(1);
+    }
+
+    @Test
+    public void testCreateWithNullShape() {
+        int[] shape = null;
+        Assert.assertThrows(NullPointerException.class, () -> new TensorBufferFloat(shape));
+    }
+
+    @Test
+    public void testCreateWithInvalidShape() {
+        int[] shape = new int[] {1, -1, 2};
+        Assert.assertThrows(IllegalArgumentException.class, () -> new TensorBufferFloat(shape));
+    }
+
+    @Test
+    public void testCreateUsingShapeWithZero() {
+        int[] shape = new int[] {1, 0, 2};
+        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat(shape);
+        assertThat(tensorBufferFloat).isNotNull();
+        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(0);
+    }
+
+    @Test
+    public void testGetDataType() {
+        TensorBufferFloat tensorBufferFloat = new TensorBufferFloat();
+        assertThat(tensorBufferFloat.getDataType()).isEqualTo(DataType.FLOAT32);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java
new file mode 100644
index 0000000..763356f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferTest.java
@@ -0,0 +1,893 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.tensorbuffer;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+
+import java.io.IOException;
+import java.nio.ByteBuffer;
+import java.nio.FloatBuffer;
+import java.util.ArrayList;
+
+/** Test helper class for inserting and retrieving arrays. */
+class ArrayTestRunner {
+    // List of TensorBuffer types to be tested.
+    private static final DataType[] BUFFER_TYPE_LIST = {DataType.FLOAT32, DataType.UINT8};
+    // List of source arrays to be loaded into TensorBuffer during the tests.
+    private final ArrayList<Object> srcArrays;
+    // List of array data type with respect to srcArrays.
+    private final ArrayList<DataType> arrDataTypes;
+    // List of array shape with respect to srcArrays.
+    private final ArrayList<int[]> arrShapes;
+    private final int[] tensorBufferShape;
+    private final ExpectedResults expectedResForFloatBuf;
+    private final ExpectedResults expectedResForByteBuf;
+
+    public ArrayTestRunner(Builder builder) {
+        if (builder.srcArrays.size() != builder.arrDataTypes.size()) {
+            throw new IllegalArgumentException(
+                    "Number of source arrays and number of data types do not match.");
+        }
+
+        this.srcArrays = builder.srcArrays;
+        this.arrDataTypes = builder.arrDataTypes;
+        this.arrShapes = builder.arrShapes;
+        this.tensorBufferShape = builder.tensorBufferShape;
+        this.expectedResForFloatBuf = builder.expectedResForFloatBuf;
+        this.expectedResForByteBuf = builder.expectedResForByteBuf;
+    }
+
+    static class ExpectedResults {
+        public float[] floatArr;
+        public int[] intArr;
+        public int[] shape;
+    }
+
+    public static class Builder {
+        private final ArrayList<Object> srcArrays = new ArrayList<>();
+        private final ArrayList<DataType> arrDataTypes = new ArrayList<>();
+        private final ArrayList<int[]> arrShapes = new ArrayList<>();
+        private int[] tensorBufferShape;
+        private final ExpectedResults expectedResForFloatBuf = new ExpectedResults();
+        private final ExpectedResults expectedResForByteBuf = new ExpectedResults();
+
+        public static Builder newInstance() {
+            return new Builder();
+        }
+
+        private Builder() {}
+
+        /** Loads a test array into the test runner. */
+        public Builder addSrcArray(Object src, int[] shape) {
+            // src should be a primitive 1D array.
+            DataType dataType = dataTypeOfArray(src);
+            switch (dataType) {
+                case INT32:
+                case FLOAT32:
+                    srcArrays.add(src);
+                    arrDataTypes.add(dataType);
+                    arrShapes.add(shape);
+                    return this;
+                default:
+                    throw new AssertionError(
+                            "Cannot resolve srouce arrays in the DataType of " + dataType);
+            }
+        }
+
+        public Builder setTensorBufferShape(int[] tensorBufferShape) {
+            this.tensorBufferShape = tensorBufferShape;
+            return this;
+        }
+
+        public Builder setExpectedResults(
+                DataType bufferType, float[] expectedFloatArr, int[] expectedIntArr) {
+            ExpectedResults er;
+            switch (bufferType) {
+                case UINT8:
+                    er = expectedResForByteBuf;
+                    break;
+                case FLOAT32:
+                    er = expectedResForFloatBuf;
+                    break;
+                default:
+                    throw new AssertionError(
+                            "Cannot test TensorBuffer in the DataType of " + bufferType);
+            }
+
+            er.floatArr = expectedFloatArr;
+            er.intArr = expectedIntArr;
+            return this;
+        }
+
+        public ArrayTestRunner build() {
+            int[] expectedShape;
+            if (arrShapes.isEmpty()) {
+                // If no array will be loaded, the array is an empty array.
+                expectedShape = new int[] {0};
+            } else {
+                expectedShape = arrShapes.get(arrShapes.size() - 1);
+            }
+            expectedResForByteBuf.shape = expectedShape;
+            expectedResForFloatBuf.shape = expectedShape;
+            return new ArrayTestRunner(this);
+        }
+    }
+
+    public static DataType[] getBufferTypeList() {
+        return BUFFER_TYPE_LIST;
+    }
+
+    /**
+     * Runs tests in the following steps: 1. Create a TensorBuffer. If tensorBufferShape is null,
+     * create a dynamic buffer. Otherwise, create a fixed-size buffer accordingly. 2. Load arrays in
+     * srcArrays one by one into the TensotBuffer. 3. Get arrays for each supported primitive types
+     * in TensorBuffer, such as int array and float array for now. Check if the results are
+     * correct. 4. Repeat Step 1 to 3 for all buffer types in BUFFER_TYPE_LIST.
+     */
+    public void run() {
+        for (DataType bufferDataType : BUFFER_TYPE_LIST) {
+            TensorBuffer tensorBuffer;
+            if (tensorBufferShape == null) {
+                tensorBuffer = TensorBuffer.createDynamic(bufferDataType);
+            } else {
+                tensorBuffer = TensorBuffer.createFixedSize(tensorBufferShape, bufferDataType);
+            }
+            for (int i = 0; i < srcArrays.size(); i++) {
+                switch (arrDataTypes.get(i)) {
+                    case INT32:
+                        int[] arrInt = (int[]) srcArrays.get(i);
+                        tensorBuffer.loadArray(arrInt, arrShapes.get(i));
+                        break;
+                    case FLOAT32:
+                        float[] arrFloat = (float[]) srcArrays.get(i);
+                        tensorBuffer.loadArray(arrFloat, arrShapes.get(i));
+                        break;
+                    default:
+                        break;
+                }
+            }
+            checkResults(tensorBuffer);
+        }
+    }
+
+    private void checkResults(TensorBuffer tensorBuffer) {
+        ExpectedResults er;
+        switch (tensorBuffer.getDataType()) {
+            case UINT8:
+                er = expectedResForByteBuf;
+                break;
+            case FLOAT32:
+                er = expectedResForFloatBuf;
+                break;
+            default:
+                throw new AssertionError("Cannot test TensorBuffer in the DataType of "
+                        + tensorBuffer.getDataType());
+        }
+
+        // Checks getIntArray() and getFloatArray().
+        int[] resIntArr = tensorBuffer.getIntArray();
+        assertThat(resIntArr).isEqualTo(er.intArr);
+        float[] resFloatArr = tensorBuffer.getFloatArray();
+        assertThat(resFloatArr).isEqualTo(er.floatArr);
+        assertThat(tensorBuffer.getShape()).isEqualTo(er.shape);
+
+        // Checks getIntValue(int index) and getFloatValue(int index).
+        int flatSize = tensorBuffer.getFlatSize();
+        float[] resFloatValues = new float[flatSize];
+        int[] resIntValues = new int[flatSize];
+        for (int i = 0; i < flatSize; i++) {
+            resFloatValues[i] = tensorBuffer.getFloatValue(i);
+            resIntValues[i] = tensorBuffer.getIntValue(i);
+        }
+        assertThat(resFloatValues).isEqualTo(er.floatArr);
+        assertThat(resIntValues).isEqualTo(er.intArr);
+    }
+
+    /** Gets the data type of an 1D array. */
+    private static DataType dataTypeOfArray(Object arr) {
+        if (arr != null) {
+            Class<?> c = arr.getClass();
+            if (c.isArray()) {
+                c = c.getComponentType();
+                if (float.class.equals(c)) {
+                    return DataType.FLOAT32;
+                } else if (int.class.equals(c)) {
+                    return DataType.INT32;
+                } else if (byte.class.equals(c)) {
+                    return DataType.UINT8;
+                } else if (long.class.equals(c)) {
+                    return DataType.INT64;
+                } else if (String.class.equals(c)) {
+                    return DataType.STRING;
+                }
+            }
+        }
+        throw new IllegalArgumentException(
+                "Requires a 1D array. Cannot resolve data type of " + arr.getClass().getName());
+    }
+}
+
+/** Tests of {@link org.tensorflow.lite.support.tensorbuffer.TensorBuffer}. */
+@RunWith(RobolectricTestRunner.class)
+public final class TensorBufferTest {
+    // FLOAT_ARRAY1 and INT_ARRAY1 correspond to each other.
+    private static final int[] ARRAY1_SHAPE = new int[] {2, 3};
+    private static final float[] FLOAT_ARRAY1 = new float[] {500.1f, 4.2f, 3.3f, 2.4f, 1.5f, 6.1f};
+    private static final float[] FLOAT_ARRAY1_ROUNDED =
+            new float[] {500.0f, 4.0f, 3.0f, 2.0f, 1.0f, 6.0f};
+    // FLOAT_ARRAY1_CAPPED and INT_ARRAY1_CAPPED correspond to the expected values when converted
+    // into uint8.
+    private static final float[] FLOAT_ARRAY1_CAPPED =
+            new float[] {255.0f, 4.0f, 3.0f, 2.0f, 1.0f, 6.0f};
+    private static final int[] INT_ARRAY1 = new int[] {500, 4, 3, 2, 1, 6};
+    private static final int[] INT_ARRAY1_CAPPED = new int[] {255, 4, 3, 2, 1, 6};
+    // FLOAT_ARRAY2 and INT_ARRAY2 correspond to each other.
+    private static final int[] ARRAY2_SHAPE = new int[] {2, 1};
+    private static final float[] FLOAT_ARRAY2 = new float[] {6.7f, 7.6f};
+    private static final float[] FLOAT_ARRAY2_ROUNDED = new float[] {6.0f, 7.0f};
+    private static final int[] INT_ARRAY2 = new int[] {6, 7};
+    // FLOAT_ARRAY2 and FLOAT_ARRAY3 have the same size.
+    private static final int[] ARRAY3_SHAPE = new int[] {2, 1};
+    private static final float[] FLOAT_ARRAY3 = new float[] {8.2f, 9.9f};
+    private static final float[] FLOAT_ARRAY3_ROUNDED = new float[] {8.0f, 9.0f};
+    // INT_ARRAY2 and INT_ARRAY3 have the same size.
+    private static final int[] INT_ARRAY3 = new int[] {8, 9};
+    private static final int[] EMPTY_ARRAY_SHAPE = new int[] {0};
+    private static final int[] EMPTY_INT_ARRAY = new int[0];
+    private static final float[] EMPTY_FLOAT_ARRAY = new float[0];
+    // Single element array which represents a scalar.
+    private static final int[] SCALAR_ARRAY_SHAPE = new int[] {};
+    private static final float[] FLOAT_SCALAR_ARRAY = new float[] {800.2f};
+    private static final float[] FLOAT_SCALAR_ARRAY_ROUNDED = new float[] {800.0f};
+    private static final float[] FLOAT_SCALAR_ARRAY_CAPPED = new float[] {255.0f};
+    private static final int[] INT_SCALAR_ARRAY = new int[] {800};
+    private static final int[] INT_SCALAR_ARRAY_CAPPED = new int[] {255};
+    // Several different ByteBuffer.
+    private static final ByteBuffer EMPTY_BYTE_BUFFER = ByteBuffer.allocateDirect(0);
+    private static final ByteBuffer FLOAT_BYTE_BUFFER1 = ByteBuffer.allocateDirect(24);
+
+    static {
+        FLOAT_BYTE_BUFFER1.rewind();
+
+        FloatBuffer floatBuffer = FLOAT_BYTE_BUFFER1.asFloatBuffer();
+        floatBuffer.put(FLOAT_ARRAY1);
+    }
+
+    private static final ByteBuffer INT_BYTE_BUFFER2 = ByteBuffer.allocateDirect(2);
+
+    static {
+        INT_BYTE_BUFFER2.rewind();
+
+        for (int a : INT_ARRAY2) {
+            INT_BYTE_BUFFER2.put((byte) a);
+        }
+    }
+
+    @Test
+    public void testCreateFixedSizeTensorBufferFloat() {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBuffer tensorBufferFloat = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        assertThat(tensorBufferFloat).isNotNull();
+        assertThat(tensorBufferFloat.getFlatSize()).isEqualTo(6);
+    }
+
+    @Test
+    public void testCreateFixedSizeTensorBufferUint8() {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBuffer tensorBufferUint8 = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        assertThat(tensorBufferUint8).isNotNull();
+        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(6);
+    }
+
+    @Test
+    public void testCreateDynamicTensorBufferFloat() {
+        TensorBuffer tensorBufferFloat = TensorBuffer.createDynamic(DataType.FLOAT32);
+        assertThat(tensorBufferFloat).isNotNull();
+    }
+
+    @Test
+    public void testCreateDynamicTensorBufferUint8() {
+        TensorBuffer tensorBufferUint8 = TensorBuffer.createDynamic(DataType.UINT8);
+        assertThat(tensorBufferUint8).isNotNull();
+    }
+
+    @Test
+    public void testCreateTensorBufferFromFixedSize() {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+        assertThat(dst.getShape()).isEqualTo(new int[] {1, 2, 3});
+    }
+
+    @Test
+    public void testCreateTensorBufferFromDynamicSize() {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBuffer src = TensorBuffer.createDynamic(DataType.UINT8);
+        src.resize(shape);
+        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+        assertThat(dst.getShape()).isEqualTo(new int[] {1, 2, 3});
+    }
+
+    @Test
+    public void testCreateTensorBufferUInt8FromUInt8() {
+        int[] shape = new int[] {INT_ARRAY1.length};
+        TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        src.loadArray(INT_ARRAY1);
+        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.UINT8);
+        int[] data = dst.getIntArray();
+        assertThat(data).isEqualTo(INT_ARRAY1_CAPPED);
+    }
+
+    @Test
+    public void testCreateTensorBufferUInt8FromFloat32() {
+        TensorBuffer src = TensorBuffer.createDynamic(DataType.FLOAT32);
+        src.loadArray(FLOAT_ARRAY1, ARRAY1_SHAPE);
+        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.UINT8);
+        int[] data = dst.getIntArray();
+        assertThat(data).isEqualTo(INT_ARRAY1_CAPPED);
+    }
+
+    @Test
+    public void testCreateTensorBufferFloat32FromUInt8() {
+        TensorBuffer src = TensorBuffer.createDynamic(DataType.UINT8);
+        src.loadArray(INT_ARRAY1, ARRAY1_SHAPE);
+        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+        float[] data = dst.getFloatArray();
+        assertThat(data).isEqualTo(FLOAT_ARRAY1_CAPPED);
+    }
+
+    @Test
+    public void testCreateTensorBufferFloat32FromFloat32() {
+        int[] shape = new int[] {FLOAT_ARRAY1.length};
+        TensorBuffer src = TensorBuffer.createFixedSize(shape, DataType.FLOAT32);
+        src.loadArray(FLOAT_ARRAY1);
+        TensorBuffer dst = TensorBuffer.createFrom(src, DataType.FLOAT32);
+        float[] data = dst.getFloatArray();
+        assertThat(data).isEqualTo(FLOAT_ARRAY1);
+    }
+
+    @Test
+    public void testGetBuffer() throws IOException {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBuffer tensorBufferUint8 = TensorBuffer.createFixedSize(shape, DataType.UINT8);
+        assertThat(tensorBufferUint8.getBuffer()).isNotNull();
+    }
+
+    @Test
+    public void testLoadAndGetIntArrayWithFixedSizeForScalarArray() throws IOException {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(INT_SCALAR_ARRAY, SCALAR_ARRAY_SHAPE)
+                .setTensorBufferShape(SCALAR_ARRAY_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY_ROUNDED,
+                        /*expectedIntArr=*/INT_SCALAR_ARRAY)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY_CAPPED,
+                        /*expectedIntArr=*/INT_SCALAR_ARRAY_CAPPED)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testLoadAndGetFloatArrayWithFixedSizeForScalarArray() throws IOException {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(FLOAT_SCALAR_ARRAY, SCALAR_ARRAY_SHAPE)
+                .setTensorBufferShape(SCALAR_ARRAY_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY,
+                        /*expectedIntArr=*/INT_SCALAR_ARRAY)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_SCALAR_ARRAY_CAPPED,
+                        /*expectedIntArr=*/INT_SCALAR_ARRAY_CAPPED)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testLoadAndGetIntArrayWithFixedSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
+                .setTensorBufferShape(ARRAY1_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY1)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
+                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testLoadAndGetFloatArrayWithFixedSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
+                .setTensorBufferShape(ARRAY1_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1,
+                        /*expectedIntArr=*/INT_ARRAY1)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
+                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testRepeatedLoadAndGetIntArrayWithSameFixedSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(INT_ARRAY2, ARRAY2_SHAPE)
+                .addSrcArray(INT_ARRAY3, ARRAY3_SHAPE)
+                .setTensorBufferShape(ARRAY2_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY3_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY3)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY3_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY3)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testRepeatedLoadAndGetFloatArrayWithSameFixedSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
+                .addSrcArray(FLOAT_ARRAY3, ARRAY3_SHAPE)
+                .setTensorBufferShape(ARRAY2_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY3,
+                        /*expectedIntArr=*/INT_ARRAY3)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY3_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY3)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testRepeatedLoadIntArrayWithDifferentFixedSize() {
+        int[] srcArr1 = INT_ARRAY1;
+        int[] srcArr2 = INT_ARRAY2;
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer =
+                    TensorBuffer.createFixedSize(new int[] {srcArr1.length}, dataType);
+            tensorBuffer.loadArray(srcArr1, new int[] {srcArr1.length});
+            // Load srcArr2 which had different size as srcArr1.
+            Assert.assertThrows(IllegalArgumentException.class,
+                    () -> tensorBuffer.loadArray(srcArr2, new int[] {srcArr2.length}));
+        }
+    }
+
+    @Test
+    public void testRepeatedLoadFloatArrayWithDifferentFixedSize() {
+        float[] srcArr1 = FLOAT_ARRAY1;
+        float[] srcArr2 = FLOAT_ARRAY2;
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer =
+                    TensorBuffer.createFixedSize(new int[] {srcArr1.length}, dataType);
+            tensorBuffer.loadArray(srcArr1, new int[] {srcArr1.length});
+            // Load srcArr2 which had different size as srcArr1.
+            Assert.assertThrows(IllegalArgumentException.class,
+                    () -> tensorBuffer.loadArray(srcArr2, new int[] {srcArr2.length}));
+        }
+    }
+
+    @Test
+    public void testLoadAndGetIntArrayWithDynamicSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY1)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
+                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testLoadAndGetFloatArrayWithDynamicSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1,
+                        /*expectedIntArr=*/INT_ARRAY1)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY1_CAPPED,
+                        /*expectedIntArr=*/INT_ARRAY1_CAPPED)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testRepeatedLoadAndGetIntArrayWithDifferentDynamicSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(INT_ARRAY1, ARRAY1_SHAPE)
+                .addSrcArray(INT_ARRAY2, ARRAY2_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY2_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY2)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY2_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY2)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testRepeatedLoadAndGetFloatArrayWithDifferentDynamicSize() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(FLOAT_ARRAY1, ARRAY1_SHAPE)
+                .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/FLOAT_ARRAY2,
+                        /*expectedIntArr=*/INT_ARRAY2)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/FLOAT_ARRAY2_ROUNDED,
+                        /*expectedIntArr=*/INT_ARRAY2)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testGetForEmptyArrayWithFixedSizeBuffer() {
+        ArrayTestRunner.Builder.newInstance()
+                .setTensorBufferShape(EMPTY_ARRAY_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
+                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
+                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testGetForEmptyArrayWithDynamicBuffer() {
+        ArrayTestRunner.Builder.newInstance()
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
+                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
+                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testRepeatedLoadAndGetForEmptyArray() {
+        ArrayTestRunner.Builder.newInstance()
+                .addSrcArray(EMPTY_INT_ARRAY, EMPTY_ARRAY_SHAPE)
+                .addSrcArray(FLOAT_ARRAY2, ARRAY2_SHAPE)
+                .addSrcArray(EMPTY_FLOAT_ARRAY, EMPTY_ARRAY_SHAPE)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.FLOAT32,
+                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
+                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
+                .setExpectedResults(
+                        /*bufferType = */ DataType.UINT8,
+                        /*expectedFloatArr=*/EMPTY_FLOAT_ARRAY,
+                        /*expectedIntArr=*/EMPTY_INT_ARRAY)
+                .build()
+                .run();
+    }
+
+    @Test
+    public void testLoadNullIntArrays() {
+        int[] nullArray = null;
+        int[] shape = new int[] {};
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            Assert.assertThrows(
+                    NullPointerException.class, () -> tensorBuffer.loadArray(nullArray, shape));
+        }
+    }
+
+    @Test
+    public void testLoadNullFloatArrays() {
+        float[] nullArray = null;
+        int[] shape = new int[] {};
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            Assert.assertThrows(
+                    NullPointerException.class, () -> tensorBuffer.loadArray(nullArray, shape));
+        }
+    }
+
+    @Test
+    public void testLoadFloatArraysWithNullShape() {
+        float[] arr = new float[] {1.0f};
+        int[] nullShape = null;
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            Assert.assertThrows(
+                    NullPointerException.class, () -> tensorBuffer.loadArray(arr, nullShape));
+        }
+    }
+
+    @Test
+    public void testLoadIntArraysWithNullShape() {
+        int[] arr = new int[] {1};
+        int[] nullShape = null;
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            Assert.assertThrows(
+                    NullPointerException.class, () -> tensorBuffer.loadArray(arr, nullShape));
+        }
+    }
+
+    @Test
+    public void testLoadIntArraysWithoutShapeAndArrayDoesNotMatchShape() {
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer fixedTensorBuffer = TensorBuffer.createFixedSize(ARRAY1_SHAPE, dataType);
+            Assert.assertThrows(
+                    IllegalArgumentException.class, () -> fixedTensorBuffer.loadArray(INT_ARRAY2));
+        }
+    }
+
+    @Test
+    public void testLoadFloatArraysWithoutShapeAndArrayDoesNotMatchShape() {
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer fixedTensorBuffer = TensorBuffer.createFixedSize(ARRAY1_SHAPE, dataType);
+            Assert.assertThrows(IllegalArgumentException.class,
+                    () -> fixedTensorBuffer.loadArray(FLOAT_ARRAY2));
+        }
+    }
+
+    @Test
+    public void testLoadByteBufferForNullBuffer() {
+        ByteBuffer byteBuffer = null;
+        int[] shape = new int[] {};
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            Assert.assertThrows(
+                    NullPointerException.class, () -> tensorBuffer.loadBuffer(byteBuffer, shape));
+        }
+    }
+
+    @Test
+    public void testLoadByteBufferForEmptyBuffer() {
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            tensorBuffer.loadBuffer(EMPTY_BYTE_BUFFER, EMPTY_ARRAY_SHAPE);
+            assertThat(tensorBuffer.getFlatSize()).isEqualTo(0);
+        }
+    }
+
+    @Test
+    public void testLoadByteBufferWithDifferentFixedSize() {
+        // Create a fixed-size TensorBuffer with size 2, and load a ByteBuffer with size 5.
+        int[] tensorBufferShape = new int[] {2};
+        TensorBuffer tensorBuffer =
+                TensorBuffer.createFixedSize(tensorBufferShape, DataType.FLOAT32);
+        Assert.assertThrows(IllegalArgumentException.class,
+                () -> tensorBuffer.loadBuffer(FLOAT_BYTE_BUFFER1, ARRAY1_SHAPE));
+    }
+
+    @Test
+    public void testLoadByteBufferWithMisMatchDataType() {
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+        int[] wrongShape = new int[] {1};
+        // Size of INT_BYTE_BUFFER is 8 bytes. It does not match the specified shape.
+        Assert.assertThrows(IllegalArgumentException.class,
+                () -> tensorBuffer.loadBuffer(INT_BYTE_BUFFER2, wrongShape));
+    }
+
+    @Test
+    public void testLoadByteBufferForTensorBufferFloat() {
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.FLOAT32);
+        tensorBuffer.loadBuffer(FLOAT_BYTE_BUFFER1, ARRAY1_SHAPE);
+        assertThat(tensorBuffer.getFloatArray()).isEqualTo(FLOAT_ARRAY1);
+        assertThat(tensorBuffer.getShape()).isEqualTo(ARRAY1_SHAPE);
+    }
+
+    @Test
+    public void testLoadByteBufferForTensorBufferUint8() {
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+        tensorBuffer.loadBuffer(INT_BYTE_BUFFER2, ARRAY2_SHAPE);
+        assertThat(tensorBuffer.getIntArray()).isEqualTo(INT_ARRAY2);
+        assertThat(tensorBuffer.getShape()).isEqualTo(ARRAY2_SHAPE);
+    }
+
+    @Test
+    public void testGetFloatValueWithInvalidIndex() {
+        float[] arrayWithSixElements = FLOAT_ARRAY1;
+        int[] shapeOfArrayWithSixElements = ARRAY1_SHAPE;
+        int[] invalidIndexes = {-1, 7};
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            tensorBuffer.loadArray(arrayWithSixElements, shapeOfArrayWithSixElements);
+            for (int invalidIndex : invalidIndexes) {
+                Assert.assertThrows(IndexOutOfBoundsException.class,
+                        () -> tensorBuffer.getFloatValue(invalidIndex));
+            }
+        }
+    }
+
+    @Test
+    public void testGetFloatValueFromScalarWithInvalidIndex() {
+        int[] shape = new int[] {};
+        float[] arr = new float[] {10.0f};
+        int[] invalidIndexes =
+                new int[] {-1, 1}; // -1 is negative, and 1 is not smaller than the flatsize.
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            tensorBuffer.loadArray(arr, shape);
+            for (int invalidIndex : invalidIndexes) {
+                Assert.assertThrows(IndexOutOfBoundsException.class,
+                        () -> tensorBuffer.getFloatValue(invalidIndex));
+            }
+        }
+    }
+
+    @Test
+    public void testGetIntValueWithInvalidIndex() {
+        float[] arrayWithSixElements = FLOAT_ARRAY1;
+        int[] shapeOfArrayWithSixElements = ARRAY1_SHAPE;
+        int[] invalidIndexes = {-1, 7};
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            tensorBuffer.loadArray(arrayWithSixElements, shapeOfArrayWithSixElements);
+            for (int invalidIndex : invalidIndexes) {
+                Assert.assertThrows(IndexOutOfBoundsException.class,
+                        () -> tensorBuffer.getIntValue(invalidIndex));
+            }
+        }
+    }
+
+    @Test
+    public void testGetIntValueFromScalarWithInvalidIndex() {
+        int[] shape = new int[] {};
+        float[] arr = new float[] {10.0f};
+        int[] invalidIndexes =
+                new int[] {-1, 1}; // -1 is negative, and 1 is not smaller than the flatsize.
+        for (DataType dataType : ArrayTestRunner.getBufferTypeList()) {
+            TensorBuffer tensorBuffer = TensorBuffer.createDynamic(dataType);
+            tensorBuffer.loadArray(arr, shape);
+            for (int invalidIndex : invalidIndexes) {
+                Assert.assertThrows(IndexOutOfBoundsException.class,
+                        () -> tensorBuffer.getIntValue(invalidIndex));
+            }
+        }
+    }
+
+    @Test
+    public void testLoadByteBufferSliceForTensorBufferFloat() {
+        TensorBuffer original = TensorBuffer.createDynamic(DataType.FLOAT32);
+        original.loadArray(new float[] {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f}, new int[] {6});
+        ByteBuffer buffer = original.getBuffer();
+        // Slice original buffer to 3 sub-buffer, each of which has 2 element
+        int numBuffers = 3;
+        int numElements = 2;
+        int subArrayLength = numElements * original.getTypeSize();
+        TensorBuffer tensorSlice = TensorBuffer.createDynamic(original.getDataType());
+        for (int i = 0; i < numBuffers; i++) {
+            buffer.position(i * subArrayLength);
+            ByteBuffer subBuffer = buffer.slice();
+            // ByteBuffer.slice doesn't keep order.
+            subBuffer.order(buffer.order()).limit(subArrayLength);
+            tensorSlice.loadBuffer(subBuffer, new int[] {numElements});
+            float[] arraySlice = tensorSlice.getFloatArray();
+            assertThat(arraySlice.length).isEqualTo(numElements);
+            assertThat(arraySlice[0]).isEqualTo(i * numElements + 1);
+            assertThat(arraySlice[1]).isEqualTo(i * numElements + 2);
+        }
+    }
+
+    @Test
+    public void testLoadByteBufferSliceForTensorBufferUInt8() {
+        TensorBuffer original = TensorBuffer.createDynamic(DataType.UINT8);
+        original.loadArray(new int[] {1, 2, 3, 4, 5, 6}, new int[] {6});
+        ByteBuffer buffer = original.getBuffer();
+        // Slice original buffer to 3 sub-buffer, each of which has 2 element
+        int numBuffers = 3;
+        int numElements = 2;
+        int subArrayLength = numElements * original.getTypeSize();
+        TensorBuffer tensorSlice = TensorBuffer.createDynamic(original.getDataType());
+        for (int i = 0; i < numBuffers; i++) {
+            buffer.position(i * subArrayLength);
+            ByteBuffer subBuffer = buffer.slice();
+            // ByteBuffer.slice doesn't keep order.
+            subBuffer.order(buffer.order()).limit(subArrayLength);
+            tensorSlice.loadBuffer(subBuffer, new int[] {numElements});
+            int[] arraySlice = tensorSlice.getIntArray();
+            assertThat(arraySlice.length).isEqualTo(numElements);
+            assertThat(arraySlice[0]).isEqualTo(i * numElements + 1);
+            assertThat(arraySlice[1]).isEqualTo(i * numElements + 2);
+        }
+    }
+
+    @Test
+    public void getShapeFailsAfterByteBufferChanged() {
+        TensorBuffer tensorBuffer =
+                TensorBuffer.createFixedSize(new int[] {3, 2}, DataType.FLOAT32);
+        ByteBuffer byteBuffer = tensorBuffer.getBuffer();
+        byteBuffer.limit(5);
+
+        IllegalStateException exception =
+                assertThrows(IllegalStateException.class, tensorBuffer::getShape);
+        assertThat(exception).hasMessageThat().contains(
+                "The size of underlying ByteBuffer (5) and the shape ([3, 2]) do not match. The"
+                + " ByteBuffer may have been changed.");
+    }
+
+    @Test
+    public void getFlatSizeFailsAfterByteBufferChanged() {
+        TensorBuffer tensorBuffer =
+                TensorBuffer.createFixedSize(new int[] {3, 2}, DataType.FLOAT32);
+        ByteBuffer byteBuffer = tensorBuffer.getBuffer();
+        byteBuffer.limit(5);
+
+        IllegalStateException exception =
+                assertThrows(IllegalStateException.class, tensorBuffer::getFlatSize);
+        assertThat(exception).hasMessageThat().contains(
+                "The size of underlying ByteBuffer (5) and the shape ([3, 2]) do not match. The"
+                + " ByteBuffer may have been changed.");
+    }
+
+    @Test
+    public void loadReadOnlyBuffersCopiesOnWrite() {
+        TensorBuffer tensorBuffer = TensorBuffer.createDynamic(DataType.UINT8);
+        ByteBuffer originalByteBuffer = ByteBuffer.allocateDirect(1);
+        originalByteBuffer.put(new byte[] {99});
+        originalByteBuffer.rewind();
+        ByteBuffer readOnlyByteBuffer = originalByteBuffer.asReadOnlyBuffer();
+
+        tensorBuffer.loadBuffer(readOnlyByteBuffer, new int[] {1});
+        assertThat(tensorBuffer.getBuffer()).isSameInstanceAs(readOnlyByteBuffer);
+
+        tensorBuffer.loadArray(new int[] {42});
+        assertThat(tensorBuffer.getBuffer()).isNotSameInstanceAs(readOnlyByteBuffer);
+        assertThat(tensorBuffer.getBuffer().get(0)).isEqualTo(42); // updated
+        assertThat(originalByteBuffer.get(0)).isEqualTo(99); // original one not changed
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java
new file mode 100644
index 0000000..1921f4e46
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/tensorbuffer/TensorBufferUint8Test.java
@@ -0,0 +1,76 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package org.tensorflow.lite.support.tensorbuffer;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import org.junit.Assert;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+import org.tensorflow.lite.DataType;
+
+/** Tests of {@link org.tensorflow.lite.support.tensorbuffer.TensorBufferUint8}. */
+@RunWith(RobolectricTestRunner.class)
+public final class TensorBufferUint8Test {
+    @Test
+    public void testCreateDynamic() {
+        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8();
+        assertThat(tensorBufferUint8).isNotNull();
+    }
+
+    @Test
+    public void testCreateFixedSize() {
+        int[] shape = new int[] {1, 2, 3};
+        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
+        assertThat(tensorBufferUint8).isNotNull();
+        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(6);
+    }
+
+    @Test
+    public void testCreateFixedSizeWithScalarShape() {
+        int[] shape = new int[] {};
+        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
+        assertThat(tensorBufferUint8).isNotNull();
+        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(1);
+    }
+
+    @Test
+    public void testCreateWithNullShape() {
+        int[] shape = null;
+        Assert.assertThrows(NullPointerException.class, () -> new TensorBufferUint8(shape));
+    }
+
+    @Test
+    public void testCreateWithInvalidShape() {
+        int[] shape = new int[] {1, -1, 2};
+        Assert.assertThrows(IllegalArgumentException.class, () -> new TensorBufferUint8(shape));
+    }
+
+    @Test
+    public void testCreateUsingShapeWithZero() {
+        int[] shape = new int[] {1, 0, 2};
+        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8(shape);
+        assertThat(tensorBufferUint8).isNotNull();
+        assertThat(tensorBufferUint8.getFlatSize()).isEqualTo(0);
+    }
+
+    @Test
+    public void testGetDataType() {
+        TensorBufferUint8 tensorBufferUint8 = new TensorBufferUint8();
+        assertThat(tensorBufferUint8.getDataType()).isEqualTo(DataType.UINT8);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/BUILD
new file mode 100644
index 0000000..120b396
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/BUILD
@@ -0,0 +1,36 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library_with_tflite(
+    name = "task_audio_native",
+    srcs = [
+        ":libtask_audio_jni.so",
+    ],
+)
+
+jni_binary_with_tflite(
+    name = "libtask_audio_jni.so",
+    srcs = [
+        "//tensorflow_lite_support/java/src/native/task/audio/classifier:audio_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
+    ],
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
+        "//tensorflow_lite_support/cc/task/audio:audio_classifier",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/audio/core:audio_buffer",
+        "//tensorflow_lite_support/cc/task/audio/proto:audio_classifier_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/audio/proto:class_proto_inc",
+        "//tensorflow_lite_support/cc/task/audio/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+        "//tensorflow_lite_support/java/jni",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/BUILD
new file mode 100644
index 0000000..af9bff9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/BUILD
@@ -0,0 +1,47 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files(["audio_classifier_jni.cc"])
+
+cc_library_with_tflite(
+    name = "audio_classifier_native",
+    srcs = [
+        ":libtask_audio_jni.so",
+    ],
+)
+
+jni_binary_with_tflite(
+    name = "libtask_audio_jni.so",
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        ":native_without_resolver",
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
+    ],
+)
+
+# Shared native logic for AudioClassifier. Combine this target and customized
+# version of op_resolver to build customized audio_classifier_native target.
+cc_library_with_tflite(
+    name = "native_without_resolver",
+    srcs = [
+        "audio_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/audio:audio_classifier",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/audio/core:audio_buffer",
+        "//tensorflow_lite_support/cc/task/audio/proto:audio_classifier_options_cc_proto",
+        "//tensorflow_lite_support/cc/task/audio/proto:class_proto_inc",
+        "//tensorflow_lite_support/cc/task/audio/proto:classifications_proto_inc",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+        "//tensorflow_lite_support/java/jni",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc
new file mode 100644
index 0000000..c3c21fa4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/audio/classifier/audio_classifier_jni.cc
@@ -0,0 +1,373 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <jni.h>
+
+#include <memory>
+#include <string>
+
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/audio/audio_classifier.h"
+#include "tensorflow_lite_support/cc/task/audio/core/audio_buffer.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/audio_classifier_options.pb.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/class_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/audio/proto/classifications_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/utils/jni_utils.h"
+
+namespace tflite {
+namespace task {
+// To be provided by a link-time library
+extern std::unique_ptr<OpResolver> CreateOpResolver();
+
+}  // namespace task
+}  // namespace tflite
+
+namespace {
+
+using ::tflite::support::StatusOr;
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
+using ::tflite::support::utils::kIllegalArgumentException;
+using ::tflite::support::utils::kInvalidPointer;
+using ::tflite::support::utils::StringListToVector;
+using ::tflite::support::utils::ThrowException;
+using ::tflite::task::audio::AudioBuffer;
+using ::tflite::task::audio::AudioClassifier;
+using ::tflite::task::audio::AudioClassifierOptions;
+using ::tflite::task::audio::Class;
+using ::tflite::task::audio::ClassificationResult;
+using ::tflite::task::core::BaseOptions;
+
+// TODO(b/183343074): Share the code below with ImageClassifier.
+
+constexpr char kCategoryClassName[] =
+    "org/tensorflow/lite/support/label/Category";
+constexpr char kStringClassName[] = "Ljava/lang/String;";
+constexpr char kEmptyString[] = "";
+
+jobject ConvertToCategory(JNIEnv* env, const Class& classification) {
+  // jclass and init of Category.
+  jclass category_class = env->FindClass(kCategoryClassName);
+  jmethodID category_create = env->GetStaticMethodID(
+      category_class, "create",
+      absl::StrCat("(", kStringClassName, kStringClassName, "FI)L",
+                   kCategoryClassName, ";")
+          .c_str());
+
+  std::string label_string = classification.has_class_name()
+                                 ? classification.class_name()
+                                 : std::to_string(classification.index());
+  jstring label = env->NewStringUTF(label_string.c_str());
+  std::string display_name_string = classification.has_display_name()
+                                        ? classification.display_name()
+                                        : kEmptyString;
+  jstring display_name = env->NewStringUTF(display_name_string.c_str());
+  jobject jcategory = env->CallStaticObjectMethod(
+      category_class, category_create, label, display_name,
+      classification.score(), classification.index());
+  env->DeleteLocalRef(category_class);
+  env->DeleteLocalRef(label);
+  env->DeleteLocalRef(display_name);
+  return jcategory;
+}
+
+jobject ConvertToClassificationResults(JNIEnv* env,
+                                       const ClassificationResult& results) {
+  // jclass and init of Classifications.
+  jclass classifications_class = env->FindClass(
+      "org/tensorflow/lite/task/audio/classifier/Classifications");
+  jmethodID classifications_create = env->GetStaticMethodID(
+      classifications_class, "create",
+      "(Ljava/util/List;ILjava/lang/String;)Lorg/tensorflow/lite/"
+      "task/audio/classifier/Classifications;");
+
+  // jclass, init, and add of ArrayList.
+  jclass array_list_class = env->FindClass("java/util/ArrayList");
+  jmethodID array_list_init =
+      env->GetMethodID(array_list_class, "<init>", "(I)V");
+  jmethodID array_list_add_method =
+      env->GetMethodID(array_list_class, "add", "(Ljava/lang/Object;)Z");
+
+  jobject classifications_list =
+      env->NewObject(array_list_class, array_list_init,
+                     static_cast<jint>(results.classifications_size()));
+  for (int i = 0; i < results.classifications_size(); i++) {
+    auto classifications = results.classifications(i);
+    jobject jcategory_list = env->NewObject(array_list_class, array_list_init,
+                                            classifications.classes_size());
+    for (const auto& classification : classifications.classes()) {
+      jobject jcategory = ConvertToCategory(env, classification);
+      env->CallBooleanMethod(jcategory_list, array_list_add_method, jcategory);
+
+      env->DeleteLocalRef(jcategory);
+    }
+
+    std::string head_name_string =
+        classifications.has_head_name()
+            ? classifications.head_name()
+            : std::to_string(classifications.head_index());
+    jstring head_name = env->NewStringUTF(head_name_string.c_str());
+
+    jobject jclassifications = env->CallStaticObjectMethod(
+        classifications_class, classifications_create, jcategory_list,
+        classifications.head_index(), head_name);
+    env->CallBooleanMethod(classifications_list, array_list_add_method,
+                           jclassifications);
+
+    env->DeleteLocalRef(head_name);
+    env->DeleteLocalRef(jcategory_list);
+    env->DeleteLocalRef(jclassifications);
+  }
+  return classifications_list;
+}
+
+// Creates an AudioClassifierOptions proto based on the Java class.
+AudioClassifierOptions ConvertToProtoOptions(JNIEnv* env,
+                                             jobject java_options,
+                                             jlong base_options_handle) {
+  AudioClassifierOptions proto_options;
+
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+
+  jclass java_options_class = env->FindClass(
+      "org/tensorflow/lite/task/audio/classifier/"
+      "AudioClassifier$AudioClassifierOptions");
+
+  jmethodID display_names_locale_id = env->GetMethodID(
+      java_options_class, "getDisplayNamesLocale", "()Ljava/lang/String;");
+  jstring display_names_locale = static_cast<jstring>(
+      env->CallObjectMethod(java_options, display_names_locale_id));
+  const char* pchars = env->GetStringUTFChars(display_names_locale, nullptr);
+  proto_options.set_display_names_locale(pchars);
+  env->ReleaseStringUTFChars(display_names_locale, pchars);
+
+  jmethodID max_results_id =
+      env->GetMethodID(java_options_class, "getMaxResults", "()I");
+  jint max_results = env->CallIntMethod(java_options, max_results_id);
+  proto_options.set_max_results(max_results);
+
+  jmethodID is_score_threshold_set_id =
+      env->GetMethodID(java_options_class, "getIsScoreThresholdSet", "()Z");
+  jboolean is_score_threshold_set =
+      env->CallBooleanMethod(java_options, is_score_threshold_set_id);
+  if (is_score_threshold_set) {
+    jmethodID score_threshold_id =
+        env->GetMethodID(java_options_class, "getScoreThreshold", "()F");
+    jfloat score_threshold =
+        env->CallFloatMethod(java_options, score_threshold_id);
+    proto_options.set_score_threshold(score_threshold);
+  }
+
+  jmethodID allow_list_id = env->GetMethodID(
+      java_options_class, "getLabelAllowList", "()Ljava/util/List;");
+  jobject allow_list = env->CallObjectMethod(java_options, allow_list_id);
+  auto allow_list_vector = StringListToVector(env, allow_list);
+  for (const auto& class_name : allow_list_vector) {
+    proto_options.add_class_name_allowlist(class_name);
+  }
+
+  jmethodID deny_list_id = env->GetMethodID(
+      java_options_class, "getLabelDenyList", "()Ljava/util/List;");
+  jobject deny_list = env->CallObjectMethod(java_options, deny_list_id);
+  auto deny_list_vector = StringListToVector(env, deny_list);
+  for (const auto& class_name : deny_list_vector) {
+    proto_options.add_class_name_denylist(class_name);
+  }
+
+  return proto_options;
+}
+
+jlong CreateAudioClassifierFromOptions(JNIEnv* env,
+                                       const AudioClassifierOptions& options) {
+  StatusOr<std::unique_ptr<AudioClassifier>> audio_classifier_or =
+      AudioClassifier::CreateFromOptions(options,
+                                         tflite::task::CreateOpResolver());
+  if (audio_classifier_or.ok()) {
+    // Deletion is handled at deinitJni time.
+    return reinterpret_cast<jlong>(audio_classifier_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(audio_classifier_or.status().code()),
+        "Error occurred when initializing AudioClassifier: %s",
+        audio_classifier_or.status().message().data());
+  }
+  return kInvalidPointer;
+}
+
+}  // namespace
+
+extern "C" JNIEXPORT void JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_deinitJni(
+    JNIEnv* env,
+    jobject thiz,
+    jlong native_handle) {
+  delete reinterpret_cast<AudioClassifier*>(native_handle);
+}
+
+// Creates an AudioClassifier instance from the model file descriptor.
+// file_descriptor_length and file_descriptor_offset are optional. Non-possitive
+// values will be ignored.
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_initJniWithModelFdAndOptions(
+    JNIEnv* env,
+    jclass thiz,
+    jint file_descriptor,
+    jlong file_descriptor_length,
+    jlong file_descriptor_offset,
+    jobject java_options,
+    jlong base_options_handle) {
+  AudioClassifierOptions proto_options =
+      ConvertToProtoOptions(env, java_options, base_options_handle);
+  auto file_descriptor_meta = proto_options.mutable_base_options()
+                                  ->mutable_model_file()
+                                  ->mutable_file_descriptor_meta();
+  file_descriptor_meta->set_fd(file_descriptor);
+  if (file_descriptor_length > 0) {
+    file_descriptor_meta->set_length(file_descriptor_length);
+  }
+  if (file_descriptor_offset > 0) {
+    file_descriptor_meta->set_offset(file_descriptor_offset);
+  }
+  return CreateAudioClassifierFromOptions(env, proto_options);
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_initJniWithByteBuffer(
+    JNIEnv* env,
+    jclass thiz,
+    jobject model_buffer,
+    jobject java_options,
+    jlong base_options_handle) {
+  AudioClassifierOptions proto_options =
+      ConvertToProtoOptions(env, java_options, base_options_handle);
+  // External proto generated header does not overload `set_file_content` with
+  // string_view, therefore GetMappedFileBuffer does not apply here.
+  // Creating a std::string will cause one extra copying of data. Thus, the
+  // most efficient way here is to set file_content using char* and its size.
+  proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+      static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
+      static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
+  return CreateAudioClassifierFromOptions(env, proto_options);
+}
+
+// TODO(b/183343074): JNI method invocation is very expensive, taking about .2ms
+// each time. Consider retrieving the AudioFormat during initialization and
+// caching it in JAVA layer.
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredSampleRateNative(
+    JNIEnv* env,
+    jclass thiz,
+    jlong native_handle) {
+  auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+  StatusOr<AudioBuffer::AudioFormat> format_or =
+      classifier->GetRequiredAudioFormat();
+  if (format_or.ok()) {
+    return format_or->sample_rate;
+  } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(format_or.status().code()),
+        "Error occurred when getting sample rate from AudioClassifier: %s",
+        format_or.status().message());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredChannelsNative(
+    JNIEnv* env,
+    jclass thiz,
+    jlong native_handle) {
+  auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+  StatusOr<AudioBuffer::AudioFormat> format_or =
+      classifier->GetRequiredAudioFormat();
+  if (format_or.ok()) {
+    return format_or->channels;
+  } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(format_or.status().code()),
+        "Error occurred when gettng channels from AudioClassifier: %s",
+        format_or.status().message());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_getRequiredInputBufferSizeNative(
+    JNIEnv* env,
+    jclass thiz,
+    jlong native_handle) {
+  auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+  return classifier->GetRequiredInputBufferSize();
+}
+
+extern "C" JNIEXPORT jobject JNICALL
+Java_org_tensorflow_lite_task_audio_classifier_AudioClassifier_classifyNative(
+    JNIEnv* env,
+    jclass thiz,
+    jlong native_handle,
+    jbyteArray java_array,
+    jint channels,
+    jint sample_rate) {
+  // Get the primitive native array. Depending on the JAVA runtime, the returned
+  // array might be a copy of the JAVA array (or not).
+  jbyte* native_array = env->GetByteArrayElements(java_array, nullptr);
+  if (native_array == nullptr) {
+    ThrowException(env, kIllegalArgumentException,
+                   "Error occurred when converting the java audio input array "
+                   "to native array.");
+    return nullptr;
+  }
+
+  jobject classification_results = nullptr;
+
+  // Prepare the AudioBuffer.
+  AudioBuffer::AudioFormat format = {channels, sample_rate};
+  const int size_in_bytes = env->GetArrayLength(java_array);
+  const int size_in_float = size_in_bytes / sizeof(float);
+  const StatusOr<std::unique_ptr<AudioBuffer>> audio_buffer_or =
+      AudioBuffer::Create(reinterpret_cast<float*>(native_array), size_in_float,
+                          format);
+
+  if (audio_buffer_or.ok()) {
+    // Actual classification
+    auto* classifier = reinterpret_cast<AudioClassifier*>(native_handle);
+    auto results_or = classifier->Classify(*(audio_buffer_or.value()));
+    if (results_or.ok()) {
+      classification_results =
+          ConvertToClassificationResults(env, results_or.value());
+    } else {
+      ThrowException(
+          env, GetExceptionClassNameForStatusCode(results_or.status().code()),
+          "Error occurred when classifying the audio clip: %s",
+          results_or.status().message().data());
+    }
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(audio_buffer_or.status().code()),
+        "Error occurred when creating the AudioBuffer: %s",
+        audio_buffer_or.status().message().data());
+  }
+
+  // Mark native_array as no longer needed.
+  // TODO(b/183343074): Wrap this in SimpleCleanUp.
+  env->ReleaseByteArrayElements(java_array, native_array, /*mode=*/0);
+  return classification_results;
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/BUILD
index d4dd7ab3..2653bf6 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/BUILD
@@ -1,16 +1,25 @@
+load(
+    "@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl",
+    "cc_library_with_tflite",
+)
+
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
     licenses = ["notice"],  # Apache 2.0
 )
 
+exports_files(["task_jni_utils.cc"])
+
 # Default provider for BuiltInOpResover. Create your own target, overwrite the
 # function to provide a MutableOpResolver for customized OPs and/or a subset of
 # builtin OPs.
-cc_library(
+cc_library_with_tflite(
     name = "builtin_op_resolver",
     srcs = ["builtin_op_resolver.cc"],
+    tflite_deps = [
+        "@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
+    ],
     deps = [
-        "@org_tensorflow//tensorflow/lite:framework",
-        "@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
+        "@org_tensorflow//tensorflow/lite:op_resolver",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/builtin_op_resolver.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/builtin_op_resolver.cc
index 050f49f..440a12f73b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/builtin_op_resolver.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/builtin_op_resolver.cc
@@ -13,14 +13,14 @@
 limitations under the License.
 ==============================================================================*/
 
-#include "tensorflow/lite/kernels/register.h"
+#include "tensorflow/lite/core/shims/cc/kernels/register.h"
 
 namespace tflite {
 namespace task {
 // Default provider for OpResolver, provides BuiltinOpResolver.
 std::unique_ptr<OpResolver> CreateOpResolver() {  // NOLINT
-  return std::unique_ptr<tflite::ops::builtin::BuiltinOpResolver>(
-      new tflite::ops::builtin::BuiltinOpResolver);
+  return std::unique_ptr<tflite_shims::ops::builtin::BuiltinOpResolver>(
+      new tflite_shims::ops::builtin::BuiltinOpResolver);
 }
 
 }  // namespace task
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc
new file mode 100644
index 0000000..75f93d6f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/core/task_jni_utils.cc
@@ -0,0 +1,55 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <jni.h>
+
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/utils/jni_utils.h"
+
+namespace {
+
+using ::tflite::proto::Delegate;
+using ::tflite::support::StatusOr;
+using ::tflite::support::utils::ConvertToProtoDelegate;
+using ::tflite::support::utils::kIllegalStateException;
+using ::tflite::support::utils::kInvalidPointer;
+using ::tflite::support::utils::ThrowException;
+using ::tflite::task::core::BaseOptions;
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_core_TaskJniUtils_createProtoBaseOptions(
+    JNIEnv* env,
+    jclass thiz,
+    jint delegate,
+    jint num_threads) {
+  StatusOr<Delegate> delegate_proto_or = ConvertToProtoDelegate(delegate);
+  if (!delegate_proto_or.ok()) {
+    ThrowException(env, kIllegalStateException,
+                   "Error occurred when converting to the proto delegate: %s",
+                   delegate_proto_or.status().message().data());
+    return kInvalidPointer;
+  }
+
+  // base_options will be owned by the task proto options, such as
+  // ImageClassifierOptions.
+  BaseOptions* base_options = new BaseOptions();
+  auto tflite_settings =
+      base_options->mutable_compute_settings()->mutable_tflite_settings();
+  tflite_settings->set_delegate(delegate_proto_or.value());
+  tflite_settings->mutable_cpu_settings()->set_num_threads(num_threads);
+  return reinterpret_cast<jlong>(base_options);
+}
+
+}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/BUILD
index a27aba5..88498f9 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/BUILD
@@ -1,34 +1,39 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
     licenses = ["notice"],  # Apache 2.0
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "task_text_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_text_jni.so",
     ],
 )
 
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_text_jni.so",
     srcs = [
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
         "//tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_jni.cc",
-        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier:bert_nl_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert:bert_nl_classifier_jni.cc",
         "//tensorflow_lite_support/java/src/native/task/text/qa:bert_question_answerer_jni.cc",
     ],
     linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
-    deps = [
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier",
+    tflite_deps = [
         "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
-        "//tensorflow_lite_support/cc/task/text/qa:bert_question_answerer",
+        "//tensorflow_lite_support/cc/task/text:bert_nl_classifier",
+        "//tensorflow_lite_support/cc/task/text:bert_question_answerer",
         "//tensorflow_lite_support/cc/utils:jni_utils",
-        "//tensorflow_lite_support/java/jni",
-        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
         "//tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_jni_utils",
-        "@org_tensorflow//tensorflow/lite:framework",
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/text/proto:bert_nl_classifier_options_proto_inc",
+        "//tensorflow_lite_support/java/jni",
+        "@org_tensorflow//tensorflow/lite:op_resolver",
         "@org_tensorflow//tensorflow/lite/kernels:kernel_util",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/BUILD
index 316c6d6..116df93 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/BUILD
@@ -1,4 +1,4 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
@@ -10,58 +10,51 @@
 ])
 
 # Default native target for nl_classifier to provide BuiltInOpResolver.
-cc_library(
+cc_library_with_tflite(
     name = "nl_classifier_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_text_jni.so",
     ],
+    deps = [
+        "@org_tensorflow//tensorflow/lite/kernels:deprecated_backends",
+    ],
 )
 
 # Note: "libtask_text_jni" is hardcoded in Java to look up the .so, therefore
 # the name should remain the same when creating customized version of
 # nl_classifier_native
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_text_jni.so",
     linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
-    deps = [
+    tflite_deps = [
         ":native_without_resolver",
         "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
     ],
 )
 
-# Custom ops resolver for Wear OS Smart Reply.
-cc_library(
-    name = "custom_ops_resolver_for_smart_reply",
-    srcs = ["custom_ops_resolver_for_smart_reply.cc"],
-    deps = [
-        "//knowledge/hobbes/chat/tensorflow/tflite:tflite-all-lingua-ops-resolver",
-        "@com_google_absl//absl/memory",
-        "@org_tensorflow//tensorflow/lite:framework",
-        "@org_tensorflow//tensorflow/lite:string_util",
-        "@org_tensorflow//tensorflow/lite/kernels:kernel_util",
-        "@org_tensorflow//tensorflow/lite/schema:schema_fbs",
-    ],
-)
-
 # Shared native logic for NLClassifier. Combine this target and customized
 # version of op_resolver to build customized nl_classifier_native target.
-cc_library(
+cc_library_with_tflite(
     name = "native_without_resolver",
     srcs = [
         "nl_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
     ],
-    deps = [
+    tflite_deps = [
         ":nl_classifier_jni_utils",
         "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
         "//tensorflow_lite_support/cc/utils:jni_utils",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/java/jni",
-        "@org_tensorflow//tensorflow/lite:framework",
+        "@org_tensorflow//tensorflow/lite:op_resolver",
         "@org_tensorflow//tensorflow/lite/kernels:kernel_util",
     ],
     alwayslink = 1,
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "nl_classifier_jni_utils",
     srcs = [
         "nl_classifier_jni_utils.cc",
@@ -69,9 +62,11 @@
     hdrs = [
         "nl_classifier_jni_utils.h",
     ],
-    deps = [
+    tflite_deps = [
         "//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier",
         "//tensorflow_lite_support/cc/utils:jni_utils",
+    ],
+    deps = [
         "//tensorflow_lite_support/java/jni",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/BUILD
new file mode 100644
index 0000000..e104ab89a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/BUILD
@@ -0,0 +1,36 @@
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files([
+    "bert_nl_classifier_jni.cc",
+])
+
+cc_library_with_tflite(
+    name = "bert_nl_classifier_native",
+    tflite_jni_binaries = [
+        ":libtask_text_jni.so",
+    ],
+)
+
+jni_binary_with_tflite(
+    name = "libtask_text_jni.so",
+    srcs = [
+        "bert_nl_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
+    ],
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/text:bert_nl_classifier",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_jni_utils",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
+        "//tensorflow_lite_support/cc/task/text/proto:bert_nl_classifier_options_proto_inc",
+        "//tensorflow_lite_support/java/jni",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc
new file mode 100644
index 0000000..2daacdf
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert/bert_nl_classifier_jni.cc
@@ -0,0 +1,118 @@
+/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <jni.h>
+
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
+#include "tensorflow_lite_support/cc/task/text/proto/bert_nl_classifier_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/utils/jni_utils.h"
+#include "tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni_utils.h"
+
+namespace {
+
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
+using ::tflite::support::utils::kInvalidPointer;
+using ::tflite::support::utils::ThrowException;
+using ::tflite::task::core::BaseOptions;
+using ::tflite::task::text::BertNLClassifier;
+using ::tflite::task::text::BertNLClassifierOptions;
+using ::tflite::task::text::nlclassifier::RunClassifier;
+
+BertNLClassifierOptions ConvertJavaBertNLClassifierOptions(
+    JNIEnv* env,
+    jobject java_options,
+    jlong base_options_handle) {
+  BertNLClassifierOptions proto_options;
+
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+  return proto_options;
+}
+
+}  // namespace
+
+extern "C" JNIEXPORT void JNICALL
+Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_deinitJni(
+    JNIEnv* env,
+    jobject thiz,
+    jlong native_handle) {
+  delete reinterpret_cast<BertNLClassifier*>(native_handle);
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithByteBuffer(
+    JNIEnv* env,
+    jclass thiz,
+    jobject model_buffer,
+    jobject java_options,
+    jlong base_options_handle) {
+  BertNLClassifierOptions proto_options = ConvertJavaBertNLClassifierOptions(
+      env, java_options, base_options_handle);
+  proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+      static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
+      static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
+
+  tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>> classifier_or =
+      BertNLClassifier::CreateFromOptions(proto_options);
+  if (classifier_or.ok()) {
+    return reinterpret_cast<jlong>(classifier_or->release());
+  } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(classifier_or.status().code()),
+        "Error occurred when initializing Bert NLClassifier: %s",
+        classifier_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithFileDescriptor(
+    JNIEnv* env,
+    jclass thiz,
+    jint fd,
+    jobject java_options,
+    jlong base_options_handle) {
+  BertNLClassifierOptions proto_options = ConvertJavaBertNLClassifierOptions(
+      env, java_options, base_options_handle);
+  proto_options.mutable_base_options()
+      ->mutable_model_file()
+      ->mutable_file_descriptor_meta()
+      ->set_fd(fd);
+
+  tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>> classifier_or =
+      BertNLClassifier::CreateFromOptions(proto_options);
+  if (classifier_or.ok()) {
+    return reinterpret_cast<jlong>(classifier_or->release());
+  } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(classifier_or.status().code()),
+        "Error occurred when initializing Bert NLClassifier: %s",
+        classifier_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT jobject JNICALL
+Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_classifyNative(
+    JNIEnv* env,
+    jclass clazz,
+    jlong native_handle,
+    jstring text) {
+  return RunClassifier(env, native_handle, text);
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier/BUILD
deleted file mode 100644
index 49f3f4e..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier/BUILD
+++ /dev/null
@@ -1,31 +0,0 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
-
-package(
-    default_visibility = ["//tensorflow_lite_support:users"],
-    licenses = ["notice"],  # Apache 2.0
-)
-
-exports_files([
-    "bert_nl_classifier_jni.cc",
-])
-
-cc_library(
-    name = "bert_nl_classifier_native",
-    srcs = [
-        ":libtask_text_jni.so",
-    ],
-)
-
-tflite_jni_binary(
-    name = "libtask_text_jni.so",
-    srcs = [
-        "bert_nl_classifier_jni.cc",
-    ],
-    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
-    deps = [
-        "//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier",
-        "//tensorflow_lite_support/cc/utils:jni_utils",
-        "//tensorflow_lite_support/java/jni",
-        "//tensorflow_lite_support/java/src/native/task/text/nlclassifier:nl_classifier_jni_utils",
-    ],
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier/bert_nl_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier/bert_nl_classifier_jni.cc
deleted file mode 100644
index 1dd3440..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/bert_nlclassifier/bert_nl_classifier_jni.cc
+++ /dev/null
@@ -1,83 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include <jni.h>
-
-#include "tensorflow_lite_support/cc/task/text/nlclassifier/bert_nl_classifier.h"
-#include "tensorflow_lite_support/cc/utils/jni_utils.h"
-#include "tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni_utils.h"
-
-namespace {
-
-using ::tflite::support::utils::GetMappedFileBuffer;
-using ::tflite::support::utils::kAssertionError;
-using ::tflite::support::utils::kInvalidPointer;
-using ::tflite::support::utils::ThrowException;
-using ::tflite::task::text::nlclassifier::BertNLClassifier;
-using ::tflite::task::text::nlclassifier::RunClassifier;
-
-extern "C" JNIEXPORT void JNICALL
-Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_deinitJni(
-    JNIEnv* env,
-    jobject thiz,
-    jlong native_handle) {
-  delete reinterpret_cast<BertNLClassifier*>(native_handle);
-}
-
-extern "C" JNIEXPORT jlong JNICALL
-Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithByteBuffer(
-    JNIEnv* env,
-    jclass thiz,
-    jobject model_buffer) {
-  auto model = GetMappedFileBuffer(env, model_buffer);
-  tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>> status =
-      BertNLClassifier::CreateFromBuffer(model.data(), model.size());
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
-  } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing Bert NLClassifier: %s",
-                   status.status().message().data());
-    return kInvalidPointer;
-  }
-}
-
-extern "C" JNIEXPORT jlong JNICALL
-Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_initJniWithFileDescriptor(
-    JNIEnv* env,
-    jclass thiz,
-    jint fd) {
-  tflite::support::StatusOr<std::unique_ptr<BertNLClassifier>> status =
-      BertNLClassifier::CreateFromFd(fd);
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
-  } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing Bert NLClassifier: %s",
-                   status.status().message().data());
-    return kInvalidPointer;
-  }
-}
-
-extern "C" JNIEXPORT jobject JNICALL
-Java_org_tensorflow_lite_task_text_nlclassifier_BertNLClassifier_classifyNative(
-    JNIEnv* env,
-    jclass clazz,
-    jlong native_handle,
-    jstring text) {
-  return RunClassifier(env, native_handle, text);
-}
-
-}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/custom_ops_resolver_for_smart_reply.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/custom_ops_resolver_for_smart_reply.cc
deleted file mode 100644
index 48cbd367..0000000
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/custom_ops_resolver_for_smart_reply.cc
+++ /dev/null
@@ -1,30 +0,0 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "absl/memory/memory.h"
-#include "knowledge/hobbes/chat/tensorflow/tflite/tflite-all-lingua-ops-resolver.h"
-#include "tensorflow/lite/op_resolver.h"
-
-namespace tflite {
-namespace task {
-// Provides custom OpResolver for test NLClassifier models.
-std::unique_ptr<OpResolver> CreateOpResolver() {  // NOLINT
-  MutableOpResolver resolver;
-  RegisterAllLinguaOps(&resolver);
-  return absl::make_unique<MutableOpResolver>(resolver);
-}
-
-}  // namespace task
-}  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc
index 6066d1d..4c71a80 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni.cc
@@ -17,6 +17,7 @@
 
 #include "tensorflow/lite/kernels/kernel_util.h"
 #include "tensorflow/lite/op_resolver.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/text/nlclassifier/nl_classifier.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 #include "tensorflow_lite_support/java/src/native/task/text/nlclassifier/nl_classifier_jni_utils.h"
@@ -31,57 +32,66 @@
 
 namespace {
 
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
 using ::tflite::support::utils::GetMappedFileBuffer;
 using ::tflite::support::utils::JStringToString;
-using ::tflite::support::utils::kAssertionError;
 using ::tflite::support::utils::kInvalidPointer;
 using ::tflite::support::utils::ThrowException;
+using ::tflite::task::core::BaseOptions;
+using ::tflite::task::text::NLClassifierOptions;
 using ::tflite::task::text::nlclassifier::NLClassifier;
-using ::tflite::task::text::nlclassifier::NLClassifierOptions;
 using ::tflite::task::text::nlclassifier::RunClassifier;
 
-NLClassifierOptions ConvertJavaNLClassifierOptions(
-    JNIEnv* env,
-    jobject java_nl_classifier_options) {
+NLClassifierOptions ConvertToProtoOptions(JNIEnv* env,
+                                          jobject java_nl_classifier_options,
+                                          jlong base_options_handle) {
   jclass nl_classifier_options_class = env->FindClass(
       "org/tensorflow/lite/task/text/nlclassifier/"
       "NLClassifier$NLClassifierOptions");
-  jmethodID input_tensor_index_method_id =
-      env->GetMethodID(nl_classifier_options_class, "inputTensorIndex", "()I");
+  jmethodID input_tensor_index_method_id = env->GetMethodID(
+      nl_classifier_options_class, "getInputTensorIndex", "()I");
   jmethodID output_score_tensor_index_method_id = env->GetMethodID(
-      nl_classifier_options_class, "outputScoreTensorIndex", "()I");
+      nl_classifier_options_class, "getOutputScoreTensorIndex", "()I");
   jmethodID output_label_tensor_index_method_id = env->GetMethodID(
-      nl_classifier_options_class, "outputLabelTensorIndex", "()I");
-  jmethodID input_tensor_name_method_id = env->GetMethodID(
-      nl_classifier_options_class, "inputTensorName", "()Ljava/lang/String;");
+      nl_classifier_options_class, "getOutputLabelTensorIndex", "()I");
+  jmethodID input_tensor_name_method_id =
+      env->GetMethodID(nl_classifier_options_class, "getInputTensorName",
+                       "()Ljava/lang/String;");
   jmethodID output_score_tensor_name_method_id =
-      env->GetMethodID(nl_classifier_options_class, "outputScoreTensorName",
+      env->GetMethodID(nl_classifier_options_class, "getOutputScoreTensorName",
                        "()Ljava/lang/String;");
   jmethodID output_label_tensor_name_method_id =
-      env->GetMethodID(nl_classifier_options_class, "outputLabelTensorName",
+      env->GetMethodID(nl_classifier_options_class, "getOutputLabelTensorName",
                        "()Ljava/lang/String;");
 
-  return {
-      .input_tensor_index = env->CallIntMethod(java_nl_classifier_options,
-                                               input_tensor_index_method_id),
-      .output_score_tensor_index = env->CallIntMethod(
-          java_nl_classifier_options, output_score_tensor_index_method_id),
-      .output_label_tensor_index = env->CallIntMethod(
-          java_nl_classifier_options, output_label_tensor_index_method_id),
-      .input_tensor_name = JStringToString(
-          env, (jstring)env->CallObjectMethod(java_nl_classifier_options,
-                                              input_tensor_name_method_id)),
-      .output_score_tensor_name = JStringToString(
-          env,
-          (jstring)env->CallObjectMethod(java_nl_classifier_options,
-                                         output_score_tensor_name_method_id)),
-      .output_label_tensor_name = JStringToString(
-          env,
-          (jstring)env->CallObjectMethod(java_nl_classifier_options,
-                                         output_label_tensor_name_method_id)),
-  };
+  NLClassifierOptions proto_options;
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+
+  proto_options.set_input_tensor_index(env->CallIntMethod(
+      java_nl_classifier_options, input_tensor_index_method_id));
+  proto_options.set_output_score_tensor_index(env->CallIntMethod(
+      java_nl_classifier_options, output_score_tensor_index_method_id));
+  proto_options.set_output_label_tensor_index(env->CallIntMethod(
+      java_nl_classifier_options, output_label_tensor_index_method_id));
+  proto_options.set_input_tensor_name(JStringToString(
+      env, (jstring)env->CallObjectMethod(java_nl_classifier_options,
+                                          input_tensor_name_method_id)));
+  proto_options.set_output_score_tensor_name(JStringToString(
+      env, (jstring)env->CallObjectMethod(java_nl_classifier_options,
+                                          output_score_tensor_name_method_id)));
+  proto_options.set_output_label_tensor_name(JStringToString(
+      env, (jstring)env->CallObjectMethod(java_nl_classifier_options,
+                                          output_label_tensor_name_method_id)));
+
+  return proto_options;
 }
 
+}  // namespace
+
 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_text_nlclassifier_NLClassifier_deinitJni(
     JNIEnv* env,
@@ -95,20 +105,25 @@
     JNIEnv* env,
     jclass thiz,
     jobject nl_classifier_options,
-    jobject model_buffer) {
+    jobject model_buffer,
+    jlong base_options_handle) {
   auto model = GetMappedFileBuffer(env, model_buffer);
-  tflite::support::StatusOr<std::unique_ptr<NLClassifier>> status =
-      NLClassifier::CreateFromBufferAndOptions(
-          model.data(), model.size(),
-          ConvertJavaNLClassifierOptions(env, nl_classifier_options),
-          tflite::task::CreateOpResolver());
+  tflite::support::StatusOr<std::unique_ptr<NLClassifier>> classifier_or;
 
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
+  NLClassifierOptions proto_options =
+      ConvertToProtoOptions(env, nl_classifier_options, base_options_handle);
+  proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+      model.data(), model.size());
+  classifier_or = NLClassifier::CreateFromOptions(
+      proto_options, tflite::task::CreateOpResolver());
+
+  if (classifier_or.ok()) {
+    return reinterpret_cast<jlong>(classifier_or->release());
   } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing NLClassifier: %s",
-                   status.status().message().data());
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(classifier_or.status().code()),
+        "Error occurred when initializing NLClassifier: %s",
+        classifier_or.status().message().data());
     return kInvalidPointer;
   }
 }
@@ -118,17 +133,26 @@
     JNIEnv* env,
     jclass thiz,
     jobject nl_classifier_options,
-    jint fd) {
-  tflite::support::StatusOr<std::unique_ptr<NLClassifier>> status =
-      NLClassifier::CreateFromFdAndOptions(
-          fd, ConvertJavaNLClassifierOptions(env, nl_classifier_options),
-          tflite::task::CreateOpResolver());
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
+    jint fd,
+    jlong base_options_handle) {
+  tflite::support::StatusOr<std::unique_ptr<NLClassifier>> classifier_or;
+
+  NLClassifierOptions proto_options =
+      ConvertToProtoOptions(env, nl_classifier_options, base_options_handle);
+  proto_options.mutable_base_options()
+      ->mutable_model_file()
+      ->mutable_file_descriptor_meta()
+      ->set_fd(fd);
+  classifier_or = NLClassifier::CreateFromOptions(
+      proto_options, tflite::task::CreateOpResolver());
+
+  if (classifier_or.ok()) {
+    return reinterpret_cast<jlong>(classifier_or->release());
   } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing NLClassifier: %s",
-                   status.status().message().data());
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(classifier_or.status().code()),
+        "Error occurred when initializing NLClassifier: %s",
+        classifier_or.status().message().data());
     return kInvalidPointer;
   }
 }
@@ -141,5 +165,3 @@
     jstring text) {
   return RunClassifier(env, native_handle, text);
 }
-
-}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/BUILD
index 9753e32..e586105 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/BUILD
@@ -1,4 +1,4 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
@@ -9,22 +9,26 @@
     "bert_question_answerer_jni.cc",
 ])
 
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_text_jni.so",
     srcs = [
         "bert_question_answerer_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
     ],
     linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
-    deps = [
-        "//tensorflow_lite_support/cc/task/text/qa:bert_question_answerer",
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/text:bert_question_answerer",
         "//tensorflow_lite_support/cc/utils:jni_utils",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/java/jni",
     ],
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "bert_question_answerer_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_text_jni.so",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc
index 9dd1895c..401e6fbd 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/text/qa/bert_question_answerer_jni.cc
@@ -15,20 +15,41 @@
 
 #include <jni.h>
 
-#include "tensorflow_lite_support/cc/task/text/qa/bert_question_answerer.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
+#include "tensorflow_lite_support/cc/task/text/bert_question_answerer.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 
 namespace {
 
+using ::tflite::support::StatusOr;
 using ::tflite::support::utils::ConvertVectorToArrayList;
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
 using ::tflite::support::utils::GetMappedFileBuffer;
 using ::tflite::support::utils::JStringToString;
-using ::tflite::task::text::qa::BertQuestionAnswerer;
-using ::tflite::task::text::qa::QaAnswer;
-using ::tflite::task::text::qa::QuestionAnswerer;
+using ::tflite::support::utils::ThrowException;
+using ::tflite::task::core::BaseOptions;
+using ::tflite::task::text::BertQuestionAnswerer;
+using ::tflite::task::text::BertQuestionAnswererOptions;
+using ::tflite::task::text::QaAnswer;
+using ::tflite::task::text::QuestionAnswerer;
 
 constexpr int kInvalidPointer = 0;
 
+// Creates a BertQuestionAnswererOptions proto based on the Java class.
+BertQuestionAnswererOptions ConvertToProtoOptions(jlong base_options_handle) {
+  BertQuestionAnswererOptions proto_options;
+
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+
+  return proto_options;
+}
+
+}  // namespace
+
 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_deinitJni(
     JNIEnv* env,
@@ -38,33 +59,35 @@
 }
 
 extern "C" JNIEXPORT jlong JNICALL
-Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithModelWithMetadataByteBuffers(
-    JNIEnv* env,
-    jclass thiz,
-    jobjectArray model_buffers) {
-  absl::string_view model_with_metadata =
-      GetMappedFileBuffer(env, env->GetObjectArrayElement(model_buffers, 0));
-
-  tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>> status =
-      BertQuestionAnswerer::CreateFromBuffer(model_with_metadata.data(),
-                                             model_with_metadata.size());
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
-  } else {
-    return kInvalidPointer;
-  }
-}
-
-extern "C" JNIEXPORT jlong JNICALL
 Java_org_tensorflow_lite_task_text_qa_BertQuestionAnswerer_initJniWithFileDescriptor(
     JNIEnv* env,
     jclass thiz,
-    jint fd) {
-  tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>> status =
-      BertQuestionAnswerer::CreateFromFd(fd);
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
+    jint file_descriptor,
+    jlong file_descriptor_length,
+    jlong file_descriptor_offset,
+    jlong base_options_handle) {
+  BertQuestionAnswererOptions proto_options =
+      ConvertToProtoOptions(base_options_handle);
+  auto file_descriptor_meta = proto_options.mutable_base_options()
+                                  ->mutable_model_file()
+                                  ->mutable_file_descriptor_meta();
+  file_descriptor_meta->set_fd(file_descriptor);
+  if (file_descriptor_length > 0) {
+    file_descriptor_meta->set_length(file_descriptor_length);
+  }
+  if (file_descriptor_offset > 0) {
+    file_descriptor_meta->set_offset(file_descriptor_offset);
+  }
+
+  StatusOr<std::unique_ptr<QuestionAnswerer>> qa_status =
+      BertQuestionAnswerer::CreateFromOptions(proto_options);
+  if (qa_status.ok()) {
+    return reinterpret_cast<jlong>(qa_status->release());
   } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(qa_status.status().code()),
+        "Error occurred when initializing BertQuestionAnswerer: %s",
+        qa_status.status().message().data());
     return kInvalidPointer;
   }
 }
@@ -79,12 +102,16 @@
   absl::string_view vocab =
       GetMappedFileBuffer(env, env->GetObjectArrayElement(model_buffers, 1));
 
-  tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>> status =
+  StatusOr<std::unique_ptr<QuestionAnswerer>> qa_status =
       BertQuestionAnswerer::CreateBertQuestionAnswererFromBuffer(
           model.data(), model.size(), vocab.data(), vocab.size());
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
+  if (qa_status.ok()) {
+    return reinterpret_cast<jlong>(qa_status->release());
   } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(qa_status.status().code()),
+        "Error occurred when initializing BertQuestionAnswerer: %s",
+        qa_status.status().message().data());
     return kInvalidPointer;
   }
 }
@@ -99,12 +126,16 @@
   absl::string_view sp_model =
       GetMappedFileBuffer(env, env->GetObjectArrayElement(model_buffers, 1));
 
-  tflite::support::StatusOr<std::unique_ptr<QuestionAnswerer>> status =
+  StatusOr<std::unique_ptr<QuestionAnswerer>> qa_status =
       BertQuestionAnswerer::CreateAlbertQuestionAnswererFromBuffer(
           model.data(), model.size(), sp_model.data(), sp_model.size());
-  if (status.ok()) {
-    return reinterpret_cast<jlong>(status->release());
+  if (qa_status.ok()) {
+    return reinterpret_cast<jlong>(qa_status->release());
   } else {
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(qa_status.status().code()),
+        "Error occurred when initializing BertQuestionAnswerer: %s",
+        qa_status.status().message().data());
     return kInvalidPointer;
   }
 }
@@ -136,5 +167,3 @@
         return qa_answer;
       });
 }
-
-}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/BUILD
index 451a50ca..6f784145 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/BUILD
@@ -1,11 +1,11 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
     licenses = ["notice"],  # Apache 2.0
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "jni_utils",
     srcs = [
         "jni_utils.cc",
@@ -13,35 +13,48 @@
     hdrs = [
         "jni_utils.h",
     ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+    ],
     deps = [
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/proto:class_proto_inc",
-        "//tensorflow_lite_support/cc/utils:jni_utils",
+        "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
         "//tensorflow_lite_support/java/jni",
         "@com_google_absl//absl/strings",
     ],
 )
 
-cc_library(
+cc_library_with_tflite(
     name = "task_vision_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_vision_jni.so",
     ],
 )
 
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_vision_jni.so",
     srcs = [
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
         "//tensorflow_lite_support/java/src/native/task/vision/classifier:image_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/vision/core:base_vision_task_api_jni.cc",
         "//tensorflow_lite_support/java/src/native/task/vision/detector:object_detector_jni.cc",
         "//tensorflow_lite_support/java/src/native/task/vision/segmenter:image_segmenter_jni.cc",
     ],
     linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
-    deps = [
-        "//tensorflow_lite_support/cc/port:statusor",
+    tflite_deps = [
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
         "//tensorflow_lite_support/cc/task/vision:image_classifier",
         "//tensorflow_lite_support/cc/task/vision:image_segmenter",
         "//tensorflow_lite_support/cc/task/vision:object_detector",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
+    ],
+    deps = [
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:classifications_proto_inc",
@@ -51,9 +64,7 @@
         "//tensorflow_lite_support/cc/task/vision/proto:object_detector_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:segmentations_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
-        "//tensorflow_lite_support/cc/utils:jni_utils",
         "//tensorflow_lite_support/java/jni",
-        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
         "@com_google_absl//absl/strings",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/BUILD
index 8bddc2a..7fdb8e3 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/BUILD
@@ -1,4 +1,4 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
@@ -7,29 +7,44 @@
 
 exports_files(["image_classifier_jni.cc"])
 
-cc_library(
+cc_library_with_tflite(
     name = "image_classifier_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_vision_jni.so",
     ],
 )
 
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_vision_jni.so",
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        ":native_without_resolver",
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
+    ],
+)
+
+# Shared native logic for ImageClassifier. Combine this target and customized
+# version of op_resolver to build customized image_classifier_native target.
+cc_library_with_tflite(
+    name = "native_without_resolver",
     srcs = [
         "image_classifier_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
+        "//tensorflow_lite_support/java/src/native/task/vision/core:base_vision_task_api_jni.cc",
     ],
-    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/vision:image_classifier",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
+    ],
     deps = [
         "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/vision:image_classifier",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:classifications_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:image_classifier_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
-        "//tensorflow_lite_support/cc/utils:jni_utils",
         "//tensorflow_lite_support/java/jni",
-        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc
index bb8f8ce..2a713cf 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/classifier/image_classifier_jni.cc
@@ -19,6 +19,7 @@
 #include <string>
 
 #include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/image_classifier.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
@@ -28,27 +29,42 @@
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 #include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"
 
+namespace tflite {
+namespace task {
+// To be provided by a link-time library
+extern std::unique_ptr<OpResolver> CreateOpResolver();
+
+}  // namespace task
+}  // namespace tflite
+
 namespace {
 
 using ::tflite::support::StatusOr;
-using ::tflite::support::utils::GetMappedFileBuffer;
-using ::tflite::support::utils::kAssertionError;
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
 using ::tflite::support::utils::kInvalidPointer;
 using ::tflite::support::utils::StringListToVector;
 using ::tflite::support::utils::ThrowException;
+using ::tflite::task::core::BaseOptions;
 using ::tflite::task::vision::BoundingBox;
 using ::tflite::task::vision::ClassificationResult;
 using ::tflite::task::vision::Classifications;
 using ::tflite::task::vision::ConvertToCategory;
-using ::tflite::task::vision::ConvertToFrameBufferOrientation;
 using ::tflite::task::vision::FrameBuffer;
 using ::tflite::task::vision::ImageClassifier;
 using ::tflite::task::vision::ImageClassifierOptions;
 
 // Creates an ImageClassifierOptions proto based on the Java class.
 ImageClassifierOptions ConvertToProtoOptions(JNIEnv* env,
-                                             jobject java_options) {
+                                             jobject java_options,
+                                             jlong base_options_handle) {
   ImageClassifierOptions proto_options;
+
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+
   jclass java_options_class = env->FindClass(
       "org/tensorflow/lite/task/vision/classifier/"
       "ImageClassifier$ImageClassifierOptions");
@@ -93,7 +109,6 @@
   for (const auto& class_name : deny_list_vector) {
     proto_options.add_class_name_blacklist(class_name);
   }
-
   return proto_options;
 }
 
@@ -139,6 +154,26 @@
   return classifications_list;
 }
 
+jlong CreateImageClassifierFromOptions(JNIEnv* env,
+                                       const ImageClassifierOptions& options) {
+  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
+      ImageClassifier::CreateFromOptions(options,
+                                         tflite::task::CreateOpResolver());
+  if (image_classifier_or.ok()) {
+    // Deletion is handled at deinitJni time.
+    return reinterpret_cast<jlong>(image_classifier_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(image_classifier_or.status().code()),
+        "Error occurred when initializing ImageClassifier: %s",
+        image_classifier_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+}  // namespace
+
 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_deinitJni(
     JNIEnv* env,
@@ -147,6 +182,9 @@
   delete reinterpret_cast<ImageClassifier*>(native_handle);
 }
 
+// Creates an ImageClassifier instance from the model file descriptor.
+// file_descriptor_length and file_descriptor_offset are optional. Non-possitive
+// values will be ignored.
 extern "C" JNIEXPORT jlong JNICALL
 Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_initJniWithModelFdAndOptions(
     JNIEnv* env,
@@ -154,26 +192,40 @@
     jint file_descriptor,
     jlong file_descriptor_length,
     jlong file_descriptor_offset,
-    jobject java_options) {
+    jobject java_options,
+    jlong base_options_handle) {
   ImageClassifierOptions proto_options =
-      ConvertToProtoOptions(env, java_options);
-  auto file_descriptor_meta = proto_options.mutable_model_file_with_metadata()
+      ConvertToProtoOptions(env, java_options, base_options_handle);
+  auto file_descriptor_meta = proto_options.mutable_base_options()
+                                  ->mutable_model_file()
                                   ->mutable_file_descriptor_meta();
   file_descriptor_meta->set_fd(file_descriptor);
-  file_descriptor_meta->set_length(file_descriptor_length);
-  file_descriptor_meta->set_offset(file_descriptor_offset);
-
-  StatusOr<std::unique_ptr<ImageClassifier>> image_classifier_or =
-      ImageClassifier::CreateFromOptions(proto_options);
-  if (image_classifier_or.ok()) {
-    // Deletion is handled at deinitJni time.
-    return reinterpret_cast<jlong>(image_classifier_or->release());
-  } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing ImageClassifier: %s",
-                   image_classifier_or.status().message().data());
-    return kInvalidPointer;
+  if (file_descriptor_length > 0) {
+    file_descriptor_meta->set_length(file_descriptor_length);
   }
+  if (file_descriptor_offset > 0) {
+    file_descriptor_meta->set_offset(file_descriptor_offset);
+  }
+  return CreateImageClassifierFromOptions(env, proto_options);
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_vision_classifier_ImageClassifier_initJniWithByteBuffer(
+    JNIEnv* env,
+    jclass thiz,
+    jobject model_buffer,
+    jobject java_options,
+    jlong base_options_handle) {
+  ImageClassifierOptions proto_options =
+      ConvertToProtoOptions(env, java_options, base_options_handle);
+  // External proto generated header does not overload `set_file_content` with
+  // string_view, therefore GetMappedFileBuffer does not apply here.
+  // Creating a std::string will cause one extra copying of data. Thus, the
+  // most efficient way here is to set file_content using char* and its size.
+  proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+      static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
+      static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
+  return CreateImageClassifierFromOptions(env, proto_options);
 }
 
 extern "C" JNIEXPORT jobject JNICALL
@@ -181,17 +233,12 @@
     JNIEnv* env,
     jclass thiz,
     jlong native_handle,
-    jobject image_byte_buffer,
-    jint width,
-    jint height,
-    jintArray jroi,
-    jint jorientation) {
+    jlong frame_buffer_handle,
+    jintArray jroi) {
   auto* classifier = reinterpret_cast<ImageClassifier*>(native_handle);
-  auto image = GetMappedFileBuffer(env, image_byte_buffer);
-  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
-      reinterpret_cast<const uint8*>(image.data()),
-      FrameBuffer::Dimension{width, height},
-      ConvertToFrameBufferOrientation(env, jorientation));
+  // frame_buffer will be deleted after inference is done in
+  // base_vision_api_jni.cc.
+  auto* frame_buffer = reinterpret_cast<FrameBuffer*>(frame_buffer_handle);
 
   int* roi_array = env->GetIntArrayElements(jroi, 0);
   BoundingBox roi;
@@ -205,10 +252,10 @@
   if (results_or.ok()) {
     return ConvertToClassificationResults(env, results_or.value());
   } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when classifying the image: %s",
-                   results_or.status().message().data());
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(results_or.status().code()),
+        "Error occurred when classifying the image: %s",
+        results_or.status().message().data());
     return nullptr;
   }
 }
-}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/BUILD
new file mode 100644
index 0000000..84d36e6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/BUILD
@@ -0,0 +1,6 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files(["base_vision_task_api_jni.cc"])
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc
new file mode 100644
index 0000000..2cda1b5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/core/base_vision_task_api_jni.cc
@@ -0,0 +1,122 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <jni.h>
+
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/utils/jni_utils.h"
+#include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"
+
+namespace {
+
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
+using ::tflite::support::utils::kInvalidPointer;
+using ::tflite::support::utils::ThrowException;
+using ::tflite::task::vision::CreateFrameBufferFromByteBuffer;
+using ::tflite::task::vision::CreateFrameBufferFromBytes;
+using ::tflite::task::vision::CreateFrameBufferFromYuvPlanes;
+using ::tflite::task::vision::FrameBuffer;
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFromByteBuffer(
+    JNIEnv* env,
+    jclass thiz,
+    jobject jimage_byte_buffer,
+    jint width,
+    jint height,
+    jint jorientation,
+    jint jcolor_space_type) {
+  auto frame_buffer_or = CreateFrameBufferFromByteBuffer(
+      env, jimage_byte_buffer, width, height, jorientation, jcolor_space_type);
+  if (frame_buffer_or.ok()) {
+    return reinterpret_cast<jlong>(frame_buffer_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(frame_buffer_or.status().code()),
+        "Error occurred when creating FrameBuffer: %s",
+        frame_buffer_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFromBytes(
+    JNIEnv* env,
+    jclass thiz,
+    jbyteArray jimage_bytes,
+    jint width,
+    jint height,
+    jint jorientation,
+    jint jcolor_space_type,
+    jlongArray jbyte_array_handle) {
+  auto frame_buffer_or =
+      CreateFrameBufferFromBytes(env, jimage_bytes, width, height, jorientation,
+                                 jcolor_space_type, jbyte_array_handle);
+  if (frame_buffer_or.ok()) {
+    return reinterpret_cast<jlong>(frame_buffer_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(frame_buffer_or.status().code()),
+        "Error occurred when creating FrameBuffer: %s",
+        frame_buffer_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_createFrameBufferFromPlanes(
+    JNIEnv* env,
+    jclass thiz,
+    jobject jy_plane,
+    jobject ju_plane,
+    jobject jv_plane,
+    jint width,
+    jint height,
+    jint row_stride_y,
+    jint row_stride_uv,
+    jint pixel_stride_uv,
+    jint orientation) {
+  auto frame_buffer_or = CreateFrameBufferFromYuvPlanes(
+      env, jy_plane, ju_plane, jv_plane, width, height, row_stride_y,
+      row_stride_uv, pixel_stride_uv, orientation);
+  if (frame_buffer_or.ok()) {
+    return reinterpret_cast<jlong>(frame_buffer_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(frame_buffer_or.status().code()),
+        "Error occurred when creating FrameBuffer: %s",
+        frame_buffer_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+extern "C" JNIEXPORT void JNICALL
+Java_org_tensorflow_lite_task_vision_core_BaseVisionTaskApi_deleteFrameBuffer(
+    JNIEnv* env,
+    jobject thiz,
+    jlong frame_buffer_handle,
+    jlong byte_array_handle,
+    jbyteArray jbyte_array) {
+  delete reinterpret_cast<FrameBuffer*>(frame_buffer_handle);
+  jbyte* bytes_ptr = reinterpret_cast<jbyte*>(byte_array_handle);
+  if (bytes_ptr != NULL) {
+    env->ReleaseByteArrayElements(jbyte_array, bytes_ptr, /*mode=*/0);
+  }
+}
+
+}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/BUILD
index 5abd3f1..7fb94132b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/BUILD
@@ -1,4 +1,4 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
@@ -7,30 +7,45 @@
 
 exports_files(["object_detector_jni.cc"])
 
-cc_library(
+cc_library_with_tflite(
     name = "object_detector_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_vision_jni.so",
     ],
 )
 
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_vision_jni.so",
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        ":native_without_resolver",
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
+    ],
+)
+
+# Shared native logic for ObjectDetector. Combine this target and customized
+# version of op_resolver to build customized object_detector_native target.
+cc_library_with_tflite(
+    name = "native_without_resolver",
     srcs = [
         "object_detector_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
+        "//tensorflow_lite_support/java/src/native/task/vision/core:base_vision_task_api_jni.cc",
     ],
-    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/vision:object_detector",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
+    ],
     deps = [
         "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/vision:object_detector",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/proto:bounding_box_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:detections_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:object_detector_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
-        "//tensorflow_lite_support/cc/utils:jni_utils",
         "//tensorflow_lite_support/java/jni",
-        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
         "@com_google_absl//absl/strings",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc
index eca7b26..f720795 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/detector/object_detector_jni.cc
@@ -18,8 +18,9 @@
 #include <memory>
 #include <string>
 
-#include "absl/strings/string_view.h"
+#include "absl/strings/string_view.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/object_detector.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/bounding_box_proto_inc.h"
@@ -29,25 +30,41 @@
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 #include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"
 
+namespace tflite {
+namespace task {
+// To be provided by a link-time library
+extern std::unique_ptr<OpResolver> CreateOpResolver();
+
+}  // namespace task
+}  // namespace tflite
+
 namespace {
 
 using ::tflite::support::StatusOr;
-using ::tflite::support::utils::GetMappedFileBuffer;
-using ::tflite::support::utils::kAssertionError;
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
 using ::tflite::support::utils::kInvalidPointer;
 using ::tflite::support::utils::StringListToVector;
 using ::tflite::support::utils::ThrowException;
+using ::tflite::task::core::BaseOptions;
 using ::tflite::task::vision::BoundingBox;
 using ::tflite::task::vision::ConvertToCategory;
-using ::tflite::task::vision::ConvertToFrameBufferOrientation;
 using ::tflite::task::vision::DetectionResult;
 using ::tflite::task::vision::FrameBuffer;
 using ::tflite::task::vision::ObjectDetector;
 using ::tflite::task::vision::ObjectDetectorOptions;
 
 // Creates an ObjectDetectorOptions proto based on the Java class.
-ObjectDetectorOptions ConvertToProtoOptions(JNIEnv* env, jobject java_options) {
+ObjectDetectorOptions ConvertToProtoOptions(JNIEnv* env,
+                                            jobject java_options,
+                                            jlong base_options_handle) {
   ObjectDetectorOptions proto_options;
+
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+
   jclass java_options_class = env->FindClass(
       "org/tensorflow/lite/task/vision/detector/"
       "ObjectDetector$ObjectDetectorOptions");
@@ -93,7 +110,6 @@
   for (const auto& class_name : deny_list_vector) {
     proto_options.add_class_name_blacklist(class_name);
   }
-
   return proto_options;
 }
 
@@ -147,6 +163,25 @@
   return detections_list;
 }
 
+jlong CreateObjectDetectorFromOptions(JNIEnv* env,
+                                      const ObjectDetectorOptions& options) {
+  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
+      ObjectDetector::CreateFromOptions(options,
+                                        tflite::task::CreateOpResolver());
+  if (object_detector_or.ok()) {
+    return reinterpret_cast<jlong>(object_detector_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(object_detector_or.status().code()),
+        "Error occurred when initializing ObjectDetector: %s",
+        object_detector_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+}  // namespace
+
 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_deinitJni(
     JNIEnv* env,
@@ -155,6 +190,9 @@
   delete reinterpret_cast<ObjectDetector*>(native_handle);
 }
 
+// Creates an ObjectDetector instance from the model file descriptor.
+// file_descriptor_length and file_descriptor_offset are optional. Non-possitive
+// values will be ignored.
 extern "C" JNIEXPORT jlong JNICALL
 Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_initJniWithModelFdAndOptions(
     JNIEnv* env,
@@ -162,25 +200,36 @@
     jint file_descriptor,
     jlong file_descriptor_length,
     jlong file_descriptor_offset,
-    jobject java_options) {
+    jobject java_options,
+    jlong base_options_handle) {
   ObjectDetectorOptions proto_options =
-      ConvertToProtoOptions(env, java_options);
-  auto file_descriptor_meta = proto_options.mutable_model_file_with_metadata()
+      ConvertToProtoOptions(env, java_options, base_options_handle);
+  auto file_descriptor_meta = proto_options.mutable_base_options()
+                                  ->mutable_model_file()
                                   ->mutable_file_descriptor_meta();
   file_descriptor_meta->set_fd(file_descriptor);
-  file_descriptor_meta->set_length(file_descriptor_length);
-  file_descriptor_meta->set_offset(file_descriptor_offset);
-
-  StatusOr<std::unique_ptr<ObjectDetector>> object_detector_or =
-      ObjectDetector::CreateFromOptions(proto_options);
-  if (object_detector_or.ok()) {
-    return reinterpret_cast<jlong>(object_detector_or->release());
-  } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing ObjectDetector: %s",
-                   object_detector_or.status().message().data());
-    return kInvalidPointer;
+  if (file_descriptor_length > 0) {
+    file_descriptor_meta->set_length(file_descriptor_length);
   }
+  if (file_descriptor_offset > 0) {
+    file_descriptor_meta->set_offset(file_descriptor_offset);
+  }
+  return CreateObjectDetectorFromOptions(env, proto_options);
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_vision_detector_ObjectDetector_initJniWithByteBuffer(
+    JNIEnv* env,
+    jclass thiz,
+    jobject model_buffer,
+    jobject java_options,
+    jlong base_options_handle) {
+  ObjectDetectorOptions proto_options =
+      ConvertToProtoOptions(env, java_options, base_options_handle);
+  proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+      static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
+      static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
+  return CreateObjectDetectorFromOptions(env, proto_options);
 }
 
 extern "C" JNIEXPORT jobject JNICALL
@@ -188,24 +237,19 @@
     JNIEnv* env,
     jclass thiz,
     jlong native_handle,
-    jobject image_byte_buffer,
-    jint width,
-    jint height,
-    jint jorientation) {
+    jlong frame_buffer_handle) {
   auto* detector = reinterpret_cast<ObjectDetector*>(native_handle);
-  absl::string_view image = GetMappedFileBuffer(env, image_byte_buffer);
-  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
-      reinterpret_cast<const uint8*>(image.data()),
-      FrameBuffer::Dimension{width, height},
-      ConvertToFrameBufferOrientation(env, jorientation));
+  // frame_buffer will be deleted after inference is done in
+  // base_vision_api_jni.cc.
+  auto* frame_buffer = reinterpret_cast<FrameBuffer*>(frame_buffer_handle);
   auto results_or = detector->Detect(*frame_buffer);
   if (results_or.ok()) {
     return ConvertToDetectionResults(env, results_or.value());
   } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when detecting the image: %s",
-                   results_or.status().message().data());
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(results_or.status().code()),
+        "Error occurred when detecting the image: %s",
+        results_or.status().message().data());
     return nullptr;
   }
 }
-}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc
index eb46b68..e0c94e2e 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.cc
@@ -15,15 +15,21 @@
 
 #include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"
 
-#include "absl/strings/str_cat.h"
+#include "absl/strings/str_cat.h"  // from @com_google_absl
+#include "tensorflow_lite_support/cc/port/status_macros.h"
+#include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
+#include "tensorflow_lite_support/cc/task/vision/utils/frame_buffer_common_utils.h"
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 
 namespace tflite {
 namespace task {
 namespace vision {
 
-using ::tflite::support::utils::kAssertionError;
+using ::tflite::support::StatusOr;
+using ::tflite::support::utils::GetMappedFileBuffer;
+using ::tflite::support::utils::kIllegalStateException;
 using ::tflite::support::utils::ThrowException;
+using ::tflite::task::vision::CreateFromRawBuffer;
 
 constexpr char kCategoryClassName[] =
     "org/tensorflow/lite/support/label/Category";
@@ -35,24 +41,51 @@
   jclass category_class = env->FindClass(kCategoryClassName);
   jmethodID category_create = env->GetStaticMethodID(
       category_class, "create",
-      absl::StrCat("(", kStringClassName, kStringClassName, "F)L",
+      absl::StrCat("(", kStringClassName, kStringClassName, "FI)L",
                    kCategoryClassName, ";")
           .c_str());
 
   std::string label_string = classification.has_class_name()
                                  ? classification.class_name()
-                                 : kEmptyString;
+                                 : std::to_string(classification.index());
   jstring label = env->NewStringUTF(label_string.c_str());
   std::string display_name_string = classification.has_display_name()
                                         ? classification.display_name()
                                         : kEmptyString;
   jstring display_name = env->NewStringUTF(display_name_string.c_str());
-  jobject jcategory =
-      env->CallStaticObjectMethod(category_class, category_create, label,
-                                  display_name, classification.score());
+  jobject jcategory = env->CallStaticObjectMethod(
+      category_class, category_create, label, display_name,
+      classification.score(), classification.index());
+  env->DeleteLocalRef(category_class);
+  env->DeleteLocalRef(label);
+  env->DeleteLocalRef(display_name);
   return jcategory;
 }
 
+FrameBuffer::Format ConvertToFrameBufferFormat(JNIEnv* env,
+                                               jint jcolor_space_type) {
+  switch (jcolor_space_type) {
+    case 0:
+      return FrameBuffer::Format::kRGB;
+    case 1:
+      return FrameBuffer::Format::kGRAY;
+    case 2:
+      return FrameBuffer::Format::kNV12;
+    case 3:
+      return FrameBuffer::Format::kNV21;
+    case 4:
+      return FrameBuffer::Format::kYV12;
+    case 5:
+      return FrameBuffer::Format::kYV21;
+    default:
+      break;
+  }
+  // Should never happen.
+  ThrowException(env, kIllegalStateException,
+                 "The color space type is unsupported: %d", jcolor_space_type);
+  return FrameBuffer::Format::kRGB;
+}
+
 FrameBuffer::Orientation ConvertToFrameBufferOrientation(JNIEnv* env,
                                                          jint jorientation) {
   switch (jorientation) {
@@ -74,12 +107,103 @@
       return FrameBuffer::Orientation::kLeftBottom;
   }
   // Should never happen.
-  ThrowException(env, kAssertionError,
+  ThrowException(env, kIllegalStateException,
                  "The FrameBuffer Orientation type is unsupported: %d",
                  jorientation);
   return FrameBuffer::Orientation::kTopLeft;
 }
 
+// TODO(b/180051417): remove the code, once FrameBuffer can digest YUV buffers
+// without format.
+// Theoretically, when using CreateFromYuvRawBuffer, "format" can always be set
+// to YV12 (or YV21, they are identical). However, prefer to set format to NV12
+// or NV21 whenever it's applicable, because NV12 and NV21 is better optimized
+// in performance than YV12 or YV21.
+StatusOr<FrameBuffer::Format> GetYUVImageFormat(const uint8* u_buffer,
+                                                const uint8* v_buffer,
+                                                int uv_pixel_stride) {
+  intptr_t u = reinterpret_cast<intptr_t>(u_buffer);
+  intptr_t v = reinterpret_cast<intptr_t>(v_buffer);
+  if ((std::abs(u - v) == 1) && (uv_pixel_stride == 2)) {
+    if (u_buffer > v_buffer) {
+      return FrameBuffer::Format::kNV21;
+    } else {
+      return FrameBuffer::Format::kNV12;
+    }
+  }
+  return FrameBuffer::Format::kYV12;
+}
+
+StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromByteBuffer(
+    JNIEnv* env,
+    jobject jimage_byte_buffer,
+    jint width,
+    jint height,
+    jint jorientation,
+    jint jcolor_space_type) {
+  absl::string_view image = GetMappedFileBuffer(env, jimage_byte_buffer);
+  return CreateFromRawBuffer(
+      reinterpret_cast<const uint8*>(image.data()),
+      FrameBuffer::Dimension{width, height},
+      ConvertToFrameBufferFormat(env, jcolor_space_type),
+      ConvertToFrameBufferOrientation(env, jorientation));
+}
+
+StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromBytes(
+    JNIEnv* env,
+    jbyteArray jimage_bytes,
+    jint width,
+    jint height,
+    jint jorientation,
+    jint jcolor_space_type,
+    jlongArray jbyte_array_handle) {
+  jbyte* jimage_ptr = env->GetByteArrayElements(jimage_bytes, NULL);
+  // Free jimage_ptr together with frame_buffer after inference is finished.
+  jlong jimage_ptr_handle = reinterpret_cast<jlong>(jimage_ptr);
+  // jbyte_array_handle has only one element, which is a holder for jimage_ptr.
+  env->SetLongArrayRegion(jbyte_array_handle, 0, 1, &jimage_ptr_handle);
+
+  if (jimage_ptr == NULL) {
+    ThrowException(env, kIllegalStateException,
+                   "Error occurred when reading image data from byte array.");
+    return nullptr;
+  }
+
+  return CreateFromRawBuffer(
+      reinterpret_cast<const uint8*>(jimage_ptr),
+      FrameBuffer::Dimension{width, height},
+      ConvertToFrameBufferFormat(env, jcolor_space_type),
+      ConvertToFrameBufferOrientation(env, jorientation));
+}
+
+StatusOr<std::unique_ptr<FrameBuffer>> CreateFrameBufferFromYuvPlanes(
+    JNIEnv* env,
+    jobject jy_plane,
+    jobject ju_plane,
+    jobject jv_plane,
+    jint width,
+    jint height,
+    jint row_stride_y,
+    jint row_stride_uv,
+    jint pixel_stride_uv,
+    jint jorientation) {
+  const uint8* y_plane =
+      reinterpret_cast<const uint8*>(GetMappedFileBuffer(env, jy_plane).data());
+  const uint8* u_plane =
+      reinterpret_cast<const uint8*>(GetMappedFileBuffer(env, ju_plane).data());
+  const uint8* v_plane =
+      reinterpret_cast<const uint8*>(GetMappedFileBuffer(env, jv_plane).data());
+
+  FrameBuffer::Format format;
+  ASSIGN_OR_RETURN(format,
+                   GetYUVImageFormat(u_plane, v_plane, pixel_stride_uv));
+
+  return CreateFromYuvRawBuffer(
+      y_plane, u_plane, v_plane, format, FrameBuffer::Dimension{width, height},
+      row_stride_y, row_stride_uv, pixel_stride_uv,
+      ConvertToFrameBufferOrientation(env, jorientation));
+}
+
 }  // namespace vision
 }  // namespace task
 }  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h
index 7cb63f3..4d7ec17 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/jni_utils.h
@@ -18,6 +18,7 @@
 
 #include <jni.h>
 
+#include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/class_proto_inc.h"
 
@@ -31,6 +32,37 @@
 FrameBuffer::Orientation ConvertToFrameBufferOrientation(JNIEnv* env,
                                                          jint jorientation);
 
+// Creates FrameBuffer from a direct ByteBuffer.
+::tflite::support::StatusOr<std::unique_ptr<FrameBuffer>>
+CreateFrameBufferFromByteBuffer(JNIEnv* env,
+                                jobject jimage_byte_buffer,
+                                jint width,
+                                jint height,
+                                jint jorientation,
+                                jint jcolor_space_type);
+
+// Creates FrameBuffer from a byte array.
+::tflite::support::StatusOr<std::unique_ptr<FrameBuffer>>
+CreateFrameBufferFromBytes(JNIEnv* env,
+                           jbyteArray jimage_bytes,
+                           jint width,
+                           jint height,
+                           jint jorientation,
+                           jint jcolor_space_type,
+                           jlongArray jbyte_array_handle);
+
+// Creates FrameBuffer from YUV planes.
+::tflite::support::StatusOr<std::unique_ptr<FrameBuffer>>
+CreateFrameBufferFromYuvPlanes(JNIEnv* env,
+                               jobject jy_plane,
+                               jobject ju_plane,
+                               jobject jv_plane,
+                               jint width,
+                               jint height,
+                               jint row_stride_y,
+                               jint row_stride_uv,
+                               jint pixel_stride_uv,
+                               jint jorientation);
 }  // namespace vision
 }  // namespace task
 }  // namespace tflite
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/BUILD
index 23d601df3..341980a 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/BUILD
@@ -1,4 +1,4 @@
-load("@org_tensorflow//tensorflow/lite:build_def.bzl", "tflite_jni_binary")
+load("@org_tensorflow//tensorflow/lite/core/shims:cc_library_with_tflite.bzl", "cc_library_with_tflite", "jni_binary_with_tflite")
 
 package(
     default_visibility = ["//tensorflow_lite_support:users"],
@@ -7,28 +7,44 @@
 
 exports_files(["image_segmenter_jni.cc"])
 
-cc_library(
+cc_library_with_tflite(
     name = "image_segmenter_native",
-    srcs = [
+    tflite_jni_binaries = [
         ":libtask_vision_jni.so",
     ],
 )
 
-tflite_jni_binary(
+jni_binary_with_tflite(
     name = "libtask_vision_jni.so",
+    linkscript = "//tensorflow_lite_support/java:default_version_script.lds",
+    tflite_deps = [
+        ":native_without_resolver",
+        "//tensorflow_lite_support/java/src/native/task/core:builtin_op_resolver",
+    ],
+)
+
+# Shared native logic for ImageSegmenter. Combine this target and customized
+# version of op_resolver to build customized image_segmenter_native target.
+cc_library_with_tflite(
+    name = "native_without_resolver",
     srcs = [
         "image_segmenter_jni.cc",
+        "//tensorflow_lite_support/java/src/native/task/core:task_jni_utils.cc",
+        "//tensorflow_lite_support/java/src/native/task/vision/core:base_vision_task_api_jni.cc",
+    ],
+    tflite_deps = [
+        "//tensorflow_lite_support/cc/task/vision:image_segmenter",
+        "//tensorflow_lite_support/cc/utils:jni_utils",
+        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
     ],
     deps = [
         "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/cc/task/vision:image_segmenter",
+        "//tensorflow_lite_support/cc/task/core/proto:base_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/core:frame_buffer",
         "//tensorflow_lite_support/cc/task/vision/proto:image_segmenter_options_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/proto:segmentations_proto_inc",
         "//tensorflow_lite_support/cc/task/vision/utils:frame_buffer_common_utils",
-        "//tensorflow_lite_support/cc/utils:jni_utils",
         "//tensorflow_lite_support/java/jni",
-        "//tensorflow_lite_support/java/src/native/task/vision:jni_utils",
         "@com_google_absl//absl/strings",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc
index 6e0bbc5..8d8c8ee 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/java/src/native/task/vision/segmenter/image_segmenter_jni.cc
@@ -18,8 +18,9 @@
 #include <memory>
 #include <string>
 
-#include "absl/strings/str_cat.h"
+#include "absl/strings/str_cat.h"  // from @com_google_absl
 #include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/cc/task/core/proto/base_options_proto_inc.h"
 #include "tensorflow_lite_support/cc/task/vision/core/frame_buffer.h"
 #include "tensorflow_lite_support/cc/task/vision/image_segmenter.h"
 #include "tensorflow_lite_support/cc/task/vision/proto/image_segmenter_options_proto_inc.h"
@@ -28,16 +29,24 @@
 #include "tensorflow_lite_support/cc/utils/jni_utils.h"
 #include "tensorflow_lite_support/java/src/native/task/vision/jni_utils.h"
 
+namespace tflite {
+namespace task {
+// To be provided by a link-time library
+extern std::unique_ptr<OpResolver> CreateOpResolver();
+
+}  // namespace task
+}  // namespace tflite
+
 namespace {
 
 using ::tflite::support::StatusOr;
 using ::tflite::support::utils::CreateByteArray;
-using ::tflite::support::utils::GetMappedFileBuffer;
-using ::tflite::support::utils::kAssertionError;
+using ::tflite::support::utils::GetExceptionClassNameForStatusCode;
 using ::tflite::support::utils::kIllegalArgumentException;
+using ::tflite::support::utils::kIllegalStateException;
 using ::tflite::support::utils::kInvalidPointer;
 using ::tflite::support::utils::ThrowException;
-using ::tflite::task::vision::ConvertToFrameBufferOrientation;
+using ::tflite::task::core::BaseOptions;
 using ::tflite::task::vision::FrameBuffer;
 using ::tflite::task::vision::ImageSegmenter;
 using ::tflite::task::vision::ImageSegmenterOptions;
@@ -59,9 +68,16 @@
 // Creates an ImageSegmenterOptions proto based on the Java class.
 ImageSegmenterOptions ConvertToProtoOptions(JNIEnv* env,
                                             jstring display_names_locale,
-                                            jint output_type) {
+                                            jint output_type,
+                                            jlong base_options_handle) {
   ImageSegmenterOptions proto_options;
 
+  if (base_options_handle != kInvalidPointer) {
+    // proto_options will free the previous base_options and set the new one.
+    proto_options.set_allocated_base_options(
+        reinterpret_cast<BaseOptions*>(base_options_handle));
+  }
+
   const char* pchars = env->GetStringUTFChars(display_names_locale, nullptr);
   proto_options.set_display_names_locale(pchars);
   env->ReleaseStringUTFChars(display_names_locale, pchars);
@@ -82,15 +98,15 @@
   return proto_options;
 }
 
-void ConvertToSegmentationResults(JNIEnv* env,
-                                  const SegmentationResult& results,
-                                  jobject jmask_buffers,
-                                  jintArray jmask_shape,
-                                  jobject jcolored_labels) {
+void ConvertFromSegmentationResults(JNIEnv* env,
+                                    const SegmentationResult& results,
+                                    jobject jmask_buffers,
+                                    jintArray jmask_shape,
+                                    jobject jcolored_labels) {
   if (results.segmentation_size() != 1) {
     // Should never happen.
     ThrowException(
-        env, kAssertionError,
+        env, kIllegalStateException,
         "ImageSegmenter only supports one segmentation result, getting %d",
         results.segmentation_size());
   }
@@ -157,6 +173,25 @@
   }
 }
 
+jlong CreateImageSegmenterFromOptions(JNIEnv* env,
+                                      const ImageSegmenterOptions& options) {
+  StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
+      ImageSegmenter::CreateFromOptions(options,
+                                        tflite::task::CreateOpResolver());
+  if (image_segmenter_or.ok()) {
+    return reinterpret_cast<jlong>(image_segmenter_or->release());
+  } else {
+    ThrowException(
+        env,
+        GetExceptionClassNameForStatusCode(image_segmenter_or.status().code()),
+        "Error occurred when initializing ImageSegmenter: %s",
+        image_segmenter_or.status().message().data());
+    return kInvalidPointer;
+  }
+}
+
+}  // namespace
+
 extern "C" JNIEXPORT void JNICALL
 Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_deinitJni(
     JNIEnv* env,
@@ -165,6 +200,9 @@
   delete reinterpret_cast<ImageSegmenter*>(native_handle);
 }
 
+// Creates an ImageSegmenter instance from the model file descriptor.
+// file_descriptor_length and file_descriptor_offset are optional. Non-possitive
+// values will be ignored.
 extern "C" JNIEXPORT jlong JNICALL
 Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithModelFdAndOptions(
     JNIEnv* env,
@@ -173,25 +211,37 @@
     jlong file_descriptor_length,
     jlong file_descriptor_offset,
     jstring display_names_locale,
-    jint output_type) {
-  ImageSegmenterOptions proto_options =
-      ConvertToProtoOptions(env, display_names_locale, output_type);
-  auto file_descriptor_meta = proto_options.mutable_model_file_with_metadata()
+    jint output_type,
+    jlong base_options_handle) {
+  ImageSegmenterOptions proto_options = ConvertToProtoOptions(
+      env, display_names_locale, output_type, base_options_handle);
+  auto file_descriptor_meta = proto_options.mutable_base_options()
+                                  ->mutable_model_file()
                                   ->mutable_file_descriptor_meta();
   file_descriptor_meta->set_fd(file_descriptor);
-  file_descriptor_meta->set_length(file_descriptor_length);
-  file_descriptor_meta->set_offset(file_descriptor_offset);
-
-  StatusOr<std::unique_ptr<ImageSegmenter>> image_segmenter_or =
-      ImageSegmenter::CreateFromOptions(proto_options);
-  if (image_segmenter_or.ok()) {
-    return reinterpret_cast<jlong>(image_segmenter_or->release());
-  } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when initializing ImageSegmenter: %s",
-                   image_segmenter_or.status().message().data());
-    return kInvalidPointer;
+  if (file_descriptor_length > 0) {
+    file_descriptor_meta->set_length(file_descriptor_length);
   }
+  if (file_descriptor_offset > 0) {
+    file_descriptor_meta->set_offset(file_descriptor_offset);
+  }
+  return CreateImageSegmenterFromOptions(env, proto_options);
+}
+
+extern "C" JNIEXPORT jlong JNICALL
+Java_org_tensorflow_lite_task_vision_segmenter_ImageSegmenter_initJniWithByteBuffer(
+    JNIEnv* env,
+    jclass thiz,
+    jobject model_buffer,
+    jstring display_names_locale,
+    jint output_type,
+    jlong base_options_handle) {
+  ImageSegmenterOptions proto_options = ConvertToProtoOptions(
+      env, display_names_locale, output_type, base_options_handle);
+  proto_options.mutable_base_options()->mutable_model_file()->set_file_content(
+      static_cast<char*>(env->GetDirectBufferAddress(model_buffer)),
+      static_cast<size_t>(env->GetDirectBufferCapacity(model_buffer)));
+  return CreateImageSegmenterFromOptions(env, proto_options);
 }
 
 extern "C" JNIEXPORT void JNICALL
@@ -199,28 +249,23 @@
     JNIEnv* env,
     jclass thiz,
     jlong native_handle,
-    jobject jimage_byte_buffer,
-    jint width,
-    jint height,
+    jlong frame_buffer_handle,
     jobject jmask_buffers,
     jintArray jmask_shape,
-    jobject jcolored_labels,
-    jint jorientation) {
+    jobject jcolored_labels) {
   auto* segmenter = reinterpret_cast<ImageSegmenter*>(native_handle);
-  absl::string_view image = GetMappedFileBuffer(env, jimage_byte_buffer);
-  std::unique_ptr<FrameBuffer> frame_buffer = CreateFromRgbRawBuffer(
-      reinterpret_cast<const uint8*>(image.data()),
-      FrameBuffer::Dimension{width, height},
-      ConvertToFrameBufferOrientation(env, jorientation));
+  // frame_buffer will be deleted after inference is done in
+  // base_vision_api_jni.cc.
+  auto* frame_buffer = reinterpret_cast<FrameBuffer*>(frame_buffer_handle);
+
   auto results_or = segmenter->Segment(*frame_buffer);
   if (results_or.ok()) {
-    ConvertToSegmentationResults(env, results_or.value(), jmask_buffers,
-                                 jmask_shape, jcolored_labels);
+    ConvertFromSegmentationResults(env, results_or.value(), jmask_buffers,
+                                   jmask_shape, jcolored_labels);
   } else {
-    ThrowException(env, kAssertionError,
-                   "Error occurred when segmenting the image: %s",
-                   results_or.status().message().data());
+    ThrowException(
+        env, GetExceptionClassNameForStatusCode(results_or.status().code()),
+        "Error occurred when segmenting the image: %s",
+        results_or.status().message().data());
   }
 }
-
-}  // namespace
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/BUILD
index ed5bedc..5e5c25b 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/BUILD
@@ -1,7 +1,7 @@
 load("//tensorflow_lite_support/metadata:build_defs.bzl", "stamp_metadata_parser_version")
 
 package(
-    default_visibility = ["//tensorflow_lite_support:users"],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -15,7 +15,12 @@
     name = "metadata_extractor",
     srcs = ["metadata_extractor.cc"],
     hdrs = ["metadata_extractor.h"],
+    visibility = ["//visibility:public"],
     deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
         "@com_google_absl//absl/container:flat_hash_map",
         "@com_google_absl//absl/memory",
         "@com_google_absl//absl/status",
@@ -23,15 +28,7 @@
         "@com_google_absl//absl/strings:str_format",
         "@flatbuffers",
         "@org_libzip//:zip",
-    ] + select({
-        "//tensorflow_lite_support/cc:tflite_use_c_api": ["@org_tensorflow//tensorflow/lite/c:c_api"],
-        "//conditions:default": ["@org_tensorflow//tensorflow/lite:framework"],
-    }) + [
         "@org_tensorflow//tensorflow/lite/schema:schema_fbs",
-        "//tensorflow_lite_support/cc:common",
-        "//tensorflow_lite_support/cc/port:status_macros",
-        "//tensorflow_lite_support/cc/port:statusor",
-        "//tensorflow_lite_support/metadata:metadata_schema_cc",
     ],
 )
 
@@ -51,3 +48,22 @@
         "@org_tensorflow//tensorflow/lite/tools:logging",
     ],
 )
+
+cc_library(
+    name = "metadata_populator",
+    srcs = ["metadata_populator.cc"],
+    hdrs = ["metadata_populator.h"],
+    visibility = ["//visibility:public"],
+    deps = [
+        "//tensorflow_lite_support/cc:common",
+        "//tensorflow_lite_support/cc/port:status_macros",
+        "//tensorflow_lite_support/cc/port:statusor",
+        "//tensorflow_lite_support/metadata:metadata_schema_cc",
+        "//tensorflow_lite_support/metadata/cc/utils:zip_mem_file",
+        "@com_google_absl//absl/container:flat_hash_map",
+        "@com_google_absl//absl/status",
+        "@flatbuffers//:runtime_cc",
+        "@org_tensorflow//tensorflow/lite/schema:schema_fbs",
+        "@zlib//:zlib_minizip",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
index 42f2a7c..3aae0aa 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.cc
@@ -17,9 +17,9 @@
 
 #include <functional>
 
-#include "absl/memory/memory.h"
-#include "absl/status/status.h"
-#include "absl/strings/str_format.h"
+#include "absl/memory/memory.h"       // from @com_google_absl
+#include "absl/status/status.h"       // from @com_google_absl
+#include "absl/strings/str_format.h"  // from @com_google_absl
 #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
 #include "lib/zip.h"                  // from @org_libzip
 #include "tensorflow/lite/schema/schema_generated.h"
@@ -27,12 +27,6 @@
 #include "tensorflow_lite_support/cc/port/status_macros.h"
 #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
 
-#if TFLITE_USE_C_API
-#include "tensorflow/lite/c/c_api.h"
-#else
-#include "tensorflow/lite/model_builder.h"
-#endif
-
 namespace tflite {
 namespace metadata {
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h
index 8eafe93..dc9a992 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_extractor.h
@@ -15,9 +15,9 @@
 #ifndef TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_EXTRACTOR_H_
 #define TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_EXTRACTOR_H_
 
-#include "absl/container/flat_hash_map.h"
-#include "absl/status/status.h"
-#include "absl/strings/string_view.h"
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "absl/strings/string_view.h"      // from @com_google_absl
 #include "tensorflow/lite/schema/schema_generated.h"
 #include "tensorflow_lite_support/cc/port/statusor.h"
 #include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h
new file mode 100644
index 0000000..9037f58
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_populator.h
@@ -0,0 +1,92 @@
+/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_POPULATOR_H_
+#define TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_POPULATOR_H_
+
+#include "absl/container/flat_hash_map.h"  // from @com_google_absl
+#include "absl/status/status.h"            // from @com_google_absl
+#include "flatbuffers/flatbuffers.h"       // from @flatbuffers
+#include "tensorflow/lite/schema/schema_generated.h"
+#include "tensorflow_lite_support/cc/port/statusor.h"
+#include "tensorflow_lite_support/metadata/metadata_schema_generated.h"
+
+namespace tflite {
+namespace metadata {
+
+// TODO(b/185787843): bring to feature parity with Python library.
+
+// Provides an interface to pack TFLite ModelMetadata [1] and corresponding
+// associated files into a TFLite FlatBuffer.
+//
+// [1]: https://www.tensorflow.org/lite/convert/metadata
+class ModelMetadataPopulator {
+ public:
+  // Creates a ModelMetadataPopulator from the provided TFLite Model FlatBuffer
+  // and returns a pointer to the new object. Ownership is transferred to the
+  // caller. Returns an error if the creation failed, which may happen e.g. if
+  // the provided buffer is not a valid TFLite FlatBuffer.
+  //
+  // It is recommended to obtain and manage the buffer through an
+  // ExternalFileHandler[1], which is optimized through mmap(2) to avoid having
+  // to load the entire buffer in memory when provided by path or file
+  // descriptor.
+  //
+  // [1]:
+  // tensorflow_lite_support/c/task/core/external_file_handler.h
+  static tflite::support::StatusOr<std::unique_ptr<ModelMetadataPopulator>>
+  CreateFromModelBuffer(const char* buffer_data, size_t buffer_size);
+
+  // Writes the TFLite ModelMetadata provided as a buffer into the TFLite
+  // FlatBuffer model.
+  //
+  // Warning: this method overwrites any already existing TFLite Model Metadata.
+  // Calling this method multiple times overwrites the metadata from previous
+  // calls, so this method should usually be called only once.
+  void LoadMetadata(const char* metadata_buffer_data,
+                    size_t metadata_buffer_size);
+
+  // Loads associated files into the TFLite FlatBuffer model. The input is a map
+  // of {filename, file contents}.
+  //
+  // Warning: this method removes any previoulsy present associated files.
+  // Calling this method multiple time removes any associated files from
+  // previous calls, so this method should usually be called only once.
+  void LoadAssociatedFiles(
+      const absl::flat_hash_map<std::string, std::string>& associated_files);
+
+  // Finalizes metadata population. Returns the TFLite FlatBuffer model with
+  // metadata and associated files as a string buffer.
+  tflite::support::StatusOr<std::string> Populate();
+
+ private:
+  // Private constructor.
+  explicit ModelMetadataPopulator(const tflite::Model& model);
+  // Zips and appends associated files to the provided model buffer. Called
+  // internally by `Populate()`.
+  tflite::support::StatusOr<std::string> AppendAssociatedFiles(
+      const char* model_buffer_data,
+      size_t model_buffer_size);
+
+  // The unpacked model FlatBuffer.
+  tflite::ModelT model_t_;
+  // The associated files.
+  absl::flat_hash_map<std::string, std::string> associated_files_;
+};
+
+}  // namespace metadata
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_SUPPORT_METADATA_CC_METADATA_POPULATOR_H_
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc
index 8c8e1fd..ed75b65 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/metadata_version.cc
@@ -22,8 +22,8 @@
 #include <string>
 #include <vector>
 
-#include "absl/strings/str_join.h"
-#include "absl/strings/str_split.h"
+#include "absl/strings/str_join.h"   // from @com_google_absl
+#include "absl/strings/str_split.h"  // from @com_google_absl
 #include "flatbuffers/flatbuffers.h"  // from @flatbuffers
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/kernels/internal/compatibility.h"
@@ -45,6 +45,7 @@
   kSubGraphMetadataInputTensorGroups = 5,
   kSubGraphMetadataOutputTensorGroups = 6,
   kProcessUnitOptionsRegexTokenizerOptions = 7,
+  kContentPropertiesAudioProperties = 8,
 };
 
 // Helper class to compare semantic versions in terms of three integers, major,
@@ -107,6 +108,8 @@
       return Version(1, 2, 0);
     case SchemaMembers::kProcessUnitOptionsRegexTokenizerOptions:
       return Version(1, 2, 1);
+    case SchemaMembers::kContentPropertiesAudioProperties:
+      return Version(1, 3, 0);
     default:
       // Should never happen.
       TFLITE_LOG(FATAL) << "Unsupported schema member: "
@@ -182,6 +185,20 @@
 }
 
 template <>
+void UpdateMinimumVersionForTable<tflite::Content>(const tflite::Content* table,
+                                                   Version* min_version) {
+  if (table == nullptr)
+    return;
+
+  // Checks the ContenProperties field.
+  if (table->content_properties_type() == ContentProperties_AudioProperties) {
+    UpdateMinimumVersion(
+        GetMemberVersion(SchemaMembers::kContentPropertiesAudioProperties),
+        min_version);
+  }
+}
+
+template <>
 void UpdateMinimumVersionForTable<tflite::TensorMetadata>(
     const tflite::TensorMetadata* table,
     Version* min_version) {
@@ -195,6 +212,9 @@
   // Checks the process_units field.
   UpdateMinimumVersionForArray<tflite::ProcessUnit>(table->process_units(),
                                                     min_version);
+
+  // Check the content field.
+  UpdateMinimumVersionForTable<tflite::Content>(table->content(), min_version);
 }
 
 template <>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/python/BUILD
index 34e9a4f..7f78543 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/python/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/python/BUILD
@@ -1,9 +1,7 @@
 load("@org_tensorflow//tensorflow:tensorflow.bzl", "pybind_extension")
 
 package(
-    default_visibility = [
-        "//tensorflow_lite_support/metadata:__subpackages__",
-    ],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/BUILD
new file mode 100644
index 0000000..ced8644
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/cc/utils/BUILD
@@ -0,0 +1,16 @@
+package(
+    default_visibility = [
+        "//tensorflow_lite_support:internal",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+cc_library(
+    name = "zip_mem_file",
+    srcs = ["zip_mem_file.cc"],
+    hdrs = ["zip_mem_file.h"],
+    deps = [
+        "@com_google_absl//absl/strings",
+        "@zlib//:zlib_minizip",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/BUILD
index d4171bf..5efd8072 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/flatbuffers_lib/BUILD
@@ -1,9 +1,7 @@
 load("@org_tensorflow//tensorflow:tensorflow.bzl", "pybind_extension")
 
 package(
-    default_visibility = [
-        "//visibility:public",
-    ],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/BUILD
index 0fbe028..5f000b4 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/BUILD
@@ -2,7 +2,6 @@
 # TensorFlow Lite Support API in Java for metadata.
 
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
-load("@org_tensorflow//tensorflow/java:build_defs.bzl", "JAVACOPTS")
 
 package(
     default_visibility = ["//visibility:public"],
@@ -16,7 +15,7 @@
 android_library(
     name = "tensorflowlite_support_metadata",
     srcs = METADATA_SRCS,
-    javacopts = JAVACOPTS,
+    javacopts = ["-source 7 -target 7"],
     manifest = "AndroidManifest.xml",
     deps = [
         "//tensorflow_lite_support/metadata:metadata_schema_fbs_android",
@@ -33,16 +32,18 @@
 java_library(
     name = "tensorflowlite_support_metadata_lib",
     srcs = METADATA_SRCS,
-    javacopts = JAVACOPTS,
+    javacopts = ["--release 7"],
     resource_jars = [
         "//tensorflow_lite_support/metadata:libmetadata_schema_java.jar",
         "//tensorflow_lite_support/metadata:libschema_fbs_java.jar",
     ],
+    # LINT.IfChange(dep)
     deps = [
         "//tensorflow_lite_support/metadata:metadata_schema_java",
         "//tensorflow_lite_support/metadata:schema_fbs_java",
         "@org_checkerframework_qual",
     ],
+    # LINT.ThenChange(<INTERNAL>/release/build_metadata_pom.sh:dep)
 )
 
 alias(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java
index c4537c8..20f5566 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/java/org/tensorflow/lite/support/metadata/MetadataParser.java
@@ -21,7 +21,7 @@
      * The version of the metadata parser that this metadata extractor library is depending on. The
      * value should match the value of "Schema Semantic version" in metadata_schema.fbs.
      */
-    public static final String VERSION = "1.2.1";
+    public static final String VERSION = "1.3.0";
 
     private MetadataParser() {}
 }
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/BUILD
index 204b24b7..22446ca 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/BUILD
@@ -31,10 +31,13 @@
         "//tensorflow_lite_support/metadata:metadata_schema_fbs_android",
         "//tensorflow_lite_support/metadata:schema_fbs_android",
         "//tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata",
-        "//third_party/java/jakarta_commons_io",
-        "//third_party/java/truth:truth-android",
         "@flatbuffers//:runtime_android",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:commons_io_commons_io",
+        "@maven//:org_robolectric_robolectric",
         "@org_checkerframework_qual",
+        "@robolectric//bazel:android-all",
     ],
 )
 
@@ -48,7 +51,10 @@
     test_class = "org.tensorflow.lite.support.metadata.ByteBufferChannelTest",
     deps = [
         "//tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata",
-        "//third_party/java/truth:truth-android",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
     ],
 )
 
@@ -65,8 +71,11 @@
     deps = [
         ":test_lib",
         "//tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata",
-        "//third_party/java/jakarta_commons_io",
-        "//third_party/java/truth:truth-android",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:commons_io_commons_io",
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
     ],
 )
 
@@ -80,7 +89,10 @@
     test_class = "org.tensorflow.lite.support.metadata.BoundedInputStreamTest",
     deps = [
         "//tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata",
-        "//third_party/java/truth:truth-android",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
     ],
 )
 
@@ -93,7 +105,7 @@
     test_class = "org.tensorflow.lite.support.metadata.MetadataParserTest",
     deps = [
         "//tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata_lib",
-        "//third_party/java/truth",
-        "@junit",
+        "@maven//:com_google_truth_truth",
+        "@maven//:junit_junit",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/assets/mobilenet_v1_1.0_224_quant.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/assets/mobilenet_v1_1.0_224_quant.tflite
new file mode 100644
index 0000000..8cf2048f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/assets/mobilenet_v1_1.0_224_quant.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java
index 5990979..9f1173a1 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/MetadataExtractorTest.java
@@ -29,6 +29,7 @@
 
 import org.apache.commons.io.IOUtils;
 import org.checkerframework.checker.nullness.qual.Nullable;
+import org.junit.Ignore;
 import org.junit.Test;
 import org.junit.runner.RunWith;
 import org.junit.runners.Suite;
@@ -107,6 +108,7 @@
             assertThat(metadataExtractor.hasMetadata()).isFalse();
         }
 
+        @Ignore
         @Test
         public void getAssociatedFile_validAssociateFile() throws Exception {
             ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
@@ -121,6 +123,7 @@
                     .isTrue();
         }
 
+        @Ignore
         @Test
         public void getAssociatedFile_invalidAssociateFile() throws Exception {
             ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
@@ -131,6 +134,7 @@
                     "The file, %s, does not exist in the zip file.", INVALID_LABEL_FILE_NAME));
         }
 
+        @Ignore
         @Test
         public void getAssociatedFile_nullFileName() throws Exception {
             ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
@@ -165,6 +169,7 @@
                     "This model does not contain associated files, and is not a Zip file.");
         }
 
+        @Ignore
         @Test
         public void getAssociatedFileNames_validFileNames() throws Exception {
             ByteBuffer mobileNetBuffer = loadMobileNetBuffer();
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java
index af80fba..80d2ddc6f 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/java/src/javatests/org/tensorflow/lite/support/metadata/ZipFileTest.java
@@ -25,6 +25,7 @@
 import androidx.test.core.app.ApplicationProvider;
 
 import org.apache.commons.io.IOUtils;
+import org.junit.Ignore;
 import org.junit.Test;
 import org.junit.runner.RunWith;
 import org.robolectric.RobolectricTestRunner;
@@ -78,6 +79,7 @@
         assertThat(exception).hasMessageThat().isEqualTo("The archive is not a ZIP archive.");
     }
 
+    @Ignore
     @Test
     public void getFileNames_correctFileName() throws Exception {
         ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
@@ -87,6 +89,7 @@
         assertThat(zipFile.getFileNames()).isEqualTo(expectedSet);
     }
 
+    @Ignore
     @Test
     public void getRawInputStream_existentFile() throws Exception {
         ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
@@ -98,6 +101,7 @@
         assertThat(IOUtils.contentEquals(goldenFileStream, fileStream)).isTrue();
     }
 
+    @Ignore
     @Test
     public void getRawInputStream_nonExistentFile() throws Exception {
         ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
@@ -109,6 +113,7 @@
                 "The file, %s, does not exist in the zip file.", INVALID_LABEL_FILE_NAME));
     }
 
+    @Ignore
     @Test
     public void close_validStatus() throws Exception {
         ByteBufferChannel modelChannel = loadModel(MODEL_PATH);
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/metadata_schema.fbs b/third_party/tflite_support/src/tensorflow_lite_support/metadata/metadata_schema.fbs
index 8faae0a..e0b95af 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/metadata_schema.fbs
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/metadata_schema.fbs
@@ -50,7 +50,7 @@
 // for which they were added.
 //
 // LINT.IfChange
-// Schema Semantic version: 1.2.1
+// Schema Semantic version: 1.3.0
 // LINT.ThenChange(//tensorflow_lite_support/\
 //     metadata/java/src/java/org/tensorflow/lite/support/metadata/\
 //     MetadataParser.java)
@@ -69,6 +69,7 @@
 // 1.2.0 - Added input_tensor_group to SubGraphMetadata.
 //         Added output_tensor_group to SubGraphMetadata.
 // 1.2.1 - Added RegexTokenizerOptions to ProcessUnitOptions.
+// 1.3.0 - Added AudioProperties to ContentProperties.
 
 // File extension of any written files.
 file_extension "tflitemeta";
@@ -80,10 +81,12 @@
   // Files such as readme.txt.
   DESCRIPTIONS = 1,
 
-  // Contains labels that annotate certain axis of the tensor. For example,
+  // Contains a list of labels (characters separated by "\n" or in lines) that
+  // annotate certain axis of the tensor. For example,
   // the label file in image classification. Those labels annotate the
   // the output tensor, such that each value in the output tensor is the
-  // probability of that corresponding category specified by the label.
+  // probability of that corresponding category specified by the label. See the
+  // example label file used in image classification [1].
   //
   // <Codegen usage>:
   // If an output tensor has an associated file as TENSOR_AXIS_LABELS, return
@@ -92,12 +95,16 @@
   // If multiple files of the same type are present, the first one is used by
   // default; additional ones are to be distinguished from one another by their
   // specified locale.
+  //
+  // [1]: https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/labels.txt
   TENSOR_AXIS_LABELS = 2,
 
-  // Contains labels that tensor values correspond to. For example, in
+  // Contains a list of labels (characters separated by "\n" or in lines) that
+  // tensor values correspond to. For example, in
   // the object detection model, one of the output tensors is the detected
   // classes. And each value in the tensor refers to the index of label in the
-  // category label file.
+  // category label file. See the example label file used in object detection
+  // [1].
   //
   // <Codegen usage>:
   // If an output tensor has an associated file as TENSOR_VALUE_LABELS, convert
@@ -105,23 +112,33 @@
   // If multiple files of the same type are present, the first one is used by
   // default; additional ones are to be distinguished from one another by their
   // specified locale.
+  //
+  // [1]: https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/labelmap.txt
   TENSOR_VALUE_LABELS = 3,
 
   // Contains sigmoid-based score calibration parameters, formatted as CSV.
   // Lines contain for each index of an output tensor the scale, slope, offset
   // and (optional) min_score parameters to be used for sigmoid fitting (in this
-  // order and in `strtof`-compatible [1] format).
+  // order and in `strtof`-compatible [1] format). Scale should be a
+  // non-negative value.
   // A line may be left empty to default calibrated scores for this index to
   // default_score.
   // In summary, each line should thus contain 0, 3 or 4 comma-separated values.
   //
+  // See the example score calibration file used in image classification [2].
+  //
   // See documentation for ScoreCalibrationOptions for details.
   //
   // [1]: https://en.cppreference.com/w/c/string/byte/strtof
+  // [2]: https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/score_calibration.txt
   TENSOR_AXIS_SCORE_CALIBRATION = 4,
 
   // Contains a list of unique words (characters separated by "\n" or in lines)
   // that help to convert natural language words to embedding vectors.
+  //
+  // See the example vocab file used in text classification [1].
+  //
+  // [1]: https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/vocab.txt
   // Added in: 1.0.1
   VOCABULARY = 5,
 }
@@ -232,6 +249,16 @@
 
 }
 
+// The properties for audio tensors.
+// Added in: 1.3.0
+table AudioProperties {
+  // The sample rate in Hz when the audio was captured.
+  sample_rate:uint;
+
+  // The channel count of the audio.
+  channels:uint;
+}
+
 enum CoordinateType : byte {
   // The coordinates are float values from 0 to 1.
   RATIO = 0,
@@ -267,6 +294,8 @@
   FeatureProperties,
   ImageProperties,
   BoundingBoxProperties,
+  // Added in: 1.3.0
+  AudioProperties,
 }
 
 table ValueRange {
@@ -412,6 +441,9 @@
 // An AssociatedFile with type TANSOR_AXIS_SCORE_CALIBRATION specifying the
 // index-specific parameters must be associated with the corresponding
 // TensorMetadata for score calibration be applied.
+//
+// See the example score calibration file used in image classification [1].
+// [1]: https://github.com/tensorflow/tflite-support/blob/master/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/score_calibration.txt
 table ScoreCalibrationOptions {
   // The function to use for transforming the uncalibrated score before
   // applying score calibration.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/BUILD
index d6d9357..3668e49 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/BUILD
@@ -1,9 +1,8 @@
 load("//tensorflow_lite_support/metadata:build_defs.bzl", "stamp_metadata_parser_version")
+# Placeholder for internal Python strict library compatibility macro.
 
 package(
-    default_visibility = [
-        "//visibility:public",
-    ],
+    default_visibility = ["//tensorflow_lite_support:internal"],
     licenses = ["notice"],  # Apache 2.0
 )
 
@@ -20,14 +19,39 @@
         ":metadata_parser_py",
     ],
     data = ["//tensorflow_lite_support/metadata:metadata_schema.fbs"],
-    srcs_version = "PY2AND3",
+    srcs_version = "PY3",
     visibility = ["//visibility:public"],
     deps = [
-        "//tensorflow_lite_support/custom_ops:expect_numpy_installed",
         "//tensorflow_lite_support/metadata:metadata_schema_py",
         "//tensorflow_lite_support/metadata:schema_py",
         "//tensorflow_lite_support/metadata/cc/python:_pywrap_metadata_version",
         "//tensorflow_lite_support/metadata/flatbuffers_lib:_pywrap_flatbuffers",
-        "//tensorflow_lite_support/tools:expect_flatbuffers_installed",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_binary(
+    name = "metadata_displayer",
+    srcs = ["metadata_displayer.py"],
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        ":metadata",
+        "@absl_py//absl:app",
+        "@absl_py//absl/flags",
+    ],
+)
+
+py_library(
+    name = "metadata_writer_for_task",
+    srcs = ["metadata_writer_for_task.py"],
+    srcs_version = "PY3",
+    deps = [
+        ":metadata",
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_writer",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:writer_utils",
     ],
 )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/__init__.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/__init__.py
new file mode 100644
index 0000000..2ae3e34
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/__init__.py
@@ -0,0 +1,13 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata.py
index 15a677d..a312974 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata.py
@@ -14,10 +14,6 @@
 # ==============================================================================
 """TensorFlow Lite metadata tools."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
 import copy
 import inspect
 import io
@@ -34,6 +30,47 @@
 from tensorflow_lite_support.metadata.cc.python import _pywrap_metadata_version
 from tensorflow_lite_support.metadata.flatbuffers_lib import _pywrap_flatbuffers
 
+try:
+  # If exists, optionally use TensorFlow to open and check files. Used to
+  # support more than local file systems.
+  # In pip requirements, we doesn't necessarily need tensorflow as a dep.
+  import tensorflow as tf  # pylint: disable=g-import-not-at-top
+  _open_file = tf.io.gfile.GFile
+  _exists_file = tf.io.gfile.exists
+except ImportError as e:
+  # If TensorFlow package doesn't exist, fall back to original open and exists.
+  _open_file = open
+  _exists_file = os.path.exists
+
+
+def _maybe_open_as_binary(filename, mode):
+  """Maybe open the binary file, and returns a file-like."""
+  if hasattr(filename, "read"):  # A file-like has read().
+    return filename
+  openmode = mode if "b" in mode else mode + "b"  # Add binary explicitly.
+  return _open_file(filename, openmode)
+
+
+def _open_as_zipfile(filename, mode="r"):
+  """Open file as a zipfile.
+
+  Args:
+    filename: str or file-like or path-like, to the zipfile.
+    mode: str, common file mode for zip.
+          (See: https://docs.python.org/3/library/zipfile.html)
+
+  Returns:
+    A ZipFile object.
+  """
+  file_like = _maybe_open_as_binary(filename, mode)
+  return zipfile.ZipFile(file_like, mode)
+
+
+def _is_zipfile(filename):
+  """Checks whether it is a zipfile."""
+  with _maybe_open_as_binary(filename, "r") as f:
+    return zipfile.is_zipfile(f)
+
 
 def get_path_to_datafile(path):
   """Gets the path to the specified file in the data dependencies.
@@ -88,6 +125,8 @@
     # populator.load_metadata_buffer(metadata_buf)
     populator.load_metadata_file(metadata_file)
     populator.load_associated_files([label.txt])
+    # For associated file buffer (bytearray read from the file), use:
+    # populator.load_associated_file_buffers({"label.txt": b"file content"})
     populator.populate()
 
     # Populating a metadata file (or a metadta buffer) and associated files to
@@ -100,6 +139,14 @@
     updated_model_buf = populator.get_model_buffer()
     with open("updated_model.tflite", "wb") as f:
       f.write(updated_model_buf)
+
+    # Transferring metadata and associated files from another TFLite model:
+    populator = MetadataPopulator.with_model_buffer(model_buf)
+    populator_dst.load_metadata_and_associated_files(src_model_buf)
+    populator_dst.populate()
+    updated_model_buf = populator.get_model_buffer()
+    with open("updated_model.tflite", "wb") as f:
+      f.write(updated_model_buf)
     ```
 
   Note that existing metadata buffer (if applied) will be overridden by the new
@@ -128,7 +175,8 @@
     _assert_model_file_identifier(model_file)
     self._model_file = model_file
     self._metadata_buf = None
-    self._associated_files = set()
+    # _associated_files is a dict of file name and file buffer.
+    self._associated_files = {}
 
   @classmethod
   def with_model_file(cls, model_file):
@@ -169,7 +217,7 @@
     Returns:
       Model buffer (in bytearray).
     """
-    with open(self._model_file, "rb") as f:
+    with _open_file(self._model_file, "rb") as f:
       return f.read()
 
   def get_packed_associated_file_list(self):
@@ -178,10 +226,10 @@
     Returns:
       List of packed associated files.
     """
-    if not zipfile.is_zipfile(self._model_file):
+    if not _is_zipfile(self._model_file):
       return []
 
-    with zipfile.ZipFile(self._model_file, "r") as zf:
+    with _open_as_zipfile(self._model_file, "r") as zf:
       return zf.namelist()
 
   def get_recorded_associated_file_list(self):
@@ -193,47 +241,31 @@
     Returns:
       List of recorded associated files.
     """
-    recorded_files = []
-
     if not self._metadata_buf:
-      return recorded_files
+      return []
 
-    metadata = _metadata_fb.ModelMetadata.GetRootAsModelMetadata(
-        self._metadata_buf, 0)
+    metadata = _metadata_fb.ModelMetadataT.InitFromObj(
+        _metadata_fb.ModelMetadata.GetRootAsModelMetadata(
+            self._metadata_buf, 0))
 
-    # Add associated files attached to ModelMetadata.
-    recorded_files += self._get_associated_files_from_table(
-        metadata, "AssociatedFiles")
+    return [
+        file.name.decode("utf-8")
+        for file in self._get_recorded_associated_file_object_list(metadata)
+    ]
 
-    # Add associated files attached to each SubgraphMetadata.
-    for j in range(metadata.SubgraphMetadataLength()):
-      subgraph = metadata.SubgraphMetadata(j)
-      recorded_files += self._get_associated_files_from_table(
-          subgraph, "AssociatedFiles")
+  def load_associated_file_buffers(self, associated_files):
+    """Loads the associated file buffers (in bytearray) to be populated.
 
-      # Add associated files attached to each input tensor.
-      for k in range(subgraph.InputTensorMetadataLength()):
-        recorded_files += self._get_associated_files_from_table(
-            subgraph.InputTensorMetadata(k), "AssociatedFiles")
-        recorded_files += self._get_associated_files_from_process_units(
-            subgraph.InputTensorMetadata(k), "ProcessUnits")
+    Args:
+      associated_files: a dictionary of associated file names and corresponding
+        file buffers, such as {"file.txt": b"file content"}. If pass in file
+          paths for the file name, only the basename will be populated.
+    """
 
-      # Add associated files attached to each output tensor.
-      for k in range(subgraph.OutputTensorMetadataLength()):
-        recorded_files += self._get_associated_files_from_table(
-            subgraph.OutputTensorMetadata(k), "AssociatedFiles")
-        recorded_files += self._get_associated_files_from_process_units(
-            subgraph.OutputTensorMetadata(k), "ProcessUnits")
-
-      # Add associated files attached to the input_process_units.
-      recorded_files += self._get_associated_files_from_process_units(
-          subgraph, "InputProcessUnits")
-
-      # Add associated files attached to the output_process_units.
-      recorded_files += self._get_associated_files_from_process_units(
-          subgraph, "OutputProcessUnits")
-
-    return recorded_files
+    self._associated_files.update({
+        os.path.basename(name): buffers
+        for name, buffers in associated_files.items()
+    })
 
   def load_associated_files(self, associated_files):
     """Loads associated files that to be concatenated after the model file.
@@ -245,9 +277,10 @@
       IOError:
         File not found.
     """
-    for af in associated_files:
-      _assert_file_exist(af)
-      self._associated_files.add(af)
+    for af_name in associated_files:
+      _assert_file_exist(af_name)
+      with _open_file(af_name, "rb") as af:
+        self.load_associated_file_buffers({af_name: af.read()})
 
   def load_metadata_buffer(self, metadata_buf):
     """Loads the metadata buffer (in bytearray) to be populated.
@@ -277,6 +310,10 @@
         _metadata_fb.ModelMetadata.GetRootAsModelMetadata(metadata_buf, 0))
     metadata.minParserVersion = min_version
 
+    # Remove local file directory in the `name` field of `AssociatedFileT`, and
+    # make it consistent with the name of the actual file packed in the model.
+    self._use_basename_for_associated_files_in_metadata(metadata)
+
     b = flatbuffers.Builder(0)
     b.Finish(metadata.Pack(b), self.METADATA_FILE_IDENTIFIER)
     metadata_buf_with_version = b.Output()
@@ -299,10 +336,28 @@
         of input/output tensor metadata.
     """
     _assert_file_exist(metadata_file)
-    with open(metadata_file, "rb") as f:
+    with _open_file(metadata_file, "rb") as f:
       metadata_buf = f.read()
     self.load_metadata_buffer(bytearray(metadata_buf))
 
+  def load_metadata_and_associated_files(self, src_model_buf):
+    """Loads the metadata and associated files from another model buffer.
+
+    Args:
+      src_model_buf: source model buffer (in bytearray) with metadata and
+        associated files.
+    """
+    # Load the model metadata from src_model_buf if exist.
+    metadata_buffer = _get_metadata_buffer(src_model_buf)
+    if metadata_buffer:
+      self.load_metadata_buffer(metadata_buffer)
+
+    # Load the associated files from src_model_buf if exist.
+    if _is_zipfile(io.BytesIO(src_model_buf)):
+      with _open_as_zipfile(io.BytesIO(src_model_buf)) as zf:
+        self.load_associated_file_buffers(
+            {f: zf.read(f) for f in zf.namelist()})
+
   def populate(self):
     """Populates loaded metadata and associated files into the model file."""
     self._assert_validate()
@@ -324,9 +379,7 @@
     packed_files = self.get_packed_associated_file_list()
 
     # Gets the file name of those associated files to be populated.
-    to_be_populated_files = []
-    for af in self._associated_files:
-      to_be_populated_files.append(os.path.basename(af))
+    to_be_populated_files = self._associated_files.keys()
 
     # Checks all files recorded in the metadata will be populated.
     for rf in recorded_files:
@@ -340,18 +393,17 @@
 
       if f not in recorded_files:
         warnings.warn(
-            "File, '{0}', does not exsit in the metadata. But packing it to "
+            "File, '{0}', does not exist in the metadata. But packing it to "
             "tflite model is still allowed.".format(f))
 
-  def _copy_archived_files(self, src_zip, dst_zip, file_list):
+  def _copy_archived_files(self, src_zip, file_list, dst_zip):
     """Copy archieved files in file_list from src_zip ro dst_zip."""
 
-    if not zipfile.is_zipfile(src_zip):
+    if not _is_zipfile(src_zip):
       raise ValueError("File, '{0}', is not a zipfile.".format(src_zip))
 
-    with zipfile.ZipFile(src_zip,
-                         "r") as src_zf, zipfile.ZipFile(dst_zip,
-                                                         "a") as dst_zf:
+    with _open_as_zipfile(src_zip, "r") as src_zf, \
+         _open_as_zipfile(dst_zip, "a") as dst_zf:
       src_list = src_zf.namelist()
       for f in file_list:
         if f not in src_list:
@@ -373,36 +425,25 @@
         either "InputProcessUnits" or "OutputProcessUnits".
 
     Returns:
-      the associated files list.
+      A list of AssociatedFileT objects.
     """
 
     if table is None:
-      return
+      return []
 
     file_list = []
-    length_method = getattr(table, field_name + "Length", None)
-    member_method = getattr(table, field_name, None)
-    if length_method is None or member_method is None:
-      raise ValueError("{0} does not have the field {1}".format(
-          type(table).__name__, field_name))
-
-    for k in range(length_method()):
-      process_unit = member_method(k)
-      tokenizer = process_unit.Options()
-      if (process_unit.OptionsType() is
-          _metadata_fb.ProcessUnitOptions.BertTokenizerOptions):
-        bert_tokenizer = _metadata_fb.BertTokenizerOptions()
-        bert_tokenizer.Init(tokenizer.Bytes, tokenizer.Pos)
+    process_units = getattr(table, field_name)
+    # If the process_units field is not populated, it will be None. Use an
+    # empty list to skip the check.
+    for process_unit in process_units or []:
+      options = process_unit.options
+      if isinstance(options, (_metadata_fb.BertTokenizerOptionsT,
+                              _metadata_fb.RegexTokenizerOptionsT)):
+        file_list += self._get_associated_files_from_table(options, "vocabFile")
+      elif isinstance(options, _metadata_fb.SentencePieceTokenizerOptionsT):
         file_list += self._get_associated_files_from_table(
-            bert_tokenizer, "VocabFile")
-      elif (process_unit.OptionsType() is
-            _metadata_fb.ProcessUnitOptions.SentencePieceTokenizerOptions):
-        sentence_piece = _metadata_fb.SentencePieceTokenizerOptions()
-        sentence_piece.Init(tokenizer.Bytes, tokenizer.Pos)
-        file_list += self._get_associated_files_from_table(
-            sentence_piece, "SentencePieceModel")
-        file_list += self._get_associated_files_from_table(
-            sentence_piece, "VocabFile")
+            options, "sentencePieceModel")
+        file_list += self._get_associated_files_from_table(options, "vocabFile")
     return file_list
 
   def _get_associated_files_from_table(self, table, field_name):
@@ -417,17 +458,62 @@
         be "VocabFile".
 
     Returns:
-      the associated files list.
+      A list of AssociatedFileT objects.
     """
 
     if table is None:
-      return
-    file_list = []
-    length_method = getattr(table, field_name + "Length")
-    member_method = getattr(table, field_name)
-    for j in range(length_method()):
-      file_list.append(member_method(j).Name().decode("utf-8"))
-    return file_list
+      return []
+
+    # If the associated file field is not populated,
+    # `getattr(table, field_name)` will be None. Return an empty list.
+    return getattr(table, field_name) or []
+
+  def _get_recorded_associated_file_object_list(self, metadata):
+    """Gets a list of AssociatedFileT objects recorded in the metadata.
+
+    Associated files may be attached to a model, a subgraph, or an input/output
+    tensor.
+
+    Args:
+      metadata: the ModelMetadataT object.
+
+    Returns:
+      List of recorded AssociatedFileT objects.
+    """
+    recorded_files = []
+
+    # Add associated files attached to ModelMetadata.
+    recorded_files += self._get_associated_files_from_table(
+        metadata, "associatedFiles")
+
+    # Add associated files attached to each SubgraphMetadata.
+    for subgraph in metadata.subgraphMetadata or []:
+      recorded_files += self._get_associated_files_from_table(
+          subgraph, "associatedFiles")
+
+      # Add associated files attached to each input tensor.
+      for tensor_metadata in subgraph.inputTensorMetadata or []:
+        recorded_files += self._get_associated_files_from_table(
+            tensor_metadata, "associatedFiles")
+        recorded_files += self._get_associated_files_from_process_units(
+            tensor_metadata, "processUnits")
+
+      # Add associated files attached to each output tensor.
+      for tensor_metadata in subgraph.outputTensorMetadata or []:
+        recorded_files += self._get_associated_files_from_table(
+            tensor_metadata, "associatedFiles")
+        recorded_files += self._get_associated_files_from_process_units(
+            tensor_metadata, "processUnits")
+
+      # Add associated files attached to the input_process_units.
+      recorded_files += self._get_associated_files_from_process_units(
+          subgraph, "inputProcessUnits")
+
+      # Add associated files attached to the output_process_units.
+      recorded_files += self._get_associated_files_from_process_units(
+          subgraph, "outputProcessUnits")
+
+    return recorded_files
 
   def _populate_associated_files(self):
     """Concatenates associated files after TensorFlow Lite model file.
@@ -441,10 +527,20 @@
     # self._model_file = old_tflite_file | label1.txt | label2.txt
     # Then after trigger populate() to add label3.txt, self._model_file becomes
     # self._model_file = old_tflite_file | label1.txt | label2.txt | label3.txt
-    with zipfile.ZipFile(self._model_file, "a") as zf:
-      for af in self._associated_files:
-        filename = os.path.basename(af)
-        zf.write(af, filename)
+    with tempfile.SpooledTemporaryFile() as temp:
+      # (1) Copy content from model file of to temp file.
+      with _open_file(self._model_file, "rb") as f:
+        shutil.copyfileobj(f, temp)
+
+      # (2) Append of to a temp file as a zip.
+      with _open_as_zipfile(temp, "a") as zf:
+        for file_name, file_buffer in self._associated_files.items():
+          zf.writestr(file_name, file_buffer)
+
+      # (3) Copy temp file to model file.
+      temp.seek(0)
+      with _open_file(self._model_file, "wb") as f:
+        shutil.copyfileobj(temp, f)
 
   def _populate_metadata_buffer(self):
     """Populates the metadata buffer (in bytearray) into the model file.
@@ -457,7 +553,7 @@
     buffer.
     """
 
-    with open(self._model_file, "rb") as f:
+    with _open_file(self._model_file, "rb") as f:
       model_buf = f.read()
 
     model = _schema_fb.ModelT.InitFromObj(
@@ -495,18 +591,22 @@
     packed_files = self.get_packed_associated_file_list()
     if packed_files:
       # Writes the updated model buffer and associated files into a new model
-      # file. Then overwrites the original model file.
-      with tempfile.NamedTemporaryFile() as temp:
-        new_file = temp.name
-      with open(new_file, "wb") as f:
-        f.write(model_buf)
-      self._copy_archived_files(self._model_file, new_file, packed_files)
-      shutil.copy(new_file, self._model_file)
-      os.remove(new_file)
+      # file (in memory). Then overwrites the original model file.
+      with tempfile.SpooledTemporaryFile() as temp:
+        temp.write(model_buf)
+        self._copy_archived_files(self._model_file, packed_files, temp)
+        temp.seek(0)
+        with _open_file(self._model_file, "wb") as f:
+          shutil.copyfileobj(temp, f)
     else:
-      with open(self._model_file, "wb") as f:
+      with _open_file(self._model_file, "wb") as f:
         f.write(model_buf)
 
+  def _use_basename_for_associated_files_in_metadata(self, metadata):
+    """Removes any associated file local directory (if exists)."""
+    for file in self._get_recorded_associated_file_object_list(metadata):
+      file.name = os.path.basename(file.name)
+
   def _validate_metadata(self, metadata_buf):
     """Validates the metadata to be populated."""
     _assert_metadata_buffer_identifier(metadata_buf)
@@ -521,7 +621,7 @@
                            model_meta.SubgraphMetadataLength()))
 
     # Verify if the number of tensor metadata matches the number of tensors.
-    with open(self._model_file, "rb") as f:
+    with _open_file(self._model_file, "rb") as f:
       model_buf = f.read()
     model = _schema_fb.Model.GetRootAsModel(model_buf, 0)
 
@@ -569,10 +669,10 @@
     with tempfile.NamedTemporaryFile() as temp:
       model_file = temp.name
 
-    with open(model_file, "wb") as f:
+    with _open_file(model_file, "wb") as f:
       f.write(model_buf)
 
-    MetadataPopulator.__init__(self, model_file)
+    super().__init__(model_file)
 
   def __del__(self):
     """Destructor of _MetadataPopulatorWithBuffer.
@@ -596,6 +696,7 @@
     """
     _assert_model_buffer_identifier(model_buffer)
     _assert_metadata_buffer_identifier(metadata_buffer)
+    self._model_buffer = model_buffer
     self._metadata_buffer = metadata_buffer
     self._associated_file_list = associated_file_list
 
@@ -614,7 +715,7 @@
       ValueError: The model does not have metadata.
     """
     _assert_file_exist(model_file)
-    with open(model_file, "rb") as f:
+    with _open_file(model_file, "rb") as f:
       return cls.with_model_buffer(f.read())
 
   @classmethod
@@ -629,20 +730,38 @@
     """
     if not model_buffer:
       raise ValueError("model_buffer cannot be empty.")
-    metadata_buffer = cls._get_metadata_buffer(model_buffer)
+    metadata_buffer = _get_metadata_buffer(model_buffer)
+    if not metadata_buffer:
+      raise ValueError("The model does not have metadata.")
     associated_file_list = cls._parse_packed_associted_file_list(model_buffer)
     return cls(model_buffer, metadata_buffer, associated_file_list)
 
+  def get_associated_file_buffer(self, filename):
+    """Get the specified associated file content in bytearray.
+
+    Args:
+      filename: name of the file to be extracted.
+
+    Returns:
+      The file content in bytearray.
+
+    Raises:
+      ValueError: if the file does not exist in the model.
+    """
+    if filename not in self._associated_file_list:
+      raise ValueError(
+          "The file, {}, does not exist in the model.".format(filename))
+
+    with _open_as_zipfile(io.BytesIO(self._model_buffer)) as zf:
+      return zf.read(filename)
+
+  def get_metadata_buffer(self):
+    """Get the metadata buffer in bytearray out from the model."""
+    return copy.deepcopy(self._metadata_buffer)
+
   def get_metadata_json(self):
     """Converts the metadata into a json string."""
-    opt = _pywrap_flatbuffers.IDLOptions()
-    opt.strict_json = True
-    parser = _pywrap_flatbuffers.Parser(opt)
-    with open(_FLATC_TFLITE_METADATA_SCHEMA_FILE) as f:
-      metadata_schema_content = f.read()
-    if not parser.parse(metadata_schema_content):
-      raise ValueError("Cannot parse metadata schema. Reason: " + parser.error)
-    return _pywrap_flatbuffers.generate_text(parser, self._metadata_buffer)
+    return convert_to_json(self._metadata_buffer)
 
   def get_packed_associated_file_list(self):
     """Returns a list of associated files that are packed in the model.
@@ -653,32 +772,6 @@
     return copy.deepcopy(self._associated_file_list)
 
   @staticmethod
-  def _get_metadata_buffer(model_buf):
-    """Returns the metadata in the model file as a buffer.
-
-    Args:
-      model_buf: valid buffer of the model file.
-
-    Returns:
-      Metadata buffer.
-
-    Raises:
-      ValueError: The model does not have metadata.
-    """
-    tflite_model = _schema_fb.Model.GetRootAsModel(model_buf, 0)
-
-    # Gets metadata from the model file.
-    for i in range(tflite_model.MetadataLength()):
-      meta = tflite_model.Metadata(i)
-      if meta.Name().decode("utf-8") == MetadataPopulator.METADATA_FIELD_NAME:
-        buffer_index = meta.Buffer()
-        metadata = tflite_model.Buffers(buffer_index)
-        metadata_buf = metadata.DataAsNumpy().tobytes()
-        return metadata_buf
-
-    raise ValueError("The model does not have metadata.")
-
-  @staticmethod
   def _parse_packed_associted_file_list(model_buf):
     """Gets a list of associated files packed to the model file.
 
@@ -690,22 +783,47 @@
     """
 
     try:
-      with zipfile.ZipFile(io.BytesIO(model_buf)) as zf:
+      with _open_as_zipfile(io.BytesIO(model_buf)) as zf:
         return zf.namelist()
     except zipfile.BadZipFile:
       return []
 
 
+# Create an individual method for getting the metadata json file, so that it can
+# be used as a standalone util.
+def convert_to_json(metadata_buffer):
+  """Converts the metadata into a json string.
+
+  Args:
+    metadata_buffer: valid metadata buffer in bytes.
+
+  Returns:
+    Metadata in JSON format.
+
+  Raises:
+    ValueError: error occured when parsing the metadata schema file.
+  """
+
+  opt = _pywrap_flatbuffers.IDLOptions()
+  opt.strict_json = True
+  parser = _pywrap_flatbuffers.Parser(opt)
+  with _open_file(_FLATC_TFLITE_METADATA_SCHEMA_FILE) as f:
+    metadata_schema_content = f.read()
+  if not parser.parse(metadata_schema_content):
+    raise ValueError("Cannot parse metadata schema. Reason: " + parser.error)
+  return _pywrap_flatbuffers.generate_text(parser, metadata_buffer)
+
+
 def _assert_file_exist(filename):
   """Checks if a file exists."""
-  if not os.path.exists(filename):
+  if not _exists_file(filename):
     raise IOError("File, '{0}', does not exist.".format(filename))
 
 
 def _assert_model_file_identifier(model_file):
   """Checks if a model file has the expected TFLite schema identifier."""
   _assert_file_exist(model_file)
-  with open(model_file, "rb") as f:
+  with _open_file(model_file, "rb") as f:
     _assert_model_buffer_identifier(f.read())
 
 
@@ -723,3 +841,25 @@
     raise ValueError(
         "The metadata buffer does not have the expected identifier, and may not"
         " be a valid TFLite Metadata.")
+
+
+def _get_metadata_buffer(model_buf):
+  """Returns the metadata in the model file as a buffer.
+
+  Args:
+    model_buf: valid buffer of the model file.
+
+  Returns:
+    Metadata buffer. Returns `None` if the model does not have metadata.
+  """
+  tflite_model = _schema_fb.Model.GetRootAsModel(model_buf, 0)
+
+  # Gets metadata from the model file.
+  for i in range(tflite_model.MetadataLength()):
+    meta = tflite_model.Metadata(i)
+    if meta.Name().decode("utf-8") == MetadataPopulator.METADATA_FIELD_NAME:
+      buffer_index = meta.Buffer()
+      metadata = tflite_model.Buffers(buffer_index)
+      return metadata.DataAsNumpy().tobytes()
+
+  return None
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_displayer.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_displayer.py
new file mode 100644
index 0000000..9d160fc
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_displayer.py
@@ -0,0 +1,34 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""CLI tool for display metadata."""
+
+from absl import app
+from absl import flags
+
+from tensorflow_lite_support.metadata.python import metadata
+
+FLAGS = flags.FLAGS
+flags.DEFINE_string('model_path', None, 'Path to the TFLite model file.')
+flags.DEFINE_string('export_json_path', None, 'Path to the output JSON file.')
+
+
+def main(_):
+  displayer = metadata.MetadataDisplayer.with_model_file(FLAGS.model_path)
+  with open(FLAGS.export_json_path, 'w') as f:
+    f.write(displayer.get_metadata_json())
+
+
+if __name__ == '__main__':
+  app.run(main)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writer_for_task.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writer_for_task.py
new file mode 100644
index 0000000..8d2a9b8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writer_for_task.py
@@ -0,0 +1,345 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the 'License');
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an 'AS IS' BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Object oriented generic metadata writer for modular task API."""
+
+import collections
+import os
+import tempfile
+from typing import Optional, List
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+CalibrationParameter = collections.namedtuple(
+    'CalibrationParameter', ['scale', 'slope', 'offset', 'min_score'])
+
+LabelItem = collections.namedtuple('LabelItem', ['locale', 'filename', 'names'])
+
+
+class Labels:
+  """Simple container holding classification labels of a particular tensor."""
+
+  def __init__(self):
+    self._labels = []  # [LabelItem]
+
+  def add(self,
+          labels: List[str],
+          locale: Optional[str] = None,
+          use_as_category_name=False,
+          exported_filename: Optional[str] = None):
+    """Adds labels in the container."""
+    if not labels:
+      raise ValueError('The list of labels is empty')
+
+    # Prepare the new item to be inserted
+    if not exported_filename:
+      exported_filename = 'labels'
+      if locale:
+        exported_filename += f'_{locale}'
+      exported_filename += '.txt'
+    item = LabelItem(locale, exported_filename, labels)
+
+    if self._labels and use_as_category_name:
+      # Category names should be the first one in the list
+      pos = 0
+
+      # Double check if we need to replace exising category name or insert one.
+      if self._labels[pos].locale:
+        # No category names available, insert one
+        self._labels.insert(pos, item)
+      else:
+        # Update the category name
+        self._labels[pos] = item
+
+    else:
+      # insert the new element at the end of the list
+      self._labels.append(item)
+    return self
+
+  def add_from_file(self,
+                    label_filepath: str,
+                    locale: Optional[str] = None,
+                    use_as_category_name=False,
+                    exported_filename: Optional[str] = None):
+    """Adds a label file in the container."""
+    with open(label_filepath, 'r') as f:
+      labels = f.read().split('\n')
+      return self.add(labels, locale, use_as_category_name, exported_filename)
+
+
+class ScoreCalibration:
+  """Simple container holding score calibration related parameters."""
+
+  # A shortcut to avoid client side code importing _metadata_fb
+  transformation_types = _metadata_fb.ScoreTransformationType
+
+  def __init__(self,
+               transformation_type: _metadata_fb.ScoreTransformationType,
+               parameters: List[CalibrationParameter],
+               default_score: int = 0):
+    self.transformation_type = transformation_type
+    self.parameters = parameters
+    self.default_score = default_score
+
+
+class Writer:
+  """Generic object-oriented Metadata writer.
+
+  Note that this API is experimental and is subject to changes. Also it only
+  supports limited input and output tensor types for now. More types are being
+  added.
+
+  Example usage:
+
+  The model has two inputs, audio and image respectively. And generates two
+  outputs: classification and embedding.
+
+  with open(model_path, 'rb') as f:
+    with Writer(f.read(), 'model_name', 'model description') as writer:
+      writer
+        .add_audio_input(sample_rate=16000, channels=1)
+        .add_image_input()
+        .add_classification_output(Labels().add(['A', 'B']))
+        .add_embedding_output()
+        .populate('model.tflite', 'model.json')
+  """
+
+  def __init__(self, model_buffer: bytearray, model_name: str,
+               model_description: str):
+    self._model_buffer = model_buffer
+    self._general_md = metadata_info.GeneralMd(
+        name=model_name, description=model_description)
+    self._input_mds = []
+    self._output_mds = []
+    self._associate_files = []
+
+  def __enter__(self):
+    self._temp_folder = tempfile.TemporaryDirectory()
+    return self
+
+  def __exit__(self, unused_exc_type, unused_exc_val, unused_exc_tb):
+    self._temp_folder.cleanup()
+    # Delete the attribute so that it errors out outside the `with` statement.
+    delattr(self, '_temp_folder')
+
+  def populate(self,
+               tflite_path: Optional[str] = None,
+               json_path: Optional[str] = None):
+    """Writes the generated flatbuffer file / json metadata to disk.
+
+    Note that you'll only need the tflite file for deployment. The JSON file
+    is useful to help you understand what's in the metadata.
+
+    Args:
+      tflite_path: path to the tflite file.
+      json_path: path to the JSON file.
+
+    Returns:
+      A tuple of (tflite_content_in_bytes, metdata_json_content)
+    """
+    tflite_content = None
+    metadata_json_content = None
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata_info(
+        model_buffer=self._model_buffer,
+        general_md=self._general_md,
+        input_md=self._input_mds,
+        output_md=self._output_mds,
+        associated_files=self._associate_files)
+
+    if tflite_path:
+      tflite_content = writer.populate()
+      writer_utils.save_file(tflite_content, tflite_path)
+
+    if json_path:
+      displayer = _metadata.MetadataDisplayer.with_model_file(tflite_path)
+      metadata_json_content = displayer.get_metadata_json()
+      with open(json_path, 'w') as f:
+        f.write(metadata_json_content)
+
+    return (tflite_content, metadata_json_content)
+
+  def _export_labels(self, filename: str, index_to_label: List[str]):
+    filepath = os.path.join(self._temp_folder.name, filename)
+    with open(filepath, 'w') as f:
+      f.write('\n'.join(index_to_label))
+    self._associate_files.append(filepath)
+    return filepath
+
+  def _input_tensor_type(self, idx):
+    return writer_utils.get_input_tensor_types(self._model_buffer)[idx]
+
+  def _output_tensor_type(self, idx):
+    return writer_utils.get_output_tensor_types(self._model_buffer)[idx]
+
+  _INPUT_AUDIO_NAME = 'audio'
+  _INPUT_AUDIO_DESCRIPTION = 'Input audio clip to be processed.'
+
+  def add_audio_input(self,
+                      sample_rate: int,
+                      channels: int,
+                      name: str = _INPUT_AUDIO_NAME,
+                      description: str = _INPUT_AUDIO_DESCRIPTION):
+    """Marks the next input tensor as an audio input."""
+    # To make Task Library working properly, sample_rate, channels need to be
+    # positive.
+    if sample_rate <= 0:
+      raise ValueError(
+          'sample_rate should be positive, but got {}.'.format(sample_rate))
+    if channels <= 0:
+      raise ValueError(
+          'channels should be positive, but got {}.'.format(channels))
+
+    input_md = metadata_info.InputAudioTensorMd(
+        name=name,
+        description=description,
+        sample_rate=sample_rate,
+        channels=channels)
+    self._input_mds.append(input_md)
+    return self
+
+  _INPUT_IMAGE_NAME = 'image'
+  _INPUT_IMAGE_DESCRIPTION = 'Input image to be processed.'
+  color_space_types = _metadata_fb.ColorSpaceType
+
+  def add_image_input(
+      self,
+      norm_mean: List[float],
+      norm_std: List[float],
+      color_space_type: Optional[
+          _metadata_fb.ColorSpaceType] = _metadata_fb.ColorSpaceType.RGB,
+      name: str = _INPUT_IMAGE_NAME,
+      description: str = _INPUT_IMAGE_DESCRIPTION):
+    """Marks the next input tensor as an image input.
+
+    Args:
+      norm_mean: The mean value used to normalize each input channel. If there
+        is only one element in the list, its value will be broadcasted to all
+        channels. Also note that norm_mean and norm_std should have the same
+        number of elements. [1]
+      norm_std: The std value used to normalize each input channel. If there is
+        only one element in the list, its value will be broadcasted to all
+        channels. [1]
+      color_space_type: The color space type of the input image. [2]
+      name: Name of the input tensor.
+      description: Description of the input tensor.
+
+    Returns:
+      The Writer instance, can be used for chained operation.
+
+    [1]:
+    https://www.tensorflow.org/lite/convert/metadata#normalization_and_quantization_parameters
+    [2]:
+    https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L172
+    """
+    input_md = metadata_info.InputImageTensorMd(
+        name=name,
+        description=description,
+        norm_mean=norm_mean,
+        norm_std=norm_std,
+        color_space_type=color_space_type,
+        tensor_type=self._input_tensor_type(len(self._input_mds)))
+
+    self._input_mds.append(input_md)
+    return self
+
+  _OUTPUT_EMBEDDING_NAME = 'embedding'
+  _OUTPUT_EMBEDDING_DESCRIPTION = 'Embedding vector of the input.'
+
+  def add_embedding_output(self,
+                           name: str = _OUTPUT_EMBEDDING_NAME,
+                           description: str = _OUTPUT_EMBEDDING_DESCRIPTION):
+    """Marks the next output tensor as embedding."""
+    output_md = metadata_info.TensorMd(name=name, description=description)
+    self._output_mds.append(output_md)
+    return self
+
+  def _export_calibration_file(self, filename: str,
+                               calibrations: List[CalibrationParameter]):
+    """Store calibration parameters in a csv file."""
+    filepath = os.path.join(self._temp_folder.name, filename)
+    with open(filepath, 'w') as f:
+      for idx, item in enumerate(calibrations):
+        if idx != 0:
+          f.write('\n')
+        if item:
+          scale, slope, offset, min_score = item
+          if all(x is not None for x in item):
+            f.write(f'{scale},{slope},{offset},{min_score}')
+          elif all(x is not None for x in item[:3]):
+            f.write(f'{scale},{slope},{offset}')
+          else:
+            raise ValueError('scale, slope and offset values can not be set to '
+                             'None.')
+          self._associate_files.append(filepath)
+    return filepath
+
+  _OUTPUT_CLASSIFICATION_NAME = 'score'
+  _OUTPUT_CLASSIFICATION_DESCRIPTION = 'Score of the labels respectively'
+
+  def add_classification_output(
+      self,
+      labels: Labels,
+      score_calibration: Optional[ScoreCalibration] = None,
+      name=_OUTPUT_CLASSIFICATION_NAME,
+      description=_OUTPUT_CLASSIFICATION_DESCRIPTION):
+    """Marks model's next output tensor as a classification head.
+
+    Example usage:
+    writer.add_classification_output(
+      Labels()
+        .add(['cat', 'dog], 'en')
+        .add(['chat', 'chien], 'fr')
+        .add(['/m/011l78', '/m/031d23'], use_as_category_name=True))
+
+    Args:
+      labels: an instance of Labels helper class.
+      score_calibration: an instance of ScoreCalibration helper class.
+      name: Metadata name of the tensor. Note that this is different from tensor
+        name in the flatbuffer.
+      description: human readable description of what the tensor does.
+
+    Returns:
+      The current Writer instance to allow chained operation.
+    """
+    calibration_md = None
+    if score_calibration:
+      calibration_md = metadata_info.ScoreCalibrationMd(
+          score_transformation_type=score_calibration.transformation_type,
+          default_score=score_calibration.default_score,
+          file_path=self._export_calibration_file('score_calibration.txt',
+                                                  score_calibration.parameters))
+
+    idx = len(self._output_mds)
+
+    label_files = []
+    for item in labels._labels:  # pylint: disable=protected-access
+      label_files.append(
+          metadata_info.LabelFileMd(
+              self._export_labels(item.filename, item.names),
+              locale=item.locale))
+
+    output_md = metadata_info.ClassificationTensorMd(
+        name=name,
+        description=description,
+        label_files=label_files,
+        tensor_type=self._output_tensor_type(idx),
+        score_calibration_md=calibration_md,
+    )
+    self._output_mds.append(output_md)
+    return self
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/BUILD
new file mode 100644
index 0000000..e84aac32
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/BUILD
@@ -0,0 +1,142 @@
+# Placeholder for internal Python strict library compatibility macro.
+
+package(
+    default_visibility = [
+        "//visibility:public",
+    ],
+    licenses = ["notice"],
+)
+
+py_library(
+    name = "metadata_writer",
+    srcs = [
+        "metadata_writer.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":writer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata:schema_py",
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_library(
+    name = "metadata_info",
+    srcs = [
+        "metadata_info.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":writer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata:schema_py",
+    ],
+)
+
+py_library(
+    name = "writer_utils",
+    srcs = [
+        "writer_utils.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata:schema_py",
+    ],
+)
+
+py_library(
+    name = "image_classifier",
+    srcs = [
+        "image_classifier.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":metadata_writer",
+        ":writer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+    ],
+)
+
+py_library(
+    name = "object_detector",
+    srcs = [
+        "object_detector.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":metadata_writer",
+        ":writer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata:schema_py",
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_library(
+    name = "image_segmenter",
+    srcs = [
+        "image_segmenter.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":metadata_writer",
+        ":writer_utils",
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+    ],
+)
+
+py_library(
+    name = "nl_classifier",
+    srcs = [
+        "nl_classifier.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":metadata_writer",
+        ":writer_utils",
+    ],
+)
+
+py_library(
+    name = "audio_classifier",
+    srcs = [
+        "audio_classifier.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":metadata_writer",
+        ":writer_utils",
+    ],
+)
+
+py_library(
+    name = "bert_nl_classifier",
+    srcs = [
+        "bert_nl_classifier.py",
+    ],
+    srcs_version = "PY3",
+    visibility = ["//visibility:public"],
+    deps = [
+        ":metadata_info",
+        ":metadata_writer",
+        ":writer_utils",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/__init__.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/__init__.py
new file mode 100644
index 0000000..2ae3e34
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/__init__.py
@@ -0,0 +1,13 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/audio_classifier.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/audio_classifier.py
new file mode 100644
index 0000000..ce9bfec
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/audio_classifier.py
@@ -0,0 +1,168 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Writes metadata and label file to the audio classifier models."""
+
+from typing import List, Optional
+
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+_MODEL_NAME = "AudioClassifier"
+_MODEL_DESCRIPTION = (
+    "Identify the most prominent type in the audio clip from a known set of "
+    "categories.")
+_INPUT_NAME = "audio_clip"
+_INPUT_DESCRIPTION = "Input audio clip to be classified."
+_OUTPUT_NAME = "probability"
+_OUTPUT_DESCRIPTION = "Scores of the labels respectively."
+
+
+class MetadataWriter(metadata_writer.MetadataWriter):
+  """Writes metadata into an audio classifier."""
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.InputAudioTensorMd] = None,
+      output_md: Optional[metadata_info.ClassificationTensorMd] = None):
+    """Creates MetadataWriter based on general/input/output information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model. If not specified, default
+        general metadata will be generated.
+      input_md: input audio tensor informaton. If not specified, default input
+        metadata will be generated.
+      output_md: output classification tensor informaton. If not specified,
+        default output metadata will be generated.
+
+    Returns:
+      A MetadataWriter object.
+    """
+    if output_md is None:
+      output_md = metadata_info.ClassificationTensorMd(
+          name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)
+
+    return cls.create_from_metadata_info_for_multihead(model_buffer, general_md,
+                                                       input_md, [output_md])
+
+  @classmethod
+  def create_from_metadata_info_for_multihead(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.InputAudioTensorMd] = None,
+      output_md_list: Optional[List[
+          metadata_info.ClassificationTensorMd]] = None):
+    """Creates a MetadataWriter instance for multihead models.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model. If not specified, default
+        general metadata will be generated.
+      input_md: input audio tensor informaton. If not specified, default input
+        metadata will be generated.
+      output_md_list: information of each output tensor head. If not specified,
+        default metadata will be generated for each output tensor. If
+        `tensor_name` in each `ClassificationTensorMd` instance is not
+        specified, elements in `output_md_list` need to have one-to-one mapping
+        with the output tensors [1] in the TFLite model.
+      [1]:
+        https://github.com/tensorflow/tflite-support/blob/b2a509716a2d71dfff706468680a729cc1604cff/tensorflow_lite_support/metadata/metadata_schema.fbs#L605-L612
+
+    Returns:
+      A MetadataWriter object.
+    """
+
+    if general_md is None:
+      general_md = metadata_info.GeneralMd(
+          name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
+
+    if input_md is None:
+      input_md = metadata_info.InputAudioTensorMd(
+          name=_INPUT_NAME, description=_INPUT_DESCRIPTION)
+
+    associated_files = []
+    for md in output_md_list or []:
+      associated_files.extend(
+          [file.file_path for file in md.associated_files or []])
+
+    return super().create_from_metadata_info(
+        model_buffer=model_buffer,
+        general_md=general_md,
+        input_md=[input_md],
+        output_md=output_md_list,
+        associated_files=associated_files)
+
+  @classmethod
+  def create_for_inference(
+      cls,
+      model_buffer: bytearray,
+      sample_rate: int,
+      channels: int,
+      label_file_paths: List[str],
+      score_calibration_md: Optional[metadata_info.ScoreCalibrationMd] = None):
+    """Creates mandatory metadata for TFLite Support inference.
+
+    The parameters required in this method are mandatory when using TFLite
+    Support features, such as Task library and Codegen tool (Android Studio ML
+    Binding). Other metadata fields will be set to default. If other fields need
+    to be filled, use the method `create_from_metadata_info` to edit them.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      sample_rate: the sample rate in Hz when the audio was captured.
+      channels: the channel count of the audio.
+      label_file_paths: paths to the label files [1] in the classification
+        tensor. Pass in an empty list if the model does not have any label file.
+      score_calibration_md: information of the score calibration operation [2]
+        in the classification tensor. Optional if the model does not use score
+        calibration.
+      [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L95
+      [2]:
+        https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L434
+
+    Returns:
+      A MetadataWriter object.
+    """
+    # To make Task Library working properly, sample_rate, channels need to be
+    # positive.
+    if sample_rate <= 0:
+      raise ValueError(
+          "sample_rate should be positive, but got {}.".format(sample_rate))
+
+    if channels <= 0:
+      raise ValueError(
+          "channels should be positive, but got {}.".format(channels))
+
+    input_md = metadata_info.InputAudioTensorMd(_INPUT_NAME, _INPUT_DESCRIPTION,
+                                                sample_rate, channels)
+
+    output_md = metadata_info.ClassificationTensorMd(
+        name=_OUTPUT_NAME,
+        description=_OUTPUT_DESCRIPTION,
+        label_files=[
+            metadata_info.LabelFileMd(file_path=file_path)
+            for file_path in label_file_paths
+        ],
+        tensor_type=writer_utils.get_output_tensor_types(model_buffer)[0],
+        score_calibration_md=score_calibration_md)
+
+    return cls.create_from_metadata_info(
+        model_buffer, input_md=input_md, output_md=output_md)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/bert_nl_classifier.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/bert_nl_classifier.py
new file mode 100644
index 0000000..1f34bcf
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/bert_nl_classifier.py
@@ -0,0 +1,150 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Writes metadata and label file to the Bert NL classifier models."""
+
+from typing import List, Optional, Union
+
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+_MODEL_NAME = "BertNLClassifier"
+_MODEL_DESCRIPTION = ("Classify the input text into a set of known categories.")
+
+_OUTPUT_NAME = "probability"
+_OUTPUT_DESCRIPTION = "Probabilities of the labels respectively."
+
+# The input tensor names of models created by Model Maker.
+_DEFAULT_ID_NAME = "serving_default_input_word_ids:0"
+_DEFAULT_MASK_NAME = "serving_default_input_mask:0"
+_DEFAULT_SEGMENT_ID_NAME = "serving_default_input_type_ids:0"
+
+
+class MetadataWriter(metadata_writer.MetadataWriter):
+  """Writes metadata into the Bert NL classifier."""
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.BertInputTensorsMd] = None,
+      output_md: Optional[metadata_info.ClassificationTensorMd] = None):
+    """Creates MetadataWriter based on general/input/output information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model. If not specified, default
+        general metadata will be generated.
+      input_md: input tensor information. If not specified, default input
+        metadata will be generated.
+      output_md: output classification tensor informaton. If not specified,
+        default output metadata will be generated.
+
+    Returns:
+      A MetadataWriter object.
+    """
+    if general_md is None:
+      general_md = metadata_info.GeneralMd(
+          name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
+
+    if input_md is None:
+      input_md = metadata_info.BertInputTensorsMd(model_buffer,
+                                                  _DEFAULT_ID_NAME,
+                                                  _DEFAULT_MASK_NAME,
+                                                  _DEFAULT_SEGMENT_ID_NAME)
+
+    if output_md is None:
+      output_md = metadata_info.ClassificationTensorMd(
+          name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)
+
+    if output_md.associated_files is None:
+      output_md.associated_files = []
+
+    return cls.create_from_metadata(
+        model_buffer,
+        model_metadata=general_md.create_metadata(),
+        input_metadata=input_md.create_input_tesnor_metadata(),
+        output_metadata=[output_md.create_metadata()],
+        associated_files=[
+            file.file_path for file in output_md.associated_files
+        ] + input_md.get_tokenizer_associated_files(),
+        input_process_units=input_md.create_input_process_unit_metadata())
+
+  @classmethod
+  def create_for_inference(
+      cls,
+      model_buffer: bytearray,
+      tokenizer_md: Union[metadata_info.BertTokenizerMd,
+                          metadata_info.SentencePieceTokenizerMd],
+      label_file_paths: List[str],
+      ids_name: str = _DEFAULT_ID_NAME,
+      mask_name: str = _DEFAULT_MASK_NAME,
+      segment_name: str = _DEFAULT_SEGMENT_ID_NAME,
+  ):
+    """Creates mandatory metadata for TFLite Support inference.
+
+    The parameters required in this method are mandatory when using TFLite
+    Support features, such as Task library and Codegen tool (Android Studio ML
+    Binding). Other metadata fields will be set to default. If other fields need
+    to be filled, use the method `create_from_metadata_info` to edit them.
+
+    `ids_name`, `mask_name`, and `segment_name` correspond to the `Tensor.name`
+    in the TFLite schema, which help to determine the tensor order when
+    populating metadata. The default values come from Model Maker.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      tokenizer_md: information of the tokenizer used to process the input
+        string, if any. Supported tokenziers are: `BertTokenizer` [1] and
+          `SentencePieceTokenizer` [2]. If the tokenizer is `RegexTokenizer`
+          [3], refer to `nl_classifier.MetadataWriter`.
+        [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L436
+        [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L473
+        [3]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L475
+      label_file_paths: paths to the label files [4] in the classification
+        tensor. Pass in an empty list if the model does not have any label file.
+        [4]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L95
+      ids_name: name of the ids tensor, which represents the tokenized ids of
+        the input text.
+      mask_name: name of the mask tensor, which represents the mask with 1 for
+        real tokens and 0 for padding tokens.
+      segment_name: name of the segment ids tensor, where `0` stands for the
+        first sequence, and `1` stands for the second sequence if exists.
+
+    Returns:
+      A MetadataWriter object.
+    """
+    input_md = metadata_info.BertInputTensorsMd(
+        model_buffer,
+        ids_name,
+        mask_name,
+        segment_name,
+        tokenizer_md=tokenizer_md)
+    output_md = metadata_info.ClassificationTensorMd(
+        name=_OUTPUT_NAME,
+        description=_OUTPUT_DESCRIPTION,
+        label_files=[
+            metadata_info.LabelFileMd(file_path=file_path)
+            for file_path in label_file_paths
+        ],
+        tensor_type=writer_utils.get_output_tensor_types(model_buffer)[0])
+
+    return cls.create_from_metadata_info(
+        model_buffer, input_md=input_md, output_md=output_md)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/image_classifier.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/image_classifier.py
new file mode 100644
index 0000000..1f07270
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/image_classifier.py
@@ -0,0 +1,138 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Writes metadata and label file to the image classifier models."""
+
+from typing import List, Optional
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+_MODEL_NAME = "ImageClassifier"
+MODEL_DESCRIPTION = ("Identify the most prominent object in the image from a "
+                     "known set of categories.")
+INPUT_NAME = "image"
+INPUT_DESCRIPTION = "Input image to be classified."
+OUTPUT_NAME = "probability"
+OUTPUT_DESCRIPTION = "Probabilities of the labels respectively."
+
+
+class MetadataWriter(metadata_writer.MetadataWriter):
+  """Writes metadata into an image classifier."""
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.InputImageTensorMd] = None,
+      output_md: Optional[metadata_info.ClassificationTensorMd] = None):
+    """Creates MetadataWriter based on general/input/output information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model. If not specified, default
+        general metadata will be generated.
+      input_md: input image tensor informaton, if not specified, default input
+        metadata will be generated.
+      output_md: output classification tensor informaton, if not specified,
+        default output metadata will be generated.
+
+    Returns:
+      A MetadataWriter object.
+    """
+
+    if general_md is None:
+      general_md = metadata_info.GeneralMd(
+          name=_MODEL_NAME, description=MODEL_DESCRIPTION)
+
+    if input_md is None:
+      input_md = metadata_info.InputImageTensorMd(
+          name=INPUT_NAME,
+          description=INPUT_DESCRIPTION,
+          color_space_type=_metadata_fb.ColorSpaceType.RGB)
+
+    if output_md is None:
+      output_md = metadata_info.ClassificationTensorMd(
+          name=OUTPUT_NAME, description=OUTPUT_DESCRIPTION)
+
+    if output_md.associated_files is None:
+      output_md.associated_files = []
+
+    return super().create_from_metadata_info(
+        model_buffer=model_buffer,
+        general_md=general_md,
+        input_md=[input_md],
+        output_md=[output_md],
+        associated_files=[
+            file.file_path for file in output_md.associated_files
+        ])
+
+  @classmethod
+  def create_for_inference(
+      cls,
+      model_buffer: bytearray,
+      input_norm_mean: List[float],
+      input_norm_std: List[float],
+      label_file_paths: List[str],
+      score_calibration_md: Optional[metadata_info.ScoreCalibrationMd] = None):
+    """Creates mandatory metadata for TFLite Support inference.
+
+    The parameters required in this method are mandatory when using TFLite
+    Support features, such as Task library and Codegen tool (Android Studio ML
+    Binding). Other metadata fields will be set to default. If other fields need
+    to be filled, use the method `create_from_metadata_info` to edit them.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      input_norm_mean: the mean value used in the input tensor normalization
+        [1].
+      input_norm_std: the std value used in the input tensor normalizarion [1].
+      label_file_paths: paths to the label files [2] in the classification
+        tensor. Pass in an empty list if the model does not have any label file.
+      score_calibration_md: information of the score calibration operation [3]
+        in the classification tensor. Optional if the model does not use score
+        calibration.
+      [1]:
+        https://www.tensorflow.org/lite/convert/metadata#normalization_and_quantization_parameters
+      [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L95
+      [3]:
+        https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L434
+
+    Returns:
+      A MetadataWriter object.
+    """
+    input_md = metadata_info.InputImageTensorMd(
+        name=INPUT_NAME,
+        description=INPUT_DESCRIPTION,
+        norm_mean=input_norm_mean,
+        norm_std=input_norm_std,
+        color_space_type=_metadata_fb.ColorSpaceType.RGB,
+        tensor_type=writer_utils.get_input_tensor_types(model_buffer)[0])
+
+    output_md = metadata_info.ClassificationTensorMd(
+        name=OUTPUT_NAME,
+        description=OUTPUT_DESCRIPTION,
+        label_files=[
+            metadata_info.LabelFileMd(file_path=file_path)
+            for file_path in label_file_paths
+        ],
+        tensor_type=writer_utils.get_output_tensor_types(model_buffer)[0],
+        score_calibration_md=score_calibration_md)
+
+    return cls.create_from_metadata_info(
+        model_buffer, input_md=input_md, output_md=output_md)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/image_segmenter.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/image_segmenter.py
new file mode 100644
index 0000000..ea3766f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/image_segmenter.py
@@ -0,0 +1,157 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Writes metadata and label file to the image segmenter models."""
+
+from typing import List, Optional
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+_MODEL_NAME = "ImageSegmenter"
+_MODEL_DESCRIPTION = ("Semantic image segmentation predicts whether each pixel "
+                      "of an image is associated with a certain class.")
+_INPUT_NAME = "image"
+_INPUT_DESCRIPTION = "Input image to be segmented."
+_OUTPUT_NAME = "segmentation_masks"
+_OUTPUT_DESCRIPTION = "Masks over the target objects with high accuracy."
+# The output tensor is in the shape of [1, ImageHeight, ImageWidth, N], where N
+# is the number of objects that the segmentation model can recognize. The output
+# tensor is essentially a list of grayscale bitmaps, where each value is the
+# probability of the corresponding pixel belonging to a certain object type.
+# Therefore, the content dimension range of the output tensor is [1, 2].
+_CONTENT_DIM_MIN = 1
+_CONTENT_DIM_MAX = 2
+
+
+def _create_segmentation_masks_metadata(
+    masks_md: metadata_info.TensorMd) -> _metadata_fb.TensorMetadataT:
+  """Creates the metadata for the segmentation masks tensor."""
+  masks_metadata = masks_md.create_metadata()
+
+  # Create tensor content information.
+  content = _metadata_fb.ContentT()
+  content.contentProperties = _metadata_fb.ImagePropertiesT()
+  content.contentProperties.colorSpace = _metadata_fb.ColorSpaceType.GRAYSCALE
+  content.contentPropertiesType = _metadata_fb.ContentProperties.ImageProperties
+  # Add the content range. See
+  # https://github.com/tensorflow/tflite-support/blob/ace5d3f3ce44c5f77c70284fa9c5a4e3f2f92abb/tensorflow_lite_support/metadata/metadata_schema.fbs#L285-L347
+  dim_range = _metadata_fb.ValueRangeT()
+  dim_range.min = _CONTENT_DIM_MIN
+  dim_range.max = _CONTENT_DIM_MAX
+  content.range = dim_range
+  masks_metadata.content = content
+
+  return masks_metadata
+
+
+class MetadataWriter(metadata_writer.MetadataWriter):
+  """Writes metadata into an image segmenter."""
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.InputImageTensorMd] = None,
+      output_md: Optional[metadata_info.TensorMd] = None):
+    """Creates MetadataWriter based on general/input/outputs information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model.
+      input_md: input image tensor informaton.
+      output_md: output segmentation mask tensor informaton. This tensor is a
+        multidimensional array of [1 x mask_height x mask_width x num_classes],
+        where mask_width and mask_height are the dimensions of the segmentation
+        masks produced by the model, and num_classes is the number of classes
+        supported by the model.
+
+    Returns:
+      A MetadataWriter object.
+    """
+
+    if general_md is None:
+      general_md = metadata_info.GeneralMd(
+          name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
+
+    if input_md is None:
+      input_md = metadata_info.InputImageTensorMd(
+          name=_INPUT_NAME,
+          description=_INPUT_DESCRIPTION,
+          color_space_type=_metadata_fb.ColorSpaceType.RGB)
+
+    if output_md is None:
+      output_md = metadata_info.TensorMd(
+          name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)
+
+    if output_md.associated_files is None:
+      output_md.associated_files = []
+
+    return super().create_from_metadata(
+        model_buffer,
+        model_metadata=general_md.create_metadata(),
+        input_metadata=[input_md.create_metadata()],
+        output_metadata=[_create_segmentation_masks_metadata(output_md)],
+        associated_files=[
+            file.file_path for file in output_md.associated_files
+        ])
+
+  @classmethod
+  def create_for_inference(cls, model_buffer: bytearray,
+                           input_norm_mean: List[float],
+                           input_norm_std: List[float],
+                           label_file_paths: List[str]):
+    """Creates mandatory metadata for TFLite Support inference.
+
+    The parameters required in this method are mandatory when using TFLite
+    Support features, such as Task library and Codegen tool (Android Studio ML
+    Binding). Other metadata fields will be set to default. If other fields need
+    to be filled, use the method `create_from_metadata_info` to edit them.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      input_norm_mean: the mean value used in the input tensor normalization
+        [1].
+      input_norm_std: the std value used in the input tensor normalizarion [1].
+      label_file_paths: paths to the label files [2] in the category tensor.
+        Pass in an empty list If the model does not have any label file.
+      [1]:
+        https://www.tensorflow.org/lite/convert/metadata#normalization_and_quantization_parameters
+      [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L108
+
+    Returns:
+      A MetadataWriter object.
+    """
+    input_md = metadata_info.InputImageTensorMd(
+        name=_INPUT_NAME,
+        description=_INPUT_DESCRIPTION,
+        norm_mean=input_norm_mean,
+        norm_std=input_norm_std,
+        color_space_type=_metadata_fb.ColorSpaceType.RGB,
+        tensor_type=writer_utils.get_input_tensor_types(model_buffer)[0])
+
+    output_md = metadata_info.TensorMd(
+        name=_OUTPUT_NAME,
+        description=_OUTPUT_DESCRIPTION,
+        associated_files=[
+            metadata_info.LabelFileMd(file_path=file_path)
+            for file_path in label_file_paths
+        ])
+
+    return cls.create_from_metadata_info(
+        model_buffer, input_md=input_md, output_md=output_md)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/metadata_info.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/metadata_info.py
new file mode 100644
index 0000000..b1b6c1c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/metadata_info.py
@@ -0,0 +1,817 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Helper classes for common model metadata information."""
+
+import collections
+import csv
+import os
+from typing import List, Optional, Type, Union
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+# Min and max values for UINT8 tensors.
+_MIN_UINT8 = 0
+_MAX_UINT8 = 255
+
+# Default description for vocabulary files.
+_VOCAB_FILE_DESCRIPTION = ("Vocabulary file to convert natural language "
+                           "words to embedding vectors.")
+
+
+class GeneralMd:
+  """A container for common metadata information of a model.
+
+  Attributes:
+    name: name of the model.
+    version: version of the model.
+    description: description of what the model does.
+    author: author of the model.
+    licenses: licenses of the model.
+  """
+
+  def __init__(self,
+               name: Optional[str] = None,
+               version: Optional[str] = None,
+               description: Optional[str] = None,
+               author: Optional[str] = None,
+               licenses: Optional[str] = None):
+    self.name = name
+    self.version = version
+    self.description = description
+    self.author = author
+    self.licenses = licenses
+
+  def create_metadata(self) -> _metadata_fb.ModelMetadataT:
+    """Creates the model metadata based on the general model information.
+
+    Returns:
+      A Flatbuffers Python object of the model metadata.
+    """
+    model_metadata = _metadata_fb.ModelMetadataT()
+    model_metadata.name = self.name
+    model_metadata.version = self.version
+    model_metadata.description = self.description
+    model_metadata.author = self.author
+    model_metadata.license = self.licenses
+    return model_metadata
+
+
+class AssociatedFileMd:
+  """A container for common associated file metadata information.
+
+  Attributes:
+    file_path: path to the associated file.
+    description: description of the associated file.
+    file_type: file type of the associated file [1].
+    locale: locale of the associated file [2].
+    [1]:
+      https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L77
+    [2]:
+      https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L154
+  """
+
+  def __init__(
+      self,
+      file_path: str,
+      description: Optional[str] = None,
+      file_type: Optional[_metadata_fb.AssociatedFileType] = _metadata_fb
+      .AssociatedFileType.UNKNOWN,
+      locale: Optional[str] = None):
+    self.file_path = file_path
+    self.description = description
+    self.file_type = file_type
+    self.locale = locale
+
+  def create_metadata(self) -> _metadata_fb.AssociatedFileT:
+    """Creates the associated file metadata.
+
+    Returns:
+      A Flatbuffers Python object of the associated file metadata.
+    """
+    file_metadata = _metadata_fb.AssociatedFileT()
+    file_metadata.name = os.path.basename(self.file_path)
+    file_metadata.description = self.description
+    file_metadata.type = self.file_type
+    file_metadata.locale = self.locale
+    return file_metadata
+
+
+class LabelFileMd(AssociatedFileMd):
+  """A container for label file metadata information."""
+
+  _LABEL_FILE_DESCRIPTION = ("Labels for categories that the model can "
+                             "recognize.")
+  _FILE_TYPE = _metadata_fb.AssociatedFileType.TENSOR_AXIS_LABELS
+
+  def __init__(self, file_path: str, locale: Optional[str] = None):
+    """Creates a LabelFileMd object.
+
+    Args:
+      file_path: file_path of the label file.
+      locale: locale of the label file [1].
+      [1]:
+      https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L154
+    """
+    super().__init__(file_path, self._LABEL_FILE_DESCRIPTION, self._FILE_TYPE,
+                     locale)
+
+
+class RegexTokenizerMd:
+  """A container for the Regex tokenizer [1] metadata information.
+
+  [1]:
+    https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L459
+  """
+
+  def __init__(self, delim_regex_pattern: str, vocab_file_path: str):
+    """Initializes a RegexTokenizerMd object.
+
+    Args:
+      delim_regex_pattern: the regular expression to segment strings and create
+        tokens.
+      vocab_file_path: path to the vocabulary file.
+    """
+    self._delim_regex_pattern = delim_regex_pattern
+    self._vocab_file_path = vocab_file_path
+
+  def create_metadata(self) -> _metadata_fb.ProcessUnitT:
+    """Creates the Bert tokenizer metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the Bert tokenizer metadata.
+    """
+    vocab = _metadata_fb.AssociatedFileT()
+    vocab.name = self._vocab_file_path
+    vocab.description = _VOCAB_FILE_DESCRIPTION
+    vocab.type = _metadata_fb.AssociatedFileType.VOCABULARY
+
+    # Create the RegexTokenizer.
+    tokenizer = _metadata_fb.ProcessUnitT()
+    tokenizer.optionsType = (
+        _metadata_fb.ProcessUnitOptions.RegexTokenizerOptions)
+    tokenizer.options = _metadata_fb.RegexTokenizerOptionsT()
+    tokenizer.options.delimRegexPattern = self._delim_regex_pattern
+    tokenizer.options.vocabFile = [vocab]
+    return tokenizer
+
+
+class BertTokenizerMd:
+  """A container for the Bert tokenizer [1] metadata information.
+
+  [1]:
+    https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L436
+  """
+
+  def __init__(self, vocab_file_path: str):
+    """Initializes a BertTokenizerMd object.
+
+    Args:
+      vocab_file_path: path to the vocabulary file.
+    """
+    self._vocab_file_path = vocab_file_path
+
+  def create_metadata(self) -> _metadata_fb.ProcessUnitT:
+    """Creates the Bert tokenizer metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the Bert tokenizer metadata.
+    """
+    vocab = _metadata_fb.AssociatedFileT()
+    vocab.name = self._vocab_file_path
+    vocab.description = _VOCAB_FILE_DESCRIPTION
+    vocab.type = _metadata_fb.AssociatedFileType.VOCABULARY
+    tokenizer = _metadata_fb.ProcessUnitT()
+    tokenizer.optionsType = _metadata_fb.ProcessUnitOptions.BertTokenizerOptions
+    tokenizer.options = _metadata_fb.BertTokenizerOptionsT()
+    tokenizer.options.vocabFile = [vocab]
+    return tokenizer
+
+
+class SentencePieceTokenizerMd:
+  """A container for the sentence piece tokenizer [1] metadata information.
+
+  [1]:
+    https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L473
+  """
+
+  _SP_MODEL_DESCRIPTION = "The sentence piece model file."
+  _SP_VOCAB_FILE_DESCRIPTION = _VOCAB_FILE_DESCRIPTION + (
+      " This file is optional during tokenization, while the sentence piece "
+      "model is mandatory.")
+
+  def __init__(self,
+               sentence_piece_model_path: str,
+               vocab_file_path: Optional[str] = None):
+    """Initializes a SentencePieceTokenizerMd object.
+
+    Args:
+      sentence_piece_model_path: path to the sentence piece model file.
+      vocab_file_path: path to the vocabulary file.
+    """
+    self._sentence_piece_model_path = sentence_piece_model_path
+    self._vocab_file_path = vocab_file_path
+
+  def create_metadata(self) -> _metadata_fb.ProcessUnitT:
+    """Creates the sentence piece tokenizer metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the sentence piece tokenizer metadata.
+    """
+    tokenizer = _metadata_fb.ProcessUnitT()
+    tokenizer.optionsType = (
+        _metadata_fb.ProcessUnitOptions.SentencePieceTokenizerOptions)
+    tokenizer.options = _metadata_fb.SentencePieceTokenizerOptionsT()
+
+    sp_model = _metadata_fb.AssociatedFileT()
+    sp_model.name = self._sentence_piece_model_path
+    sp_model.description = self._SP_MODEL_DESCRIPTION
+    tokenizer.options.sentencePieceModel = [sp_model]
+    if self._vocab_file_path:
+      vocab = _metadata_fb.AssociatedFileT()
+      vocab.name = self._vocab_file_path
+      vocab.description = self._SP_VOCAB_FILE_DESCRIPTION
+      vocab.type = _metadata_fb.AssociatedFileType.VOCABULARY
+      tokenizer.options.vocabFile = [vocab]
+    return tokenizer
+
+
+class ScoreCalibrationMd:
+  """A container for score calibration [1] metadata information.
+
+  [1]:
+    https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L434
+  """
+
+  _SCORE_CALIBRATION_FILE_DESCRIPTION = (
+      "Contains sigmoid-based score calibration parameters. The main purposes "
+      "of score calibration is to make scores across classes comparable, so "
+      "that a common threshold can be used for all output classes.")
+  _FILE_TYPE = _metadata_fb.AssociatedFileType.TENSOR_AXIS_SCORE_CALIBRATION
+
+  def __init__(self,
+               score_transformation_type: _metadata_fb.ScoreTransformationType,
+               default_score: float, file_path: str):
+    """Creates a ScoreCalibrationMd object.
+
+    Args:
+      score_transformation_type: type of the function used for transforming the
+        uncalibrated score before applying score calibration.
+      default_score: the default calibrated score to apply if the uncalibrated
+        score is below min_score or if no parameters were specified for a given
+        index.
+      file_path: file_path of the score calibration file [1].
+      [1]:
+        https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L122
+
+    Raises:
+      ValueError: if the score_calibration file is malformed.
+    """
+    self._score_transformation_type = score_transformation_type
+    self._default_score = default_score
+    self._file_path = file_path
+
+    # Sanity check the score calibration file.
+    with open(self._file_path) as calibration_file:
+      csv_reader = csv.reader(calibration_file, delimiter=",")
+      for row in csv_reader:
+        if row and len(row) != 3 and len(row) != 4:
+          raise ValueError(
+              f"Expected empty lines or 3 or 4 parameters per line in score"
+              f" calibration file, but got {len(row)}.")
+
+        if row and float(row[0]) < 0:
+          raise ValueError(
+              f"Expected scale to be a non-negative value, but got "
+              f"{float(row[0])}.")
+
+  def create_metadata(self) -> _metadata_fb.ProcessUnitT:
+    """Creates the score calibration metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the score calibration metadata.
+    """
+    score_calibration = _metadata_fb.ProcessUnitT()
+    score_calibration.optionsType = (
+        _metadata_fb.ProcessUnitOptions.ScoreCalibrationOptions)
+    options = _metadata_fb.ScoreCalibrationOptionsT()
+    options.scoreTransformation = self._score_transformation_type
+    options.defaultScore = self._default_score
+    score_calibration.options = options
+    return score_calibration
+
+  def create_score_calibration_file_md(self) -> AssociatedFileMd:
+    return AssociatedFileMd(self._file_path,
+                            self._SCORE_CALIBRATION_FILE_DESCRIPTION,
+                            self._FILE_TYPE)
+
+
+class TensorMd:
+  """A container for common tensor metadata information.
+
+  Attributes:
+    name: name of the tensor.
+    description: description of what the tensor is.
+    min_values: per-channel minimum value of the tensor.
+    max_values: per-channel maximum value of the tensor.
+    content_type: content_type of the tensor.
+    associated_files: information of the associated files in the tensor.
+    tensor_name: name of the corresponding tensor [1] in the TFLite model. It is
+      used to locate the corresponding tensor and decide the order of the tensor
+      metadata [2] when populating model metadata.
+    [1]:
+      https://github.com/tensorflow/tensorflow/blob/cb67fef35567298b40ac166b0581cd8ad68e5a3a/tensorflow/lite/schema/schema.fbs#L1129-L1136
+    [2]:
+      https://github.com/tensorflow/tflite-support/blob/b2a509716a2d71dfff706468680a729cc1604cff/tensorflow_lite_support/metadata/metadata_schema.fbs#L595-L612
+  """
+
+  def __init__(self,
+               name: Optional[str] = None,
+               description: Optional[str] = None,
+               min_values: Optional[List[float]] = None,
+               max_values: Optional[List[float]] = None,
+               content_type: _metadata_fb.ContentProperties = _metadata_fb
+               .ContentProperties.FeatureProperties,
+               associated_files: Optional[List[Type[AssociatedFileMd]]] = None,
+               tensor_name: Optional[str] = None):
+    self.name = name
+    self.description = description
+    self.min_values = min_values
+    self.max_values = max_values
+    self.content_type = content_type
+    self.associated_files = associated_files
+    self.tensor_name = tensor_name
+
+  def create_metadata(self) -> _metadata_fb.TensorMetadataT:
+    """Creates the input tensor metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the input metadata.
+    """
+    tensor_metadata = _metadata_fb.TensorMetadataT()
+    tensor_metadata.name = self.name
+    tensor_metadata.description = self.description
+
+    # Create min and max values
+    stats = _metadata_fb.StatsT()
+    stats.max = self.max_values
+    stats.min = self.min_values
+    tensor_metadata.stats = stats
+
+    # Create content properties
+    content = _metadata_fb.ContentT()
+    if self.content_type is _metadata_fb.ContentProperties.FeatureProperties:
+      content.contentProperties = _metadata_fb.FeaturePropertiesT()
+    elif self.content_type is _metadata_fb.ContentProperties.ImageProperties:
+      content.contentProperties = _metadata_fb.ImagePropertiesT()
+    elif self.content_type is (
+        _metadata_fb.ContentProperties.BoundingBoxProperties):
+      content.contentProperties = _metadata_fb.BoundingBoxPropertiesT()
+    elif self.content_type is _metadata_fb.ContentProperties.AudioProperties:
+      content.contentProperties = _metadata_fb.AudioPropertiesT()
+
+    content.contentPropertiesType = self.content_type
+    tensor_metadata.content = content
+
+    # TODO(b/174091474): check if multiple label files have populated locale.
+    # Create associated files
+    if self.associated_files:
+      tensor_metadata.associatedFiles = [
+          file.create_metadata() for file in self.associated_files
+      ]
+    return tensor_metadata
+
+
+class InputImageTensorMd(TensorMd):
+  """A container for input image tensor metadata information.
+
+  Attributes:
+    norm_mean: the mean value used in tensor normalization [1].
+    norm_std: the std value used in the tensor normalization [1]. norm_mean and
+      norm_std must have the same dimension.
+    color_space_type: the color space type of the input image [2].
+    [1]:
+      https://www.tensorflow.org/lite/convert/metadata#normalization_and_quantization_parameters
+    [2]:
+      https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L172
+  """
+
+  # Min and max float values for image pixels.
+  _MIN_PIXEL = 0.0
+  _MAX_PIXEL = 255.0
+
+  def __init__(
+      self,
+      name: Optional[str] = None,
+      description: Optional[str] = None,
+      norm_mean: Optional[List[float]] = None,
+      norm_std: Optional[List[float]] = None,
+      color_space_type: Optional[
+          _metadata_fb.ColorSpaceType] = _metadata_fb.ColorSpaceType.UNKNOWN,
+      tensor_type: Optional[_schema_fb.TensorType] = None):
+    """Initializes the instance of InputImageTensorMd.
+
+    Args:
+      name: name of the tensor.
+      description: description of what the tensor is.
+      norm_mean: the mean value used in tensor normalization [1].
+      norm_std: the std value used in the tensor normalization [1]. norm_mean
+        and norm_std must have the same dimension.
+      color_space_type: the color space type of the input image [2].
+      tensor_type: data type of the tensor.
+      [1]:
+        https://www.tensorflow.org/lite/convert/metadata#normalization_and_quantization_parameters
+      [2]:
+      https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L172
+
+    Raises:
+      ValueError: if norm_mean and norm_std have different dimensions.
+    """
+    if norm_std and norm_mean and len(norm_std) != len(norm_mean):
+      raise ValueError(
+          f"norm_mean and norm_std are expected to be the same dim. But got "
+          f"{len(norm_mean)} and {len(norm_std)}")
+
+    if tensor_type is _schema_fb.TensorType.UINT8:
+      min_values = [_MIN_UINT8]
+      max_values = [_MAX_UINT8]
+    elif tensor_type is _schema_fb.TensorType.FLOAT32 and norm_std and norm_mean:
+      min_values = [
+          float(self._MIN_PIXEL - mean) / std
+          for mean, std in zip(norm_mean, norm_std)
+      ]
+      max_values = [
+          float(self._MAX_PIXEL - mean) / std
+          for mean, std in zip(norm_mean, norm_std)
+      ]
+    else:
+      # Uint8 and Float32 are the two major types currently. And Task library
+      # doesn't support other types so far.
+      min_values = None
+      max_values = None
+
+    super().__init__(name, description, min_values, max_values,
+                     _metadata_fb.ContentProperties.ImageProperties)
+    self.norm_mean = norm_mean
+    self.norm_std = norm_std
+    self.color_space_type = color_space_type
+
+  def create_metadata(self) -> _metadata_fb.TensorMetadataT:
+    """Creates the input image metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the input image metadata.
+    """
+    tensor_metadata = super().create_metadata()
+    tensor_metadata.content.contentProperties.colorSpace = self.color_space_type
+    # Create normalization parameters
+    if self.norm_mean and self.norm_std:
+      normalization = _metadata_fb.ProcessUnitT()
+      normalization.optionsType = (
+          _metadata_fb.ProcessUnitOptions.NormalizationOptions)
+      normalization.options = _metadata_fb.NormalizationOptionsT()
+      normalization.options.mean = self.norm_mean
+      normalization.options.std = self.norm_std
+      tensor_metadata.processUnits = [normalization]
+    return tensor_metadata
+
+
+class InputTextTensorMd(TensorMd):
+  """A container for the input text tensor metadata information.
+
+  Attributes:
+    tokenizer_md: information of the tokenizer in the input text tensor, if any.
+  """
+
+  def __init__(self,
+               name: Optional[str] = None,
+               description: Optional[str] = None,
+               tokenizer_md: Optional[RegexTokenizerMd] = None):
+    """Initializes the instance of InputTextTensorMd.
+
+    Args:
+      name: name of the tensor.
+      description: description of what the tensor is.
+      tokenizer_md: information of the tokenizer in the input text tensor, if
+        any. Only `RegexTokenizer` [1] is currenly supported. If the tokenizer
+        is `BertTokenizer` [2] or `SentencePieceTokenizer` [3], refer to
+        `bert_nl_classifier.MetadataWriter`.
+        [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L475
+        [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L436
+        [3]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L473
+    """
+    super().__init__(name, description)
+    self.tokenizer_md = tokenizer_md
+
+  def create_metadata(self) -> _metadata_fb.TensorMetadataT:
+    """Creates the input text metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the input text metadata.
+
+    Raises:
+      ValueError: if the type of tokenizer_md is unsupported.
+    """
+    if not isinstance(self.tokenizer_md, (type(None), RegexTokenizerMd)):
+      raise ValueError(
+          f"The type of tokenizer_options, {type(self.tokenizer_md)}, is "
+          f"unsupported")
+
+    tensor_metadata = super().create_metadata()
+    if self.tokenizer_md:
+      tensor_metadata.processUnits = [self.tokenizer_md.create_metadata()]
+    return tensor_metadata
+
+
+class InputAudioTensorMd(TensorMd):
+  """A container for the input audio tensor metadata information.
+
+  Attributes:
+    sample_rate: the sample rate in Hz when the audio was captured.
+    channels: the channel count of the audio.
+  """
+
+  def __init__(self,
+               name: Optional[str] = None,
+               description: Optional[str] = None,
+               sample_rate: int = 0,
+               channels: int = 0):
+    """Initializes the instance of InputAudioTensorMd.
+
+    Args:
+      name: name of the tensor.
+      description: description of what the tensor is.
+      sample_rate: the sample rate in Hz when the audio was captured.
+      channels: the channel count of the audio.
+    """
+    super().__init__(
+        name,
+        description,
+        content_type=_metadata_fb.ContentProperties.AudioProperties)
+
+    self.sample_rate = sample_rate
+    self.channels = channels
+
+  def create_metadata(self) -> _metadata_fb.TensorMetadataT:
+    """Creates the input audio metadata based on the information.
+
+    Returns:
+      A Flatbuffers Python object of the input audio metadata.
+
+    Raises:
+      ValueError: if any value of sample_rate, channels is negative.
+    """
+    # 0 is the default value in Flatbuffers.
+    if self.sample_rate < 0:
+      raise ValueError(
+          f"sample_rate should be non-negative, but got {self.sample_rate}.")
+
+    if self.channels < 0:
+      raise ValueError(
+          f"channels should be non-negative, but got {self.channels}.")
+
+    tensor_metadata = super().create_metadata()
+    properties = tensor_metadata.content.contentProperties
+    properties.sampleRate = self.sample_rate
+    properties.channels = self.channels
+
+    return tensor_metadata
+
+
+class ClassificationTensorMd(TensorMd):
+  """A container for the classification tensor metadata information.
+
+  Attributes:
+    label_files: information of the label files [1] in the classification
+      tensor.
+    score_calibration_md: information of the score calibration operation [2] in
+      the classification tensor.
+    [1]:
+      https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L95
+    [2]:
+      https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L434
+  """
+
+  # Min and max float values for classification results.
+  _MIN_FLOAT = 0.0
+  _MAX_FLOAT = 1.0
+
+  def __init__(self,
+               name: Optional[str] = None,
+               description: Optional[str] = None,
+               label_files: Optional[List[LabelFileMd]] = None,
+               tensor_type: Optional[_schema_fb.TensorType] = None,
+               score_calibration_md: Optional[ScoreCalibrationMd] = None,
+               tensor_name: Optional[str] = None):
+    """Initializes the instance of ClassificationTensorMd.
+
+    Args:
+      name: name of the tensor.
+      description: description of what the tensor is.
+      label_files: information of the label files [1] in the classification
+        tensor.
+      tensor_type: data type of the tensor.
+      score_calibration_md: information of the score calibration files operation
+        [2] in the classification tensor.
+      tensor_name: name of the corresponding tensor [3] in the TFLite model. It
+        is used to locate the corresponding classification tensor and decide the
+        order of the tensor metadata [4] when populating model metadata.
+      [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L95
+      [2]:
+        https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L434
+      [3]:
+        https://github.com/tensorflow/tensorflow/blob/cb67fef35567298b40ac166b0581cd8ad68e5a3a/tensorflow/lite/schema/schema.fbs#L1129-L1136
+      [4]:
+        https://github.com/tensorflow/tflite-support/blob/b2a509716a2d71dfff706468680a729cc1604cff/tensorflow_lite_support/metadata/metadata_schema.fbs#L595-L612
+    """
+    self.score_calibration_md = score_calibration_md
+
+    if tensor_type is _schema_fb.TensorType.UINT8:
+      min_values = [_MIN_UINT8]
+      max_values = [_MAX_UINT8]
+    elif tensor_type is _schema_fb.TensorType.FLOAT32:
+      min_values = [self._MIN_FLOAT]
+      max_values = [self._MAX_FLOAT]
+    else:
+      # Uint8 and Float32 are the two major types currently. And Task library
+      # doesn't support other types so far.
+      min_values = None
+      max_values = None
+
+    associated_files = label_files or []
+    if self.score_calibration_md:
+      associated_files.append(
+          score_calibration_md.create_score_calibration_file_md())
+
+    super().__init__(name, description, min_values, max_values,
+                     _metadata_fb.ContentProperties.FeatureProperties,
+                     associated_files, tensor_name)
+
+  def create_metadata(self) -> _metadata_fb.TensorMetadataT:
+    """Creates the classification tensor metadata based on the information."""
+    tensor_metadata = super().create_metadata()
+    if self.score_calibration_md:
+      tensor_metadata.processUnits = [
+          self.score_calibration_md.create_metadata()
+      ]
+    return tensor_metadata
+
+
+class CategoryTensorMd(TensorMd):
+  """A container for the category tensor metadata information."""
+
+  def __init__(self,
+               name: Optional[str] = None,
+               description: Optional[str] = None,
+               label_files: Optional[List[LabelFileMd]] = None):
+    """Initializes a CategoryTensorMd object.
+
+    Args:
+      name: name of the tensor.
+      description: description of what the tensor is.
+      label_files: information of the label files [1] in the category tensor.
+      [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L108
+    """
+    # In category tensors, label files are in the type of TENSOR_VALUE_LABELS.
+    value_label_files = label_files
+    if value_label_files:
+      for file in value_label_files:
+        file.file_type = _metadata_fb.AssociatedFileType.TENSOR_VALUE_LABELS
+
+    super().__init__(
+        name=name, description=description, associated_files=value_label_files)
+
+
+class BertInputTensorsMd:
+  """A container for the input tensor metadata information of Bert models."""
+
+  _IDS_NAME = "ids"
+  _IDS_DESCRIPTION = "Tokenized ids of the input text."
+  _MASK_NAME = "mask"
+  _MASK_DESCRIPTION = ("Mask with 1 for real tokens and 0 for padding "
+                       "tokens.")
+  _SEGMENT_IDS_NAME = "segment_ids"
+  _SEGMENT_IDS_DESCRIPTION = (
+      "0 for the first sequence, 1 for the second sequence if exists.")
+
+  def __init__(self,
+               model_buffer: bytearray,
+               ids_name: str,
+               mask_name: str,
+               segment_name: str,
+               ids_md: Optional[TensorMd] = None,
+               mask_md: Optional[TensorMd] = None,
+               segment_ids_md: Optional[TensorMd] = None,
+               tokenizer_md: Union[None, BertTokenizerMd,
+                                   SentencePieceTokenizerMd] = None):
+    """Initializes a BertInputTensorsMd object.
+
+    `ids_name`, `mask_name`, and `segment_name` correspond to the `Tensor.name`
+    in the TFLite schema, which help to determine the tensor order when
+    populating metadata.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      ids_name: name of the ids tensor, which represents the tokenized ids of
+        the input text.
+      mask_name: name of the mask tensor, which represents the mask with 1 for
+        real tokens and 0 for padding tokens.
+      segment_name: name of the segment ids tensor, where `0` stands for the
+        first sequence, and `1` stands for the second sequence if exists.
+      ids_md: input ids tensor informaton.
+      mask_md: input mask tensor informaton.
+      segment_ids_md: input segment tensor informaton.
+      tokenizer_md: information of the tokenizer used to process the input
+        string, if any. Supported tokenziers are: `BertTokenizer` [1] and
+          `SentencePieceTokenizer` [2]. If the tokenizer is `RegexTokenizer`
+          [3], refer to `nl_classifier.MetadataWriter`.
+        [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L436
+        [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L473
+        [3]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L475
+    """
+
+    self._input_names = [ids_name, mask_name, segment_name]
+
+    # Get the input tensor names in order from the model. Later, we need to
+    # order the input metadata according to this tensor order.
+    self._ordered_input_names = writer_utils.get_input_tensor_names(
+        model_buffer)
+
+    # Verify that self._ordered_input_names (read from the model) and
+    # self._input_name (collected from users) are aligned.
+    if collections.Counter(self._ordered_input_names) != collections.Counter(
+        self._input_names):
+      raise ValueError(
+          f"The input tensor names ({self._ordered_input_names}) do not match "
+          f"the tensor names read from the model ({self._input_names}).")
+
+    if ids_md is None:
+      ids_md = TensorMd(name=self._IDS_NAME, description=self._IDS_DESCRIPTION)
+
+    if mask_md is None:
+      mask_md = TensorMd(
+          name=self._MASK_NAME, description=self._MASK_DESCRIPTION)
+
+    if segment_ids_md is None:
+      segment_ids_md = TensorMd(
+          name=self._SEGMENT_IDS_NAME,
+          description=self._SEGMENT_IDS_DESCRIPTION)
+
+    # The order of self._input_md matches the order of self._input_names.
+    self._input_md = [ids_md, mask_md, segment_ids_md]
+
+    if not isinstance(tokenizer_md,
+                      (type(None), BertTokenizerMd, SentencePieceTokenizerMd)):
+      raise ValueError(
+          f"The type of tokenizer_options, {type(tokenizer_md)}, is unsupported"
+      )
+
+    self._tokenizer_md = tokenizer_md
+
+  def create_input_tesnor_metadata(self) -> List[_metadata_fb.TensorMetadataT]:
+    """Creates the input metadata for the three input tesnors."""
+    # The order of the three input tensors may vary with each model conversion.
+    # We need to order the input metadata according to the tensor order in the
+    # model.
+    ordered_metadata = []
+    name_md_dict = dict(zip(self._input_names, self._input_md))
+    for name in self._ordered_input_names:
+      ordered_metadata.append(name_md_dict[name].create_metadata())
+    return ordered_metadata
+
+  def create_input_process_unit_metadata(
+      self) -> List[_metadata_fb.ProcessUnitT]:
+    """Creates the input process unit metadata."""
+    if self._tokenizer_md:
+      return [self._tokenizer_md.create_metadata()]
+    else:
+      return []
+
+  def get_tokenizer_associated_files(self) -> List[str]:
+    """Gets the associated files that are packed in the tokenizer."""
+    if self._tokenizer_md:
+      return writer_utils.get_tokenizer_associated_files(
+          self._tokenizer_md.create_metadata().options)
+    else:
+      return []
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/metadata_writer.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/metadata_writer.py
new file mode 100644
index 0000000..702a254
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/metadata_writer.py
@@ -0,0 +1,239 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Helper class to write metadata into TFLite models."""
+
+import collections
+from typing import List, Optional, Type
+
+import flatbuffers
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+
+class MetadataWriter:
+  """Writes the metadata and associated files into a TFLite model."""
+
+  def __init__(self,
+               model_buffer: bytearray,
+               metadata_buffer: Optional[bytearray] = None,
+               associated_files: Optional[List[str]] = None):
+    """Constructs the MetadataWriter.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      metadata_buffer: valid buffer of the metadata.
+      associated_files: path to the associated files to be populated.
+    """
+    self._model_buffer = model_buffer
+    self._metadata_buffer = metadata_buffer
+    self._associated_files = associated_files if associated_files else []
+    self._populated_model_buffer = None
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[List[Type[metadata_info.TensorMd]]] = None,
+      output_md: Optional[List[Type[metadata_info.TensorMd]]] = None,
+      associated_files: Optional[List[str]] = None):
+    """Creates MetadataWriter based on the metadata information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model.
+      input_md: metadata information of the input tensors.
+      output_md: metadata information of the output tensors.
+      associated_files: path to the associated files to be populated.
+
+    Returns:
+      A MetadataWriter Object.
+
+    Raises:
+      ValueError: if the tensor names from `input_md` and `output_md` do not
+      match the tensor names read from the model.
+    """
+
+    if general_md is None:
+      general_md = metadata_info.GeneralMd()
+    if input_md is None:
+      input_md = []
+    if output_md is None:
+      output_md = []
+
+    # Order the input/output metadata according to tensor orders from the model.
+    input_md = _order_tensor_metadata(
+        input_md, writer_utils.get_input_tensor_names(model_buffer))
+    output_md = _order_tensor_metadata(
+        output_md, writer_utils.get_output_tensor_names(model_buffer))
+
+    model_metadata = general_md.create_metadata()
+    input_metadata = [m.create_metadata() for m in input_md]
+    output_metadata = [m.create_metadata() for m in output_md]
+    return cls.create_from_metadata(model_buffer, model_metadata,
+                                    input_metadata, output_metadata,
+                                    associated_files)
+
+  @classmethod
+  def create_from_metadata(
+      cls,
+      model_buffer: bytearray,
+      model_metadata: Optional[_metadata_fb.ModelMetadataT] = None,
+      input_metadata: Optional[List[_metadata_fb.TensorMetadataT]] = None,
+      output_metadata: Optional[List[_metadata_fb.TensorMetadataT]] = None,
+      associated_files: Optional[List[str]] = None,
+      input_process_units: Optional[List[_metadata_fb.ProcessUnitT]] = None,
+      output_process_units: Optional[List[_metadata_fb.ProcessUnitT]] = None):
+    """Creates MetadataWriter based on the metadata Flatbuffers Python Objects.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      model_metadata: general model metadata [1]. The subgraph_metadata will be
+        refreshed with input_metadata and output_metadata.
+      input_metadata: a list of metadata of the input tensors [2].
+      output_metadata: a list of metadata of the output tensors [3].
+      associated_files: path to the associated files to be populated.
+      input_process_units: a lits of metadata of the input process units [4].
+      output_process_units: a lits of metadata of the output process units [5].
+      [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L640-L681
+      [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L590
+      [3]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L599
+      [4]:
+        https://github.com/tensorflow/tflite-support/blob/b5cc57c74f7990d8bc055795dfe8d50267064a57/tensorflow_lite_support/metadata/metadata_schema.fbs#L646
+      [5]:
+        https://github.com/tensorflow/tflite-support/blob/b5cc57c74f7990d8bc055795dfe8d50267064a57/tensorflow_lite_support/metadata/metadata_schema.fbs#L650
+    Returns:
+      A MetadataWriter Object.
+    """
+    # Create empty tensor metadata when input_metadata/output_metadata are None
+    # to bypass MetadataPopulator verification.
+    if not input_metadata:
+      model = _schema_fb.Model.GetRootAsModel(model_buffer, 0)
+      num_input_tensors = model.Subgraphs(0).InputsLength()
+      input_metadata = [
+          _metadata_fb.TensorMetadataT() for i in range(num_input_tensors)
+      ]
+
+    if not output_metadata:
+      model = _schema_fb.Model.GetRootAsModel(model_buffer, 0)
+      num_output_tensors = model.Subgraphs(0).OutputsLength()
+      output_metadata = [
+          _metadata_fb.TensorMetadataT() for i in range(num_output_tensors)
+      ]
+
+    _fill_default_tensor_names(
+        input_metadata, writer_utils.get_input_tensor_names(model_buffer))
+
+    _fill_default_tensor_names(
+        output_metadata, writer_utils.get_output_tensor_names(model_buffer))
+
+    subgraph_metadata = _metadata_fb.SubGraphMetadataT()
+    subgraph_metadata.inputTensorMetadata = input_metadata
+    subgraph_metadata.outputTensorMetadata = output_metadata
+    subgraph_metadata.inputProcessUnits = input_process_units
+    subgraph_metadata.outputProcessUnits = output_process_units
+
+    if model_metadata is None:
+      model_metadata = _metadata_fb.ModelMetadataT()
+    model_metadata.subgraphMetadata = [subgraph_metadata]
+
+    b = flatbuffers.Builder(0)
+    b.Finish(
+        model_metadata.Pack(b),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    return cls(model_buffer, b.Output(), associated_files)
+
+  def populate(self) -> bytearray:
+    """Populates the metadata and label file to the model file.
+
+    Returns:
+      A new model buffer with the metadata and associated files.
+    """
+    if self._populated_model_buffer:
+      return self._populated_model_buffer
+
+    populator = _metadata.MetadataPopulator.with_model_buffer(
+        self._model_buffer)
+    if self._model_buffer is not None:
+      populator.load_metadata_buffer(self._metadata_buffer)
+    if self._associated_files:
+      populator.load_associated_files(self._associated_files)
+    populator.populate()
+    self._populated_model_buffer = populator.get_model_buffer()
+    return self._populated_model_buffer
+
+  def get_metadata_json(self) -> str:
+    """Gets the generated JSON metadata string before populated into model.
+
+    This method returns the metadata buffer before populated into the model.
+    More fields could be filled by MetadataPopulator, such as
+    min_parser_version. Use get_populated_metadata_json() if you want to get the
+    final metadata string.
+
+    Returns:
+      The generated JSON metadata string before populated into model.
+    """
+    return _metadata.convert_to_json(bytes(self._metadata_buffer))
+
+  def get_populated_metadata_json(self) -> str:
+    """Gets the generated JSON metadata string after populated into model.
+
+    More fields could be filled by MetadataPopulator, such as
+    min_parser_version. Use get_metadata_json() if you want to get the
+    original metadata string.
+
+    Returns:
+      The generated JSON metadata string after populated into model.
+    """
+    displayer = _metadata.MetadataDisplayer.with_model_buffer(self.populate())
+    return displayer.get_metadata_json()
+
+
+# If tensor name in metadata is empty, default to the tensor name saved in
+# the model.
+def _fill_default_tensor_names(
+    tensor_metadata: List[_metadata_fb.TensorMetadataT],
+    tensor_names_from_model: List[str]):
+  for metadata, name in zip(tensor_metadata, tensor_names_from_model):
+    metadata.name = metadata.name or name
+
+
+def _order_tensor_metadata(
+    tensor_md: List[Type[metadata_info.TensorMd]],
+    tensor_names_from_model: List[str]) -> List[Type[metadata_info.TensorMd]]:
+  """Orders tensor_md according to the tensor names from the model."""
+  tensor_names_from_arg = [
+      md.tensor_name for md in tensor_md or [] if md.tensor_name is not None
+  ]
+  if not tensor_names_from_arg:
+    return tensor_md
+
+  if collections.Counter(tensor_names_from_arg) != collections.Counter(
+      tensor_names_from_model):
+    raise ValueError(
+        "The tensor names from arguments ({}) do not match the tensor names"
+        " read from the model ({}).".format(tensor_names_from_arg,
+                                            tensor_names_from_model))
+  ordered_tensor_md = []
+  name_md_dict = dict(zip(tensor_names_from_arg, tensor_md))
+  for name in tensor_names_from_model:
+    ordered_tensor_md.append(name_md_dict[name])
+  return ordered_tensor_md
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/nl_classifier.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/nl_classifier.py
new file mode 100644
index 0000000..a20d1fd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/nl_classifier.py
@@ -0,0 +1,134 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Writes metadata and label file to the NL classifier models."""
+
+from typing import List, Optional
+
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+_MODEL_NAME = "NLClassifier"
+_MODEL_DESCRIPTION = ("Classify the input text into a set of known categories.")
+_INPUT_NAME = "input_text"
+_INPUT_DESCRIPTION = ("Embedding vectors representing the input text to be "
+                      "classified.")
+_OUTPUT_NAME = "probability"
+_OUTPUT_DESCRIPTION = "Probabilities of the labels respectively."
+
+
+class MetadataWriter(metadata_writer.MetadataWriter):
+  """Writes metadata into the NL classifier."""
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.InputTextTensorMd] = None,
+      output_md: Optional[metadata_info.ClassificationTensorMd] = None):
+    """Creates MetadataWriter based on general/input/output information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model. If not specified, default
+        general metadata will be generated.
+      input_md: input text tensor information, if not specified, default input
+        metadata will be generated.
+      output_md: output classification tensor information, if not specified,
+        default output metadata will be generated.
+
+    Returns:
+      A MetadataWriter object.
+    """
+
+    if general_md is None:
+      general_md = metadata_info.GeneralMd(
+          name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
+
+    if input_md is None:
+      input_md = metadata_info.InputTextTensorMd(
+          name=_INPUT_NAME, description=_INPUT_DESCRIPTION)
+
+    if output_md is None:
+      output_md = metadata_info.ClassificationTensorMd(
+          name=_OUTPUT_NAME, description=_OUTPUT_DESCRIPTION)
+
+    if output_md.associated_files is None:
+      output_md.associated_files = []
+
+    tokenizer_files = []
+    if input_md.tokenizer_md:
+      tokenizer_files = writer_utils.get_tokenizer_associated_files(
+          input_md.tokenizer_md.create_metadata().options)
+
+    return super().create_from_metadata_info(
+        model_buffer=model_buffer,
+        general_md=general_md,
+        input_md=[input_md],
+        output_md=[output_md],
+        associated_files=[
+            file.file_path for file in output_md.associated_files
+        ] + tokenizer_files)
+
+  @classmethod
+  def create_for_inference(
+      cls, model_buffer: bytearray,
+      tokenizer_md: Optional[metadata_info.RegexTokenizerMd],
+      label_file_paths: List[str]):
+    """Creates mandatory metadata for TFLite Support inference.
+
+    The parameters required in this method are mandatory when using TFLite
+    Support features, such as Task library and Codegen tool (Android Studio ML
+    Binding). Other metadata fields will be set to default. If other fields need
+    to be filled, use the method `create_from_metadata_info` to edit them.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      tokenizer_md: information of the tokenizer used to process the input
+        string, if any. Only `RegexTokenizer` [1] is currently supported. If the
+        tokenizer is `BertTokenizer` [2] or `SentencePieceTokenizer` [3], refer
+        to `bert_nl_classifier.MetadataWriter`.
+        [1]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L475
+        [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L436
+        [3]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L473
+      label_file_paths: paths to the label files [4] in the classification
+        tensor. Pass in an empty list if the model does not have any label
+        file.
+        [4]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L95
+
+    Returns:
+      A MetadataWriter object.
+    """
+    input_md = metadata_info.InputTextTensorMd(
+        name=_INPUT_NAME,
+        description=_INPUT_DESCRIPTION,
+        tokenizer_md=tokenizer_md)
+
+    output_md = metadata_info.ClassificationTensorMd(
+        name=_OUTPUT_NAME,
+        description=_OUTPUT_DESCRIPTION,
+        label_files=[
+            metadata_info.LabelFileMd(file_path=file_path)
+            for file_path in label_file_paths
+        ],
+        tensor_type=writer_utils.get_output_tensor_types(model_buffer)[0])
+
+    return cls.create_from_metadata_info(
+        model_buffer, input_md=input_md, output_md=output_md)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/object_detector.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/object_detector.py
new file mode 100644
index 0000000..3caf063
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/object_detector.py
@@ -0,0 +1,295 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Writes metadata and label file to the object detector models."""
+
+import logging
+from typing import List, Optional, Type, Union
+
+import flatbuffers
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+
+_MODEL_NAME = "ObjectDetector"
+_MODEL_DESCRIPTION = (
+    "Identify which of a known set of objects might be present and provide "
+    "information about their positions within the given image or a video "
+    "stream.")
+_INPUT_NAME = "image"
+_INPUT_DESCRIPTION = "Input image to be detected."
+# The output tensor names shouldn't be changed since these name will be used
+# to handle the order of output in TFLite Task Library when doing inference
+# in on-device application.
+_OUTPUT_LOCATION_NAME = "location"
+_OUTPUT_LOCATION_DESCRIPTION = "The locations of the detected boxes."
+_OUTPUT_CATRGORY_NAME = "category"
+_OUTPUT_CATEGORY_DESCRIPTION = "The categories of the detected boxes."
+_OUTPUT_SCORE_NAME = "score"
+_OUTPUT_SCORE_DESCRIPTION = "The scores of the detected boxes."
+_OUTPUT_NUMBER_NAME = "number of detections"
+_OUTPUT_NUMBER_DESCRIPTION = "The number of the detected boxes."
+_CONTENT_VALUE_DIM = 2
+_BOUNDING_BOX_INDEX = (1, 0, 3, 2)
+_GROUP_NAME = "detection_result"
+
+
+def _create_1d_value_range(dim: int) -> _metadata_fb.ValueRangeT:
+  """Creates the 1d ValueRange based on the given dimension."""
+  value_range = _metadata_fb.ValueRangeT()
+  value_range.min = dim
+  value_range.max = dim
+  return value_range
+
+
+def _create_location_metadata(
+    location_md: metadata_info.TensorMd) -> _metadata_fb.TensorMetadataT:
+  """Creates the metadata for the location tensor."""
+  location_metadata = location_md.create_metadata()
+  content = _metadata_fb.ContentT()
+  content.contentPropertiesType = (
+      _metadata_fb.ContentProperties.BoundingBoxProperties)
+  properties = _metadata_fb.BoundingBoxPropertiesT()
+  properties.index = list(_BOUNDING_BOX_INDEX)
+  properties.type = _metadata_fb.BoundingBoxType.BOUNDARIES
+  properties.coordinateType = _metadata_fb.CoordinateType.RATIO
+  content.contentProperties = properties
+  content.range = _create_1d_value_range(_CONTENT_VALUE_DIM)
+  location_metadata.content = content
+  return location_metadata
+
+
+# This is needed for both the output category tensor and the score tensor.
+def _create_metadata_with_value_range(
+    tensor_md: metadata_info.TensorMd) -> _metadata_fb.TensorMetadataT:
+  """Creates tensor metadata with extra value range information."""
+  tensor_metadata = tensor_md.create_metadata()
+  tensor_metadata.content.range = _create_1d_value_range(_CONTENT_VALUE_DIM)
+  return tensor_metadata
+
+
+def _get_tflite_outputs(model_buffer: bytearray) -> List[int]:
+  """Gets the tensor indices of output in the TFLite Subgraph."""
+  model = _schema_fb.Model.GetRootAsModel(model_buffer, 0)
+  return model.Subgraphs(0).OutputsAsNumpy()
+
+
+def _extend_new_files(
+    file_list: List[str],
+    associated_files: Optional[List[Type[metadata_info.AssociatedFileMd]]]):
+  """Extends new associated files to the file list."""
+  if not associated_files:
+    return
+
+  for file in associated_files:
+    if file.file_path not in file_list:
+      file_list.append(file.file_path)
+
+
+class MetadataWriter(metadata_writer.MetadataWriter):
+  """Writes metadata into an object detector."""
+
+  @classmethod
+  def create_from_metadata_info(
+      cls,
+      model_buffer: bytearray,
+      general_md: Optional[metadata_info.GeneralMd] = None,
+      input_md: Optional[metadata_info.InputImageTensorMd] = None,
+      output_location_md: Optional[metadata_info.TensorMd] = None,
+      output_category_md: Optional[metadata_info.CategoryTensorMd] = None,
+      output_score_md: Union[None, metadata_info.TensorMd,
+                             metadata_info.ClassificationTensorMd] = None,
+      output_number_md: Optional[metadata_info.TensorMd] = None):
+    """Creates MetadataWriter based on general/input/outputs information.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      general_md: general information about the model.
+      input_md: input image tensor informaton.
+      output_location_md: output location tensor informaton. The location tensor
+        is a multidimensional array of [N][4] floating point values between 0
+        and 1, the inner arrays representing bounding boxes in the form [top,
+        left, bottom, right].
+      output_category_md: output category tensor information. The category
+        tensor is an array of N integers (output as floating point values) each
+        indicating the index of a class label from the labels file.
+      output_score_md: output score tensor information. The score tensor is an
+        array of N floating point values between 0 and 1 representing
+        probability that a class was detected. Use ClassificationTensorMd to
+        calibrate score.
+      output_number_md: output number of detections tensor information. This
+        tensor is an integer value of N.
+
+    Returns:
+      A MetadataWriter object.
+    """
+    if general_md is None:
+      general_md = metadata_info.GeneralMd(
+          name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
+
+    if input_md is None:
+      input_md = metadata_info.InputImageTensorMd(
+          name=_INPUT_NAME,
+          description=_INPUT_DESCRIPTION,
+          color_space_type=_metadata_fb.ColorSpaceType.RGB)
+
+    warn_message_format = (
+        "The output name isn't the default string \"%s\". This may cause the "
+        "model not work in the TFLite Task Library since the tensor name will "
+        "be used to handle the output order in the TFLite Task Library.")
+    if output_location_md is None:
+      output_location_md = metadata_info.TensorMd(
+          name=_OUTPUT_LOCATION_NAME, description=_OUTPUT_LOCATION_DESCRIPTION)
+    elif output_location_md.name != _OUTPUT_LOCATION_NAME:
+      logging.warning(warn_message_format, _OUTPUT_LOCATION_NAME)
+
+    if output_category_md is None:
+      output_category_md = metadata_info.CategoryTensorMd(
+          name=_OUTPUT_CATRGORY_NAME, description=_OUTPUT_CATEGORY_DESCRIPTION)
+    elif output_category_md.name != _OUTPUT_CATRGORY_NAME:
+      logging.warning(warn_message_format, _OUTPUT_CATRGORY_NAME)
+
+    if output_score_md is None:
+      output_score_md = metadata_info.ClassificationTensorMd(
+          name=_OUTPUT_SCORE_NAME,
+          description=_OUTPUT_SCORE_DESCRIPTION,
+      )
+    elif output_score_md.name != _OUTPUT_SCORE_NAME:
+      logging.warning(warn_message_format, _OUTPUT_SCORE_NAME)
+
+    if output_number_md is None:
+      output_number_md = metadata_info.TensorMd(
+          name=_OUTPUT_NUMBER_NAME, description=_OUTPUT_NUMBER_DESCRIPTION)
+    elif output_number_md.name != _OUTPUT_NUMBER_NAME:
+      logging.warning(warn_message_format, _OUTPUT_NUMBER_NAME)
+
+    # Create output tensor group info.
+    group = _metadata_fb.TensorGroupT()
+    group.name = _GROUP_NAME
+    group.tensorNames = [
+        output_location_md.name, output_category_md.name, output_score_md.name
+    ]
+
+    # Gets the tensor inidces of tflite outputs and then gets the order of the
+    # output metadata by the value of tensor indices. For instance, if the
+    # output indices are [601, 599, 598, 600], tensor names and indices aligned
+    # are:
+    #   - location: 598
+    #   - category: 599
+    #   - score: 600
+    #   - number of detections: 601
+    # because of the op's ports of TFLITE_DETECTION_POST_PROCESS
+    # (https://github.com/tensorflow/tensorflow/blob/a4fe268ea084e7d323133ed7b986e0ae259a2bc7/tensorflow/lite/kernels/detection_postprocess.cc#L47-L50).
+    # Thus, the metadata of tensors are sorted in this way, according to
+    # output_tensor_indicies correctly.
+    output_tensor_indices = _get_tflite_outputs(model_buffer)
+    metadata_list = [
+        _create_location_metadata(output_location_md),
+        _create_metadata_with_value_range(output_category_md),
+        _create_metadata_with_value_range(output_score_md),
+        output_number_md.create_metadata()
+    ]
+
+    # Align indices with tensors.
+    sorted_indices = sorted(output_tensor_indices)
+    indices_to_tensors = dict(zip(sorted_indices, metadata_list))
+
+    # Output metadata according to output_tensor_indices.
+    output_metadata = [indices_to_tensors[i] for i in output_tensor_indices]
+
+    # Create subgraph info.
+    subgraph_metadata = _metadata_fb.SubGraphMetadataT()
+    subgraph_metadata.inputTensorMetadata = [input_md.create_metadata()]
+    subgraph_metadata.outputTensorMetadata = output_metadata
+    subgraph_metadata.outputTensorGroups = [group]
+
+    # Create model metadata
+    model_metadata = general_md.create_metadata()
+    model_metadata.subgraphMetadata = [subgraph_metadata]
+
+    b = flatbuffers.Builder(0)
+    b.Finish(
+        model_metadata.Pack(b),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+
+    associated_files = []
+    _extend_new_files(associated_files, output_category_md.associated_files)
+    _extend_new_files(associated_files, output_score_md.associated_files)
+    return cls(model_buffer, b.Output(), associated_files=associated_files)
+
+  @classmethod
+  def create_for_inference(
+      cls,
+      model_buffer: bytearray,
+      input_norm_mean: List[float],
+      input_norm_std: List[float],
+      label_file_paths: List[str],
+      score_calibration_md: Optional[metadata_info.ScoreCalibrationMd] = None):
+    """Creates mandatory metadata for TFLite Support inference.
+
+    The parameters required in this method are mandatory when using TFLite
+    Support features, such as Task library and Codegen tool (Android Studio ML
+    Binding). Other metadata fields will be set to default. If other fields need
+    to be filled, use the method `create_from_metadata_info` to edit them.
+
+    Args:
+      model_buffer: valid buffer of the model file.
+      input_norm_mean: the mean value used in the input tensor normalization
+        [1].
+      input_norm_std: the std value used in the input tensor normalizarion [1].
+      label_file_paths: paths to the label files [2] in the category tensor.
+        Pass in an empty list, If the model does not have any label file.
+      score_calibration_md: information of the score calibration operation [3]
+        in the classification tensor. Optional if the model does not use score
+        calibration.
+      [1]:
+        https://www.tensorflow.org/lite/convert/metadata#normalization_and_quantization_parameters
+      [2]:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L108
+      [3]:
+        https://github.com/tensorflow/tflite-support/blob/5e0cdf5460788c481f5cd18aab8728ec36cf9733/tensorflow_lite_support/metadata/metadata_schema.fbs#L434
+
+    Returns:
+      A MetadataWriter object.
+    """
+    input_md = metadata_info.InputImageTensorMd(
+        name=_INPUT_NAME,
+        description=_INPUT_DESCRIPTION,
+        norm_mean=input_norm_mean,
+        norm_std=input_norm_std,
+        color_space_type=_metadata_fb.ColorSpaceType.RGB,
+        tensor_type=writer_utils.get_input_tensor_types(model_buffer)[0])
+
+    output_category_md = metadata_info.CategoryTensorMd(
+        name=_OUTPUT_CATRGORY_NAME,
+        description=_OUTPUT_CATEGORY_DESCRIPTION,
+        label_files=[
+            metadata_info.LabelFileMd(file_path=file_path)
+            for file_path in label_file_paths
+        ])
+
+    output_score_md = metadata_info.ClassificationTensorMd(
+        name=_OUTPUT_SCORE_NAME,
+        description=_OUTPUT_SCORE_DESCRIPTION,
+        score_calibration_md=score_calibration_md
+    )
+
+    return cls.create_from_metadata_info(
+        model_buffer,
+        input_md=input_md,
+        output_category_md=output_category_md,
+        output_score_md=output_score_md)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/writer_utils.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/writer_utils.py
new file mode 100644
index 0000000..a8815fb
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/writer_utils.py
@@ -0,0 +1,182 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Helper methods for writing metadata into TFLite models."""
+
+import array
+import functools
+from typing import List, Union, Optional
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+
+
+def compute_flat_size(tensor_shape: Optional["array.array[int]"]) -> int:
+  """Computes the flat size (number of elements) of tensor shape.
+
+  Args:
+    tensor_shape: an array of the tensor shape values.
+
+  Returns:
+    The flat size of the tensor shape. Return 0 if tensor_shape is None.
+  """
+  if not tensor_shape:
+    return 0
+  return functools.reduce(lambda x, y: x * y, tensor_shape)
+
+
+def get_input_tensor_names(model_buffer: bytearray) -> List[str]:
+  """Gets a list of the input tensor names."""
+  subgraph = _get_subgraph(model_buffer)
+  tensor_names = []
+  for i in range(subgraph.InputsLength()):
+    index = subgraph.Inputs(i)
+    tensor_names.append(subgraph.Tensors(index).Name().decode("utf-8"))
+  return tensor_names
+
+
+def get_output_tensor_names(model_buffer: bytearray) -> List[str]:
+  """Gets a list of the output tensor names."""
+  subgraph = _get_subgraph(model_buffer)
+  tensor_names = []
+  for i in range(subgraph.OutputsLength()):
+    index = subgraph.Outputs(i)
+    tensor_names.append(subgraph.Tensors(index).Name().decode("utf-8"))
+  return tensor_names
+
+
+def get_input_tensor_types(
+    model_buffer: bytearray) -> List[_schema_fb.TensorType]:
+  """Gets a list of the input tensor types."""
+  subgraph = _get_subgraph(model_buffer)
+  tensor_types = []
+  for i in range(subgraph.InputsLength()):
+    index = subgraph.Inputs(i)
+    tensor_types.append(subgraph.Tensors(index).Type())
+  return tensor_types
+
+
+def get_output_tensor_types(
+    model_buffer: bytearray) -> List[_schema_fb.TensorType]:
+  """Gets a list of the output tensor types."""
+  subgraph = _get_subgraph(model_buffer)
+  tensor_types = []
+  for i in range(subgraph.OutputsLength()):
+    index = subgraph.Outputs(i)
+    tensor_types.append(subgraph.Tensors(index).Type())
+  return tensor_types
+
+
+def get_input_tensor_shape(model_buffer: bytearray,
+                           tensor_index: int) -> array.array:
+  """Gets the shape of the specified input tensor."""
+  subgraph = _get_subgraph(model_buffer)
+  return subgraph.Tensors(subgraph.Inputs(tensor_index)).ShapeAsNumpy()
+
+
+def load_file(file_path: str, mode: str = "rb") -> Union[str, bytes]:
+  """Loads file from the file path.
+
+  Args:
+    file_path: valid file path string.
+    mode: a string specifies the model in which the file is opened. Use "rt" for
+      reading in text mode; use "rb" for reading in binary mode.
+
+  Returns:
+    The loaded file in str or bytes.
+  """
+  with open(file_path, mode) as file:
+    return file.read()
+
+
+def save_file(file_bytes: Union[bytes, bytearray],
+              save_to_path: str,
+              mode: str = "wb"):
+  """Loads file from the file path.
+
+  Args:
+    file_bytes: the bytes to be saved to file.
+    save_to_path: valid file path string.
+    mode: a string specifies the model in which the file is opened. Use "wt" for
+      writing in text mode; use "wb" for writing in binary mode.
+
+  Returns:
+    The loaded file in str or bytes.
+  """
+  with open(save_to_path, mode) as file:
+    file.write(file_bytes)
+
+
+def get_tokenizer_associated_files(
+    tokenizer_options: Union[None, _metadata_fb.BertTokenizerOptionsT,
+                             _metadata_fb.SentencePieceTokenizerOptionsT,
+                             _metadata_fb.RegexTokenizerOptionsT]
+) -> List[Optional[str]]:
+  """Gets a list of associated files packed in the tokenzier_options.
+
+  Args:
+    tokenizer_options: a tokenizer metadata object. Support the following
+      tokenizer types:
+      1. BertTokenizerOptions:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L436
+      2. SentencePieceTokenizerOptions:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L473
+      3. RegexTokenizerOptions:
+        https://github.com/tensorflow/tflite-support/blob/b80289c4cd1224d0e1836c7654e82f070f9eefaa/tensorflow_lite_support/metadata/metadata_schema.fbs#L475
+
+  Returns:
+    A list of associated files included in tokenizer_options.
+  """
+
+  if not tokenizer_options:
+    return []
+
+  def _get_file_path(files: _metadata_fb.AssociatedFileT) -> List[str]:
+    if not files:
+      return []
+    return [file.name for file in files]
+
+  if isinstance(tokenizer_options, (_metadata_fb.BertTokenizerOptionsT,
+                                    _metadata_fb.RegexTokenizerOptionsT)):
+    return _get_file_path(tokenizer_options.vocabFile)
+  elif isinstance(tokenizer_options,
+                  _metadata_fb.SentencePieceTokenizerOptionsT):
+    return _get_file_path(tokenizer_options.vocabFile) + _get_file_path(
+        tokenizer_options.sentencePieceModel)
+  else:
+    return []
+
+
+def _get_subgraph(model_buffer: bytearray) -> _schema_fb.SubGraph:
+  """Gets the subgraph of the model.
+
+  TFLite does not support multi-subgraph. A model should have exactly one
+  subgraph.
+
+  Args:
+    model_buffer: valid buffer of the model file.
+
+  Returns:
+    The subgraph of the model.
+
+  Raises:
+    ValueError: if the model has more than one subgraph or has no subgraph.
+  """
+
+  model = _schema_fb.Model.GetRootAsModel(model_buffer, 0)
+
+  # Use the first subgraph as default. TFLite Interpreter doesn't support
+  # multiple subgraphs yet, but models with mini-benchmark may have multiple
+  # subgraphs for acceleration evaluation purpose.
+  return model.Subgraphs(0)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/BUILD
new file mode 100644
index 0000000..2b54974
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/BUILD
@@ -0,0 +1,50 @@
+package(
+    default_visibility = [
+        "//visibility:public",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+py_test(
+    name = "metadata_test",
+    srcs = ["metadata_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        # build rule placeholder: six dep,
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata:schema_py",
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_test(
+    name = "metadata_parser_test",
+    srcs = ["metadata_parser_test.py"],
+    python_version = "PY3",
+    srcs_version = "PY2AND3",
+    deps = [
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata/python:metadata",
+    ],
+)
+
+py_test(
+    name = "metadata_writer_for_task_test",
+    srcs = ["metadata_writer_for_task_test.py"],
+    data = [
+        "//tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier:test_files",
+        "//tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder:test_files",
+        "//tensorflow_lite_support/metadata/python/tests/testdata/image_classifier:test_files",
+    ],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata/python:metadata_writer_for_task",
+        "//tensorflow_lite_support/metadata/python/tests/metadata_writers:test_utils",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_parser_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_parser_test.py
new file mode 100644
index 0000000..e02d69ae
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_parser_test.py
@@ -0,0 +1,37 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for tensorflow_lite_support.metadata.metadata_parser."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import re
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata.python import metadata_parser
+
+
+class MetadataParserTest(tf.test.TestCase):
+
+  def testVersionWellFormedSemanticVersion(self):
+    # Validates that the version is well-formed (x.y.z).
+    self.assertTrue(
+        re.match('[0-9]+\\.[0-9]+\\.[0-9]+',
+                 metadata_parser.MetadataParser.VERSION))
+
+
+if __name__ == '__main__':
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_test.py
new file mode 100644
index 0000000..bf8d3b7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_test.py
@@ -0,0 +1,860 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for tensorflow_lite_support.metadata.metadata."""
+
+import enum
+import os
+
+from absl.testing import parameterized
+import six
+import tensorflow as tf
+
+import flatbuffers
+from tensorflow.python.platform import resource_loader
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+
+
+class Tokenizer(enum.Enum):
+  BERT_TOKENIZER = 0
+  SENTENCE_PIECE = 1
+
+
+class TensorType(enum.Enum):
+  INPUT = 0
+  OUTPUT = 1
+
+
+def _read_file(file_name, mode="rb"):
+  with open(file_name, mode) as f:
+    return f.read()
+
+
+class MetadataTest(tf.test.TestCase, parameterized.TestCase):
+
+  def setUp(self):
+    super(MetadataTest, self).setUp()
+    self._invalid_model_buf = None
+    self._invalid_file = "not_existed_file"
+    self._model_buf = self._create_model_buf()
+    self._model_file = self.create_tempfile().full_path
+    with open(self._model_file, "wb") as f:
+      f.write(self._model_buf)
+    self._metadata_file = self._create_metadata_file()
+    self._metadata_file_with_version = self._create_metadata_file_with_version(
+        self._metadata_file, "1.0.0")
+    self._file1 = self.create_tempfile("file1").full_path
+    self._file2 = self.create_tempfile("file2").full_path
+    self._file2_content = b"file2_content"
+    with open(self._file2, "wb") as f:
+      f.write(self._file2_content)
+    self._file3 = self.create_tempfile("file3").full_path
+
+  def _create_model_buf(self):
+    # Create a model with two inputs and one output, which matches the metadata
+    # created by _create_metadata_file().
+    metadata_field = _schema_fb.MetadataT()
+    subgraph = _schema_fb.SubGraphT()
+    subgraph.inputs = [0, 1]
+    subgraph.outputs = [2]
+
+    metadata_field.name = "meta"
+    buffer_field = _schema_fb.BufferT()
+    model = _schema_fb.ModelT()
+    model.subgraphs = [subgraph]
+    # Creates the metadata and buffer fields for testing purposes.
+    model.metadata = [metadata_field, metadata_field]
+    model.buffers = [buffer_field, buffer_field, buffer_field]
+    model_builder = flatbuffers.Builder(0)
+    model_builder.Finish(
+        model.Pack(model_builder),
+        _metadata.MetadataPopulator.TFLITE_FILE_IDENTIFIER)
+    return model_builder.Output()
+
+  def _create_metadata_file(self):
+    associated_file1 = _metadata_fb.AssociatedFileT()
+    associated_file1.name = b"file1"
+    associated_file2 = _metadata_fb.AssociatedFileT()
+    associated_file2.name = b"file2"
+    self.expected_recorded_files = [
+        six.ensure_str(associated_file1.name),
+        six.ensure_str(associated_file2.name)
+    ]
+
+    input_meta = _metadata_fb.TensorMetadataT()
+    output_meta = _metadata_fb.TensorMetadataT()
+    output_meta.associatedFiles = [associated_file2]
+    subgraph = _metadata_fb.SubGraphMetadataT()
+    # Create a model with two inputs and one output.
+    subgraph.inputTensorMetadata = [input_meta, input_meta]
+    subgraph.outputTensorMetadata = [output_meta]
+
+    model_meta = _metadata_fb.ModelMetadataT()
+    model_meta.name = "Mobilenet_quantized"
+    model_meta.associatedFiles = [associated_file1]
+    model_meta.subgraphMetadata = [subgraph]
+    b = flatbuffers.Builder(0)
+    b.Finish(
+        model_meta.Pack(b),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+
+    metadata_file = self.create_tempfile().full_path
+    with open(metadata_file, "wb") as f:
+      f.write(b.Output())
+    return metadata_file
+
+  def _create_model_buffer_with_wrong_identifier(self):
+    wrong_identifier = b"widn"
+    model = _schema_fb.ModelT()
+    model_builder = flatbuffers.Builder(0)
+    model_builder.Finish(model.Pack(model_builder), wrong_identifier)
+    return model_builder.Output()
+
+  def _create_metadata_buffer_with_wrong_identifier(self):
+    # Creates a metadata with wrong identifier
+    wrong_identifier = b"widn"
+    metadata = _metadata_fb.ModelMetadataT()
+    metadata_builder = flatbuffers.Builder(0)
+    metadata_builder.Finish(metadata.Pack(metadata_builder), wrong_identifier)
+    return metadata_builder.Output()
+
+  def _populate_metadata_with_identifier(self, model_buf, metadata_buf,
+                                         identifier):
+    # For testing purposes only. MetadataPopulator cannot populate metadata with
+    # wrong identifiers.
+    model = _schema_fb.ModelT.InitFromObj(
+        _schema_fb.Model.GetRootAsModel(model_buf, 0))
+    buffer_field = _schema_fb.BufferT()
+    buffer_field.data = metadata_buf
+    model.buffers = [buffer_field]
+    # Creates a new metadata field.
+    metadata_field = _schema_fb.MetadataT()
+    metadata_field.name = _metadata.MetadataPopulator.METADATA_FIELD_NAME
+    metadata_field.buffer = len(model.buffers) - 1
+    model.metadata = [metadata_field]
+    b = flatbuffers.Builder(0)
+    b.Finish(model.Pack(b), identifier)
+    return b.Output()
+
+  def _create_metadata_file_with_version(self, metadata_file, min_version):
+    # Creates a new metadata file with the specified min_version for testing
+    # purposes.
+    metadata_buf = bytearray(_read_file(metadata_file))
+
+    metadata = _metadata_fb.ModelMetadataT.InitFromObj(
+        _metadata_fb.ModelMetadata.GetRootAsModelMetadata(metadata_buf, 0))
+    metadata.minParserVersion = min_version
+
+    b = flatbuffers.Builder(0)
+    b.Finish(
+        metadata.Pack(b), _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+
+    metadata_file_with_version = self.create_tempfile().full_path
+    with open(metadata_file_with_version, "wb") as f:
+      f.write(b.Output())
+    return metadata_file_with_version
+
+
+class MetadataPopulatorTest(MetadataTest):
+
+  def _create_bert_tokenizer(self):
+    vocab_file_name = "bert_vocab"
+    vocab = _metadata_fb.AssociatedFileT()
+    vocab.name = vocab_file_name
+    vocab.type = _metadata_fb.AssociatedFileType.VOCABULARY
+    tokenizer = _metadata_fb.ProcessUnitT()
+    tokenizer.optionsType = _metadata_fb.ProcessUnitOptions.BertTokenizerOptions
+    tokenizer.options = _metadata_fb.BertTokenizerOptionsT()
+    tokenizer.options.vocabFile = [vocab]
+    return tokenizer, [vocab_file_name]
+
+  def _create_sentence_piece_tokenizer(self):
+    sp_model_name = "sp_model"
+    vocab_file_name = "sp_vocab"
+    sp_model = _metadata_fb.AssociatedFileT()
+    sp_model.name = sp_model_name
+    vocab = _metadata_fb.AssociatedFileT()
+    vocab.name = vocab_file_name
+    vocab.type = _metadata_fb.AssociatedFileType.VOCABULARY
+    tokenizer = _metadata_fb.ProcessUnitT()
+    tokenizer.optionsType = (
+        _metadata_fb.ProcessUnitOptions.SentencePieceTokenizerOptions)
+    tokenizer.options = _metadata_fb.SentencePieceTokenizerOptionsT()
+    tokenizer.options.sentencePieceModel = [sp_model]
+    tokenizer.options.vocabFile = [vocab]
+    return tokenizer, [sp_model_name, vocab_file_name]
+
+  def _create_tokenizer(self, tokenizer_type):
+    if tokenizer_type is Tokenizer.BERT_TOKENIZER:
+      return self._create_bert_tokenizer()
+    elif tokenizer_type is Tokenizer.SENTENCE_PIECE:
+      return self._create_sentence_piece_tokenizer()
+    else:
+      raise ValueError(
+          "The tokenizer type, {0}, is unsupported.".format(tokenizer_type))
+
+  def _create_tempfiles(self, file_names):
+    tempfiles = []
+    for name in file_names:
+      tempfiles.append(self.create_tempfile(name).full_path)
+    return tempfiles
+
+  def _create_model_meta_with_subgraph_meta(self, subgraph_meta):
+    model_meta = _metadata_fb.ModelMetadataT()
+    model_meta.subgraphMetadata = [subgraph_meta]
+    b = flatbuffers.Builder(0)
+    b.Finish(
+        model_meta.Pack(b),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    return b.Output()
+
+  def testToValidModelFile(self):
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    self.assertIsInstance(populator, _metadata.MetadataPopulator)
+
+  def testToInvalidModelFile(self):
+    with self.assertRaises(IOError) as error:
+      _metadata.MetadataPopulator.with_model_file(self._invalid_file)
+    self.assertEqual("File, '{0}', does not exist.".format(self._invalid_file),
+                     str(error.exception))
+
+  def testToValidModelBuffer(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    self.assertIsInstance(populator, _metadata.MetadataPopulator)
+
+  def testToInvalidModelBuffer(self):
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataPopulator.with_model_buffer(self._invalid_model_buf)
+    self.assertEqual("model_buf cannot be empty.", str(error.exception))
+
+  def testToModelBufferWithWrongIdentifier(self):
+    model_buf = self._create_model_buffer_with_wrong_identifier()
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataPopulator.with_model_buffer(model_buf)
+    self.assertEqual(
+        "The model provided does not have the expected identifier, and "
+        "may not be a valid TFLite model.", str(error.exception))
+
+  def testSinglePopulateAssociatedFile(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    populator.load_associated_files([self._file1])
+    populator.populate()
+
+    packed_files = populator.get_packed_associated_file_list()
+    expected_packed_files = [os.path.basename(self._file1)]
+    self.assertEqual(set(packed_files), set(expected_packed_files))
+
+  def testRepeatedPopulateAssociatedFile(self):
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_associated_files([self._file1, self._file2])
+    # Loads file2 multiple times.
+    populator.load_associated_files([self._file2])
+    populator.populate()
+
+    packed_files = populator.get_packed_associated_file_list()
+    expected_packed_files = [
+        os.path.basename(self._file1),
+        os.path.basename(self._file2)
+    ]
+    self.assertLen(packed_files, 2)
+    self.assertEqual(set(packed_files), set(expected_packed_files))
+
+    # Check if the model buffer read from file is the same as that read from
+    # get_model_buffer().
+    model_buf_from_file = _read_file(self._model_file)
+    model_buf_from_getter = populator.get_model_buffer()
+    self.assertEqual(model_buf_from_file, model_buf_from_getter)
+
+  def testPopulateInvalidAssociatedFile(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    with self.assertRaises(IOError) as error:
+      populator.load_associated_files([self._invalid_file])
+    self.assertEqual("File, '{0}', does not exist.".format(self._invalid_file),
+                     str(error.exception))
+
+  def testPopulatePackedAssociatedFile(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    populator.load_associated_files([self._file1])
+    populator.populate()
+    with self.assertRaises(ValueError) as error:
+      populator.load_associated_files([self._file1])
+      populator.populate()
+    self.assertEqual(
+        "File, '{0}', has already been packed.".format(
+            os.path.basename(self._file1)), str(error.exception))
+
+  def testLoadAssociatedFileBuffers(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    file_buffer = _read_file(self._file1)
+    populator.load_associated_file_buffers({self._file1: file_buffer})
+    populator.populate()
+
+    packed_files = populator.get_packed_associated_file_list()
+    expected_packed_files = [os.path.basename(self._file1)]
+    self.assertEqual(set(packed_files), set(expected_packed_files))
+
+  def testRepeatedLoadAssociatedFileBuffers(self):
+    file_buffer1 = _read_file(self._file1)
+    file_buffer2 = _read_file(self._file2)
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+
+    populator.load_associated_file_buffers({
+        self._file1: file_buffer1,
+        self._file2: file_buffer2
+    })
+    # Loads file2 multiple times.
+    populator.load_associated_file_buffers({self._file2: file_buffer2})
+    populator.populate()
+
+    packed_files = populator.get_packed_associated_file_list()
+    expected_packed_files = [
+        os.path.basename(self._file1),
+        os.path.basename(self._file2)
+    ]
+    self.assertEqual(set(packed_files), set(expected_packed_files))
+
+    # Check if the model buffer read from file is the same as that read from
+    # get_model_buffer().
+    model_buf_from_file = _read_file(self._model_file)
+    model_buf_from_getter = populator.get_model_buffer()
+    self.assertEqual(model_buf_from_file, model_buf_from_getter)
+
+  def testLoadPackedAssociatedFileBuffersFails(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    file_buffer = _read_file(self._file1)
+    populator.load_associated_file_buffers({self._file1: file_buffer})
+    populator.populate()
+
+    # Load file1 again should fail.
+    with self.assertRaises(ValueError) as error:
+      populator.load_associated_file_buffers({self._file1: file_buffer})
+      populator.populate()
+    self.assertEqual(
+        "File, '{0}', has already been packed.".format(
+            os.path.basename(self._file1)), str(error.exception))
+
+  def testGetPackedAssociatedFileList(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    packed_files = populator.get_packed_associated_file_list()
+    self.assertEqual(packed_files, [])
+
+  def testPopulateMetadataFileToEmptyModelFile(self):
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_metadata_file(self._metadata_file)
+    populator.load_associated_files([self._file1, self._file2])
+    populator.populate()
+
+    model_buf_from_file = _read_file(self._model_file)
+    model = _schema_fb.Model.GetRootAsModel(model_buf_from_file, 0)
+    # self._model_file already has two elements in the metadata field, so the
+    # populated TFLite metadata will be the third element.
+    metadata_field = model.Metadata(2)
+    self.assertEqual(
+        six.ensure_str(metadata_field.Name()),
+        six.ensure_str(_metadata.MetadataPopulator.METADATA_FIELD_NAME))
+
+    buffer_index = metadata_field.Buffer()
+    buffer_data = model.Buffers(buffer_index)
+    metadata_buf_np = buffer_data.DataAsNumpy()
+    metadata_buf = metadata_buf_np.tobytes()
+    expected_metadata_buf = bytearray(
+        _read_file(self._metadata_file_with_version))
+    self.assertEqual(metadata_buf, expected_metadata_buf)
+
+    recorded_files = populator.get_recorded_associated_file_list()
+    self.assertEqual(set(recorded_files), set(self.expected_recorded_files))
+
+    # Up to now, we've proved the correctness of the model buffer that read from
+    # file. Then we'll test if get_model_buffer() gives the same model buffer.
+    model_buf_from_getter = populator.get_model_buffer()
+    self.assertEqual(model_buf_from_file, model_buf_from_getter)
+
+  def testPopulateMetadataFileWithoutAssociatedFiles(self):
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_metadata_file(self._metadata_file)
+    populator.load_associated_files([self._file1])
+    # Suppose to populate self._file2, because it is recorded in the metadta.
+    with self.assertRaises(ValueError) as error:
+      populator.populate()
+    self.assertEqual(("File, '{0}', is recorded in the metadata, but has "
+                      "not been loaded into the populator.").format(
+                          os.path.basename(self._file2)), str(error.exception))
+
+  def testPopulateMetadataBufferWithWrongIdentifier(self):
+    metadata_buf = self._create_metadata_buffer_with_wrong_identifier()
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    with self.assertRaises(ValueError) as error:
+      populator.load_metadata_buffer(metadata_buf)
+    self.assertEqual(
+        "The metadata buffer does not have the expected identifier, and may not"
+        " be a valid TFLite Metadata.", str(error.exception))
+
+  def _assert_golden_metadata(self, model_file):
+    model_buf_from_file = _read_file(model_file)
+    model = _schema_fb.Model.GetRootAsModel(model_buf_from_file, 0)
+    # There are two elements in model.Metadata array before the population.
+    # Metadata should be packed to the third element in the array.
+    metadata_field = model.Metadata(2)
+    self.assertEqual(
+        six.ensure_str(metadata_field.Name()),
+        six.ensure_str(_metadata.MetadataPopulator.METADATA_FIELD_NAME))
+
+    buffer_index = metadata_field.Buffer()
+    buffer_data = model.Buffers(buffer_index)
+    metadata_buf_np = buffer_data.DataAsNumpy()
+    metadata_buf = metadata_buf_np.tobytes()
+    expected_metadata_buf = bytearray(
+        _read_file(self._metadata_file_with_version))
+    self.assertEqual(metadata_buf, expected_metadata_buf)
+
+  def testPopulateMetadataFileToModelWithMetadataAndAssociatedFiles(self):
+    # First, creates a dummy metadata different from self._metadata_file. It
+    # needs to have the same input/output tensor numbers as self._model_file.
+    # Populates it and the associated files into the model.
+    input_meta = _metadata_fb.TensorMetadataT()
+    output_meta = _metadata_fb.TensorMetadataT()
+    subgraph = _metadata_fb.SubGraphMetadataT()
+    # Create a model with two inputs and one output.
+    subgraph.inputTensorMetadata = [input_meta, input_meta]
+    subgraph.outputTensorMetadata = [output_meta]
+    model_meta = _metadata_fb.ModelMetadataT()
+    model_meta.subgraphMetadata = [subgraph]
+    b = flatbuffers.Builder(0)
+    b.Finish(
+        model_meta.Pack(b),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    metadata_buf = b.Output()
+
+    # Populate the metadata.
+    populator1 = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator1.load_metadata_buffer(metadata_buf)
+    populator1.load_associated_files([self._file1, self._file2])
+    populator1.populate()
+
+    # Then, populate the metadata again.
+    populator2 = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator2.load_metadata_file(self._metadata_file)
+    populator2.populate()
+
+    # Test if the metadata is populated correctly.
+    self._assert_golden_metadata(self._model_file)
+
+  def testPopulateMetadataFileToModelFileWithMetadataAndBufFields(self):
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_metadata_file(self._metadata_file)
+    populator.load_associated_files([self._file1, self._file2])
+    populator.populate()
+
+    # Tests if the metadata is populated correctly.
+    self._assert_golden_metadata(self._model_file)
+
+    recorded_files = populator.get_recorded_associated_file_list()
+    self.assertEqual(set(recorded_files), set(self.expected_recorded_files))
+
+    # Up to now, we've proved the correctness of the model buffer that read from
+    # file. Then we'll test if get_model_buffer() gives the same model buffer.
+    model_buf_from_file = _read_file(self._model_file)
+    model_buf_from_getter = populator.get_model_buffer()
+    self.assertEqual(model_buf_from_file, model_buf_from_getter)
+
+  def testPopulateInvalidMetadataFile(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    with self.assertRaises(IOError) as error:
+      populator.load_metadata_file(self._invalid_file)
+    self.assertEqual("File, '{0}', does not exist.".format(self._invalid_file),
+                     str(error.exception))
+
+  def testPopulateInvalidMetadataBuffer(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    with self.assertRaises(ValueError) as error:
+      populator.load_metadata_buffer([])
+    self.assertEqual("The metadata to be populated is empty.",
+                     str(error.exception))
+
+  def testGetModelBufferBeforePopulatingData(self):
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    model_buf = populator.get_model_buffer()
+    expected_model_buf = self._model_buf
+    self.assertEqual(model_buf, expected_model_buf)
+
+  def testLoadMetadataBufferWithNoSubgraphMetadataThrowsException(self):
+    # Create a dummy metadata without Subgraph.
+    model_meta = _metadata_fb.ModelMetadataT()
+    builder = flatbuffers.Builder(0)
+    builder.Finish(
+        model_meta.Pack(builder),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    meta_buf = builder.Output()
+
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    with self.assertRaises(ValueError) as error:
+      populator.load_metadata_buffer(meta_buf)
+    self.assertEqual(
+        "The number of SubgraphMetadata should be exactly one, but got 0.",
+        str(error.exception))
+
+  def testLoadMetadataBufferWithWrongInputMetaNumberThrowsException(self):
+    # Create a dummy metadata with no input tensor metadata, while the expected
+    # number is 2.
+    output_meta = _metadata_fb.TensorMetadataT()
+    subgprah_meta = _metadata_fb.SubGraphMetadataT()
+    subgprah_meta.outputTensorMetadata = [output_meta]
+    model_meta = _metadata_fb.ModelMetadataT()
+    model_meta.subgraphMetadata = [subgprah_meta]
+    builder = flatbuffers.Builder(0)
+    builder.Finish(
+        model_meta.Pack(builder),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    meta_buf = builder.Output()
+
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    with self.assertRaises(ValueError) as error:
+      populator.load_metadata_buffer(meta_buf)
+    self.assertEqual(
+        ("The number of input tensors (2) should match the number of "
+         "input tensor metadata (0)"), str(error.exception))
+
+  def testLoadMetadataBufferWithWrongOutputMetaNumberThrowsException(self):
+    # Create a dummy metadata with no output tensor metadata, while the expected
+    # number is 1.
+    input_meta = _metadata_fb.TensorMetadataT()
+    subgprah_meta = _metadata_fb.SubGraphMetadataT()
+    subgprah_meta.inputTensorMetadata = [input_meta, input_meta]
+    model_meta = _metadata_fb.ModelMetadataT()
+    model_meta.subgraphMetadata = [subgprah_meta]
+    builder = flatbuffers.Builder(0)
+    builder.Finish(
+        model_meta.Pack(builder),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    meta_buf = builder.Output()
+
+    populator = _metadata.MetadataPopulator.with_model_buffer(self._model_buf)
+    with self.assertRaises(ValueError) as error:
+      populator.load_metadata_buffer(meta_buf)
+    self.assertEqual(
+        ("The number of output tensors (1) should match the number of "
+         "output tensor metadata (0)"), str(error.exception))
+
+  def testLoadMetadataAndAssociatedFilesShouldSucceeds(self):
+    # Create a src model with metadata and two associated files.
+    src_model_buf = self._create_model_buf()
+    populator_src = _metadata.MetadataPopulator.with_model_buffer(src_model_buf)
+    populator_src.load_metadata_file(self._metadata_file)
+    populator_src.load_associated_files([self._file1, self._file2])
+    populator_src.populate()
+
+    # Create a model to be populated with the metadata and files from
+    # src_model_buf.
+    dst_model_buf = self._create_model_buf()
+    populator_dst = _metadata.MetadataPopulator.with_model_buffer(dst_model_buf)
+    populator_dst.load_metadata_and_associated_files(
+        populator_src.get_model_buffer())
+    populator_dst.populate()
+
+    # Tests if the metadata and associated files are populated correctly.
+    dst_model_file = self.create_tempfile().full_path
+    with open(dst_model_file, "wb") as f:
+      f.write(populator_dst.get_model_buffer())
+    self._assert_golden_metadata(dst_model_file)
+
+    recorded_files = populator_dst.get_recorded_associated_file_list()
+    self.assertEqual(set(recorded_files), set(self.expected_recorded_files))
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "InputTensorWithBert",
+          "tensor_type": TensorType.INPUT,
+          "tokenizer_type": Tokenizer.BERT_TOKENIZER
+      }, {
+          "testcase_name": "OutputTensorWithBert",
+          "tensor_type": TensorType.OUTPUT,
+          "tokenizer_type": Tokenizer.BERT_TOKENIZER
+      }, {
+          "testcase_name": "InputTensorWithSentencePiece",
+          "tensor_type": TensorType.INPUT,
+          "tokenizer_type": Tokenizer.SENTENCE_PIECE
+      }, {
+          "testcase_name": "OutputTensorWithSentencePiece",
+          "tensor_type": TensorType.OUTPUT,
+          "tokenizer_type": Tokenizer.SENTENCE_PIECE
+      })
+  def testGetRecordedAssociatedFileListWithSubgraphTensor(
+      self, tensor_type, tokenizer_type):
+    # Creates a metadata with the tokenizer in the tensor process units.
+    tokenizer, expected_files = self._create_tokenizer(tokenizer_type)
+
+    # Create the tensor with process units.
+    tensor = _metadata_fb.TensorMetadataT()
+    tensor.processUnits = [tokenizer]
+
+    # Create the subgrah with the tensor.
+    subgraph = _metadata_fb.SubGraphMetadataT()
+    dummy_tensor_meta = _metadata_fb.TensorMetadataT()
+    subgraph.outputTensorMetadata = [dummy_tensor_meta]
+    if tensor_type is TensorType.INPUT:
+      subgraph.inputTensorMetadata = [tensor, dummy_tensor_meta]
+      subgraph.outputTensorMetadata = [dummy_tensor_meta]
+    elif tensor_type is TensorType.OUTPUT:
+      subgraph.inputTensorMetadata = [dummy_tensor_meta, dummy_tensor_meta]
+      subgraph.outputTensorMetadata = [tensor]
+    else:
+      raise ValueError(
+          "The tensor type, {0}, is unsupported.".format(tensor_type))
+
+    # Create a model metadata with the subgraph metadata
+    meta_buffer = self._create_model_meta_with_subgraph_meta(subgraph)
+
+    # Creates the tempfiles.
+    tempfiles = self._create_tempfiles(expected_files)
+
+    # Creates the MetadataPopulator object.
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_metadata_buffer(meta_buffer)
+    populator.load_associated_files(tempfiles)
+    populator.populate()
+
+    recorded_files = populator.get_recorded_associated_file_list()
+    self.assertEqual(set(recorded_files), set(expected_files))
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "InputTensorWithBert",
+          "tensor_type": TensorType.INPUT,
+          "tokenizer_type": Tokenizer.BERT_TOKENIZER
+      }, {
+          "testcase_name": "OutputTensorWithBert",
+          "tensor_type": TensorType.OUTPUT,
+          "tokenizer_type": Tokenizer.BERT_TOKENIZER
+      }, {
+          "testcase_name": "InputTensorWithSentencePiece",
+          "tensor_type": TensorType.INPUT,
+          "tokenizer_type": Tokenizer.SENTENCE_PIECE
+      }, {
+          "testcase_name": "OutputTensorWithSentencePiece",
+          "tensor_type": TensorType.OUTPUT,
+          "tokenizer_type": Tokenizer.SENTENCE_PIECE
+      })
+  def testGetRecordedAssociatedFileListWithSubgraphProcessUnits(
+      self, tensor_type, tokenizer_type):
+    # Creates a metadata with the tokenizer in the subgraph process units.
+    tokenizer, expected_files = self._create_tokenizer(tokenizer_type)
+
+    # Create the subgraph with process units.
+    subgraph = _metadata_fb.SubGraphMetadataT()
+    if tensor_type is TensorType.INPUT:
+      subgraph.inputProcessUnits = [tokenizer]
+    elif tensor_type is TensorType.OUTPUT:
+      subgraph.outputProcessUnits = [tokenizer]
+    else:
+      raise ValueError(
+          "The tensor type, {0}, is unsupported.".format(tensor_type))
+
+    # Creates the input and output tensor meta to match self._model_file.
+    dummy_tensor_meta = _metadata_fb.TensorMetadataT()
+    subgraph.inputTensorMetadata = [dummy_tensor_meta, dummy_tensor_meta]
+    subgraph.outputTensorMetadata = [dummy_tensor_meta]
+
+    # Create a model metadata with the subgraph metadata
+    meta_buffer = self._create_model_meta_with_subgraph_meta(subgraph)
+
+    # Creates the tempfiles.
+    tempfiles = self._create_tempfiles(expected_files)
+
+    # Creates the MetadataPopulator object.
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_metadata_buffer(meta_buffer)
+    populator.load_associated_files(tempfiles)
+    populator.populate()
+
+    recorded_files = populator.get_recorded_associated_file_list()
+    self.assertEqual(set(recorded_files), set(expected_files))
+
+  def testPopulatedFullPathAssociatedFileShouldSucceed(self):
+    # Create AssociatedFileT using the full path file name.
+    associated_file = _metadata_fb.AssociatedFileT()
+    associated_file.name = self._file1
+
+    # Create model metadata with the associated file.
+    subgraph = _metadata_fb.SubGraphMetadataT()
+    subgraph.associatedFiles = [associated_file]
+    # Creates the input and output tensor metadata to match self._model_file.
+    dummy_tensor = _metadata_fb.TensorMetadataT()
+    subgraph.inputTensorMetadata = [dummy_tensor, dummy_tensor]
+    subgraph.outputTensorMetadata = [dummy_tensor]
+    md_buffer = self._create_model_meta_with_subgraph_meta(subgraph)
+
+    # Populate the metadata to a model.
+    populator = _metadata.MetadataPopulator.with_model_file(self._model_file)
+    populator.load_metadata_buffer(md_buffer)
+    populator.load_associated_files([self._file1])
+    populator.populate()
+
+    # The recorded file name in metadata should only contain file basename; file
+    # directory should not be included.
+    recorded_files = populator.get_recorded_associated_file_list()
+    self.assertEqual(set(recorded_files), set([os.path.basename(self._file1)]))
+
+
+class MetadataDisplayerTest(MetadataTest):
+
+  def setUp(self):
+    super(MetadataDisplayerTest, self).setUp()
+    self._model_with_meta_file = (
+        self._create_model_with_metadata_and_associated_files())
+
+  def _create_model_with_metadata_and_associated_files(self):
+    model_buf = self._create_model_buf()
+    model_file = self.create_tempfile().full_path
+    with open(model_file, "wb") as f:
+      f.write(model_buf)
+
+    populator = _metadata.MetadataPopulator.with_model_file(model_file)
+    populator.load_metadata_file(self._metadata_file)
+    populator.load_associated_files([self._file1, self._file2])
+    populator.populate()
+    return model_file
+
+  def testLoadModelBufferMetadataBufferWithWrongIdentifierThrowsException(self):
+    model_buf = self._create_model_buffer_with_wrong_identifier()
+    metadata_buf = self._create_metadata_buffer_with_wrong_identifier()
+    model_buf = self._populate_metadata_with_identifier(
+        model_buf, metadata_buf,
+        _metadata.MetadataPopulator.TFLITE_FILE_IDENTIFIER)
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataDisplayer.with_model_buffer(model_buf)
+    self.assertEqual(
+        "The metadata buffer does not have the expected identifier, and may not"
+        " be a valid TFLite Metadata.", str(error.exception))
+
+  def testLoadModelBufferModelBufferWithWrongIdentifierThrowsException(self):
+    model_buf = self._create_model_buffer_with_wrong_identifier()
+    metadata_file = self._create_metadata_file()
+    wrong_identifier = b"widn"
+    metadata_buf = bytearray(_read_file(metadata_file))
+    model_buf = self._populate_metadata_with_identifier(model_buf, metadata_buf,
+                                                        wrong_identifier)
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataDisplayer.with_model_buffer(model_buf)
+    self.assertEqual(
+        "The model provided does not have the expected identifier, and "
+        "may not be a valid TFLite model.", str(error.exception))
+
+  def testLoadModelFileInvalidModelFileThrowsException(self):
+    with self.assertRaises(IOError) as error:
+      _metadata.MetadataDisplayer.with_model_file(self._invalid_file)
+    self.assertEqual("File, '{0}', does not exist.".format(self._invalid_file),
+                     str(error.exception))
+
+  def testLoadModelFileModelWithoutMetadataThrowsException(self):
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataDisplayer.with_model_file(self._model_file)
+    self.assertEqual("The model does not have metadata.", str(error.exception))
+
+  def testLoadModelFileModelWithMetadata(self):
+    displayer = _metadata.MetadataDisplayer.with_model_file(
+        self._model_with_meta_file)
+    self.assertIsInstance(displayer, _metadata.MetadataDisplayer)
+
+  def testLoadModelBufferInvalidModelBufferThrowsException(self):
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataDisplayer.with_model_buffer(_read_file(self._file1))
+    self.assertEqual("model_buffer cannot be empty.", str(error.exception))
+
+  def testLoadModelBufferModelWithOutMetadataThrowsException(self):
+    with self.assertRaises(ValueError) as error:
+      _metadata.MetadataDisplayer.with_model_buffer(self._create_model_buf())
+    self.assertEqual("The model does not have metadata.", str(error.exception))
+
+  def testLoadModelBufferModelWithMetadata(self):
+    displayer = _metadata.MetadataDisplayer.with_model_buffer(
+        _read_file(self._model_with_meta_file))
+    self.assertIsInstance(displayer, _metadata.MetadataDisplayer)
+
+  def testGetAssociatedFileBufferShouldSucceed(self):
+    # _model_with_meta_file contains file1 and file2.
+    displayer = _metadata.MetadataDisplayer.with_model_file(
+        self._model_with_meta_file)
+
+    actual_content = displayer.get_associated_file_buffer("file2")
+    self.assertEqual(actual_content, self._file2_content)
+
+  def testGetAssociatedFileBufferFailsWithNonExistentFile(self):
+    # _model_with_meta_file contains file1 and file2.
+    displayer = _metadata.MetadataDisplayer.with_model_file(
+        self._model_with_meta_file)
+
+    non_existent_file = "non_existent_file"
+    with self.assertRaises(ValueError) as error:
+      displayer.get_associated_file_buffer(non_existent_file)
+    self.assertEqual(
+        "The file, {}, does not exist in the model.".format(non_existent_file),
+        str(error.exception))
+
+  def testGetMetadataBufferShouldSucceed(self):
+    displayer = _metadata.MetadataDisplayer.with_model_file(
+        self._model_with_meta_file)
+    actual_buffer = displayer.get_metadata_buffer()
+    actual_json = _metadata.convert_to_json(actual_buffer)
+
+    # Verifies the generated json file.
+    golden_json_file_path = resource_loader.get_path_to_datafile(
+        "testdata/golden_json.json")
+    with open(golden_json_file_path, "r") as f:
+      expected = f.read()
+    self.assertEqual(actual_json, expected)
+
+  def testGetMetadataJsonModelWithMetadata(self):
+    displayer = _metadata.MetadataDisplayer.with_model_file(
+        self._model_with_meta_file)
+    actual = displayer.get_metadata_json()
+
+    # Verifies the generated json file.
+    golden_json_file_path = resource_loader.get_path_to_datafile(
+        "testdata/golden_json.json")
+    expected = _read_file(golden_json_file_path, "r")
+    self.assertEqual(actual, expected)
+
+  def testGetPackedAssociatedFileListModelWithMetadata(self):
+    displayer = _metadata.MetadataDisplayer.with_model_file(
+        self._model_with_meta_file)
+    packed_files = displayer.get_packed_associated_file_list()
+
+    expected_packed_files = [
+        os.path.basename(self._file1),
+        os.path.basename(self._file2)
+    ]
+    self.assertLen(
+        packed_files, 2,
+        "The following two associated files packed to the model: {0}; {1}"
+        .format(expected_packed_files[0], expected_packed_files[1]))
+    self.assertEqual(set(packed_files), set(expected_packed_files))
+
+
+class MetadataUtilTest(MetadataTest):
+
+  def test_convert_to_json_should_succeed(self):
+    metadata_buf = _read_file(self._metadata_file_with_version)
+    metadata_json = _metadata.convert_to_json(metadata_buf)
+
+    # Verifies the generated json file.
+    golden_json_file_path = resource_loader.get_path_to_datafile(
+        "testdata/golden_json.json")
+    expected = _read_file(golden_json_file_path, "r")
+    self.assertEqual(metadata_json, expected)
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writer_for_task_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writer_for_task_test.py
new file mode 100644
index 0000000..8c4f331
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writer_for_task_test.py
@@ -0,0 +1,507 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for tensorflow_lite_support.metadata.metadata_writer_for_task."""
+
+import os
+import sys
+import tensorflow as tf
+from tensorflow_lite_support.metadata.python import metadata_writer_for_task as mt
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_AUDIO_CLASSIFICATION_MODEL = '../testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.tflite'
+_AUDIO_EMBEDDING_MODEL = '../testdata/audio_embedder/yamnet_embedding.tflite'
+_IMAGE_CLASSIFIER_MODEL = '../testdata/image_classifier/mobilenet_v2_1.0_224.tflite'
+
+
+class LabelsTest(tf.test.TestCase):
+
+  def test_category_name(self):
+    labels = mt.Labels()
+    self.assertEqual(
+        labels.add(['a', 'b'], use_as_category_name=True)._labels,
+        [(None, 'labels.txt', ['a', 'b'])])
+    # Overwrite categories
+    self.assertEqual(
+        labels.add(['new_a', 'new_b'], use_as_category_name=True)._labels,
+        [(None, 'labels.txt', ['new_a', 'new_b'])])
+
+  def test_locale(self):
+    labels = mt.Labels()
+
+    # Add from file.
+    en_filepath = self.create_tempfile().full_path
+    with open(en_filepath, 'w') as f:
+      f.write('a\nb')
+    labels.add_from_file(en_filepath, 'en')
+
+    # Customized file name
+    labels.add(['A', 'B'], 'fr', exported_filename='my_file.txt')
+    self.assertEqual(labels._labels, [
+        ('en', 'labels_en.txt', ['a', 'b']),
+        ('fr', 'my_file.txt', ['A', 'B']),
+    ])
+
+    # Add category name, which should be the first file in the list.
+    labels.add(['aa', 'bb'], 'cn', use_as_category_name=True)
+    self.assertEqual(labels._labels, [
+        ('cn', 'labels_cn.txt', ['aa', 'bb']),
+        ('en', 'labels_en.txt', ['a', 'b']),
+        ('fr', 'my_file.txt', ['A', 'B']),
+    ])
+
+
+class MetadataWriterForTaskTest(tf.test.TestCase):
+
+  def test_initialize_without_with_block(self):
+    writer = mt.Writer(
+        test_utils.load_file(_AUDIO_CLASSIFICATION_MODEL),
+        model_name='test_model',
+        model_description='test_description')
+
+    # Calling `add_classification_output` outside the `with` block fails.
+    with self.assertRaisesRegex(AttributeError, '_temp_folder'):
+      writer.add_classification_output(mt.Labels().add(['cat', 'dog']))
+
+    writer.__enter__()
+    writer.add_classification_output(mt.Labels().add(['cat', 'dog']))
+    writer.__exit__(*sys.exc_info())
+
+    # Calling `add_classification_output` after `with` block closes also fails.
+    with self.assertRaisesRegex(AttributeError, '_temp_folder'):
+      writer.add_classification_output(mt.Labels().add(['cat', 'dog']))
+
+  def test_initialize_and_populate(self):
+    with mt.Writer(
+        test_utils.load_file(_AUDIO_CLASSIFICATION_MODEL),
+        model_name='my_audio_model',
+        model_description='my_description') as writer:
+      out_dir = self.create_tempdir()
+      _, metadata_json = writer.populate(
+          os.path.join(out_dir, 'model.tflite'),
+          os.path.join(out_dir, 'metadata.json'))
+      self.assertJsonEqual(
+          metadata_json, """{
+  "name": "my_audio_model",
+  "description": "my_description",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "waveform_binary"
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "tower0/network/layer32/final_output"
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
+""")
+
+  def test_audio_classifier(self):
+    with mt.Writer(
+        test_utils.load_file(_AUDIO_CLASSIFICATION_MODEL),
+        model_name='audio_classifier',
+        model_description='Classify the input audio clip') as writer:
+      out_dir = self.create_tempdir()
+      writer.add_audio_input(sample_rate=16000, channels=1)
+      writer.add_classification_output(mt.Labels().add(
+          ['sound1', 'sound2'], 'en', use_as_category_name=True))
+      writer.populate(
+          os.path.join(out_dir, 'model.tflite'),
+          os.path.join(out_dir, 'metadata.tflite'))
+      self.assertEqual(
+          test_utils.load_file(os.path.join(out_dir, 'metadata.tflite'), 'r'),
+          """{
+  "name": "audio_classifier",
+  "description": "Classify the input audio clip",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio",
+          "description": "Input audio clip to be processed.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 16000,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "score",
+          "description": "Score of the labels respectively",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels_en.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "en"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.3.0"
+}
+""")
+
+  def test_audio_classifier_with_locale(self):
+    with mt.Writer(
+        test_utils.load_file(_AUDIO_CLASSIFICATION_MODEL),
+        model_name='audio_classifier',
+        model_description='Classify the input audio clip') as writer:
+      out_dir = self.create_tempdir()
+      writer.add_audio_input(sample_rate=16000, channels=1)
+      writer.add_classification_output(mt.Labels().add(
+          ['/id1', '/id2'],
+          use_as_category_name=True).add(['sound1', 'sound2'],
+                                         'en').add(['son1', 'son2'], 'fr'))
+      _, metadata_json = writer.populate(
+          os.path.join(out_dir, 'model.tflite'),
+          os.path.join(out_dir, 'metadata.tflite'))
+      self.assertEqual(
+          metadata_json, """{
+  "name": "audio_classifier",
+  "description": "Classify the input audio clip",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio",
+          "description": "Input audio clip to be processed.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 16000,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "score",
+          "description": "Score of the labels respectively",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "labels_en.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "en"
+            },
+            {
+              "name": "labels_fr.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "fr"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.3.0"
+}
+""")
+
+  def test_audio_classifier_with_locale_and_score_calibration(self):
+    with mt.Writer(
+        test_utils.load_file(_AUDIO_CLASSIFICATION_MODEL),
+        model_name='audio_classifier',
+        model_description='Classify the input audio clip') as writer:
+      out_dir = self.create_tempdir()
+      writer.add_audio_input(sample_rate=16000, channels=1)
+      writer.add_classification_output(
+          mt.Labels().add(['/id1', '/id2'], use_as_category_name=True).add(
+              ['sound1', 'sound2'], 'en').add(['son1', 'son2'], 'fr'),
+          score_calibration=mt.ScoreCalibration(
+              mt.ScoreCalibration.transformation_types.INVERSE_LOGISTIC, [
+                  mt.CalibrationParameter(1., 2., 3., None),
+                  mt.CalibrationParameter(1., 2., 3., 4.),
+              ],
+              default_score=0.5))
+      _, metadata_json = writer.populate(
+          os.path.join(out_dir, 'model.tflite'),
+          os.path.join(out_dir, 'metadata.tflite'))
+      self.assertEqual(
+          metadata_json, """{
+  "name": "audio_classifier",
+  "description": "Classify the input audio clip",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio",
+          "description": "Input audio clip to be processed.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 16000,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "score",
+          "description": "Score of the labels respectively",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "INVERSE_LOGISTIC",
+                "default_score": 0.5
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "labels_en.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "en"
+            },
+            {
+              "name": "labels_fr.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "fr"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.3.0"
+}
+""")
+
+  def test_audio_embedder(self):
+    with mt.Writer(
+        test_utils.load_file(_AUDIO_EMBEDDING_MODEL),
+        model_name='audio_embedder',
+        model_description='Generate embedding for the input audio clip'
+    ) as writer:
+      out_dir = self.create_tempdir()
+      writer.add_audio_input(sample_rate=16000, channels=1)
+      writer.add_embedding_output()
+      _, metadata_json = writer.populate(
+          os.path.join(out_dir, 'model.tflite'),
+          os.path.join(out_dir, 'metadata.json'))
+      self.assertEqual(
+          metadata_json, """{
+  "name": "audio_embedder",
+  "description": "Generate embedding for the input audio clip",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio",
+          "description": "Input audio clip to be processed.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 16000,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "embedding",
+          "description": "Embedding vector of the input.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.3.0"
+}
+""")
+
+  def test_image_classifier(self):
+    with mt.Writer(
+        test_utils.load_file(_IMAGE_CLASSIFIER_MODEL),
+        model_name='image_classifier',
+        model_description='Imagenet classification model') as writer:
+      out_dir = self.create_tempdir()
+      writer.add_image_input(
+          norm_mean=[127.5, 127.5, 127.5],
+          norm_std=[127.5, 127.5, 127.5],
+          color_space_type=mt.Writer.color_space_types.RGB)
+      writer.add_classification_output(mt.Labels().add(['a', 'b', 'c']))
+      _, metadata_json = writer.populate(
+          os.path.join(out_dir, 'model.tflite'),
+          os.path.join(out_dir, 'metadat.json'))
+      self.assertEqual(
+          metadata_json, """{
+  "name": "image_classifier",
+  "description": "Imagenet classification model",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be processed.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5,
+                  127.5,
+                  127.5
+                ],
+                "std": [
+                  127.5,
+                  127.5,
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0,
+              1.0,
+              1.0
+            ],
+            "min": [
+              -1.0,
+              -1.0,
+              -1.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "score",
+          "description": "Score of the labels respectively",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
+""")
+
+
+if __name__ == '__main__':
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/BUILD
new file mode 100644
index 0000000..fc1365d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/BUILD
@@ -0,0 +1,171 @@
+# Placeholder for internal Python strict test compatibility macro.
+# Placeholder for internal Python strict library compatibility macro.
+
+package(
+    default_visibility = [
+        "//visibility:public",
+    ],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+py_library(
+    name = "test_utils",
+    testonly = 1,
+    srcs = [
+        "test_utils.py",
+    ],
+    visibility = ["//tensorflow_lite_support/metadata/python/tests:__subpackages__"],
+)
+
+py_test(
+    name = "metadata_writer_test",
+    srcs = ["metadata_writer_test.py"],
+    data = [
+        "//tensorflow_lite_support/metadata/python/tests/testdata:test_files",
+        "//tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier:test_files",
+        "//tensorflow_lite_support/metadata/python/tests/testdata/question_answerer:test_files",
+    ],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_writer",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_test(
+    name = "metadata_info_test",
+    srcs = ["metadata_info_test.py"],
+    data = [
+        "//tensorflow_lite_support/metadata/python/tests/testdata:test_files",
+        "//tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier:test_files",
+        "//tensorflow_lite_support/metadata/python/tests/testdata/image_classifier:test_files",
+    ],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata:schema_py",
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "@absl_py//absl/testing:parameterized",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_test(
+    name = "writer_utils_test",
+    srcs = ["writer_utils_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/object_detector:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:schema_py",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:writer_utils",
+    ],
+)
+
+py_test(
+    name = "image_classifier_test",
+    srcs = ["image_classifier_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/image_classifier:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:image_classifier",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "@absl_py//absl/testing:parameterized",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_test(
+    name = "object_detector_test",
+    srcs = ["object_detector_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/object_detector:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:object_detector",
+        "@absl_py//absl/testing:parameterized",
+    ],
+)
+
+py_test(
+    name = "image_segmenter_test",
+    srcs = ["image_segmenter_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata/python/metadata_writers:image_segmenter",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_test(
+    name = "nl_classifier_test",
+    srcs = ["nl_classifier_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:nl_classifier",
+        "@flatbuffers//:runtime_py",
+    ],
+)
+
+py_test(
+    name = "audio_classifier_test",
+    srcs = ["audio_classifier_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata:metadata_schema_py",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:audio_classifier",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+        "@absl_py//absl/testing:parameterized",
+    ],
+)
+
+py_test(
+    name = "bert_nl_classifier_test",
+    srcs = ["bert_nl_classifier_test.py"],
+    data = ["//tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier:test_files"],
+    python_version = "PY3",
+    srcs_version = "PY3",
+    deps = [
+        ":test_utils",
+        # build rule placeholder: tensorflow dep,
+        "//tensorflow_lite_support/metadata/python:metadata",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:bert_nl_classifier",
+        "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/audio_classifier_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/audio_classifier_test.py
new file mode 100644
index 0000000..643f30e7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/audio_classifier_test.py
@@ -0,0 +1,183 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for AudioClassifier.MetadataWriter."""
+
+from absl.testing import parameterized
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python.metadata_writers import audio_classifier
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_FIXED_INPUT_SIZE_MODEL = "../testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.tflite"
+_DYNAMIC_INPUT_SIZE_MODEL = "../testdata/audio_classifier/yamnet_tfhub.tflite"
+_MULTIHEAD_MODEL = "../testdata/audio_classifier/two_heads.tflite"
+_YAMNET_LABEL_FILE = "../testdata/audio_classifier/yamnet_521_labels.txt"
+_LABEL_FILE = "../testdata/audio_classifier/labelmap.txt"
+_DEFAULT_SCORE_CALIBRATION_VALUE = 0.2
+_JSON_FOR_INFERENCE_DYNAMIC = "../testdata/audio_classifier/yamnet_tfhub.json"
+_JSON_FOR_INFERENCE_FIXED = "../testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.json"
+_JSON_DEFAULT = "../testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6_default.json"
+_JSON_DEFAULT_MULTIHEAD = "../testdata/audio_classifier/two_heads_default.json"
+_JSON_MULTIHEAD = "../testdata/audio_classifier/two_heads.json"
+_SAMPLE_RATE = 2
+_CHANNELS = 1
+
+
+class MetadataWriterTest(tf.test.TestCase):
+
+  def test_create_for_inference_should_succeed_dynamic_input_shape_model(self):
+    writer = audio_classifier.MetadataWriter.create_for_inference(
+        test_utils.load_file(_DYNAMIC_INPUT_SIZE_MODEL), _SAMPLE_RATE,
+        _CHANNELS, [_LABEL_FILE],
+        metadata_info.ScoreCalibrationMd(
+            _metadata_fb.ScoreTransformationType.LOG,
+            _DEFAULT_SCORE_CALIBRATION_VALUE,
+            test_utils.create_calibration_file(self.get_temp_dir())))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_FOR_INFERENCE_DYNAMIC, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_for_inference_should_succeed_with_fixed_input_shape_model(
+      self):
+    writer = audio_classifier.MetadataWriter.create_for_inference(
+        test_utils.load_file(_FIXED_INPUT_SIZE_MODEL), _SAMPLE_RATE, _CHANNELS,
+        [_YAMNET_LABEL_FILE],
+        metadata_info.ScoreCalibrationMd(
+            _metadata_fb.ScoreTransformationType.LOG,
+            _DEFAULT_SCORE_CALIBRATION_VALUE,
+            test_utils.create_calibration_file(self.get_temp_dir())))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_FOR_INFERENCE_FIXED, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_from_metadata_info_by_default_should_succeed(self):
+    writer = audio_classifier.MetadataWriter.create_from_metadata_info(
+        test_utils.load_file(_FIXED_INPUT_SIZE_MODEL))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_DEFAULT, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_from_metadata_info_by_default_succeeds_for_multihead(self):
+    writer = (
+        audio_classifier.MetadataWriter.create_from_metadata_info_for_multihead(
+            test_utils.load_file(_MULTIHEAD_MODEL)))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_DEFAULT_MULTIHEAD, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_from_metadata_info_succeeds_for_multihead(self):
+    calibration_file1 = test_utils.create_calibration_file(
+        self.get_temp_dir(), "score_cali_1.txt")
+    calibration_file2 = test_utils.create_calibration_file(
+        self.get_temp_dir(), "score_cali_2.txt")
+
+    general_md = metadata_info.GeneralMd(name="AudioClassifier")
+    input_md = metadata_info.InputAudioTensorMd(
+        name="audio_clip", sample_rate=_SAMPLE_RATE, channels=_CHANNELS)
+    # The output tensors in the model are: Identity, Identity_1
+    # Create metadata in a different order to test if MetadataWriter can correct
+    # it.
+    output_head_md_1 = metadata_info.ClassificationTensorMd(
+        name="head1",
+        label_files=[
+            metadata_info.LabelFileMd("labels_en_1.txt"),
+            metadata_info.LabelFileMd("labels_cn_1.txt")
+        ],
+        score_calibration_md=metadata_info.ScoreCalibrationMd(
+            _metadata_fb.ScoreTransformationType.LOG,
+            _DEFAULT_SCORE_CALIBRATION_VALUE, calibration_file1),
+        tensor_name="Identity_1")
+    output_head_md_2 = metadata_info.ClassificationTensorMd(
+        name="head2",
+        label_files=[
+            metadata_info.LabelFileMd("labels_en_2.txt"),
+            metadata_info.LabelFileMd("labels_cn_2.txt")
+        ],
+        score_calibration_md=metadata_info.ScoreCalibrationMd(
+            _metadata_fb.ScoreTransformationType.LOG,
+            _DEFAULT_SCORE_CALIBRATION_VALUE, calibration_file2),
+        tensor_name="Identity")
+
+    writer = (
+        audio_classifier.MetadataWriter.create_from_metadata_info_for_multihead(
+            test_utils.load_file(_MULTIHEAD_MODEL), general_md, input_md,
+            [output_head_md_1, output_head_md_2]))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_MULTIHEAD, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class MetadataWriterSampleRateTest(tf.test.TestCase, parameterized.TestCase):
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "negative",
+          "wrong_sample_rate": -1
+      }, {
+          "testcase_name": "zero",
+          "wrong_sample_rate": 0
+      })
+  def test_create_for_inference_fails_with_wrong_sample_rate(
+      self, wrong_sample_rate):
+
+    with self.assertRaises(ValueError) as error:
+      audio_classifier.MetadataWriter.create_for_inference(
+          test_utils.load_file(_DYNAMIC_INPUT_SIZE_MODEL), wrong_sample_rate,
+          _CHANNELS, [_LABEL_FILE],
+          metadata_info.ScoreCalibrationMd(
+              _metadata_fb.ScoreTransformationType.LOG,
+              _DEFAULT_SCORE_CALIBRATION_VALUE,
+              test_utils.create_calibration_file(self.get_temp_dir())))
+
+    self.assertEqual(
+        "sample_rate should be positive, but got {}.".format(wrong_sample_rate),
+        str(error.exception))
+
+
+class MetadataWriterChannelsTest(tf.test.TestCase, parameterized.TestCase):
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "negative",
+          "wrong_channels": -1
+      }, {
+          "testcase_name": "zero",
+          "wrong_channels": 0
+      })
+  def test_create_for_inference_fails_with_wrong_channels(self, wrong_channels):
+
+    with self.assertRaises(ValueError) as error:
+      audio_classifier.MetadataWriter.create_for_inference(
+          test_utils.load_file(_DYNAMIC_INPUT_SIZE_MODEL), _SAMPLE_RATE,
+          wrong_channels, [_LABEL_FILE],
+          metadata_info.ScoreCalibrationMd(
+              _metadata_fb.ScoreTransformationType.LOG,
+              _DEFAULT_SCORE_CALIBRATION_VALUE,
+              test_utils.create_calibration_file(self.get_temp_dir())))
+
+    self.assertEqual(
+        "channels should be positive, but got {}.".format(wrong_channels),
+        str(error.exception))
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/bert_nl_classifier_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/bert_nl_classifier_test.py
new file mode 100644
index 0000000..730af7e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/bert_nl_classifier_test.py
@@ -0,0 +1,70 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for bert_nl_classifier.MetadataWriter."""
+
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import bert_nl_classifier
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_TEST_DIR = "tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/"
+_MODEL = "../testdata/bert_nl_classifier/bert_nl_classifier_no_metadata.tflite"
+_LABEL_FILE = _TEST_DIR + "labels.txt"
+_VOCAB_FILE = _TEST_DIR + "mobilebert_vocab.txt"
+_SP_MODEL_FILE = _TEST_DIR + "30k-clean.model"
+_DELIM_REGEX_PATTERN = r"[^\w\']+"
+_JSON_FOR_INFERENCE_WITH_BERT = "../testdata/bert_nl_classifier/bert_nl_classifier_with_bert_tokenizer.json"
+_JSON_FOR_INFERENCE_WITH_SENTENCE_PIECE = "../testdata/bert_nl_classifier/bert_nl_classifier_with_sentence_piece.json"
+_JSON_DEFAULT = "../testdata/bert_nl_classifier/bert_nl_classifier_default.json"
+
+
+class MetadataWriterTest(tf.test.TestCase):
+
+  def test_create_for_inference_with_bert_should_succeed(self):
+    writer = bert_nl_classifier.MetadataWriter.create_for_inference(
+        test_utils.load_file(_MODEL),
+        metadata_info.BertTokenizerMd(_VOCAB_FILE), [_LABEL_FILE])
+
+    displayer = _metadata.MetadataDisplayer.with_model_buffer(writer.populate())
+    metadata_json = displayer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_FOR_INFERENCE_WITH_BERT, "r")
+
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_for_inference_with_sentence_piece_should_succeed(self):
+    writer = bert_nl_classifier.MetadataWriter.create_for_inference(
+        test_utils.load_file(_MODEL),
+        metadata_info.SentencePieceTokenizerMd(_SP_MODEL_FILE), [_LABEL_FILE])
+
+    displayer = _metadata.MetadataDisplayer.with_model_buffer(writer.populate())
+    metadata_json = displayer.get_metadata_json()
+    expected_json = test_utils.load_file(
+        _JSON_FOR_INFERENCE_WITH_SENTENCE_PIECE, "r")
+
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_from_metadata_info_by_default_should_succeed(self):
+    writer = bert_nl_classifier.MetadataWriter.create_from_metadata_info(
+        test_utils.load_file(_MODEL))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_DEFAULT, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/image_classifier_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/image_classifier_test.py
new file mode 100644
index 0000000..5035d43d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/image_classifier_test.py
@@ -0,0 +1,83 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for ImageClassifier.MetadataWriter."""
+
+from absl.testing import parameterized
+
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python.metadata_writers import image_classifier
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_FLOAT_MODEL = "../testdata/image_classifier/mobilenet_v2_1.0_224.tflite"
+_QUANT_MODEL = "../testdata/image_classifier/mobilenet_v2_1.0_224_quant.tflite"
+_LABEL_FILE = "../testdata/image_classifier/labels.txt"
+_SCORE_CALIBRATION_FILE = "../testdata/image_classifier/score_calibration.txt"
+_DEFAULT_SCORE_CALIBRATION_VALUE = 0.2
+_NORM_MEAN = 127.5
+_NORM_STD = 127.5
+_FLOAT_JSON_FOR_INFERENCE = "../testdata/image_classifier/mobilenet_v2_1.0_224.json"
+_FLOAT_JSON_DEFAULT = "../testdata/image_classifier/mobilenet_v2_1.0_224_default.json"
+_QUANT_JSON_FOR_INFERENCE = "../testdata/image_classifier/mobilenet_v2_1.0_224_quant.json"
+_JSON_DEFAULT = "../testdata/image_classifier/mobilenet_v2_1.0_224_default.json"
+
+
+class MetadataWriterTest(tf.test.TestCase, parameterized.TestCase):
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "float_model",
+          "model_file": _FLOAT_MODEL,
+          "golden_json": _FLOAT_JSON_FOR_INFERENCE
+      }, {
+          "testcase_name": "quant_model",
+          "model_file": _QUANT_MODEL,
+          "golden_json": _QUANT_JSON_FOR_INFERENCE
+      })
+  def test_create_for_inference_should_succeed(self, model_file, golden_json):
+    writer = image_classifier.MetadataWriter.create_for_inference(
+        test_utils.load_file(model_file), [_NORM_MEAN], [_NORM_STD],
+        [_LABEL_FILE],
+        metadata_info.ScoreCalibrationMd(
+            _metadata_fb.ScoreTransformationType.LOG,
+            _DEFAULT_SCORE_CALIBRATION_VALUE,
+            test_utils.get_resource_path(_SCORE_CALIBRATION_FILE)))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(golden_json, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "float_model",
+          "model_file": _FLOAT_MODEL,
+      }, {
+          "testcase_name": "quant_model",
+          "model_file": _QUANT_MODEL,
+      })
+  def test_create_from_metadata_info_by_default_should_succeed(
+      self, model_file):
+    writer = image_classifier.MetadataWriter.create_from_metadata_info(
+        test_utils.load_file(model_file))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_DEFAULT, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/image_segmenter_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/image_segmenter_test.py
new file mode 100644
index 0000000..b7b5147
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/image_segmenter_test.py
@@ -0,0 +1,50 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for image_segmenter.MetadataWriter."""
+
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata.python.metadata_writers import image_segmenter
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_MODEL = "../testdata/image_segmenter/deeplabv3.tflite"
+_LABEL_FILE = "../testdata/image_segmenter/labelmap.txt"
+_NORM_MEAN = 127.5
+_NORM_STD = 127.5
+_JSON_FOR_INFERENCE = "../testdata/image_segmenter/deeplabv3.json"
+_JSON_DEFAULT = "../testdata/image_segmenter/deeplabv3_default.json"
+
+
+class MetadataWriterTest(tf.test.TestCase):
+
+  def test_create_for_inference_should_succeed(self):
+    writer = image_segmenter.MetadataWriter.create_for_inference(
+        test_utils.load_file(_MODEL), [_NORM_MEAN], [_NORM_STD], [_LABEL_FILE])
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_FOR_INFERENCE, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_from_metadata_info_by_default_should_succeed(self):
+    writer = image_segmenter.MetadataWriter.create_from_metadata_info(
+        test_utils.load_file(_MODEL))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_DEFAULT, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/metadata_info_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/metadata_info_test.py
new file mode 100644
index 0000000..f860f5b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/metadata_info_test.py
@@ -0,0 +1,491 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for metadata info classes."""
+
+from absl.testing import parameterized
+import tensorflow as tf
+
+import flatbuffers
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_SCORE_CALIBRATION_FILE = test_utils.get_resource_path(
+    "../testdata/image_classifier/score_calibration.txt")
+
+
+class GeneralMdTest(tf.test.TestCase):
+
+  _EXPECTED_GENERAL_META_JSON = "../testdata/general_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    general_md = metadata_info.GeneralMd(
+        name="model",
+        version="v1",
+        description="A ML model.",
+        author="TensorFlow",
+        licenses="Apache")
+    general_metadata = general_md.create_metadata()
+
+    # Create the Flatbuffers object and convert it to the json format.
+    builder = flatbuffers.Builder(0)
+    builder.Finish(
+        general_metadata.Pack(builder),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    metadata_json = _metadata.convert_to_json(bytes(builder.Output()))
+
+    expected_json = test_utils.load_file(self._EXPECTED_GENERAL_META_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class AssociatedFileMdTest(tf.test.TestCase):
+
+  _EXPECTED_META_JSON = "../testdata/associated_file_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    file_md = metadata_info.AssociatedFileMd(
+        file_path="label.txt",
+        description="The label file.",
+        file_type=_metadata_fb.AssociatedFileType.TENSOR_AXIS_LABELS,
+        locale="en")
+    file_metadata = file_md.create_metadata()
+
+    # Create the Flatbuffers object and convert it to the json format.
+    model_metadata = _metadata_fb.ModelMetadataT()
+    model_metadata.associatedFiles = [file_metadata]
+    builder = flatbuffers.Builder(0)
+    builder.Finish(
+        model_metadata.Pack(builder),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    metadata_json = _metadata.convert_to_json(bytes(builder.Output()))
+
+    expected_json = test_utils.load_file(self._EXPECTED_META_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class TensorMdTest(tf.test.TestCase, parameterized.TestCase):
+
+  _TENSOR_NAME = "input"
+  _TENSOR_DESCRIPTION = "The input tensor."
+  _TENSOR_MIN = 0
+  _TENSOR_MAX = 1
+  _LABEL_FILE_EN = "labels.txt"
+  _LABEL_FILE_CN = "labels_cn.txt"  # Locale label file in Chinese.
+  _EXPECTED_FEATURE_TENSOR_JSON = "../testdata/feature_tensor_meta.json"
+  _EXPECTED_IMAGE_TENSOR_JSON = "../testdata/image_tensor_meta.json"
+  _EXPECTED_BOUNDING_BOX_TENSOR_JSON = "../testdata/bounding_box_tensor_meta.json"
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "feature_tensor",
+          "content_type": _metadata_fb.ContentProperties.FeatureProperties,
+          "golden_json": _EXPECTED_FEATURE_TENSOR_JSON
+      }, {
+          "testcase_name": "image_tensor",
+          "content_type": _metadata_fb.ContentProperties.ImageProperties,
+          "golden_json": _EXPECTED_IMAGE_TENSOR_JSON
+      }, {
+          "testcase_name": "bounding_box_tensor",
+          "content_type": _metadata_fb.ContentProperties.BoundingBoxProperties,
+          "golden_json": _EXPECTED_BOUNDING_BOX_TENSOR_JSON
+      })
+  def test_create_metadata_should_succeed(self, content_type, golden_json):
+    associated_file1 = metadata_info.AssociatedFileMd(
+        file_path=self._LABEL_FILE_EN, locale="en")
+    associated_file2 = metadata_info.AssociatedFileMd(
+        file_path=self._LABEL_FILE_CN, locale="cn")
+
+    tensor_md = metadata_info.TensorMd(
+        name=self._TENSOR_NAME,
+        description=self._TENSOR_DESCRIPTION,
+        min_values=[self._TENSOR_MIN],
+        max_values=[self._TENSOR_MAX],
+        content_type=content_type,
+        associated_files=[associated_file1, associated_file2])
+    tensor_metadata = tensor_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(tensor_metadata))
+    expected_json = test_utils.load_file(golden_json, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class InputImageTensorMdTest(tf.test.TestCase, parameterized.TestCase):
+
+  _NAME = "image"
+  _DESCRIPTION = "The input image."
+  _NORM_MEAN = (0, 127.5, 255)
+  _NORM_STD = (127.5, 127.5, 127.5)
+  _COLOR_SPACE_TYPE = _metadata_fb.ColorSpaceType.RGB
+  _EXPECTED_FLOAT_TENSOR_JSON = "../testdata/input_image_tensor_float_meta.json"
+  _EXPECTED_UINT8_TENSOR_JSON = "../testdata/input_image_tensor_uint8_meta.json"
+  _EXPECTED_UNSUPPORTED_TENSOR_JSON = "../testdata/input_image_tensor_unsupported_meta.json"
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "float",
+          "tensor_type": _schema_fb.TensorType.FLOAT32,
+          "golden_json": _EXPECTED_FLOAT_TENSOR_JSON
+      }, {
+          "testcase_name": "uint8",
+          "tensor_type": _schema_fb.TensorType.UINT8,
+          "golden_json": _EXPECTED_UINT8_TENSOR_JSON
+      }, {
+          "testcase_name": "unsupported_tensor_type",
+          "tensor_type": _schema_fb.TensorType.INT16,
+          "golden_json": _EXPECTED_UNSUPPORTED_TENSOR_JSON
+      })
+  def test_create_metadata_should_succeed(self, tensor_type, golden_json):
+    tesnor_md = metadata_info.InputImageTensorMd(
+        name=self._NAME,
+        description=self._DESCRIPTION,
+        norm_mean=list(self._NORM_MEAN),
+        norm_std=list(self._NORM_STD),
+        color_space_type=self._COLOR_SPACE_TYPE,
+        tensor_type=tensor_type)
+    tensor_metadata = tesnor_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(tensor_metadata))
+    expected_json = test_utils.load_file(golden_json, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_init_should_throw_exception_with_incompatible_mean_and_std(self):
+    norm_mean = [0]
+    norm_std = [1, 2]
+    with self.assertRaises(ValueError) as error:
+      metadata_info.InputImageTensorMd(norm_mean=norm_mean, norm_std=norm_std)
+    self.assertEqual(
+        f"norm_mean and norm_std are expected to be the same dim. But got "
+        f"{len(norm_mean)} and {len(norm_std)}", str(error.exception))
+
+
+class InputTextTensorMdTest(tf.test.TestCase):
+
+  _NAME = "input text"
+  _DESCRIPTION = "The input string."
+  _VOCAB_FILE = "vocab.txt"
+  _DELIM_REGEX_PATTERN = r"[^\w\']+"
+  _EXPECTED_TENSOR_JSON = "../testdata/input_text_tesnor_meta.json"
+  _EXPECTED_TENSOR_DEFAULT_JSON = "../testdata/input_text_tesnor_default_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    regex_tokenizer_md = metadata_info.RegexTokenizerMd(
+        self._DELIM_REGEX_PATTERN, self._VOCAB_FILE)
+
+    text_tensor_md = metadata_info.InputTextTensorMd(self._NAME,
+                                                     self._DESCRIPTION,
+                                                     regex_tokenizer_md)
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(
+            text_tensor_md.create_metadata()))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_metadata_by_default_should_succeed(self):
+    text_tensor_md = metadata_info.InputTextTensorMd()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(
+            text_tensor_md.create_metadata()))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_DEFAULT_JSON,
+                                         "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_metadata_throws_exception_with_unsupported_tokenizer(self):
+    invalid_tokenzier = metadata_info.BertTokenizerMd("vocab.txt")
+
+    with self.assertRaises(ValueError) as error:
+      tensor_md = metadata_info.InputTextTensorMd(
+          tokenizer_md=invalid_tokenzier)
+      tensor_md.create_metadata()
+
+    self.assertEqual(
+        f"The type of tokenizer_options, {type(invalid_tokenzier)}, is "
+        f"unsupported", str(error.exception))
+
+
+class InputAudioTensorMd(tf.test.TestCase):
+
+  _NAME = "input text"
+  _DESCRIPTION = "The input string."
+  _SAMPLE_RATE = 10
+  _CHANNELS = 2
+  _EXPECTED_TENSOR_JSON = "../testdata/input_audio_tesnor_meta.json"
+  _EXPECTED_TENSOR_DEFAULT_JSON = "../testdata/input_audio_tesnor_default_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    text_tensor_md = metadata_info.InputAudioTensorMd(self._NAME,
+                                                      self._DESCRIPTION,
+                                                      self._SAMPLE_RATE,
+                                                      self._CHANNELS)
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(
+            text_tensor_md.create_metadata()))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_metadata_by_default_should_succeed(self):
+    audio_tensor_md = metadata_info.InputAudioTensorMd()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(
+            audio_tensor_md.create_metadata()))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_DEFAULT_JSON,
+                                         "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_metadata_fail_with_negative_sample_rate(self):
+    negative_sample_rate = -1
+    with self.assertRaises(ValueError) as error:
+      tensor_md = metadata_info.InputAudioTensorMd(
+          sample_rate=negative_sample_rate)
+      tensor_md.create_metadata()
+
+    self.assertEqual(
+        f"sample_rate should be non-negative, but got {negative_sample_rate}.",
+        str(error.exception))
+
+  def test_create_metadata_fail_with_negative_channels(self):
+    negative_channels = -1
+    with self.assertRaises(ValueError) as error:
+      tensor_md = metadata_info.InputAudioTensorMd(channels=negative_channels)
+      tensor_md.create_metadata()
+
+    self.assertEqual(
+        f"channels should be non-negative, but got {negative_channels}.",
+        str(error.exception))
+
+
+class ClassificationTensorMdTest(tf.test.TestCase, parameterized.TestCase):
+
+  _NAME = "probability"
+  _DESCRIPTION = "The classification result tensor."
+  _LABEL_FILE_EN = "labels.txt"
+  _LABEL_FILE_CN = "labels_cn.txt"  # Locale label file in Chinese.
+  _CALIBRATION_DEFAULT_SCORE = 0.2
+  _EXPECTED_FLOAT_TENSOR_JSON = "../testdata/classification_tensor_float_meta.json"
+  _EXPECTED_UINT8_TENSOR_JSON = "../testdata/classification_tensor_uint8_meta.json"
+  _EXPECTED_UNSUPPORTED_TENSOR_JSON = "../testdata/classification_tensor_unsupported_meta.json"
+
+  @parameterized.named_parameters(
+      {
+          "testcase_name": "float",
+          "tensor_type": _schema_fb.TensorType.FLOAT32,
+          "golden_json": _EXPECTED_FLOAT_TENSOR_JSON
+      }, {
+          "testcase_name": "uint8",
+          "tensor_type": _schema_fb.TensorType.UINT8,
+          "golden_json": _EXPECTED_UINT8_TENSOR_JSON
+      }, {
+          "testcase_name": "unsupported_tensor_type",
+          "tensor_type": _schema_fb.TensorType.INT16,
+          "golden_json": _EXPECTED_UNSUPPORTED_TENSOR_JSON
+      })
+  def test_create_metadata_should_succeed(self, tensor_type, golden_json):
+    label_file_en = metadata_info.LabelFileMd(
+        file_path=self._LABEL_FILE_EN, locale="en")
+    label_file_cn = metadata_info.LabelFileMd(
+        file_path=self._LABEL_FILE_CN, locale="cn")
+    score_calibration_md = metadata_info.ScoreCalibrationMd(
+        _metadata_fb.ScoreTransformationType.IDENTITY,
+        self._CALIBRATION_DEFAULT_SCORE, _SCORE_CALIBRATION_FILE)
+
+    tesnor_md = metadata_info.ClassificationTensorMd(
+        name=self._NAME,
+        description=self._DESCRIPTION,
+        label_files=[label_file_en, label_file_cn],
+        tensor_type=tensor_type,
+        score_calibration_md=score_calibration_md)
+    tensor_metadata = tesnor_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(tensor_metadata))
+    expected_json = test_utils.load_file(golden_json, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class CategoryTensorMdTest(tf.test.TestCase, parameterized.TestCase):
+
+  _NAME = "category"
+  _DESCRIPTION = "The category tensor."
+  _LABEL_FILE_EN = "labels.txt"
+  _LABEL_FILE_CN = "labels_cn.txt"  # Locale label file in Chinese.
+  _EXPECTED_TENSOR_JSON = "../testdata/category_tensor_float_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    label_file_en = metadata_info.LabelFileMd(
+        file_path=self._LABEL_FILE_EN, locale="en")
+    label_file_cn = metadata_info.LabelFileMd(
+        file_path=self._LABEL_FILE_CN, locale="cn")
+    tesnor_md = metadata_info.CategoryTensorMd(
+        name=self._NAME,
+        description=self._DESCRIPTION,
+        label_files=[label_file_en, label_file_cn])
+    tensor_metadata = tesnor_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_tensor(tensor_metadata))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class RegexTokenizerMdTest(tf.test.TestCase):
+
+  _VOCAB_FILE = "vocab.txt"
+  _DELIM_REGEX_PATTERN = r"[^\w\']+"
+  _EXPECTED_TENSOR_JSON = "../testdata/regex_tokenizer_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    tokenizer_md = metadata_info.RegexTokenizerMd(self._DELIM_REGEX_PATTERN,
+                                                  self._VOCAB_FILE)
+    tokenizer_metadata = tokenizer_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_process_uint(tokenizer_metadata))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class BertTokenizerMdTest(tf.test.TestCase):
+
+  _VOCAB_FILE = "vocab.txt"
+  _EXPECTED_TENSOR_JSON = "../testdata/bert_tokenizer_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    tokenizer_md = metadata_info.BertTokenizerMd(self._VOCAB_FILE)
+    tokenizer_metadata = tokenizer_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_process_uint(tokenizer_metadata))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class SentencePieceTokenizerMdTest(tf.test.TestCase):
+
+  _VOCAB_FILE = "vocab.txt"
+  _SP_MODEL = "sp.model"
+  _EXPECTED_TENSOR_JSON = "../testdata/sentence_piece_tokenizer_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    tokenizer_md = metadata_info.SentencePieceTokenizerMd(
+        self._SP_MODEL, self._VOCAB_FILE)
+    tokenizer_metadata = tokenizer_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_process_uint(tokenizer_metadata))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+class ScoreCalibrationMdTest(tf.test.TestCase):
+  _DEFAULT_VALUE = 0.2
+  _EXPECTED_TENSOR_JSON = "../testdata/score_calibration_tensor_meta.json"
+  _EXPECTED_MODEL_META_JSON = "../testdata/score_calibration_file_meta.json"
+
+  def test_create_metadata_should_succeed(self):
+    score_calibration_md = metadata_info.ScoreCalibrationMd(
+        _metadata_fb.ScoreTransformationType.LOG, self._DEFAULT_VALUE,
+        _SCORE_CALIBRATION_FILE)
+    score_calibration_metadata = score_calibration_md.create_metadata()
+
+    metadata_json = _metadata.convert_to_json(
+        _create_dummy_model_metadata_with_process_uint(
+            score_calibration_metadata))
+    expected_json = test_utils.load_file(self._EXPECTED_TENSOR_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_score_calibration_file_md_should_succeed(self):
+    score_calibration_md = metadata_info.ScoreCalibrationMd(
+        _metadata_fb.ScoreTransformationType.LOG, self._DEFAULT_VALUE,
+        _SCORE_CALIBRATION_FILE)
+    score_calibration_file_md = (
+        score_calibration_md.create_score_calibration_file_md())
+    file_metadata = score_calibration_file_md.create_metadata()
+
+    # Create the Flatbuffers object and convert it to the json format.
+    model_metadata = _metadata_fb.ModelMetadataT()
+    model_metadata.associatedFiles = [file_metadata]
+    builder = flatbuffers.Builder(0)
+    builder.Finish(
+        model_metadata.Pack(builder),
+        _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+    metadata_json = _metadata.convert_to_json(bytes(builder.Output()))
+
+    expected_json = test_utils.load_file(self._EXPECTED_MODEL_META_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_score_calibration_file_fails_with_less_colunms(self):
+    malformed_calibration_file = test_utils.create_calibration_file(
+        self.get_temp_dir(), content="1.0,0.2")
+
+    with self.assertRaisesRegex(
+        ValueError,
+        "Expected empty lines or 3 or 4 parameters per line in score" +
+        " calibration file, but got 2."):
+      metadata_info.ScoreCalibrationMd(_metadata_fb.ScoreTransformationType.LOG,
+                                       self._DEFAULT_VALUE,
+                                       malformed_calibration_file)
+
+  def test_create_score_calibration_file_fails_with_negative_scale(self):
+    malformed_calibration_file = test_utils.create_calibration_file(
+        self.get_temp_dir(), content="-1.0,0.2,0.1")
+
+    with self.assertRaisesRegex(
+        ValueError, "Expected scale to be a non-negative value, but got -1.0."):
+      metadata_info.ScoreCalibrationMd(_metadata_fb.ScoreTransformationType.LOG,
+                                       self._DEFAULT_VALUE,
+                                       malformed_calibration_file)
+
+
+def _create_dummy_model_metadata_with_tensor(
+    tensor_metadata: _metadata_fb.TensorMetadataT) -> bytes:
+  # Create a dummy model using the tensor metadata.
+  subgraph_metadata = _metadata_fb.SubGraphMetadataT()
+  subgraph_metadata.inputTensorMetadata = [tensor_metadata]
+  model_metadata = _metadata_fb.ModelMetadataT()
+  model_metadata.subgraphMetadata = [subgraph_metadata]
+
+  # Create the Flatbuffers object and convert it to the json format.
+  builder = flatbuffers.Builder(0)
+  builder.Finish(
+      model_metadata.Pack(builder),
+      _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+  return bytes(builder.Output())
+
+
+def _create_dummy_model_metadata_with_process_uint(
+    process_unit_metadata: _metadata_fb.ProcessUnitT) -> bytes:
+  # Create a dummy model using the tensor metadata.
+  subgraph_metadata = _metadata_fb.SubGraphMetadataT()
+  subgraph_metadata.inputProcessUnits = [process_unit_metadata]
+  model_metadata = _metadata_fb.ModelMetadataT()
+  model_metadata.subgraphMetadata = [subgraph_metadata]
+
+  # Create the Flatbuffers object and convert it to the json format.
+  builder = flatbuffers.Builder(0)
+  builder.Finish(
+      model_metadata.Pack(builder),
+      _metadata.MetadataPopulator.METADATA_FILE_IDENTIFIER)
+  return bytes(builder.Output())
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/metadata_writer_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/metadata_writer_test.py
new file mode 100644
index 0000000..574da0f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/metadata_writer_test.py
@@ -0,0 +1,203 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for MetadataWriter."""
+
+import os
+import tensorflow as tf
+
+from tensorflow.python.platform import resource_loader
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_writer
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_MODEL = "../testdata/mobilenet_v2_1.0_224_quant.tflite"
+_MULTI_INPUTS_MODEL = "../testdata/question_answerer/mobilebert_float.tflite"
+_MULTI_OUTPUTS_MODEL = "../testdata/audio_classifier/two_heads.tflite"
+_MODEL_NAME = "mobilenet_v2_1.0_224_quant"
+_INPUT_NAME = "image"
+_OUTPUT_NAME = "probability"
+_LABEL_FILE = resource_loader.get_path_to_datafile("../testdata/labels.txt")
+_EXPECTED_DUMMY_JSON = "../testdata/mobilenet_v2_1.0_224_quant_dummy.json"
+_EXPECTED_META_INFO_JSON = "../testdata/mobilenet_v2_1.0_224_quant_meta_info_.json"
+_EXPECTED_DEFAULT_JSON = "../testdata/mobilenet_v2_1.0_224_quant_default.json"
+# Before populated into the model, metadata does not have the verson string
+_EXPECTED_DUMMY_NO_VERSION_JSON = "../testdata/mobilenet_v2_1.0_224_quant_dummy_no_version.json"
+_EXPECTED_MULTI_INPUTS_JSON = "../testdata/multi_inputs.json"
+_EXPECTED_MULTI_OUTPUTS_JSON = "../testdata/multi_outputs.json"
+
+
+class MetadataWriterTest(tf.test.TestCase):
+
+  def test_populate_from_metadata_should_succeed(self):
+    model_buffer = test_utils.load_file(_MODEL)
+    model_metadata, input_metadata, output_metadata = (
+        self._create_dummy_metadata())
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata(
+        model_buffer, model_metadata, [input_metadata], [output_metadata],
+        [_LABEL_FILE])
+    model_with_metadata = writer.populate()
+
+    self._assert_correct_metadata(model_with_metadata, _EXPECTED_DUMMY_JSON,
+                                  _LABEL_FILE)
+
+  def test_create_from_metadata_with_default_value_should_succeed(self):
+    model_buffer = test_utils.load_file(_MODEL)
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata(model_buffer)
+    model_with_metadata = writer.populate()
+
+    self._assert_correct_metadata(model_with_metadata, _EXPECTED_DEFAULT_JSON)
+
+  def test_populate_create_from_metadata_info_should_succeed(self):
+    model_buffer = test_utils.load_file(_MODEL)
+    general_md = metadata_info.GeneralMd(name=_MODEL_NAME)
+    input_md = metadata_info.TensorMd(name=_INPUT_NAME)
+    output_md = metadata_info.TensorMd(name=_OUTPUT_NAME)
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata_info(
+        model_buffer, general_md, [input_md], [output_md], [_LABEL_FILE])
+    model_with_metadata = writer.populate()
+
+    self._assert_correct_metadata(model_with_metadata, _EXPECTED_META_INFO_JSON,
+                                  _LABEL_FILE)
+
+  def test_create_from_metadata_info_with_default_value_should_succeed(self):
+    model_buffer = test_utils.load_file(_MODEL)
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata_info(
+        model_buffer)
+    model_with_metadata = writer.populate()
+
+    self._assert_correct_metadata(model_with_metadata, _EXPECTED_DEFAULT_JSON)
+
+  def test_create_from_metadata_info_with_input_tensor_name_should_succeed(
+      self):
+    model_buffer = test_utils.load_file(_MULTI_INPUTS_MODEL)
+    # The input tensors in the model are: input_ids, input_mask, segment_ids.
+    input_md_1 = metadata_info.TensorMd(name="ids", tensor_name="input_ids")
+    input_md_2 = metadata_info.TensorMd(name="mask", tensor_name="input_mask")
+    input_md_3 = metadata_info.TensorMd(
+        name="segment", tensor_name="segment_ids")
+
+    # Create input metadata in a different order to test if MetadataWriter can
+    # correct it.
+    writer = metadata_writer.MetadataWriter.create_from_metadata_info(
+        model_buffer, input_md=[input_md_2, input_md_3, input_md_1])
+    model_with_metadata = writer.populate()
+
+    self._assert_correct_metadata(model_with_metadata,
+                                  _EXPECTED_MULTI_INPUTS_JSON)
+
+  def test_create_from_metadata_info_fails_with_wrong_input_tesnor_name(self):
+    model_buffer = test_utils.load_file(_MODEL)
+    input_md = metadata_info.TensorMd(tensor_name="wrong_tensor_name")
+    with self.assertRaises(ValueError) as error:
+      metadata_writer.MetadataWriter.create_from_metadata_info(
+          model_buffer, input_md=[input_md])
+    self.assertEqual(
+        "The tensor names from arguments (['wrong_tensor_name']) do not match"
+        " the tensor names read from the model (['input']).",
+        str(error.exception))
+
+  def test_create_from_metadata_info_with_output_tensor_name_should_succeed(
+      self):
+    model_buffer = test_utils.load_file(_MULTI_OUTPUTS_MODEL)
+    # The output tensors in the model are: Identity, Identity_1
+    output_md_1 = metadata_info.TensorMd(
+        name="Identity", tensor_name="Identity")
+    output_md_2 = metadata_info.TensorMd(
+        name="Identity 1", tensor_name="Identity_1")
+
+    # Create output metadata in a different order to test if MetadataWriter can
+    # correct it.
+    writer = metadata_writer.MetadataWriter.create_from_metadata_info(
+        model_buffer, output_md=[output_md_2, output_md_1])
+    model_with_metadata = writer.populate()
+
+    self._assert_correct_metadata(model_with_metadata,
+                                  _EXPECTED_MULTI_OUTPUTS_JSON)
+
+  def test_create_from_metadata_info_fails_with_wrong_output_tesnor_name(self):
+    model_buffer = test_utils.load_file(_MODEL)
+    output_md = metadata_info.TensorMd(tensor_name="wrong_tensor_name")
+    with self.assertRaises(ValueError) as error:
+      metadata_writer.MetadataWriter.create_from_metadata_info(
+          model_buffer, output_md=[output_md])
+    self.assertEqual(
+        "The tensor names from arguments (['wrong_tensor_name']) do not match"
+        " the tensor names read from the model (['output']).",
+        str(error.exception))
+
+  def test_get_metadata_json_should_succeed(self):
+    model_buffer = test_utils.load_file(_MODEL)
+    model_metadata, input_metadata, output_metadata = (
+        self._create_dummy_metadata())
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata(
+        model_buffer, model_metadata, [input_metadata], [output_metadata],
+        [_LABEL_FILE])
+    metadata_json = writer.get_metadata_json()
+
+    expected_json = test_utils.load_file(_EXPECTED_DUMMY_NO_VERSION_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_get_populated_metadata_json_should_succeed(self):
+    model_buffer = test_utils.load_file(_MODEL)
+    model_metadata, input_metadata, output_metadata = (
+        self._create_dummy_metadata())
+
+    writer = metadata_writer.MetadataWriter.create_from_metadata(
+        model_buffer, model_metadata, [input_metadata], [output_metadata],
+        [_LABEL_FILE])
+    metadata_json = writer.get_populated_metadata_json()
+
+    expected_json = test_utils.load_file(_EXPECTED_DUMMY_JSON, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def _assert_correct_metadata(self,
+                               model_with_metadata,
+                               expected_json_file,
+                               expected_label_file=None):
+    # Verify if the metadata populated is correct.
+    displayer = _metadata.MetadataDisplayer.with_model_buffer(
+        model_with_metadata)
+    metadata_json = displayer.get_metadata_json()
+    expected_json = test_utils.load_file(expected_json_file, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+    # Verify if the associated file is packed as expected.
+    if expected_label_file:
+      packed_files = displayer.get_packed_associated_file_list()
+      expected_packed_files = [os.path.basename(expected_label_file)]
+      self.assertEqual(set(packed_files), set(expected_packed_files))
+
+  def _create_dummy_metadata(self):
+    # Create dummy input metadata
+    input_metadata = _metadata_fb.TensorMetadataT()
+    input_metadata.name = _INPUT_NAME
+    # Create dummy output metadata
+    output_metadata = _metadata_fb.TensorMetadataT()
+    output_metadata.name = _OUTPUT_NAME
+    # Create dummy model_metadata
+    model_metadata = _metadata_fb.ModelMetadataT()
+    model_metadata.name = _MODEL_NAME
+    return model_metadata, input_metadata, output_metadata
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/nl_classifier_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/nl_classifier_test.py
new file mode 100644
index 0000000..eda6913
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/nl_classifier_test.py
@@ -0,0 +1,56 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for nl_classifier.MetadataWriter."""
+
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata.python import metadata as _metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import nl_classifier
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_TEST_DIR = "tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/"
+_MODEL = "../testdata/nl_classifier/movie_review.tflite"
+_LABEL_FILE = _TEST_DIR + "labels.txt"
+_VOCAB_FILE = _TEST_DIR + "vocab.txt"
+_DELIM_REGEX_PATTERN = r"[^\w\']+"
+_JSON_FOR_INFERENCE_REGEX = "../testdata/nl_classifier/movie_review_regex.json"
+_JSON_DEFAULT = "../testdata/nl_classifier/movie_review_default.json"
+
+
+class MetadataWriterTest(tf.test.TestCase):
+
+  def test_create_for_inference_should_succeed(self):
+    writer = nl_classifier.MetadataWriter.create_for_inference(
+        test_utils.load_file(_MODEL),
+        metadata_info.RegexTokenizerMd(_DELIM_REGEX_PATTERN, _VOCAB_FILE),
+        [_LABEL_FILE])
+
+    displayer = _metadata.MetadataDisplayer.with_model_buffer(writer.populate())
+    metadata_json = displayer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_FOR_INFERENCE_REGEX, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def test_create_from_metadata_info_by_default_should_succeed(self):
+    writer = nl_classifier.MetadataWriter.create_from_metadata_info(
+        test_utils.load_file(_MODEL))
+
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(_JSON_DEFAULT, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/object_detector_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/object_detector_test.py
new file mode 100644
index 0000000..ddb6d68
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/object_detector_test.py
@@ -0,0 +1,129 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for ObjectDetector.MetadataWriter."""
+
+import json
+import os
+import tempfile
+
+from absl.testing import parameterized
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata import metadata_schema_py_generated as _metadata_fb
+from tensorflow_lite_support.metadata.python import metadata
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import object_detector
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_PATH = "../testdata/object_detector/"
+_MODEL = "../testdata/object_detector/ssd_mobilenet_v1.tflite"
+_LABEL_FILE = "../testdata/object_detector/labelmap.txt"
+_NORM_MEAN = 127.5
+_NORM_STD = 127.5
+_JSON_FOR_INFERENCE = "../testdata/object_detector/ssd_mobilenet_v1.json"
+_JSON_DEFAULT = "../testdata/object_detector/ssd_mobilenet_v1_default.json"
+
+_MODEL_COCO = "../testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_no_metadata.tflite"
+_SCORE_CALIBRATION_FILE = "../testdata/object_detector/score_calibration.csv"
+_SCORE_CALIBRATION_DEFAULT_SCORE = 0.2
+_JSON_FOR_SCORE_CALIBRATION = "../testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration.json"
+
+_DUMMY_SCORE_CALIBRATION_FILE = "../testdata/object_detector/score_calibration_dummy.csv"
+_DUMMY_SCORE_CALIBRATION_DEFAULT_SCORE = 0.0
+_JSON_FOR_DUMMY_SCORE_CALIBRATION = "../testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration_dummy.json"
+_EXPECTED_DUMMY_MODEL = "../testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite"
+
+
+class MetadataWriterTest(tf.test.TestCase, parameterized.TestCase):
+
+  def setUp(self):
+    super().setUp()
+    self._label_file = test_utils.get_resource_path(_LABEL_FILE)
+    self._score_file = test_utils.get_resource_path(_SCORE_CALIBRATION_FILE)
+    self._dummy_score_file = test_utils.get_resource_path(
+        _DUMMY_SCORE_CALIBRATION_FILE)
+
+  @parameterized.parameters(
+      ("ssd_mobilenet_v1"),
+      ("efficientdet_lite0_v1"),
+  )
+  def test_create_for_inference_should_succeed(self, model_name):
+    model_path = os.path.join(_PATH, model_name + ".tflite")
+    writer = object_detector.MetadataWriter.create_for_inference(
+        test_utils.load_file(model_path), [_NORM_MEAN], [_NORM_STD],
+        [self._label_file])
+
+    json_path = os.path.join(_PATH, model_name + ".json")
+    self._validate_metadata(writer, json_path)
+    self._validate_populated_model(writer)
+
+  @parameterized.parameters(
+      ("ssd_mobilenet_v1"),
+      ("efficientdet_lite0_v1"),
+  )
+  def test_create_from_metadata_info_by_default_should_succeed(
+      self, model_name: str):
+    model_path = os.path.join(_PATH, model_name + ".tflite")
+    writer = object_detector.MetadataWriter.create_from_metadata_info(
+        test_utils.load_file(model_path))
+    json_path = os.path.join(_PATH, model_name + "_default.json")
+    self._validate_metadata(writer, json_path)
+    self._validate_populated_model(writer)
+
+  def test_create_for_inference_score_calibration_should_succeed(self):
+    score_calibration_md = metadata_info.ScoreCalibrationMd(
+        _metadata_fb.ScoreTransformationType.INVERSE_LOGISTIC,
+        _SCORE_CALIBRATION_DEFAULT_SCORE,
+        self._score_file,
+    )
+    writer = object_detector.MetadataWriter.create_for_inference(
+        test_utils.load_file(_MODEL_COCO), [_NORM_MEAN], [_NORM_STD],
+        [self._label_file], score_calibration_md)
+    self._validate_metadata(writer, _JSON_FOR_SCORE_CALIBRATION)
+    self._validate_populated_model(writer)
+
+  def test_create_for_inference_dummy_score_calibration_should_succeed(self):
+    score_calibration_md = metadata_info.ScoreCalibrationMd(
+        _metadata_fb.ScoreTransformationType.INVERSE_LOGISTIC,
+        _DUMMY_SCORE_CALIBRATION_DEFAULT_SCORE,
+        self._dummy_score_file,
+    )
+    writer = object_detector.MetadataWriter.create_for_inference(
+        test_utils.load_file(_MODEL_COCO), [_NORM_MEAN], [_NORM_STD],
+        [self._label_file], score_calibration_md)
+    self._validate_metadata(writer, _JSON_FOR_DUMMY_SCORE_CALIBRATION)
+    self._validate_populated_model(writer)
+
+    # Test if populated model is equivalent to the expected model.
+    metadata_dict = json.loads(writer.get_metadata_json())
+    displayer = metadata.MetadataDisplayer.with_model_buffer(
+        test_utils.load_file(_EXPECTED_DUMMY_MODEL))
+    expected_metadata_dict = json.loads(displayer.get_metadata_json())
+    self.assertDictContainsSubset(metadata_dict, expected_metadata_dict)
+
+  def _validate_metadata(self, writer, expected_json_file):
+    metadata_json = writer.get_metadata_json()
+    expected_json = test_utils.load_file(expected_json_file, "r")
+    self.assertEqual(metadata_json, expected_json)
+
+  def _validate_populated_model(self, writer):
+    with tempfile.NamedTemporaryFile() as tmp:
+      with open(tmp.name, "wb") as f:
+        f.write(writer.populate())
+      self.assertGreater(os.path.getsize(tmp.name), 0)
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/test_utils.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/test_utils.py
new file mode 100644
index 0000000..52b0ea5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/test_utils.py
@@ -0,0 +1,41 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Test utils for MetadataWriter."""
+
+import os
+from typing import Union
+from tensorflow.python.platform import resource_loader
+
+
+def create_calibration_file(file_dir: str,
+                            file_name: str = "score_calibration.txt",
+                            content: str = "1.0,2.0,3.0,4.0") -> str:
+  """Creates the calibration file."""
+  calibration_file = os.path.join(file_dir, file_name)
+  with open(calibration_file, mode="w") as file:
+    file.write(content)
+  return calibration_file
+
+
+def load_file(file_name: str, mode: str = "rb") -> Union[str, bytes]:
+  """Loads files from resources."""
+  file_path = get_resource_path(file_name)
+  with open(file_path, mode) as file:
+    return file.read()
+
+
+def get_resource_path(file_name: str) -> str:
+  """Gets resource path from the loader."""
+  return resource_loader.get_path_to_datafile(file_name)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/writer_utils_test.py b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/writer_utils_test.py
new file mode 100644
index 0000000..b0502d3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/metadata_writers/writer_utils_test.py
@@ -0,0 +1,121 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for wrtier util methods."""
+
+import array
+import tensorflow as tf
+
+from tensorflow_lite_support.metadata import schema_py_generated as _schema_fb
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
+from tensorflow_lite_support.metadata.python.tests.metadata_writers import test_utils
+
+_FLOAT_TYPE = _schema_fb.TensorType.FLOAT32
+_UINT8_TYPE = _schema_fb.TensorType.UINT8
+# mobilebert_float.tflite has 1 input tensor and 4 output tensors.
+_MODEL_NAME = "../testdata/object_detector/ssd_mobilenet_v1.tflite"
+_IMAGE_TENSOR_INDEX = 0
+_EXPECTED_INPUT_TYPES = _UINT8_TYPE
+_EXPECTED_INPUT_IMAGE_SHAPE = (1, 300, 300, 3)
+_EXPECTED_OUTPUT_TYPES = (_FLOAT_TYPE, _FLOAT_TYPE, _FLOAT_TYPE, _FLOAT_TYPE)
+_EXOECTED_INPUT_TENSOR_NAMES = "normalized_input_image_tensor"
+_EXOECTED_OUTPUT_TENSOR_NAMES = ("TFLite_Detection_PostProcess",
+                                 "TFLite_Detection_PostProcess:1",
+                                 "TFLite_Detection_PostProcess:2",
+                                 "TFLite_Detection_PostProcess:3")
+
+
+class WriterUtilsTest(tf.test.TestCase):
+
+  def test_compute_flat_size(self):
+    shape = array.array("i", [1, 2, 3])
+    expected_flat_size = 6
+
+    flat_size = writer_utils.compute_flat_size(shape)
+    self.assertEqual(flat_size, expected_flat_size)
+
+  def test_compute_flat_size_with_none_shape(self):
+    shape = None
+    expected_flat_size = 0
+
+    flat_size = writer_utils.compute_flat_size(shape)
+    self.assertEqual(flat_size, expected_flat_size)
+
+  def test_get_input_tensor_names(self):
+    tensor_names = writer_utils.get_input_tensor_names(
+        model_buffer=test_utils.load_file(_MODEL_NAME))
+    self.assertEqual(tensor_names, [_EXOECTED_INPUT_TENSOR_NAMES])
+
+  def test_get_output_tensor_names(self):
+    tensor_names = writer_utils.get_output_tensor_names(
+        model_buffer=test_utils.load_file(_MODEL_NAME))
+    self.assertEqual(tensor_names, list(_EXOECTED_OUTPUT_TENSOR_NAMES))
+
+  def test_get_input_tensor_types(self):
+    tensor_types = writer_utils.get_input_tensor_types(
+        model_buffer=test_utils.load_file(_MODEL_NAME))
+    self.assertEqual(tensor_types, [_EXPECTED_INPUT_TYPES])
+
+  def test_get_output_tensor_types(self):
+    tensor_types = writer_utils.get_output_tensor_types(
+        model_buffer=test_utils.load_file(_MODEL_NAME))
+    self.assertEqual(tensor_types, list(_EXPECTED_OUTPUT_TYPES))
+
+  def test_get_input_tensor_shape(self):
+    tensor_shape = writer_utils.get_input_tensor_shape(
+        test_utils.load_file(_MODEL_NAME), _IMAGE_TENSOR_INDEX)
+    self.assertEqual(list(tensor_shape), list(_EXPECTED_INPUT_IMAGE_SHAPE))
+
+  def test_save_and_load_file(self):
+    expected_file_bytes = b"This is a test file."
+    file_path = self.create_tempfile().full_path
+
+    writer_utils.save_file(expected_file_bytes, file_path)
+    file_bytes = writer_utils.load_file(file_path)
+    self.assertEqual(file_bytes, expected_file_bytes)
+
+  def test_get_tokenizer_associated_files_with_bert_tokenizer(self):
+    # Create Bert tokenizer
+    vocab_file = "vocab.txt"
+    tokenizer_md = metadata_info.BertTokenizerMd(vocab_file)
+
+    associated_files = writer_utils.get_tokenizer_associated_files(
+        tokenizer_md.create_metadata().options)
+    self.assertEqual(associated_files, [vocab_file])
+
+  def test_get_tokenizer_associated_files_with_sentence_piece_tokenizer(self):
+    # Create Sentence Piece tokenizer
+    vocab_file = "vocab.txt"
+    sp_model = "sp.model"
+    tokenizer_md = metadata_info.SentencePieceTokenizerMd(sp_model, vocab_file)
+
+    associated_files = writer_utils.get_tokenizer_associated_files(
+        tokenizer_md.create_metadata().options)
+    self.assertEqual(set(associated_files), set([vocab_file, sp_model]))
+
+  def test_get_tokenizer_associated_files_with_regex_tokenizer(self):
+    # Create Regex tokenizer
+    delim_regex_pattern = r"[^\w\']+"
+    vocab_file = "vocab.txt"
+    tokenizer_md = metadata_info.RegexTokenizerMd(delim_regex_pattern,
+                                                  vocab_file)
+
+    associated_files = writer_utils.get_tokenizer_associated_files(
+        tokenizer_md.create_metadata().options)
+    self.assertEqual(associated_files, [vocab_file])
+
+
+if __name__ == "__main__":
+  tf.test.main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/BUILD
new file mode 100644
index 0000000..0f8caca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/associated_file_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/associated_file_meta.json
new file mode 100644
index 0000000..2a3d47b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/associated_file_meta.json
@@ -0,0 +1,10 @@
+{
+  "associated_files": [
+    {
+      "name": "label.txt",
+      "description": "The label file.",
+      "type": "TENSOR_AXIS_LABELS",
+      "locale": "en"
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/BUILD
new file mode 100644
index 0000000..0f8caca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/daredevil_sound_recognizer_320ms.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/daredevil_sound_recognizer_320ms.json
new file mode 100644
index 0000000..8881154
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/daredevil_sound_recognizer_320ms.json
@@ -0,0 +1,63 @@
+{
+  "name": "AudioClassifier",
+  "description": "Identify the most prominent type in the audio clip from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio_clip",
+          "description": "Input audio clip to be classified.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 2,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Scores of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/labelmap.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/labelmap.txt
new file mode 100644
index 0000000..15f635e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/labelmap.txt
@@ -0,0 +1,2 @@
+speech
+laughter
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads.json
new file mode 100644
index 0000000..a572614
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads.json
@@ -0,0 +1,95 @@
+{
+  "name": "AudioClassifier",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio_clip",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 2,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "head2",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labels_en_2.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "labels_cn_2.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_cali_2.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        },
+        {
+          "name": "head1",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labels_en_1.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "labels_cn_1.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_cali_1.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads.tflite
new file mode 100644
index 0000000..5ad4ffe
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads_default.json
new file mode 100644
index 0000000..9f98f84
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/two_heads_default.json
@@ -0,0 +1,29 @@
+{
+  "name": "AudioClassifier",
+  "description": "Identify the most prominent type in the audio clip from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio_clip",
+          "description": "Input audio clip to be classified.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "Identity"
+        },
+        {
+          "name": "Identity_1"
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_521_labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_521_labels.txt
new file mode 100644
index 0000000..c3e864e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_521_labels.txt
@@ -0,0 +1,521 @@
+Speech
+Child speech, kid speaking
+Conversation
+Narration, monologue
+Babbling
+Speech synthesizer
+Shout
+Bellow
+Whoop
+Yell
+Children shouting
+Screaming
+Whispering
+Laughter
+Baby laughter
+Giggle
+Snicker
+Belly laugh
+Chuckle, chortle
+Crying, sobbing
+Baby cry, infant cry
+Whimper
+Wail, moan
+Sigh
+Singing
+Choir
+Yodeling
+Chant
+Mantra
+Child singing
+Synthetic singing
+Rapping
+Humming
+Groan
+Grunt
+Whistling
+Breathing
+Wheeze
+Snoring
+Gasp
+Pant
+Snort
+Cough
+Throat clearing
+Sneeze
+Sniff
+Run
+Shuffle
+Walk, footsteps
+Chewing, mastication
+Biting
+Gargling
+Stomach rumble
+Burping, eructation
+Hiccup
+Fart
+Hands
+Finger snapping
+Clapping
+Heart sounds, heartbeat
+Heart murmur
+Cheering
+Applause
+Chatter
+Crowd
+Hubbub, speech noise, speech babble
+Children playing
+Animal
+Domestic animals, pets
+Dog
+Bark
+Yip
+Howl
+Bow-wow
+Growling
+Whimper (dog)
+Cat
+Purr
+Meow
+Hiss
+Caterwaul
+Livestock, farm animals, working animals
+Horse
+Clip-clop
+Neigh, whinny
+Cattle, bovinae
+Moo
+Cowbell
+Pig
+Oink
+Goat
+Bleat
+Sheep
+Fowl
+Chicken, rooster
+Cluck
+Crowing, cock-a-doodle-doo
+Turkey
+Gobble
+Duck
+Quack
+Goose
+Honk
+Wild animals
+Roaring cats (lions, tigers)
+Roar
+Bird
+Bird vocalization, bird call, bird song
+Chirp, tweet
+Squawk
+Pigeon, dove
+Coo
+Crow
+Caw
+Owl
+Hoot
+Bird flight, flapping wings
+Canidae, dogs, wolves
+Rodents, rats, mice
+Mouse
+Patter
+Insect
+Cricket
+Mosquito
+Fly, housefly
+Buzz
+Bee, wasp, etc.
+Frog
+Croak
+Snake
+Rattle
+Whale vocalization
+Music
+Musical instrument
+Plucked string instrument
+Guitar
+Electric guitar
+Bass guitar
+Acoustic guitar
+Steel guitar, slide guitar
+Tapping (guitar technique)
+Strum
+Banjo
+Sitar
+Mandolin
+Zither
+Ukulele
+Keyboard (musical)
+Piano
+Electric piano
+Organ
+Electronic organ
+Hammond organ
+Synthesizer
+Sampler
+Harpsichord
+Percussion
+Drum kit
+Drum machine
+Drum
+Snare drum
+Rimshot
+Drum roll
+Bass drum
+Timpani
+Tabla
+Cymbal
+Hi-hat
+Wood block
+Tambourine
+Rattle (instrument)
+Maraca
+Gong
+Tubular bells
+Mallet percussion
+Marimba, xylophone
+Glockenspiel
+Vibraphone
+Steelpan
+Orchestra
+Brass instrument
+French horn
+Trumpet
+Trombone
+Bowed string instrument
+String section
+Violin, fiddle
+Pizzicato
+Cello
+Double bass
+Wind instrument, woodwind instrument
+Flute
+Saxophone
+Clarinet
+Harp
+Bell
+Church bell
+Jingle bell
+Bicycle bell
+Tuning fork
+Chime
+Wind chime
+Change ringing (campanology)
+Harmonica
+Accordion
+Bagpipes
+Didgeridoo
+Shofar
+Theremin
+Singing bowl
+Scratching (performance technique)
+Pop music
+Hip hop music
+Beatboxing
+Rock music
+Heavy metal
+Punk rock
+Grunge
+Progressive rock
+Rock and roll
+Psychedelic rock
+Rhythm and blues
+Soul music
+Reggae
+Country
+Swing music
+Bluegrass
+Funk
+Folk music
+Middle Eastern music
+Jazz
+Disco
+Classical music
+Opera
+Electronic music
+House music
+Techno
+Dubstep
+Drum and bass
+Electronica
+Electronic dance music
+Ambient music
+Trance music
+Music of Latin America
+Salsa music
+Flamenco
+Blues
+Music for children
+New-age music
+Vocal music
+A capella
+Music of Africa
+Afrobeat
+Christian music
+Gospel music
+Music of Asia
+Carnatic music
+Music of Bollywood
+Ska
+Traditional music
+Independent music
+Song
+Background music
+Theme music
+Jingle (music)
+Soundtrack music
+Lullaby
+Video game music
+Christmas music
+Dance music
+Wedding music
+Happy music
+Sad music
+Tender music
+Exciting music
+Angry music
+Scary music
+Wind
+Rustling leaves
+Wind noise (microphone)
+Thunderstorm
+Thunder
+Water
+Rain
+Raindrop
+Rain on surface
+Stream
+Waterfall
+Ocean
+Waves, surf
+Steam
+Gurgling
+Fire
+Crackle
+Vehicle
+Boat, Water vehicle
+Sailboat, sailing ship
+Rowboat, canoe, kayak
+Motorboat, speedboat
+Ship
+Motor vehicle (road)
+Car
+Vehicle horn, car horn, honking
+Toot
+Car alarm
+Power windows, electric windows
+Skidding
+Tire squeal
+Car passing by
+Race car, auto racing
+Truck
+Air brake
+Air horn, truck horn
+Reversing beeps
+Ice cream truck, ice cream van
+Bus
+Emergency vehicle
+Police car (siren)
+Ambulance (siren)
+Fire engine, fire truck (siren)
+Motorcycle
+Traffic noise, roadway noise
+Rail transport
+Train
+Train whistle
+Train horn
+Railroad car, train wagon
+Train wheels squealing
+Subway, metro, underground
+Aircraft
+Aircraft engine
+Jet engine
+Propeller, airscrew
+Helicopter
+Fixed-wing aircraft, airplane
+Bicycle
+Skateboard
+Engine
+Light engine (high frequency)
+Dental drill, dentist's drill
+Lawn mower
+Chainsaw
+Medium engine (mid frequency)
+Heavy engine (low frequency)
+Engine knocking
+Engine starting
+Idling
+Accelerating, revving, vroom
+Door
+Doorbell
+Ding-dong
+Sliding door
+Slam
+Knock
+Tap
+Squeak
+Cupboard open or close
+Drawer open or close
+Dishes, pots, and pans
+Cutlery, silverware
+Chopping (food)
+Frying (food)
+Microwave oven
+Blender
+Water tap, faucet
+Sink (filling or washing)
+Bathtub (filling or washing)
+Hair dryer
+Toilet flush
+Toothbrush
+Electric toothbrush
+Vacuum cleaner
+Zipper (clothing)
+Keys jangling
+Coin (dropping)
+Scissors
+Electric shaver, electric razor
+Shuffling cards
+Typing
+Typewriter
+Computer keyboard
+Writing
+Alarm
+Telephone
+Telephone bell ringing
+Ringtone
+Telephone dialing, DTMF
+Dial tone
+Busy signal
+Alarm clock
+Siren
+Civil defense siren
+Buzzer
+Smoke detector, smoke alarm
+Fire alarm
+Foghorn
+Whistle
+Steam whistle
+Mechanisms
+Ratchet, pawl
+Clock
+Tick
+Tick-tock
+Gears
+Pulleys
+Sewing machine
+Mechanical fan
+Air conditioning
+Cash register
+Printer
+Camera
+Single-lens reflex camera
+Tools
+Hammer
+Jackhammer
+Sawing
+Filing (rasp)
+Sanding
+Power tool
+Drill
+Explosion
+Gunshot, gunfire
+Machine gun
+Fusillade
+Artillery fire
+Cap gun
+Fireworks
+Firecracker
+Burst, pop
+Eruption
+Boom
+Wood
+Chop
+Splinter
+Crack
+Glass
+Chink, clink
+Shatter
+Liquid
+Splash, splatter
+Slosh
+Squish
+Drip
+Pour
+Trickle, dribble
+Gush
+Fill (with liquid)
+Spray
+Pump (liquid)
+Stir
+Boiling
+Sonar
+Arrow
+Whoosh, swoosh, swish
+Thump, thud
+Thunk
+Electronic tuner
+Effects unit
+Chorus effect
+Basketball bounce
+Bang
+Slap, smack
+Whack, thwack
+Smash, crash
+Breaking
+Bouncing
+Whip
+Flap
+Scratch
+Scrape
+Rub
+Roll
+Crushing
+Crumpling, crinkling
+Tearing
+Beep, bleep
+Ping
+Ding
+Clang
+Squeal
+Creak
+Rustle
+Whir
+Clatter
+Sizzle
+Clicking
+Clickety-clack
+Rumble
+Plop
+Jingle, tinkle
+Hum
+Zing
+Boing
+Crunch
+Silence
+Sine wave
+Harmonic
+Chirp tone
+Sound effect
+Pulse
+Inside, small room
+Inside, large room or hall
+Inside, public space
+Outside, urban or manmade
+Outside, rural or natural
+Reverberation
+Echo
+Noise
+Environmental noise
+Static
+Mains hum
+Distortion
+Sidetone
+Cacophony
+White noise
+Pink noise
+Throbbing
+Vibration
+Television
+Radio
+Field recording
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_tfhub.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_tfhub.json
new file mode 100644
index 0000000..8881154
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_tfhub.json
@@ -0,0 +1,63 @@
+{
+  "name": "AudioClassifier",
+  "description": "Identify the most prominent type in the audio clip from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio_clip",
+          "description": "Input audio clip to be classified.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 2,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Scores of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_tfhub.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_tfhub.tflite
new file mode 100644
index 0000000..f19a3fbc
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_tfhub.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.json
new file mode 100644
index 0000000..a6a3a87
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.json
@@ -0,0 +1,63 @@
+{
+  "name": "AudioClassifier",
+  "description": "Identify the most prominent type in the audio clip from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio_clip",
+          "description": "Input audio clip to be classified.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 2,
+              "channels": 1
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Scores of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "yamnet_521_labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.tflite
new file mode 100644
index 0000000..52b93a3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6_default.json
new file mode 100644
index 0000000..af556e6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_classifier/yamnet_wavin_quantized_mel_relu6_default.json
@@ -0,0 +1,34 @@
+{
+  "name": "AudioClassifier",
+  "description": "Identify the most prominent type in the audio clip from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio_clip",
+          "description": "Input audio clip to be classified.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Scores of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder/BUILD
new file mode 100644
index 0000000..0f8caca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder/yamnet_embedding.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder/yamnet_embedding.tflite
new file mode 100644
index 0000000..dff6786
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/audio_embedder/yamnet_embedding.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/BUILD
new file mode 100644
index 0000000..7b77249
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/BUILD
@@ -0,0 +1,32 @@
+load("//tensorflow_lite_support/tools/build_rules:http_files.bzl", "tflite_file", "tflite_model")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+        "*.model",
+    ]) + [
+        ":bert_nl_classifier_no_metadata",
+        "mobilebert_vocab",
+        ":30k-clean",
+    ],
+)
+
+tflite_model(name = "bert_nl_classifier_no_metadata")
+
+tflite_file(
+    name = "mobilebert_vocab",
+    extension = "txt",
+)
+
+tflite_file(
+    name = "30k-clean",
+    extension = "model",
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_default.json
new file mode 100644
index 0000000..19b1bc7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_default.json
@@ -0,0 +1,59 @@
+{
+  "name": "BertNLClassifier",
+  "description": "Classify the input text into a set of known categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "description": "Tokenized ids of the input text.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "segment_ids",
+          "description": "0 for the first sequence, 1 for the second sequence if exists.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "mask",
+          "description": "Mask with 1 for real tokens and 0 for padding tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "input_process_units": [
+
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_with_bert_tokenizer.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_with_bert_tokenizer.json
new file mode 100644
index 0000000..24e4367
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_with_bert_tokenizer.json
@@ -0,0 +1,84 @@
+{
+  "name": "BertNLClassifier",
+  "description": "Classify the input text into a set of known categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "description": "Tokenized ids of the input text.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "segment_ids",
+          "description": "0 for the first sequence, 1 for the second sequence if exists.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "mask",
+          "description": "Mask with 1 for real tokens and 0 for padding tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ],
+      "input_process_units": [
+        {
+          "options_type": "BertTokenizerOptions",
+          "options": {
+            "vocab_file": [
+              {
+                "name": "mobilebert_vocab.txt",
+                "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.1.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_with_sentence_piece.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_with_sentence_piece.json
new file mode 100644
index 0000000..9472e50
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/bert_nl_classifier_with_sentence_piece.json
@@ -0,0 +1,83 @@
+{
+  "name": "BertNLClassifier",
+  "description": "Classify the input text into a set of known categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "description": "Tokenized ids of the input text.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "segment_ids",
+          "description": "0 for the first sequence, 1 for the second sequence if exists.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "mask",
+          "description": "Mask with 1 for real tokens and 0 for padding tokens.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ],
+      "input_process_units": [
+        {
+          "options_type": "SentencePieceTokenizerOptions",
+          "options": {
+            "sentencePiece_model": [
+              {
+                "name": "30k-clean.model",
+                "description": "The sentence piece model file."
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.1.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/labels.txt
new file mode 100644
index 0000000..0cbde6b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_nl_classifier/labels.txt
@@ -0,0 +1,2 @@
+negative
+positive
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_tokenizer_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_tokenizer_meta.json
new file mode 100644
index 0000000..c90e7df
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bert_tokenizer_meta.json
@@ -0,0 +1,20 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_process_units": [
+        {
+          "options_type": "BertTokenizerOptions",
+          "options": {
+            "vocab_file": [
+              {
+                "name": "vocab.txt",
+                "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bounding_box_tensor_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bounding_box_tensor_meta.json
new file mode 100644
index 0000000..55b0624c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/bounding_box_tensor_meta.json
@@ -0,0 +1,35 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input",
+          "description": "The input tensor.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "locale": "cn"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/category_tensor_float_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/category_tensor_float_meta.json
new file mode 100644
index 0000000..9ca0588
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/category_tensor_float_meta.json
@@ -0,0 +1,33 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "category",
+          "description": "The category tensor.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_VALUE_LABELS",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_VALUE_LABELS",
+              "locale": "cn"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_float_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_float_meta.json
new file mode 100644
index 0000000..1b146d5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_float_meta.json
@@ -0,0 +1,52 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "The classification result tensor.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "cn"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_uint8_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_uint8_meta.json
new file mode 100644
index 0000000..f544afd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_uint8_meta.json
@@ -0,0 +1,52 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "The classification result tensor.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "cn"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_unsupported_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_unsupported_meta.json
new file mode 100644
index 0000000..98cf178
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/classification_tensor_unsupported_meta.json
@@ -0,0 +1,46 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "The classification result tensor.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS",
+              "locale": "cn"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/feature_tensor_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/feature_tensor_meta.json
new file mode 100644
index 0000000..4502d24c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/feature_tensor_meta.json
@@ -0,0 +1,35 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input",
+          "description": "The input tensor.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "locale": "cn"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/general_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/general_meta.json
new file mode 100644
index 0000000..1145cf404
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/general_meta.json
@@ -0,0 +1,7 @@
+{
+  "name": "model",
+  "description": "A ML model.",
+  "version": "v1",
+  "author": "TensorFlow",
+  "license": "Apache"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/golden_json.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/golden_json.json
new file mode 100644
index 0000000..601a597
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/golden_json.json
@@ -0,0 +1,28 @@
+{
+  "name": "Mobilenet_quantized",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+        },
+        {
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "associated_files": [
+            {
+              "name": "file2"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "associated_files": [
+    {
+      "name": "file1"
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/BUILD
new file mode 100644
index 0000000..0f8caca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/labels.txt
new file mode 100644
index 0000000..fe81123
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/labels.txt
@@ -0,0 +1,1001 @@
+background
+tench
+goldfish
+great white shark
+tiger shark
+hammerhead
+electric ray
+stingray
+cock
+hen
+ostrich
+brambling
+goldfinch
+house finch
+junco
+indigo bunting
+robin
+bulbul
+jay
+magpie
+chickadee
+water ouzel
+kite
+bald eagle
+vulture
+great grey owl
+European fire salamander
+common newt
+eft
+spotted salamander
+axolotl
+bullfrog
+tree frog
+tailed frog
+loggerhead
+leatherback turtle
+mud turtle
+terrapin
+box turtle
+banded gecko
+common iguana
+American chameleon
+whiptail
+agama
+frilled lizard
+alligator lizard
+Gila monster
+green lizard
+African chameleon
+Komodo dragon
+African crocodile
+American alligator
+triceratops
+thunder snake
+ringneck snake
+hognose snake
+green snake
+king snake
+garter snake
+water snake
+vine snake
+night snake
+boa constrictor
+rock python
+Indian cobra
+green mamba
+sea snake
+horned viper
+diamondback
+sidewinder
+trilobite
+harvestman
+scorpion
+black and gold garden spider
+barn spider
+garden spider
+black widow
+tarantula
+wolf spider
+tick
+centipede
+black grouse
+ptarmigan
+ruffed grouse
+prairie chicken
+peacock
+quail
+partridge
+African grey
+macaw
+sulphur-crested cockatoo
+lorikeet
+coucal
+bee eater
+hornbill
+hummingbird
+jacamar
+toucan
+drake
+red-breasted merganser
+goose
+black swan
+tusker
+echidna
+platypus
+wallaby
+koala
+wombat
+jellyfish
+sea anemone
+brain coral
+flatworm
+nematode
+conch
+snail
+slug
+sea slug
+chiton
+chambered nautilus
+Dungeness crab
+rock crab
+fiddler crab
+king crab
+American lobster
+spiny lobster
+crayfish
+hermit crab
+isopod
+white stork
+black stork
+spoonbill
+flamingo
+little blue heron
+American egret
+bittern
+crane
+limpkin
+European gallinule
+American coot
+bustard
+ruddy turnstone
+red-backed sandpiper
+redshank
+dowitcher
+oystercatcher
+pelican
+king penguin
+albatross
+grey whale
+killer whale
+dugong
+sea lion
+Chihuahua
+Japanese spaniel
+Maltese dog
+Pekinese
+Shih-Tzu
+Blenheim spaniel
+papillon
+toy terrier
+Rhodesian ridgeback
+Afghan hound
+basset
+beagle
+bloodhound
+bluetick
+black-and-tan coonhound
+Walker hound
+English foxhound
+redbone
+borzoi
+Irish wolfhound
+Italian greyhound
+whippet
+Ibizan hound
+Norwegian elkhound
+otterhound
+Saluki
+Scottish deerhound
+Weimaraner
+Staffordshire bullterrier
+American Staffordshire terrier
+Bedlington terrier
+Border terrier
+Kerry blue terrier
+Irish terrier
+Norfolk terrier
+Norwich terrier
+Yorkshire terrier
+wire-haired fox terrier
+Lakeland terrier
+Sealyham terrier
+Airedale
+cairn
+Australian terrier
+Dandie Dinmont
+Boston bull
+miniature schnauzer
+giant schnauzer
+standard schnauzer
+Scotch terrier
+Tibetan terrier
+silky terrier
+soft-coated wheaten terrier
+West Highland white terrier
+Lhasa
+flat-coated retriever
+curly-coated retriever
+golden retriever
+Labrador retriever
+Chesapeake Bay retriever
+German short-haired pointer
+vizsla
+English setter
+Irish setter
+Gordon setter
+Brittany spaniel
+clumber
+English springer
+Welsh springer spaniel
+cocker spaniel
+Sussex spaniel
+Irish water spaniel
+kuvasz
+schipperke
+groenendael
+malinois
+briard
+kelpie
+komondor
+Old English sheepdog
+Shetland sheepdog
+collie
+Border collie
+Bouvier des Flandres
+Rottweiler
+German shepherd
+Doberman
+miniature pinscher
+Greater Swiss Mountain dog
+Bernese mountain dog
+Appenzeller
+EntleBucher
+boxer
+bull mastiff
+Tibetan mastiff
+French bulldog
+Great Dane
+Saint Bernard
+Eskimo dog
+malamute
+Siberian husky
+dalmatian
+affenpinscher
+basenji
+pug
+Leonberg
+Newfoundland
+Great Pyrenees
+Samoyed
+Pomeranian
+chow
+keeshond
+Brabancon griffon
+Pembroke
+Cardigan
+toy poodle
+miniature poodle
+standard poodle
+Mexican hairless
+timber wolf
+white wolf
+red wolf
+coyote
+dingo
+dhole
+African hunting dog
+hyena
+red fox
+kit fox
+Arctic fox
+grey fox
+tabby
+tiger cat
+Persian cat
+Siamese cat
+Egyptian cat
+cougar
+lynx
+leopard
+snow leopard
+jaguar
+lion
+tiger
+cheetah
+brown bear
+American black bear
+ice bear
+sloth bear
+mongoose
+meerkat
+tiger beetle
+ladybug
+ground beetle
+long-horned beetle
+leaf beetle
+dung beetle
+rhinoceros beetle
+weevil
+fly
+bee
+ant
+grasshopper
+cricket
+walking stick
+cockroach
+mantis
+cicada
+leafhopper
+lacewing
+dragonfly
+damselfly
+admiral
+ringlet
+monarch
+cabbage butterfly
+sulphur butterfly
+lycaenid
+starfish
+sea urchin
+sea cucumber
+wood rabbit
+hare
+Angora
+hamster
+porcupine
+fox squirrel
+marmot
+beaver
+guinea pig
+sorrel
+zebra
+hog
+wild boar
+warthog
+hippopotamus
+ox
+water buffalo
+bison
+ram
+bighorn
+ibex
+hartebeest
+impala
+gazelle
+Arabian camel
+llama
+weasel
+mink
+polecat
+black-footed ferret
+otter
+skunk
+badger
+armadillo
+three-toed sloth
+orangutan
+gorilla
+chimpanzee
+gibbon
+siamang
+guenon
+patas
+baboon
+macaque
+langur
+colobus
+proboscis monkey
+marmoset
+capuchin
+howler monkey
+titi
+spider monkey
+squirrel monkey
+Madagascar cat
+indri
+Indian elephant
+African elephant
+lesser panda
+giant panda
+barracouta
+eel
+coho
+rock beauty
+anemone fish
+sturgeon
+gar
+lionfish
+puffer
+abacus
+abaya
+academic gown
+accordion
+acoustic guitar
+aircraft carrier
+airliner
+airship
+altar
+ambulance
+amphibian
+analog clock
+apiary
+apron
+ashcan
+assault rifle
+backpack
+bakery
+balance beam
+balloon
+ballpoint
+Band Aid
+banjo
+bannister
+barbell
+barber chair
+barbershop
+barn
+barometer
+barrel
+barrow
+baseball
+basketball
+bassinet
+bassoon
+bathing cap
+bath towel
+bathtub
+beach wagon
+beacon
+beaker
+bearskin
+beer bottle
+beer glass
+bell cote
+bib
+bicycle-built-for-two
+bikini
+binder
+binoculars
+birdhouse
+boathouse
+bobsled
+bolo tie
+bonnet
+bookcase
+bookshop
+bottlecap
+bow
+bow tie
+brass
+brassiere
+breakwater
+breastplate
+broom
+bucket
+buckle
+bulletproof vest
+bullet train
+butcher shop
+cab
+caldron
+candle
+cannon
+canoe
+can opener
+cardigan
+car mirror
+carousel
+carpenter's kit
+carton
+car wheel
+cash machine
+cassette
+cassette player
+castle
+catamaran
+CD player
+cello
+cellular telephone
+chain
+chainlink fence
+chain mail
+chain saw
+chest
+chiffonier
+chime
+china cabinet
+Christmas stocking
+church
+cinema
+cleaver
+cliff dwelling
+cloak
+clog
+cocktail shaker
+coffee mug
+coffeepot
+coil
+combination lock
+computer keyboard
+confectionery
+container ship
+convertible
+corkscrew
+cornet
+cowboy boot
+cowboy hat
+cradle
+crane
+crash helmet
+crate
+crib
+Crock Pot
+croquet ball
+crutch
+cuirass
+dam
+desk
+desktop computer
+dial telephone
+diaper
+digital clock
+digital watch
+dining table
+dishrag
+dishwasher
+disk brake
+dock
+dogsled
+dome
+doormat
+drilling platform
+drum
+drumstick
+dumbbell
+Dutch oven
+electric fan
+electric guitar
+electric locomotive
+entertainment center
+envelope
+espresso maker
+face powder
+feather boa
+file
+fireboat
+fire engine
+fire screen
+flagpole
+flute
+folding chair
+football helmet
+forklift
+fountain
+fountain pen
+four-poster
+freight car
+French horn
+frying pan
+fur coat
+garbage truck
+gasmask
+gas pump
+goblet
+go-kart
+golf ball
+golfcart
+gondola
+gong
+gown
+grand piano
+greenhouse
+grille
+grocery store
+guillotine
+hair slide
+hair spray
+half track
+hammer
+hamper
+hand blower
+hand-held computer
+handkerchief
+hard disc
+harmonica
+harp
+harvester
+hatchet
+holster
+home theater
+honeycomb
+hook
+hoopskirt
+horizontal bar
+horse cart
+hourglass
+iPod
+iron
+jack-o'-lantern
+jean
+jeep
+jersey
+jigsaw puzzle
+jinrikisha
+joystick
+kimono
+knee pad
+knot
+lab coat
+ladle
+lampshade
+laptop
+lawn mower
+lens cap
+letter opener
+library
+lifeboat
+lighter
+limousine
+liner
+lipstick
+Loafer
+lotion
+loudspeaker
+loupe
+lumbermill
+magnetic compass
+mailbag
+mailbox
+maillot
+maillot
+manhole cover
+maraca
+marimba
+mask
+matchstick
+maypole
+maze
+measuring cup
+medicine chest
+megalith
+microphone
+microwave
+military uniform
+milk can
+minibus
+miniskirt
+minivan
+missile
+mitten
+mixing bowl
+mobile home
+Model T
+modem
+monastery
+monitor
+moped
+mortar
+mortarboard
+mosque
+mosquito net
+motor scooter
+mountain bike
+mountain tent
+mouse
+mousetrap
+moving van
+muzzle
+nail
+neck brace
+necklace
+nipple
+notebook
+obelisk
+oboe
+ocarina
+odometer
+oil filter
+organ
+oscilloscope
+overskirt
+oxcart
+oxygen mask
+packet
+paddle
+paddlewheel
+padlock
+paintbrush
+pajama
+palace
+panpipe
+paper towel
+parachute
+parallel bars
+park bench
+parking meter
+passenger car
+patio
+pay-phone
+pedestal
+pencil box
+pencil sharpener
+perfume
+Petri dish
+photocopier
+pick
+pickelhaube
+picket fence
+pickup
+pier
+piggy bank
+pill bottle
+pillow
+ping-pong ball
+pinwheel
+pirate
+pitcher
+plane
+planetarium
+plastic bag
+plate rack
+plow
+plunger
+Polaroid camera
+pole
+police van
+poncho
+pool table
+pop bottle
+pot
+potter's wheel
+power drill
+prayer rug
+printer
+prison
+projectile
+projector
+puck
+punching bag
+purse
+quill
+quilt
+racer
+racket
+radiator
+radio
+radio telescope
+rain barrel
+recreational vehicle
+reel
+reflex camera
+refrigerator
+remote control
+restaurant
+revolver
+rifle
+rocking chair
+rotisserie
+rubber eraser
+rugby ball
+rule
+running shoe
+safe
+safety pin
+saltshaker
+sandal
+sarong
+sax
+scabbard
+scale
+school bus
+schooner
+scoreboard
+screen
+screw
+screwdriver
+seat belt
+sewing machine
+shield
+shoe shop
+shoji
+shopping basket
+shopping cart
+shovel
+shower cap
+shower curtain
+ski
+ski mask
+sleeping bag
+slide rule
+sliding door
+slot
+snorkel
+snowmobile
+snowplow
+soap dispenser
+soccer ball
+sock
+solar dish
+sombrero
+soup bowl
+space bar
+space heater
+space shuttle
+spatula
+speedboat
+spider web
+spindle
+sports car
+spotlight
+stage
+steam locomotive
+steel arch bridge
+steel drum
+stethoscope
+stole
+stone wall
+stopwatch
+stove
+strainer
+streetcar
+stretcher
+studio couch
+stupa
+submarine
+suit
+sundial
+sunglass
+sunglasses
+sunscreen
+suspension bridge
+swab
+sweatshirt
+swimming trunks
+swing
+switch
+syringe
+table lamp
+tank
+tape player
+teapot
+teddy
+television
+tennis ball
+thatch
+theater curtain
+thimble
+thresher
+throne
+tile roof
+toaster
+tobacco shop
+toilet seat
+torch
+totem pole
+tow truck
+toyshop
+tractor
+trailer truck
+tray
+trench coat
+tricycle
+trimaran
+tripod
+triumphal arch
+trolleybus
+trombone
+tub
+turnstile
+typewriter keyboard
+umbrella
+unicycle
+upright
+vacuum
+vase
+vault
+velvet
+vending machine
+vestment
+viaduct
+violin
+volleyball
+waffle iron
+wall clock
+wallet
+wardrobe
+warplane
+washbasin
+washer
+water bottle
+water jug
+water tower
+whiskey jug
+whistle
+wig
+window screen
+window shade
+Windsor tie
+wine bottle
+wing
+wok
+wooden spoon
+wool
+worm fence
+wreck
+yawl
+yurt
+web site
+comic book
+crossword puzzle
+street sign
+traffic light
+book jacket
+menu
+plate
+guacamole
+consomme
+hot pot
+trifle
+ice cream
+ice lolly
+French loaf
+bagel
+pretzel
+cheeseburger
+hotdog
+mashed potato
+head cabbage
+broccoli
+cauliflower
+zucchini
+spaghetti squash
+acorn squash
+butternut squash
+cucumber
+artichoke
+bell pepper
+cardoon
+mushroom
+Granny Smith
+strawberry
+orange
+lemon
+fig
+pineapple
+banana
+jackfruit
+custard apple
+pomegranate
+hay
+carbonara
+chocolate sauce
+dough
+meat loaf
+pizza
+potpie
+burrito
+red wine
+espresso
+cup
+eggnog
+alp
+bubble
+cliff
+coral reef
+geyser
+lakeside
+promontory
+sandbar
+seashore
+valley
+volcano
+ballplayer
+groom
+scuba diver
+rapeseed
+daisy
+yellow lady's slipper
+corn
+acorn
+hip
+buckeye
+coral fungus
+agaric
+gyromitra
+stinkhorn
+earthstar
+hen-of-the-woods
+bolete
+ear
+toilet tissue
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224.json
new file mode 100644
index 0000000..3c032df
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224.json
@@ -0,0 +1,81 @@
+{
+  "name": "ImageClassifier",
+  "description": "Identify the most prominent object in the image from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be classified.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              -1.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224.tflite
new file mode 100644
index 0000000..56268e1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_default.json
new file mode 100644
index 0000000..5380fa5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_default.json
@@ -0,0 +1,35 @@
+{
+  "name": "ImageClassifier",
+  "description": "Identify the most prominent object in the image from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be classified.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_quant.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_quant.json
new file mode 100644
index 0000000..a1b58ce
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_quant.json
@@ -0,0 +1,81 @@
+{
+  "name": "ImageClassifier",
+  "description": "Identify the most prominent object in the image from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be classified.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "LOG",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            },
+            {
+              "name": "score_calibration.txt",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_quant.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_quant.tflite
new file mode 100644
index 0000000..c26ff77
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/mobilenet_v2_1.0_224_quant.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/score_calibration.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/score_calibration.txt
new file mode 100644
index 0000000..b64f0c1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_classifier/score_calibration.txt
@@ -0,0 +1,511 @@
+
+0.9876328110694885,0.36622241139411926,0.5352765321731567,0.71484375
+0.9584911465644836,1.0602262020111084,0.2777034342288971,0.019999999552965164
+0.9698624014854431,0.8795201778411865,0.539591908454895,0.00390625
+0.7486230731010437,1.1876736879348755,2.552982807159424,0.019999999552965164
+0.9745277166366577,0.3739396333694458,0.4621727764606476,0.19921875
+0.9683839678764343,0.6996201276779175,0.7690851092338562,0.019999999552965164
+0.6875,0.31044548749923706,1.0056899785995483,0.019999999552965164
+0.9849396347999573,0.8532888889312744,-0.2361421436071396,0.03125
+0.9878578186035156,1.0118975639343262,0.13313621282577515,0.359375
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\ No newline at end of file
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/BUILD
new file mode 100644
index 0000000..0f8caca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3.json
new file mode 100644
index 0000000..c7bf7c5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3.json
@@ -0,0 +1,66 @@
+{
+  "name": "ImageSegmenter",
+  "description": "Semantic image segmentation predicts whether each pixel of an image is associated with a certain class.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be segmented.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              -1.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "segmentation_masks",
+          "description": "Masks over the target objects with high accuracy.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "GRAYSCALE"
+            },
+            "range": {
+              "min": 1,
+              "max": 2
+            }
+          },
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3.tflite
new file mode 100644
index 0000000..d2d9a9b0
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3_default.json
new file mode 100644
index 0000000..18cb12f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/deeplabv3_default.json
@@ -0,0 +1,40 @@
+{
+  "name": "ImageSegmenter",
+  "description": "Semantic image segmentation predicts whether each pixel of an image is associated with a certain class.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be segmented.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "segmentation_masks",
+          "description": "Masks over the target objects with high accuracy.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "GRAYSCALE"
+            },
+            "range": {
+              "min": 1,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/labelmap.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/labelmap.txt
new file mode 100644
index 0000000..204608c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_segmenter/labelmap.txt
@@ -0,0 +1,21 @@
+background
+aeroplane
+bicycle
+bird
+boat
+bottle
+bus
+car
+cat
+chair
+cow
+dining table
+dog
+horse
+motorbike
+person
+potted plant
+sheep
+sofa
+train
+tv
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_tensor_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_tensor_meta.json
new file mode 100644
index 0000000..834848c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/image_tensor_meta.json
@@ -0,0 +1,35 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input",
+          "description": "The input tensor.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "locale": "en"
+            },
+            {
+              "name": "labels_cn.txt",
+              "locale": "cn"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_audio_tesnor_default_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_audio_tesnor_default_meta.json
new file mode 100644
index 0000000..6cfdc83
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_audio_tesnor_default_meta.json
@@ -0,0 +1,17 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_audio_tesnor_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_audio_tesnor_meta.json
new file mode 100644
index 0000000..6988dac
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_audio_tesnor_meta.json
@@ -0,0 +1,21 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input text",
+          "description": "The input string.",
+          "content": {
+            "content_properties_type": "AudioProperties",
+            "content_properties": {
+              "sample_rate": 10,
+              "channels": 2
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_float_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_float_meta.json
new file mode 100644
index 0000000..2f9b288
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_float_meta.json
@@ -0,0 +1,47 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "The input image.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  0.0,
+                  127.5,
+                  255.0
+                ],
+                "std": [
+                  127.5,
+                  127.5,
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              2.0,
+              1.0,
+              0.0
+            ],
+            "min": [
+              0.0,
+              -1.0,
+              -2.0
+            ]
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_uint8_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_uint8_meta.json
new file mode 100644
index 0000000..fc1d840
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_uint8_meta.json
@@ -0,0 +1,43 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "The input image.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  0.0,
+                  127.5,
+                  255.0
+                ],
+                "std": [
+                  127.5,
+                  127.5,
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_unsupported_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_unsupported_meta.json
new file mode 100644
index 0000000..09a05aa
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_image_tensor_unsupported_meta.json
@@ -0,0 +1,37 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "The input image.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  0.0,
+                  127.5,
+                  255.0
+                ],
+                "std": [
+                  127.5,
+                  127.5,
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_text_tesnor_default_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_text_tesnor_default_meta.json
new file mode 100644
index 0000000..07c23bb
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_text_tesnor_default_meta.json
@@ -0,0 +1,17 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_text_tesnor_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_text_tesnor_meta.json
new file mode 100644
index 0000000..04bab2f
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/input_text_tesnor_meta.json
@@ -0,0 +1,34 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input text",
+          "description": "The input string.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "RegexTokenizerOptions",
+              "options": {
+                "delim_regex_pattern": "[^\\w\\']+",
+                "vocab_file": [
+                  {
+                    "name": "vocab.txt",
+                    "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                    "type": "VOCABULARY"
+                  }
+                ]
+              }
+            }
+          ],
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/labels.txt
new file mode 100644
index 0000000..fe81123
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/labels.txt
@@ -0,0 +1,1001 @@
+background
+tench
+goldfish
+great white shark
+tiger shark
+hammerhead
+electric ray
+stingray
+cock
+hen
+ostrich
+brambling
+goldfinch
+house finch
+junco
+indigo bunting
+robin
+bulbul
+jay
+magpie
+chickadee
+water ouzel
+kite
+bald eagle
+vulture
+great grey owl
+European fire salamander
+common newt
+eft
+spotted salamander
+axolotl
+bullfrog
+tree frog
+tailed frog
+loggerhead
+leatherback turtle
+mud turtle
+terrapin
+box turtle
+banded gecko
+common iguana
+American chameleon
+whiptail
+agama
+frilled lizard
+alligator lizard
+Gila monster
+green lizard
+African chameleon
+Komodo dragon
+African crocodile
+American alligator
+triceratops
+thunder snake
+ringneck snake
+hognose snake
+green snake
+king snake
+garter snake
+water snake
+vine snake
+night snake
+boa constrictor
+rock python
+Indian cobra
+green mamba
+sea snake
+horned viper
+diamondback
+sidewinder
+trilobite
+harvestman
+scorpion
+black and gold garden spider
+barn spider
+garden spider
+black widow
+tarantula
+wolf spider
+tick
+centipede
+black grouse
+ptarmigan
+ruffed grouse
+prairie chicken
+peacock
+quail
+partridge
+African grey
+macaw
+sulphur-crested cockatoo
+lorikeet
+coucal
+bee eater
+hornbill
+hummingbird
+jacamar
+toucan
+drake
+red-breasted merganser
+goose
+black swan
+tusker
+echidna
+platypus
+wallaby
+koala
+wombat
+jellyfish
+sea anemone
+brain coral
+flatworm
+nematode
+conch
+snail
+slug
+sea slug
+chiton
+chambered nautilus
+Dungeness crab
+rock crab
+fiddler crab
+king crab
+American lobster
+spiny lobster
+crayfish
+hermit crab
+isopod
+white stork
+black stork
+spoonbill
+flamingo
+little blue heron
+American egret
+bittern
+crane
+limpkin
+European gallinule
+American coot
+bustard
+ruddy turnstone
+red-backed sandpiper
+redshank
+dowitcher
+oystercatcher
+pelican
+king penguin
+albatross
+grey whale
+killer whale
+dugong
+sea lion
+Chihuahua
+Japanese spaniel
+Maltese dog
+Pekinese
+Shih-Tzu
+Blenheim spaniel
+papillon
+toy terrier
+Rhodesian ridgeback
+Afghan hound
+basset
+beagle
+bloodhound
+bluetick
+black-and-tan coonhound
+Walker hound
+English foxhound
+redbone
+borzoi
+Irish wolfhound
+Italian greyhound
+whippet
+Ibizan hound
+Norwegian elkhound
+otterhound
+Saluki
+Scottish deerhound
+Weimaraner
+Staffordshire bullterrier
+American Staffordshire terrier
+Bedlington terrier
+Border terrier
+Kerry blue terrier
+Irish terrier
+Norfolk terrier
+Norwich terrier
+Yorkshire terrier
+wire-haired fox terrier
+Lakeland terrier
+Sealyham terrier
+Airedale
+cairn
+Australian terrier
+Dandie Dinmont
+Boston bull
+miniature schnauzer
+giant schnauzer
+standard schnauzer
+Scotch terrier
+Tibetan terrier
+silky terrier
+soft-coated wheaten terrier
+West Highland white terrier
+Lhasa
+flat-coated retriever
+curly-coated retriever
+golden retriever
+Labrador retriever
+Chesapeake Bay retriever
+German short-haired pointer
+vizsla
+English setter
+Irish setter
+Gordon setter
+Brittany spaniel
+clumber
+English springer
+Welsh springer spaniel
+cocker spaniel
+Sussex spaniel
+Irish water spaniel
+kuvasz
+schipperke
+groenendael
+malinois
+briard
+kelpie
+komondor
+Old English sheepdog
+Shetland sheepdog
+collie
+Border collie
+Bouvier des Flandres
+Rottweiler
+German shepherd
+Doberman
+miniature pinscher
+Greater Swiss Mountain dog
+Bernese mountain dog
+Appenzeller
+EntleBucher
+boxer
+bull mastiff
+Tibetan mastiff
+French bulldog
+Great Dane
+Saint Bernard
+Eskimo dog
+malamute
+Siberian husky
+dalmatian
+affenpinscher
+basenji
+pug
+Leonberg
+Newfoundland
+Great Pyrenees
+Samoyed
+Pomeranian
+chow
+keeshond
+Brabancon griffon
+Pembroke
+Cardigan
+toy poodle
+miniature poodle
+standard poodle
+Mexican hairless
+timber wolf
+white wolf
+red wolf
+coyote
+dingo
+dhole
+African hunting dog
+hyena
+red fox
+kit fox
+Arctic fox
+grey fox
+tabby
+tiger cat
+Persian cat
+Siamese cat
+Egyptian cat
+cougar
+lynx
+leopard
+snow leopard
+jaguar
+lion
+tiger
+cheetah
+brown bear
+American black bear
+ice bear
+sloth bear
+mongoose
+meerkat
+tiger beetle
+ladybug
+ground beetle
+long-horned beetle
+leaf beetle
+dung beetle
+rhinoceros beetle
+weevil
+fly
+bee
+ant
+grasshopper
+cricket
+walking stick
+cockroach
+mantis
+cicada
+leafhopper
+lacewing
+dragonfly
+damselfly
+admiral
+ringlet
+monarch
+cabbage butterfly
+sulphur butterfly
+lycaenid
+starfish
+sea urchin
+sea cucumber
+wood rabbit
+hare
+Angora
+hamster
+porcupine
+fox squirrel
+marmot
+beaver
+guinea pig
+sorrel
+zebra
+hog
+wild boar
+warthog
+hippopotamus
+ox
+water buffalo
+bison
+ram
+bighorn
+ibex
+hartebeest
+impala
+gazelle
+Arabian camel
+llama
+weasel
+mink
+polecat
+black-footed ferret
+otter
+skunk
+badger
+armadillo
+three-toed sloth
+orangutan
+gorilla
+chimpanzee
+gibbon
+siamang
+guenon
+patas
+baboon
+macaque
+langur
+colobus
+proboscis monkey
+marmoset
+capuchin
+howler monkey
+titi
+spider monkey
+squirrel monkey
+Madagascar cat
+indri
+Indian elephant
+African elephant
+lesser panda
+giant panda
+barracouta
+eel
+coho
+rock beauty
+anemone fish
+sturgeon
+gar
+lionfish
+puffer
+abacus
+abaya
+academic gown
+accordion
+acoustic guitar
+aircraft carrier
+airliner
+airship
+altar
+ambulance
+amphibian
+analog clock
+apiary
+apron
+ashcan
+assault rifle
+backpack
+bakery
+balance beam
+balloon
+ballpoint
+Band Aid
+banjo
+bannister
+barbell
+barber chair
+barbershop
+barn
+barometer
+barrel
+barrow
+baseball
+basketball
+bassinet
+bassoon
+bathing cap
+bath towel
+bathtub
+beach wagon
+beacon
+beaker
+bearskin
+beer bottle
+beer glass
+bell cote
+bib
+bicycle-built-for-two
+bikini
+binder
+binoculars
+birdhouse
+boathouse
+bobsled
+bolo tie
+bonnet
+bookcase
+bookshop
+bottlecap
+bow
+bow tie
+brass
+brassiere
+breakwater
+breastplate
+broom
+bucket
+buckle
+bulletproof vest
+bullet train
+butcher shop
+cab
+caldron
+candle
+cannon
+canoe
+can opener
+cardigan
+car mirror
+carousel
+carpenter's kit
+carton
+car wheel
+cash machine
+cassette
+cassette player
+castle
+catamaran
+CD player
+cello
+cellular telephone
+chain
+chainlink fence
+chain mail
+chain saw
+chest
+chiffonier
+chime
+china cabinet
+Christmas stocking
+church
+cinema
+cleaver
+cliff dwelling
+cloak
+clog
+cocktail shaker
+coffee mug
+coffeepot
+coil
+combination lock
+computer keyboard
+confectionery
+container ship
+convertible
+corkscrew
+cornet
+cowboy boot
+cowboy hat
+cradle
+crane
+crash helmet
+crate
+crib
+Crock Pot
+croquet ball
+crutch
+cuirass
+dam
+desk
+desktop computer
+dial telephone
+diaper
+digital clock
+digital watch
+dining table
+dishrag
+dishwasher
+disk brake
+dock
+dogsled
+dome
+doormat
+drilling platform
+drum
+drumstick
+dumbbell
+Dutch oven
+electric fan
+electric guitar
+electric locomotive
+entertainment center
+envelope
+espresso maker
+face powder
+feather boa
+file
+fireboat
+fire engine
+fire screen
+flagpole
+flute
+folding chair
+football helmet
+forklift
+fountain
+fountain pen
+four-poster
+freight car
+French horn
+frying pan
+fur coat
+garbage truck
+gasmask
+gas pump
+goblet
+go-kart
+golf ball
+golfcart
+gondola
+gong
+gown
+grand piano
+greenhouse
+grille
+grocery store
+guillotine
+hair slide
+hair spray
+half track
+hammer
+hamper
+hand blower
+hand-held computer
+handkerchief
+hard disc
+harmonica
+harp
+harvester
+hatchet
+holster
+home theater
+honeycomb
+hook
+hoopskirt
+horizontal bar
+horse cart
+hourglass
+iPod
+iron
+jack-o'-lantern
+jean
+jeep
+jersey
+jigsaw puzzle
+jinrikisha
+joystick
+kimono
+knee pad
+knot
+lab coat
+ladle
+lampshade
+laptop
+lawn mower
+lens cap
+letter opener
+library
+lifeboat
+lighter
+limousine
+liner
+lipstick
+Loafer
+lotion
+loudspeaker
+loupe
+lumbermill
+magnetic compass
+mailbag
+mailbox
+maillot
+maillot
+manhole cover
+maraca
+marimba
+mask
+matchstick
+maypole
+maze
+measuring cup
+medicine chest
+megalith
+microphone
+microwave
+military uniform
+milk can
+minibus
+miniskirt
+minivan
+missile
+mitten
+mixing bowl
+mobile home
+Model T
+modem
+monastery
+monitor
+moped
+mortar
+mortarboard
+mosque
+mosquito net
+motor scooter
+mountain bike
+mountain tent
+mouse
+mousetrap
+moving van
+muzzle
+nail
+neck brace
+necklace
+nipple
+notebook
+obelisk
+oboe
+ocarina
+odometer
+oil filter
+organ
+oscilloscope
+overskirt
+oxcart
+oxygen mask
+packet
+paddle
+paddlewheel
+padlock
+paintbrush
+pajama
+palace
+panpipe
+paper towel
+parachute
+parallel bars
+park bench
+parking meter
+passenger car
+patio
+pay-phone
+pedestal
+pencil box
+pencil sharpener
+perfume
+Petri dish
+photocopier
+pick
+pickelhaube
+picket fence
+pickup
+pier
+piggy bank
+pill bottle
+pillow
+ping-pong ball
+pinwheel
+pirate
+pitcher
+plane
+planetarium
+plastic bag
+plate rack
+plow
+plunger
+Polaroid camera
+pole
+police van
+poncho
+pool table
+pop bottle
+pot
+potter's wheel
+power drill
+prayer rug
+printer
+prison
+projectile
+projector
+puck
+punching bag
+purse
+quill
+quilt
+racer
+racket
+radiator
+radio
+radio telescope
+rain barrel
+recreational vehicle
+reel
+reflex camera
+refrigerator
+remote control
+restaurant
+revolver
+rifle
+rocking chair
+rotisserie
+rubber eraser
+rugby ball
+rule
+running shoe
+safe
+safety pin
+saltshaker
+sandal
+sarong
+sax
+scabbard
+scale
+school bus
+schooner
+scoreboard
+screen
+screw
+screwdriver
+seat belt
+sewing machine
+shield
+shoe shop
+shoji
+shopping basket
+shopping cart
+shovel
+shower cap
+shower curtain
+ski
+ski mask
+sleeping bag
+slide rule
+sliding door
+slot
+snorkel
+snowmobile
+snowplow
+soap dispenser
+soccer ball
+sock
+solar dish
+sombrero
+soup bowl
+space bar
+space heater
+space shuttle
+spatula
+speedboat
+spider web
+spindle
+sports car
+spotlight
+stage
+steam locomotive
+steel arch bridge
+steel drum
+stethoscope
+stole
+stone wall
+stopwatch
+stove
+strainer
+streetcar
+stretcher
+studio couch
+stupa
+submarine
+suit
+sundial
+sunglass
+sunglasses
+sunscreen
+suspension bridge
+swab
+sweatshirt
+swimming trunks
+swing
+switch
+syringe
+table lamp
+tank
+tape player
+teapot
+teddy
+television
+tennis ball
+thatch
+theater curtain
+thimble
+thresher
+throne
+tile roof
+toaster
+tobacco shop
+toilet seat
+torch
+totem pole
+tow truck
+toyshop
+tractor
+trailer truck
+tray
+trench coat
+tricycle
+trimaran
+tripod
+triumphal arch
+trolleybus
+trombone
+tub
+turnstile
+typewriter keyboard
+umbrella
+unicycle
+upright
+vacuum
+vase
+vault
+velvet
+vending machine
+vestment
+viaduct
+violin
+volleyball
+waffle iron
+wall clock
+wallet
+wardrobe
+warplane
+washbasin
+washer
+water bottle
+water jug
+water tower
+whiskey jug
+whistle
+wig
+window screen
+window shade
+Windsor tie
+wine bottle
+wing
+wok
+wooden spoon
+wool
+worm fence
+wreck
+yawl
+yurt
+web site
+comic book
+crossword puzzle
+street sign
+traffic light
+book jacket
+menu
+plate
+guacamole
+consomme
+hot pot
+trifle
+ice cream
+ice lolly
+French loaf
+bagel
+pretzel
+cheeseburger
+hotdog
+mashed potato
+head cabbage
+broccoli
+cauliflower
+zucchini
+spaghetti squash
+acorn squash
+butternut squash
+cucumber
+artichoke
+bell pepper
+cardoon
+mushroom
+Granny Smith
+strawberry
+orange
+lemon
+fig
+pineapple
+banana
+jackfruit
+custard apple
+pomegranate
+hay
+carbonara
+chocolate sauce
+dough
+meat loaf
+pizza
+potpie
+burrito
+red wine
+espresso
+cup
+eggnog
+alp
+bubble
+cliff
+coral reef
+geyser
+lakeside
+promontory
+sandbar
+seashore
+valley
+volcano
+ballplayer
+groom
+scuba diver
+rapeseed
+daisy
+yellow lady's slipper
+corn
+acorn
+hip
+buckeye
+coral fungus
+agaric
+gyromitra
+stinkhorn
+earthstar
+hen-of-the-woods
+bolete
+ear
+toilet tissue
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant.json
new file mode 100644
index 0000000..ecb72f8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant.json
@@ -0,0 +1,67 @@
+{
+  "name": "ImageClassifier",
+  "description": "Identify the most prominent object in the image from a known set of categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be classified.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant.tflite
new file mode 100644
index 0000000..c26ff77
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_default.json
new file mode 100644
index 0000000..b1f84e58
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_default.json
@@ -0,0 +1,17 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input"
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "output"
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_dummy.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_dummy.json
new file mode 100644
index 0000000..d4f9169
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_dummy.json
@@ -0,0 +1,18 @@
+{
+  "name": "mobilenet_v2_1.0_224_quant",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image"
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability"
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_dummy_no_version.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_dummy_no_version.json
new file mode 100644
index 0000000..52c1541
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_dummy_no_version.json
@@ -0,0 +1,17 @@
+{
+  "name": "mobilenet_v2_1.0_224_quant",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image"
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability"
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_meta_info_.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_meta_info_.json
new file mode 100644
index 0000000..1396d15
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/mobilenet_v2_1.0_224_quant_meta_info_.json
@@ -0,0 +1,32 @@
+{
+  "name": "mobilenet_v2_1.0_224_quant",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/multi_inputs.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/multi_inputs.json
new file mode 100644
index 0000000..64f3066
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/multi_inputs.json
@@ -0,0 +1,47 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "ids",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "mask",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "segment",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "end_logits"
+        },
+        {
+          "name": "start_logits"
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/multi_outputs.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/multi_outputs.json
new file mode 100644
index 0000000..bdf0870b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/multi_outputs.json
@@ -0,0 +1,34 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "audio"
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "Identity",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "Identity 1",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.0.0"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/BUILD
new file mode 100644
index 0000000..0f8caca
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/BUILD
@@ -0,0 +1,13 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/labels.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/labels.txt
new file mode 100644
index 0000000..84b84ff
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/labels.txt
@@ -0,0 +1,2 @@
+Negative
+Positive
\ No newline at end of file
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review.tflite
new file mode 100644
index 0000000..0ec3f5a4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review_default.json
new file mode 100644
index 0000000..2b06c29
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review_default.json
@@ -0,0 +1,34 @@
+{
+  "name": "NLClassifier",
+  "description": "Classify the input text into a set of known categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input_text",
+          "description": "Embedding vectors representing the input text to be classified.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review_regex.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review_regex.json
new file mode 100644
index 0000000..de81e42
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/movie_review_regex.json
@@ -0,0 +1,63 @@
+{
+  "name": "NLClassifier",
+  "description": "Classify the input text into a set of known categories.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "input_text",
+          "description": "Embedding vectors representing the input text to be classified.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "RegexTokenizerOptions",
+              "options": {
+                "delim_regex_pattern": "[^\\w\\']+",
+                "vocab_file": [
+                  {
+                    "name": "vocab.txt",
+                    "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                    "type": "VOCABULARY"
+                  }
+                ]
+              }
+            }
+          ],
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "probability",
+          "description": "Probabilities of the labels respectively.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+            "max": [
+              1.0
+            ],
+            "min": [
+              0.0
+            ]
+          },
+          "associated_files": [
+            {
+              "name": "labels.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_AXIS_LABELS"
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "min_parser_version": "1.2.1"
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/vocab.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/vocab.txt
new file mode 100644
index 0000000..0a27d7c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/nl_classifier/vocab.txt
@@ -0,0 +1,10000 @@
+<PAD> 0
+<START> 1
+<UNKNOWN> 2
+<UNUSED> 3
+the 4
+and 5
+a 6
+of 7
+to 8
+is 9
+br 10
+in 11
+it 12
+i 13
+this 14
+that 15
+was 16
+as 17
+for 18
+with 19
+movie 20
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+on 23
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+or 42
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/BUILD
new file mode 100644
index 0000000..9cf6039e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/BUILD
@@ -0,0 +1,14 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+        "*.csv",
+    ]),
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_no_metadata.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_no_metadata.tflite
new file mode 100644
index 0000000..8015ee5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_no_metadata.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite
new file mode 100644
index 0000000..6416c4c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29_score_calibration.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration.json
new file mode 100644
index 0000000..9459b77
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration.json
@@ -0,0 +1,139 @@
+{
+  "name": "ObjectDetector",
+  "description": "Identify which of a known set of objects might be present and provide information about their positions within the given image or a video stream.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be detected.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "location",
+          "description": "The locations of the detected boxes.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+              "index": [
+                1,
+                0,
+                3,
+                2
+              ],
+              "type": "BOUNDARIES"
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "category",
+          "description": "The categories of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_VALUE_LABELS"
+            }
+          ]
+        },
+        {
+          "name": "score",
+          "description": "The scores of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "INVERSE_LOGISTIC",
+                "default_score": 0.2
+              }
+            }
+          ],
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "score_calibration.csv",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        },
+        {
+          "name": "number of detections",
+          "description": "The number of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_groups": [
+        {
+          "name": "detection_result",
+          "tensor_names": [
+            "location",
+            "category",
+            "score"
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration_dummy.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration_dummy.json
new file mode 100644
index 0000000..888c832a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/coco_ssd_mobilenet_v1_score_calibration_dummy.json
@@ -0,0 +1,138 @@
+{
+  "name": "ObjectDetector",
+  "description": "Identify which of a known set of objects might be present and provide information about their positions within the given image or a video stream.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be detected.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "location",
+          "description": "The locations of the detected boxes.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+              "index": [
+                1,
+                0,
+                3,
+                2
+              ],
+              "type": "BOUNDARIES"
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "category",
+          "description": "The categories of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_VALUE_LABELS"
+            }
+          ]
+        },
+        {
+          "name": "score",
+          "description": "The scores of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "ScoreCalibrationOptions",
+              "options": {
+                "score_transformation": "INVERSE_LOGISTIC"
+              }
+            }
+          ],
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "score_calibration_dummy.csv",
+              "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+              "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+            }
+          ]
+        },
+        {
+          "name": "number of detections",
+          "description": "The number of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_groups": [
+        {
+          "name": "detection_result",
+          "tensor_names": [
+            "location",
+            "category",
+            "score"
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1.json
new file mode 100644
index 0000000..3c29c17
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1.json
@@ -0,0 +1,123 @@
+{
+  "name": "ObjectDetector",
+  "description": "Identify which of a known set of objects might be present and provide information about their positions within the given image or a video stream.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be detected.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "score",
+          "description": "The scores of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "location",
+          "description": "The locations of the detected boxes.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+              "index": [
+                1,
+                0,
+                3,
+                2
+              ],
+              "type": "BOUNDARIES"
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "number of detections",
+          "description": "The number of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "category",
+          "description": "The categories of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_VALUE_LABELS"
+            }
+          ]
+        }
+      ],
+      "output_tensor_groups": [
+        {
+          "name": "detection_result",
+          "tensor_names": [
+            "location",
+            "category",
+            "score"
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1.tflite
new file mode 100644
index 0000000..c2d49da
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1_default.json
new file mode 100644
index 0000000..77e4955
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/efficientdet_lite0_v1_default.json
@@ -0,0 +1,97 @@
+{
+  "name": "ObjectDetector",
+  "description": "Identify which of a known set of objects might be present and provide information about their positions within the given image or a video stream.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be detected.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "score",
+          "description": "The scores of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "location",
+          "description": "The locations of the detected boxes.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+              "index": [
+                1,
+                0,
+                3,
+                2
+              ],
+              "type": "BOUNDARIES"
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "number of detections",
+          "description": "The number of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "category",
+          "description": "The categories of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_groups": [
+        {
+          "name": "detection_result",
+          "tensor_names": [
+            "location",
+            "category",
+            "score"
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/labelmap.txt b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/labelmap.txt
new file mode 100644
index 0000000..695772dc
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/labelmap.txt
@@ -0,0 +1,90 @@
+person
+bicycle
+car
+motorcycle
+airplane
+bus
+train
+truck
+boat
+traffic light
+fire hydrant
+???
+stop sign
+parking meter
+bench
+bird
+cat
+dog
+horse
+sheep
+cow
+elephant
+bear
+zebra
+giraffe
+???
+backpack
+umbrella
+???
+???
+handbag
+tie
+suitcase
+frisbee
+skis
+snowboard
+sports ball
+kite
+baseball bat
+baseball glove
+skateboard
+surfboard
+tennis racket
+bottle
+???
+wine glass
+cup
+fork
+knife
+spoon
+bowl
+banana
+apple
+sandwich
+orange
+broccoli
+carrot
+hot dog
+pizza
+donut
+cake
+chair
+couch
+potted plant
+bed
+???
+dining table
+???
+???
+toilet
+???
+tv
+laptop
+mouse
+remote
+keyboard
+cell phone
+microwave
+oven
+toaster
+sink
+refrigerator
+???
+book
+clock
+vase
+scissors
+teddy bear
+hair drier
+toothbrush
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/score_calibration.csv b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/score_calibration.csv
new file mode 100644
index 0000000..1127d3d
--- /dev/null
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/score_calibration_dummy.csv b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/score_calibration_dummy.csv
new file mode 100644
index 0000000..98b1b14
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/score_calibration_dummy.csv
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diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1.json
new file mode 100644
index 0000000..36eb0c4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1.json
@@ -0,0 +1,123 @@
+{
+  "name": "ObjectDetector",
+  "description": "Identify which of a known set of objects might be present and provide information about their positions within the given image or a video stream.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be detected.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "process_units": [
+            {
+              "options_type": "NormalizationOptions",
+              "options": {
+                "mean": [
+                  127.5
+                ],
+                "std": [
+                  127.5
+                ]
+              }
+            }
+          ],
+          "stats": {
+            "max": [
+              255.0
+            ],
+            "min": [
+              0.0
+            ]
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "location",
+          "description": "The locations of the detected boxes.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+              "index": [
+                1,
+                0,
+                3,
+                2
+              ],
+              "type": "BOUNDARIES"
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "category",
+          "description": "The categories of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          },
+          "associated_files": [
+            {
+              "name": "labelmap.txt",
+              "description": "Labels for categories that the model can recognize.",
+              "type": "TENSOR_VALUE_LABELS"
+            }
+          ]
+        },
+        {
+          "name": "score",
+          "description": "The scores of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "number of detections",
+          "description": "The number of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_groups": [
+        {
+          "name": "detection_result",
+          "tensor_names": [
+            "location",
+            "category",
+            "score"
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1.tflite b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1.tflite
new file mode 100644
index 0000000..8015ee5
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1.tflite
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1_default.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1_default.json
new file mode 100644
index 0000000..365892a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/object_detector/ssd_mobilenet_v1_default.json
@@ -0,0 +1,97 @@
+{
+  "name": "ObjectDetector",
+  "description": "Identify which of a known set of objects might be present and provide information about their positions within the given image or a video stream.",
+  "subgraph_metadata": [
+    {
+      "input_tensor_metadata": [
+        {
+          "name": "image",
+          "description": "Input image to be detected.",
+          "content": {
+            "content_properties_type": "ImageProperties",
+            "content_properties": {
+              "color_space": "RGB"
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_metadata": [
+        {
+          "name": "location",
+          "description": "The locations of the detected boxes.",
+          "content": {
+            "content_properties_type": "BoundingBoxProperties",
+            "content_properties": {
+              "index": [
+                1,
+                0,
+                3,
+                2
+              ],
+              "type": "BOUNDARIES"
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "category",
+          "description": "The categories of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "score",
+          "description": "The scores of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            },
+            "range": {
+              "min": 2,
+              "max": 2
+            }
+          },
+          "stats": {
+          }
+        },
+        {
+          "name": "number of detections",
+          "description": "The number of the detected boxes.",
+          "content": {
+            "content_properties_type": "FeatureProperties",
+            "content_properties": {
+            }
+          },
+          "stats": {
+          }
+        }
+      ],
+      "output_tensor_groups": [
+        {
+          "name": "detection_result",
+          "tensor_names": [
+            "location",
+            "category",
+            "score"
+          ]
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/question_answerer/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/question_answerer/BUILD
new file mode 100644
index 0000000..a136206
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/question_answerer/BUILD
@@ -0,0 +1,17 @@
+load("//tensorflow_lite_support/tools/build_rules:http_files.bzl", "tflite_model")
+
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+filegroup(
+    name = "test_files",
+    srcs = glob([
+        "*.json",
+        "*.tflite",
+        "*.txt",
+    ]) + [":mobilebert_float"],
+)
+
+tflite_model(name = "mobilebert_float")
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/regex_tokenizer_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/regex_tokenizer_meta.json
new file mode 100644
index 0000000..dc1f2f6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/regex_tokenizer_meta.json
@@ -0,0 +1,21 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_process_units": [
+        {
+          "options_type": "RegexTokenizerOptions",
+          "options": {
+            "delim_regex_pattern": "[^\\w\\']+",
+            "vocab_file": [
+              {
+                "name": "vocab.txt",
+                "description": "Vocabulary file to convert natural language words to embedding vectors.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/score_calibration_file_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/score_calibration_file_meta.json
new file mode 100644
index 0000000..c47d846
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/score_calibration_file_meta.json
@@ -0,0 +1,9 @@
+{
+  "associated_files": [
+    {
+      "name": "score_calibration.txt",
+      "description": "Contains sigmoid-based score calibration parameters. The main purposes of score calibration is to make scores across classes comparable, so that a common threshold can be used for all output classes.",
+      "type": "TENSOR_AXIS_SCORE_CALIBRATION"
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/score_calibration_tensor_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/score_calibration_tensor_meta.json
new file mode 100644
index 0000000..fd6c0e4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/score_calibration_tensor_meta.json
@@ -0,0 +1,15 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_process_units": [
+        {
+          "options_type": "ScoreCalibrationOptions",
+          "options": {
+            "score_transformation": "LOG",
+            "default_score": 0.2
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/sentence_piece_tokenizer_meta.json b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/sentence_piece_tokenizer_meta.json
new file mode 100644
index 0000000..b728908
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/metadata/python/tests/testdata/sentence_piece_tokenizer_meta.json
@@ -0,0 +1,26 @@
+{
+  "subgraph_metadata": [
+    {
+      "input_process_units": [
+        {
+          "options_type": "SentencePieceTokenizerOptions",
+          "options": {
+            "sentencePiece_model": [
+              {
+                "name": "sp.model",
+                "description": "The sentence piece model file."
+              }
+            ],
+            "vocab_file": [
+              {
+                "name": "vocab.txt",
+                "description": "Vocabulary file to convert natural language words to embedding vectors. This file is optional during tokenization, while the sentence piece model is mandatory.",
+                "type": "VOCABULARY"
+              }
+            ]
+          }
+        }
+      ]
+    }
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/README.md b/third_party/tflite_support/src/tensorflow_lite_support/odml/README.md
new file mode 100644
index 0000000..f9f568d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/README.md
@@ -0,0 +1,7 @@
+# Standardized ODML Data Containers
+
+Provides a set of standardized on-device ML (ODML) data containers, which could
+be shared cross-platforms, among different ODML frameworks (TFLite, MediaPipe,
+ML Kit), to increase the interoperability, share data conversions with hardwares
+(CPU, OpenGL, OpenCL, NNAPI, AHardwareBuffer, Vulkan, etc.) and reduce data
+copies.
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/BUILD
new file mode 100644
index 0000000..0da2aa4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/BUILD
@@ -0,0 +1,126 @@
+# ODML image library for iOS
+
+load(
+    "@org_tensorflow//tensorflow/lite/ios:ios.bzl",
+    "TFL_MINIMUM_OS_VERSION",
+)
+load(
+    "@org_tensorflow//tensorflow/lite:special_rules.bzl",
+    "tflite_ios_lab_runner",
+)
+load(
+    "@build_bazel_rules_apple//apple:ios.bzl",
+    "ios_static_framework",
+    "ios_unit_test",
+)
+
+package(
+    default_visibility = ["//visibility:private"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+SOURCES = glob([
+    "sources/*.h",
+    "sources/*.m",
+    "sources/*.mm",
+])
+
+API_HEADERS = glob([
+    "apis/*.h",
+])
+
+# Compiler flags for building regular non-test libraries.
+RELEASE_COPTS = [
+    # Enables language-specific warnings for Objective-C, Objective-C++, C, and C++.
+    "-Wall",
+    # Warns if functions, variables, and types marked with the deprecated attribute are being used.
+    "-Wdeprecated-declarations",
+    # Warns for errors in documentation.
+    "-Wdocumentation",
+    # Turns all warnings into errors.
+    "-Werror",
+    # Enables extra warning flags that are not enabled by -Wall.
+    "-Wextra",
+    # Warns if a global function is defined without a previous prototype declaration.
+    "-Wmissing-prototypes",
+    # From -Wextra. Disables warning when signed value is converted to unsigned value during comparison.
+    "-Wno-sign-compare",
+    # From -Wextra. Disables warning for unused parameters, which are common in delegate methods and block callbacks.
+    "-Wno-unused-parameter",
+    # Warns if a global or local variable or type declaration shadows another variable, parameter, type, class member, or instance variable.
+    "-Wshadow",
+    # Warns if a function is declared or defined without specifying the argument types. For a block with no args, use (void) instead of ().
+    "-Wstrict-prototypes",
+    # Warns if an @selector() expression is encountered with a method name that hasn't been defined yet.
+    "-Wundeclared-selector",
+    # Turn off warnings for headers not part of TensorFlow Lite Objective-C API.
+    "--system-header-prefix=third_party/tensorflow/lite/c/",
+]
+
+# Compiler flags for building test libraries.
+TEST_COPTS = RELEASE_COPTS + [
+    # From -Wall. Disables warning when passing nil to a callee that requires a non-null argument.
+    "-Wno-nonnull",
+    # Disables warning when a global or local variable or type declaration shadows another.
+    "-Wno-shadow",
+]
+
+objc_library(
+    name = "MLImage",
+    srcs = SOURCES,
+    hdrs = API_HEADERS,
+    copts = RELEASE_COPTS,
+    module_name = "MLImage",
+    sdk_frameworks = [
+        "CoreGraphics",
+        "CoreMedia",
+        "CoreVideo",
+    ],
+    visibility = ["//visibility:public"],
+    alwayslink = 1,
+)
+
+ios_static_framework(
+    name = "MLImage_framework",
+    hdrs = API_HEADERS,
+    bundle_name = "MLImage",
+    minimum_os_version = TFL_MINIMUM_OS_VERSION,
+    visibility = ["//visibility:public"],
+    deps = [":MLImage"],
+)
+
+ios_unit_test(
+    name = "tests",
+    size = "small",
+    minimum_os_version = TFL_MINIMUM_OS_VERSION,
+    runner = tflite_ios_lab_runner("IOS_LATEST"),
+    deps = [
+        ":TestsLibrary",
+    ],
+)
+
+objc_library(
+    name = "TestsLibrary",
+    testonly = 1,
+    srcs = glob([
+        "tests/*.m",
+    ]),
+    hdrs = glob([
+        "apis/*.h",
+        "sources/*.h",
+        "tests/*.h",
+    ]),
+    copts = TEST_COPTS,
+    data = glob([
+        "resources/*.jpg",
+    ]),
+    sdk_frameworks = [
+        "Accelerate",
+        "CoreGraphics",
+        "CoreMedia",
+        "CoreVideo",
+    ],
+    deps = [
+        ":MLImage",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj/Configs/MLImage.tulsigen b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj/Configs/MLImage.tulsigen
new file mode 100644
index 0000000..2a9620d28
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj/Configs/MLImage.tulsigen
@@ -0,0 +1,54 @@
+{
+  "sourceFilters" : [
+    "third_party/tensorflow_lite_support/odml/ios/image",
+    "third_party/tensorflow_lite_support/odml/ios/image/apis",
+    "third_party/tensorflow_lite_support/odml/ios/image/sources",
+    "third_party/tensorflow_lite_support/odml/ios/image/tests"
+  ],
+  "buildTargets" : [
+    "//third_party/tensorflow_lite_support/odml/ios/image:MLImage",
+    "//third_party/tensorflow_lite_support/odml/ios/image:tests"
+  ],
+  "projectName" : "MLImage",
+  "optionSet" : {
+    "LaunchActionPreActionScript" : {
+      "p" : "$(inherited)"
+    },
+    "BazelBuildStartupOptionsRelease" : {
+      "p" : "$(inherited)"
+    },
+    "BazelBuildOptionsRelease" : {
+      "p" : "$(inherited)"
+    },
+    "BazelBuildOptionsDebug" : {
+      "p" : "$(inherited)"
+    },
+    "EnvironmentVariables" : {
+      "p" : "$(inherited)"
+    },
+    "BuildActionPreActionScript" : {
+      "p" : "$(inherited)"
+    },
+    "CommandlineArguments" : {
+      "p" : "$(inherited)"
+    },
+    "TestActionPreActionScript" : {
+      "p" : "$(inherited)"
+    },
+    "BazelBuildStartupOptionsDebug" : {
+      "p" : "$(inherited)"
+    },
+    "BuildActionPostActionScript" : {
+      "p" : "$(inherited)"
+    },
+    "TestActionPostActionScript" : {
+      "p" : "$(inherited)"
+    },
+    "LaunchActionPostActionScript" : {
+      "p" : "$(inherited)"
+    }
+  },
+  "additionalFilePaths" : [
+    "third_party/tensorflow_lite_support/odml/ios/image/BUILD"
+  ]
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj/project.tulsiconf b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj/project.tulsiconf
new file mode 100644
index 0000000..15279da
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj/project.tulsiconf
@@ -0,0 +1,17 @@
+{
+  "configDefaults" : {
+    "optionSet" : {
+      "BazelBuildOptionsDebug" : {
+
+      },
+      "BazelBuildOptionsRelease" : {
+
+      },
+    }
+  },
+  "projectName" : "MLImage",
+  "packages" : [
+    "third_party/tensorflow_lite_support/odml/ios/image"
+  ],
+  "workspaceRoot" : "../../../../../.."
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/README.md b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/README.md
new file mode 100644
index 0000000..2f9a0658
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/README.md
@@ -0,0 +1,27 @@
+# MLImage for iOS
+
+MLImage is a lightweight image library for iOS developers. It provides a
+common image format to increase interoperability among various on-device
+machine learning frameworks.
+
+Build the `MLImage` Objective-C library target:
+
+```shell
+bazel build -c opt --apple_platform_type=ios tensorflow_lite_support/odml/ios/image:MLImage
+```
+
+Build the `tests` target:
+
+```shell
+bazel test -c opt --apple_platform_type=ios tensorflow_lite_support/odml/ios/image:tests
+```
+
+#### Generate the Xcode project using Tulsi
+
+Open the `//tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj` using
+the [TulsiApp](https://github.com/bazelbuild/tulsi) or by running the
+[`generate_xcodeproj.sh`](https://github.com/bazelbuild/tulsi/blob/master/src/tools/generate_xcodeproj.sh):
+
+```shell
+generate_xcodeproj.sh --genconfig tensorflow_lite_support/odml/ios/image/MLImage.tulsiproj:MLImage --outputfolder ~/path/to/generated/MLImage.xcodeproj
+```
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h
new file mode 100644
index 0000000..0c49491
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/apis/GMLImage.h
@@ -0,0 +1,103 @@
+// Copyright 2021 Google LLC. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at:
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import <CoreMedia/CoreMedia.h>
+#import <CoreVideo/CoreVideo.h>
+#import <UIKit/UIKit.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+/** Types of image sources. */
+typedef NSInteger GMLImageSourceType NS_TYPED_ENUM
+    NS_SWIFT_NAME(MLImageSourceType);
+/** Image source is a `UIImage`. */
+static const GMLImageSourceType GMLImageSourceTypeImage = 0;
+/** Image source is a `CVPixelBuffer`. */
+static const GMLImageSourceType GMLImageSourceTypePixelBuffer = 1;
+/** Image source is a `CMSampleBuffer`. */
+static const GMLImageSourceType GMLImageSourceTypeSampleBuffer = 2;
+
+/** An image used in on-device machine learning. */
+NS_SWIFT_NAME(MLImage)
+@interface GMLImage : NSObject
+
+/** Width of the image in pixels. */
+@property(nonatomic, readonly) CGFloat width;
+
+/** Height of the image in pixels. */
+@property(nonatomic, readonly) CGFloat height;
+
+/**
+ * The display orientation of the image. If `imageSourceType` is `.image`, the
+ * default value is `image.imageOrientation`; otherwise the default value is
+ * `.up`.
+ */
+@property(nonatomic) UIImageOrientation orientation;
+
+/** The type of the image source. */
+@property(nonatomic, readonly) GMLImageSourceType imageSourceType;
+
+/** The source image. `nil` if `imageSourceType` is not `.image`. */
+@property(nonatomic, readonly, nullable) UIImage* image;
+
+/** The source pixel buffer. `nil` if `imageSourceType` is not `.pixelBuffer`.
+ */
+@property(nonatomic, readonly, nullable) CVPixelBufferRef pixelBuffer;
+
+/** The source sample buffer. `nil` if `imageSourceType` is not `.sampleBuffer`.
+ */
+@property(nonatomic, readonly, nullable) CMSampleBufferRef sampleBuffer;
+
+/**
+ * Initializes an `MLImage` object with the given image.
+ *
+ * @param image The image to use as the source. Its `CGImage` property must not
+ * be `NULL`.
+ * @return A new `MLImage` instance with the given image as the source. `nil` if
+ * the given `image` is `nil` or invalid.
+ */
+- (nullable instancetype)initWithImage:(UIImage*)image
+    NS_DESIGNATED_INITIALIZER;
+
+/**
+ * Initializes an `MLImage` object with the given pixel buffer.
+ *
+ * @param pixelBuffer The pixel buffer to use as the source. It will be retained
+ * by the new `MLImage` instance for the duration of its lifecycle.
+ * @return A new `MLImage` instance with the given pixel buffer as the source.
+ * `nil` if the given pixel buffer is `nil` or invalid.
+ */
+- (nullable instancetype)initWithPixelBuffer:(CVPixelBufferRef)pixelBuffer
+    NS_DESIGNATED_INITIALIZER;
+
+/**
+ * Initializes an `MLImage` object with the given sample buffer.
+ *
+ * @param sampleBuffer The sample buffer to use as the source. It will be
+ * retained by the new `MLImage` instance for the duration of its lifecycle. The
+ * sample buffer must be based on a pixel buffer (not compressed data). In
+ * practice, it should be the video output of the camera on an iOS device, not
+ * other arbitrary types of `CMSampleBuffer`s.
+ * @return A new `MLImage` instance with the given sample buffer as the source.
+ * `nil` if the given sample buffer is `nil` or invalid.
+ */
+- (nullable instancetype)initWithSampleBuffer:(CMSampleBufferRef)sampleBuffer
+    NS_DESIGNATED_INITIALIZER;
+
+/** Unavailable. */
+- (instancetype)init NS_UNAVAILABLE;
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/resources/grace_hopper.jpg b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/resources/grace_hopper.jpg
new file mode 100644
index 0000000..d2a4278
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/resources/grace_hopper.jpg
Binary files differ
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m
new file mode 100644
index 0000000..38ca7426
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/sources/GMLImage.m
@@ -0,0 +1,91 @@
+// Copyright 2021 Google LLC. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at:
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "tensorflow_lite_support/odml/ios/image/apis/GMLImage.h"
+
+NS_ASSUME_NONNULL_BEGIN
+
+@implementation GMLImage
+
+#pragma mark - Public
+
+- (nullable instancetype)initWithImage:(UIImage*)image {
+  if (image.CGImage == NULL) {
+    return nil;
+  }
+
+  self = [super init];
+  if (self != nil) {
+    _imageSourceType = GMLImageSourceTypeImage;
+    _orientation = image.imageOrientation;
+    _image = image;
+    _width = image.size.width * image.scale;
+    _height = image.size.height * image.scale;
+  }
+  return self;
+}
+
+- (nullable instancetype)initWithPixelBuffer:(CVPixelBufferRef)pixelBuffer {
+  if (pixelBuffer == NULL) {
+    return nil;
+  }
+
+  self = [super init];
+  if (self != nil) {
+    _imageSourceType = GMLImageSourceTypePixelBuffer;
+    _orientation = UIImageOrientationUp;
+    CVPixelBufferRetain(pixelBuffer);
+    _pixelBuffer = pixelBuffer;
+    _width = CVPixelBufferGetWidth(pixelBuffer);
+    _height = CVPixelBufferGetHeight(pixelBuffer);
+  }
+  return self;
+}
+
+- (nullable instancetype)initWithSampleBuffer:(CMSampleBufferRef)sampleBuffer {
+  if (!CMSampleBufferIsValid(sampleBuffer)) {
+    return nil;
+  }
+
+  CVImageBufferRef imageBuffer = CMSampleBufferGetImageBuffer(sampleBuffer);
+  if (imageBuffer == NULL) {
+    return nil;
+  }
+
+  self = [super init];
+  if (self != nil) {
+    _imageSourceType = GMLImageSourceTypeSampleBuffer;
+    _orientation = UIImageOrientationUp;
+    CFRetain(sampleBuffer);
+    _sampleBuffer = sampleBuffer;
+    _width = CVPixelBufferGetWidth(imageBuffer);
+    _height = CVPixelBufferGetHeight(imageBuffer);
+  }
+  return self;
+}
+
+#pragma mark - NSObject
+
+- (void)dealloc {
+  if (_sampleBuffer != NULL) {
+    CFRelease(_sampleBuffer);
+  }
+  if (_pixelBuffer != NULL) {
+    CVPixelBufferRelease(_pixelBuffer);
+  }
+}
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m
new file mode 100644
index 0000000..8abee1a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/ios/image/tests/GMLImageTests.m
@@ -0,0 +1,196 @@
+// Copyright 2021 Google LLC. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at:
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "tensorflow_lite_support/odml/ios/image/apis/GMLImage.h"
+
+#import <Accelerate/Accelerate.h>
+#import <CoreGraphics/CoreGraphics.h>
+#import <CoreMedia/CoreMedia.h>
+#import <CoreVideo/CoreVideo.h>
+#import <XCTest/XCTest.h>
+
+NS_ASSUME_NONNULL_BEGIN
+
+static NSString* const kTestImageName = @"grace_hopper";
+static NSString* const kTestImageType = @"jpg";
+static CGFloat kTestImageWidthInPixels = 517.0f;
+static CGFloat kTestImageHeightInPixels = 606.0f;
+
+/** Unit tests for `GMLImage`. */
+@interface GMLImageTests : XCTestCase
+
+/** Test image. */
+@property(nonatomic, nullable) UIImage* image;
+
+@end
+
+@implementation GMLImageTests
+
+#pragma mark - Tests
+
+- (void)setUp {
+  [super setUp];
+  NSString* imageName =
+      [[NSBundle bundleForClass:[self class]] pathForResource:kTestImageName
+                                                       ofType:kTestImageType];
+  self.image = [[UIImage alloc] initWithContentsOfFile:imageName];
+}
+
+- (void)tearDown {
+  self.image = nil;
+  [super tearDown];
+}
+
+- (void)testInitWithImage {
+  GMLImage* mlImage = [[GMLImage alloc] initWithImage:self.image];
+  XCTAssertNotNil(mlImage);
+  XCTAssertEqual(mlImage.imageSourceType, GMLImageSourceTypeImage);
+  XCTAssertEqual(mlImage.orientation, self.image.imageOrientation);
+  mlImage.orientation = UIImageOrientationDown;
+  XCTAssertEqual(mlImage.orientation, UIImageOrientationDown);
+  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels,
+                             FLT_EPSILON);
+  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels,
+                             FLT_EPSILON);
+}
+
+- (void)testInitWithImage_nilImage {
+  GMLImage* mlImage = [[GMLImage alloc] initWithImage:nil];
+  XCTAssertNil(mlImage);
+}
+
+- (void)testInitWithSampleBuffer {
+  CMSampleBufferRef sampleBuffer = [self sampleBuffer];
+  GMLImage* mlImage = [[GMLImage alloc] initWithSampleBuffer:sampleBuffer];
+  XCTAssertNotNil(mlImage);
+  XCTAssertEqual(mlImage.imageSourceType, GMLImageSourceTypeSampleBuffer);
+  XCTAssertEqual(mlImage.orientation, UIImageOrientationUp);
+  mlImage.orientation = UIImageOrientationDown;
+  XCTAssertEqual(mlImage.orientation, UIImageOrientationDown);
+  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels,
+                             FLT_EPSILON);
+  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels,
+                             FLT_EPSILON);
+}
+
+- (void)testInitWithSampleBuffer_nilImage {
+  GMLImage* mlImage = [[GMLImage alloc] initWithSampleBuffer:nil];
+  XCTAssertNil(mlImage);
+}
+
+- (void)testInitWithPixelBuffer {
+  CMSampleBufferRef sampleBuffer = [self sampleBuffer];
+  CVPixelBufferRef pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer);
+  GMLImage* mlImage = [[GMLImage alloc] initWithPixelBuffer:pixelBuffer];
+  XCTAssertNotNil(mlImage);
+  XCTAssertEqual(mlImage.imageSourceType, GMLImageSourceTypePixelBuffer);
+  XCTAssertEqual(mlImage.orientation, UIImageOrientationUp);
+  mlImage.orientation = UIImageOrientationDown;
+  XCTAssertEqual(mlImage.orientation, UIImageOrientationDown);
+  XCTAssertEqualWithAccuracy(mlImage.width, kTestImageWidthInPixels,
+                             FLT_EPSILON);
+  XCTAssertEqualWithAccuracy(mlImage.height, kTestImageHeightInPixels,
+                             FLT_EPSILON);
+}
+
+- (void)testInitWithPixelBuffer_nilImage {
+  GMLImage* mlImage = [[GMLImage alloc] initWithPixelBuffer:nil];
+  XCTAssertNil(mlImage);
+}
+
+#pragma mark - Private
+
+/**
+ * Converts the input image in RGBA space into a `CMSampleBuffer`.
+ *
+ * @return `CMSampleBuffer` converted from the given `UIImage`.
+ */
+- (CMSampleBufferRef)sampleBuffer {
+  // Rotate the image and convert from RGBA to BGRA.
+  CGImageRef CGImage = self.image.CGImage;
+  size_t width = CGImageGetWidth(CGImage);
+  size_t height = CGImageGetHeight(CGImage);
+  size_t bpr = CGImageGetBytesPerRow(CGImage);
+
+  CGDataProviderRef provider = CGImageGetDataProvider(CGImage);
+  NSData* imageRGBAData =
+      (id)CFBridgingRelease(CGDataProviderCopyData(provider));
+  const uint8_t order[4] = {2, 1, 0, 3};
+
+  NSData* imageBGRAData = nil;
+  unsigned char* bgraPixel = (unsigned char*)malloc([imageRGBAData length]);
+  if (bgraPixel) {
+    vImage_Buffer src;
+    src.height = height;
+    src.width = width;
+    src.rowBytes = bpr;
+    src.data = (void*)[imageRGBAData bytes];
+
+    vImage_Buffer dest;
+    dest.height = height;
+    dest.width = width;
+    dest.rowBytes = bpr;
+    dest.data = bgraPixel;
+
+    // Specify ordering changes in map.
+    vImage_Error error =
+        vImagePermuteChannels_ARGB8888(&src, &dest, order, kvImageNoFlags);
+
+    // Package the result.
+    if (error == kvImageNoError) {
+      imageBGRAData = [NSData dataWithBytes:bgraPixel
+                                     length:[imageRGBAData length]];
+    }
+
+    // Memory cleanup.
+    free(bgraPixel);
+  }
+
+  if (imageBGRAData == nil) {
+    XCTFail(@"Failed to convert input image.");
+  }
+
+  // Write data to `CMSampleBuffer`.
+  NSDictionary* options = @{
+    (__bridge NSString*)kCVPixelBufferCGImageCompatibilityKey : @(YES),
+    (__bridge NSString*)kCVPixelBufferCGBitmapContextCompatibilityKey : @(YES)
+  };
+  CVPixelBufferRef pixelBuffer;
+  CVReturn status = CVPixelBufferCreateWithBytes(
+      kCFAllocatorDefault, width, height, kCVPixelFormatType_32BGRA,
+      (void*)[imageBGRAData bytes], bpr, NULL, nil,
+      (__bridge CFDictionaryRef)options, &pixelBuffer);
+
+  if (status != kCVReturnSuccess) {
+    XCTFail(@"Failed to create pixel buffer.");
+  }
+
+  CVPixelBufferLockBaseAddress(pixelBuffer, 0);
+  CMVideoFormatDescriptionRef videoInfo = NULL;
+  CMVideoFormatDescriptionCreateForImageBuffer(kCFAllocatorDefault, pixelBuffer,
+                                               &videoInfo);
+
+  CMSampleBufferRef buffer;
+  CMSampleBufferCreateForImageBuffer(kCFAllocatorDefault, pixelBuffer, true,
+                                     NULL, NULL, videoInfo,
+                                     &kCMTimingInfoInvalid, &buffer);
+
+  CVPixelBufferUnlockBaseAddress(pixelBuffer, 0);
+
+  return buffer;
+}
+
+@end
+
+NS_ASSUME_NONNULL_END
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/AndroidManifest.xml
new file mode 100644
index 0000000..aa95182
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/AndroidManifest.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="utf-8"?>
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+    package="com.google.android.odml.image">
+  <uses-sdk android:minSdkVersion="16" />
+  <application />
+</manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/BUILD
new file mode 100644
index 0000000..882fcf2
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/BUILD
@@ -0,0 +1,17 @@
+load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+
+licenses(["notice"])
+
+android_library(
+    name = "image",
+    srcs = glob(["src/**/*.java"]),
+    custom_package = "com.google.android.odml.image",
+    manifest = "AndroidManifest.xml",
+    visibility = [
+        "//visibility:public",
+    ],
+    deps = [
+        "@com_google_auto_value",
+        "@maven//:androidx_annotation_annotation",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/image.pgcfg b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/image.pgcfg
new file mode 100644
index 0000000..95a2a2d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/image.pgcfg
@@ -0,0 +1,38 @@
+# Copyright 2021 Google LLC. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Keep objects marked as needing to be "kept" when making the SDK, but don't
+# export these rules to end developers, so they will be allowed to strip these.
+-keep @interface com.google.android.odml.image.annotation.KeepForSdk
+-keep @com.google.android.odml.image.annotation.KeepForSdk class *
+-keepclasseswithmembers,includedescriptorclasses class * {
+  @com.google.android.odml.image.annotation.KeepForSdk <fields>;
+}
+-keepclasseswithmembers,includedescriptorclasses class * {
+  # We use "!bridge" below to avoid applying the keep on "bridge" methods.
+  # Bridge methods are generated by the Java compiler during type erasure:
+  # https://docs.oracle.com/javase/tutorial/java/generics/bridgeMethods.html
+  # This may cause a super class that does not need the @KeepForSdk on a method
+  # to get a generated method that does include the @KeepForSdk (because the
+  # subclass has @KeepForSdk on the method being bridged). Since the generated
+  # method in the super class gets @KeepForSdk, this causes the super class
+  # itself to be unnecessarily kept by name. Since our @KeepForSdk are meant to
+  # be explicit directives on a particular method (and not necessarily
+  # inheritted), we do not need to apply the @KeepForSdk rule on such bridge
+  # methods.
+  @com.google.android.odml.image.annotation.KeepForSdk !bridge <methods>;
+}
+-keepclasseswithmembers,includedescriptorclasses class * {
+  @com.google.android.odml.image.annotation.KeepForSdk <init>(...);
+}
\ No newline at end of file
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java
new file mode 100644
index 0000000..59116a7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapExtractor.java
@@ -0,0 +1,50 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Bitmap;
+
+/**
+ * Utility for extracting {@link android.graphics.Bitmap} from {@link MlImage}.
+ *
+ * <p>Currently it only supports {@link MlImage} with {@link MlImage#STORAGE_TYPE_BITMAP}, otherwise
+ * {@link IllegalArgumentException} will be thrown.
+ */
+public final class BitmapExtractor {
+    /**
+     * Extracts a {@link android.graphics.Bitmap} from an {@link MlImage}.
+     *
+     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+     *
+     * @param image the image to extract {@link android.graphics.Bitmap} from.
+     * @return the {@link android.graphics.Bitmap} stored in {@link MlImage}
+     * @throws IllegalArgumentException when the extraction requires unsupported format or data type
+     *     conversions.
+     */
+    public static Bitmap extract(MlImage image) {
+        ImageContainer imageContainer = image.getContainer(MlImage.STORAGE_TYPE_BITMAP);
+        if (imageContainer != null) {
+            return ((BitmapImageContainer) imageContainer).getBitmap();
+        } else {
+            // TODO(b/180504869): Support ByteBuffer -> Bitmap conversion.
+            throw new IllegalArgumentException(
+                    "Extracting Bitmap from an MlImage created by objects other than Bitmap is not"
+                    + " supported");
+        }
+    }
+
+    private BitmapExtractor() {}
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java
new file mode 100644
index 0000000..b1b02f8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapImageContainer.java
@@ -0,0 +1,59 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Bitmap;
+
+import com.google.android.odml.image.MlImage.ImageFormat;
+
+class BitmapImageContainer implements ImageContainer {
+    private final Bitmap bitmap;
+    private final ImageProperties properties;
+
+    public BitmapImageContainer(Bitmap bitmap) {
+        this.bitmap = bitmap;
+        this.properties = ImageProperties.builder()
+                                  .setImageFormat(convertFormatCode(bitmap.getConfig()))
+                                  .setStorageType(MlImage.STORAGE_TYPE_BITMAP)
+                                  .build();
+    }
+
+    public Bitmap getBitmap() {
+        return bitmap;
+    }
+
+    @Override
+    public ImageProperties getImageProperties() {
+        return properties;
+    }
+
+    @Override
+    public void close() {
+        bitmap.recycle();
+    }
+
+    @ImageFormat
+    static int convertFormatCode(Bitmap.Config config) {
+        switch (config) {
+            case ALPHA_8:
+                return MlImage.IMAGE_FORMAT_ALPHA;
+            case ARGB_8888:
+                return MlImage.IMAGE_FORMAT_RGBA;
+            default:
+                return MlImage.IMAGE_FORMAT_UNKNOWN;
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java
new file mode 100644
index 0000000..6c4552b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/BitmapMlImageBuilder.java
@@ -0,0 +1,108 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.content.Context;
+import android.graphics.Bitmap;
+import android.graphics.Rect;
+import android.net.Uri;
+import android.provider.MediaStore;
+
+import java.io.IOException;
+
+/**
+ * Builds {@link MlImage} from {@link android.graphics.Bitmap}.
+ *
+ * <p>You can pass in either mutable or immutable {@link android.graphics.Bitmap}. However once
+ * {@link android.graphics.Bitmap} is passed in, to keep data integrity you shouldn't modify content
+ * in it.
+ *
+ * <p>Use {@link BitmapExtractor} to get {@link android.graphics.Bitmap} you passed in.
+ */
+public class BitmapMlImageBuilder {
+    // Mandatory fields.
+    private final Bitmap bitmap;
+
+    // Optional fields.
+    private int rotation;
+    private Rect roi;
+    private long timestamp;
+
+    /**
+     * Creates the builder with a mandatory {@link android.graphics.Bitmap}.
+     *
+     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
+     * values will be set with default:
+     *
+     * <ul>
+     *   <li>rotation: 0
+     * </ul>
+     *
+     * @param bitmap image data object.
+     */
+    public BitmapMlImageBuilder(Bitmap bitmap) {
+        this.bitmap = bitmap;
+        rotation = 0;
+        roi = new Rect(0, 0, bitmap.getWidth(), bitmap.getHeight());
+        timestamp = 0;
+    }
+
+    /**
+     * Creates the builder to build {@link MlImage} from a file.
+     *
+     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
+     * values will be set with default:
+     *
+     * <ul>
+     *   <li>rotation: 0
+     * </ul>
+     *
+     * @param context the application context.
+     * @param uri the path to the resource file.
+     */
+    public BitmapMlImageBuilder(Context context, Uri uri) throws IOException {
+        this(MediaStore.Images.Media.getBitmap(context.getContentResolver(), uri));
+    }
+
+    /**
+     * Sets value for {@link MlImage#getRotation()}.
+     *
+     * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
+     */
+    public BitmapMlImageBuilder setRotation(int rotation) {
+        MlImage.validateRotation(rotation);
+        this.rotation = rotation;
+        return this;
+    }
+
+    /** Sets value for {@link MlImage#getRoi()}. */
+    BitmapMlImageBuilder setRoi(Rect roi) {
+        this.roi = roi;
+        return this;
+    }
+
+    /** Sets value for {@link MlImage#getTimestamp()}. */
+    BitmapMlImageBuilder setTimestamp(long timestamp) {
+        this.timestamp = timestamp;
+        return this;
+    }
+
+    /** Builds an {@link MlImage} instance. */
+    public MlImage build() {
+        return new MlImage(new BitmapImageContainer(bitmap), rotation, roi, timestamp,
+                bitmap.getWidth(), bitmap.getHeight());
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java
new file mode 100644
index 0000000..d5861c8c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferExtractor.java
@@ -0,0 +1,267 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Bitmap;
+import android.graphics.Bitmap.Config;
+import android.os.Build.VERSION;
+import android.os.Build.VERSION_CODES;
+
+import com.google.android.odml.image.MlImage.ImageFormat;
+import com.google.auto.value.AutoValue;
+
+import java.nio.ByteBuffer;
+import java.nio.ByteOrder;
+import java.util.Locale;
+
+/**
+ * Utility for extracting {@link ByteBuffer} from {@link MlImage}.
+ *
+ * <p>Currently it only supports {@link MlImage} with {@link MlImage#STORAGE_TYPE_BYTEBUFFER},
+ * otherwise {@link IllegalArgumentException} will be thrown.
+ */
+public class ByteBufferExtractor {
+    /**
+     * Extracts a {@link ByteBuffer} from an {@link MlImage}.
+     *
+     * <p>The returned {@link ByteBuffer} is a read-only view, with the first available {@link
+     * ImageProperties} whose storage type is {@code MlImage.STORAGE_TYPE_BYTEBUFFER}.
+     *
+     * @see MlImage#getContainedImageProperties()
+     * @return A read-only {@link ByteBuffer}.
+     * @throws IllegalArgumentException when the image doesn't contain a {@link ByteBuffer} storage.
+     */
+    public static ByteBuffer extract(MlImage image) {
+        ImageContainer container = image.getContainer();
+        switch (container.getImageProperties().getStorageType()) {
+            case MlImage.STORAGE_TYPE_BYTEBUFFER:
+                ByteBufferImageContainer byteBufferImageContainer =
+                        (ByteBufferImageContainer) container;
+                return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer();
+            default:
+                throw new IllegalArgumentException(
+                        "Extract ByteBuffer from an MlImage created by objects other than Bytebuffer is not"
+                        + " supported");
+        }
+    }
+
+    /**
+     * Extracts a readonly {@link ByteBuffer} in given {@code targetFormat} from an {@link MlImage}.
+     *
+     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+     *
+     * <p>Format conversion spec:
+     *
+     * <ul>
+     *   <li>When extracting RGB images to RGBA format, A channel will always set to 255.
+     *   <li>When extracting RGBA images to RGB format, A channel will be dropped.
+     * </ul>
+     *
+     * @param image the image to extract buffer from.
+     * @param targetFormat the image format of the result bytebuffer.
+     * @return the readonly {@link ByteBuffer} stored in {@link MlImage}
+     * @throws IllegalArgumentException when the extraction requires unsupported format or data type
+     *     conversions.
+     */
+    static ByteBuffer extract(MlImage image, @ImageFormat int targetFormat) {
+        ImageContainer container;
+        ImageProperties byteBufferProperties =
+                ImageProperties.builder()
+                        .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
+                        .setImageFormat(targetFormat)
+                        .build();
+        if ((container = image.getContainer(byteBufferProperties)) != null) {
+            ByteBufferImageContainer byteBufferImageContainer =
+                    (ByteBufferImageContainer) container;
+            return byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer();
+        } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER)) != null) {
+            ByteBufferImageContainer byteBufferImageContainer =
+                    (ByteBufferImageContainer) container;
+            @ImageFormat
+            int sourceFormat = byteBufferImageContainer.getImageFormat();
+            return convertByteBuffer(
+                    byteBufferImageContainer.getByteBuffer(), sourceFormat, targetFormat)
+                    .asReadOnlyBuffer();
+        } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP)) != null) {
+            BitmapImageContainer bitmapImageContainer = (BitmapImageContainer) container;
+            ByteBuffer byteBuffer =
+                    extractByteBufferFromBitmap(bitmapImageContainer.getBitmap(), targetFormat)
+                            .asReadOnlyBuffer();
+            image.addContainer(new ByteBufferImageContainer(byteBuffer, targetFormat));
+            return byteBuffer;
+        } else {
+            throw new IllegalArgumentException(
+                    "Extracting ByteBuffer from an MlImage created by objects other than Bitmap or"
+                    + " Bytebuffer is not supported");
+        }
+    }
+
+    /** A wrapper for a {@link ByteBuffer} and its {@link ImageFormat}. */
+    @AutoValue
+    abstract static class Result {
+        /**
+         * Gets the {@link ByteBuffer} in the result of {@link
+         * ByteBufferExtractor#extract(MlImage)}.
+         */
+        public abstract ByteBuffer buffer();
+
+        /**
+         * Gets the {@link ImageFormat} in the result of {@link
+         * ByteBufferExtractor#extract(MlImage)}.
+         */
+        @ImageFormat
+        public abstract int format();
+
+        static Result create(ByteBuffer buffer, @ImageFormat int imageFormat) {
+            return new AutoValue_ByteBufferExtractor_Result(buffer, imageFormat);
+        }
+    }
+
+    /**
+     * Extracts a {@link ByteBuffer} in any available {@code imageFormat} from an {@link MlImage}.
+     *
+     * <p>It will make the best effort to return an already existed {@link ByteBuffer} to avoid
+     * copy.
+     *
+     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+     *
+     * @return the readonly {@link ByteBuffer} stored in {@link MlImage}
+     * @throws IllegalArgumentException when {@code image} doesn't contain {@link ByteBuffer} with
+     *     given {@code imageFormat}
+     */
+    static Result extractInRecommendedFormat(MlImage image) {
+        ImageContainer container;
+        if ((container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP)) != null) {
+            Bitmap bitmap = ((BitmapImageContainer) container).getBitmap();
+            @ImageFormat
+            int format = adviseImageFormat(bitmap);
+            Result result = Result.create(
+                    extractByteBufferFromBitmap(bitmap, format).asReadOnlyBuffer(), format);
+
+            image.addContainer(new ByteBufferImageContainer(result.buffer(), result.format()));
+            return result;
+        } else if ((container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER)) != null) {
+            ByteBufferImageContainer byteBufferImageContainer =
+                    (ByteBufferImageContainer) container;
+            return Result.create(byteBufferImageContainer.getByteBuffer().asReadOnlyBuffer(),
+                    byteBufferImageContainer.getImageFormat());
+        } else {
+            throw new IllegalArgumentException(
+                    "Extract ByteBuffer from an MlImage created by objects other than Bitmap or Bytebuffer"
+                    + " is not supported");
+        }
+    }
+
+    @ImageFormat
+    private static int adviseImageFormat(Bitmap bitmap) {
+        if (bitmap.getConfig() == Config.ARGB_8888) {
+            return MlImage.IMAGE_FORMAT_RGBA;
+        } else {
+            throw new IllegalArgumentException(String.format(
+                    "Extracting ByteBuffer from an MlImage created by a Bitmap in config %s is not"
+                            + " supported",
+                    bitmap.getConfig()));
+        }
+    }
+
+    private static ByteBuffer extractByteBufferFromBitmap(
+            Bitmap bitmap, @ImageFormat int imageFormat) {
+        if (VERSION.SDK_INT >= VERSION_CODES.JELLY_BEAN_MR1 && bitmap.isPremultiplied()) {
+            throw new IllegalArgumentException(
+                    "Extracting ByteBuffer from an MlImage created by a premultiplied Bitmap is not"
+                    + " supported");
+        }
+        if (bitmap.getConfig() == Config.ARGB_8888) {
+            if (imageFormat == MlImage.IMAGE_FORMAT_RGBA) {
+                ByteBuffer buffer = ByteBuffer.allocateDirect(bitmap.getByteCount());
+                bitmap.copyPixelsToBuffer(buffer);
+                buffer.rewind();
+                return buffer;
+            } else if (imageFormat == MlImage.IMAGE_FORMAT_RGB) {
+                // TODO(b/180504869): Try Use RGBA buffer to create RGB buffer which might be
+                // faster.
+                int w = bitmap.getWidth();
+                int h = bitmap.getHeight();
+                int[] pixels = new int[w * h];
+                bitmap.getPixels(pixels, 0, w, 0, 0, w, h);
+                ByteBuffer buffer = ByteBuffer.allocateDirect(w * h * 3);
+                buffer.order(ByteOrder.nativeOrder());
+                for (int pixel : pixels) {
+                    // getPixels returns Color in ARGB rather than copyPixelsToBuffer which returns
+                    // RGBA
+                    buffer.put((byte) ((pixel >> 16) & 0xff));
+                    buffer.put((byte) ((pixel >> 8) & 0xff));
+                    buffer.put((byte) (pixel & 0xff));
+                }
+                buffer.rewind();
+                return buffer;
+            }
+        }
+        throw new IllegalArgumentException(String.format(
+                "Extracting ByteBuffer from an MlImage created by Bitmap and convert from %s to format"
+                        + " %d is not supported",
+                bitmap.getConfig(), imageFormat));
+    }
+
+    private static ByteBuffer convertByteBuffer(
+            ByteBuffer source, @ImageFormat int sourceFormat, @ImageFormat int targetFormat) {
+        if (sourceFormat == MlImage.IMAGE_FORMAT_RGB && targetFormat == MlImage.IMAGE_FORMAT_RGBA) {
+            ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 3 * 4);
+            // Extend the buffer when the target is longer than the source. Use two cursors and
+            // sweep the array reversely to convert in-place.
+            byte[] array = new byte[target.capacity()];
+            source.get(array, 0, source.capacity());
+            source.rewind();
+            int rgbCursor = source.capacity();
+            int rgbaCursor = target.capacity();
+            while (rgbCursor != rgbaCursor) {
+                array[--rgbaCursor] = (byte) 0xff; // A
+                array[--rgbaCursor] = array[--rgbCursor]; // B
+                array[--rgbaCursor] = array[--rgbCursor]; // G
+                array[--rgbaCursor] = array[--rgbCursor]; // R
+            }
+            target.put(array, 0, target.capacity());
+            target.rewind();
+            return target;
+        } else if (sourceFormat == MlImage.IMAGE_FORMAT_RGBA
+                && targetFormat == MlImage.IMAGE_FORMAT_RGB) {
+            ByteBuffer target = ByteBuffer.allocateDirect(source.capacity() / 4 * 3);
+            // Shrink the buffer when the target is shorter than the source. Use two cursors and
+            // sweep the array to convert in-place.
+            byte[] array = new byte[source.capacity()];
+            source.get(array, 0, source.capacity());
+            source.rewind();
+            int rgbaCursor = 0;
+            int rgbCursor = 0;
+            while (rgbaCursor < array.length) {
+                array[rgbCursor++] = array[rgbaCursor++]; // R
+                array[rgbCursor++] = array[rgbaCursor++]; // G
+                array[rgbCursor++] = array[rgbaCursor++]; // B
+                rgbaCursor++;
+            }
+            target.put(array, 0, target.capacity());
+            target.rewind();
+            return target;
+        } else {
+            throw new IllegalArgumentException(String.format(Locale.ENGLISH,
+                    "Convert bytebuffer image format from %d to %d is not supported", sourceFormat,
+                    targetFormat));
+        }
+    }
+
+    // ByteBuffer is not able to be instantiated.
+    private ByteBufferExtractor() {}
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java
new file mode 100644
index 0000000..f872db4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferImageContainer.java
@@ -0,0 +1,55 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import com.google.android.odml.image.MlImage.ImageFormat;
+
+import java.nio.ByteBuffer;
+
+class ByteBufferImageContainer implements ImageContainer {
+    private final ByteBuffer buffer;
+    private final ImageProperties properties;
+
+    public ByteBufferImageContainer(ByteBuffer buffer, @ImageFormat int imageFormat) {
+        this.buffer = buffer;
+        this.properties = ImageProperties.builder()
+                                  .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
+                                  .setImageFormat(imageFormat)
+                                  .build();
+    }
+
+    public ByteBuffer getByteBuffer() {
+        return buffer;
+    }
+
+    @Override
+    public ImageProperties getImageProperties() {
+        return properties;
+    }
+
+    /**
+     * Returns the image format.
+     */
+    @ImageFormat
+    public int getImageFormat() {
+        return properties.getImageFormat();
+    }
+
+    @Override
+    public void close() {
+        // No op for ByteBuffer.
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java
new file mode 100644
index 0000000..f4b0b31
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ByteBufferMlImageBuilder.java
@@ -0,0 +1,103 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Rect;
+
+import com.google.android.odml.image.MlImage.ImageFormat;
+
+import java.nio.ByteBuffer;
+
+/**
+ * Builds a {@link MlImage} from a {@link ByteBuffer}.
+ *
+ * <p>You can pass in either mutable or immutable {@link ByteBuffer}. However once {@link
+ * ByteBuffer} is passed in, to keep data integrity you shouldn't modify content in it.
+ *
+ * <p>Use {@link ByteBufferExtractor} to get {@link ByteBuffer} you passed in.
+ */
+public class ByteBufferMlImageBuilder {
+    // Mandatory fields.
+    private final ByteBuffer buffer;
+    private final int width;
+    private final int height;
+    @ImageFormat
+    private final int imageFormat;
+
+    // Optional fields.
+    private int rotation;
+    private Rect roi;
+    private long timestamp;
+
+    /**
+     * Creates the builder with mandatory {@link ByteBuffer} and the represented image.
+     *
+     * <p>We will validate the size of the {@code byteBuffer} with given {@code width}, {@code
+     * height} and {@code imageFormat}.
+     *
+     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
+     * values will be set with default:
+     *
+     * <ul>
+     *   <li>rotation: 0
+     * </ul>
+     *
+     * @param byteBuffer image data object.
+     * @param width the width of the represented image.
+     * @param height the height of the represented image.
+     * @param imageFormat how the data encode the image.
+     */
+    public ByteBufferMlImageBuilder(
+            ByteBuffer byteBuffer, int width, int height, @ImageFormat int imageFormat) {
+        this.buffer = byteBuffer;
+        this.width = width;
+        this.height = height;
+        this.imageFormat = imageFormat;
+        // TODO(b/180504869): Validate bytebuffer size with width, height and image format
+        this.rotation = 0;
+        this.roi = new Rect(0, 0, width, height);
+        this.timestamp = 0;
+    }
+
+    /**
+     * Sets value for {@link MlImage#getRotation()}.
+     *
+     * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
+     */
+    public ByteBufferMlImageBuilder setRotation(int rotation) {
+        MlImage.validateRotation(rotation);
+        this.rotation = rotation;
+        return this;
+    }
+
+    /** Sets value for {@link MlImage#getRoi()}. */
+    ByteBufferMlImageBuilder setRoi(Rect roi) {
+        this.roi = roi;
+        return this;
+    }
+
+    /** Sets value for {@link MlImage#getTimestamp()}. */
+    ByteBufferMlImageBuilder setTimestamp(long timestamp) {
+        this.timestamp = timestamp;
+        return this;
+    }
+
+    /** Builds an {@link MlImage} instance. */
+    public MlImage build() {
+        return new MlImage(new ByteBufferImageContainer(buffer, imageFormat), rotation, roi,
+                timestamp, width, height);
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java
new file mode 100644
index 0000000..bfa7c0a
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageContainer.java
@@ -0,0 +1,30 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import com.google.android.odml.image.annotation.KeepForSdk;
+
+/** Manages internal image data storage. The interface is package-private. */
+@KeepForSdk
+interface ImageContainer {
+    /** Returns the properties of the contained image. */
+    @KeepForSdk
+    ImageProperties getImageProperties();
+
+    /** Close the image container and releases the image resource inside. */
+    @KeepForSdk
+    void close();
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java
new file mode 100644
index 0000000..a61e97b8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/ImageProperties.java
@@ -0,0 +1,84 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import com.google.android.odml.image.MlImage.ImageFormat;
+import com.google.android.odml.image.MlImage.StorageType;
+import com.google.android.odml.image.annotation.KeepForSdk;
+import com.google.auto.value.AutoValue;
+import com.google.auto.value.extension.memoized.Memoized;
+
+/** Groups a set of properties to describe how an image is stored. */
+@AutoValue
+public abstract class ImageProperties {
+    /**
+     * Gets the pixel format of the image.
+     *
+     * @see MlImage.ImageFormat
+     */
+    @ImageFormat
+    public abstract int getImageFormat();
+
+    /**
+     * Gets the storage type of the image.
+     *
+     * @see MlImage.StorageType
+     */
+    @StorageType
+    public abstract int getStorageType();
+
+    @Memoized
+    @Override
+    public abstract int hashCode();
+
+    /**
+     * Creates a builder of {@link ImageProperties}.
+     *
+     * @see ImageProperties.Builder
+     */
+    @KeepForSdk
+    static Builder builder() {
+        return new AutoValue_ImageProperties.Builder();
+    }
+
+    /** Builds a {@link ImageProperties}. */
+    @AutoValue.Builder
+    @KeepForSdk
+    abstract static class Builder {
+        /**
+         * Sets the {@link MlImage.ImageFormat}.
+         *
+         * @see ImageProperties#getImageFormat
+         */
+        @KeepForSdk
+        abstract Builder setImageFormat(@ImageFormat int value);
+
+        /**
+         * Sets the {@link MlImage.StorageType}.
+         *
+         * @see ImageProperties#getStorageType
+         */
+        @KeepForSdk
+        abstract Builder setStorageType(@StorageType int value);
+
+        /** Builds the {@link ImageProperties}. */
+        @KeepForSdk
+        abstract ImageProperties build();
+    }
+
+    // Hide the constructor.
+    ImageProperties() {}
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java
new file mode 100644
index 0000000..9ed88ee3
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageContainer.java
@@ -0,0 +1,74 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.media.Image;
+import android.os.Build;
+import android.os.Build.VERSION;
+import android.os.Build.VERSION_CODES;
+
+import androidx.annotation.RequiresApi;
+
+import com.google.android.odml.image.MlImage.ImageFormat;
+
+@RequiresApi(VERSION_CODES.KITKAT)
+class MediaImageContainer implements ImageContainer {
+    private final Image mediaImage;
+    private final ImageProperties properties;
+
+    public MediaImageContainer(Image mediaImage) {
+        this.mediaImage = mediaImage;
+        this.properties = ImageProperties.builder()
+                                  .setStorageType(MlImage.STORAGE_TYPE_MEDIA_IMAGE)
+                                  .setImageFormat(convertFormatCode(mediaImage.getFormat()))
+                                  .build();
+    }
+
+    public Image getImage() {
+        return mediaImage;
+    }
+
+    @Override
+    public ImageProperties getImageProperties() {
+        return properties;
+    }
+
+    @Override
+    public void close() {
+        mediaImage.close();
+    }
+
+    @ImageFormat
+    static int convertFormatCode(int graphicsFormat) {
+        // We only cover the format mentioned in
+        // https://developer.android.com/reference/android/media/Image#getFormat()
+        if (VERSION.SDK_INT >= Build.VERSION_CODES.M) {
+            if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGBA_8888) {
+                return MlImage.IMAGE_FORMAT_RGBA;
+            } else if (graphicsFormat == android.graphics.ImageFormat.FLEX_RGB_888) {
+                return MlImage.IMAGE_FORMAT_RGB;
+            }
+        }
+        switch (graphicsFormat) {
+            case android.graphics.ImageFormat.JPEG:
+                return MlImage.IMAGE_FORMAT_JPEG;
+            case android.graphics.ImageFormat.YUV_420_888:
+                return MlImage.IMAGE_FORMAT_YUV_420_888;
+            default:
+                return MlImage.IMAGE_FORMAT_UNKNOWN;
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java
new file mode 100644
index 0000000..59ed98b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaImageExtractor.java
@@ -0,0 +1,52 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.media.Image;
+import android.os.Build.VERSION_CODES;
+
+import androidx.annotation.RequiresApi;
+
+/**
+ * Utility for extracting {@link android.media.Image} from {@link MlImage}.
+ *
+ * <p>Currently it only supports {@link MlImage} with {@link MlImage#STORAGE_TYPE_MEDIA_IMAGE},
+ * otherwise {@link IllegalArgumentException} will be thrown.
+ */
+@RequiresApi(VERSION_CODES.KITKAT)
+public class MediaImageExtractor {
+    private MediaImageExtractor() {}
+
+    /**
+     * Extracts a {@link android.media.Image} from an {@link MlImage}. Currently it only works for
+     * {@link MlImage} that built from {@link MediaMlImageBuilder}.
+     *
+     * <p>Notice: Properties of the {@code image} like rotation will not take effects.
+     *
+     * @param image the image to extract {@link android.media.Image} from.
+     * @return {@link android.media.Image} that stored in {@link MlImage}.
+     * @throws IllegalArgumentException if the extraction failed.
+     */
+    public static Image extract(MlImage image) {
+        ImageContainer container;
+        if ((container = image.getContainer(MlImage.STORAGE_TYPE_MEDIA_IMAGE)) != null) {
+            return ((MediaImageContainer) container).getImage();
+        }
+        throw new IllegalArgumentException(
+                "Extract Media Image from an MlImage created by objects other than Media Image"
+                + " is not supported");
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java
new file mode 100644
index 0000000..80771bd
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MediaMlImageBuilder.java
@@ -0,0 +1,89 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Rect;
+import android.media.Image;
+import android.os.Build.VERSION_CODES;
+
+import androidx.annotation.RequiresApi;
+
+/**
+ * Builds {@link MlImage} from {@link android.media.Image}.
+ *
+ * <p>Once {@link android.media.Image} is passed in, to keep data integrity you shouldn't modify
+ * content in it.
+ *
+ * <p>Use {@link MediaImageExtractor} to get {@link android.media.Image} you passed in.
+ */
+@RequiresApi(VERSION_CODES.KITKAT)
+public class MediaMlImageBuilder {
+    // Mandatory fields.
+    private final Image mediaImage;
+
+    // Optional fields.
+    private int rotation;
+    private Rect roi;
+    private long timestamp;
+
+    /**
+     * Creates the builder with a mandatory {@link android.media.Image}.
+     *
+     * <p>Also calls {@link #setRotation(int)} to set the optional properties. If not set, the
+     * values will be set with default:
+     *
+     * <ul>
+     *   <li>rotation: 0
+     * </ul>
+     *
+     * @param mediaImage image data object.
+     */
+    public MediaMlImageBuilder(Image mediaImage) {
+        this.mediaImage = mediaImage;
+        this.rotation = 0;
+        this.roi = new Rect(0, 0, mediaImage.getWidth(), mediaImage.getHeight());
+        this.timestamp = 0;
+    }
+
+    /**
+     * Sets value for {@link MlImage#getRotation()}.
+     *
+     * @throws IllegalArgumentException if the rotation value is not 0, 90, 180 or 270.
+     */
+    public MediaMlImageBuilder setRotation(int rotation) {
+        MlImage.validateRotation(rotation);
+        this.rotation = rotation;
+        return this;
+    }
+
+    /** Sets value for {@link MlImage#getRoi()}. */
+    MediaMlImageBuilder setRoi(Rect roi) {
+        this.roi = roi;
+        return this;
+    }
+
+    /** Sets value for {@link MlImage#getTimestamp()}. */
+    MediaMlImageBuilder setTimestamp(long timestamp) {
+        this.timestamp = timestamp;
+        return this;
+    }
+
+    /** Builds an {@link MlImage} instance. */
+    public MlImage build() {
+        return new MlImage(new MediaImageContainer(mediaImage), rotation, roi, timestamp,
+                mediaImage.getWidth(), mediaImage.getHeight());
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java
new file mode 100644
index 0000000..7e21e6ad
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/MlImage.java
@@ -0,0 +1,296 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Rect;
+
+import androidx.annotation.IntDef;
+import androidx.annotation.Nullable;
+
+import com.google.android.odml.image.annotation.KeepForSdk;
+
+import java.io.Closeable;
+import java.lang.annotation.Retention;
+import java.lang.annotation.RetentionPolicy;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Map.Entry;
+
+/**
+ * Wraps image data for on-device machine learning (ODML) usages.
+ *
+ * <p>{@link MlImage} is designed to be an immutable image container, which could be shared
+ * cross-platforms, among different Google ODML frameworks(TFLite Support, MLKit).
+ *
+ * <p>It is a common abstraction image that could help to chain different frameworks that adapts
+ * {@link MlImage} together.
+ *
+ * <p>To construct an {@link MlImage}, use the provided builders:
+ *
+ * <ul>
+ *   <li>{@link ByteBufferMlImageBuilder}
+ *   <li>{@link BitmapMlImageBuilder}
+ *   <li>{@link MediaMlImageBuilder}
+ * </ul>
+ *
+ * <p>{@link MlImage} uses reference counting to maintain internal storage. When it is created the
+ * reference count is 1. Developer can call {@link #close()} to reduce reference count to release
+ * internal storage earlier, otherwise Java garbage collection will release the storage eventually.
+ *
+ * <p>To extract concrete image, first check {@link StorageType} and then use the provided
+ * extractors:
+ *
+ * <ul>
+ *   <li>{@link ByteBufferExtractor}
+ *   <li>{@link BitmapExtractor}
+ *   <li>{@link MediaImageExtractor}
+ * </ul>
+ *
+ * In future release, {@link MlImage} will support internal conversion(e.g. Bitmap -> ByteBuffer)
+ * and multiple storages.
+ */
+public class MlImage implements Closeable {
+    /** Specifies the image format of an image. */
+    @IntDef({
+            IMAGE_FORMAT_UNKNOWN,
+            IMAGE_FORMAT_RGBA,
+            IMAGE_FORMAT_RGB,
+            IMAGE_FORMAT_NV12,
+            IMAGE_FORMAT_NV21,
+            IMAGE_FORMAT_YV12,
+            IMAGE_FORMAT_YV21,
+            IMAGE_FORMAT_YUV_420_888,
+            IMAGE_FORMAT_ALPHA,
+            IMAGE_FORMAT_JPEG,
+    })
+    @Retention(RetentionPolicy.SOURCE)
+    public @interface ImageFormat {}
+
+    public static final int IMAGE_FORMAT_UNKNOWN = 0;
+    public static final int IMAGE_FORMAT_RGBA = 1;
+    public static final int IMAGE_FORMAT_RGB = 2;
+    public static final int IMAGE_FORMAT_NV12 = 3;
+    public static final int IMAGE_FORMAT_NV21 = 4;
+    public static final int IMAGE_FORMAT_YV12 = 5;
+    public static final int IMAGE_FORMAT_YV21 = 6;
+    public static final int IMAGE_FORMAT_YUV_420_888 = 7;
+    public static final int IMAGE_FORMAT_ALPHA = 8;
+    public static final int IMAGE_FORMAT_JPEG = 9;
+
+    /** Specifies the image container type. Would be useful for choosing extractors. */
+    @IntDef({
+            STORAGE_TYPE_BITMAP,
+            STORAGE_TYPE_BYTEBUFFER,
+            STORAGE_TYPE_MEDIA_IMAGE,
+            STORAGE_TYPE_IMAGE_PROXY,
+    })
+    @Retention(RetentionPolicy.SOURCE)
+    public @interface StorageType {}
+
+    public static final int STORAGE_TYPE_BITMAP = 1;
+    public static final int STORAGE_TYPE_BYTEBUFFER = 2;
+    public static final int STORAGE_TYPE_MEDIA_IMAGE = 3;
+    public static final int STORAGE_TYPE_IMAGE_PROXY = 4;
+
+    /**
+     * Returns a list of supported image properties for this {@link MlImage}.
+     *
+     * <p>Currently {@link MlImage} only support single storage type so the size of return list will
+     * always be 1.
+     *
+     * @see ImageProperties
+     */
+    public List<ImageProperties> getContainedImageProperties() {
+        return Collections.singletonList(getContainer().getImageProperties());
+    }
+
+    /** Returns the rotation value attached to the image. Rotation value will be 0, 90, 180, 270. */
+    public int getRotation() {
+        return rotation;
+    }
+
+    /** Returns the timestamp attached to the image. */
+    long getTimestamp() {
+        return timestamp;
+    }
+
+    /** Returns the width of the image. */
+    public int getWidth() {
+        return width;
+    }
+
+    /** Returns the height of the image. */
+    public int getHeight() {
+        return height;
+    }
+
+    /** Returns the region-of-interest rectangle attached to the image. */
+    Rect getRoi() {
+        Rect result = new Rect();
+        result.set(roi);
+        return result;
+    }
+
+    /**
+     * Acquires a reference on this {@link MlImage}. This will increase the reference count by 1.
+     */
+    private synchronized void acquire() {
+        referenceCount += 1;
+    }
+
+    /**
+     * Removes a reference that was previously acquired or init.
+     *
+     * <p>When {@link MlImage} is created, it has 1 reference count.
+     *
+     * <p>When the reference count becomes 0, it will release the resource under the hood.
+     */
+    @Override
+    // TODO(b/189767728): Create an internal flag to indicate image is closed, or use referenceCount
+    public synchronized void close() {
+        referenceCount -= 1;
+        if (referenceCount == 0) {
+            for (ImageContainer imageContainer : containerMap.values()) {
+                imageContainer.close();
+            }
+        }
+    }
+
+    /**
+     * Advanced API access for {@link MlImage}.
+     *
+     * <p>These APIs are useful for other infrastructures, for example, acquiring extra reference
+     * count for {@link MlImage}. However, an App developer should avoid using the following APIs.
+     *
+     * <p>APIs inside are treated as internal APIs which are subject to change.
+     */
+    public static final class Internal {
+        /**
+         * Acquires a reference on this {@link MlImage}. This will increase the reference count
+         * by 1.
+         *
+         * <p>This method is more useful for image consumer to acquire a reference so image resource
+         * will not be closed accidentally. As image creator, normal developer doesn't need to call
+         * this method.
+         *
+         * <p>The reference count is 1 when {@link MlImage} is created. Developer can call {@link
+         * #close()} to indicate it doesn't need this {@link MlImage} anymore.
+         *
+         * @see #close()
+         */
+        public void acquire() {
+            image.acquire();
+        }
+
+        private final MlImage image;
+
+        // Only MlImage creates the internal helper.
+        private Internal(MlImage image) {
+            this.image = image;
+        }
+    }
+
+    /** Gets {@link Internal} object which contains internal APIs. */
+    public Internal getInternal() {
+        return new Internal(this);
+    }
+
+    private final Map<ImageProperties, ImageContainer> containerMap;
+    private final int rotation;
+    private final Rect roi;
+    private final long timestamp;
+    private final int width;
+    private final int height;
+
+    private int referenceCount;
+
+    /** Constructs an {@link MlImage} with a built container. */
+    @KeepForSdk
+    MlImage(ImageContainer container, int rotation, Rect roi, long timestamp, int width,
+            int height) {
+        this.containerMap = new HashMap<>();
+        containerMap.put(container.getImageProperties(), container);
+        this.rotation = rotation;
+        this.roi = new Rect();
+        this.roi.set(roi);
+        this.timestamp = timestamp;
+        this.width = width;
+        this.height = height;
+        this.referenceCount = 1;
+    }
+
+    /**
+     * Gets one available container.
+     *
+     * @return the current container.
+     */
+    @KeepForSdk
+    ImageContainer getContainer() {
+        // According to the design, in the future we will support multiple containers in one image.
+        // Currently just return the original container.
+        // TODO(b/182443927): Cache multiple containers in MlImage.
+        return containerMap.values().iterator().next();
+    }
+
+    /**
+     * Gets container from required {@code storageType}. Returns {@code null} if not existed.
+     *
+     * <p>If there are multiple containers with required {@code storageType}, returns the first one.
+     */
+    @Nullable
+    @KeepForSdk
+    ImageContainer getContainer(@StorageType int storageType) {
+        for (Entry<ImageProperties, ImageContainer> entry : containerMap.entrySet()) {
+            if (entry.getKey().getStorageType() == storageType) {
+                return entry.getValue();
+            }
+        }
+        return null;
+    }
+
+    /**
+     * Gets container from required {@code imageProperties}. Returns {@code null} if non existed.
+     */
+    @Nullable
+    @KeepForSdk
+    ImageContainer getContainer(ImageProperties imageProperties) {
+        return containerMap.get(imageProperties);
+    }
+
+    /** Adds a new container if it doesn't exist. Returns {@code true} if it succeeds. */
+    boolean addContainer(ImageContainer container) {
+        ImageProperties imageProperties = container.getImageProperties();
+        if (containerMap.containsKey(imageProperties)) {
+            return false;
+        }
+        containerMap.put(imageProperties, container);
+        return true;
+    }
+
+    /**
+     * Validates rotation values for builders. Only supports 0, 90, 180, 270.
+     *
+     * @throws IllegalArgumentException if the rotation value is invalid.
+     */
+    static void validateRotation(int rotation) {
+        if (rotation != 0 && rotation != 90 && rotation != 180 && rotation != 270) {
+            throw new IllegalArgumentException(
+                    "Rotation value " + rotation + " is not valid. Use only 0, 90, 180 or 270.");
+        }
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/annotation/KeepForSdk.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/annotation/KeepForSdk.java
new file mode 100644
index 0000000..8442e1d6
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/src/com/google/android/odml/image/annotation/KeepForSdk.java
@@ -0,0 +1,27 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+package com.google.android.odml.image.annotation;
+
+import java.lang.annotation.Documented;
+import java.lang.annotation.ElementType;
+import java.lang.annotation.Target;
+
+/**
+ * Indicates that this object (class, method, etc) should be retained and not renamed when
+ * generating the SDK, but should be allowed to be stripped or renamed in end developer apps.
+ */
+@Target({ElementType.TYPE, ElementType.FIELD, ElementType.METHOD, ElementType.CONSTRUCTOR})
+@Documented // Technically not needed as this doesn't impact end apps, but kept for consistency.
+public @interface KeepForSdk {}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/AndroidManifest.xml b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/AndroidManifest.xml
new file mode 100644
index 0000000..d04979a7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/AndroidManifest.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="utf-8"?>
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+    package="com.google.android.odml.image">
+
+  <uses-sdk
+      android:minSdkVersion="16"
+      android:targetSdkVersion="29" />
+</manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BUILD
new file mode 100644
index 0000000..87642d10
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BUILD
@@ -0,0 +1,111 @@
+load("@build_bazel_rules_android//android:rules.bzl", "android_library", "android_local_test")
+
+licenses(["notice"])
+
+INSTRUMENTED_TESTS = glob(["*InstrumentedTest.java"])
+
+android_library(
+    name = "odml-image-test",
+    srcs = [
+        "TestImageCreator.java",
+    ],
+    custom_package = "com.google.android.odml.image",
+    # TODO(b/163039980): Use JAVACOPTS in TF. "-Xep:RemoveUnusedImports:ERROR" wierdly break the build.
+    javacopts = ["-source 7 -target 7"],
+    manifest = "AndroidManifest.xml",
+    deps = [
+        "@maven//:androidx_annotation_annotation",
+    ],
+)
+
+android_local_test(
+    name = "BitmapMlImageBuilderTest",
+    srcs = ["BitmapMlImageBuilderTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "com.google.android.odml.image.BitmapMlImageBuilderTest",
+    deps = [
+        "//tensorflow_lite_support/odml/java/image",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "BitmapExtractorTest",
+    srcs = ["BitmapExtractorTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "com.google.android.odml.image.BitmapExtractorTest",
+    deps = [
+        ":odml-image-test",
+        "//tensorflow_lite_support/odml/java/image",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "ByteBufferMlImageBuilderTest",
+    srcs = ["ByteBufferMlImageBuilderTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "com.google.android.odml.image.ByteBufferMlImageBuilderTest",
+    deps = [
+        "//tensorflow_lite_support/odml/java/image",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "ByteBufferExtractorTest",
+    srcs = ["ByteBufferExtractorTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "com.google.android.odml.image.ByteBufferExtractorTest",
+    deps = [
+        ":odml-image-test",
+        "//tensorflow_lite_support/odml/java/image",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "MediaMlImageTest",
+    srcs = [
+        "MediaImageExtractorTest.java",
+        "MediaMlImageBuilderTest.java",
+    ],
+    manifest = "AndroidManifest.xml",
+    test_class = "com.google.android.odml.image.MediaMlImageBuilderTest",
+    deps = [
+        "//tensorflow_lite_support/odml/java/image",
+        "//third_party/java/mockito:mockito-android",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
+
+android_local_test(
+    name = "TextureImageExtractorTest",
+    srcs = ["TextureImageExtractorTest.java"],
+    manifest = "AndroidManifest.xml",
+    test_class = "com.google.android.odml.image.TextureImageExtractorTest",
+    deps = [
+        ":odml-image-test",
+        "//tensorflow_lite_support/odml/java/image",
+        "//third_party/java/mockito:mockito-android",
+        "@maven//:androidx_test_core",
+        "@maven//:com_google_truth_truth",  # android
+        "@maven//:org_robolectric_robolectric",
+        "@robolectric//bazel:android-all",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java
new file mode 100644
index 0000000..8408a0e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapExtractorTest.java
@@ -0,0 +1,52 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import android.graphics.Bitmap;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+import java.nio.ByteBuffer;
+
+/** Unit test for {@link BitmapExtractor}. */
+@RunWith(RobolectricTestRunner.class)
+public class BitmapExtractorTest {
+    @Test
+    public void extract_fromBitmap_succeeds() {
+        Bitmap bitmap = TestImageCreator.createRgbaBitmap();
+        MlImage image = new BitmapMlImageBuilder(bitmap).build();
+
+        Bitmap result = BitmapExtractor.extract(image);
+
+        assertThat(result).isSameInstanceAs(bitmap);
+    }
+
+    @Test
+    public void extract_fromByteBuffer_throwsException() {
+        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
+                                .build();
+
+        assertThrows(IllegalArgumentException.class, () -> BitmapExtractor.extract(image));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java
new file mode 100644
index 0000000..9a4051c
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/BitmapMlImageBuilderTest.java
@@ -0,0 +1,88 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import android.graphics.Bitmap;
+import android.graphics.Bitmap.Config;
+import android.graphics.Rect;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+/** Tests for {@link BitmapMlImageBuilder} */
+@RunWith(RobolectricTestRunner.class)
+public final class BitmapMlImageBuilderTest {
+    @Test
+    public void build_fromBitmap_succeeds() {
+        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+
+        MlImage image = new BitmapMlImageBuilder(bitmap).build();
+        ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_BITMAP);
+
+        assertThat(image.getWidth()).isEqualTo(20);
+        assertThat(image.getHeight()).isEqualTo(25);
+        assertThat(image.getContainedImageProperties())
+                .containsExactly(ImageProperties.builder()
+                                         .setImageFormat(MlImage.IMAGE_FORMAT_RGBA)
+                                         .setStorageType(MlImage.STORAGE_TYPE_BITMAP)
+                                         .build());
+        assertThat(((BitmapImageContainer) container).getBitmap().getConfig())
+                .isEqualTo(Config.ARGB_8888);
+    }
+
+    @Test
+    public void build_withOptionalProperties_succeeds() {
+        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+
+        MlImage image = new BitmapMlImageBuilder(bitmap)
+                                .setRoi(new Rect(0, 5, 10, 15))
+                                .setRotation(90)
+                                .setTimestamp(12345)
+                                .build();
+
+        assertThat(image.getTimestamp()).isEqualTo(12345);
+        assertThat(image.getRotation()).isEqualTo(90);
+        assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
+    }
+
+    @Test
+    public void build_withInvalidRotation_throwsException() {
+        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+        BitmapMlImageBuilder builder = new BitmapMlImageBuilder(bitmap);
+
+        assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
+    }
+
+    @Test
+    public void release_recyclesBitmap() {
+        Bitmap bitmap = Bitmap.createBitmap(20, 25, Config.ARGB_8888);
+
+        MlImage image = new BitmapMlImageBuilder(bitmap)
+                                .setRoi(new Rect(0, 5, 10, 15))
+                                .setRotation(90)
+                                .setTimestamp(12345)
+                                .build();
+        assertThat(bitmap.isRecycled()).isFalse();
+        image.close();
+
+        assertThat(bitmap.isRecycled()).isTrue();
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java
new file mode 100644
index 0000000..e675ba9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferExtractorTest.java
@@ -0,0 +1,157 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import android.graphics.Bitmap;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+import java.nio.Buffer;
+import java.nio.ByteBuffer;
+
+/**
+ * Tests for {@link ByteBufferExtractor}.
+ *
+ * <p>{@code RGBA}{@link Bitmap} to {@code RGBA}{@link ByteBuffer} convesion is not tested here,
+ * like {@link ByteBufferExtractorInstrumentedTest#extract_rgbaFromRgbaBitmap_succeeds()}, because
+ * Robolectric seems not handling {@link Bitmap#copyPixelsToBuffer(Buffer)} correctly. So that we
+ * only test that path in the instrumented unit test.
+ */
+@RunWith(RobolectricTestRunner.class)
+public final class ByteBufferExtractorTest {
+    @Test
+    public void extract_fromByteBuffer_succeeds() {
+        ByteBuffer byteBuffer = TestImageCreator.createRgbBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(byteBuffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
+                                .build();
+
+        ByteBuffer result = ByteBufferExtractor.extract(image);
+
+        assertThat(result).isEquivalentAccordingToCompareTo(byteBuffer);
+        assertThat(result.isReadOnly()).isTrue();
+    }
+
+    @Test
+    public void extract_fromBitmap_throws() {
+        Bitmap rgbaBitmap = TestImageCreator.createRgbaBitmap();
+        MlImage image = new BitmapMlImageBuilder(rgbaBitmap).build();
+
+        assertThrows(IllegalArgumentException.class, () -> ByteBufferExtractor.extract(image));
+    }
+
+    @Test
+    public void extract_rgbFromRgbByteBuffer_succeeds() {
+        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
+                                .build();
+
+        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+
+        assertThat(result.isReadOnly()).isTrue();
+        assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
+    }
+
+    @Test
+    public void extract_rgbFromRgbaByteBuffer_succeeds() {
+        ByteBuffer buffer = TestImageCreator.createRgbaBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGBA)
+                                .build();
+
+        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+
+        assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
+        assertThat(buffer.position()).isEqualTo(0);
+    }
+
+    @Test
+    public void extract_rgbaFromRgbByteBuffer_succeeds() {
+        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
+                                .build();
+
+        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGBA);
+
+        assertThat(result).isEquivalentAccordingToCompareTo(
+                TestImageCreator.createOpaqueRgbaBuffer());
+        assertThat(buffer.position()).isEqualTo(0);
+    }
+
+    @Test
+    public void extract_rgbFromRgbaBitmap_succeeds() {
+        Bitmap rgbaBitmap = TestImageCreator.createRgbaBitmap();
+        MlImage image = new BitmapMlImageBuilder(rgbaBitmap).build();
+
+        ByteBuffer result = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+
+        assertThat(result.isReadOnly()).isTrue();
+        assertThat(result).isEquivalentAccordingToCompareTo(TestImageCreator.createRgbBuffer());
+
+        // Verifies ByteBuffer is cached inside MlImage.
+        ByteBufferImageContainer byteBufferImageContainer =
+                (ByteBufferImageContainer) image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
+        assertThat(byteBufferImageContainer.getByteBuffer()).isEqualTo(result);
+        assertThat(byteBufferImageContainer.getImageFormat()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+
+        // Verifies that extracted ByteBuffer is the cached one.
+        ByteBuffer result2 = ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_RGB);
+        assertThat(result2).isEqualTo(result);
+    }
+
+    @Test
+    public void extract_unsupportedFormatFromByteBuffer_throws() {
+        ByteBuffer buffer = TestImageCreator.createRgbaBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGBA)
+                                .build();
+
+        assertThrows(IllegalArgumentException.class,
+                () -> ByteBufferExtractor.extract(image, MlImage.IMAGE_FORMAT_YUV_420_888));
+    }
+
+    @Test
+    public void extractInRecommendedFormat_anyFormatFromRgbByteBuffer_succeeds() {
+        ByteBuffer buffer = TestImageCreator.createRgbBuffer();
+        MlImage image = new ByteBufferMlImageBuilder(buffer, TestImageCreator.getWidth(),
+                TestImageCreator.getHeight(), MlImage.IMAGE_FORMAT_RGB)
+                                .build();
+
+        ByteBufferExtractor.Result result = ByteBufferExtractor.extractInRecommendedFormat(image);
+
+        assertThat(result.buffer().isReadOnly()).isTrue();
+        assertThat(result.format()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+
+        // Verifies ByteBuffer is cached inside MlImage.
+        ByteBufferImageContainer byteBufferImageContainer =
+                (ByteBufferImageContainer) image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
+        assertThat(byteBufferImageContainer.getByteBuffer()).isEqualTo(result.buffer());
+        assertThat(byteBufferImageContainer.getImageFormat()).isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+
+        // Verifies that extracted ByteBuffer is the cached one.
+        ByteBufferExtractor.Result result2 = ByteBufferExtractor.extractInRecommendedFormat(image);
+        assertThat(result2.buffer()).isEqualTo(result.buffer());
+        assertThat(result2.format()).isEqualTo(result.format());
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java
new file mode 100644
index 0000000..374c82b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/ByteBufferMlImageBuilderTest.java
@@ -0,0 +1,77 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+
+import android.graphics.Rect;
+
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.robolectric.RobolectricTestRunner;
+
+import java.nio.ByteBuffer;
+
+/** Tests for {@link ByteBufferMlImageBuilder} */
+@RunWith(RobolectricTestRunner.class)
+public final class ByteBufferMlImageBuilderTest {
+    @Test
+    public void build_fromByteBuffer_succeeds() {
+        ByteBuffer buffer = ByteBuffer.allocate(500);
+
+        MlImage image =
+                new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB).build();
+        ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_BYTEBUFFER);
+
+        assertThat(image.getWidth()).isEqualTo(20);
+        assertThat(image.getHeight()).isEqualTo(25);
+        assertThat(image.getRoi()).isEqualTo(new Rect(0, 0, 20, 25));
+        assertThat(image.getRotation()).isEqualTo(0);
+        assertThat(image.getContainedImageProperties())
+                .containsExactly(ImageProperties.builder()
+                                         .setStorageType(MlImage.STORAGE_TYPE_BYTEBUFFER)
+                                         .setImageFormat(MlImage.IMAGE_FORMAT_RGB)
+                                         .build());
+        assertThat(((ByteBufferImageContainer) container).getImageFormat())
+                .isEqualTo(MlImage.IMAGE_FORMAT_RGB);
+    }
+
+    @Test
+    public void build_withOptionalProperties_succeeds() {
+        ByteBuffer buffer = ByteBuffer.allocate(500);
+
+        MlImage image = new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB)
+                                .setRoi(new Rect(0, 5, 10, 15))
+                                .setRotation(90)
+                                .setTimestamp(12345)
+                                .build();
+
+        assertThat(image.getTimestamp()).isEqualTo(12345);
+        assertThat(image.getRotation()).isEqualTo(90);
+        assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
+    }
+
+    @Test
+    public void build_withInvalidRotation_throwsException() {
+        ByteBuffer buffer = ByteBuffer.allocate(500);
+        ByteBufferMlImageBuilder builder =
+                new ByteBufferMlImageBuilder(buffer, 20, 25, MlImage.IMAGE_FORMAT_RGB);
+
+        assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java
new file mode 100644
index 0000000..fa832671
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaImageExtractorTest.java
@@ -0,0 +1,68 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.mockito.Mockito.when;
+
+import android.graphics.Bitmap;
+import android.graphics.Bitmap.Config;
+import android.graphics.ImageFormat;
+import android.media.Image;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.mockito.Mock;
+import org.mockito.MockitoAnnotations;
+import org.robolectric.RobolectricTestRunner;
+
+/** Tests for {@link MediaImageExtractor} */
+@RunWith(RobolectricTestRunner.class)
+public final class MediaImageExtractorTest {
+    private static final int HEIGHT = 100;
+    private static final int WIDTH = 50;
+
+    @Mock
+    private Image mediaImage;
+
+    @Before
+    public void setUp() {
+        MockitoAnnotations.initMocks(this);
+
+        when(mediaImage.getHeight()).thenReturn(HEIGHT);
+        when(mediaImage.getWidth()).thenReturn(WIDTH);
+        when(mediaImage.getFormat()).thenReturn(ImageFormat.YUV_420_888);
+    }
+
+    @Test
+    public void extract_fromMediaMlImage_succeeds() {
+        MlImage image = new MediaMlImageBuilder(mediaImage).build();
+        Image extractedMediaImage = MediaImageExtractor.extract(image);
+
+        assertThat(extractedMediaImage).isSameInstanceAs(image);
+    }
+
+    @Test
+    public void extract_fromBitmapMlImage_throwsException() {
+        MlImage image = new BitmapMlImageBuilder(
+                Bitmap.createBitmap(/* width= */ 20, /* height= */ 25, Config.ARGB_8888))
+                                .build();
+        assertThrows(IllegalArgumentException.class, () -> MediaImageExtractor.extract(image));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java
new file mode 100644
index 0000000..60397fec
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/MediaMlImageBuilderTest.java
@@ -0,0 +1,90 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import static com.google.common.truth.Truth.assertThat;
+
+import static org.junit.Assert.assertThrows;
+import static org.mockito.Mockito.when;
+
+import android.graphics.ImageFormat;
+import android.graphics.Rect;
+import android.media.Image;
+
+import org.junit.Before;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.mockito.Mock;
+import org.mockito.MockitoAnnotations;
+import org.robolectric.RobolectricTestRunner;
+
+/** Tests for {@link MediaMlImageBuilder} */
+@RunWith(RobolectricTestRunner.class)
+public final class MediaMlImageBuilderTest {
+    private static final int HEIGHT = 100;
+    private static final int WIDTH = 50;
+
+    @Mock
+    private Image mediaImage;
+
+    @Before
+    public void setUp() {
+        MockitoAnnotations.initMocks(this);
+
+        when(mediaImage.getHeight()).thenReturn(HEIGHT);
+        when(mediaImage.getWidth()).thenReturn(WIDTH);
+        when(mediaImage.getFormat()).thenReturn(ImageFormat.YUV_420_888);
+    }
+
+    @Test
+    public void build_fromMediaImage_succeeds() {
+        MlImage image = new MediaMlImageBuilder(mediaImage).build();
+        ImageContainer container = image.getContainer(MlImage.STORAGE_TYPE_MEDIA_IMAGE);
+
+        assertThat(image.getWidth()).isEqualTo(WIDTH);
+        assertThat(image.getHeight()).isEqualTo(HEIGHT);
+        assertThat(image.getRoi()).isEqualTo(new Rect(0, 0, WIDTH, HEIGHT));
+        assertThat(image.getRotation()).isEqualTo(0);
+        assertThat(image.getTimestamp()).isAtLeast(0);
+        assertThat(image.getContainedImageProperties())
+                .containsExactly(ImageProperties.builder()
+                                         .setStorageType(MlImage.STORAGE_TYPE_MEDIA_IMAGE)
+                                         .setImageFormat(MlImage.IMAGE_FORMAT_YUV_420_888)
+                                         .build());
+        assertThat(((MediaImageContainer) container).getImage().getFormat())
+                .isEqualTo(ImageFormat.YUV_420_888);
+    }
+
+    @Test
+    public void build_withOptionalProperties_succeeds() {
+        MlImage image = new MediaMlImageBuilder(mediaImage)
+                                .setTimestamp(12345)
+                                .setRoi(new Rect(0, 5, 10, 15))
+                                .setRotation(90)
+                                .build();
+
+        assertThat(image.getTimestamp()).isEqualTo(12345);
+        assertThat(image.getRotation()).isEqualTo(90);
+        assertThat(image.getRoi()).isEqualTo(new Rect(0, 5, 10, 15));
+    }
+
+    @Test
+    public void build_withInvalidRotation_throwsException() {
+        MediaMlImageBuilder builder = new MediaMlImageBuilder(mediaImage);
+
+        assertThrows(IllegalArgumentException.class, () -> builder.setRotation(360));
+    }
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java
new file mode 100644
index 0000000..28f54be
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/tests/src/com/google/android/odml/image/TestImageCreator.java
@@ -0,0 +1,148 @@
+/* Copyright 2021 Google LLC. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+package com.google.android.odml.image;
+
+import android.graphics.Bitmap;
+import android.graphics.Color;
+
+import java.nio.ByteBuffer;
+
+/**
+ * Creates test images.
+ *
+ * <p>Typically, {@link TestImageCreator} creates a 10x2 image, which looks like:
+ *
+ * <p>{@code BBBBBWWWWW}
+ *
+ * <p>{@code GGGGGRRRRR}
+ *
+ * <p>where B=0x000093, W=0xffffff, G=0x009300, R=0x930000.
+ *
+ * <p>The value of ALPHA channel is 0x70 or 0xff, depending on the settings.
+ *
+ * <p>The created {@link Bitmap} is not pre-multiplied.
+ */
+final class TestImageCreator {
+    private static final int RED = 0x73;
+    private static final int GREEN = 0x85;
+    private static final int BLUE = 0x96;
+    private static final int ALPHA = 0x70;
+
+    static int getWidth() {
+        return 10;
+    }
+
+    static int getHeight() {
+        return 2;
+    }
+
+    /**
+     * Creates an example non-pre-multiplied bitmap which is 100% opaque.
+     *
+     * @see TestImageCreator for details.
+     */
+    static Bitmap createOpaqueRgbaBitmap() {
+        return createRgbaBitmap(0xff);
+    }
+
+    /**
+     * Creates an example non-pre-multiplied bitmap which has non-trivial alpha channel.
+     *
+     * @see TestImageCreator for details.
+     */
+    static Bitmap createRgbaBitmap() {
+        return createRgbaBitmap(ALPHA);
+    }
+
+    /**
+     * Creates an example 10x2 bitmap demonstrated in the class doc. A channel sets to {@code
+     * alpha}.
+     */
+    static Bitmap createRgbaBitmap(int alpha) {
+        int[] colors = new int[20];
+        for (int i = 0; i < 5; i++) {
+            colors[i] = Color.argb(alpha, 0, 0, BLUE);
+            colors[i + 5] = Color.argb(alpha, 0xff, 0xff, 0xff);
+            colors[i + 10] = Color.argb(alpha, 0, GREEN, 0);
+            colors[i + 15] = Color.argb(alpha, RED, 0, 0);
+        }
+        // We don't use Bitmap#createBitmap(int[] ...) here, because that method creates
+        // pre-multiplied bitmaps.
+        Bitmap bitmap = Bitmap.createBitmap(10, 2, Bitmap.Config.ARGB_8888);
+        bitmap.setPremultiplied(false);
+        bitmap.setPixels(colors, 0, 10, 0, 0, 10, 2);
+        return bitmap;
+    }
+
+    /**
+     * Creates an example 10*10*3 bytebuffer in R-G-B format.
+     *
+     * @see TestImageCreator for details.
+     */
+    static ByteBuffer createRgbBuffer() {
+        return createRgbOrRgbaBuffer(false, 0xff);
+    }
+
+    /**
+     * Creates an example 10*10*4 bytebuffer in R-G-B-A format.
+     *
+     * @see TestImageCreator for details.
+     */
+    static ByteBuffer createRgbaBuffer() {
+        return createRgbOrRgbaBuffer(true, ALPHA);
+    }
+
+    /**
+     * Creates an example 10*10*4 bytebuffer in R-G-B-A format, but the A channel is 0xFF.
+     *
+     * @see TestImageCreator for details.
+     */
+    static ByteBuffer createOpaqueRgbaBuffer() {
+        return createRgbOrRgbaBuffer(true, 0xff);
+    }
+
+    /**
+     * Creates an example 10x2x4 (or 10x2x3 if no alpha) bytebuffer demonstrated in the class doc.
+     *
+     * @param withAlpha if true, set A to {@code alpha}, otherwise A channel is ignored.
+     * @param alpha alpha channel value. Only effective when {@code withAlpha} is {@code true}.
+     */
+    static ByteBuffer createRgbOrRgbaBuffer(boolean withAlpha, int alpha) {
+        int capacity = withAlpha ? 80 : 60;
+        ByteBuffer buffer = ByteBuffer.allocateDirect(capacity);
+        putColorInByteBuffer(buffer, 0, 0, BLUE, withAlpha, alpha, 5);
+        putColorInByteBuffer(buffer, 0xff, 0xff, 0xff, withAlpha, alpha, 5);
+        putColorInByteBuffer(buffer, 0, GREEN, 0, withAlpha, alpha, 5);
+        putColorInByteBuffer(buffer, RED, 0, 0, withAlpha, alpha, 5);
+        buffer.rewind();
+        return buffer;
+    }
+
+    private static void putColorInByteBuffer(
+            ByteBuffer buffer, int r, int g, int b, boolean withAlpha, int alpha, int num) {
+        for (int i = 0; i < num; i++) {
+            buffer.put((byte) r);
+            buffer.put((byte) g);
+            buffer.put((byte) b);
+            if (withAlpha) {
+                buffer.put((byte) alpha);
+            }
+        }
+    }
+
+    // Should not be instantiated.
+    private TestImageCreator() {}
+}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/third_party_licenses/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/third_party_licenses/BUILD
new file mode 100644
index 0000000..b3c4abb
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/odml/java/image/third_party_licenses/BUILD
@@ -0,0 +1,68 @@
+# This file is auto generated by addlicensedeps.py. Please do not edit any part
+# of this file except to add missing licenses to the extra_licenses parameter.
+#
+# This file should not need to be updated unless the license_presubmit_check is
+# failing. To update it, run the following command from a CitC client on Linux:
+#
+# /google/bin/releases/opensource/tools/addlicensedeps_py/addlicensedeps --target=//third_party/tensorflow_lite_support/odml/java/image:image --create_licenses_and_metadata_filegroups
+
+load("//devtools/compliance/addlicensedeps/py:third_party_licenses.bzl", "third_party_licenses")
+
+licenses(["notice"])
+
+third_party_licenses(
+    create_licenses_and_metadata_filegroups = True,
+    custom_output_directory = None,
+    custom_package = None,
+    extra_licenses = {},
+    generated_licenses = {
+        "AndroidX activity library": "third_party/java/androidx/activity/hack_for_licenses/LICENSE",
+        "AndroidX annotation experimental library": "third_party/java/androidx/annotation/experimental/LICENSE",
+        "AndroidX annotation library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/annotations/LICENSE",
+        "AndroidX architecture core library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/core/common/LICENSE",
+        "AndroidX architecture library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/core/runtime/LICENSE",
+        "AndroidX asynclayoutinflater library": "third_party/java/androidx/asynclayoutinflater/LICENSE",
+        "AndroidX collection library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/collections/LICENSE",
+        "AndroidX concurrent futures library": "third_party/java/androidx/concurrent/futures/LICENSE",
+        "AndroidX coordinatorlayout library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/coordinatorlayout/LICENSE",
+        "AndroidX core library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/compat/LICENSE",
+        "AndroidX cursoradapter library": "third_party/java/androidx/cursoradapter/LICENSE",
+        "AndroidX customview library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/customview/LICENSE",
+        "AndroidX documentfile library": "third_party/java/androidx/documentfile/LICENSE",
+        "AndroidX drawerlayout library": "third_party/java/androidx/drawerlayout/LICENSE",
+        "AndroidX fragment library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/fragment/LICENSE",
+        "AndroidX interpolator library": "third_party/java/androidx/interpolator/LICENSE",
+        "AndroidX legacy coreui library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/core_ui/LICENSE",
+        "AndroidX legacy coreutils library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/core_utils/LICENSE",
+        "AndroidX legacy v4 library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/v4/LICENSE",
+        "AndroidX lifecycle common library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/lifecycle/common/LICENSE",
+        "AndroidX lifecycle livedatacore library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/lifecycle/livedata_core/LICENSE",
+        "AndroidX lifecycle runtime library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/lifecycle/runtime/LICENSE",
+        "AndroidX lifecycle viewmodel library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/lifecycle/viewmodel/LICENSE",
+        "AndroidX lifecycle viewmodel savedstate library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/arch_components/lifecycle/lifecycle_viewmodel_savedstate/LICENSE",
+        "AndroidX loader library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/loader/LICENSE",
+        "AndroidX localbroadcastmanager library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/localbroadcastmanager/LICENSE",
+        "AndroidX media base library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/media_compat/LICENSE",
+        "AndroidX print library": "third_party/java/androidx/print/LICENSE",
+        "AndroidX savedstate library": "third_party/java/androidx/savedstate/hack_for_licenses/LICENSE",
+        "AndroidX swiperefreshlayout library": "third_party/java/androidx/swiperefreshlayout/LICENSE",
+        "AndroidX tracing library": "third_party/java/androidx/tracing/hack_for_licenses/LICENSE",
+        "AndroidX versionedparcelable library": "third_party/java/android/android_sdk_linux/extras/android/compatibility/versionedparcelable/LICENSE",
+        "AndroidX viewpager library": "third_party/java/androidx/viewpager/LICENSE",
+        "Animal Sniffer": "third_party/java/animal_sniffer/LICENSE",
+        "Checker Framework Annotations": "third_party/java/checker_framework_annotations/LICENSE",
+        "Error Prone": "third_party/java/error_prone/LICENSE",
+        "Google Auto": "third_party/java/auto/LICENSE",
+        "Guava JDK5": "third_party/java/android_libs/guava_jdk5/LICENSE",
+        "Guava JDK7": "third_party/java_src/google_common/LICENSE",
+        "J2ObjC": "third_party/java/j2objc/LICENSE",
+        "JSR 250": "third_party/java/jsr250_annotations/LICENSE",
+        "JSR 305": "third_party/java/jsr305_annotations/LICENSE",
+        "JSpecify": "third_party/java/jspecify_annotations/LICENSE",
+        "JsInterop Annotations": "third_party/java_src/jsinterop_annotations/java/jsinterop/annotations/LICENSE",
+        "TensorFlow Lite Support": "third_party/tensorflow_lite_support/LICENSE",
+        "Kotlin": "third_party/kotlin/kotlin/LICENSE",
+    },
+    platform = "android",
+    target = "//tensorflow_lite_support/odml/java/image",
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/opensource/opensource_only.files b/third_party/tflite_support/src/tensorflow_lite_support/opensource/opensource_only.files
index be426420..71f2c89 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/opensource/opensource_only.files
+++ b/third_party/tflite_support/src/tensorflow_lite_support/opensource/opensource_only.files
@@ -1,7 +1,8 @@
+tensorflow_lite_support/cc/port/build_defs.bzl
 tensorflow_lite_support/custom_ops/kernel/sentencepiece/native.bzl
+tensorflow_lite_support/opensource/.bazelversion
 tensorflow_lite_support/opensource/BUILD
 tensorflow_lite_support/opensource/WORKSPACE
-tensorflow_lite_support/opensource/cc_build_defs.bzl
 tensorflow_lite_support/third_party/android/BUILD
 tensorflow_lite_support/third_party/android/android.bzl.tpl
 tensorflow_lite_support/third_party/android/android_configure.BUILD.tpl
@@ -24,6 +25,13 @@
 tensorflow_lite_support/third_party/toolchains/java/BUILD
 tensorflow_lite_support/third_party/utf.BUILD
 tensorflow_lite_support/third_party/zlib.BUILD
+tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_instrumentation_test_template.xml
+tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_target_stub.xml
+tensorflow_lite_support/tools/build_rules/android_test/android_library_instrumentation_tests.bzl
+tensorflow_lite_support/tools/build_rules/android_test/android_multidevice_instrumentation_test.bzl
+tensorflow_lite_support/tools/build_rules/android_test/generate_instrumentation_tests.bzl
+tensorflow_lite_support/tools/build_rules/android_test/infer_java_package_name.bzl
+tensorflow_lite_support/tools/build_rules/http_files.bzl
 tensorflow_lite_support/tools/ci_build/build_all.sh
 tensorflow_lite_support/tools/ci_build/common.sh
 tensorflow_lite_support/tools/ci_build/common_win.bat
@@ -31,6 +39,7 @@
 tensorflow_lite_support/tools/pip_package/MANIFEST.in
 tensorflow_lite_support/tools/pip_package/README
 tensorflow_lite_support/tools/pip_package/build_pip_package.sh
+tensorflow_lite_support/tools/pip_package/metadata_writers.__init__.py
 tensorflow_lite_support/tools/pip_package/setup.py
 tensorflow_lite_support/tools/pip_package/simple_console_for_windows.py
 tensorflow_lite_support/tools/pip_package/tflite_support.__init__.py
\ No newline at end of file
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/tools/BUILD
index c3525ca..402b274 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/BUILD
@@ -13,8 +13,3 @@
         "@absl_py//absl/flags",
     ],
 )
-
-py_library(
-    name = "expect_flatbuffers_installed",
-    srcs = [],
-)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/Build_TFLite_Support_Targets.ipynb b/third_party/tflite_support/src/tensorflow_lite_support/tools/Build_TFLite_Support_Targets.ipynb
new file mode 100644
index 0000000..3e7e64e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/Build_TFLite_Support_Targets.ipynb
@@ -0,0 +1,278 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Build_TensorFlow_Lite_Support_Libraries_with_Bazel_and_Colab.ipynb",
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "bFF0wwGKvyxw"
+      },
+      "source": [
+        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+        "you may not use this file except in compliance with the License.\n",
+        "You may obtain a copy of the License at\n",
+        "    http://www.apache.org/licenses/LICENSE-2.0\n",
+        "Unless required by applicable law or agreed to in writing, software\n",
+        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+        "See the License for the specific language governing permissions and\n",
+        "limitations under the License."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_u2bOkHzv4F4"
+      },
+      "source": [
+        "# Build TensorFlow Lite Support libraries with Bazel "
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "sh4xCk3Ygq6p"
+      },
+      "source": [
+        "## Set up Android environment"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "S-NOtaam7Ebn"
+      },
+      "source": [
+        "# Create folders\n",
+        "!mkdir -p '/android/sdk'\n",
+        "\n",
+        "# Download and move android SDK tools to specific folders\n",
+        "!wget -q 'https://dl.google.com/android/repository/tools_r25.2.5-linux.zip'\n",
+        "\n",
+        "!unzip 'tools_r25.2.5-linux.zip'\n",
+        "!mv '/content/tools' '/android/sdk'\n",
+        "# Copy paste the folder\n",
+        "!cp -r /android/sdk/tools /android/android-sdk-linux\n",
+        "\n",
+        "# Download NDK, unzip and move contents\n",
+        "!wget 'https://dl.google.com/android/repository/android-ndk-r19c-linux-x86_64.zip'\n",
+        "\n",
+        "!unzip 'android-ndk-r19c-linux-x86_64.zip'\n",
+        "!mv /content/android-ndk-r19c /content/ndk\n",
+        "!mv '/content/ndk' '/android'\n",
+        "# Copy paste the folder\n",
+        "!cp -r /android/ndk /android/android-ndk-r19c\n",
+        "\n",
+        "# Remove .zip files\n",
+        "!rm 'tools_r25.2.5-linux.zip'\n",
+        "!rm 'android-ndk-r19c-linux-x86_64.zip'\n",
+        "\n",
+        "# Make android ndk executable to all users\n",
+        "!chmod -R go=u '/android'"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "dTZrWYNwhd7G"
+      },
+      "source": [
+        "# Set and view environment variables\n",
+        "%env PATH = /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tools/node/bin:/tools/google-cloud-sdk/bin:/opt/bin:/android/sdk/tools:/android/sdk/platform-tools:/android/ndk\n",
+        "%env ANDROID_SDK_API_LEVEL=29\n",
+        "%env ANDROID_API_LEVEL=29\n",
+        "%env ANDROID_BUILD_TOOLS_VERSION=29.0.2\n",
+        "%env ANDROID_DEV_HOME=/android\n",
+        "%env ANDROID_NDK_API_LEVEL=21\n",
+        "%env ANDROID_NDK_FILENAME=android-ndk-r19c-linux-x86_64.zip\n",
+        "%env ANDROID_NDK_HOME=/android/ndk\n",
+        "%env ANDROID_NDK_URL=https://dl.google.com/android/repository/android-ndk-r19c-linux-x86_64.zip\n",
+        "%env ANDROID_SDK_FILENAME=tools_r25.2.5-linux.zip\n",
+        "%env ANDROID_SDK_HOME=/android/sdk\n",
+        "#%env ANDROID_HOME=/android/sdk\n",
+        "%env ANDROID_SDK_URL=https://dl.google.com/android/repository/tools_r25.2.5-linux.zip\n",
+        "\n",
+        "#!echo $PATH\n",
+        "!export -p"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "e26VrdXdL2U6"
+      },
+      "source": [
+        "# Install specific versions of sdk, tools etc.\n",
+        "!android update sdk --no-ui -a \\\n",
+        "  --filter tools,platform-tools,android-29,build-tools-29.0.2"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "3eAfl3MmySzO"
+      },
+      "source": [
+        "## Install BAZEL with Baselisk"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "Dj_P2Fb-yTqq"
+      },
+      "source": [
+        "# Download Latest version of Bazelisk\n",
+        "!wget https://github.com/bazelbuild/bazelisk/releases/latest/download/bazelisk-linux-amd64\n",
+        "\n",
+        "# Make script executable\n",
+        "!chmod +x bazelisk-linux-amd64\n",
+        "\n",
+        "# Adding to the path\n",
+        "!sudo mv bazelisk-linux-amd64 /usr/local/bin/bazel\n",
+        "\n",
+        "# Extract bazel info\n",
+        "!bazel"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "AMPL9u6tzOMJ"
+      },
+      "source": [
+        "# Clone TensorFlow Lite Support repository OR upload your custom folder to build\n",
+        "!git clone https://github.com/tensorflow/tflite-support.git"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "9KXH-1So0VOd"
+      },
+      "source": [
+        "# Move into tflite-support folder\n",
+        "%cd /content/tflite-support/\n",
+        "\n",
+        "!ls"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "2D2tsSFs7Hrq"
+      },
+      "source": [
+        "## Build .aar files"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "8XM37u827jD_"
+      },
+      "source": [
+        "#@title Select library. { display-mode: \"form\" }\n",
+        "\n",
+        "library = 'Support library' #@param [\"Support library\", \"Task Vision library\", \"Task Text library\", \"Task Audio library\",\"Metadata library\",\"C++ image_classifier\",\"C++ image_objector\",\"C++ image_segmenter\",\"C++ image_embedder\",\"C++ nl_classifier\",\"C++ bert_nl_classifier\", \"C++ bert_question_answerer\", \"C++ metadata_extractor\"]\n",
+        "\n",
+        "print('You selected:', library)\n",
+        "\n",
+        "if library == 'Support library':\n",
+        "    library = '//tensorflow_lite_support/java:tensorflowlite_support.aar'\n",
+        "elif library == 'Task Vision library':\n",
+        "    library = '//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision:task-library-vision'\n",
+        "elif library == 'Task Text library':\n",
+        "    library = '//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text:task-library-text'\n",
+        "elif library == 'Task Audio library':\n",
+        "    library = '//tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio:task-library-audio'\n",
+        "elif library == 'Metadata library':\n",
+        "    library = '//tensorflow_lite_support/metadata/java:tensorflow-lite-support-metadata-lib'\n",
+        "elif library == 'C++ image_classifier':\n",
+        "    library = '//tensorflow_lite_support/cc/task/vision:image_classifier'\n",
+        "elif library == 'C++ image_objector':\n",
+        "    library = '//tensorflow_lite_support/cc/task/vision:image_objector'\n",
+        "elif library == 'C++ image_segmenter':\n",
+        "    library = '//tensorflow_lite_support/cc/task/vision:image_segmenter'\n",
+        "elif library == 'C++ image_embedder':\n",
+        "    library = '//tensorflow_lite_support/cc/task/vision:image_embedder'\n",
+        "elif library == 'C++ nl_classifier':\n",
+        "    library = '//tensorflow_lite_support/cc/task/text/nlclassifier:nl_classifier'\n",
+        "elif library == 'C++ bert_nl_classifier':\n",
+        "    library = '//tensorflow_lite_support/cc/task/text/nlclassifier:bert_nl_classifier'\n",
+        "elif library == 'C++ bert_question_answerer':\n",
+        "    library = '//tensorflow_lite_support/cc/task/text/qa:bert_question_answerer'\n",
+        "elif library == 'C++ metadata_extractor':\n",
+        "    library = '//tensorflow_lite_support/metadata/cc:metadata_extractor'\n",
+        "\n"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "WwanGSg-FE-0"
+      },
+      "source": [
+        "#@title Select platform(s). { display-mode: \"form\" }\n",
+        "\n",
+        "platforms = 'arm64-v8a,armeabi-v7a' #@param [\"arm64-v8a,armeabi-v7a\",\"x86\", \"x86_64\", \"arm64-v8a\", \"armeabi-v7a\",\"x86,x86_64,arm64-v8a,armeabi-v7a\"]\n",
+        "print('You selected:', platforms)\n"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "FBw-vFrw0hdc"
+      },
+      "source": [
+        "# Build library\n",
+        "!bazel build \\\n",
+        "    --fat_apk_cpu='{platforms}' \\\n",
+        "    '{library}'"
+      ],
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "vRCanN-W5Av7"
+      },
+      "source": [
+        ""
+      ],
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/BUILD
new file mode 100644
index 0000000..34d04920
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/BUILD
@@ -0,0 +1,4 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_instrumentation_test_template.xml b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_instrumentation_test_template.xml
new file mode 100644
index 0000000..7c43c16
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_instrumentation_test_template.xml
@@ -0,0 +1,31 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!--
+  ~ Copyright (C) 2018 The Android Open Source Project
+  ~
+  ~ Licensed under the Apache License, Version 2.0 (the "License");
+  ~ you may not use this file except in compliance with the License.
+  ~ You may obtain a copy of the License at
+  ~
+  ~   http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing, software
+  ~ distributed under the License is distributed on an "AS IS" BASIS,
+  ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  ~ See the License for the specific language governing permissions and
+  ~ limitations under the License.
+  -->
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+    package="${applicationId}" >
+
+    <uses-sdk
+        android:minSdkVersion="19"
+        android:targetSdkVersion="28" />
+
+    <application/>
+
+    <instrumentation
+        android:name="androidx.test.runner.AndroidJUnitRunner"
+        android:targetPackage="${instrumentationTargetPackage}">
+    </instrumentation>
+
+</manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_target_stub.xml b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_target_stub.xml
new file mode 100644
index 0000000..e1f4f30
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/AndroidManifest_target_stub.xml
@@ -0,0 +1,24 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!--
+  ~ Copyright (C) 2018 The Android Open Source Project
+  ~
+  ~ Licensed under the Apache License, Version 2.0 (the "License");
+  ~ you may not use this file except in compliance with the License.
+  ~ You may obtain a copy of the License at
+  ~
+  ~   http://www.apache.org/licenses/LICENSE-2.0
+  ~
+  ~ Unless required by applicable law or agreed to in writing, software
+  ~ distributed under the License is distributed on an "AS IS" BASIS,
+  ~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  ~ See the License for the specific language governing permissions and
+  ~ limitations under the License.
+  -->
+<manifest xmlns:android="http://schemas.android.com/apk/res/android"
+    package="${applicationId}" >
+
+    <uses-sdk
+        android:minSdkVersion="19"
+        android:targetSdkVersion="28" />
+
+</manifest>
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/BUILD
new file mode 100644
index 0000000..a515bdda
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/BUILD
@@ -0,0 +1,11 @@
+package(
+    default_visibility = ["//tensorflow_lite_support:users"],
+    licenses = ["notice"],  # Apache 2.0
+)
+
+exports_files(
+    [
+        "AndroidManifest_instrumentation_test_template.xml",
+        "AndroidManifest_target_stub.xml",
+    ],
+)
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/android_library_instrumentation_tests.bzl b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/android_library_instrumentation_tests.bzl
new file mode 100644
index 0000000..b0028e8
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/android_library_instrumentation_tests.bzl
@@ -0,0 +1,78 @@
+"""A rule wrapper for an instrumentation test for an android library."""
+
+load(
+    "//tensorflow_lite_support/tools/build_rules/android_test:generate_instrumentation_tests.bzl",
+    "generate_instrumentation_tests",
+)
+load(
+    "//tensorflow_lite_support/tools/build_rules/android_test:infer_java_package_name.bzl",
+    "infer_java_package_name",
+)
+
+def android_library_instrumentation_tests(
+        name,
+        srcs,
+        deps,
+        target_devices,
+        test_java_package = None,
+        library_args = {},
+        binary_args = {},
+        **kwargs):
+    """A macro for an instrumentation test whose target under test is an android_library.
+
+    Will generate a 'self-instrumentating' test binary and other associated rules
+
+    The intent of this wrapper is to simplify the build API for creating instrumentation test rules
+    for simple cases, while still supporting build_cleaner for automatic dependency management.
+
+    This will generate:
+      - an unused stub android_binary under test, to placate bazel
+      - a test_lib android_library, containing all sources and dependencies
+      - a test_binary android_binary (soon to be android_application)
+      - the manifest to use for the test library.
+      - for each device combination:
+         - an android_instrumentation_test rule)
+
+    Args:
+      name: the name to use for the generated android_library rule. This is needed for build_cleaner to
+        manage dependencies
+      srcs: the test sources to generate rules for
+      deps: the build dependencies to use for the generated test binary
+      target_devices: array of device targets to execute on
+      test_java_package: Optional. A custom root package name to use for the tests. If unset
+          will be derived based on current path to a java source root
+      library_args: additional arguments to pass to generated android_library
+      binary_args: additional arguments to pass to generated android_binary
+      **kwargs: arguments to pass to generated android_instrumentation_test rules
+    """
+    library_name = "%s_library" % name
+    test_java_package_name = test_java_package if test_java_package else infer_java_package_name()
+
+    native.android_binary(
+        name = "target_stub_binary",
+        manifest = "//tensorflow_lite_support/tools/build_rules/android_test:AndroidManifest_target_stub.xml",
+        # use the same package name as the test package, so it gets overridden
+        manifest_values = {"applicationId": test_java_package_name},
+        testonly = 1,
+    )
+
+    native.android_library(
+        name = library_name,
+        srcs = srcs,
+        testonly = 1,
+        deps = deps,
+        **library_args
+    )
+
+    generate_instrumentation_tests(
+        name = name,
+        srcs = srcs,
+        deps = [library_name],
+        target_devices = target_devices,
+        test_java_package_name = test_java_package_name,
+        test_android_package_name = test_java_package_name,
+        instrumentation_target_package = test_java_package_name,
+        instruments = ":target_stub_binary",
+        binary_args = binary_args,
+        **kwargs
+    )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/android_multidevice_instrumentation_test.bzl b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/android_multidevice_instrumentation_test.bzl
new file mode 100644
index 0000000..c252b03b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/android_multidevice_instrumentation_test.bzl
@@ -0,0 +1,17 @@
+"""Utility for running single test on multiple emulator targets."""
+
+def android_multidevice_instrumentation_test(name, target_devices, **kwargs):
+    """Generates a android_instrumentation_test rule for each given device.
+
+    Args:
+      name: Name prefix to use for the rules. The name of the generated rules will follow:
+        name + target_device[-6:] eg name-15_x86
+      target_devices: array of device targets
+      **kwargs: arguments to pass to generated android_test rules
+    """
+    for device in target_devices:
+        native.android_instrumentation_test(
+            name = name + "-" + device[-6:],
+            target_device = device,
+            **kwargs
+        )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/generate_instrumentation_tests.bzl b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/generate_instrumentation_tests.bzl
new file mode 100644
index 0000000..fb586d1
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/generate_instrumentation_tests.bzl
@@ -0,0 +1,62 @@
+"""Internal helper function for generating instrumentation tests ."""
+
+load(
+    "//tensorflow_lite_support/tools/build_rules/android_test:android_multidevice_instrumentation_test.bzl",
+    "android_multidevice_instrumentation_test",
+)
+
+def generate_instrumentation_tests(
+        name,
+        srcs,
+        deps,
+        target_devices,
+        test_java_package_name,
+        test_android_package_name,
+        instrumentation_target_package,
+        instruments,
+        binary_args = {},
+        **kwargs):
+    """A helper rule to generate instrumentation tests.
+
+
+    This will generate:
+      - a test_binary android_binary (soon to be android_application)
+      - the manifest to use for the test library.
+      - for each device combination:
+         - an android_instrumentation_test rule)
+
+    Args:
+      name: unique prefix to use for generated rules
+      srcs: the test sources to generate rules for
+      deps: the build dependencies to use for the generated test binary
+      target_devices: array of device targets to execute on
+      test_java_package_name: the root java package name for the tests.
+      test_android_package_name: the android package name to use for the android_binary test app. Typically this is the same as test_java_package_name
+      instrumentation_target_package: the android package name to specify as instrumentationTargetPackage in the test_app manifest
+      instruments: The android binary the tests instrument.
+      binary_args: Optional additional arguments to pass to generated android_binary
+      **kwargs: arguments to pass to generated android_instrumentation_test rules
+    """
+
+    _manifest_values = {
+        "applicationId": test_android_package_name,
+        "instrumentationTargetPackage": instrumentation_target_package,
+    }
+    _manifest_values.update(binary_args.pop("manifest_values", {}))
+    native.android_binary(
+        name = "%s_binary" % name,
+        instruments = instruments,
+        manifest = "//tensorflow_lite_support/tools/build_rules/android_test:AndroidManifest_instrumentation_test_template.xml",
+        manifest_values = _manifest_values,
+        testonly = 1,
+        deps = deps + [
+            "@maven//:androidx_test_runner",
+        ],
+        **binary_args
+    )
+    android_multidevice_instrumentation_test(
+        name = "%s_tests" % name,
+        target_devices = target_devices,
+        test_app = "%s_binary" % name,
+        **kwargs
+    )
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/infer_java_package_name.bzl b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/infer_java_package_name.bzl
new file mode 100644
index 0000000..929bb7e
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/android_test/infer_java_package_name.bzl
@@ -0,0 +1,28 @@
+"""A rule for inferring a java package name."""
+
+_JAVA_ROOTS = [
+    "javatests/",
+    "javatest/",
+    "java/",
+]
+
+def infer_java_package_name():
+    """Infer a java package name based on current path below 'javatests' or 'java'"""
+    return _infer_java_package_name_from_path(native.package_name())
+
+def infer_java_package_name_from_label(label):
+    package_path = _get_path_from_label(label)
+    return _infer_java_package_name_from_path(package_path)
+
+def _infer_java_package_name_from_path(package_path):
+    for root in _JAVA_ROOTS:
+        if root in package_path:
+            root_index = package_path.rindex(root) + len(root)
+            return package_path[root_index:].replace("/", ".")
+    fail("Could not find one of java roots %s in %s" % (_JAVA_ROOTS, package_path))
+
+def _get_path_from_label(label_string):
+    label_string = label_string.split(":")[0]
+    if not label_string.startswith("//"):
+        label_string = "//%s%s" % (native.package_name(), label_string)
+    return label_string
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/http_files.bzl b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/http_files.bzl
new file mode 100644
index 0000000..58be497
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/build_rules/http_files.bzl
@@ -0,0 +1,28 @@
+"""Build rule to depend on files downloaded from http_file."""
+
+def tflite_file(name, extension):
+    """Links the tflite file from http_file with the current directory.
+
+    Args:
+      name: the name of the tflite_file target, which is also the name of the
+      tflite file specified through http_file in WORKSPACE. For example, if
+      `name` is Foo, `tflite_file` will create a link to the downloaded file
+      file "@Foo//file" to the current directory as "Foo.tflite".
+      extension: the extension of the file.
+    """
+    native.genrule(
+        name = "%s_ln" % (name),
+        srcs = ["@%s//file" % (name)],
+        outs = ["%s.%s" % (name, extension)],
+        output_to_bindir = 1,
+        cmd = "ln $< $@",
+    )
+
+    native.filegroup(
+        name = name,
+        srcs = ["%s.%s" % (name, extension)],
+    )
+
+def tflite_model(name):
+    """Links the tflite model from http_file with the current directory."""
+    tflite_file(name, "tflite")
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh
index 5bbfb60..4219a8e 100755
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/build_all.sh
@@ -17,17 +17,56 @@
 
 set -ex
 
-bazel build -c opt --config=monolithic \
-    //tensorflow_lite_support/java:tensorflowlite_support \
-    //tensorflow_lite_support/codegen/python:codegen \
-    //tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata_lib \
-    //tensorflow_lite_support/metadata/cc:metadata_extractor \
-    //tensorflow_lite_support/custom_ops/kernel:all \
-    //tensorflow_lite_support/custom_ops/python:tflite_text_api
+bash tensorflow_lite_support/custom_ops/tf_configure.sh
 
-# Build Task libraries.
+# TODO(b/200756963): Make it possible to build flatbuffer schema libraries with
+# more jobs.
 bazel build -c opt --config=monolithic \
+    //tensorflow_lite_support/metadata/java:tensorflowlite_support_metadata_lib \
+    //tensorflow_lite_support/metadata/cc:metadata_extractor
+
+export BAZEL_PARALLEL="-j 32"
+
+# General targets.
+bazel build -c opt ${BAZEL_PARALLEL} --config=monolithic \
+    //tensorflow_lite_support/codegen/python:codegen \
+    //tensorflow_lite_support/custom_ops/kernel:all \
+    //tensorflow_lite_support/custom_ops/python:tflite_text_api \
+    //tensorflow_lite_support/examples/task/audio/desktop:audio_classifier_demo
+
+# Android targets.
+bazel build -c opt ${BAZEL_PARALLEL} --config=monolithic \
     --config=android_arm64 --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a \
+    //tensorflow_lite_support/java:tensorflowlite_support \
+    //tensorflow_lite_support/cc/task/vision:image_embedder \
+    //tensorflow_lite_support/cc/task/audio:audio_embedder \
+    //tensorflow_lite_support/cc/task/processor:all \
+    //tensorflow_lite_support/odml/java/image \
     //tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/core:base-task-api.aar \
     //tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/text:task-library-text \
-    //tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision:task-library-vision
+    //tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/vision:task-library-vision \
+    //tensorflow_lite_support/java/src/java/org/tensorflow/lite/task/audio:task-library-audio \
+    //tensorflow_lite_support/acceleration/configuration:gpu-delegate-plugin
+
+bazel clean
+# Coral plugin.
+bazel build -c opt ${BAZEL_PARALLEL} --define=darwinn_portable=1 \
+    //tensorflow_lite_support/acceleration/configuration:edgetpu_coral_plugin
+
+# Tests.
+
+bazel clean
+
+bazel test -c opt $BAZEL_PARALLEL --test_output=all \
+    //tensorflow_lite_support/c/test/... \
+    //tensorflow_lite_support/cc/test/task/vision:all \
+    //tensorflow_lite_support/cc/test/task/text/... \
+    //tensorflow_lite_support/custom_ops/kernel/sentencepiece:all \
+    //tensorflow_lite_support/metadata/python/tests:metadata_test \
+    //tensorflow_lite_support/metadata/python/tests/metadata_writers:all \
+
+bazel test -c opt $BAZEL_PARALLEL --test_output=all --build_tests_only \
+    --build_tag_filters=-tflite_emulator_test_android \
+    --test_tag_filters=-tflite_emulator_test_android \
+    //tensorflow_lite_support/java/src/javatests/org/tensorflow/lite/support/...
+
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/build_ios_framework.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/build_ios_framework.sh
new file mode 100755
index 0000000..8f8ae294
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/build_ios_framework.sh
@@ -0,0 +1,137 @@
+#!/usr/bin/env bash
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+# Set the following variables as appropriate.
+#   * BAZEL: path to bazel. defaults to the first one available in PATH
+#   * TFLS_BUILD_VERSION: to specify the release version. defaults to 0.0.1-dev
+#   * IS_RELEASE_BUILD: set as true if this build should be a release build
+#   * ARCHIVE_FRAMEWORK: set as true if the framework should be archived
+#   * DEST_DIR: destination directory to which the framework will be copied
+
+set -ex
+
+if [[ "$(uname)" != "Darwin" ]]; then
+  echo "This build script only works on macOS."
+  exit 1
+fi
+
+BAZEL="${BAZEL:-$(which bazel)}"
+TFLS_BUILD_VERSION=${TFLS_BUILD_VERSION:-0.0.1-dev}
+TFLS_ROOT_DIR=$(git rev-parse --show-toplevel)
+
+if [[ ! -x "${BAZEL}" ]]; then
+  echo "bazel executable is not found."
+  exit 1
+fi
+
+if [[ -z "${DEST_DIR}" || "${DEST_DIR}" == ${TFLS_ROOT_DIR}* ]]; then
+  echo "DEST_DIR variable must be set and not be under the repository root."
+  exit 1
+fi
+
+# Builds the C API framework for the specified framework for iOS.
+function build_c_api_framework {
+  "${BAZEL}" build -c opt --config=ios_fat \
+    //tensorflow_lite_support/ios:$1C_framework
+}
+
+function create_framework_archive {
+  TARGET_FRAMEWORK_NAME="$1"
+  C_API_FRAMEWORK_NAME="$1C"
+
+  TFLS_IOS_DIR=tensorflow_lite_support/ios
+  BAZEL_IOS_OUTDIR="bazel-bin/${TFLS_IOS_DIR}"
+
+  # Change to the Bazel iOS output directory.
+  pushd "${BAZEL_IOS_OUTDIR}"
+
+  # Create the temporary directory for the given framework.
+  ARCHIVE_NAME="${TARGET_FRAMEWORK_NAME}-${TFLS_BUILD_VERSION}"
+  TFLS_TMPDIR="$(mktemp -d)"
+
+  # Unzip the framework into the appropriate directory structure for CocoaPods.
+  # The final archive should contain the C API framework as a vendored framework
+  # as well as all the Obj-C source code and the header files.
+  #
+  # The directory structure will be like:
+  #
+  # ${TFLS_TMPDIR}/
+  #  |-- tensorflow_lite_support/
+  #  |   |-- cc/
+  #  |   |   +-- <C-API header files...>
+  #  |   +-- ios/
+  #  |       +-- <Obj-C header/source files...>
+  #  +-- Frameworks/
+  #      +-- TensorFlowLiteTaskTextC.framework
+  #
+
+  # ----- (1) Copy source files -----
+  pushd "${TFLS_ROOT_DIR}"
+
+  # Source files to be archived along with the static framework.
+  SRC_PATTERNS="
+    */cc/*c_api*.h
+    */ios/task/text/*/Sources/*
+    */ios/task/text/apis/*
+  "
+
+  # List of individual files obtained from the patterns above.
+  SRC_FILES=$(xargs -n1 find * -wholename <<< "${SRC_PATTERNS}" | sort | uniq)
+
+  # Copy source files with the intermediate directories preserved.
+  xargs -n1 -I{} rsync -R {} "${TFLS_TMPDIR}" <<< "${SRC_FILES}"
+  popd
+
+  # ----- (2) Unzip the prebuilt C API framework -----
+  unzip "${C_API_FRAMEWORK_NAME}_framework.zip" -d "${TFLS_TMPDIR}"/Frameworks
+
+  # ----- (3) Move the framework to the destination -----
+  if [[ "${ARCHIVE_FRAMEWORK}" == true ]]; then
+    TARGET_DIR="$(realpath "${TARGET_FRAMEWORK_NAME}")"
+
+    # Create the framework archive directory.
+    if [[ "${IS_RELEASE_BUILD}" == true ]]; then
+      # Get the first 16 bytes of the sha256 checksum of the root directory.
+      SHA256_CHECKSUM=$(find "${TFLS_TMPDIR}" -type f -print0 | xargs -0 shasum -a 256 | sort | shasum -a 256 | cut -c1-16)
+      FRAMEWORK_ARCHIVE_DIR="${TARGET_DIR}/${TFLS_BUILD_VERSION}/${SHA256_CHECKSUM}"
+    else
+      FRAMEWORK_ARCHIVE_DIR="${TARGET_DIR}/${TFLS_BUILD_VERSION}"
+    fi
+    mkdir -p "${FRAMEWORK_ARCHIVE_DIR}"
+
+    # Zip up the framework and move to the archive directory.
+    pushd "${TFLS_TMPDIR}"
+    TFLS_ARCHIVE_FILE="${ARCHIVE_NAME}.tar.gz"
+    tar -cvzf "${TFLS_ARCHIVE_FILE}" .
+    mv "${TFLS_ARCHIVE_FILE}" "${FRAMEWORK_ARCHIVE_DIR}"
+    popd
+
+    # Move the target directory to the Kokoro artifacts directory.
+    mv "${TARGET_DIR}" "$(realpath "${DEST_DIR}")"/
+  else
+    rsync -r "${TFLS_TMPDIR}/" "$(realpath "${DEST_DIR}")/"
+  fi
+
+  # Clean up the temporary directory for the framework.
+  rm -rf "${TFLS_TMPDIR}"
+
+  # Pop back to the TFLS root directory.
+  popd
+}
+
+cd "${TFLS_ROOT_DIR}"
+build_c_api_framework TensorFlowLiteTaskText
+create_framework_archive TensorFlowLiteTaskText
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/pip_smoke_test.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/pip_smoke_test.sh
new file mode 100755
index 0000000..49f8c3d
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/builds/pip_smoke_test.sh
@@ -0,0 +1,117 @@
+#!/bin/bash
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+# Pip install TensorFlow Lite Support and run basic test on the pip package.
+
+# Important: Use msys shell to run this script on Windows.
+
+set -e
+set -x
+
+function run_smoke_test() {
+  VENV_TMP_DIR="$(mktemp -d)"
+
+  if [[ "$OSTYPE" == "msys" ]]; then
+    VENV_TMP_DIR="$(cygpath -m $VENV_TMP_DIR)"
+  fi
+
+  python -m virtualenv "${VENV_TMP_DIR}" || \
+      die "FAILED: Unable to create virtualenv"
+
+  if [[ "$OSTYPE" == "msys" ]]; then
+    source "${VENV_TMP_DIR}/Scripts/activate" || \
+        die "FAILED: Unable to activate virtualenv "
+  else
+    source "${VENV_TMP_DIR}/bin/activate" || \
+        die "FAILED: Unable to activate virtualenv "
+  fi
+
+  # install tflite-support
+  python -m pip install ${WHL_NAME} || \
+      die "pip install (forcing to reinstall tflite-support) FAILED"
+  echo "Successfully installed pip package ${WHL_NAME}"
+
+  # Download a test model
+  export TEST_MODEL="$(pwd)/test.tflite"
+  wget https://tfhub.dev/tensorflow/lite-model/mobilenet_v1_0.75_192_quantized/1/metadata/1\?lite-format\=tflite -O "$TEST_MODEL"
+  if [[ "$OSTYPE" == "msys" ]]; then
+    TEST_MODEL=$(cygpath -m $TEST_MODEL)
+  fi
+
+  test_tfls_imports
+
+  test_codegen
+
+  # Deactivate from virtualenv.
+  deactivate || source deactivate || \
+      die "FAILED: Unable to deactivate from existing virtualenv."
+
+  echo "All smoke test passes!"
+}
+
+function test_tfls_imports() {
+  TMP_DIR=$(mktemp -d)
+  pushd "${TMP_DIR}"
+
+  # test for basic import and metadata display.
+  RET_VAL=$(python -c "from tflite_support import metadata; \
+md = metadata.MetadataDisplayer.with_model_file(\"$TEST_MODEL\"); \
+print(md.get_metadata_json())")
+
+  # just check if the model name is there.
+  if ! [[ ${RET_VAL} == *"MobileNetV1 image classifier (quantized)"* ]]; then
+    echo "Unexpected return value: ${RET_VAL}"
+    echo "PIP smoke test on virtualenv FAILED, do not upload ${WHL_NAME}."
+    return 1
+  fi
+
+  RESULT=$?
+
+  popd
+  return $RESULT
+}
+
+function test_codegen() {
+  TMP_DIR=$(mktemp -d)
+  pushd "${TMP_DIR}"
+
+  # test for basic import and metadata display.
+  tflite_codegen --model ${TEST_MODEL} --destination tmp
+  RESULT=$?
+
+  # just check if the model name is there.
+  if [[ ${RESULT} -ne 0 ]]; then
+    echo "Unexpected return value: ${RESULT}"
+    echo "PIP smoke test on virtualenv FAILED, do not upload ${WHL_NAME}."
+    return 1
+  fi
+
+  popd
+  return $RESULT
+}
+
+###########################################################################
+# Main
+###########################################################################
+if [[ -z "${1}" ]]; then
+  echo "TFLite Support WHL path not given, unable to install and test."
+  return 1
+fi
+
+which python
+python --version
+
+WHL_NAME=${1}
+run_smoke_test
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat
index 35f39a7..702fb89f 100755
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/common_win.bat
@@ -22,7 +22,7 @@
 @REM Setup Bazel
 @REM
 :: Download Bazel from github and make sure its found in PATH.
-SET BAZEL_VERSION=3.1.0
+SET BAZEL_VERSION=3.7.2
 md C:\tools\bazel\
 wget -q https://github.com/bazelbuild/bazel/releases/download/%BAZEL_VERSION%/bazel-%BAZEL_VERSION%-windows-x86_64.exe -O C:/tools/bazel/bazel.exe
 SET PATH=C:\tools\bazel;%PATH%
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/update_version.py b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/update_version.py
new file mode 100644
index 0000000..86fa588
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/ci_build/update_version.py
@@ -0,0 +1,120 @@
+# lint as: python3
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License..
+# ==============================================================================
+"""Update version code in the repo.
+
+We use a python script rather than GNU tools to avoid cross-platform
+difficulties.
+
+The script takes 3 argument:
+ --src <path> a path pointing to the code repo.
+ --version <version> the new version code.
+ --nightly [default: false] when true, the version code will append a build
+   suffix (e.g. dev20201103)
+
+It should not run by bazel. Use it as a simple python script.
+"""
+
+import argparse
+import datetime
+import os
+import re
+
+SETUP_PY_PATH = "tensorflow_lite_support/tools/pip_package/setup.py"
+
+
+def replace_string_in_line(search, replace, filename):
+  """Replace the string in every line of the file in-place."""
+  with open(filename, "r") as f:
+    content = f.read()
+  with open(filename, "w") as f:
+    f.write(re.sub(search, replace, content))
+
+
+def get_current_version(path):
+  """Get the current version code from setup.py."""
+  for line in open(os.path.join(path, SETUP_PY_PATH)):
+    match = re.search("^_VERSION = '([a-z0-9\\.\\-]+)'", line)
+    if match:
+      return match.group(1)
+  print("Cannot find current version!")
+  return None
+
+
+def update_version(path, current_version, new_version):
+  """Update the version code in the codebase."""
+  # Update setup.py
+  replace_string_in_line(
+      "_VERSION = '%s'" % current_version,
+      # pep440 requires such a replacement
+      "_VERSION = '%s'" % new_version.replace("-", "."),
+      os.path.join(path, SETUP_PY_PATH))
+
+
+class CustomTimeZone(datetime.tzinfo):
+
+  def utcoffset(self, dt):
+    return -datetime.timedelta(hours=8)
+
+  def tzname(self, dt):
+    return "UTC-8"
+
+  def dst(self, dt):
+    return datetime.timedelta(0)
+
+
+def remove_build_suffix(version):
+  """Remove build suffix (if exists) from a version."""
+  if version.find("-dev") >= 0:
+    return version[:version.find("-dev")]
+  if version.find(".dev") >= 0:
+    return version[:version.find(".dev")]
+  if version.find("dev") >= 0:
+    return version[:version.find("dev")]
+  return version
+
+
+def main():
+  parser = argparse.ArgumentParser(description="Update TFLS version in repo")
+  parser.add_argument(
+      "--src",
+      help="a path pointing to the code repo",
+      required=True,
+      default="")
+  parser.add_argument("--version", help="the new SemVer code", default="")
+  parser.add_argument(
+      "--nightly",
+      help="if true, a build suffix will append to the version code. If "
+      "current version code or the <version> argument provided contains a "
+      "build suffix, the suffix will be replaced with the timestamp",
+      action="store_true")
+  args = parser.parse_args()
+
+  path = args.src
+  current_version = get_current_version(path)
+  if not current_version:
+    return
+  new_version = args.version if args.version else current_version
+  if args.nightly:
+    new_version = remove_build_suffix(new_version)
+    # Use UTC-8 rather than uncertain local time.
+    d = datetime.datetime.now(tz=CustomTimeZone())
+    new_version += "-dev" + d.strftime("%Y%m%d")
+  print("Updating version from %s to %s" % (current_version, new_version))
+  update_version(path, current_version, new_version)
+
+
+if __name__ == "__main__":
+  main()
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/BUILD b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/BUILD
index 61df24a..4341e34 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/BUILD
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/BUILD
@@ -12,6 +12,13 @@
     "setup.py",
     "//tensorflow_lite_support/codegen/python:codegen",
     "//tensorflow_lite_support/metadata/python:metadata",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:writer_utils",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:metadata_info",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:image_classifier",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:object_detector",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:image_segmenter",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:audio_classifier",
+    "//tensorflow_lite_support/metadata/python/metadata_writers:nl_classifier",
 ]
 
 filegroup(
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/build_pip_package.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/build_pip_package.sh
index 66c05b4..d27c392 100755
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/build_pip_package.sh
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/build_pip_package.sh
@@ -92,6 +92,8 @@
   # A helper entry.
   mkdir ${TMPDIR}/tflite_support
   cp tensorflow_lite_support/tools/pip_package/tflite_support.__init__.py ${TMPDIR}/tflite_support/__init__.py
+  mkdir ${TMPDIR}/tflite_support/metadata_writers
+  cp tensorflow_lite_support/tools/pip_package/metadata_writers.__init__.py ${TMPDIR}/tflite_support/metadata_writers/__init__.py
 }
 
 function build_wheel() {
@@ -133,8 +135,9 @@
   echo "                              if dstdir is not set do not build, only prepare sources"
   echo ""
   echo "  Options:"
-  echo "    --project_name <name> set project name to name"
-  echo "    --nightly_flag        build TFLite Support nightly"
+  echo "    --project_name <name>           set project name to <name>"
+  echo "    --version <version>             reset the pip package version to <version>"
+  echo "    --nightly_flag                  build TFLite Support nightly"
   echo ""
   echo "When using bazel, add the following flag: --run_under=\"cd \$PWD && \""
   echo ""
@@ -148,6 +151,7 @@
   SRCDIR=""
   DSTDIR=""
   CLEANSRC=1
+  VERSION=""
   while true; do
     if [[ "$1" == "--help" ]]; then
       usage
@@ -160,6 +164,12 @@
         break
       fi
       PROJECT_NAME="$1"
+    elif [[ "$1" == "--version" ]]; then
+      shift
+      if [[ -z "$1" ]]; then
+        break
+      fi
+      VERSION="$1"
     elif [[ "$1" == "--src" ]]; then
       shift
       SRCDIR="$(real_path $1)"
@@ -168,7 +178,9 @@
       shift
       DSTDIR="$(real_path $1)"
     else
-      DSTDIR="$(real_path $1)"
+      echo "Unrecognized flag: $1"
+      usage
+      exit 1
     fi
     shift
 
@@ -188,8 +200,6 @@
     SRCDIR="$(mktemp -d -t tmp.XXXXXXXXXX)"
   fi
 
-  prepare_src "$SRCDIR"
-
   if [[ -z "$DSTDIR" ]]; then
       # only want to prepare sources
       exit
@@ -201,6 +211,24 @@
     PKG_NAME_FLAG="--project_name tflite_support_nightly"
   fi
 
+  # Set additional package name flags (for ARM builds).
+  if [[ -n ${EXTRA_PKG_NAME_FLAG} ]]; then
+      PKG_NAME_FLAG="${PKG_NAME_FLAG} ${EXTRA_PKG_NAME_FLAG}"
+  fi
+
+  if [[ ${NIGHTLY_BUILD} == "1" ]]; then
+    # we use a script to update versions to avoid any tool differences on different platforms.
+    if [[ ! -z ${VERSION} ]]; then
+      python tensorflow_lite_support/tools/ci_build/update_version.py --src "." --version ${VERSION} --nightly
+    else
+      python tensorflow_lite_support/tools/ci_build/update_version.py --src "." --nightly
+    fi
+  elif [[ ! -z ${VERSION} ]]; then
+    python tensorflow_lite_support/tools/ci_build/update_version.py --src "." --version ${VERSION}
+  fi
+
+  prepare_src "$SRCDIR"
+
   build_wheel "$SRCDIR" "$DSTDIR" "$PKG_NAME_FLAG"
 
   if [[ $CLEANSRC -ne 0 ]]; then
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/metadata_writers.__init__.py b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/metadata_writers.__init__.py
new file mode 100644
index 0000000..83336a7
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/metadata_writers.__init__.py
@@ -0,0 +1,23 @@
+# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""An import entry for the metadata writers library."""
+
+from tensorflow_lite_support.metadata.python.metadata_writers import audio_classifier
+from tensorflow_lite_support.metadata.python.metadata_writers import image_classifier
+from tensorflow_lite_support.metadata.python.metadata_writers import image_segmenter
+from tensorflow_lite_support.metadata.python.metadata_writers import metadata_info
+from tensorflow_lite_support.metadata.python.metadata_writers import nl_classifier
+from tensorflow_lite_support.metadata.python.metadata_writers import object_detector
+from tensorflow_lite_support.metadata.python.metadata_writers import writer_utils
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/Dockerfile.py3 b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/Dockerfile.py3
new file mode 100644
index 0000000..74ed5d9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/Dockerfile.py3
@@ -0,0 +1,60 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+ARG IMAGE
+FROM ${IMAGE}
+ARG PYTHON_VERSION
+
+COPY update_sources.sh /
+RUN /update_sources.sh
+
+RUN apt-get update && \
+    apt-get install -y \
+      build-essential \
+      software-properties-common \
+      zlib1g-dev  \
+      curl \
+      unzip \
+      git && \
+    apt-get clean
+
+# Install Python packages.
+RUN dpkg --add-architecture armhf
+RUN dpkg --add-architecture arm64
+RUN yes | add-apt-repository ppa:deadsnakes/ppa
+RUN apt-get update && \
+    apt-get install -y \
+      python$PYTHON_VERSION \
+      python$PYTHON_VERSION-dev \
+      python$PYTHON_VERSION-distutils \
+      libpython$PYTHON_VERSION-dev \
+      libpython$PYTHON_VERSION-dev:armhf \
+      libpython$PYTHON_VERSION-dev:arm64
+RUN ln -sf /usr/bin/python$PYTHON_VERSION /usr/bin/python3
+RUN curl -OL https://bootstrap.pypa.io/get-pip.py
+RUN python3 get-pip.py
+RUN rm get-pip.py
+RUN pip3 install --upgrade pip
+RUN pip3 install numpy~=1.19.2 setuptools pybind11
+RUN ln -sf /usr/include/python$PYTHON_VERSION /usr/include/python3
+RUN ln -sf /usr/local/lib/python$PYTHON_VERSION/dist-packages/numpy/core/include/numpy /usr/include/python3/numpy
+RUN ln -sf /usr/bin/python3 /usr/bin/python
+
+ENV CI_BUILD_PYTHON=python$PYTHON_VERSION
+ENV CROSSTOOL_PYTHON_INCLUDE_PATH=/usr/include/python$PYTHON_VERSION
+
+COPY install_bazel.sh /
+RUN /install_bazel.sh
+
+COPY with_the_same_user /
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/Makefile b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/Makefile
new file mode 100644
index 0000000..31d600b
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/Makefile
@@ -0,0 +1,63 @@
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Values: debian:<version>, ubuntu:<version>
+BASE_IMAGE ?= ubuntu:16.04
+PYTHON_VERSION ?= 3.9
+
+MAKEFILE_DIR := $(realpath $(dir $(lastword $(MAKEFILE_LIST))))
+WORKSPACE_DIR := $(MAKEFILE_DIR)/../../../..
+TAG_IMAGE := "tflite-runtime-builder-$(subst :,-,$(BASE_IMAGE))"
+
+DOCKER_PARAMS := --pid=host \
+    --env "CI_BUILD_USER=$(shell id -u -n)" \
+    --env "CI_BUILD_UID=$(shell id -u)" \
+    --env "CI_BUILD_GROUP=$(shell id -g -n)" \
+    --env "CI_BUILD_GID=$(shell id -g)" \
+		--env "CI_BUILD_HOME=$(WORKSPACE_DIR)/bazel-ci_build-cache" \
+		--volume $(WORKSPACE_DIR)/bazel-ci_build-cache:$(WORKSPACE_DIR)/bazel-ci-build-cache \
+		--volume $(WORKSPACE_DIR):/workspace \
+		--workdir /workspace
+
+.PHONY: help \
+        docker-image \
+        docker-shell \
+        docker-build \
+        clean
+
+help:
+	@echo "make docker-image -- build docker image"
+	@echo "make docker-shell -- run shell inside the docker image"
+	@echo "make docker-build -- build wheel and deb inside the docker image"
+	@echo "make clean        -- remove wheel and deb files"
+
+docker-image:
+	docker build -t $(TAG_IMAGE) --build-arg IMAGE=$(BASE_IMAGE) --build-arg PYTHON_VERSION=$(PYTHON_VERSION) -f $(MAKEFILE_DIR)/Dockerfile.py3 $(MAKEFILE_DIR)/.
+
+docker-shell: docker-image
+	mkdir -p $(WORKSPACE_DIR)/bazel-ci_build-cache
+	docker run --rm --interactive --tty \
+		$(DOCKER_PARAMS) \
+		$(TAG_IMAGE) /with_the_same_user /bin/bash
+
+docker-build: docker-image
+	mkdir -p $(WORKSPACE_DIR)/bazel-ci_build-cache
+	docker run \
+		--rm --interactive $(shell tty -s && echo --tty) \
+		$(DOCKER_PARAMS) \
+		$(TAG_IMAGE) \
+		/with_the_same_user /bin/bash -C tensorflow_lite_support/tools/pip_package/rpi/build_arm_pip_package.sh
+
+clean:
+	rm -rf $(CURDIR)/wheels
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/build_arm_pip_package.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/build_arm_pip_package.sh
new file mode 100755
index 0000000..9676de4
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/build_arm_pip_package.sh
@@ -0,0 +1,22 @@
+#!/usr/bin/env bash
+# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+set -ex
+
+bazel build -c opt --config=elinux_armhf tensorflow_lite_support/tools/pip_package:build_pip_package
+EXTRA_PKG_NAME_FLAG="--plat-name=manylinux2014-armv7l" ./bazel-bin/tensorflow_lite_support/tools/pip_package/build_pip_package --dst wheels --nightly_flag
+bazel build -c opt --config=elinux_aarch64 tensorflow_lite_support/tools/pip_package:build_pip_package
+EXTRA_PKG_NAME_FLAG="--plat-name=manylinux2014-aarch64" ./bazel-bin/tensorflow_lite_support/tools/pip_package/build_pip_package --dst wheels --nightly_flag
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/install_bazel.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/install_bazel.sh
new file mode 100755
index 0000000..063e1f9
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/install_bazel.sh
@@ -0,0 +1,40 @@
+#!/usr/bin/env bash
+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+# Select bazel version.
+BAZEL_VERSION="3.7.2"
+
+set +e
+local_bazel_ver=$(bazel version 2>&1 | grep -i label | awk '{print $3}')
+
+if [[ "$local_bazel_ver" == "$BAZEL_VERSION" ]]; then
+  exit 0
+fi
+
+set -e
+
+# Install bazel.
+mkdir -p /bazel
+cd /bazel
+if [[ ! -f "bazel-$BAZEL_VERSION-installer-linux-x86_64.sh" ]]; then
+  curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh
+fi
+chmod +x /bazel/bazel-*.sh
+/bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh
+rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh
+
+# Enable bazel auto completion.
+echo "source /usr/local/lib/bazel/bin/bazel-complete.bash" >> ~/.bashrc
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/update_sources.sh b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/update_sources.sh
new file mode 100755
index 0000000..40e3213
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/update_sources.sh
@@ -0,0 +1,28 @@
+#!/usr/bin/env bash
+# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+#!/bin/bash
+. /etc/os-release
+
+[[ "${NAME}" == "Ubuntu" ]] || exit 0
+
+sed -i "s/deb\ /deb \[arch=amd64\]\ /g" /etc/apt/sources.list
+
+cat <<EOT >> /etc/apt/sources.list
+deb [arch=arm64,armhf] http://ports.ubuntu.com/ubuntu-ports ${UBUNTU_CODENAME} main universe
+deb [arch=arm64,armhf] http://ports.ubuntu.com/ubuntu-ports ${UBUNTU_CODENAME}-updates main universe
+deb [arch=arm64,armhf] http://ports.ubuntu.com/ubuntu-ports ${UBUNTU_CODENAME}-security main universe
+EOT
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/with_the_same_user b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/with_the_same_user
new file mode 100755
index 0000000..0c8c5069
--- /dev/null
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/rpi/with_the_same_user
@@ -0,0 +1,65 @@
+#!/usr/bin/env bash
+# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+# This script is a wrapper creating the same user inside container as the one
+# running the ci_build.sh outside the container. It also set the home directory
+# for the user inside container to match the same absolute path as the workspace
+# outside of container.
+# We do this so that the bazel running inside container generate symbolic links
+# and user permissions which makes sense outside of container.
+# Do not run this manually. It does not make sense. It is intended to be called
+# by ci_build.sh only.
+
+set -e
+
+COMMAND=("$@")
+
+if ! touch /this_is_writable_file_system; then
+  echo "You can't write to your filesystem!"
+  echo "If you are in Docker you should check you do not have too many images" \
+      "with too many files in them. Docker has some issue with it."
+  exit 1
+else
+  rm /this_is_writable_file_system
+fi
+
+if [ -n "${CI_BUILD_USER_FORCE_BADNAME}" ]; then
+  ADDUSER_OPTS="--force-badname"
+fi
+
+apt-get install sudo
+
+getent group "${CI_BUILD_GID}" || addgroup ${ADDUSER_OPTS} --gid "${CI_BUILD_GID}" "${CI_BUILD_GROUP}"
+getent passwd "${CI_BUILD_UID}" || adduser ${ADDUSER_OPTS} \
+    --gid "${CI_BUILD_GID}" --uid "${CI_BUILD_UID}" \
+    --gecos "${CI_BUILD_USER} (generated by with_the_same_user script)" \
+    --disabled-password --home "${CI_BUILD_HOME}" --quiet "${CI_BUILD_USER}"
+usermod -a -G sudo "${CI_BUILD_USER}"
+echo "${CI_BUILD_USER} ALL=(ALL) NOPASSWD:ALL" > /etc/sudoers.d/90-nopasswd-sudo
+
+if [[ "${TF_NEED_ROCM}" -eq 1 ]]; then
+  # ROCm requires the video group in order to use the GPU for compute. If it
+  # exists on the host, add it to the container.
+  getent group video || addgroup video && adduser "${CI_BUILD_USER}" video
+fi
+
+if [ -e /root/.bazelrc ]; then
+  cp /root/.bazelrc "${CI_BUILD_HOME}/.bazelrc"
+  chown "${CI_BUILD_UID}:${CI_BUILD_GID}" "${CI_BUILD_HOME}/.bazelrc"
+fi
+
+sudo -u "#${CI_BUILD_UID}" --preserve-env "LD_LIBRARY_PATH=${LD_LIBRARY_PATH}" \
+"HOME=${CI_BUILD_HOME}" ${COMMAND[@]}
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/setup.py b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/setup.py
index 9b8d0ad..df97ebe7 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/setup.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/setup.py
@@ -43,16 +43,18 @@
 # This version string is semver compatible, but incompatible with pip.
 # For pip, we will remove all '-' characters from this string, and use the
 # result for pip.
-_VERSION = '0.1.0'
+_VERSION = '0.3.0'
 
 SETUP_PACKAGES = [
-    'pybind11 >= 2.4',
+    'pybind11 >= 2.6.0',
 ]
 
 REQUIRED_PACKAGES = [
     'absl-py >= 0.7.0',
-    'numpy >= 1.16.0',
-    'flatbuffers >= 1.12',
+    'numpy >= 1.19.2',
+    # TODO(b/187981032): remove the constraint for 2.0 once the incompatibile
+    # issue is resolved.
+    'flatbuffers >= 1.12, <2',
 ] + SETUP_PACKAGES
 
 project_name = 'tflite-support'
diff --git a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/tflite_support.__init__.py b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/tflite_support.__init__.py
index c5bf3de..da5c2d8 100644
--- a/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/tflite_support.__init__.py
+++ b/third_party/tflite_support/src/tensorflow_lite_support/tools/pip_package/tflite_support.__init__.py
@@ -26,3 +26,4 @@
 from tensorflow_lite_support.metadata import metadata_schema_py_generated
 from tensorflow_lite_support.metadata import schema_py_generated
 from tensorflow_lite_support.metadata.python import metadata
+from tflite_support import metadata_writers
diff --git a/third_party/tflite_support/src/third_party/com_google_absl_f863b622fe13612433fdf43f76547d5edda0c93001.diff b/third_party/tflite_support/src/third_party/com_google_absl_f863b622fe13612433fdf43f76547d5edda0c93001.diff
index 0cd2dff..5725c34 100644
--- a/third_party/tflite_support/src/third_party/com_google_absl_f863b622fe13612433fdf43f76547d5edda0c93001.diff
+++ b/third_party/tflite_support/src/third_party/com_google_absl_f863b622fe13612433fdf43f76547d5edda0c93001.diff
@@ -1,8 +1,8 @@
 diff --git a/absl/time/internal/cctz/BUILD.bazel b/absl/time/internal/cctz/BUILD.bazel
-index 9fceffe..e7f9d01 100644
+index 45a9529..461164d 100644
 --- a/absl/time/internal/cctz/BUILD.bazel
 +++ b/absl/time/internal/cctz/BUILD.bazel
-@@ -69,8 +69,5 @@ cc_library(
+@@ -75,9 +75,6 @@ cc_library(
          "include/cctz/zone_info_source.h",
      ],
      linkopts = select({
@@ -11,4 +11,4 @@
 -        ],
          ":ios": [
              "-framework Foundation",
-         ],
\ No newline at end of file
+         ],
diff --git a/third_party/tflite_support/src/third_party/com_google_protobuf_fixes.diff b/third_party/tflite_support/src/third_party/com_google_protobuf_fixes.diff
deleted file mode 100644
index b9bc17e..0000000
--- a/third_party/tflite_support/src/third_party/com_google_protobuf_fixes.diff
+++ /dev/null
@@ -1,140 +0,0 @@
-diff --git a/BUILD b/BUILD
-index 79871d621..51b3a063f 100644
---- a/BUILD
-+++ b/BUILD
-@@ -26,7 +26,7 @@ config_setting(
- # ZLIB configuration
- ################################################################################
-
--ZLIB_DEPS = ["@zlib//:zlib"]
-+ZLIB_DEPS = ["@zlib"]
-
- ################################################################################
- # Protobuf Runtime Library
-@@ -157,6 +157,7 @@ cc_library(
-     includes = ["src/"],
-     linkopts = LINK_OPTS,
-     visibility = ["//visibility:public"],
-+    alwayslink = 1,
- )
-
- PROTOBUF_DEPS = select({
-@@ -230,6 +231,7 @@ cc_library(
-     linkopts = LINK_OPTS,
-     visibility = ["//visibility:public"],
-     deps = [":protobuf_lite"] + PROTOBUF_DEPS,
-+    alwayslink = 1,
- )
-
- # This provides just the header files for use in projects that need to build
-@@ -318,13 +320,13 @@ cc_proto_library(
-
- [native_cc_proto_library(
-     name = proto + "_cc_proto",
--    deps = [proto + "_proto"],
-     visibility = ["//visibility:private"],
-+    deps = [proto + "_proto"],
- ) for proto in WELL_KNOWN_PROTO_MAP.keys()]
-
- cc_proto_blacklist_test(
-     name = "cc_proto_blacklist_test",
--    deps = [proto + "_cc_proto" for proto in WELL_KNOWN_PROTO_MAP.keys()]
-+    deps = [proto + "_cc_proto" for proto in WELL_KNOWN_PROTO_MAP.keys()],
- )
-
- ################################################################################
-@@ -900,7 +902,6 @@ py_proto_library(
-     py_extra_srcs = glob(["python/**/__init__.py"]),
-     py_libs = [
-         ":python_srcs",
--        "@six//:six",
-     ],
-     srcs_version = "PY2AND3",
-     visibility = ["//visibility:public"],
-@@ -1002,7 +1003,9 @@ cc_library(
- # Note: We use `native_proto_common` here because we depend on an implementation-detail of
- # `proto_lang_toolchain`, which may not be available on `proto_common`.
- reject_blacklisted_files = hasattr(native_proto_common, "proto_lang_toolchain_rejects_files_do_not_use_or_we_will_break_you_without_mercy")
-+
- cc_toolchain_blacklisted_protos = [proto + "_proto" for proto in WELL_KNOWN_PROTO_MAP.keys()] if reject_blacklisted_files else [":well_known_protos"]
-+
- proto_lang_toolchain(
-     name = "cc_toolchain",
-     blacklisted_protos = cc_toolchain_blacklisted_protos,
-diff --git a/protobuf.bzl b/protobuf.bzl
-index 829464d44..4ac23594b 100644
---- a/protobuf.bzl
-+++ b/protobuf.bzl
-@@ -87,6 +87,8 @@ def _proto_gen_impl(ctx):
-     for dep in ctx.attr.deps:
-         import_flags += dep.proto.import_flags
-         deps += dep.proto.deps
-+    import_flags = depset(import_flags).to_list()
-+    deps = depset(deps).to_list()
-
-     if not ctx.attr.gen_cc and not ctx.attr.gen_py and not ctx.executable.plugin:
-         return struct(
-diff --git a/src/google/protobuf/io/gzip_stream.h b/src/google/protobuf/io/gzip_stream.h
-index b1ce1d36c..d5d560ea7 100644
---- a/src/google/protobuf/io/gzip_stream.h
-+++ b/src/google/protobuf/io/gzip_stream.h
-@@ -47,10 +47,12 @@
- #include <google/protobuf/stubs/common.h>
- #include <google/protobuf/io/zero_copy_stream.h>
- #include <google/protobuf/port.h>
--#include <zlib.h>
--
- #include <google/protobuf/port_def.inc>
-
-+#if HAVE_ZLIB
-+#include <zlib.h>
-+#endif  // HAVE_ZLIB
-+
- namespace google {
- namespace protobuf {
- namespace io {
-@@ -76,8 +78,10 @@ class PROTOBUF_EXPORT GzipInputStream : public ZeroCopyInputStream {
-   virtual ~GzipInputStream();
-
-   // Return last error message or NULL if no error.
-+#if HAVE_ZLIB
-   inline const char* ZlibErrorMessage() const { return zcontext_.msg; }
-   inline int ZlibErrorCode() const { return zerror_; }
-+#endif  // HAVE_ZLIB
-
-   // implements ZeroCopyInputStream ----------------------------------
-   bool Next(const void** data, int* size);
-@@ -90,8 +94,10 @@ class PROTOBUF_EXPORT GzipInputStream : public ZeroCopyInputStream {
-
-   ZeroCopyInputStream* sub_stream_;
-
-+ #if HAVE_ZLIB
-   z_stream zcontext_;
-   int zerror_;
-+ #endif // HAVE_ZLIB
-
-   void* output_buffer_;
-   void* output_position_;
-@@ -142,9 +148,11 @@ class PROTOBUF_EXPORT GzipOutputStream : public ZeroCopyOutputStream {
-
-   virtual ~GzipOutputStream();
-
-+#if HAVE_ZLIB
-   // Return last error message or NULL if no error.
-   inline const char* ZlibErrorMessage() const { return zcontext_.msg; }
-   inline int ZlibErrorCode() const { return zerror_; }
-+#endif  // HAVE_ZLIB
-
-   // Flushes data written so far to zipped data in the underlying stream.
-   // It is the caller's responsibility to flush the underlying stream if
-@@ -177,8 +185,10 @@ class PROTOBUF_EXPORT GzipOutputStream : public ZeroCopyOutputStream {
-   void* sub_data_;
-   int sub_data_size_;
-
-+#if HAVE_ZLIB
-   z_stream zcontext_;
-   int zerror_;
-+#endif  //HAVE_ZLIB
-   void* input_buffer_;
-   size_t input_buffer_length_;
-
diff --git a/third_party/tflite_support/src/third_party/flatbuffers/BUILD.bazel b/third_party/tflite_support/src/third_party/flatbuffers/BUILD.bazel
index 1ee46f05..9bd6965 100644
--- a/third_party/tflite_support/src/third_party/flatbuffers/BUILD.bazel
+++ b/third_party/tflite_support/src/third_party/flatbuffers/BUILD.bazel
@@ -1,4 +1,5 @@
 load("@build_bazel_rules_android//android:rules.bzl", "android_library")
+load(":build_defs.bzl", "flatbuffer_py_strip_prefix_srcs")
 
 package(default_visibility = ["//visibility:public"])
 
@@ -102,8 +103,10 @@
     visibility = ["//visibility:public"],
 )
 
-filegroup(
-    name = "runtime_py_srcs",
+# Note: Don't include "flexbuffers.py" as it's not available in the latest
+# pip package (version 1.12.0) and causes failures in internal pip tests.
+flatbuffer_py_strip_prefix_srcs(
+    name = "flatbuffer_py_strip_prefix",
     srcs = [
         "python/flatbuffers/__init__.py",
         "python/flatbuffers/builder.py",
@@ -114,6 +117,21 @@
         "python/flatbuffers/table.py",
         "python/flatbuffers/util.py",
     ],
+    strip_prefix = "python/flatbuffers/",
+)
+
+filegroup(
+    name = "runtime_py_srcs",
+    srcs = [
+        "__init__.py",
+        "builder.py",
+        "compat.py",
+        "encode.py",
+        "number_types.py",
+        "packer.py",
+        "table.py",
+        "util.py",
+    ],
 )
 
 py_library(
diff --git a/third_party/tflite_support/src/third_party/flatbuffers/build_defs.bzl b/third_party/tflite_support/src/third_party/flatbuffers/build_defs.bzl
index 45ff816..2f1e8ce4 100644
--- a/third_party/tflite_support/src/third_party/flatbuffers/build_defs.bzl
+++ b/third_party/tflite_support/src/third_party/flatbuffers/build_defs.bzl
@@ -24,6 +24,7 @@
         out_prefix = "",
         includes = [],
         include_paths = [],
+        compatible_with = [],
         flatc_args = DEFAULT_FLATC_ARGS,
         reflection_name = "",
         reflection_visibility = None,
@@ -43,6 +44,8 @@
           single source targets. Usually is a directory name.
       includes: Optional, list of filegroups of schemas that the srcs depend on.
       include_paths: Optional, list of paths the includes files can be found in.
+      compatible_with: Optional, passed to genrule for environments this rule
+          can be built for.
       flatc_args: Optional, list of additional arguments to pass to flatc.
       reflection_name: Optional, if set this will generate the flatbuffer
         reflection binaries for the schemas.
@@ -72,6 +75,7 @@
         srcs = srcs,
         outs = outs,
         output_to_bindir = output_to_bindir,
+        compatible_with = compatible_with,
         tools = includes + [flatc_path],
         cmd = genrule_cmd,
         message = "Generating flatbuffer files for %s:" % (name),
@@ -97,6 +101,7 @@
             srcs = srcs,
             outs = reflection_outs,
             output_to_bindir = output_to_bindir,
+            compatible_with = compatible_with,
             tools = includes + [flatc_path],
             cmd = reflection_genrule_cmd,
             message = "Generating flatbuffer reflection binary for %s:" % (name),
@@ -111,6 +116,7 @@
         #         native.FilesetEntry(files = reflection_outs),
         #     ],
         #     visibility = reflection_visibility,
+        #     compatible_with = compatible_with,
         # )
 
 def flatbuffer_cc_library(
@@ -120,6 +126,7 @@
         out_prefix = "",
         includes = [],
         include_paths = [],
+        compatible_with = [],
         flatc_args = DEFAULT_FLATC_ARGS,
         visibility = None,
         srcs_filegroup_visibility = None,
@@ -175,6 +182,8 @@
       includes: Optional, list of filegroups of schemas that the srcs depend on.
           ** SEE REMARKS BELOW **
       include_paths: Optional, list of paths the includes files can be found in.
+      compatible_with: Optional, passed to genrule for environments this rule
+          can be built for
       flatc_args: Optional list of additional arguments to pass to flatc
           (e.g. --gen-mutable).
       visibility: The visibility of the generated cc_library. By default, use the
@@ -198,6 +207,7 @@
         out_prefix = out_prefix,
         includes = includes,
         include_paths = include_paths,
+        compatible_with = compatible_with,
         flatc_args = flatc_args,
         reflection_name = reflection_name,
         reflection_visibility = visibility,
@@ -215,6 +225,7 @@
         includes = ["."],
         linkstatic = 1,
         visibility = visibility,
+        compatible_with = compatible_with,
     )
 
     # A filegroup for the `srcs`. That is, all the schema files for this
@@ -223,6 +234,7 @@
         name = srcs_filegroup_name if srcs_filegroup_name else "%s_includes" % (name),
         srcs = srcs,
         visibility = srcs_filegroup_visibility if srcs_filegroup_visibility != None else visibility,
+        compatible_with = compatible_with,
     )
 
 # Custom provider to track dependencies transitively.
@@ -349,18 +361,37 @@
     output_to_genfiles = True,
 )
 
+def flatbuffer_py_strip_prefix_srcs(name, srcs = [], strip_prefix = ""):
+    """Strips path prefix.
+
+    Args:
+      name: Rule name. (required)
+      srcs: Source .py files. (required)
+      strip_prefix: Path that needs to be stripped from the srcs filepaths. (required)
+    """
+    for src in srcs:
+        native.genrule(
+            name = name + "_" + src.replace(".", "_").replace("/", "_"),
+            srcs = [src],
+            outs = [src.replace(strip_prefix, "")],
+            cmd = "cp $< $@",
+        )
+
 def _concat_flatbuffer_py_srcs_impl(ctx):
     # Merge all generated python files. The files are concatenated and the
     # import statements are removed. Finally we import the flatbuffer runtime
     # library.
-    command = "for f in $(find %s -name '*.py'); do cat $f | sed '/import flatbuffers/d' >> %s; done; "
-    command += "sed -i '1s/^/import flatbuffers\\'$'\\n/' %s"
+    # IMPORTANT: Our Windows shell does not support "find ... -exec" properly.
+    # If changing the commandline here, please build wheels and run smoke tests
+    # on all the three operation systems.
+    command = "echo 'import flatbuffers\n' > %s; "
+    command += "for f in $(find %s -name '*.py'); do cat $f | sed '/import flatbuffers/d' >> %s; done "
     ctx.actions.run_shell(
         inputs = ctx.attr.deps[0].files,
         outputs = [ctx.outputs.out],
         command = command % (
-            ctx.attr.deps[0].files.to_list()[0].path,
             ctx.outputs.out.path,
+            ctx.attr.deps[0].files.to_list()[0].path,
             ctx.outputs.out.path,
         ),
     )
diff --git a/third_party/tflite_support/src/third_party/libzip.BUILD b/third_party/tflite_support/src/third_party/libzip.BUILD
index b69ccf4..2f75f40 100644
--- a/third_party/tflite_support/src/third_party/libzip.BUILD
+++ b/third_party/tflite_support/src/third_party/libzip.BUILD
@@ -2,7 +2,7 @@
     default_visibility = ["//visibility:public"],
 )
 
-load("@org_tensorflow_lite_support//tensorflow_lite_support/tools:build_rules/expand_template.bzl", "cmake_substitutions", "expand_template")
+load("@org_tensorflow_lite_support//tensorflow_lite_support/tools/build_rules:expand_template.bzl", "cmake_substitutions", "expand_template")
 
 _CMAKE_VARIABLES = {
     "INT16_T_LIBZIP": 2,
@@ -34,12 +34,12 @@
 _CMAKE_VARIABLES.update(dict([
     (
         "ZIP_{sign}INT{size}_T".format(
-            sign = sign.upper(),
             size = size,
+            sign = sign.upper(),
         ),
         "{sign}int{size}_t".format(
-            sign = sign.lower(),
             size = size,
+            sign = sign.lower(),
         ),
     )
     for sign in ("U", "")
@@ -130,12 +130,12 @@
 _VARS.update(dict([
     (
         "ZIP_{sign}INT{size}_T".format(
-            sign = sign.upper(),
             size = size,
+            sign = sign.upper(),
         ),
         "{sign}int{size}_t".format(
-            sign = sign.lower(),
             size = size,
+            sign = sign.lower(),
         ),
     )
     for sign in ("U", "")
diff --git a/third_party/tflite_support/src/third_party/tensorflow_lite_ios_build.patch b/third_party/tflite_support/src/third_party/tensorflow_lite_ios_build.patch
index e5d3128fc..2edf08b 100644
--- a/third_party/tflite_support/src/third_party/tensorflow_lite_ios_build.patch
+++ b/third_party/tflite_support/src/third_party/tensorflow_lite_ios_build.patch
@@ -1,37 +1,4 @@
-diff --git a/tensorflow/lite/experimental/ios/BUILD.apple b/tensorflow/lite/experimental/ios/BUILD
-similarity index 99%
-rename from tensorflow/lite/experimental/ios/BUILD.apple
-rename to tensorflow/lite/experimental/ios/BUILD
-index e1e3be2bcd..912d27702b 100644
---- a/tensorflow/lite/experimental/ios/BUILD.apple
-+++ b/tensorflow/lite/experimental/ios/BUILD
-@@ -21,6 +21,7 @@ sh_binary(
-     srcs = [
-         "hide_symbols_with_allowlist.sh",
-     ],
-+    visibility = ["//visibility:public"],
- )
- 
- strip_common_include_path_prefix(
-diff --git a/tensorflow/lite/experimental/ios/ios.bzl b/tensorflow/lite/experimental/ios/ios.bzl
-index 63747eb8d1..07bcb49de0 100644
---- a/tensorflow/lite/experimental/ios/ios.bzl
-+++ b/tensorflow/lite/experimental/ios/ios.bzl
-@@ -60,7 +60,7 @@ def tflite_ios_static_framework(
-            "BUNDLE_NAME=\"" + bundle_name + "\" " +
-            "ALLOWLIST_FILE_PATH=\"$(location " + allowlist_symbols_file + ")\" " +
-            "OUTPUT=\"$(OUTS)\" " +
--           "\"$(location //tensorflow/lite/experimental/ios:hide_symbols_with_allowlist)\"")
-+           "\"$(location @org_tensorflow//tensorflow/lite/experimental/ios:hide_symbols_with_allowlist)\"")
- 
-     native.genrule(
-         name = name,
-@@ -68,7 +68,7 @@ def tflite_ios_static_framework(
-         outs = [name + ".zip"],
-         cmd = cmd,
-         tools = [
--            "//tensorflow/lite/experimental/ios:hide_symbols_with_allowlist",
-+            "@org_tensorflow//tensorflow/lite/experimental/ios:hide_symbols_with_allowlist",
-         ],
-     )
- 
+diff --git a/tensorflow/lite/ios/BUILD.apple b/tensorflow/lite/ios/BUILD
+similarity index 100%
+rename from tensorflow/lite/ios/BUILD.apple
+rename to tensorflow/lite/ios/BUILD
diff --git a/third_party/tflite_support/src/third_party/zlib.BUILD b/third_party/tflite_support/src/third_party/zlib.BUILD
index 275782e..3a93488 100644
--- a/third_party/tflite_support/src/third_party/zlib.BUILD
+++ b/third_party/tflite_support/src/third_party/zlib.BUILD
@@ -37,3 +37,30 @@
     copts = ["-Wno-implicit-function-declaration"],
     includes = ["."],
 )
+
+cc_library(
+    name = "zlib_minizip",
+    srcs = [
+        "contrib/minizip/ioapi.c",
+        "contrib/minizip/miniunz.c",
+        "contrib/minizip/minizip.c",
+        "contrib/minizip/unzip.c",
+        "contrib/minizip/zip.c",
+    ],
+    hdrs = [
+        "contrib/minizip/crypt.h",
+        "contrib/minizip/ioapi.h",
+        "contrib/minizip/mztools.h",
+        "contrib/minizip/unzip.h",
+        "contrib/minizip/zip.h",
+    ],
+    copts = [
+        "-Wno-dangling-else",
+        "-Wno-format",
+        "-Wno-incompatible-pointer-types",
+        "-Wno-incompatible-pointer-types-discards-qualifiers",
+        "-Wno-parentheses",
+        "-DIOAPI_NO_64",
+    ],
+    deps = [":zlib"],
+)
diff --git a/tools/android/checkxmlstyle/checkxmlstyle.py b/tools/android/checkxmlstyle/checkxmlstyle.py
index 44c46e5..3d3fb35 100644
--- a/tools/android/checkxmlstyle/checkxmlstyle.py
+++ b/tools/android/checkxmlstyle/checkxmlstyle.py
@@ -310,7 +310,13 @@
   namespace = {'android': 'http://schemas.android.com/apk/res/android'}
   errors = []
   for f in IncludedFiles(input_api):
-    root = ET.fromstring(input_api.ReadFile(f))
+    try:
+      root = ET.fromstring(input_api.ReadFile(f))
+    except ET.ParseError:
+      print('*' * 80)
+      print('Parse error processing file:', f)
+      print('*' * 80)
+      raise
     # Check if there are text attributes defined outside text appearances.
     for attribute in text_attributes:
       # Get style name that contains text attributes but is not text appearance.
diff --git a/tools/binary_size/libsupersize/archive.py b/tools/binary_size/libsupersize/archive.py
index 417bb39e..1ed215c9 100644
--- a/tools/binary_size/libsupersize/archive.py
+++ b/tools/binary_size/libsupersize/archive.py
@@ -47,14 +47,6 @@
 import zip_util
 
 
-# Holds computation state that is live only when an output directory exists.
-_OutputDirectoryContext = collections.namedtuple('_OutputDirectoryContext', [
-    'elf_object_paths',  # Only when elf_path is also provided.
-    'known_inputs',  # Only when elf_path is also provided.
-    'output_directory',
-    'thin_archives',
-])
-
 # When ensuring matching section sizes between .elf and .map files, these
 # sections should be ignored. When lld creates a combined library with
 # partitions, some sections (like .text) exist in each partition, but the ones
@@ -79,16 +71,34 @@
 _MAX_SAME_NAME_ALIAS_COUNT = 40  # 50kb is basically negligible.
 
 
+# Holds computation state that is live only when an output directory exists.
+@dataclasses.dataclass
+class _OutputDirectoryContext:
+  elf_object_paths: list  # Non-None only when elf_path is.
+  known_inputs: list  # Non-None only when elf_path is.
+  output_directory: str
+  thin_archives: list
+
+
 @dataclasses.dataclass
 class NativeSpec:
   # One (or more) of apk_so_path, map_path, elf_path must be non-None.
   tool_prefix: str  # Never None.
+  # Path within the .apk of the .so file. Non-None only when apk_spec is.
   apk_so_path: str = None
   map_path: str = None
   elf_path: str = None  # Unstripped .so path.
-  linker_name: str = None
+  linker_name: str = None  # Requires map_path. Either 'gold' or 'lld'.
   track_string_literals: bool = True
 
+  @property
+  def algorithm(self):
+    if self.map_path:
+      return 'linker_map'
+    if self.elf_path:
+      return 'dwarf'
+    return 'sections'
+
 
 @dataclasses.dataclass
 class PakSpec:
@@ -700,13 +710,7 @@
         native_spec.tool_prefix)
     update_build_config(models.BUILD_CONFIG_TOOL_PREFIX, relative_tool_prefix)
 
-    if native_spec.map_path:
-      metadata[models.METADATA_ELF_ALGORITHM] = 'linker_map'
-    elif native_spec.elf_path:
-      metadata[models.METADATA_ELF_ALGORITHM] = 'dwarf'
-    else:
-      metadata[models.METADATA_ELF_ALGORITHM] = 'sections'
-
+    metadata[models.METADATA_ELF_ALGORITHM] = native_spec.algorithm
     if native_spec.linker_name:
       update_build_config(models.BUILD_CONFIG_LINKER_NAME,
                           native_spec.linker_name)
@@ -1029,69 +1033,6 @@
     return path
 
 
-def _ParseApkOtherSymbols(*, apk_spec, native_spec, section_ranges,
-                          resources_pathmap_path, metadata):
-  apk_so_path = native_spec and native_spec.apk_so_path
-  res_source_mapper = _ResourceSourceMapper(apk_spec.size_info_prefix,
-                                            apk_spec.path_defaults)
-  resource_deobfuscator = _ResourcePathDeobfuscator(resources_pathmap_path)
-  apk_symbols = []
-  dex_size = 0
-  zip_info_total = 0
-  zipalign_total = 0
-  with zipfile.ZipFile(apk_spec.apk_path) as z:
-    signing_block_size = zip_util.MeasureApkSignatureBlock(z)
-    for zip_info in z.infolist():
-      zip_info_total += zip_info.compress_size
-      # Account for zipalign overhead that exists in local file header.
-      zipalign_total += zip_util.ReadZipInfoExtraFieldLength(z, zip_info)
-      # Account for zipalign overhead that exists in central directory header.
-      # Happens when python aligns entries in apkbuilder.py, but does not
-      # exist when using Android's zipalign. E.g. for bundle .apks files.
-      zipalign_total += len(zip_info.extra)
-      # Skip files that we explicitly analyze: .so, .dex, and .pak.
-      if zip_info.filename == apk_so_path:
-        continue
-      if apk_spec.analyze_dex and zip_info.filename.endswith('.dex'):
-        dex_size += zip_info.file_size
-        continue
-      if zip_info.filename.endswith('.pak'):
-        continue
-
-      resource_filename = resource_deobfuscator.MaybeRemapPath(
-          zip_info.filename)
-      source_path = res_source_mapper.FindSourceForPath(resource_filename)
-      if source_path is None:
-        source_path = os.path.join(models.APK_PREFIX_PATH, resource_filename)
-      apk_symbols.append(
-          models.Symbol(
-              models.SECTION_OTHER,
-              zip_info.compress_size,
-              source_path=source_path,
-              full_name=resource_filename))  # Full name must disambiguate
-
-  # Store zipalign overhead and signing block size as metadata rather than an
-  # "Overhead:" symbol because they fluctuate in size, and would be a source of
-  # noise in symbol diffs if included as symbols (http://crbug.com/1130754).
-  # Might be even better if we had an option in Tiger Viewer to ignore certain
-  # symbols, but taking this as a short-cut for now.
-  metadata[models.METADATA_ZIPALIGN_OVERHEAD] = zipalign_total
-  metadata[models.METADATA_SIGNING_BLOCK_SIZE] = signing_block_size
-
-  # Overhead includes:
-  #  * Size of all local zip headers (minus zipalign padding).
-  #  * Size of central directory & end of central directory.
-  overhead_size = (os.path.getsize(apk_spec.apk_path) - zip_info_total -
-                   zipalign_total - signing_block_size)
-  assert overhead_size >= 0, 'Apk overhead must be non-negative'
-  zip_overhead_symbol = models.Symbol(
-      models.SECTION_OTHER, overhead_size, full_name='Overhead: APK file')
-  apk_symbols.append(zip_overhead_symbol)
-  _ExtendSectionRange(section_ranges, models.SECTION_OTHER,
-                      sum(s.size for s in apk_symbols))
-  return dex_size, apk_symbols
-
-
 def _CalculateElfOverhead(section_ranges, elf_path):
   if elf_path:
     section_sizes_total_without_bss = sum(
@@ -1192,98 +1133,85 @@
   return source_mapper, ninja_elf_object_paths
 
 
-def CreateContainerSymbols(*,
-                           container_name,
-                           metadata,
-                           apk_spec,
-                           pak_spec,
-                           native_spec,
-                           source_directory,
-                           output_directory=None,
-                           resources_pathmap_path=None,
-                           pak_id_map=None):
-  """Creates a Container (with sections sizes) and symbols for a SizeInfo.
+def _CreateNativeSymbols(*,
+                         metadata,
+                         apk_spec,
+                         native_spec,
+                         output_directory=None,
+                         pak_id_map=None):
+  """Creates native symbols for the given native_spec.
 
   Args:
-    container_name: Name for the created Container. May be '' if only one
-        Container exists.
     metadata: Metadata dict from CreateMetadata().
     apk_spec: Instance of ApkSpec, or None.
-    pak_spec: Instance of PakSpec, or None.
-    native_spec: Instance of NativeSpec, or None.
+    native_spec: Instance of NativeSpec.
     output_directory: Build output directory. If None, source_paths and symbol
         alias information will not be recorded.
-    source_directory: Path to source root.
-    resources_pathmap_path: Path to the pathmap file that maps original
-        resource paths to shortened resource paths.
-    pak_id_map: Instance of PakIdMap, or None.
+    pak_id_map: Instance of PakIdMap.
 
   Returns:
-    List of symbols.
+    A tuple of (section_ranges, raw_symbols).
   """
   apk_elf_result = None
-  if apk_spec and native_spec and native_spec.apk_so_path:
+  if apk_spec and native_spec.apk_so_path:
     # Extraction takes around 1 second, so do it in parallel.
     apk_elf_result = parallel.ForkAndCall(
         _ElfInfoFromApk,
         (apk_spec.apk_path, native_spec.apk_so_path, native_spec.tool_prefix))
 
+  raw_symbols = []
   ninja_source_mapper = None
   dwarf_source_mapper = None
   section_ranges = {}
-  raw_symbols = []
-  object_paths_by_name = None
-  if native_spec:
-    ninja_elf_object_paths = None
-    if output_directory and native_spec.map_path:
-      # Finds all objects passed to the linker and creates a map of .o -> .cc.
-      ninja_source_mapper, ninja_elf_object_paths = _ParseNinjaFiles(
-          output_directory, native_spec.elf_path)
-    elif native_spec.elf_path:
-      logging.info('Parsing source path info via dwarfdump')
-      dwarf_source_mapper = dwarfdump.CreateAddressSourceMapper(
-          native_spec.elf_path, native_spec.tool_prefix)
-      logging.info('Found %d source paths across %s ranges',
-                   dwarf_source_mapper.NumberOfPaths(),
-                   dwarf_source_mapper.num_ranges)
+  ninja_elf_object_paths = None
+  if output_directory and native_spec.map_path:
+    # Finds all objects passed to the linker and creates a map of .o -> .cc.
+    ninja_source_mapper, ninja_elf_object_paths = _ParseNinjaFiles(
+        output_directory, native_spec.elf_path)
+  elif native_spec.elf_path:
+    logging.info('Parsing source path info via dwarfdump')
+    dwarf_source_mapper = dwarfdump.CreateAddressSourceMapper(
+        native_spec.elf_path, native_spec.tool_prefix)
+    logging.info('Found %d source paths across %s ranges',
+                 dwarf_source_mapper.NumberOfPaths(),
+                 dwarf_source_mapper.num_ranges)
 
-    # Start by finding elf_object_paths so that nm can run on them while the
-    # linker .map is being parsed.
-    if ninja_elf_object_paths:
-      elf_object_paths, thin_archives = ar.ExpandThinArchives(
-          ninja_elf_object_paths, output_directory)
-      known_inputs = set(elf_object_paths)
-      known_inputs.update(ninja_elf_object_paths)
+  # Start by finding elf_object_paths so that nm can run on them while the
+  # linker .map is being parsed.
+  if ninja_elf_object_paths:
+    elf_object_paths, thin_archives = ar.ExpandThinArchives(
+        ninja_elf_object_paths, output_directory)
+    known_inputs = set(elf_object_paths)
+    known_inputs.update(ninja_elf_object_paths)
+  else:
+    elf_object_paths = []
+    known_inputs = None
+    # When we don't know which elf file is used, just search all paths.
+    # TODO(agrieve): Seems to be used only for tests. Remove?
+    if ninja_source_mapper:
+      thin_archives = set(
+          p for p in ninja_source_mapper.IterAllPaths() if p.endswith('.a')
+          and ar.IsThinArchive(os.path.join(output_directory, p)))
     else:
-      elf_object_paths = []
-      known_inputs = None
-      # When we don't know which elf file is used, just search all paths.
-      # TODO(agrieve): Seems to be used only for tests. Remove?
-      if ninja_source_mapper:
-        thin_archives = set(
-            p for p in ninja_source_mapper.IterAllPaths() if p.endswith('.a')
-            and ar.IsThinArchive(os.path.join(output_directory, p)))
-      else:
-        thin_archives = None
+      thin_archives = None
 
-    outdir_context = None
-    if output_directory:
-      outdir_context = _OutputDirectoryContext(
-          elf_object_paths=elf_object_paths,
-          known_inputs=known_inputs,
-          output_directory=output_directory,
-          thin_archives=thin_archives)
+  outdir_context = None
+  if output_directory:
+    outdir_context = _OutputDirectoryContext(elf_object_paths=elf_object_paths,
+                                             known_inputs=known_inputs,
+                                             output_directory=output_directory,
+                                             thin_archives=thin_archives)
 
-    if native_spec.elf_path or native_spec.map_path:
-      section_ranges, raw_symbols, object_paths_by_name = _ParseElfInfo(
-          native_spec, outdir_context=outdir_context)
-
-      if pak_id_map and native_spec.map_path:
-        # For trichrome, pak files are in different apks than native library,
-        # so need to pass along pak_id_map separately and ensure
-        # TrichromeLibrary appears first in .ssargs file.
-        logging.debug('Extracting pak IDs from symbol names')
-        pak_id_map.Update(object_paths_by_name, ninja_source_mapper)
+  object_paths_by_name = None
+  if native_spec.elf_path or native_spec.map_path:
+    section_ranges, raw_symbols, object_paths_by_name = _ParseElfInfo(
+        native_spec, outdir_context=outdir_context)
+    if pak_id_map and native_spec.map_path:
+      # For trichrome, pak files are in different apks than native library,
+      # so need to pass along pak_id_map separately and ensure
+      # TrichromeLibrary appears first in .ssargs file.
+      logging.debug('Extracting pak IDs from symbol names')
+      pak_id_map.Update(object_paths_by_name, ninja_source_mapper)
 
   if apk_elf_result:
     logging.debug('Extracting section sizes from .so within .apk')
@@ -1291,7 +1219,7 @@
     if metadata and models.METADATA_ELF_BUILD_ID in metadata:
       assert apk_build_id == metadata[models.METADATA_ELF_BUILD_ID], (
           'BuildID from apk_elf_result did not match')
-  elif native_spec and native_spec.elf_path:
+  elif native_spec.elf_path:
     # Strip ELF before capturing section information to avoid recording
     # debug sections.
     with tempfile.NamedTemporaryFile(
@@ -1303,79 +1231,16 @@
                                                   native_spec.tool_prefix)
       elf_overhead_size = _CalculateElfOverhead(section_ranges, f.name)
 
-  if native_spec:
-    raw_symbols, other_elf_symbols = _AddUnattributedSectionSymbols(
-        raw_symbols, section_ranges)
+  raw_symbols, other_elf_symbols = _AddUnattributedSectionSymbols(
+      raw_symbols, section_ranges)
 
-  other_symbols = []
-  if apk_spec and apk_spec.size_info_prefix:
-    # Can modify |section_ranges|.
-    dex_size, other_symbols = _ParseApkOtherSymbols(
-        apk_spec=apk_spec,
-        native_spec=native_spec,
-        section_ranges=section_ranges,
-        resources_pathmap_path=resources_pathmap_path,
-        metadata=metadata)
-
-    if apk_spec.analyze_dex:
-      logging.info('Analyzing Dex')
-      dex_symbols = apkanalyzer.CreateDexSymbols(apk_spec.apk_path,
-                                                 apk_spec.mapping_path,
-                                                 apk_spec.size_info_prefix)
-
-      # We can't meaningfully track section size of dex methods vs other, so
-      # just fake the size of dex methods as the sum of symbols, and make
-      # "dex other" responsible for any unattributed bytes.
-      dex_method_size = int(
-          round(
-              sum(s.pss for s in dex_symbols
-                  if s.section_name == models.SECTION_DEX_METHOD)))
-      section_ranges[models.SECTION_DEX_METHOD] = (0, dex_method_size)
-      section_ranges[models.SECTION_DEX] = (0, dex_size - dex_method_size)
-
-      dex_other_size = int(
-          round(
-              sum(s.pss for s in dex_symbols
-                  if s.section_name == models.SECTION_DEX)))
-      unattributed_dex = section_ranges[models.SECTION_DEX][1] - dex_other_size
-      # Compare against -5 instead of 0 to guard against round-off errors.
-      assert unattributed_dex >= -5, ('Dex symbols take up more space than '
-                                      'the dex sections have available')
-      if unattributed_dex > 0:
-        dex_symbols.append(
-            models.Symbol(
-                models.SECTION_DEX,
-                unattributed_dex,
-                full_name='** .dex (unattributed - includes string literals)'))
-      raw_symbols.extend(dex_symbols)
-
-  if pak_spec:
-    logging.debug('Creating Pak symbols')
-    if pak_spec.apk_pak_paths:
-      assert apk_spec.size_info_prefix
-      # Can modify |section_ranges|.
-      raw_symbols += pakfile.CreatePakSymbolsFromApk(section_ranges,
-                                                     apk_spec.apk_path,
-                                                     pak_spec.apk_pak_paths,
-                                                     apk_spec.size_info_prefix,
-                                                     pak_id_map)
-    else:
-      # Can modify |section_ranges|.
-      raw_symbols += pakfile.CreatePakSymbolsFromFiles(section_ranges,
-                                                       pak_spec.pak_paths,
-                                                       pak_spec.pak_info_path,
-                                                       output_directory,
-                                                       pak_id_map)
-
-  if native_spec:
-    other_symbols.extend(other_elf_symbols)
-    if native_spec.elf_path:
-      elf_overhead_symbol = models.Symbol(models.SECTION_OTHER,
-                                          elf_overhead_size,
-                                          full_name='Overhead: ELF file')
-      _ExtendSectionRange(section_ranges, models.SECTION_OTHER,
-                          elf_overhead_size)
-      other_symbols.append(elf_overhead_symbol)
+  other_symbols = other_elf_symbols
+  if native_spec.elf_path:
+    elf_overhead_symbol = models.Symbol(models.SECTION_OTHER,
+                                        elf_overhead_size,
+                                        full_name='Overhead: ELF file')
+    _ExtendSectionRange(section_ranges, models.SECTION_OTHER, elf_overhead_size)
+    other_symbols.append(elf_overhead_symbol)
 
   # Always have .other come last.
   other_symbols.sort(key=lambda s: (s.IsOverhead(), s.full_name.startswith(
@@ -1386,20 +1251,226 @@
     _AddSourcePathsUsingObjectPaths(ninja_source_mapper, raw_symbols)
   elif dwarf_source_mapper:
     _AddSourcePathsUsingAddress(dwarf_source_mapper, raw_symbols)
+
+  # Path normalization must come before compacting aliases so that
+  # ancestor paths do not mix generated and non-generated paths.
   _NormalizePaths(raw_symbols)
 
+  logging.info('Converting excessive aliases into shared-path symbols')
+  _CompactLargeAliasesIntoSharedSymbols(raw_symbols)
+
+  if native_spec.elf_path or native_spec.map_path:
+    logging.debug('Connecting nm aliases')
+    _ConnectNmAliases(raw_symbols)
+
+  return section_ranges, raw_symbols
+
+
+def _CreatePakSymbols(*, pak_spec, pak_id_map, apk_spec, output_directory):
+  logging.debug('Creating Pak symbols')
+  section_ranges = {}
+  if apk_spec:
+    assert apk_spec.size_info_prefix
+    # Can modify |section_ranges|.
+    raw_symbols = pakfile.CreatePakSymbolsFromApk(section_ranges,
+                                                  apk_spec.apk_path,
+                                                  pak_spec.apk_pak_paths,
+                                                  apk_spec.size_info_prefix,
+                                                  pak_id_map)
+  else:
+    # Can modify |section_ranges|.
+    raw_symbols = pakfile.CreatePakSymbolsFromFiles(section_ranges,
+                                                    pak_spec.pak_paths,
+                                                    pak_spec.pak_info_path,
+                                                    output_directory,
+                                                    pak_id_map)
+  return section_ranges, raw_symbols
+
+
+def _CreateDexSymbols(*, apk_spec):
+  """Create dex symbols for the given apk_spec.
+
+  Args:
+    apk_spec: Instance of ApkSpec or None.
+
+  Returns:
+    A tuple of (section_ranges, raw_symbols).
+  """
+  logging.info('Analyzing classes.dex for %s', apk_spec.split_name
+               or apk_spec.apk_path)
+
+  def compute_dex_size():
+    with zipfile.ZipFile(apk_spec.apk_path) as z:
+      return sum(i.file_size for i in z.infolist()
+                 if i.filename.endswith('.dex'))
+
+  dex_size_result = parallel.CallOnThread(compute_dex_size)
+  raw_symbols = apkanalyzer.CreateDexSymbols(apk_spec.apk_path,
+                                             apk_spec.mapping_path,
+                                             apk_spec.size_info_prefix)
+  dex_size = dex_size_result.get()
+
+  sizes = collections.Counter()
+  for s in raw_symbols:
+    sizes[s.section_name] += s.pss
+  assert len(sizes) <= 2, 'Unexpected: ' + str(sizes)
+  dex_method_size = round(sizes[models.SECTION_DEX_METHOD])
+  dex_other_size = round(sizes[models.SECTION_DEX])
+
+  unattributed_dex = dex_size - dex_method_size - dex_other_size
+  # Compare against -5 instead of 0 to guard against round-off errors.
+  assert unattributed_dex >= -5, (
+      'sum(dex_symbols.size) > filesize(classes.dex). {} vs {}'.format(
+          dex_method_size + dex_other_size, dex_size))
+
+  if unattributed_dex > 0:
+    raw_symbols.append(
+        models.Symbol(
+            models.SECTION_DEX,
+            unattributed_dex,
+            full_name='** .dex (unattributed - includes string literals)'))
+
+  # We can't meaningfully track section size of dex methods vs other, so
+  # just fake the size of dex methods as the sum of symbols, and make
+  # "dex other" responsible for any unattributed bytes.
+  section_ranges = {
+      models.SECTION_DEX_METHOD: (0, dex_method_size),
+      models.SECTION_DEX: (0, dex_size - dex_method_size),
+  }
+
+  return section_ranges, raw_symbols
+
+
+def _CreateApkOtherSymbols(*,
+                           metadata,
+                           apk_spec,
+                           native_spec,
+                           resources_pathmap_path=None):
+  """Creates a Container (with sections sizes) and symbols for a SizeInfo.
+
+  Args:
+    metadata: Metadata dict from CreateMetadata().
+    apk_spec: Instance of ApkSpec or None.
+    native_spec: Instance of NativeSpec or None.
+    resources_pathmap_path: Path to the pathmap file that maps original
+        resource paths to shortened resource paths.
+
+  Returns:
+    A tuple of (section_ranges, raw_symbols).
+  """
+  logging.info('Creating symbols for other APK entries')
+  apk_so_path = native_spec and native_spec.apk_so_path
+  res_source_mapper = _ResourceSourceMapper(apk_spec.size_info_prefix,
+                                            apk_spec.path_defaults)
+  resource_deobfuscator = _ResourcePathDeobfuscator(resources_pathmap_path)
+  raw_symbols = []
+  zip_info_total = 0
+  zipalign_total = 0
+  with zipfile.ZipFile(apk_spec.apk_path) as z:
+    signing_block_size = zip_util.MeasureApkSignatureBlock(z)
+    for zip_info in z.infolist():
+      zip_info_total += zip_info.compress_size
+      # Account for zipalign overhead that exists in local file header.
+      zipalign_total += zip_util.ReadZipInfoExtraFieldLength(z, zip_info)
+      # Account for zipalign overhead that exists in central directory header.
+      # Happens when python aligns entries in apkbuilder.py, but does not
+      # exist when using Android's zipalign. E.g. for bundle .apks files.
+      zipalign_total += len(zip_info.extra)
+      # Skip files that we explicitly analyze: .so, .dex, and .pak.
+      if zip_info.filename == apk_so_path:
+        continue
+      if apk_spec.analyze_dex and zip_info.filename.endswith('.dex'):
+        continue
+      if zip_info.filename.endswith('.pak'):
+        continue
+
+      resource_filename = resource_deobfuscator.MaybeRemapPath(
+          zip_info.filename)
+      source_path = res_source_mapper.FindSourceForPath(resource_filename)
+      if source_path is None:
+        source_path = os.path.join(models.APK_PREFIX_PATH, resource_filename)
+      raw_symbols.append(
+          models.Symbol(
+              models.SECTION_OTHER,
+              zip_info.compress_size,
+              source_path=source_path,
+              full_name=resource_filename))  # Full name must disambiguate
+
+  # Store zipalign overhead and signing block size as metadata rather than an
+  # "Overhead:" symbol because they fluctuate in size, and would be a source of
+  # noise in symbol diffs if included as symbols (http://crbug.com/1130754).
+  # Might be even better if we had an option in Tiger Viewer to ignore certain
+  # symbols, but taking this as a short-cut for now.
+  metadata[models.METADATA_ZIPALIGN_OVERHEAD] = zipalign_total
+  metadata[models.METADATA_SIGNING_BLOCK_SIZE] = signing_block_size
+
+  # Overhead includes:
+  #  * Size of all local zip headers (minus zipalign padding).
+  #  * Size of central directory & end of central directory.
+  overhead_size = (os.path.getsize(apk_spec.apk_path) - zip_info_total -
+                   zipalign_total - signing_block_size)
+  assert overhead_size >= 0, 'Apk overhead must be non-negative'
+  zip_overhead_symbol = models.Symbol(models.SECTION_OTHER,
+                                      overhead_size,
+                                      full_name='Overhead: APK file')
+  raw_symbols.append(zip_overhead_symbol)
+
+  section_ranges = {}
+  _ExtendSectionRange(section_ranges, models.SECTION_OTHER,
+                      sum(s.size for s in raw_symbols))
+  return section_ranges, raw_symbols
+
+
+def CreateContainerSymbols(*, container_name, metadata, apk_spec, pak_spec,
+                           native_spec, source_directory, output_directory,
+                           resources_pathmap_path, pak_id_map):
+  raw_symbols = []
+  section_sizes = {}
+
+  def add_syms(section_ranges, new_raw_symbols):
+    new_section_sizes = {
+        k: size
+        for k, (address, size) in section_ranges.items()
+    }
+    if models.SECTION_OTHER in new_section_sizes:
+      section_sizes[models.SECTION_OTHER] = section_sizes.get(
+          models.SECTION_OTHER, 0) + new_section_sizes[models.SECTION_OTHER]
+      del new_section_sizes[models.SECTION_OTHER]
+
+    assert not (set(section_sizes) & set(new_section_sizes)), (
+        'Section collision: {}\n\n {}'.format(section_sizes, new_section_sizes))
+    section_sizes.update(new_section_sizes)
+
+    # _CreateNativeSymbols() already calls _NormalizePaths().
+    if new_raw_symbols and not new_raw_symbols[0].IsNative():
+      _NormalizePaths(new_raw_symbols)
+    raw_symbols.extend(new_raw_symbols)
+
+  if native_spec:
+    add_syms(*_CreateNativeSymbols(metadata=metadata,
+                                   apk_spec=apk_spec,
+                                   native_spec=native_spec,
+                                   output_directory=output_directory,
+                                   pak_id_map=pak_id_map))
+
+  if pak_spec:
+    add_syms(*_CreatePakSymbols(pak_spec=pak_spec,
+                                pak_id_map=pak_id_map,
+                                apk_spec=apk_spec,
+                                output_directory=output_directory))
+  if apk_spec:
+    if apk_spec.analyze_dex:
+      add_syms(*_CreateDexSymbols(apk_spec=apk_spec))
+    add_syms(
+        *_CreateApkOtherSymbols(metadata=metadata,
+                                apk_spec=apk_spec,
+                                native_spec=native_spec,
+                                resources_pathmap_path=resources_pathmap_path))
+
   default_component = apk_spec.default_component if apk_spec else ''
   dir_metadata.PopulateComponents(raw_symbols,
                                   source_directory,
                                   default_component=default_component)
-  logging.info('Converting excessive aliases into shared-path symbols')
-  _CompactLargeAliasesIntoSharedSymbols(raw_symbols)
-
-  if native_spec:
-    logging.debug('Connecting nm aliases')
-    _ConnectNmAliases(raw_symbols)
-
-  section_sizes = {k: size for k, (address, size) in section_ranges.items()}
   container = models.Container(name=container_name,
                                metadata=metadata,
                                section_sizes=section_sizes)
@@ -1828,6 +1899,8 @@
                                or top_args.output_directory)
   analyze_native = not (sub_args.java_only or sub_args.no_native
                         or top_args.java_only or top_args.no_native)
+  analyze_dex = not (sub_args.native_only or sub_args.no_java
+                     or top_args.native_only or top_args.no_java)
 
   apk_path = apk_path or sub_args.apk_file
   if split_name:
@@ -1856,8 +1929,7 @@
       apk_spec.size_info_prefix = os.path.join(top_args.output_directory,
                                                'size-info',
                                                os.path.basename(apk_prefix))
-    apk_spec.analyze_dex = not (sub_args.native_only or sub_args.no_java
-                                or top_args.native_only or top_args.no_java)
+    apk_spec.analyze_dex = bool(analyze_dex and apk_spec.size_info_prefix)
     apk_spec.path_defaults = {
         k: v['source_path']
         for k, v in json_config.get('apk_files', {}).items()
diff --git a/tools/binary_size/libsupersize/integration_test.py b/tools/binary_size/libsupersize/integration_test.py
index c90890f..50ec9b8 100755
--- a/tools/binary_size/libsupersize/integration_test.py
+++ b/tools/binary_size/libsupersize/integration_test.py
@@ -296,6 +296,7 @@
               native_spec=native_spec,
               source_directory=_TEST_SOURCE_DIR,
               output_directory=output_directory,
+              resources_pathmap_path=None,
               pak_id_map=pak_id_map)
           raw_symbols_list.append(raw_symbols)
 
diff --git a/tools/clang/plugins/CheckLayoutObjectMethodsVisitor.cpp b/tools/clang/plugins/CheckLayoutObjectMethodsVisitor.cpp
index caa5482..b360366 100644
--- a/tools/clang/plugins/CheckLayoutObjectMethodsVisitor.cpp
+++ b/tools/clang/plugins/CheckLayoutObjectMethodsVisitor.cpp
@@ -75,8 +75,9 @@
                 cxxRecordDecl(isSameOrDerivedFrom("::blink::LayoutObject"))),
             has(compoundStmt()),
             // Avoid matching the following cases
-            unless(anyOf(isConstexpr(), isDefaulted(), cxxConstructorDecl(),
-                         cxxDestructorDecl(), isStaticStorageClass(),
+            unless(anyOf(isConstexpr(), isDefaulted(), isPure(),
+                         cxxConstructorDecl(), cxxDestructorDecl(),
+                         isStaticStorageClass(),
                          // Do not trace lambdas (no name, possibly tracking
                          // more parameters than intended because of [&]).
                          hasParent(cxxRecordDecl(isLambda())),
@@ -95,12 +96,14 @@
     const auto* stmt = method->getBody();
     assert(stmt);
 
-    auto* stmts = llvm::dyn_cast<clang::CompoundStmt>(stmt)->body_front();
-    if (clang::CXXMemberCallExpr::classof(stmts)) {
-      auto* call = llvm::dyn_cast<clang::CXXMemberCallExpr>(stmts);
-      const std::string& name = call->getMethodDecl()->getNameAsString();
-      if (name == "CheckIsNotDestroyed")
-        return;
+    if (!llvm::dyn_cast<clang::CompoundStmt>(stmt)->body_empty()) {
+      auto* stmts = llvm::dyn_cast<clang::CompoundStmt>(stmt)->body_front();
+      if (clang::CXXMemberCallExpr::classof(stmts)) {
+        auto* call = llvm::dyn_cast<clang::CXXMemberCallExpr>(stmts);
+        const std::string& name = call->getMethodDecl()->getNameAsString();
+        if (name == "CheckIsNotDestroyed")
+          return;
+      }
     }
 
     auto* type = method->getParent();
diff --git a/tools/clang/plugins/tests/layout_object_methods.h b/tools/clang/plugins/tests/layout_object_methods.h
index cdaae5b..08239b5 100644
--- a/tools/clang/plugins/tests/layout_object_methods.h
+++ b/tools/clang/plugins/tests/layout_object_methods.h
@@ -15,7 +15,7 @@
  public:
   // These methods should be ignored.
   static void StaticMethod() {}
-  void CheckIsNotDestroyed() {}
+  void CheckIsNotDestroyed() const {}
   void Trace(Visitor*) const {}
 
   int ShouldPass1() {
@@ -28,19 +28,24 @@
     foo();
     return 0;
   }
+
+  virtual void VirtualEmptyMethod() = 0;
+  void EmptyMethod() {}
 };
 
 class LayoutBoxModelObject : public LayoutObject {
  public:
-  int ShouldPass2() {
+  int ShouldPass2() const {
     CheckIsNotDestroyed();
     return 0;
   }
-  int ShouldFail2() {
+  int ShouldFail2() const {
     ShouldPass2();
     CheckIsNotDestroyed();  // This should be the first statement.
     return 0;
   }
+
+  void VirtualEmptyMethod() override {}
 };
 
 class LayoutBox : public LayoutBoxModelObject {
@@ -54,6 +59,8 @@
     CheckIsNotDestroyed();  // This should be the first statement.
     return 0;
   }
+
+  void VirtualEmptyMethod() override {}
 };
 
 }  // namespace blink
diff --git a/tools/clang/plugins/tests/layout_object_methods.txt b/tools/clang/plugins/tests/layout_object_methods.txt
index 71e025a..a57e685 100644
--- a/tools/clang/plugins/tests/layout_object_methods.txt
+++ b/tools/clang/plugins/tests/layout_object_methods.txt
@@ -2,10 +2,19 @@
 ./layout_object_methods.h:26:3: warning: [layout] LayoutObject's method 'ShouldFail1' in 'LayoutObject' must call CheckIsNotDestroyed() at the beginning.
   int ShouldFail1() {
   ^~~~~~~~~~~~~~~~~~~
-./layout_object_methods.h:39:3: warning: [layout] LayoutObject's method 'ShouldFail2' in 'LayoutBoxModelObject' must call CheckIsNotDestroyed() at the beginning.
-  int ShouldFail2() {
-  ^~~~~~~~~~~~~~~~~~~
-./layout_object_methods.h:52:3: warning: [layout] LayoutObject's method 'ShouldFail3' in 'LayoutBox' must call CheckIsNotDestroyed() at the beginning.
+./layout_object_methods.h:33:3: warning: [layout] LayoutObject's method 'EmptyMethod' in 'LayoutObject' must call CheckIsNotDestroyed() at the beginning.
+  void EmptyMethod() {}
+  ^~~~~~~~~~~~~~~~~~~~~
+./layout_object_methods.h:42:3: warning: [layout] LayoutObject's method 'ShouldFail2' in 'LayoutBoxModelObject' must call CheckIsNotDestroyed() at the beginning.
+  int ShouldFail2() const {
+  ^~~~~~~~~~~~~~~~~~~~~~~~~
+./layout_object_methods.h:48:3: warning: [layout] LayoutObject's method 'VirtualEmptyMethod' in 'LayoutBoxModelObject' must call CheckIsNotDestroyed() at the beginning.
+  void VirtualEmptyMethod() override {}
+  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+./layout_object_methods.h:57:3: warning: [layout] LayoutObject's method 'ShouldFail3' in 'LayoutBox' must call CheckIsNotDestroyed() at the beginning.
   int ShouldFail3() {
   ^~~~~~~~~~~~~~~~~~~
-3 warnings generated.
+./layout_object_methods.h:63:3: warning: [layout] LayoutObject's method 'VirtualEmptyMethod' in 'LayoutBox' must call CheckIsNotDestroyed() at the beginning.
+  void VirtualEmptyMethod() override {}
+  ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+6 warnings generated.
diff --git a/tools/clang/scripts/update.py b/tools/clang/scripts/update.py
index 4b55f6f..23d0f00 100755
--- a/tools/clang/scripts/update.py
+++ b/tools/clang/scripts/update.py
@@ -35,7 +35,7 @@
 # Reverting problematic clang rolls is safe, though.
 # This is the output of `git describe` and is usable as a commit-ish.
 CLANG_REVISION = 'llvmorg-14-init-12719-gc4b45eeb'
-CLANG_SUB_REVISION = 2
+CLANG_SUB_REVISION = 3
 
 PACKAGE_VERSION = '%s-%s' % (CLANG_REVISION, CLANG_SUB_REVISION)
 RELEASE_VERSION = '14.0.0'
diff --git a/tools/gritsettings/resource_ids.spec b/tools/gritsettings/resource_ids.spec
index a552aea9..90c9af0 100644
--- a/tools/gritsettings/resource_ids.spec
+++ b/tools/gritsettings/resource_ids.spec
@@ -529,7 +529,7 @@
     "includes": [3320],
   },
   "<(SHARED_INTERMEDIATE_DIR)/ash/webui/personalization_app/resources/ash_personalization_app_resources.grd": {
-    "META": {"sizes": {"includes": [50],}},
+    "META": {"sizes": {"includes": [120],}},
     "includes": [3340],
   },
   "<(SHARED_INTERMEDIATE_DIR)/ash/webui/demo_mode_app_ui/ash_demo_mode_app_resources.grd": {
diff --git a/tools/mac/power/BUILD.gn b/tools/mac/power/BUILD.gn
index cb6091ead..b64ca06 100644
--- a/tools/mac/power/BUILD.gn
+++ b/tools/mac/power/BUILD.gn
@@ -31,6 +31,8 @@
     "power_sampler/csv_exporter.h",
     "power_sampler/json_exporter.cc",
     "power_sampler/json_exporter.h",
+    "power_sampler/m1_sampler.h",
+    "power_sampler/m1_sampler.mm",
     "power_sampler/main_display_sampler.cc",
     "power_sampler/main_display_sampler.h",
     "power_sampler/monitor.cc",
@@ -78,6 +80,7 @@
     "power_sampler/battery_sampler_unittest.cc",
     "power_sampler/csv_exporter_unittest.cc",
     "power_sampler/json_exporter_unittest.cc",
+    "power_sampler/m1_sampler_unittest.mm",
     "power_sampler/main_display_sampler_unittest.cc",
     "power_sampler/resource_coalition_sampler_unittest.cc",
     "power_sampler/sampling_controller_unittest.cc",
diff --git a/tools/mac/power/power_sampler/m1_sampler.h b/tools/mac/power/power_sampler/m1_sampler.h
new file mode 100644
index 0000000..5542be6
--- /dev/null
+++ b/tools/mac/power/power_sampler/m1_sampler.h
@@ -0,0 +1,44 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#ifndef TOOLS_MAC_POWER_POWER_SAMPLER_M1_SAMPLER_H_
+#define TOOLS_MAC_POWER_POWER_SAMPLER_M1_SAMPLER_H_
+
+#include <memory>
+
+#include "tools/mac/power/power_sampler/sampler.h"
+
+namespace power_metrics {
+class M1SensorsReader;
+}
+
+namespace power_sampler {
+
+// The M1 sensors sampler samples the temperature of M1 P-Cores and E-Cores.
+class M1Sampler : public Sampler {
+ public:
+  static constexpr char kSamplerName[] = "m1";
+
+  ~M1Sampler() override;
+
+  // Creates and initializes a new sampler, if possible.
+  // Returns nullptr on failure.
+  static std::unique_ptr<M1Sampler> Create();
+
+  // Sampler implementation.
+  std::string GetName() override;
+  DatumNameUnits GetDatumNameUnits() override;
+  Sample GetSample(base::TimeTicks sample_time) override;
+
+ private:
+  friend class M1SamplerTest;
+
+  M1Sampler(std::unique_ptr<power_metrics::M1SensorsReader> reader);
+
+  std::unique_ptr<power_metrics::M1SensorsReader> reader_;
+};
+
+}  // namespace power_sampler
+
+#endif  // TOOLS_MAC_POWER_POWER_SAMPLER_M1_SAMPLER_H_
diff --git a/tools/mac/power/power_sampler/m1_sampler.mm b/tools/mac/power/power_sampler/m1_sampler.mm
new file mode 100644
index 0000000..4f6049f
--- /dev/null
+++ b/tools/mac/power/power_sampler/m1_sampler.mm
@@ -0,0 +1,61 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "tools/mac/power/power_sampler/m1_sampler.h"
+
+#include "base/memory/ptr_util.h"
+#include "base/strings/string_piece.h"
+#include "components/power_metrics/m1_sensors_mac.h"
+
+namespace power_sampler {
+
+namespace {
+
+void MaybeAddToSample(Sampler::Sample* sample,
+                      base::StringPiece name,
+                      absl::optional<double> val) {
+  if (val.has_value())
+    sample->emplace(name, val.value());
+}
+
+}  // namespace
+
+M1Sampler::~M1Sampler() = default;
+
+// static
+std::unique_ptr<M1Sampler> M1Sampler::Create() {
+  std::unique_ptr<power_metrics::M1SensorsReader> reader =
+      power_metrics::M1SensorsReader::Create();
+  if (!reader)
+    return nullptr;
+  return base::WrapUnique(new M1Sampler(std::move(reader)));
+}
+
+std::string M1Sampler::GetName() {
+  return kSamplerName;
+}
+
+Sampler::DatumNameUnits M1Sampler::GetDatumNameUnits() {
+  DatumNameUnits ret{{"p_cores_temperature", "C"},
+                     {"e_cores_temperature", "C"}};
+  return ret;
+}
+
+Sampler::Sample M1Sampler::GetSample(base::TimeTicks sample_time) {
+  Sample sample;
+  power_metrics::M1SensorsReader::TemperaturesCelsius temperatures =
+      reader_->ReadTemperatures();
+
+  MaybeAddToSample(&sample, "p_cores_temperature", temperatures.p_cores);
+  MaybeAddToSample(&sample, "e_cores_temperature", temperatures.e_cores);
+
+  return sample;
+}
+
+M1Sampler::M1Sampler(std::unique_ptr<power_metrics::M1SensorsReader> reader)
+    : reader_(std::move(reader)) {
+  DCHECK(reader_);
+}
+
+}  // namespace power_sampler
diff --git a/tools/mac/power/power_sampler/m1_sampler_unittest.mm b/tools/mac/power/power_sampler/m1_sampler_unittest.mm
new file mode 100644
index 0000000..681a2f1
--- /dev/null
+++ b/tools/mac/power/power_sampler/m1_sampler_unittest.mm
@@ -0,0 +1,100 @@
+// Copyright 2021 The Chromium Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style license that can be
+// found in the LICENSE file.
+
+#include "tools/mac/power/power_sampler/m1_sampler.h"
+
+#include <memory>
+
+#include "base/containers/flat_map.h"
+#include "base/memory/ptr_util.h"
+#include "components/power_metrics/m1_sensors_mac.h"
+#include "testing/gmock/include/gmock/gmock.h"
+#include "testing/gtest/include/gtest/gtest.h"
+#include "third_party/abseil-cpp/absl/types/optional.h"
+#include "tools/mac/power/power_sampler/battery_sampler.h"
+
+namespace power_sampler {
+
+namespace {
+
+using testing::UnorderedElementsAre;
+
+class TestM1SensorsReader : public power_metrics::M1SensorsReader {
+ public:
+  TestM1SensorsReader()
+      : power_metrics::M1SensorsReader(
+            base::ScopedCFTypeRef<IOHIDEventSystemClientRef>()) {}
+
+  void set_temperatures(TemperaturesCelsius temperatures) {
+    temperatures_ = temperatures;
+  }
+
+  // power_metrics::M1SensorsReader:
+  TemperaturesCelsius ReadTemperatures() override { return temperatures_; }
+
+ private:
+  TemperaturesCelsius temperatures_;
+};
+
+}  // namespace
+
+class M1SamplerTest : public testing::Test {
+ public:
+  M1SamplerTest() {
+    std::unique_ptr<TestM1SensorsReader> reader =
+        std::make_unique<TestM1SensorsReader>();
+    reader_ = reader.get();
+    sampler_ = base::WrapUnique(new M1Sampler(std::move(reader)));
+  }
+
+  TestM1SensorsReader* reader_ = nullptr;
+  std::unique_ptr<M1Sampler> sampler_;
+};
+
+TEST_F(M1SamplerTest, NameAndGetDatumNameUnits) {
+  EXPECT_EQ("m1", sampler_->GetName());
+
+  auto datum_name_units = sampler_->GetDatumNameUnits();
+  EXPECT_THAT(datum_name_units,
+              UnorderedElementsAre(std::make_pair("p_cores_temperature", "C"),
+                                   std::make_pair("e_cores_temperature", "C")));
+}
+
+TEST_F(M1SamplerTest, GetSample_AllFieldsAvailable) {
+  power_metrics::M1SensorsReader::TemperaturesCelsius temperatures;
+  temperatures.p_cores = 1;
+  temperatures.e_cores = 2;
+  reader_->set_temperatures(temperatures);
+
+  Sampler::Sample sample = sampler_->GetSample(base::TimeTicks());
+  EXPECT_THAT(sample,
+              UnorderedElementsAre(std::make_pair("p_cores_temperature", 1),
+                                   std::make_pair("e_cores_temperature", 2)));
+}
+
+TEST_F(M1SamplerTest, GetSample_IndividualFieldNotAvailable) {
+  {
+    power_metrics::M1SensorsReader::TemperaturesCelsius temperatures;
+    temperatures.p_cores = absl::nullopt;
+    temperatures.e_cores = 2;
+    reader_->set_temperatures(temperatures);
+
+    Sampler::Sample sample = sampler_->GetSample(base::TimeTicks());
+    EXPECT_THAT(sample,
+                UnorderedElementsAre(std::make_pair("e_cores_temperature", 2)));
+  }
+
+  {
+    power_metrics::M1SensorsReader::TemperaturesCelsius temperatures;
+    temperatures.p_cores = 1;
+    temperatures.e_cores = absl::nullopt;
+    reader_->set_temperatures(temperatures);
+
+    Sampler::Sample sample = sampler_->GetSample(base::TimeTicks());
+    EXPECT_THAT(sample,
+                UnorderedElementsAre(std::make_pair("p_cores_temperature", 1)));
+  }
+}
+
+}  // namespace power_sampler
diff --git a/tools/mac/power/power_sampler/power_sampler_main.cc b/tools/mac/power/power_sampler/power_sampler_main.cc
index 9250d2b..da9a9f1 100644
--- a/tools/mac/power/power_sampler/power_sampler_main.cc
+++ b/tools/mac/power/power_sampler/power_sampler_main.cc
@@ -20,6 +20,7 @@
 #include "tools/mac/power/power_sampler/battery_sampler.h"
 #include "tools/mac/power/power_sampler/csv_exporter.h"
 #include "tools/mac/power/power_sampler/json_exporter.h"
+#include "tools/mac/power/power_sampler/m1_sampler.h"
 #include "tools/mac/power/power_sampler/main_display_sampler.h"
 #include "tools/mac/power/power_sampler/resource_coalition_sampler.h"
 #include "tools/mac/power/power_sampler/sample_counter.h"
@@ -234,6 +235,13 @@
       return kStatusRuntimeError;
     }
   }
+  if (ConsumeSamplerName(power_sampler::M1Sampler::kSamplerName,
+                         sampler_names) ||
+      all_samplers) {
+    if (!MaybeAddSamplerToController<power_sampler::M1Sampler>(controller)) {
+      return kStatusRuntimeError;
+    }
+  }
   if (ConsumeSamplerName(power_sampler::UserIdleLevelSampler::kSamplerName,
                          sampler_names) ||
       all_samplers) {
diff --git a/tools/mac/power/power_sampler/smc_sampler_unittest.mm b/tools/mac/power/power_sampler/smc_sampler_unittest.mm
index b696da3..4e7b850 100644
--- a/tools/mac/power/power_sampler/smc_sampler_unittest.mm
+++ b/tools/mac/power/power_sampler/smc_sampler_unittest.mm
@@ -3,6 +3,7 @@
 // found in the LICENSE file.
 
 #include "tools/mac/power/power_sampler/smc_sampler.h"
+
 #include <memory>
 
 #include "base/containers/flat_map.h"
diff --git a/tools/mb/mb_config.pyl b/tools/mb/mb_config.pyl
index b9c4463..3d2a243 100644
--- a/tools/mb/mb_config.pyl
+++ b/tools/mb/mb_config.pyl
@@ -277,8 +277,8 @@
         'reclient': 'gpu_tests_release_bot_reclient',
       },
       'Comparison Windows': {
-        'goma': 'gpu_tests_release_bot',
-        'reclient': 'gpu_tests_release_bot_reclient',
+        'goma': 'gpu_tests_release_bot_minimal_symbols',
+        'reclient': 'gpu_tests_release_bot_minimal_symbols_reclient',
       },
       'Libfuzzer Upload Chrome OS ASan': 'libfuzzer_chromeos_asan_release_bot',
       'Libfuzzer Upload Linux ASan': 'libfuzzer_asan_release_bot',
@@ -291,7 +291,7 @@
       'Linux Builder (j-500) (reclient)': 'gpu_tests_release_bot_reclient',
       'Linux CFI (reclient shadow)': 'cfi_full_cfi_icall_cfi_diag_thin_lto_release_static_dcheck_always_on_reclient',
       'Linux Builder (j-500) (reclient)': 'gpu_tests_release_bot_reclient',
-      'Linux Viz': 'release_trybot_minimal_symbols',
+      'Linux Viz': 'release_trybot_minimal_symbols_reclient',
       'lacros-amd64-generic-rel-fyi': 'chromeos_amd64-generic_lacros_rel',
       'linux-ash-chromium-builder-fyi-rel': 'chromeos_with_codecs_release_bot',
       'linux-lacros-builder-fyi-rel': 'lacros_on_linux_release_bot',
@@ -453,7 +453,7 @@
       'GPU Mac Builder': 'gpu_tests_release_trybot_minimal_symbols',
       'GPU Mac Builder (dbg)': 'gpu_tests_debug_bot',
       'GPU Linux Builder': 'gpu_tests_release_trybot_minimal_symbols',
-      'GPU Linux Builder (dbg)': 'gpu_tests_debug_bot',
+      'GPU Linux Builder (dbg)': 'gpu_tests_debug_bot_reclient',
       'GPU Win x64 Builder': 'gpu_tests_release_bot_dcheck_always_on_resource_allowlisting',
       'GPU Win x64 Builder Code Coverage': 'gpu_tests_release_trybot_resource_allowlisting_code_coverage',
       'GPU Win x64 Builder (dbg)': 'gpu_tests_debug_bot',
@@ -480,7 +480,7 @@
       'GPU FYI Win x64 DX12 Vulkan Builder': 'gpu_fyi_tests_dx12vk_release_trybot',
       'GPU FYI Win x64 DX12 Vulkan Builder (dbg)': 'gpu_fyi_tests_dx12vk_debug_trybot',
       'GPU FYI XR Win x64 Builder': 'gpu_fyi_tests_release_trybot',
-      'Linux FYI GPU TSAN Release': 'gpu_fyi_tests_release_trybot_tsan',
+      'Linux FYI GPU TSAN Release': 'gpu_fyi_tests_release_trybot_tsan_reclient',
       'Linux FYI SkiaRenderer Dawn Release (Intel HD 630)': 'gpu_tests_sk_dawn_release_trybot',
       'Optional Android Release (Nexus 5X)': 'gpu_tests_android_release_trybot_arm64',
       'Optional Android Release (Pixel 4)': 'gpu_tests_android_release_trybot',
@@ -1194,6 +1194,7 @@
       'win10_chromium_x64_rel_ng_exp': 'release_trybot',
       'win10_chromium_x64_rel_ng_rts': 'gpu_tests_release_trybot_resource_allowlisting_code_coverage',
       'win10-rel-orchestrator': 'gpu_tests_release_trybot_resource_allowlisting_code_coverage',
+      'win11-x64-fyi-rel': 'gpu_tests_release_trybot_resource_allowlisting_code_coverage',
       'win-annotator-rel': 'release_trybot',
       'win-asan': 'asan_clang_fuzzer_static_v8_heap_minimal_symbols_release',
       'win-celab-try-rel': 'release_bot_minimal_symbols',
@@ -2236,6 +2237,10 @@
       'gpu_fyi_tests', 'release_trybot_minimal_symbols', 'tsan', 'disable_nacl',
     ],
 
+    'gpu_fyi_tests_release_trybot_tsan_reclient': [
+      'gpu_fyi_tests', 'release_trybot_minimal_symbols_reclient', 'tsan', 'disable_nacl',
+    ],
+
     'gpu_fyi_tests_release_trybot_x86': [
       'gpu_fyi_tests', 'release_trybot_minimal_symbols', 'x86', 'disable_nacl',
     ],
diff --git a/tools/mb/mb_config_expectations/chromium.fyi.json b/tools/mb/mb_config_expectations/chromium.fyi.json
index 2320959..d458782 100644
--- a/tools/mb/mb_config_expectations/chromium.fyi.json
+++ b/tools/mb/mb_config_expectations/chromium.fyi.json
@@ -56,6 +56,7 @@
       "is_component_build": false,
       "is_debug": false,
       "proprietary_codecs": true,
+      "symbol_level": 1,
       "use_goma": true
     },
     "reclient": {
@@ -64,6 +65,7 @@
       "is_component_build": false,
       "is_debug": false,
       "proprietary_codecs": true,
+      "symbol_level": 1,
       "use_rbe": true,
       "use_remoteexec": true
     }
@@ -230,7 +232,8 @@
       "is_component_build": false,
       "is_debug": false,
       "symbol_level": 1,
-      "use_goma": true
+      "use_rbe": true,
+      "use_remoteexec": true
     }
   },
   "Mac Builder (reclient compare)": {
diff --git a/tools/mb/mb_config_expectations/chromium.gpu.fyi.json b/tools/mb/mb_config_expectations/chromium.gpu.fyi.json
index c88bf19..725ec0a 100644
--- a/tools/mb/mb_config_expectations/chromium.gpu.fyi.json
+++ b/tools/mb/mb_config_expectations/chromium.gpu.fyi.json
@@ -296,7 +296,8 @@
       "is_tsan": true,
       "proprietary_codecs": true,
       "symbol_level": 1,
-      "use_goma": true
+      "use_rbe": true,
+      "use_remoteexec": true
     }
   },
   "Linux FYI SkiaRenderer Dawn Release (Intel HD 630)": {
diff --git a/tools/mb/mb_config_expectations/chromium.gpu.json b/tools/mb/mb_config_expectations/chromium.gpu.json
index 287c485..360fc0c 100644
--- a/tools/mb/mb_config_expectations/chromium.gpu.json
+++ b/tools/mb/mb_config_expectations/chromium.gpu.json
@@ -36,7 +36,8 @@
       "is_debug": true,
       "proprietary_codecs": true,
       "symbol_level": 1,
-      "use_goma": true
+      "use_rbe": true,
+      "use_remoteexec": true
     }
   },
   "GPU Mac Builder": {
diff --git a/tools/mb/mb_config_expectations/tryserver.chromium.win.json b/tools/mb/mb_config_expectations/tryserver.chromium.win.json
index f5a90f8..91960ea 100644
--- a/tools/mb/mb_config_expectations/tryserver.chromium.win.json
+++ b/tools/mb/mb_config_expectations/tryserver.chromium.win.json
@@ -334,6 +334,21 @@
       "use_goma": true
     }
   },
+  "win11-x64-fyi-rel": {
+    "gn_args": {
+      "blink_enable_generated_code_formatting": false,
+      "coverage_instrumentation_input_file": "//.code-coverage/files_to_instrument.txt",
+      "dcheck_always_on": true,
+      "enable_resource_allowlist_generation": false,
+      "ffmpeg_branding": "Chrome",
+      "is_component_build": false,
+      "is_debug": false,
+      "proprietary_codecs": true,
+      "symbol_level": 0,
+      "use_clang_coverage": true,
+      "use_goma": true
+    }
+  },
   "win7-rel": {
     "gn_args": {
       "blink_enable_generated_code_formatting": false,
diff --git a/tools/metrics/histograms/enums.xml b/tools/metrics/histograms/enums.xml
index d0c9ef6..a13f62a 100644
--- a/tools/metrics/histograms/enums.xml
+++ b/tools/metrics/histograms/enums.xml
@@ -32124,6 +32124,18 @@
   <int value="1213" label="Pairing Failed: Error UI Dismissed By User"/>
 </enum>
 
+<enum name="FastPairHandshakeFailureReason">
+  <int value="0" label="Failed to initialize GATT connection"/>
+  <int value="1" label="Failed to create FastPairDataEncryptor"/>
+  <int value="2"
+      label="Failed to write to the Key-based Pairing Characteristic"/>
+  <int value="3"
+      label="Failed to decrypt the the Key-based Pairing Characteristic
+             response"/>
+  <int value="4"
+      label="Incorrect Key-based Pairing Characteristic response type"/>
+</enum>
+
 <enum name="FastPairPairFailure">
   <int value="0" label="Failed to create a GATT connection to the device"/>
   <int value="1" label="Failed to find the expected GATT service"/>
@@ -36417,7 +36429,8 @@
   <int value="3884" label="WebAppManifestProtocolHandlers"/>
   <int value="3885" label="RTCPeerConnectionOfferAllowExtmapMixedFalse"/>
   <int value="3886" label="NewCanvas2DAPI"/>
-  <int value="3887" label="ServiceWorkerSubresourceFilterBypassedRequest"/>
+  <int value="3887"
+      label="OBSOLETE_ServiceWorkerSubresourceFilterBypassedRequest"/>
   <int value="3888" label="WebGPU"/>
   <int value="3889" label="CSSFilterColorMatrix"/>
   <int value="3890" label="HTMLFencedFrameElement"/>
@@ -72989,6 +73002,8 @@
   <int value="20" label="kPendingNotificationCloseEvent"/>
   <int value="21" label="kFeedbackDialog"/>
   <int value="22" label="kWebAppUpdate"/>
+  <int value="23" label="kGettingWebAppInfo"/>
+  <int value="24" label="kCrxInstaller"/>
 </enum>
 
 <enum name="ProfileMenuActionableItem">
@@ -83995,6 +84010,12 @@
   <int value="9" label="Failed"/>
 </enum>
 
+<enum name="StatefulFormat">
+  <summary>ChromeOS Stateful Partition Format</summary>
+  <int value="0" label="Raw partition"/>
+  <int value="1" label="Logical volume"/>
+</enum>
+
 <enum name="StateStoreInitResult">
   <int value="0"
       label="Kept pref: platform-specific store non-existent or not
diff --git a/tools/metrics/histograms/metadata/arc/histograms.xml b/tools/metrics/histograms/metadata/arc/histograms.xml
index c8d57a5a..74b1434 100644
--- a/tools/metrics/histograms/metadata/arc/histograms.xml
+++ b/tools/metrics/histograms/metadata/arc/histograms.xml
@@ -617,8 +617,8 @@
 <histogram name="Arc.CompanionLibraryApisCounter"
     enum="CompanionLibraryApisList" expires_after="2022-04-10">
   <owner>sstan@google.com</owner>
-  <owner>bartfab@chromium.org</owner>
-  <owner>giovax@google.com</owner>
+  <owner>mhasank@google.com</owner>
+  <owner>arc-commercial@google.com</owner>
   <summary>
     Records the number of times ChromeOS Companion Library API called. Counter
     adding when its Stub library receive the call from applications.
@@ -1857,7 +1857,7 @@
 
 <histogram name="Arc.Supervision.Transition.Result"
     enum="ArcSupervisionTransitionResult" expires_after="2022-08-03">
-  <owner>giovax@chromium.org</owner>
+  <owner>mhasank@chromium.org</owner>
   <owner>arc-commercial@google.com</owner>
   <summary>
     The result (success or the type of failure) of ARC supervision transition
diff --git a/tools/metrics/histograms/metadata/bluetooth/histograms.xml b/tools/metrics/histograms/metadata/bluetooth/histograms.xml
index 78ebb77..ae5e567 100644
--- a/tools/metrics/histograms/metadata/bluetooth/histograms.xml
+++ b/tools/metrics/histograms/metadata/bluetooth/histograms.xml
@@ -383,6 +383,58 @@
   </summary>
 </histogram>
 
+<histogram name="Bluetooth.ChromeOS.FastPair.FastPairRepository.Cache.Result"
+    enum="Boolean" expires_after="2022-09-20">
+  <owner>shanefitz@google.com</owner>
+  <owner>julietlevesque@google.com</owner>
+  <owner>chromeos-cross-device-eng@google.com</owner>
+  <summary>
+    Records whether or not device metadata we retrieve is in the cache in the
+    repository. Records true when the metadata is in the cache, and false when
+    the metadata is not in the cache. Emitted in the FastPairRepository on a
+    GetDeviceMetadata request.
+  </summary>
+</histogram>
+
+<histogram name="Bluetooth.ChromeOS.FastPair.FootprintsFetcher.Delete.Result"
+    enum="BooleanSuccess" expires_after="2022-09-20">
+  <owner>shanefitz@google.com</owner>
+  <owner>julietlevesque@google.com</owner>
+  <owner>chromeos-cross-device-eng@google.com</owner>
+  <summary>
+    Records the success or failure of a Delete request in the FootprintsFetcher.
+    A failure is considered no response from the server. A success is considered
+    a response that is able to be parsed. Emitted when the HTTP response is
+    received from the Footprints server.
+  </summary>
+</histogram>
+
+<histogram name="Bluetooth.ChromeOS.FastPair.FootprintsFetcher.Get.Result"
+    enum="BooleanSuccess" expires_after="2022-09-20">
+  <owner>shanefitz@google.com</owner>
+  <owner>julietlevesque@google.com</owner>
+  <owner>chromeos-cross-device-eng@google.com</owner>
+  <summary>
+    Records the success or failure of a Get request in the FootprintsFetcher. A
+    failure is considered either no response, or a response that is unable to be
+    parsed. A success is considered a response that is able to be parsed.
+    Emitted when the HTTP response is received from the Footprints server.
+  </summary>
+</histogram>
+
+<histogram name="Bluetooth.ChromeOS.FastPair.FootprintsFetcher.Post.Result"
+    enum="BooleanSuccess" expires_after="2022-09-20">
+  <owner>shanefitz@google.com</owner>
+  <owner>julietlevesque@google.com</owner>
+  <owner>chromeos-cross-device-eng@google.com</owner>
+  <summary>
+    Records the success or failure of a Post request in the FootprintsFetcher. A
+    failure is considered no response from the server. A success is considered a
+    response that is able to be parsed. Emitted when the HTTP response is
+    received from the Footprints server.
+  </summary>
+</histogram>
+
 <histogram name="Bluetooth.ChromeOS.FastPair.GattConnection.ErrorReason"
     enum="BluetoothDeviceConnectErrorCode" expires_after="2022-09-20">
   <owner>shanefitz@google.com</owner>
@@ -407,6 +459,32 @@
   </summary>
 </histogram>
 
+<histogram name="Bluetooth.ChromeOS.FastPair.Handshake.FailureReason"
+    enum="FastPairHandshakeFailureReason" expires_after="2022-09-20">
+  <owner>shanefitz@google.com</owner>
+  <owner>julietlevesque@google.com</owner>
+  <owner>chromeos-cross-device-eng@google.com</owner>
+  <summary>
+    Records reason behind the failure of the big picture Fast Pair Handshake
+    with a device (see 'Bluetooth.ChromeOS.FastPair.Handshake.Result'). Emitted
+    on Handshake failure.
+  </summary>
+</histogram>
+
+<histogram name="Bluetooth.ChromeOS.FastPair.Handshake.Result"
+    enum="BooleanSuccess" expires_after="2022-09-20">
+  <owner>shanefitz@google.com</owner>
+  <owner>julietlevesque@google.com</owner>
+  <owner>chromeos-cross-device-eng@google.com</owner>
+  <summary>
+    Records the success or failure of the big picture Fast Pair Handshake with a
+    device. Possible failures include : creating a Gatt connection, creating the
+    data encryptor, writing to the device, parsing the response bytes from the
+    device. Success is considered when we receive a valid response from the
+    device. Emitted when the Handshake reaches a terminal point.
+  </summary>
+</histogram>
+
 <histogram name="Bluetooth.ChromeOS.FastPair.KeyBasedPairing.DecryptResult"
     enum="BooleanSuccess" expires_after="2022-09-20">
   <owner>shanefitz@google.com</owner>
diff --git a/tools/metrics/histograms/metadata/platform/histograms.xml b/tools/metrics/histograms/metadata/platform/histograms.xml
index 99ff3dbc..d262006 100644
--- a/tools/metrics/histograms/metadata/platform/histograms.xml
+++ b/tools/metrics/histograms/metadata/platform/histograms.xml
@@ -884,6 +884,13 @@
   </summary>
 </histogram>
 
+<histogram name="Platform.StatefulFormat" enum="StatefulFormat"
+    expires_after="2022-10-21">
+  <owner>sarthakkukreti@chromium.org</owner>
+  <owner>gwendal@chromium.org</owner>
+  <summary>Chrome OS stateful partition format. Sampled once per boot.</summary>
+</histogram>
+
 <histogram name="Platform.StatefulFreeSpace" units="MB"
     expires_after="2022-10-21">
   <owner>asavery@chromium.org</owner>
diff --git a/tools/metrics/histograms/metadata/startup/histograms.xml b/tools/metrics/histograms/metadata/startup/histograms.xml
index 40fc591..078e604 100644
--- a/tools/metrics/histograms/metadata/startup/histograms.xml
+++ b/tools/metrics/histograms/metadata/startup/histograms.xml
@@ -259,6 +259,19 @@
   </summary>
 </histogram>
 
+<histogram name="Startup.Android.LastVisitedTabIsSRPWhenOverviewShownAtLaunch"
+    enum="Boolean" expires_after="2022-08-09">
+  <owner>hanxi@chromium.org</owner>
+  <owner>spdonghao@chromium.org</owner>
+  <owner>fredmello@chromium.org</owner>
+  <summary>
+    Records whether or not the last visited tab is a search result page when
+    StartSurface is shown at launch. This histogram is only recorded when
+    StartSurface is shown at launch due to &quot;return to tab switcher&quot;
+    feature.
+  </summary>
+</histogram>
+
 <histogram name="Startup.Android.ShowChromeStartSegmentationResult"
     enum="ShowChromeStartSegmentationResult" expires_after="2022-08-09">
   <owner>hanxi@chromium.org</owner>
diff --git a/tools/traffic_annotation/summary/annotations.xml b/tools/traffic_annotation/summary/annotations.xml
index 8b127ee3..d44bde8 100644
--- a/tools/traffic_annotation/summary/annotations.xml
+++ b/tools/traffic_annotation/summary/annotations.xml
@@ -352,4 +352,5 @@
  <item id="wallpaper_backdrop_surprise_me_image" added_in_milestone="99" content_hash_code="0383b9db" os_list="chromeos" file_path="chrome/browser/ash/wallpaper_handlers/wallpaper_handlers.cc" />
  <item id="nearby_connections_wifi_lan" added_in_milestone="99" content_hash_code="06b30010" os_list="chromeos" file_path="chrome/services/sharing/nearby/platform/wifi_lan_medium.cc" />
  <item id="timezone_lookup" added_in_milestone="98" content_hash_code="01e64e71" os_list="chromeos" file_path="ash/components/timezone/timezone_request.cc" />
+ <item id="oma_download_handler_android" added_in_milestone="99" content_hash_code="03226fe2" os_list="android" file_path="chrome/android/java/src/org/chromium/chrome/browser/download/OMADownloadHandler.java" />
 </annotations>
diff --git a/tools/traffic_annotation/summary/grouping.xml b/tools/traffic_annotation/summary/grouping.xml
index 22e449c..2b3f9adc0 100644
--- a/tools/traffic_annotation/summary/grouping.xml
+++ b/tools/traffic_annotation/summary/grouping.xml
@@ -36,6 +36,7 @@
       <traffic_annotation unique_id="gstatic_onboarding_definition"/>
       <traffic_annotation unique_id="kids_chrome_management_client_classify_url"/>
       <traffic_annotation unique_id="minidump_uploader_android"/>
+      <traffic_annotation unique_id="oma_download_handler_android"/>
       <traffic_annotation unique_id="partner_bookmarks_reader_get_favicon"/>
       <traffic_annotation unique_id="permission_request_creator"/>
       <traffic_annotation unique_id="publish_note_request"/>
diff --git a/ui/accessibility/accessibility_features.cc b/ui/accessibility/accessibility_features.cc
index 2297086..bbe6a2867 100644
--- a/ui/accessibility/accessibility_features.cc
+++ b/ui/accessibility/accessibility_features.cc
@@ -150,7 +150,7 @@
 
 const base::Feature kExperimentalAccessibilityDictationExtension{
     "ExperimentalAccessibilityDictationExtension",
-    base::FEATURE_DISABLED_BY_DEFAULT};
+    base::FEATURE_ENABLED_BY_DEFAULT};
 
 bool IsExperimentalAccessibilityDictationExtensionEnabled() {
   return base::FeatureList::IsEnabled(
diff --git a/ui/accessibility/platform/inspect/ax_api_type.cc b/ui/accessibility/platform/inspect/ax_api_type.cc
index a2b511b..4d6ebf32 100644
--- a/ui/accessibility/platform/inspect/ax_api_type.cc
+++ b/ui/accessibility/platform/inspect/ax_api_type.cc
@@ -4,6 +4,8 @@
 
 #include "ui/accessibility/platform/inspect/ax_api_type.h"
 
+#include <cstring>
+
 namespace ui {
 
 namespace {
diff --git a/ui/base/models/table_model.cc b/ui/base/models/table_model.cc
index 228008a..42a19ca 100644
--- a/ui/base/models/table_model.cc
+++ b/ui/base/models/table_model.cc
@@ -7,6 +7,7 @@
 #include "base/check.h"
 #include "base/i18n/string_compare.h"
 #include "base/notreached.h"
+#include "third_party/icu/source/i18n/unicode/coll.h"
 #include "ui/base/l10n/l10n_util.h"
 #include "ui/base/models/image_model.h"
 
@@ -43,7 +44,7 @@
 // TableModel -----------------------------------------------------------------
 
 // Used for sorting.
-static icu::Collator* g_collator = NULL;
+static icu::Collator* g_collator = nullptr;
 
 ui::ImageModel TableModel::GetIcon(int row) {
   return ui::ImageModel();
@@ -54,8 +55,11 @@
 }
 
 int TableModel::CompareValues(int row1, int row2, int column_id) {
-  DCHECK(row1 >= 0 && row1 < RowCount() &&
-         row2 >= 0 && row2 < RowCount());
+  DCHECK_GE(row1, 0);
+  DCHECK_LT(row1, RowCount());
+  DCHECK_GE(row2, 0);
+  DCHECK_LT(row2, RowCount());
+
   std::u16string value1 = GetText(row1, column_id);
   std::u16string value2 = GetText(row2, column_id);
   icu::Collator* collator = GetCollator();
@@ -69,15 +73,17 @@
 
 void TableModel::ClearCollator() {
   delete g_collator;
-  g_collator = NULL;
+  g_collator = nullptr;
 }
 
+TableModel::~TableModel() = default;
+
 icu::Collator* TableModel::GetCollator() {
   if (!g_collator) {
     UErrorCode create_status = U_ZERO_ERROR;
     g_collator = icu::Collator::createInstance(create_status);
     if (!U_SUCCESS(create_status)) {
-      g_collator = NULL;
+      g_collator = nullptr;
       NOTREACHED();
     }
   }
diff --git a/ui/base/models/table_model.h b/ui/base/models/table_model.h
index 7cd5fca..f32af40 100644
--- a/ui/base/models/table_model.h
+++ b/ui/base/models/table_model.h
@@ -6,10 +6,14 @@
 #define UI_BASE_MODELS_TABLE_MODEL_H_
 
 #include <string>
-#include <vector>
 
 #include "base/component_export.h"
-#include "third_party/icu/source/i18n/unicode/coll.h"
+#include "third_party/icu/source/common/unicode/uversion.h"
+
+// third_party/icu/source/common/unicode/uversion.h will set namespace icu.
+namespace U_ICU_NAMESPACE {
+class Collator;
+}
 
 namespace ui {
 
@@ -55,7 +59,7 @@
   void ClearCollator();
 
  protected:
-  virtual ~TableModel() {}
+  virtual ~TableModel();
 
   // Returns the collator used by CompareValues.
   icu::Collator* GetCollator();
diff --git a/ui/compositor/compositor_animation_observer.cc b/ui/compositor/compositor_animation_observer.cc
index 6c5d76d8..b3a9724 100644
--- a/ui/compositor/compositor_animation_observer.cc
+++ b/ui/compositor/compositor_animation_observer.cc
@@ -13,10 +13,11 @@
 
 namespace ui {
 
-// Do not fail on SANITIZER builds as they run slow.
-#if !DCHECK_IS_ON() || defined(ADDRESS_SANITIZER) ||          \
-    defined(MEMORY_SANITIZER) || defined(THREAD_SANITIZER) || \
-    defined(LEAK_SANITIZER) || defined(UNDEFINED_SANITIZER)
+// Do not fail on builds that run slow, such as SANITIZER, debug.
+#if !DCHECK_IS_ON() || defined(ADDRESS_SANITIZER) ||           \
+    defined(MEMORY_SANITIZER) || defined(THREAD_SANITIZER) ||  \
+    defined(LEAK_SANITIZER) || defined(UNDEFINED_SANITIZER) || \
+    !defined(NDEBUG)
 #define NOTREACHED_OR_WARN() LOG(WARNING)
 #else
 #define NOTREACHED_OR_WARN() NOTREACHED()
diff --git a/ui/ozone/platform/drm/gpu/drm_overlay_candidates.cc b/ui/ozone/platform/drm/gpu/drm_overlay_candidates.cc
index 24f2610..1ca2737 100644
--- a/ui/ozone/platform/drm/gpu/drm_overlay_candidates.cc
+++ b/ui/ozone/platform/drm/gpu/drm_overlay_candidates.cc
@@ -4,6 +4,7 @@
 
 #include "ui/ozone/platform/drm/gpu/drm_overlay_candidates.h"
 
+#include "media/media_buildflags.h"
 #include "ui/ozone/platform/drm/gpu/drm_overlay_manager.h"
 #include "ui/ozone/public/overlay_surface_candidate.h"
 
@@ -13,11 +14,20 @@
                                            gfx::AcceleratedWidget widget)
     : overlay_manager_(manager), widget_(widget) {}
 
-DrmOverlayCandidates::~DrmOverlayCandidates() = default;
+DrmOverlayCandidates::~DrmOverlayCandidates() {
+  overlay_manager_->RegisterOverlayRequirement(widget_, false);
+}
 
 void DrmOverlayCandidates::CheckOverlaySupport(
     std::vector<OverlaySurfaceCandidate>* candidates) {
   overlay_manager_->CheckOverlaySupport(candidates, widget_);
 }
 
+void DrmOverlayCandidates::RegisterOverlayRequirement(bool requires_overlay) {
+#if !BUILDFLAG(USE_CHROMEOS_PROTECTED_MEDIA)
+  DCHECK(!requires_overlay);
+#endif
+  overlay_manager_->RegisterOverlayRequirement(widget_, requires_overlay);
+}
+
 }  // namespace ui
diff --git a/ui/ozone/platform/drm/gpu/drm_overlay_candidates.h b/ui/ozone/platform/drm/gpu/drm_overlay_candidates.h
index a680368..cbbd6d7 100644
--- a/ui/ozone/platform/drm/gpu/drm_overlay_candidates.h
+++ b/ui/ozone/platform/drm/gpu/drm_overlay_candidates.h
@@ -29,6 +29,7 @@
   // OverlayCandidatesOzone:
   void CheckOverlaySupport(
       std::vector<OverlaySurfaceCandidate>* candidates) override;
+  void RegisterOverlayRequirement(bool requires_overlay) override;
 
  private:
   DrmOverlayManager* const overlay_manager_;  // Not owned.
diff --git a/ui/ozone/platform/drm/gpu/drm_overlay_manager.cc b/ui/ozone/platform/drm/gpu/drm_overlay_manager.cc
index 29030d9c..79227e5 100644
--- a/ui/ozone/platform/drm/gpu/drm_overlay_manager.cc
+++ b/ui/ozone/platform/drm/gpu/drm_overlay_manager.cc
@@ -66,6 +66,15 @@
   TRACE_EVENT0("hwoverlays", "DrmOverlayManager::CheckOverlaySupport");
   DCHECK_CALLED_ON_VALID_THREAD(thread_checker_);
 
+  // Check if another display has an overlay requirement, and if so do not
+  // allow overlays. Some ChromeOS boards only support one overlay across all
+  // displays so we want the overlay to go somewhere that requires it first vs.
+  // a display that will just be using it as an optimization.
+  if (!widgets_with_required_overlays_.empty() &&
+      !widgets_with_required_overlays_.contains(widget)) {
+    return;
+  }
+
   std::vector<OverlaySurfaceCandidate> result_candidates;
   for (auto& candidate : *candidates) {
     bool can_handle = CanHandleCandidate(candidate, widget);
@@ -140,6 +149,15 @@
                         cache_hit);
 }
 
+void DrmOverlayManager::RegisterOverlayRequirement(
+    gfx::AcceleratedWidget widget,
+    bool requires_overlay) {
+  if (requires_overlay)
+    widgets_with_required_overlays_.insert(widget);
+  else
+    widgets_with_required_overlays_.erase(widget);
+}
+
 bool DrmOverlayManager::CanHandleCandidate(
     const OverlaySurfaceCandidate& candidate,
     gfx::AcceleratedWidget widget) const {
diff --git a/ui/ozone/platform/drm/gpu/drm_overlay_manager.h b/ui/ozone/platform/drm/gpu/drm_overlay_manager.h
index 43b9fac..c9927dd4 100644
--- a/ui/ozone/platform/drm/gpu/drm_overlay_manager.h
+++ b/ui/ozone/platform/drm/gpu/drm_overlay_manager.h
@@ -8,6 +8,7 @@
 #include <memory>
 #include <vector>
 
+#include "base/containers/flat_set.h"
 #include "base/containers/lru_cache.h"
 #include "base/threading/thread_checker.h"
 #include "ui/gfx/native_widget_types.h"
@@ -43,6 +44,12 @@
   void CheckOverlaySupport(std::vector<OverlaySurfaceCandidate>* candidates,
                            gfx::AcceleratedWidget widget);
 
+  // Should be called by the overlay processor to indicate if a widget has a
+  // candidate that requires an overlay. This is to prioritize which display
+  // gets the overlay in a multiple display environment.
+  void RegisterOverlayRequirement(gfx::AcceleratedWidget widget,
+                                  bool requires_overlay);
+
  protected:
   // Sends a request to see if overlay configuration will work. Implementations
   // should call UpdateCacheForOverlayCandidates() with the response.
@@ -89,6 +96,8 @@
   std::map<gfx::AcceleratedWidget, OverlayCandidatesListCache>
       widget_cache_map_;
 
+  base::flat_set<gfx::AcceleratedWidget> widgets_with_required_overlays_;
+
   THREAD_CHECKER(thread_checker_);
 };
 
diff --git a/ui/ozone/platform/drm/gpu/drm_overlay_manager_unittest.cc b/ui/ozone/platform/drm/gpu/drm_overlay_manager_unittest.cc
index d49fed0..24e93a0 100644
--- a/ui/ozone/platform/drm/gpu/drm_overlay_manager_unittest.cc
+++ b/ui/ozone/platform/drm/gpu/drm_overlay_manager_unittest.cc
@@ -271,4 +271,41 @@
   manager.CheckOverlaySupport(&candidates, kPrimaryWidget);
 }
 
+TEST(DrmOverlayManagerTest, RequiredOverlayMultiDisplay) {
+  TestDrmOverlayManager manager;
+
+  // Primary has a requirement, secondary does not, should only make a request
+  // on the primary.
+  std::vector<OverlaySurfaceCandidate> candidates1 = {
+      CreateCandidate(gfx::Rect(0, 0, 100, 100), 0)};
+
+  manager.RegisterOverlayRequirement(kPrimaryWidget, true);
+  manager.RegisterOverlayRequirement(kSecondaryWidget, false);
+  // Call 4 Times to go beyond the Throttle Request Size
+  for (int i = 0; i < 4; ++i)
+    manager.CheckOverlaySupport(&candidates1, kPrimaryWidget);
+  EXPECT_EQ(manager.requests().size(), 1u);
+  // Call 4 Times to go beyond the Throttle Request Size
+  for (int i = 0; i < 4; ++i)
+    manager.CheckOverlaySupport(&candidates1, kSecondaryWidget);
+  EXPECT_EQ(manager.requests().size(), 1u);
+  manager.requests().clear();
+
+  // Secondary has a requirement, primary does not, should only make a request
+  // on the secondary.
+  std::vector<OverlaySurfaceCandidate> candidates2 = {
+      CreateCandidate(gfx::Rect(0, 0, 200, 200), 0)};
+
+  manager.RegisterOverlayRequirement(kPrimaryWidget, false);
+  manager.RegisterOverlayRequirement(kSecondaryWidget, true);
+  // Call 4 Times to go beyond the Throttle Request Size
+  for (int i = 0; i < 4; ++i)
+    manager.CheckOverlaySupport(&candidates2, kPrimaryWidget);
+  EXPECT_TRUE(manager.requests().empty());
+  // Call 4 Times to go beyond the Throttle Request Size
+  for (int i = 0; i < 4; ++i)
+    manager.CheckOverlaySupport(&candidates2, kSecondaryWidget);
+  EXPECT_EQ(manager.requests().size(), 1u);
+}
+
 }  // namespace ui
diff --git a/ui/ozone/platform/scenic/scenic_surface.cc b/ui/ozone/platform/scenic/scenic_surface.cc
index 45b1e8f..9d61fa3 100644
--- a/ui/ozone/platform/scenic/scenic_surface.cc
+++ b/ui/ozone/platform/scenic/scenic_surface.cc
@@ -136,13 +136,6 @@
         UpdateViewHolderScene();
         break;
       }
-      case fuchsia::ui::gfx::Event::kViewDetachedFromScene: {
-        DCHECK(event.gfx().view_detached_from_scene().view_id == parent_->id());
-        // Present an empty frame to ensure that the outdated content doesn't
-        // become visible if the view is attached again.
-        PresentEmptyImage();
-        break;
-      }
       default:
         break;
     }
@@ -526,32 +519,6 @@
   safe_presenter_.QueuePresent();
 }
 
-void ScenicSurface::PresentEmptyImage() {
-  if (last_frame_present_time_ == base::TimeTicks())
-    return;
-
-  fuchsia::sysmem::BufferCollectionTokenSyncPtr dummy_collection_token;
-  zx_status_t status =
-      sysmem_buffer_manager_->GetAllocator()->AllocateSharedCollection(
-          dummy_collection_token.NewRequest());
-  if (status != ZX_OK) {
-    ZX_DLOG(ERROR, status)
-        << "fuchsia.sysmem.Allocator.AllocateSharedCollection()";
-    return;
-  }
-
-  const uint32_t image_id = ++next_unique_id_;
-  image_pipe_->AddBufferCollection(image_id, std::move(dummy_collection_token));
-  fuchsia::sysmem::ImageFormat_2 image_format;
-  image_format.coded_width = 1;
-  image_format.coded_height = 1;
-  image_pipe_->AddImage(image_id, image_id, 0, image_format);
-
-  image_pipe_->PresentImage(image_id, last_frame_present_time_.ToZxTime(), {},
-                            {}, [](fuchsia::images::PresentationInfo) {});
-  image_pipe_->RemoveBufferCollection(image_id);
-}
-
 ScenicSurface::PresentedFrame::PresentedFrame(
     uint32_t ordinal,
     uint32_t image_id,
diff --git a/ui/ozone/platform/scenic/scenic_surface.h b/ui/ozone/platform/scenic/scenic_surface.h
index 5587aec6..b242c9a 100644
--- a/ui/ozone/platform/scenic/scenic_surface.h
+++ b/ui/ozone/platform/scenic/scenic_surface.h
@@ -141,8 +141,6 @@
   void OnPresentComplete(fuchsia::images::PresentationInfo presentation_info);
   void UpdateViewHolderScene();
 
-  void PresentEmptyImage();
-
   scenic::Session scenic_session_;
   std::unique_ptr<scenic::View> parent_;
 
diff --git a/ui/ozone/platform/wayland/host/wayland_window_drag_controller_unittest.cc b/ui/ozone/platform/wayland/host/wayland_window_drag_controller_unittest.cc
index ecd049c..b1efbab 100644
--- a/ui/ozone/platform/wayland/host/wayland_window_drag_controller_unittest.cc
+++ b/ui/ozone/platform/wayland/host/wayland_window_drag_controller_unittest.cc
@@ -572,7 +572,9 @@
 // 5. Drag it a bit more (within window 2) and then calls EndMoveLoop(),
 //    emulating a window snap), and then
 // 6. With the window in "snapped" state, drag it further and then drop.
-TEST_P(WaylandWindowDragControllerTest, DragToOtherWindowSnapDragDrop_TOUCH) {
+// TODO(crbug.com/1285380): Reenable test when flakiness is fixed.
+TEST_P(WaylandWindowDragControllerTest,
+       DISABLED_DragToOtherWindowSnapDragDrop_TOUCH) {
   // Init and open |target_window|.
   PlatformWindowInitProperties properties{gfx::Rect{80, 80}};
   properties.type = PlatformWindowType::kWindow;
diff --git a/ui/ozone/public/overlay_candidates_ozone.h b/ui/ozone/public/overlay_candidates_ozone.h
index 2f8df59e..27e32a9a 100644
--- a/ui/ozone/public/overlay_candidates_ozone.h
+++ b/ui/ozone/public/overlay_candidates_ozone.h
@@ -27,6 +27,10 @@
   // if necessary.
   virtual void CheckOverlaySupport(OverlaySurfaceCandidateList* surfaces);
 
+  // This should be invoked during overlay processing to indicate if there are
+  // any candidates for this processor that have an overlay requirement.
+  virtual void RegisterOverlayRequirement(bool requires_overlay) {}
+
   virtual ~OverlayCandidatesOzone();
 };
 
diff --git a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.html b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.html
index eebb09c..b35427c 100644
--- a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.html
+++ b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.html
@@ -7,6 +7,13 @@
     max-height: 32px;
   }
 
+  #deviceName {
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    width: 404px;
+  }
+
   #container:hover {
     background-color: var(--cr-hover-background-color);
     cursor: pointer;
diff --git a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.js b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.js
index b5e6130a0..fc3cc99f 100644
--- a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.js
+++ b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_item.js
@@ -73,6 +73,16 @@
     };
   }
 
+  /** @override */
+  focus() {
+    // Prevent scroll stops iron list from trying to bring this element to view,
+    // if it is the |lastFocused| element and scrolled out of view. This can
+    // happen if this element is tabbed to or selected and then scrolled out of
+    // view.
+    // TODO(b/210743107) Add a test for this.
+    this.$.container.focus({preventScroll: true});
+  }
+
   /**
    * @return {boolean}
    * @private
diff --git a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.html b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.html
index ec4bfab..395c47cb 100644
--- a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.html
+++ b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.html
@@ -21,9 +21,9 @@
     <localized-link
         localized-string="[[i18nAdvanced('bluetoothPairingLearnMoreLabel')]]">
     </localized-link>
-    <div id="deviceListTitle" tabindex="0">
+    <h2 id="deviceListTitle" aria-live="polite">
       [[getDeviceListTitle_(devices.*, isBluetoothEnabled)]]
-    </div>
+    </h2>
     <template  is="dom-if" if="[[shouldShowDeviceList_(devices.*,
         isBluetoothEnabled)]]" restamp>
       <div id="container" class="layout vertical flex" scrollable
diff --git a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.js b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.js
index 4ab6acc..448e27d 100644
--- a/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.js
+++ b/ui/webui/resources/cr_components/chromeos/bluetooth/bluetooth_pairing_device_selection_page.js
@@ -47,6 +47,7 @@
       devices: {
         type: Array,
         value: [],
+        observer: 'onDevicesChanged_',
       },
 
       /**
@@ -132,6 +133,15 @@
   }
 
   /** @private */
+  onDevicesChanged_() {
+    // CrScrollableBehaviorInterface method required for list items to be
+    // properly rendered when devices updates. This is because iron-list size
+    // is not fixed, if this is not called iron-list container would not be
+    // properly sized.
+    this.updateScrollableContents();
+  }
+
+  /** @private */
   onDevicePendingPairingChanged_() {
     // If |devicePendingPairing_| has changed to a defined value, it was the
     // last selected device. |devicePendingPairing_| gets reset to null whenever
diff --git a/ui/webui/resources/cr_elements/cr_button/cr_button.html b/ui/webui/resources/cr_elements/cr_button/cr_button.html
index 481c386..214f571e 100644
--- a/ui/webui/resources/cr_elements/cr_button/cr_button.html
+++ b/ui/webui/resources/cr_elements/cr_button/cr_button.html
@@ -11,18 +11,18 @@
     <style include="cr-hidden-style">
       :host {
         --active-shadow-rgb: var(--google-grey-800-rgb);
-        --active-shadow-action-rgb: var(--google-blue-refresh-500-rgb);
+        --active-shadow-action-rgb: var(--google-blue-500-rgb);
         --bg-action: var(--google-blue-600);
-        --border-color: var(--google-grey-refresh-300);
-        --disabled-bg-action: var(--google-grey-refresh-100);
+        --border-color: var(--google-grey-300);
+        --disabled-bg-action: var(--google-grey-100);
         --disabled-bg: white;
-        --disabled-border-color: var(--google-grey-refresh-100);
+        --disabled-border-color: var(--google-grey-100);
         --disabled-text-color: var(--google-grey-600);
         --focus-shadow-color: rgba(var(--google-blue-600-rgb), .4);
         --hover-bg-action: rgba(var(--google-blue-600-rgb), .9);
-        --hover-bg-color: rgba(var(--google-blue-refresh-500-rgb), .04);
-        --hover-border-color: var(--google-blue-refresh-100);
-        --hover-shadow-action-rgb: var(--google-blue-refresh-500-rgb);
+        --hover-bg-color: rgba(var(--google-blue-500-rgb), .04);
+        --hover-border-color: var(--google-blue-100);
+        --hover-shadow-action-rgb: var(--google-blue-500-rgb);
         --ink-color-action: white;
         /* Blue-ish color used either as a background or as a text color,
          * depending on the type of button. */
@@ -39,24 +39,24 @@
           --active-bg: black linear-gradient(rgba(255, 255, 255, .06),
                                              rgba(255, 255, 255, .06));
           --active-shadow-rgb: 0, 0, 0;
-          --active-shadow-action-rgb: var(--google-blue-refresh-500-rgb);
-          --bg-action: var(--google-blue-refresh-300);
-          --border-color: var(--google-grey-refresh-700);
+          --active-shadow-action-rgb: var(--google-blue-500-rgb);
+          --bg-action: var(--google-blue-300);
+          --border-color: var(--google-grey-700);
           --disabled-bg-action: var(--google-grey-800);
           /* TODO(dbeam): get --disabled-bg from Namrata. */
           --disabled-bg: transparent;
           --disabled-border-color: var(--google-grey-800);
-          --disabled-text-color: var(--google-grey-refresh-500);
-          --focus-shadow-color: rgba(var(--google-blue-refresh-300-rgb), .5);
+          --disabled-text-color: var(--google-grey-500);
+          --focus-shadow-color: rgba(var(--google-blue-300-rgb), .5);
           --hover-bg-action: var(--bg-action)
               linear-gradient(rgba(0, 0, 0, .08), rgba(0, 0, 0, .08));
-          --hover-bg-color: rgba(var(--google-blue-refresh-300-rgb), .08);
+          --hover-bg-color: rgba(var(--google-blue-300-rgb), .08);
           --ink-color-action: black;
-          --ink-color: var(--google-blue-refresh-300);
+          --ink-color: var(--google-blue-300);
           --ripple-opacity-action: .16;
           --ripple-opacity: .16;
           --text-color-action: var(--google-grey-900);
-          --text-color: var(--google-blue-refresh-300);
+          --text-color: var(--google-blue-300);
         }
       }
 
diff --git a/ui/webui/resources/cr_elements/cr_checkbox/cr_checkbox.html b/ui/webui/resources/cr_elements/cr_checkbox/cr_checkbox.html
index 0014143..05ff980 100644
--- a/ui/webui/resources/cr_elements/cr_checkbox/cr_checkbox.html
+++ b/ui/webui/resources/cr_elements/cr_checkbox/cr_checkbox.html
@@ -46,7 +46,7 @@
         --cr-checkbox-checked-ripple-opacity: .2;
         --cr-checkbox-mark-color: white;
         --cr-checkbox-ripple-unchecked-color: var(--google-grey-900);
-        --cr-checkbox-unchecked-box-color: var(--google-grey-refresh-700);
+        --cr-checkbox-unchecked-box-color: var(--google-grey-700);
         --cr-checkbox-unchecked-ripple-opacity: .15;
       }
 
@@ -55,8 +55,8 @@
           /* Dark mode colors. */
           --cr-checkbox-checked-ripple-opacity: .4;
           --cr-checkbox-mark-color: var(--google-grey-900);
-          --cr-checkbox-ripple-unchecked-color: var(--google-grey-refresh-500);
-          --cr-checkbox-unchecked-box-color: var(--google-grey-refresh-500);
+          --cr-checkbox-ripple-unchecked-color: var(--google-grey-500);
+          --cr-checkbox-unchecked-box-color: var(--google-grey-500);
           --cr-checkbox-unchecked-ripple-opacity: .4;
         }
       }
diff --git a/ui/webui/resources/cr_elements/cr_dialog/cr_dialog.html b/ui/webui/resources/cr_elements/cr_dialog/cr_dialog.html
index 42af22f..087a2ad 100644
--- a/ui/webui/resources/cr_elements/cr_dialog/cr_dialog.html
+++ b/ui/webui/resources/cr_elements/cr_dialog/cr_dialog.html
@@ -30,7 +30,7 @@
 
       @media (prefers-color-scheme: dark) {
         dialog {
-          --scroll-border-color: var(--google-grey-refresh-700);
+          --scroll-border-color: var(--google-grey-700);
           background-color: var(--google-grey-900);
           /* Note: the colors in linear-gradient() are intentionally the same to
            * add a 4% white layer on top of the fully opaque background-color. */
diff --git a/ui/webui/resources/cr_elements/cr_icon_button/cr_icon_button.html b/ui/webui/resources/cr_elements/cr_icon_button/cr_icon_button.html
index efb1d0d..e7ec685 100644
--- a/ui/webui/resources/cr_elements/cr_icon_button/cr_icon_button.html
+++ b/ui/webui/resources/cr_elements/cr_icon_button/cr_icon_button.html
@@ -7,7 +7,7 @@
   <template>
     <style>
       :host {
-        --cr-icon-button-fill-color: var(--google-grey-refresh-700);
+        --cr-icon-button-fill-color: var(--google-grey-700);
         --cr-icon-button-icon-start-offset: 0;
         --cr-icon-button-icon-size: 20px;
         --cr-icon-button-size: 36px;
@@ -103,7 +103,7 @@
 
       @media (prefers-color-scheme: dark) {
         :host {
-          --cr-icon-button-fill-color: var(--google-grey-refresh-500);
+          --cr-icon-button-fill-color: var(--google-grey-500);
         }
       }
     </style>
diff --git a/ui/webui/resources/cr_elements/cr_icons_css.html b/ui/webui/resources/cr_elements/cr_icons_css.html
index 24df8913..ab07360 100644
--- a/ui/webui/resources/cr_elements/cr_icons_css.html
+++ b/ui/webui/resources/cr_elements/cr_icons_css.html
@@ -81,7 +81,7 @@
         -webkit-mask-position: center;
         -webkit-mask-repeat: no-repeat;
         -webkit-mask-size: var(--cr-icon-size);
-        background-color: var(--cr-icon-color, var(--google-grey-refresh-700));
+        background-color: var(--cr-icon-color, var(--google-grey-700));
         flex-shrink: 0;
         height: var(--cr-icon-ripple-size);
         margin-inline-end: var(--cr-icon-ripple-margin);
@@ -101,7 +101,7 @@
 
       @media (prefers-color-scheme: dark) {
         .cr-icon {
-          background-color: var(--cr-icon-color, var(--google-grey-refresh-500));
+          background-color: var(--cr-icon-color, var(--google-grey-500));
         }
       }
     </style>
diff --git a/ui/webui/resources/cr_elements/cr_input/cr_input_style_css.html b/ui/webui/resources/cr_elements/cr_input/cr_input_style_css.html
index 3ce3bbb..8422436 100644
--- a/ui/webui/resources/cr_elements/cr_input/cr_input_style_css.html
+++ b/ui/webui/resources/cr_elements/cr_input/cr_input_style_css.html
@@ -8,7 +8,7 @@
   <template>
     <style>
       :host {
-        --cr-input-background-color: var(--google-grey-refresh-100);
+        --cr-input-background-color: var(--google-grey-100);
         --cr-input-color: var(--cr-primary-text-color);
         --cr-input-error-color: var(--google-red-600);
         --cr-input-focus-color: var(--google-blue-600);
@@ -21,8 +21,8 @@
       @media (prefers-color-scheme: dark) {
         :host {
           --cr-input-background-color: rgba(0, 0, 0, .3);
-          --cr-input-error-color: var(--google-red-refresh-300);
-          --cr-input-focus-color: var(--google-blue-refresh-300);
+          --cr-input-error-color: var(--google-red-300);
+          --cr-input-focus-color: var(--google-blue-300);
         }
       }
 
diff --git a/ui/webui/resources/cr_elements/cr_link_row/cr_link_row.html b/ui/webui/resources/cr_elements/cr_link_row/cr_link_row.html
index aa663ee..d3eb55a5 100644
--- a/ui/webui/resources/cr_elements/cr_link_row/cr_link_row.html
+++ b/ui/webui/resources/cr_elements/cr_link_row/cr_link_row.html
@@ -15,7 +15,7 @@
 
   #startIcon {
     --iron-icon-fill-color: var(--cr-link-row-start-icon-color,
-        var(--google-grey-refresh-700));
+        var(--google-grey-700));
     display: flex;
     flex-shrink: 0;
     padding-inline-end: var(--cr-icon-button-margin-start);
@@ -25,7 +25,7 @@
   @media (prefers-color-scheme: dark) {
     #startIcon {
       --iron-icon-fill-color: var(--cr-link-row-start-icon-color,
-          var(--google-grey-refresh-500));
+          var(--google-grey-500));
     }
   }
 
diff --git a/ui/webui/resources/cr_elements/cr_nav_menu_item_style.html b/ui/webui/resources/cr_elements/cr_nav_menu_item_style.html
index 5cbb718..02d2cb0 100644
--- a/ui/webui/resources/cr_elements/cr_nav_menu_item_style.html
+++ b/ui/webui/resources/cr_elements/cr_nav_menu_item_style.html
@@ -13,7 +13,7 @@
     }
 
     :host-context([enable-branding-update]) .cr-nav-menu-item {
-      --iron-icon-fill-color: var(--google-grey-refresh-700);
+      --iron-icon-fill-color: var(--google-grey-700);
       border-end-end-radius: 100px;
       border-start-end-radius: 100px;
       box-sizing: border-box;
@@ -49,12 +49,12 @@
     :host-context([enable-branding-update]) .cr-nav-menu-item[selected] {
       --iron-icon-fill-color: var(--google-blue-600);
       background: var(--google-blue-50);
-      color: var(--google-blue-refresh-700);
+      color: var(--google-blue-700);
     }
 
     @media (prefers-color-scheme: dark) {
       :host-context([enable-branding-update]) .cr-nav-menu-item {
-        --iron-icon-fill-color: var(--google-grey-refresh-500);
+        --iron-icon-fill-color: var(--google-grey-500);
         color: white;
       }
 
@@ -65,7 +65,7 @@
 
       :host-context([enable-branding-update]) .cr-nav-menu-item[selected] {
         --iron-icon-fill-color: black;
-        background: var(--google-blue-refresh-300);
+        background: var(--google-blue-300);
         color: var(--google-grey-900);
       }
 
diff --git a/ui/webui/resources/cr_elements/cr_profile_avatar_selector/cr_profile_avatar_selector.html b/ui/webui/resources/cr_elements/cr_profile_avatar_selector/cr_profile_avatar_selector.html
index fe45be1..4d4059f 100644
--- a/ui/webui/resources/cr_elements/cr_profile_avatar_selector/cr_profile_avatar_selector.html
+++ b/ui/webui/resources/cr_elements/cr_profile_avatar_selector/cr_profile_avatar_selector.html
@@ -6,7 +6,7 @@
       }
 
       #avatar-grid .avatar {
-        --avatar-focus-color: var(--google-grey-refresh-700);
+        --avatar-focus-color: var(--google-grey-700);
         --avatar-gap-color: white;
         --avatar-gap-width: 2px;
         --avatar-selected-color: var(--google-blue-500);
@@ -29,9 +29,9 @@
 
       @media (prefers-color-scheme: dark) {
         #avatar-grid .avatar {
-          --avatar-focus-color: var(--google-grey-refresh-500);
+          --avatar-focus-color: var(--google-grey-500);
           --avatar-gap-color: var(--google-grey-800);
-          --avatar-selected-color: var(--google-blue-refresh-300);
+          --avatar-selected-color: var(--google-blue-300);
         }
       }
 
diff --git a/ui/webui/resources/cr_elements/cr_radio_button/cr_radio_button_style_css.html b/ui/webui/resources/cr_elements/cr_radio_button/cr_radio_button_style_css.html
index 38704200..a3fdf64c 100644
--- a/ui/webui/resources/cr_elements/cr_radio_button/cr_radio_button_style_css.html
+++ b/ui/webui/resources/cr_elements/cr_radio_button/cr_radio_button_style_css.html
@@ -13,7 +13,7 @@
             rgba(var(--google-blue-600-rgb), .2);
         --cr-radio-button-ink-size: 40px;
         --cr-radio-button-size: 16px;
-        --cr-radio-button-unchecked-color: var(--google-grey-refresh-700);
+        --cr-radio-button-unchecked-color: var(--google-grey-700);
         --cr-radio-button-unchecked-ripple-color:
             rgba(var(--google-grey-600-rgb), .15);
 
@@ -27,12 +27,12 @@
 
       @media (prefers-color-scheme: dark) {
         :host {
-          --cr-radio-button-checked-color: var(--google-blue-refresh-300);
+          --cr-radio-button-checked-color: var(--google-blue-300);
           --cr-radio-button-checked-ripple-color:
-              rgba(var(--google-blue-refresh-300-rgb), .4);
-          --cr-radio-button-unchecked-color: var(--google-grey-refresh-500);
+              rgba(var(--google-blue-300-rgb), .4);
+          --cr-radio-button-unchecked-color: var(--google-grey-500);
           --cr-radio-button-unchecked-ripple-color:
-              rgba(var(--google-grey-refresh-300-rgb), .4);
+              rgba(var(--google-grey-300-rgb), .4);
         }
       }
 
diff --git a/ui/webui/resources/cr_elements/cr_search_field/cr_search_field.html b/ui/webui/resources/cr_elements/cr_search_field/cr_search_field.html
index 9fea65eb5..a05bc091 100644
--- a/ui/webui/resources/cr_elements/cr_search_field/cr_search_field.html
+++ b/ui/webui/resources/cr_elements/cr_search_field/cr_search_field.html
@@ -2,7 +2,7 @@
       :host {
         display: flex;
         user-select: none;
-        --cr-search-field-clear-icon-fill: var(--google-grey-refresh-700);
+        --cr-search-field-clear-icon-fill: var(--google-grey-700);
         --cr-search-field-clear-icon-margin-end : -4px;
         --cr-search-field-input-border-bottom: 1px solid var(--cr-secondary-text-color);
       }
diff --git a/ui/webui/resources/cr_elements/cr_slider/cr_slider.html b/ui/webui/resources/cr_elements/cr_slider/cr_slider.html
index a0e8f6e9..98732f99 100644
--- a/ui/webui/resources/cr_elements/cr_slider/cr_slider.html
+++ b/ui/webui/resources/cr_elements/cr_slider/cr_slider.html
@@ -23,17 +23,17 @@
 
       @media (prefers-color-scheme: dark) {
         :host {
-          --cr-slider-active-color: var(--google-blue-refresh-300);
+          --cr-slider-active-color: var(--google-blue-300);
           --cr-slider-container-color:
-              rgba(var(--google-blue-refresh-500-rgb), .48);
+              rgba(var(--google-blue-500-rgb), .48);
           --cr-slider-container-disabled-color:
               rgba(var(--google-grey-600-rgb), .48);
           /* --cr-slider-disabled-color is the same in dark mode (GG600). */
-          --cr-slider-knob-color-rgb: var(--google-blue-refresh-300-rgb);
+          --cr-slider-knob-color-rgb: var(--google-blue-300-rgb);
           --cr-slider-knob-disabled-color:
               var(--google-grey-900-white-4-percent);
-          --cr-slider-marker-active-color: var(--google-blue-refresh-300);
-          --cr-slider-marker-color: var(--google-blue-refresh-300);
+          --cr-slider-marker-active-color: var(--google-blue-300);
+          --cr-slider-marker-color: var(--google-blue-300);
           --cr-slider-marker-disabled-color: rgba(255, 255, 255, .54);
           --cr-slider-ripple-color: rgba(var(--cr-slider-knob-color-rgb), .4);
         }
diff --git a/ui/webui/resources/cr_elements/cr_tabs/cr_tabs.html b/ui/webui/resources/cr_elements/cr_tabs/cr_tabs.html
index 1005206..c8158da 100644
--- a/ui/webui/resources/cr_elements/cr_tabs/cr_tabs.html
+++ b/ui/webui/resources/cr_elements/cr_tabs/cr_tabs.html
@@ -37,7 +37,7 @@
 
       @media (prefers-color-scheme: dark) {
         .selected {
-          color: var(--cr-tabs-selected-color, var(--google-blue-refresh-300));
+          color: var(--cr-tabs-selected-color, var(--google-blue-300));
         }
       }
 
@@ -62,7 +62,7 @@
 
       @media (prefers-color-scheme: dark) {
         .selected .tab-icon {
-          background-color: var(--cr-tabs-selected-color, var(--google-blue-refresh-300));
+          background-color: var(--cr-tabs-selected-color, var(--google-blue-300));
         }
       }
 
@@ -96,7 +96,7 @@
 
       @media (prefers-color-scheme: dark) {
         .tab-indicator {
-          background: var(--cr-tabs-selected-color, var(--google-blue-refresh-300));
+          background: var(--cr-tabs-selected-color, var(--google-blue-300));
         }
       }
     </style>
diff --git a/ui/webui/resources/cr_elements/cr_toast/cr_toast.html b/ui/webui/resources/cr_elements/cr_toast/cr_toast.html
index 7547715..ba028b86 100644
--- a/ui/webui/resources/cr_elements/cr_toast/cr_toast.html
+++ b/ui/webui/resources/cr_elements/cr_toast/cr_toast.html
@@ -9,7 +9,7 @@
         :host {
           --cr-toast-background: var(--google-grey-900)
               linear-gradient(rgba(255, 255, 255, .06), rgba(255, 255, 255, .06));
-          --cr-toast-button-color: var(--google-blue-refresh-300);
+          --cr-toast-button-color: var(--google-blue-300);
           --cr-toast-text-color: var(--google-grey-200);
         }
       }
diff --git a/ui/webui/resources/cr_elements/cr_toggle/cr_toggle.html b/ui/webui/resources/cr_elements/cr_toggle/cr_toggle.html
index c7e12ea..41e0f42 100644
--- a/ui/webui/resources/cr_elements/cr_toggle/cr_toggle.html
+++ b/ui/webui/resources/cr_elements/cr_toggle/cr_toggle.html
@@ -26,26 +26,26 @@
 
       @media (prefers-color-scheme: dark) {
         :host {
-          --cr-toggle-checked-bar-color: var(--google-blue-refresh-300);
-          --cr-toggle-checked-button-color: var(--google-blue-refresh-300);
+          --cr-toggle-checked-bar-color: var(--google-blue-300);
+          --cr-toggle-checked-button-color: var(--google-blue-300);
           --cr-toggle-checked-ripple-color:
-              rgba(var(--google-blue-refresh-300-rgb), .4);
-          --cr-toggle-unchecked-bar-color: var(--google-grey-refresh-500);
-          --cr-toggle-unchecked-button-color: var(--google-grey-refresh-300);
+              rgba(var(--google-blue-300-rgb), .4);
+          --cr-toggle-unchecked-bar-color: var(--google-grey-500);
+          --cr-toggle-unchecked-button-color: var(--google-grey-300);
           --cr-toggle-unchecked-ripple-color:
-              rgba(var(--google-grey-refresh-300-rgb), .4);
+              rgba(var(--google-grey-300-rgb), .4);
         }
       }
       /* Keep the prefers-color-scheme and [dark] rules the same. */
       :host([dark]) {
-        --cr-toggle-checked-bar-color: var(--google-blue-refresh-300);
-        --cr-toggle-checked-button-color: var(--google-blue-refresh-300);
+        --cr-toggle-checked-bar-color: var(--google-blue-300);
+        --cr-toggle-checked-button-color: var(--google-blue-300);
         --cr-toggle-checked-ripple-color:
-            rgba(var(--google-blue-refresh-300-rgb), .4);
-        --cr-toggle-unchecked-bar-color: var(--google-grey-refresh-500);
-        --cr-toggle-unchecked-button-color: var(--google-grey-refresh-300);
+            rgba(var(--google-blue-300-rgb), .4);
+        --cr-toggle-unchecked-bar-color: var(--google-grey-500);
+        --cr-toggle-unchecked-button-color: var(--google-grey-300);
         --cr-toggle-unchecked-ripple-color:
-            rgba(var(--google-grey-refresh-300-rgb), .4);
+            rgba(var(--google-grey-300-rgb), .4);
       }
 
       :host([disabled]) {
diff --git a/ui/webui/resources/cr_elements/cr_toolbar/cr_toolbar_search_field.html b/ui/webui/resources/cr_elements/cr_toolbar/cr_toolbar_search_field.html
index 499e941..c854656 100644
--- a/ui/webui/resources/cr_elements/cr_toolbar/cr_toolbar_search_field.html
+++ b/ui/webui/resources/cr_elements/cr_toolbar/cr_toolbar_search_field.html
@@ -30,7 +30,7 @@
         :host-context([enable-branding-update]) cr-icon-button {
           --cr-icon-button-fill-color: var(
               --cr-toolbar-search-field-input-icon-color,
-              var(--google-grey-refresh-700));
+              var(--google-grey-700));
         }
       }
 
@@ -38,7 +38,7 @@
         cr-icon-button {
           --cr-icon-button-fill-color: var(
               --cr-toolbar-search-field-input-icon-color,
-              var(--google-grey-refresh-500));
+              var(--google-grey-500));
         }
       }
 
@@ -54,7 +54,7 @@
       @media (prefers-color-scheme: light) {
         :host-context([enable-branding-update]) #prompt {
           color: var(--cr-toolbar-search-field-prompt-color,
-              var(--google-grey-refresh-700));
+              var(--google-grey-700));
         }
       }
 
@@ -80,7 +80,7 @@
         :host-context([enable-branding-update]) paper-spinner-lite {
           --paper-spinner-color: var(
               --cr-toolbar-search-field-input-icon-color,
-              var(--google-grey-refresh-700));
+              var(--google-grey-700));
         }
       }
 
@@ -132,7 +132,7 @@
 
       @media (prefers-color-scheme: light) {
         :host-context([enable-branding-update]) input {
-          caret-color: var(--google-blue-refresh-700);
+          caret-color: var(--google-blue-700);
           color: var(--cr-toolbar-search-field-input-text-color,
               var(--google-grey-900));
         }
@@ -168,7 +168,7 @@
         :host-context([enable-branding-update]):host(:not([narrow])) {
           background:
               var(--cr-toolbar-search-field-background,
-                  var(--google-grey-refresh-100));
+                  var(--google-grey-100));
         }
       }
 
diff --git a/ui/webui/resources/cr_elements/md_select_css.html b/ui/webui/resources/cr_elements/md_select_css.html
index 704f1f1..6ce0769 100644
--- a/ui/webui/resources/cr_elements/md_select_css.html
+++ b/ui/webui/resources/cr_elements/md_select_css.html
@@ -8,7 +8,7 @@
     <style>
       .md-select {
         --md-arrow-width: 10px;
-        --md-select-bg-color: var(--google-grey-refresh-100);
+        --md-select-bg-color: var(--google-grey-100);
         --md-select-focus-shadow-color: rgba(var(--google-blue-600-rgb), .4);
         --md-select-option-bg-color: white;
         --md-select-side-padding: 8px;
@@ -42,7 +42,7 @@
         .md-select {
           --md-select-bg-color: rgba(0, 0, 0, .3);
           --md-select-focus-shadow-color:
-              rgba(var(--google-blue-refresh-300-rgb), .5);
+              rgba(var(--google-blue-300-rgb), .5);
           --md-select-option-bg-color: var(--google-grey-900-white-4-percent);
           --md-select-text-color: var(--cr-primary-text-color);
           background-image: url(chrome://resources/images/dark/arrow_down.svg);
diff --git a/ui/webui/resources/cr_elements/mwb_shared_vars.html b/ui/webui/resources/cr_elements/mwb_shared_vars.html
index b5640ee..27f26e1 100644
--- a/ui/webui/resources/cr_elements/mwb_shared_vars.html
+++ b/ui/webui/resources/cr_elements/mwb_shared_vars.html
@@ -2,7 +2,7 @@
   <style>
     html {
       --mwb-background-color: white;
-      --mwb-icon-button-fill-color: var(--google-grey-refresh-700);
+      --mwb-icon-button-fill-color: var(--google-grey-700);
       --mwb-icon-button-focus-ring-color: var(--google-blue-600);
       --mwb-icon-button-hover-background-color: rgba(var(--google-grey-900-rgb), 0.1);
       --mwb-icon-size: 16px;
@@ -13,8 +13,8 @@
       --mwb-list-section-title-font-size: 11px;
       --mwb-list-section-title-height: 40px;
       --mwb-primary-text-font-size: 13px;
-      --mwb-scrollbar-thumb-color: var(--google-grey-refresh-300);
-      --mwb-scrollbar-thumb-hover-color: var(--google-grey-refresh-500);
+      --mwb-scrollbar-thumb-color: var(--google-grey-300);
+      --mwb-scrollbar-thumb-hover-color: var(--google-grey-500);
       --mwb-scrollbar-track-color: var(--mwb-background-color);
       --mwb-scrollbar-width: 4px;
       --mwb-secondary-text-font-size: 12px;
@@ -23,13 +23,13 @@
     @media (prefers-color-scheme: dark) {
       html {
         --mwb-background-color: var(--google-grey-900);
-        --mwb-icon-button-fill-color: var(--google-grey-refresh-300);
+        --mwb-icon-button-fill-color: var(--google-grey-300);
         --mwb-icon-button-focus-ring-color: var(--google-blue-300);
         --mwb-icon-button-hover-background-color: rgba(255, 255, 255, 0.1);
         --mwb-list-item-hover-background-color: rgb(55, 56, 58); /* #37383a */
         --mwb-list-item-selected-background-color: rgb(68, 69, 71); /* #444547 */
-        --mwb-scrollbar-thumb-color: var(--google-grey-refresh-500);
-        --mwb-scrollbar-thumb-hover-color: var(--google-grey-refresh-300);
+        --mwb-scrollbar-thumb-color: var(--google-grey-500);
+        --mwb-scrollbar-thumb-hover-color: var(--google-grey-300);
       }
     }
   </style>
diff --git a/ui/webui/resources/cr_elements/policy/cr_tooltip_icon.html b/ui/webui/resources/cr_elements/policy/cr_tooltip_icon.html
index d1ddc2d..4a07dec 100644
--- a/ui/webui/resources/cr_elements/policy/cr_tooltip_icon.html
+++ b/ui/webui/resources/cr_elements/policy/cr_tooltip_icon.html
@@ -17,7 +17,7 @@
         --iron-icon-width: var(--cr-icon-size);
         --iron-icon-height: var(--cr-icon-size);
         --iron-icon-fill-color:
-          var(--cr-tooltip-icon-fill-color, var(--google-grey-refresh-700));
+          var(--cr-tooltip-icon-fill-color, var(--google-grey-700));
       }
     </style>
     <iron-icon id="indicator" tabindex="0" aria-label$="[[iconAriaLabel]]"
diff --git a/ui/webui/resources/cr_elements/shared_style_css.html b/ui/webui/resources/cr_elements/shared_style_css.html
index d862a9a..c0976a8 100644
--- a/ui/webui/resources/cr_elements/shared_style_css.html
+++ b/ui/webui/resources/cr_elements/shared_style_css.html
@@ -11,13 +11,13 @@
     <style include="cr-hidden-style cr-icons">
       html,
       :host {
-        --scrollable-border-color: var(--google-grey-refresh-300);
+        --scrollable-border-color: var(--google-grey-300);
       }
 
       @media (prefers-color-scheme: dark) {
         html,
         :host {
-          --scrollable-border-color: var(--google-grey-refresh-700);
+          --scrollable-border-color: var(--google-grey-700);
         }
       }
 
diff --git a/weblayer/browser/android/javatests/src/org/chromium/weblayer/test/WebMessageTest.java b/weblayer/browser/android/javatests/src/org/chromium/weblayer/test/WebMessageTest.java
index 6067332..ef61144 100644
--- a/weblayer/browser/android/javatests/src/org/chromium/weblayer/test/WebMessageTest.java
+++ b/weblayer/browser/android/javatests/src/org/chromium/weblayer/test/WebMessageTest.java
@@ -99,7 +99,12 @@
         assertNotNull(webMessageCallback.mLastMessage);
         assertNotNull(webMessageCallback.mLastProxy);
         assertEquals("from page", webMessageCallback.mLastMessage.getContents());
-        WebMessageReplyProxy lastProxy = webMessageCallback.mLastProxy;
+        final WebMessageReplyProxy lastProxy = webMessageCallback.mLastProxy;
+        int majorVersion = TestThreadUtils.runOnUiThreadBlockingNoException(
+                () -> WebLayer.getSupportedMajorVersion(mActivityTestRule.getActivity()));
+        if (majorVersion >= 99) {
+            assertNotNull(runOnUiThreadBlocking(() -> { return lastProxy.getPage(); }));
+        }
         webMessageCallback.reset();
 
         int currentCallCount = callbackHelper.getCallCount();
diff --git a/weblayer/browser/java/org/chromium/weblayer_private/WebMessageReplyProxyImpl.java b/weblayer/browser/java/org/chromium/weblayer_private/WebMessageReplyProxyImpl.java
index 9eeef1e..2b213f47 100644
--- a/weblayer/browser/java/org/chromium/weblayer_private/WebMessageReplyProxyImpl.java
+++ b/weblayer/browser/java/org/chromium/weblayer_private/WebMessageReplyProxyImpl.java
@@ -25,12 +25,16 @@
     private final int mId;
 
     private WebMessageReplyProxyImpl(long nativeWebMessageReplyProxyImpl, int id,
-            IWebMessageCallbackClient client, boolean isMainFrame, String sourceOrigin) {
+            IWebMessageCallbackClient client, boolean isMainFrame, String sourceOrigin,
+            PageImpl page) {
         mNativeWebMessageReplyProxyImpl = nativeWebMessageReplyProxyImpl;
         mClient = client;
         mId = id;
         try {
             client.onNewReplyProxy(this, mId, isMainFrame, sourceOrigin);
+            if (WebLayerFactoryImpl.getClientMajorVersion() >= 99) {
+                client.onSetPage(mId, page.getClientPage());
+            }
         } catch (RemoteException e) {
             throw new APICallException(e);
         }
@@ -38,9 +42,10 @@
 
     @CalledByNative
     private static WebMessageReplyProxyImpl create(long nativeWebMessageReplyProxyImpl, int id,
-            IWebMessageCallbackClient client, boolean isMainFrame, String sourceOrigin) {
+            IWebMessageCallbackClient client, boolean isMainFrame, String sourceOrigin,
+            PageImpl page) {
         return new WebMessageReplyProxyImpl(
-                nativeWebMessageReplyProxyImpl, id, client, isMainFrame, sourceOrigin);
+                nativeWebMessageReplyProxyImpl, id, client, isMainFrame, sourceOrigin, page);
     }
 
     @CalledByNative
diff --git a/weblayer/browser/java/org/chromium/weblayer_private/interfaces/IWebMessageCallbackClient.aidl b/weblayer/browser/java/org/chromium/weblayer_private/interfaces/IWebMessageCallbackClient.aidl
index d42f3a0..641b855 100644
--- a/weblayer/browser/java/org/chromium/weblayer_private/interfaces/IWebMessageCallbackClient.aidl
+++ b/weblayer/browser/java/org/chromium/weblayer_private/interfaces/IWebMessageCallbackClient.aidl
@@ -4,6 +4,7 @@
 
 package org.chromium.weblayer_private.interfaces;
 
+import org.chromium.weblayer_private.interfaces.IClientPage;
 import org.chromium.weblayer_private.interfaces.IWebMessageReplyProxy;
 
 interface IWebMessageCallbackClient {
@@ -16,4 +17,7 @@
 
   // @since 90
   void onReplyProxyActiveStateChanged(in int proxyId) = 3;
+
+  // @since 99
+  void onSetPage(in int proxyId, IClientPage page) = 4;
 }
diff --git a/weblayer/browser/js_communication/web_message_browsertest.cc b/weblayer/browser/js_communication/web_message_browsertest.cc
index 064273a..a0b2e9d 100644
--- a/weblayer/browser/js_communication/web_message_browsertest.cc
+++ b/weblayer/browser/js_communication/web_message_browsertest.cc
@@ -134,6 +134,8 @@
   ASSERT_EQ(2u, current_connection->messages().size());
   EXPECT_EQ(u"from page", current_connection->messages()[0]);
   EXPECT_EQ(u"bouncing from c++", current_connection->messages()[1]);
+  // WebLayer's Page has no functions, verify it can be requested.
+  current_connection->proxy()->GetPage();
 }
 
 class WebMessageTestWithBfCache : public WebLayerBrowserTest {
@@ -179,6 +181,7 @@
   ASSERT_TRUE(web_message_host);
   EXPECT_FALSE(web_message_host->proxy()->IsInBackForwardCache());
   EXPECT_EQ(0, web_message_host->back_forward_cache_state_changed_call_count());
+  Page* original_page = &(web_message_host->proxy()->GetPage());
 
   // Navigate to a new host. The old page should go into the cache.
   OneShotNavigationObserver observer1(shell());
@@ -196,5 +199,7 @@
   observer2.WaitForNavigation();
   web_message_host->WaitForBackForwardStateToBe(false);
   EXPECT_EQ(2, web_message_host->back_forward_cache_state_changed_call_count());
+  EXPECT_EQ(original_page, &(web_message_host->proxy()->GetPage()));
 }
+
 }  // namespace weblayer
diff --git a/weblayer/browser/js_communication/web_message_host_factory_wrapper.cc b/weblayer/browser/js_communication/web_message_host_factory_wrapper.cc
index e5914a6..c3ef27a 100644
--- a/weblayer/browser/js_communication/web_message_host_factory_wrapper.cc
+++ b/weblayer/browser/js_communication/web_message_host_factory_wrapper.cc
@@ -8,6 +8,9 @@
 #include "components/js_injection/browser/web_message.h"
 #include "components/js_injection/browser/web_message_host.h"
 #include "components/js_injection/browser/web_message_reply_proxy.h"
+#include "content/public/browser/page.h"
+#include "content/public/browser/render_frame_host.h"
+#include "weblayer/browser/page_impl.h"
 #include "weblayer/public/js_communication/web_message.h"
 #include "weblayer/public/js_communication/web_message_host.h"
 #include "weblayer/public/js_communication/web_message_host_factory.h"
@@ -50,6 +53,16 @@
   bool IsInBackForwardCache() override {
     return proxy_->IsInBackForwardCache();
   }
+  Page& GetPage() override {
+    // In general WebLayer avoids exposing child frames. As such, GetPage()
+    // returns the Page of the main frame.
+    PageImpl* page =
+        PageImpl::GetForPage(proxy_->GetPage().GetMainDocument().GetPage());
+    // NavigationControllerImpl creates the PageImpl when navigation finishes so
+    // that by the time this is called the Page should have been created.
+    DCHECK(page);
+    return *page;
+  }
 
  private:
   raw_ptr<js_injection::WebMessageReplyProxy> proxy_;
diff --git a/weblayer/browser/js_communication/web_message_reply_proxy_impl.cc b/weblayer/browser/js_communication/web_message_reply_proxy_impl.cc
index d01203d..d484d9d 100644
--- a/weblayer/browser/js_communication/web_message_reply_proxy_impl.cc
+++ b/weblayer/browser/js_communication/web_message_reply_proxy_impl.cc
@@ -9,6 +9,7 @@
 #include "base/android/jni_android.h"
 #include "base/android/jni_string.h"
 #include "weblayer/browser/java/jni/WebMessageReplyProxyImpl_jni.h"
+#include "weblayer/browser/page_impl.h"
 #include "weblayer/public/js_communication/web_message.h"
 #include "weblayer/public/js_communication/web_message_reply_proxy.h"
 
@@ -24,7 +25,8 @@
   auto* env = base::android::AttachCurrentThread();
   java_object_ = Java_WebMessageReplyProxyImpl_create(
       env, reinterpret_cast<intptr_t>(this), id, client, is_main_frame,
-      base::android::ConvertUTF8ToJavaString(env, origin_string));
+      base::android::ConvertUTF8ToJavaString(env, origin_string),
+      static_cast<PageImpl&>(reply_proxy->GetPage()).java_page());
 }
 
 WebMessageReplyProxyImpl::~WebMessageReplyProxyImpl() {
diff --git a/weblayer/public/java/org/chromium/weblayer/Tab.java b/weblayer/public/java/org/chromium/weblayer/Tab.java
index 166b022..c503d97 100644
--- a/weblayer/public/java/org/chromium/weblayer/Tab.java
+++ b/weblayer/public/java/org/chromium/weblayer/Tab.java
@@ -15,6 +15,7 @@
 
 import org.chromium.weblayer_private.interfaces.APICallException;
 import org.chromium.weblayer_private.interfaces.IClientNavigation;
+import org.chromium.weblayer_private.interfaces.IClientPage;
 import org.chromium.weblayer_private.interfaces.IContextMenuParams;
 import org.chromium.weblayer_private.interfaces.IErrorPageCallbackClient;
 import org.chromium.weblayer_private.interfaces.IExternalIntentInIncognitoCallbackClient;
@@ -836,6 +837,13 @@
             assert proxy != null;
             mCallback.onWebMessageReplyProxyActiveStateChanged(proxy);
         }
+
+        @Override
+        public void onSetPage(int proxyId, IClientPage clientPage) {
+            StrictModeWorkaround.apply();
+            assert mProxyIdToProxy.get(proxyId) != null;
+            mProxyIdToProxy.get(proxyId).setPage((Page) clientPage);
+        }
     }
 
     private final class TabClientImpl extends ITabClient.Stub {
diff --git a/weblayer/public/java/org/chromium/weblayer/WebMessageReplyProxy.java b/weblayer/public/java/org/chromium/weblayer/WebMessageReplyProxy.java
index 5075249..098c4b2 100644
--- a/weblayer/public/java/org/chromium/weblayer/WebMessageReplyProxy.java
+++ b/weblayer/public/java/org/chromium/weblayer/WebMessageReplyProxy.java
@@ -23,6 +23,8 @@
     private final boolean mIsMainFrame;
     private final String mSourceOrigin;
     private boolean mIsClosed;
+    // Added in 99.
+    private Page mPage;
 
     // Constructor for test mocking.
     protected WebMessageReplyProxy() {
@@ -101,4 +103,25 @@
             throw new APICallException(e);
         }
     }
+
+    /**
+     * Returns the Page associated with this proxy. For child frame, the Page of the main frame is
+     * returned.
+     *
+     * @return The Page.
+     *
+     * @since 99
+     */
+    public Page getPage() {
+        ThreadCheck.ensureOnUiThread();
+        if (WebLayer.getSupportedMajorVersionInternal() < 99) {
+            throw new UnsupportedOperationException();
+        }
+        return mPage;
+    }
+
+    // Only called in >= 99.
+    void setPage(Page page) {
+        mPage = page;
+    }
 }
diff --git a/weblayer/public/js_communication/web_message_reply_proxy.h b/weblayer/public/js_communication/web_message_reply_proxy.h
index e464b80..6406364 100644
--- a/weblayer/public/js_communication/web_message_reply_proxy.h
+++ b/weblayer/public/js_communication/web_message_reply_proxy.h
@@ -9,6 +9,7 @@
 
 namespace weblayer {
 
+class Page;
 struct WebMessage;
 
 // Used to send messages to the page.
@@ -19,6 +20,10 @@
   // Returns true if the page is in the back/forward cache.
   virtual bool IsInBackForwardCache() = 0;
 
+  // Returns the Page this proxy was created for. This always returns the Page
+  // of the main frame.
+  virtual Page& GetPage() = 0;
+
  protected:
   virtual ~WebMessageReplyProxy() = default;
 };
diff --git a/weblayer/public/page.h b/weblayer/public/page.h
index 5a65af2..d50a476b 100644
--- a/weblayer/public/page.h
+++ b/weblayer/public/page.h
@@ -9,9 +9,9 @@
 
 // This objects tracks the lifetime of a loaded web page. Most of the time there
 // is only one Page object per tab. However features like back-forward cache,
-// prerendering etc... sometime involve the creation of additional Page object.
+// prerendering etc... sometime involve the creation of additional Page objects.
 // Navigation::getPage() will return the Page for a given navigation. Similarly
-// it'll the same Page object that's passed in
+// it'll be the same Page object that's passed in
 // NavigationObserver::OnPageDestroyed().
 class Page {
  protected: